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A discrete fractional random transform
NASA Astrophysics Data System (ADS)
Liu, Zhengjun; Zhao, Haifa; Liu, Shutian
We propose a discrete fractional random transform based on a generalization of the discrete fractional Fourier transform with an intrinsic randomness. Such discrete fractional random transform inheres excellent mathematical properties of the fractional Fourier transform along with some fantastic features of its own. As a primary application, the discrete fractional random transform has been used for image encryption and decryption.
Time to the Doctorate: Multilevel Discrete-Time Hazard Analysis
ERIC Educational Resources Information Center
Wao, Hesborn O.
Secondary data on 1,028 graduate students nested within 24 programs and admitted into either a Ph. D. or Ed. D. program between 1990 and 2006 at an American public university were used to illustrate the benefits of employing multilevel discrete-time hazard analysis in understanding the timing of doctorate completion in Education and the factors…
Discrete fluorescent saturation regimes in multilevel systems
NASA Technical Reports Server (NTRS)
Kastner, S. O.; Bhatia, A. K.
Using models of multilevel atoms, the fluorescent process was examined for the ratio of the photooxidation rate, Pij, to the collisional oxidation rate, Cij, in the pumped resonance transition i-j. It is shown that, in the full range of the parameter Pij/Cij, there exist three distinct regimes (I, II, and III) which may be usefully exploited. These regimes are defined, respectively, by the following conditions: Pij/Cij smaller than about 1; Pij/Cij much greater than 1 and Pij much lower than Cki; and Pij/Cij much greater than 1 and Pij much higher than Cki, where Cki is the collisional rate populating the source level i. The only regime which is characterized by the sensitivity of fluorescent-fluorescent line intensity ratios to Pij is regime I. If regime III is reached, even fluorescent-nonfluorescent line ratios become independent of Pij. The analysis is applied to the resonant photoexcitation of a carbonlike ion.
Handling Correlations between Covariates and Random Slopes in Multilevel Models
ERIC Educational Resources Information Center
Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders
This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…
Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials
ERIC Educational Resources Information Center
Sanders, Elizabeth A.
This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…
Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective
ERIC Educational Resources Information Center
Zhu, Xiaoshu
The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…
Randomness and multilevel interactions in biology.
Buiatti, Marcello; Longo, Giuseppe
The dynamic instability of living systems and the "superposition" of different forms of randomness are viewed, in this paper, as components of the contingently changing, or even increasing, organization of life through ontogenesis or evolution. To this purpose, we first survey how classical and quantum physics define randomness differently. We then discuss why this requires, in our view, an enriched understanding of the effects of their concurrent presence in biological systems' dynamics. Biological randomness is then presented not only as an essential component of the heterogeneous determination and intrinsic unpredictability proper to life phenomena, due to the nesting of, and interaction between many levels of organization, but also as a key component of its structural stability. We will note as well that increasing organization, while increasing "order", induces growing disorder, not only by energy dispersal effects, but also by increasing variability and differentiation. Finally, we discuss the cooperation between diverse components in biological networks; this cooperation implies the presence of constraints due to the particular nature of bio-entanglement and bio-resonance, two notions to be reviewed and defined in the paper. PMID:23637008
Multilevel, discrete, point-interval data can predict bioattenuation`s potential
Kabis, T.W.
Closely spaced, discrete-interval groundwater sampling is critical for monitoring aqueous-phase contaminants at hazardous waste sites. Data obtained from discrete-interval sampling devices accurately represent horizontal and vertical extants of contaminant plumes. Discrete point-interval groundwater sampling has been tested in various applications, including natural- and forced-gradient tracer tests plume delineation, and in identifying discrete zones of microbial activity and vertical chemical gradients within an aquifer. An increasingly popular strategy is to avoid active remediation in favor of natural, in-situ attenuation processes. Evaluation of natural attenuation, particularly in-situ bioremediation resulting from multiple terminal electron acceptors, requires site-specific data. Here, multilevel, discrete, point-interval groundwater sampling data is critical. Because groundwater samples from standard monitoring wells often are derived from large vertical sampling zones, the resulting data presents a smeared picture of chemical-microbial conditions; moreover, the potential for natural in-situ bioattenuation can be under- or overestimated without multilevel, discrete, point-interval data. Discrete, point-interval samplers provide a sound basis for evaluating remediation options. One potential obstacle has been the lack of a multipurpose, cost-effective sampler that is operational under a variety of field conditions.
Multilevel models for survival analysis with random effects.
Yau, K K
A method for modeling survival data with multilevel clustering is described. The Cox partial likelihood is incorporated into the generalized linear mixed model (GLMM) methodology. Parameter estimation is achieved by maximizing a log likelihood analogous to the likelihood associated with the best linear unbiased prediction (BLUP) at the initial step of estimation and is extended to obtain residual maximum likelihood (REML) estimators of the variance component. Estimating equations for a three-level hierarchical survival model are developed in detail, and such a model is applied to analyze a set of chronic granulomatous disease (CGD) data on recurrent infections as an illustration with both hospital and patient effects being considered as random. Only the latter gives a significant contribution. A simulation study is carried out to evaluate the performance of the REML estimators. Further extension of the estimation procedure to models with an arbitrary number of levels is also discussed. PMID:11252624
The ergodic decomposition of stationary discrete random processes
NASA Technical Reports Server (NTRS)
Gray, R. M.; Davisson, L. D.
The ergodic decomposition is discussed, and a version focusing on the structure of individual sample functions of stationary processes is proved for the special case of discrete-time random processes with discrete alphabets. The result is stronger in this case than the usual theorem, and the proof is both intuitive and simple. Estimation-theoretic and information-theoretic interpretations are developed and applied to prove existence theorems for universal source codes, both noiseless and with a fidelity criterion.
Webster, Clayton G; Jantsch, Peter A; Teckentrup, Aretha L; Gunzburger, Max D
Stochastic Collocation (SC) methods for stochastic partial differential equa- tions (SPDEs) suffer from the curse of dimensionality, whereby increases in the stochastic dimension cause an explosion of computational effort. To combat these challenges, multilevel approximation methods seek to decrease computational complexity by balancing spatial and stochastic discretization errors. As a form of variance reduction, multilevel techniques have been successfully applied to Monte Carlo (MC) methods, but may be extended to accelerate other methods for SPDEs in which the stochastic and spatial degrees of freedom are de- coupled. This article presents general convergence and computational complexity analysis of a multilevel method for SPDEs, demonstrating its advantages with regard to standard, single level approximation. The numerical results will highlight conditions under which multilevel sparse grid SC is preferable to the more traditional MC and SC approaches.
First-principles modeling of electromagnetic scattering by discrete and discretely heterogeneous random media
NASA Astrophysics Data System (ADS)
Mishchenko, Michael I.; Dlugach, Janna M.; Yurkin, Maxim A.; Bi, Lei; Cairns, Brian; Liu, Li; Panetta, R. Lee; Travis, Larry D.; Yang, Ping; Zakharova, Nadezhda T.
A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell's equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell-Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell-Lorentz equations, we trace the development of
A discrete time random walk model for anomalous diffusion
NASA Astrophysics Data System (ADS)
Angstmann, C. N.; Donnelly, I. C.; Henry, B. I.; Nichols, J. A.
The continuous time random walk, introduced in the physics literature by Montroll and Weiss, has been widely used to model anomalous diffusion in external force fields. One of the features of this model is that the governing equations for the evolution of the probability density function, in the diffusion limit, can generally be simplified using fractional calculus. This has in turn led to intensive research efforts over the past decade to develop robust numerical methods for the governing equations, represented as fractional partial differential equations. Here we introduce a discrete time random walk that can also be used to model anomalous diffusion in an external force field. The governing evolution equations for the probability density function share the continuous time random walk diffusion limit. Thus the discrete time random walk provides a novel numerical method for solving anomalous diffusion equations in the diffusion limit, including the fractional Fokker-Planck equation. This method has the clear advantage that the discretisation of the diffusion limit equation, which is necessary for numerical analysis, is itself a well defined physical process. Some examples using the discrete time random walk to provide numerical solutions of the probability density function for anomalous subdiffusion, including forcing, are provided.
Discrete Randomness in Discrete Time Quantum Walk: Study Via Stochastic Averaging
NASA Astrophysics Data System (ADS)
Ellinas, D.; Bracken, A. J.; Smyrnakis, I.
The role of classical noise in quantum walks (QW) on integers is investigated in the form of discrete dichotomic random variable affecting its reshuffling matrix parametrized as a SU2)/U (1) coset element. Analysis in terms of quantum statistical moments and generating functions, derived by the completely positive trace preserving (CPTP) map governing evolution, reveals a pronounced eventual transition in walk's diffusion mode, from a quantum ballistic regime with rate O(t) to a classical diffusive regime with rate O(√{t}), when condition (strength of noise parameter)2 × (number of steps) = 1, is satisfied. The role of classical randomness is studied showing that the randomized QW, when treated on the stochastic average level by means of an appropriate CPTP averaging map, turns out to be equivalent to a novel quantized classical walk without randomness. This result emphasizes the dual role of quantization/randomization in the context of classical random walk.
Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain
NASA Technical Reports Server (NTRS)
Lang, R. H.
Microwave remote sensing of agricultural crops and forested regions is studied. Long term goals of the research involve modeling vegetation so that radar signatures can be used to infer the parameters which characterize the vegetation and underlying ground. Vegetation is modeled by discrete scatterers viz, leaves, stems, branches and trunks. These are replaced by glossy dielectric discs and cylinders. Rough surfaces are represented by their mean and spectral characteristics. Average scattered power is then calculated by employing discrete random media methodology such as the distorted Born approximation or transport theory. Both coherent and incoherent multiple scattering techniques are explored. Once direct methods are developed, inversion techniques can be investigated.
Asymptotic Effect of Misspecification in the Random Part of the Multilevel Model
ERIC Educational Resources Information Center
Berkhof, Johannes; Kampen, Jarl Kennard
The authors examine the asymptotic effect of omitting a random coefficient in the multilevel model and derive expressions for the change in (a) the variance components estimator and (b) the estimated variance of the fixed effects estimator. They apply the method of moments, which yields a closed form expression for the omission effect. In…
Conceptualizing and Testing Random Indirect Effects and Moderated Mediation in Multilevel Models: New Procedures and Recommendations
ERIC Educational Resources Information Center
Bauer, Daniel J.; Preacher, Kristopher J.; Gil, Karen M.
The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects.…
A discrete impulsive model for random heating and Brownian motion
NASA Astrophysics Data System (ADS)
Ramshaw, John D.
The energy of a mechanical system subjected to a random force with zero mean increases irreversibly and diverges with time in the absence of friction or dissipation. This random heating effect is usually encountered in phenomenological theories formulated in terms of stochastic differential equations, the epitome of which is the Langevin equation of Brownian motion. We discuss a simple discrete impulsive model that captures the essence of random heating and Brownian motion. The model may be regarded as a discrete analog of the Langevin equation, although it is developed ab initio. Its analysis requires only simple algebraic manipulations and elementary averaging concepts, but no stochastic differential equations (or even calculus). The irreversibility in the model is shown to be a consequence of a natural causal stochastic condition that is closely analogous to Boltzmann's molecular chaos hypothesis in the kinetic theory of gases. The model provides a simple introduction to several ostensibly more advanced topics, including random heating, molecular chaos, irreversibility, Brownian motion, the Langevin equation, and fluctuation-dissipation theorems.
Multilevel Cell Storage and Resistance Variability in Resistive Random Access Memory
NASA Astrophysics Data System (ADS)
Pantelis, D. I.; Karakizis, P. N.; Dragatogiannis, D. A.; Charitidis, C. A.
Multilevel per cell (MLC) storage in resistive random access memory (ReRAM) is attractive in achieving high-density and low-cost memory and will be required in future. In this chapter, MLC storage and resistance variability and reliability of multilevel in ReRAM are discussed. Different MLC operation schemes with their physical mechanisms and a comprehensive analysis of resistance variability have been provided. Various factors that can induce variability and their effect on the resistance margin between the multiple resistance levels are assessed. The reliability characteristics and the impact on MLC storage have also been assessed.
Weighted discrete least-squares polynomial approximation using randomized quadratures
NASA Astrophysics Data System (ADS)
Zhou, Tao; Narayan, Akil; Xiu, Dongbin
We discuss the problem of polynomial approximation of multivariate functions using discrete least squares collocation. The problem stems from uncertainty quantification (UQ), where the independent variables of the functions are random variables with specified probability measure. We propose to construct the least squares approximation on points randomly and uniformly sampled from tensor product Gaussian quadrature points. We analyze the stability properties of this method and prove that the method is asymptotically stable, provided that the number of points scales linearly (up to a logarithmic factor) with the cardinality of the polynomial space. Specific results in both bounded and unbounded domains are obtained, along with a convergence result for Chebyshev measure. Numerical examples are provided to verify the theoretical results.
Multilevel Compression of Random Walks on Networks Reveals Hierarchical Organization in Large Integrated Systems
Rosvall, Martin; Bergstrom, Carl T.
To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation, which reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network — the optimal number of levels and modular partition at each level — with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines: life sciences, physical sciences, ecology and earth sciences, and social sciences. In general, we find shallow hierarchical structures in globally interconnected systems, such as neural networks, and rich multilevel organizations in systems with highly separated regions, such as road networks. PMID:21494658
Multiple imputation of missing covariate values in multilevel models with random slopes: a cautionary note.
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander
Multiple imputation (MI) has become one of the main procedures used to treat missing data, but the guidelines from the methodological literature are not easily transferred to multilevel research. For models including random slopes, proper MI can be difficult, especially when the covariate values are partially missing. In the present article, we discuss applications of MI in multilevel random-coefficient models, theoretical challenges posed by slope variation, and the current limitations of standard MI software. Our findings from three simulation studies suggest that (a) MI is able to recover most parameters, but is currently not well suited to capture slope variation entirely when covariate values are missing; (b) MI offers reasonable estimates for most parameters, even in smaller samples or when its assumptions are not met; and PMID:25939979
Genome mapping by random anchoring: A discrete theoretical analysis
NASA Astrophysics Data System (ADS)
Zhang, M. Q.; Marr, T. G.
As a part of the international human genome project, large-scale genomic maps of human and other model organisms are being generated. More recently, mapping using various anchoring (as opposed to the traditional "fingerprinting") strategies have been proposed based largely on mathematical models. In all of the theoretical work dealing with anchoring, an anchor has been idealized as a point on a continuous, infinite-length genome. In general, it is not desirable to make these assumptions, since in practice they may be violated under a variety of actual biological situations. Here we analyze a discrete model that can be used to predict the expected progress made when mapping by random anchoring. By virtue of keeping all three length scales (genome length, clone length, and probe length) finite, our results for the random anchoring strategy are derived in full generality, which contain previous results as special cases and hence can have broad application for planning mapping experiments or assessing the accuracy of the continuum models. Finally, we pose a challenging nonrandom anchoring model corresponding to a more efficient mapping scheme.
Multibeam Approach to Pulse Scattering from Discrete Random Media.
NASA Astrophysics Data System (ADS)
Kilic, Ozlem
The problem of a pulsed aperture illuminating a two dimensional layer of discrete random medium over a flat, homogenous background is considered. The layer consists of sparsely distributed dielectric scatterers that are randomly oriented in space. The behavior of the backscattered signal from the medium is examined in the time domain for the case of a short pulse incidence. The excitation of the antenna is assumed to be arbitrary, and is represented as a discrete sum of shifted and tilted Gaussian beams by using Gabor expansion. The expansion is exact, and with the appropriate choice of beam parameters, the radiation pattern can be matched by considering only a few beams. The beams in the expansion represent the main and side lobes of the antenna, making it possible to examine the individual effects of each lobe on the backscattered signature. The received power at the antenna is composed of a coherent and an incoherent part associated respectively with the mean and the fluctuating parts of the scattered fields from the medium. The coherent term is observed as a sharp peak, while the incoherent term builds up and decays more slowly. The incoherent response is dominated by three terms: direct, direct reflected and reflected. The direct term is associated with the volume scattering and arrives first at the antenna. The second term observed at the antenna is the direct reflected component, which results from a single interaction between the scatterer and the ground. Depending on the attenuation inside the medium, this term can be the strongest return at the antenna. The reflected term which involves a double bounce from the ground arrives last due to the relatively longer path it travels. Using the multibeam representation, it is possible to examine individual returns from the side and main lobes of the antenna radiation pattern. The interference of the antenna lobes with each other can also be formulated via the multibeam representation. Strong responses from the
Who Is Most at Risk for School Removal? A Multilevel Discrete-Time Survival Analysis of Individual- and Context-Level Influences
ERIC Educational Resources Information Center
Petras, Hanno; Masyn, Katherine E.; Buckley, Jacquelyn A.; Ialongo, Nicholas S.; Kellam, Sheppard
The focus of this study was to prospectively investigate the effect of aggressive behavior and of classroom behavioral context, as measured in the fall of 1st grade, on the timing of 1st school removal across Grades 1-7 in a sample of predominately urban minority youths from Baltimore, Maryland. Using a multilevel discrete-time survival framework,…
Emergence of multilevel selection in the prisoner's dilemma game on coevolving random networks
NASA Astrophysics Data System (ADS)
Szolnoki, Attila; Perc, Matjaž
We study the evolution of cooperation in the prisoner's dilemma game, whereby a coevolutionary rule is introduced that molds the random topology of the interaction network in two ways. First, existing links are deleted whenever a player adopts a new strategy or its degree exceeds a threshold value; second, new links are added randomly after a given number of game iterations. These coevolutionary processes correspond to the generic formation of new links and deletion of existing links that, especially in human societies, appear frequently as a consequence of ongoing socialization, change of lifestyle or death. Due to the counteraction of deletions and additions of links the initial heterogeneity of the interaction network is qualitatively preserved, and thus cannot be held responsible for the observed promotion of cooperation. Indeed, the coevolutionary rule evokes the spontaneous emergence of a powerful multilevel selection mechanism, which despite the sustained random topology of the evolving network, maintains cooperation across the whole span of defection temptation values.
Multilevel, Two-Parameter, and Random-Weights Generalizations of a Model with Internal Restrictions on Item Difficulty
ERIC Educational Resources Information Center
Wang, Wen-Chung; Jin, Kuan-Yu
In this study, all the advantages of slope parameters, random weights, and latent regression are acknowledged when dealing with component and composite items by adding slope parameters and random weights into the standard item response model with internal restrictions on item difficulty and formulating this new model within a multilevel framework…
Performance of Empirical Bayes Estimators of Level-2 Random Parameters in Multilevel Analysis: A Monte Carlo Study for Longitudinal Designs
ERIC Educational Resources Information Center
Candel, Math J. J. M.; Winkens, Bjorn
Multilevel analysis is a useful technique for analyzing longitudinal data. To describe a person's development across time, the quality of the estimates of the random coefficients, which relate time to individual changes in a relevant dependent variable, is of importance. The present study compares three estimators of the random coefficients: the…
Double-image encryption scheme combining DWT-based compressive sensing with discrete fractional random transform
NASA Astrophysics Data System (ADS)
Zhou, Nanrun; Yang, Jianping; Tan, Changfa; Pan, Shumin; Zhou, Zhihong
A new discrete fractional random transform based on two circular matrices is designed and a novel double-image encryption-compression scheme is proposed by combining compressive sensing with discrete fractional random transform. The two random circular matrices and the measurement matrix utilized in compressive sensing are constructed by using a two-dimensional sine Logistic modulation map. Two original images can be compressed, encrypted with compressive sensing and connected into one image. The resulting image is re-encrypted by Arnold transform and the discrete fractional random transform. Simulation results and security analysis demonstrate the validity and security of the scheme.
Self-consistent quasiparticle random-phase approximation for a multilevel pairing model
Hung, N. Quang; Dang, N. Dinh
Particle-number projection within the Lipkin-Nogami (LN) method is applied to the self-consistent quasiparticle random-phase approximation (SCQRPA), which is tested in an exactly solvable multilevel pairing model. The SCQRPA equations are numerically solved to find the energies of the ground and excited states at various numbers {omega} of doubly degenerate equidistant levels. The use of the LN method allows one to avoid the collapse of the BCS (QRPA) to obtain the energies of the ground and excited states as smooth functions of the interaction parameter G. The comparison between results given by different approximations such as the SCRPA, QRPA, LNQRPA, SCQRPA, and LNSCQRPA is carried out. Although the use of the LN method significantly improves the agreement with the exact results in the intermediate coupling region, we found that in the strong coupling region the SCQRPA results are closest to the exact ones.
ERIC Educational Resources Information Center
Frees, Edward W.; Kim, Jee-Seon
Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling--model disturbances, random coefficients, and future response…
One-dimensional random field Ising model and discrete stochastic mappings
Behn, U.; Zagrebnov, V.A.
Previous results relating the one-dimensional random field Ising model to a discrete stochastic mapping are generalized to a two-valued correlated random (Markovian) field and to the case of zero temperature. The fractal dimension of the support of the invariant measure is calculated in a simple approximation and its dependence on the physical parameters is discussed.
Random sequential adsorption of polydisperse mixtures on discrete substrates.
Budinski-Petković, Lj; Vrhovac, S B; Loncarević, I
We study random sequential adsorption of polydisperse mixtures of extended objects both on a triangular and on a square lattice. The depositing objects are formed by self-avoiding random walks on two-dimensional lattices. Numerical simulations were performed to determine the influence of the number of mixture components and length of the shapes making the mixture on the kinetics of the deposition process. We find that the late stage deposition kinetics follows an exponential law theta(t) approximately theta_{jam}-Aexp(-tsigma) not only for the whole mixture, but also for the individual components. We discuss in detail how the quantities such as jamming coverage theta_{jam} and the relaxation time sigma depend on the mixture composition. Our results suggest that the order of symmetry axis of the shape may exert a decisive influence on adsorption kinetics of each mixture component. PMID:19256849
Estimation of Parameters from Discrete Random Nonstationary Time Series
NASA Astrophysics Data System (ADS)
Takayasu, H.; Nakamura, T.
For the analysis of nonstationary stochastic time series we introduce a formulation to estimate the underlying time-dependent parameters. This method is designed for random events with small numbers that are out of the applicability range of the normal distribution. The method is demonstrated for numerical data generated by a known system, and applied to time series of traffic accidents, batting average of a baseball player and sales volume of home electronics.
Multilevel Monte Carlo for Two Phase Flow and Transport in a Subsurface Reservoir with Random Permeability
NASA Astrophysics Data System (ADS)
Müller, Florian; Jenny, Patrick; Daniel, Meyer
To a large extent, the flow and transport behaviour within a subsurface reservoir is governed by its permeability. Typically, permeability measurements of a subsurface reservoir are affordable at few spatial locations only. Due to this lack of information, permeability fields are preferably described by stochastic models rather than deterministically. A stochastic method is needed to asses the transition of the input uncertainty in permeability through the system of partial differential equations describing flow and transport to the output quantity of interest. Monte Carlo (MC) is an established method for quantifying uncertainty arising in subsurface flow and transport problems. Although robust and easy to implement, MC suffers from slow statistical convergence. To reduce the computational cost of MC, the multilevel Monte Carlo (MLMC) method was introduced. Instead of sampling a random output quantity of interest on the finest affordable grid as in case of MC, MLMC operates on a hierarchy of grids. If parts of the sampling process are successfully delegated to coarser grids where sampling is inexpensive, MLMC can dramatically outperform MC. MLMC has proven to accelerate MC for several applications including integration problems, stochastic ordinary differential equations in finance as well as stochastic elliptic and hyperbolic partial differential equations. In this study, MLMC is combined with a reservoir simulator to assess uncertain two phase (water/oil) flow and transport within a random permeability field. The performance of MLMC is compared to MC for a two-dimensional reservoir with a multi-point Gaussian logarithmic permeability field. It is found that MLMC yields significant speed-ups with respect to MC while providing results of essentially equal accuracy. This finding holds true not only for one specific Gaussian logarithmic permeability model but for a range of correlation lengths and variances.
Monte Carlo simulation for temporal characteristics of pulse laser propagation in discrete random medium
NASA Astrophysics Data System (ADS)
Wang, Ping; Yuan, Hongwu; Mei, Haiping; Zhang, Qianghua
Study the laser pulses transmission time characteristics in discrete random medium using the Monte Carlo method. Firstly, the medium optical parameters have been given by OPAC software. Then, create a Monte Carlo model and Monte Carlo simulation of photon transport behavior of a large number of tracking, statistics obtain the photon average arrival time and average pulse broadening case, the calculation result with calculation results of two-frequency mutual coherence function are compared, the results are very consistent. Finally, medium impulse response function given by polynomial fitting method can be used to correct discrete random medium inter-symbol interference in optical communications and reduce the rate of system error.
Generation of Random Particle Packings for Discrete Element Models
NASA Astrophysics Data System (ADS)
Abe, S.; Weatherley, D.; Ayton, T.
An important step in the setup process of Discrete Element Model (DEM) simulations is the generation of a suitable particle packing. There are quite a number of properties such a granular material specimen should ideally have, such as high coordination number, isotropy, the ability to fill arbitrary bounding volumes and the absence of locked-in stresses. An algorithm which is able to produce specimens fulfilling these requirements is the insertion based sphere packing algorithm originally proposed by Place and Mora, 2001 [2] and extended in this work. The algorithm works in two stages. First a number of "seed" spheres are inserted into the bounding volume. In the second stage the gaps between the "seed" spheres are filled by inserting new spheres in a way so they have D+1 (i.e. 3 in 2D, 4 in 3D) touching contacts with either other spheres or the boundaries of the enclosing volume. Here we present an implementation of the algorithm and a systematic statistical analysis of the generated sphere packings. The analysis of the particle radius distribution shows that they follow a power-law with an exponent ≈ D (i.e. ≈3 for a 3D packing and ≈2 for 2D). Although the algorithm intrinsically guarantees coordination numbers of at least 4 in 3D and 3 in 2D, the coordination numbers realized in the generated packings can be significantly higher, reaching beyond 50 if the range of particle radii is sufficiently large. Even for relatively small ranges of particle sizes (e.g. Rmin = 0.5Rmax) the maximum coordination number may exceed 10. The degree of isotropy of the generated sphere packing is also analysed in both 2D and 3D, by measuring the distribution of orientations of vectors joining the centres of adjacent particles. If the range of particle sizes is small, the packing algorithm yields moderate anisotropy approaching that expected for a face-centred cubic packing of equal-sized particles. However, once Rmin < 0.3Rmax a very high degree of isotropy is demonstrated in
Covariate Adjustment Strategy Increases Power in the Randomized Controlled Trial With Discrete-Time Survival Endpoints
ERIC Educational Resources Information Center
Safarkhani, Maryam; Moerbeek, Mirjam
In a randomized controlled trial, a decision needs to be made about the total number of subjects for adequate statistical power. One way to increase the power of a trial is by including a predictive covariate in the model. In this article, the effects of various covariate adjustment strategies on increasing the power is studied for discrete-time…
Multi-level Monte Carlo finite volume methods for uncertainty quantification of acoustic wave propagation in random heterogeneous layered medium
NASA Astrophysics Data System (ADS)
Mishra, S.; Schwab, Ch.; Šukys, J.
We consider the very challenging problem of efficient uncertainty quantification for acoustic wave propagation in a highly heterogeneous, possibly layered, random medium, characterized by possibly anisotropic, piecewise log-exponentially distributed Gaussian random fields. A multi-level Monte Carlo finite volume method is proposed, along with a novel, bias-free upscaling technique that allows to represent the input random fields, generated using spectral FFT methods, efficiently. Combined together with a recently developed dynamic load balancing algorithm that scales to massively parallel computing architectures, the proposed method is able to robustly compute uncertainty for highly realistic random subsurface formations that can contain a very high number (millions) of sources of uncertainty. Numerical experiments, in both two and three space dimensions, illustrating the efficiency of the method are presented.
Comparing Algorithms for Graph Isomorphism Using Discrete- and Continuous-Time Quantum Random Walks
Rudinger, Kenneth; Gamble, John King; Bach, Eric; Friesen, Mark; Joynt, Robert; Coppersmith, S. N.
Berry and Wang [Phys. Rev. A 83, 042317 (2011)] show numerically that a discrete-time quan- tum random walk of two noninteracting particles is able to distinguish some non-isomorphic strongly regular graphs from the same family. Here we analytically demonstrate how it is possible for these walks to distinguish such graphs, while continuous-time quantum walks of two noninteracting parti- cles cannot. We show analytically and numerically that even single-particle discrete-time quantum random walks can distinguish some strongly regular graphs, though not as many as two-particle noninteracting discrete-time walks. Additionally, we demonstrate how, given the same quantum random walk, subtle di erences in the graph certi cate construction algorithm can nontrivially im- pact the walk's distinguishing power. We also show that no continuous-time walk of a xed number of particles can distinguish all strongly regular graphs when used in conjunction with any of the graph certi cates we consider. We extend this constraint to discrete-time walks of xed numbers of noninteracting particles for one kind of graph certi cate; it remains an open question as to whether or not this constraint applies to the other graph certi cates we consider.
Comparing Algorithms for Graph Isomorphism Using Discrete- and Continuous-Time Quantum Random Walks
Rudinger, Kenneth; Gamble, John King; Bach, Eric; Friesen, Mark; Joynt, Robert; Coppersmith, S. N.
Berry and Wang [Phys. Rev. A 83, 042317 (2011)] show numerically that a discrete-time quan- tum random walk of two noninteracting particles is able to distinguish some non-isomorphic strongly regular graphs from the same family. Here we analytically demonstrate how it is possible for these walks to distinguish such graphs, while continuous-time quantum walks of two noninteracting parti- cles cannot. We show analytically and numerically that even single-particle discrete-time quantum random walks can distinguish some strongly regular graphs, though not as many as two-particle noninteracting discrete-time walks. Additionally, we demonstrate how, given the same quantum random walk, subtle di erencesmore » in the graph certi cate construction algorithm can nontrivially im- pact the walk's distinguishing power. We also show that no continuous-time walk of a xed number of particles can distinguish all strongly regular graphs when used in conjunction with any of the graph certi cates we consider. We extend this constraint to discrete-time walks of xed numbers of noninteracting particles for one kind of graph certi cate; it remains an open question as to whether or not this constraint applies to the other graph certi cates we consider.« less
Recursive state estimation for discrete time-varying stochastic nonlinear systems with randomly occurring deception attacks
NASA Astrophysics Data System (ADS)
Ding, Derui; Shen, Yuxuan; Song, Yan; Wang, Yongxiong
This paper is concerned with the state estimation problem for a class of discrete time-varying stochastic nonlinear systems with randomly occurring deception attacks. The stochastic nonlinearity described by statistical means which covers several classes of well-studied nonlinearities as special cases is taken into discussion. The randomly occurring deception attacks are modelled by a set of random variables obeying Bernoulli distributions with given probabilities. The purpose of the addressed state estimation problem is to design an estimator with hope to minimize the upper bound for estimation error covariance at each sampling instant. Such an upper bound is minimized by properly designing the estimator gain. The proposed estimation scheme in the form of two Riccati-like difference equations is of a recursive form. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed scheme.
Coherent Backscattering by Polydisperse Discrete Random Media: Exact T-Matrix Results
NASA Technical Reports Server (NTRS)
Mishchenko, Michael I.; Dlugach, Janna M.; Mackowski, Daniel W.
The numerically exact superposition T-matrix method is used to compute, for the first time to our knowledge, electromagnetic scattering by finite spherical volumes composed of polydisperse mixtures of spherical particles with different size parameters or different refractive indices. The backscattering patterns calculated in the far-field zone of the polydisperse multiparticle volumes reveal unequivocally the classical manifestations of the effect of weak localization of electromagnetic waves in discrete random media, thereby corroborating the universal interference nature of coherent backscattering. The polarization opposition effect is shown to be the least robust manifestation of weak localization fading away with increasing particle size parameter.
Contrasting the Effectiveness of Fluency Interventions for Students with or at Risk for Learning Disabilities: A Multilevel Random Coefficient Modeling Meta-Analysis
ERIC Educational Resources Information Center
Morgan, Paul L.; Sideridis, Georgios D.
This study had two purposes. First, we sought to compare the overall effectiveness of different types of fluency interventions for students with learning disabilities (LD). Second, we attempted to identify how individual- and class-level characteristics moderated each intervention's effectiveness. We used multilevel random coefficient modeling to…
Multilevel Monte Carlo for two phase flow and Buckley–Leverett transport in random heterogeneous porous media
Müller, Florian Jenny, Patrick Meyer, Daniel W.
Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley–Leverett transport in random heterogeneous porous media. The performance of MLMC is compared to MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.
Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay
Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Nakamori, S.
This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.
Simulation of electromagnetic scattering by random discrete particles using a hybrid FE-BI-CBFM technique
NASA Astrophysics Data System (ADS)
Cui, Z.-W.; Han, Y.-P.; Li, C.-Y.
A hybrid finite element-boundary integral-characteristic basis function method (FE-BI-CBFM) is proposed for an efficient simulation of electromagnetic scattering by random discrete particles. Specifically, the finite element method (FEM) is used to obtain the solution of the vector wave equation inside each particle and the boundary integral equation (BIE) using Green's functions is applied on the surfaces of all the particles as a global boundary condition. The coupling system of equations is solved by employing the characteristic basis function method (CBFM) based on the use of macro-basis functions constructed according to the Foldy-Lax multiple scattering equations. Due to the flexibility of FEM, the proposed hybrid technique can easily deal with the problems of multiple scattering by randomly distributed inhomogeneous particles that are often beyond the scope of traditional numerical methods. Some numerical examples are presented to demonstrate the validity and capability of the proposed method.
Dynamical Localization for Discrete and Continuous Random Schrödinger Operators
NASA Astrophysics Data System (ADS)
Germinet, F.; De Bièvre, S.
We show for a large class of random Schrödinger operators Ho on and on that dynamical localization holds, i.e. that, with probability one, for a suitable energy interval I and for q a positive real,
Discrete-time systems with random switches: From systems stability to networks synchronization.
Guo, Yao; Lin, Wei; Ho, Daniel W C
In this article, we develop some approaches, which enable us to more accurately and analytically identify the essential patterns that guarantee the almost sure stability of discrete-time systems with random switches. We allow for the case that the elements in the switching connection matrix even obey some unbounded and continuous-valued distributions. In addition to the almost sure stability, we further investigate the almost sure synchronization in complex dynamical networks consisting of randomly connected nodes. Numerical examples illustrate that a chaotic dynamics in the synchronization manifold is preserved when statistical parameters enter some almost sure synchronization region established by the developed approach. Moreover, some delicate configurations are considered on probability space for ensuring synchronization in networks whose nodes are described by nonlinear maps. Both theoretical and numerical results on synchronization are presented by setting only a few random connections in each switch duration. More interestingly, we analytically find it possible to achieve almost sure synchronization in the randomly switching complex networks even with very large population sizes, which cannot be easily realized in non-switching but deterministically connected networks. PMID:27036191
Discrete-time systems with random switches: From systems stability to networks synchronization
NASA Astrophysics Data System (ADS)
Guo, Yao; Lin, Wei; Ho, Daniel W. C.
In this article, we develop some approaches, which enable us to more accurately and analytically identify the essential patterns that guarantee the almost sure stability of discrete-time systems with random switches. We allow for the case that the elements in the switching connection matrix even obey some unbounded and continuous-valued distributions. In addition to the almost sure stability, we further investigate the almost sure synchronization in complex dynamical networks consisting of randomly connected nodes. Numerical examples illustrate that a chaotic dynamics in the synchronization manifold is preserved when statistical parameters enter some almost sure synchronization region established by the developed approach. Moreover, some delicate configurations are considered on probability space for ensuring synchronization in networks whose nodes are described by nonlinear maps. Both theoretical and numerical results on synchronization are presented by setting only a few random connections in each switch duration. More interestingly, we analytically find it possible to achieve almost sure synchronization in the randomly switching complex networks even with very large population sizes, which cannot be easily realized in non-switching but deterministically connected networks.
Community-Based Prevention of Marital Dysfunction: Multilevel Modeling of a Randomized Effectiveness Study
ERIC Educational Resources Information Center
Laurenceau, Jean-Philippe; Stanley, Scott M.; Olmos-Gallo, Antonio; Baucom, Brian; Markham, Howard J.
This study is a cluster randomized controlled trial of the Prevention and Relationship Enhancement Program (PREP; H. J. Markman, S. M. Stanley, & S. L. Blumberg, 2001). Fifty-seven religious organizations (ROs), consisting of 217 newlywed couples, were randomly assigned to 1 of 3 intervention conditions: PREP delivered by university clinicians…
Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network
NASA Technical Reports Server (NTRS)
Kuhn, D. Richard; Kacker, Raghu; Lei, Yu
This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.
An exploratory discrete-time multilevel analysis of the effect of social support on the survival of elderly people in China
Feng, Zhixin; Jones, Kelvyn; Wang, Wenfei Winnie
This study undertakes a survival analysis of elderly persons in China using Chinese Longitudinal Healthy Longevity Survey 2002–2008. Employing discrete-time multilevel models, we explored the effect of social support on the survival of elderly people in China. This study focuses on objective (living arrangements and received support) and subjective activities (perceived support) of social support, finding that the effect of different activities of social support on the survival of elderly people varies according to the availability of different support resources. Specifically, living with a spouse, financial independence, perceiving care support from any resource is associated with higher survival rates for elderly people. Separate analysis focusing on urban elderly and rural elderly revealed broadly similar results. There is a larger difference between those perceiving care support from family or social service and not perceiving care support in urban areas comparing to those in rural areas. Those who cannot pay medical expenses are the least likely to survive. The higher level of economic development in province has no significant effect on the survival of elderly people for the whole sample model and the elderly people in urban areas; however, there is a negative influence on the survival of the rural elderly people. PMID:25703671
Coupling of discrete random walks and continuous modeling for three-dimensional tumor-induced angiogenesis
NASA Astrophysics Data System (ADS)
Vilanova, Guillermo; Colominas, Ignasi; Gomez, Hector
The growth of new vascular networks from pre-existing capillaries (angiogenesis) plays a pivotal role in tumor development. Mathematical modeling of tumor-induced angiogenesis may help understand the underlying biology of the process and provide new hypotheses for experimentation. Here, we couple an existing deterministic continuum theory with a discrete random walk, proposing a new model that accounts for chemotactic and haptotactic cellular migration. We propose an efficient numerical method to approximate the solution of the model. The accuracy, stability and effectiveness of our algorithms permitted us to perform large-scale three-dimensional simulations which, in contrast to two-dimensional calculations, show a topological complexity similar to that found in experiments. Finally, we use our model and simulations to investigate the role of haptotaxis and chemotaxis in the mobility of tip endothelial cells and its influence in the final vascular patterns.
Fast state estimation subject to random data loss in discrete-time nonlinear stochastic systems
NASA Astrophysics Data System (ADS)
Mahdi Alavi, S. M.; Saif, Mehrdad
This paper focuses on the design of the standard observer in discrete-time nonlinear stochastic systems subject to random data loss. By the assumption that the system response is incrementally bounded, two sufficient conditions are subsequently derived that guarantee exponential mean-square stability and fast convergence of the estimation error for the problem at hand. An efficient algorithm is also presented to obtain the observer gain. Finally, the proposed methodology is employed for monitoring the Continuous Stirred Tank Reactor (CSTR) via a wireless communication network. The effectiveness of the designed observer is extensively assessed by using an experimental tested-bed that has been fabricated for performance evaluation of the over wireless-network estimation techniques under realistic radio channel conditions.
Multilevel ensemble Kalman filtering
Hoel, Hakon; Law, Kody J. H.; Tempone, Raul
This study embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. Finally, the resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials
ERIC Educational Resources Information Center
Van Horn, M. Lee; Fagan, Abigail A.; Jaki, Thomas; Brown, Eric C.; Hawkins, J. David; Arthur, Michael W.; Abbott, Robert D.; Catalano, Richard F.
There is evidence to suggest that the effects of behavioral interventions may be limited to specific types of individuals, but methods for evaluating such outcomes have not been fully developed. This study proposes the use of finite mixture models to evaluate whether interventions, and, specifically, group randomized trials, impact participants…
Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams
NASA Technical Reports Server (NTRS)
Mackowski, Daniel W.; Mishchenko, Michael I.
The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.
Exponential H∞ filtering for discrete-time switched neural networks with random delays.
Mathiyalagan, Kalidass; Su, Hongye; Shi, Peng; Sakthivel, Rathinasamy
This paper addresses the exponential H∞ filtering problem for a class of discrete-time switched neural networks with random time-varying delays. The involved delays are assumed to be randomly time-varying which are characterized by introducing a Bernoulli stochastic variable. Effects of both variation range and distribution probability of the time delays are considered. The nonlinear activation functions are assumed to satisfy the sector conditions. Our aim is to estimate the state by designing a full order filter such that the filter error system is globally exponentially stable with an expected decay rate and a H∞ performance attenuation level. The filter is designed by using a piecewise Lyapunov-Krasovskii functional together with linear matrix inequality (LMI) approach and average dwell time method. First, a set of sufficient LMI conditions are established to guarantee the exponential mean-square stability of the augmented system and then the parameters of full-order filter are expressed in terms of solutions to a set of LMI conditions. The proposed LMI conditions can be easily solved by using standard software packages. Finally, numerical examples by means of practical problems are provided to illustrate the effectiveness of the proposed filter design. PMID:25020225
Calibration of Discrete Random Walk (DRW) Model via G.I Taylor's Dispersion Theory
NASA Astrophysics Data System (ADS)
Javaherchi, Teymour; Aliseda, Alberto
Prediction of particle dispersion in turbulent flows is still an important challenge with many applications to environmental, as well as industrial, fluid mechanics. Several models of dispersion have been developed to predict particle trajectories and their relative velocities, in combination with a RANS-based simulation of the background flow. The interaction of the particles with the velocity fluctuations at different turbulent scales represents a significant difficulty in generalizing the models to the wide range of flows where they are used. We focus our attention on the Discrete Random Walk (DRW) model applied to flow in a channel, particularly to the selection of eddies lifetimes as realizations of a Poisson distribution with a mean value proportional to κ / ɛ . We present a general method to determine the constant of this proportionality by matching the DRW model dispersion predictions for fluid element and particle dispersion to G.I Taylor's classical dispersion theory. This model parameter is critical to the magnitude of predicted dispersion. A case study of its influence on sedimentation of suspended particles in a tidal channel with an array of Marine Hydrokinetic (MHK) turbines highlights the dependency of results on this time scale parameter. Support from US DOE through the Northwest National Marine Renewable Energy Center, a UW-OSU partnership.
Poynting-Stokes tensor and radiative transfer in discrete random media: the microphysical paradigm.
Mishchenko, Michael I
This paper solves the long-standing problem of establishing the fundamental physical link between the radiative transfer theory and macroscopic electromagnetics in the case of elastic scattering by a sparse discrete random medium. The radiative transfer equation (RTE) is derived directly from the macroscopic Maxwell equations by computing theoretically the appropriately defined so-called Poynting-Stokes tensor carrying information on both the direction, magnitude, and polarization characteristics of local electromagnetic energy flow. Our derivation from first principles shows that to compute the local Poynting vector averaged over a sufficiently long period of time, one can solve the RTE for the direction-dependent specific intensity column vector and then integrate the direction-weighted specific intensity over all directions. Furthermore, we demonstrate that the specific intensity (or specific intensity column vector) can be measured with a well-collimated radiometer (photopolarimeter), which provides the ultimate physical justification for the use of such instruments in radiation-budget and particle-characterization applications. However, the specific intensity cannot be interpreted in phenomenological terms as signifying the amount of electromagnetic energy transported in a given direction per unit area normal to this direction per unit time per unit solid angle. Also, in the case of a densely packed scattering medium the relation of the measurement with a well-collimated radiometer to the time-averaged local Poynting vector remains uncertain, and the theoretical modeling of this measurement is likely to require a much more complicated approach than solving an RTE. PMID:20940872
A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference
Thomas, D.L.; Johnson, D.; Griffith, B.
Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a
Adaptive multi-level conditional random fields for detection and segmentation of small enhanced pathology in medical images.
Karimaghaloo, Zahra; Arnold, Douglas L; Arbel, Tal
Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive
Ulam's method to estimate invariant measures and Lyapunov exponents for one-dimensional discretely randomized photonic structures
NASA Astrophysics Data System (ADS)
Kissel, Glen J.
In the one-dimensional optical analog to Anderson localization, a periodically layered medium has one or more parameters randomly disordered. Such a medium can be modeled by an infinite product of 2x2 random transfer matrices with the upper Lyapunov exponent of the matrix product identified as the localization factor (inverse localization length). Furstenberg's integral formula for the Lyapunov exponent requires integration with respect to both the probability measure of the random matrices and the invariant probability measure of the direction of the vector propagated by the random matrix product. This invariant measure is difficult to find analytically, so one of several numerical techniques must be used in its calculation. Here, we focus on one of those techniques, Ulam's method, which sets up a sparse matrix of the probabilities that an entire interval of possible directions will be transferred to some other interval of directions. The left eigenvector of this sparse matrix forms the estimated invariant measure. While Ulam's method is shown to produce results as accurate as others, it suffers from long computation times. The Ulam method, along with other approaches, is demonstrated on a random Fibonacci sequence having a known answer, and on a quarter-wave stack model with discrete disorder in layer thickness.
Discrete-Time Pricing and Optimal Exercise of American Perpetual Warrants in the Geometric Random Walk Model
Vanderbei, Robert J.; P Latin-Small-Letter-Dotless-I nar, Mustafa C.; Bozkaya, Efe B.
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
A simple device unit consisting of all NiO storage and switch elements for multilevel terabit nonvolatile random access memory.
Lee, Myoung-Jae; Ahn, Seung-Eon; Lee, Chang Bum; Kim, Chang-Jung; Jeon, Sanghun; Chung, U-In; Yoo, In-Kyeong; Park, Gyeong-Su; Han, Seungwu; Hwang, In Rok; Park, Bae-Ho
Present charge-based silicon memories are unlikely to reach terabit densities because of scaling limits. As the feature size of memory shrinks to just tens of nanometers, there is insufficient volume available to store charge. Also, process temperatures higher than 800 °C make silicon incompatible with three-dimensional (3D) stacking structures. Here we present a device unit consisting of all NiO storage and switch elements for multilevel terabit nonvolatile random access memory using resistance switching. It is demonstrated that NiO films are scalable to around 30 nm and compatible with multilevel cell technology. The device unit can be a building block for 3D stacking structure because of its simple structure and constituent, high performance, and process temperature lower than 300 °C. Memory resistance switching of NiO storage element is accompanied by an increase in density of grain boundary while threshold resistance switching of NiO switch element is controlled by current flowing through NiO film. PMID:21988144
Investigation of detonation propagation through an array of random discrete energy sources using the reactive Burgers' analog
NASA Astrophysics Data System (ADS)
di Labbio, Giuseppe; Kiyanda, Charles Basenga; Mi, Xiaocheng; Higgins, Andrew Jason; Nikiforakis, Nikolaos; Ng, Hoi Dick
For a homogeneous reactive medium such as a combustible gaseous mixture, the detonation wave is nearly always observed to propagate at a velocity predicted by the Chapman-Jouguet (CJ) condition. Although the CJ condition was originally formulated for a wave propagating in homogeneous media at constant velocity, it has been posited that this condition may also determine the average detonation velocity in heterogeneous media. This work aims to test the applicability of the CJ condition to heterogeneous media on the one-dimensional reactive Burgers' equation, a tractable analog to the reactive Euler equations, with the reaction governed by an Arrhenius rate law. In this study, heterogeneity is modeled using discrete energy sources, of random energy content, randomly distributed throughout space such that the total energy release is equivalent to that of a homogeneous medium with constant energy density. The equations are solved using a second-order finite volume approach with an exact Riemann solver. The evolution of the discrete detonation is tracked over a long duration and its average propagation velocity is computed. In all cases, the average detonation velocity was found to be in agreement with the velocity predicted by the CJ condition for the equivalent homogeneous system.
Multifractality, imperfect scaling and hydrological properties of rainfall time series simulated by continuous universal multifractal and discrete random cascade models
NASA Astrophysics Data System (ADS)
Serinaldi, F.
Discrete multiplicative random cascade (MRC) models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity) at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC) model based on beta distribution and a discrete canonical beta-logstable (BLS), the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM) model, which is used as a physically based benchmark model. Monte Carlo simulations point out that the dependence of MC and BLS
Random Graphs Associated to Some Discrete and Continuous Time Preferential Attachment Models
NASA Astrophysics Data System (ADS)
Pachon, Angelica; Polito, Federico; Sacerdote, Laura
We give a common description of Simon, Barabási-Albert, II-PA and Price growth models, by introducing suitable random graph processes with preferential attachment mechanisms. Through the II-PA model, we prove the conditions for which the asymptotic degree distribution of the Barabási-Albert model coincides with the asymptotic in-degree distribution of the Simon model. Furthermore, we show that when the number of vertices in the Simon model (with parameter α ) goes to infinity, a portion of them behave as a Yule model with parameters (λ ,β ) = (1-α ,1), and through this relation we explain why asymptotic properties of a random vertex in Simon model, coincide with the asymptotic properties of a random genus in Yule model. As a by-product of our analysis, we prove the explicit expression of the in-degree distribution for the II-PA model, given without proof in Newman (Contemp Phys 46:323-351, 2005). References to traditional and recent applications of the these models are also discussed.
Scattering of electromagnetic waves from a half-space of randomly distributed discrete scatterers and polarized backscattering ratio law
NASA Technical Reports Server (NTRS)
Zhu, P. Y.
The effective-medium approximation is applied to investigate scattering from a half-space of randomly and densely distributed discrete scatterers. Starting from vector wave equations, an approximation, called effective-medium Born approximation, a particular way, treating Green's functions, and special coordinates, of which the origin is set at the field point, are used to calculate the bistatic- and back-scatterings. An analytic solution of backscattering with closed form is obtained and it shows a depolarization effect. The theoretical results are in good agreement with the experimental measurements in the cases of snow, multi- and first-year sea-ice. The root product ratio of polarization to depolarization in backscattering is equal to 8; this result constitutes a law about polarized scattering phenomena in the nature.
Depinning of a discrete elastic string from a two-dimensional random array of weak pinning points
Proville, Laurent
The present work is essentially concerned with the development of statistical theory for the low temperature dislocation glide in concentrated solid solutions where atom-sized obstacles impede plastic flow. In connection with such a problem, we compute analytically the external force required to drag an elastic string along a discrete two-dimensional square lattice, where some obstacles have been randomly distributed. Some numerical simulations allow us to demonstrate the remarkable agreement between simulations and theory for an obstacle density ranging from 1% to 50% and for lattices with different aspect ratios. The theory proves efficient on the condition that the obstacle-chain interaction remains sufficiently weak compared to the string stiffness.
Non-fragile H∞ filtering for nonlinear discrete-time delay systems with randomly occurring gain variations.
Liu, Yajuan; Park, Ju H; Guo, Bao-Zhu
In this paper,the problem of H∞ filtering for a class of nonlinear discrete-time delay systems is investigated. The time delay is assumed to be belonging to a given interval, and the designed filter includes additive gain variations which are supposed to be random and satisfy the Bernoulli distribution. By the augmented Lyapunov functional approach, a sufficient condition is developed to ensure that the filtering error system is asymptotically mean-square stable with a prescribed H∞ performance. In addition, an improved result of H∞ filtering for linear system is also derived. The filter parameters are obtained by solving a set of linear matrix inequalities. For nonlinear systems, the applicability of the developed filtering result is confirmed by a longitudinal flight system, and an additional example for linear system is presented to demonstrate the less conservativeness of the proposed design method. PMID:27157851
A Multilevel Algorithm for the Solution of Second Order Elliptic Differential Equations on Sparse Grids
NASA Technical Reports Server (NTRS)
Pflaum, Christoph
A multilevel algorithm is presented that solves general second order elliptic partial differential equations on adaptive sparse grids. The multilevel algorithm consists of several V-cycles. Suitable discretizations provide that the discrete equation system can be solved in an efficient way. Numerical experiments show a convergence rate of order Omicron(1) for the multilevel algorithm.
Reliable H∞ control of discrete-time systems against random intermittent faults
NASA Astrophysics Data System (ADS)
Tao, Yuan; Shen, Dong; Fang, Mengqi; Wang, Youqing
A passive fault-tolerant control strategy is proposed for systems subject to a novel kind of intermittent fault, which is described by a Bernoulli distributed random variable. Three cases of fault location are considered, namely, sensor fault, actuator fault, and both sensor and actuator faults. The dynamic feedback controllers are designed not only to stabilise the fault-free system, but also to guarantee an acceptable performance of the faulty system. The robust H∞ performance index is used to evaluate the effectiveness of the proposed control scheme. In terms of linear matrix inequality, the sufficient conditions of the existence of controllers are given. An illustrative example indicates the effectiveness of the proposed fault-tolerant control method.
Reverse engineering discrete dynamical systems from data sets with random input vectors.
Just, Winfried
Recently a new algorithm for reverse engineering of biochemical networks was developed by Laubenbacher and Stigler. It is based on methods from computational algebra and finds most parsimonious models for a given data set. We derive mathematically rigorous estimates for the expected amount of data needed by this algorithm to find the correct model. In particular, we demonstrate that for one type of input parameter (graded term orders), the expected data requirements scale polynomially with the number n of chemicals in the network, while for another type of input parameters (randomly chosen lex orders) this number scales exponentially in n. We also show that, for a modification of the algorithm, the expected data requirements scale as the logarithm of n. PMID:17061920
Enhancing adolescent self-efficacy and collective efficacy through public engagement around HIV/AIDS competence: a multilevel, cluster randomized-controlled trial.
Carlson, Mary; Brennan, Robert T; Earls, Felton
The potential capacity of children to confront the HIV/AIDS pandemic is rarely considered. Interventions to address the impact of the pandemic on children and adolescents commonly target only their vulnerabilities. We evaluated the Young Citizens Program, an adolescent-centered health promotion curriculum designed to increase self- and collective efficacy through public education and community mobilization across a municipality in the Kilimanjaro Region of Tanzania. The theoretical framework for the program integrates aspects of human capability, communicative action, social ecology and social cognition. The design consists of a cluster randomized-controlled trial (CRCT). Fifteen pairs of matched geopolitically defined neighborhoods of roughly 2000-4000 residents were randomly allocated to treatment and control arms. Within each neighborhood cluster, 24 randomly selected adolescents, ages 9-14, deliberated on topics of social ecology, citizenship, community health and HIV/AIDS competence. Building on their acquired understanding and confidence, they dramatized the scientific basis and social context of HIV infection, testing and treatment in their communities over a 28-week period. The curriculum comprised 5 modules: Group Formation, Understanding our Community, Health and our Community, Making Assessments and Taking Action in our Community and Inter-Acting in our Community. Adolescent participants and adult residents representative of their neighborhoods were surveyed before and after the intervention; data were analyzed using multilevel modeling. In treatment neighborhoods, adolescents increased their deliberative and communicative efficacy and adults showed higher collective efficacy for children. Following the CRCT assessments, the control group received the same curriculum. In the Kilimanjaro Region, the Young Citizens Program is becoming recognized as a structural, health promotion approach through which adolescent self-efficacy and child collective efficacy
Reliable H ∞ control for discrete uncertain time-delay systems with randomly occurring nonlinearities: the output feedback case
NASA Astrophysics Data System (ADS)
Liu, Yisha; Wang, Zidong; Wang, Wei
This article is concerned with the reliable H ∞ output feedback control problem against actuator failures for a class of uncertain discrete time-delay systems with randomly occurred nonlinearities (RONs). The failures of actuators are quantified by a variable varying in a given interval. RONs are introduced to model a class of sector-like nonlinearities that occur in a probabilistic way according to a Bernoulli distributed white sequence with a known conditional probability. The time-varying delay is unknown with the given lower and upper bounds. Attention is focused on the analysis and design of an output feedback controller such that, for all possible actuator failures, RONs, time-delays as well as admissible parameter uncertainties, the closed-loop system is exponentially mean-square stable and also achieves a prescribed H ∞ performance level. A linear matrix inequality approach is developed to solve the addressed problem. A numerical example is given to demonstrate the effectiveness of the proposed design approach.
Assessing the consistency of the treatment effect under the discrete random effects model in multiregional clinical trials.
Liu, Jung-Tzu; Tsou, Hsiao-Hui; Gordon Lan, K K; Chen, Chi-Tian; Lai, Yi-Hsuan; Chang, Wan-Jung; Tzeng, Chyng-Shyan; Hsiao, Chin-Fu
In recent years, developing pharmaceutical products via multiregional clinical trials (MRCTs) has become standard. Traditionally, an MRCT would assume that a treatment effect is uniform across regions. However, heterogeneity among regions may have impact upon the evaluation of a medicine's effect. In this study, we consider a random effects model using discrete distribution (DREM) to account for heterogeneous treatment effects across regions for the design and evaluation of MRCTs. We derive an power function for a treatment that is beneficial under DREM and illustrate determination of the overall sample size in an MRCT. We use the concept of consistency based on Method 2 of the Japanese Ministry of Health, Labour, and Welfare's guidance to evaluate the probability for treatment benefit and consistency under DREM. We further derive an optimal sample size allocation over regions to maximize the power for consistency. Moreover, we provide three algorithms for deriving sample size at the desired level of power for benefit and consistency. In practice, regional treatment effects are unknown. Thus, we provide some guidelines on the design of MRCTs with consistency when the regional treatment effect are assumed to fall into a specified interval. Numerical examples are given to illustrate applications of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26833851
Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking.
Reboussin, Beth A; Preisser, John S; Song, Eun-Young; Wolfson, Mark
Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called 'clustering'. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure. PMID:24347839
Multilevel Growth Curve Analyses of Treatment Effects of a Web-Based Intervention for Stress Reduction: Randomized Controlled Trial
Raeder, Sabine; Kraft, Pål; Bjørkli, Cato Alexander
Background Stress is commonly experienced by many people and it is a contributing factor to many mental and physical health conditions, However, few efforts have been made to develop and test the effects of interventions for stress. Objective The aim of this study was to examine the effects of a Web-based stress-reduction intervention on stress, investigate mindfulness and procrastination as potential mediators of any treatment effects, and test whether the intervention is equally effective for females as males, all ages, and all levels of education. Methods We employed a randomized controlled trial in this study. Participants were recruited online via Facebook and randomly assigned to either the stress intervention or a control condition. The Web-based stress intervention was fully automated and consisted of 13 sessions over 1 month. The controls were informed that they would get access to the intervention after the final data collection. Data were collected at baseline and at 1, 2, and 6 months after intervention onset by means of online questionnaires. Outcomes were stress, mindfulness, and procrastination, which were all measured at every measurement occasion. Results A total of 259 participants were included and were allocated to either the stress intervention (n=126) or the control condition (n=133). Participants in the intervention and control group were comparable at baseline; however, results revealed that participants in the stress intervention followed a statistically different (ie, cubic) developmental trajectory in stress levels over time compared to the controls. A growth curve analysis showed that participants in the stress intervention (unstandardized beta coefficient [B]=–3.45, P=.008) recovered more quickly compared to the control group (B=–0.81, P=.34) from baseline to 1 month. Although participants in the stress intervention did show increases in stress levels during the study period (B=2.23, P=.008), long-term stress levels did decrease
A multilevel stochastic collocation method for SPDEs
Gunzburger, Max; Jantsch, Peter; Teckentrup, Aretha; Webster, Clayton
We present a multilevel stochastic collocation method that, as do multilevel Monte Carlo methods, uses a hierarchy of spatial approximations to reduce the overall computational complexity when solving partial differential equations with random inputs. For approximation in parameter space, a hierarchy of multi-dimensional interpolants of increasing fidelity are used. Rigorous convergence and computational cost estimates for the new multilevel stochastic collocation method are derived and used to demonstrate its advantages compared to standard single-level stochastic collocation approximations as well as multilevel Monte Carlo methods.
Multilevel Modeling with Correlated Effects
ERIC Educational Resources Information Center
Kim, Jee-Seon; Frees, Edward W.
When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…
Scattering in discrete random media with implications to propagation through rain. Ph.D. Thesis George Washingtion Univ., Washington, D.C.
NASA Technical Reports Server (NTRS)
Ippolito, L. J., Jr.
The multiple scattering effects on wave propagation through a volume of discrete scatterers were investigated. The mean field and intensity for a distribution of scatterers was developed using a discrete random media formulation, and second order series expansions for the mean field and total intensity derived for one-dimensional and three-dimensional configurations. The volume distribution results were shown to proceed directly from the one-dimensional results. The multiple scattering intensity expansion was compared to the classical single scattering intensity and the classical result was found to represent only the first three terms in the total intensity expansion. The Foldy approximation to the mean field was applied to develop the coherent intensity, and was found to exactly represent all coherent terms of the total intensity.
Parallel multilevel preconditioners
Bramble, J.H.; Pasciak, J.E.; Xu, Jinchao.
In this paper, we shall report on some techniques for the development of preconditioners for the discrete systems which arise in the approximation of solutions to elliptic boundary value problems. Here we shall only state the resulting theorems. It has been demonstrated that preconditioned iteration techniques often lead to the most computationally effective algorithms for the solution of the large algebraic systems corresponding to boundary value problems in two and three dimensional Euclidean space. The use of preconditioned iteration will become even more important on computers with parallel architecture. This paper discusses an approach for developing completely parallel multilevel preconditioners. In order to illustrate the resulting algorithms, we shall describe the simplest application of the technique to a model elliptic problem.
Improving multilevel Monte Carlo for stochastic differential equations with application to the Langevin equation
Müller, Eike H.; Scheichl, Rob; Shardlow, Tony
This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and especially the Langevin equation. We use modified equations analysis as an alternative to strong-approximation theory for the integrator, and we apply this to introduce MLMC for Langevin-type equations with integrators based on operator splitting. We combine this with extrapolation and investigate the use of discrete random variables in place of the Gaussian increments, which is a well-known technique for the weak approximation of SDEs. We show that, for small-noise problems, discrete random variables can lead to an increase in efficiency of almost two orders of magnitude for practical levels of accuracy.
Family, Community and Clinic Collaboration to Treat Overweight and Obese Children: Stanford GOALS -- a Randomized Controlled Trial of a Three-Year, Multi-Component, Multi-Level, Multi-Setting Intervention
Robinson, Thomas N.; Matheson, Donna; Desai, Manisha; Wilson, Darrell M.; Weintraub, Dana L.; Haskell, William L.; McClain, Arianna; McClure, Samuel; Banda, Jorge; Sanders, Lee M.; Haydel, K. Farish; Killen, Joel D.
Objective To test the effects of a three-year, community-based, multi-component, multi-level, multi-setting (MMM) approach for treating overweight and obese children. Design Two-arm, parallel group, randomized controlled trial with measures at baseline, 12, 24, and 36 months after randomization. Participants Seven through eleven year old, overweight and obese children (BMI ≥ 85th percentile) and their parents/caregivers recruited from community locations in low-income, primarily Latino neighborhoods in Northern California. Interventions Families are randomized to the MMM intervention versus a community health education active-placebo comparison intervention. Interventions last for three years for each participant. The MMM intervention includes a community-based after school team sports program designed specifically for overweight and obese children, a home-based family intervention to reduce screen time, alter the home food/eating environment, and promote self-regulatory skills for eating and activity behavior change, and a primary care behavioral counseling intervention linked to the community and home interventions. The active-placebo comparison intervention includes semi-annual health education home visits, monthly health education newsletters for children and for parents/guardians, and a series of community-based health education events for families. Main Outcome Measure Body mass index trajectory over the three-year study. Secondary outcome measures include waist circumference, triceps skinfold thickness, accelerometer-measured physical activity, 24-hour dietary recalls, screen time and other sedentary behaviors, blood pressure, fasting lipids, glucose, insulin, hemoglobin A1c, C-reactive protein, alanine aminotransferase, and psychosocial measures. Conclusions The Stanford GOALS trial is testing the efficacy of a novel community-based multi-component, multi-level, multi-setting treatment for childhood overweight and obesity in low-income, Latino families
An adaptive multi-level simulation algorithm for stochastic biological systems
NASA Astrophysics Data System (ADS)
Lester, C.; Yates, C. A.; Giles, M. B.; Baker, R. E.
Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, "Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics," SIAM Multiscale Model. Simul. 10(1), 146-179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the
A GPU accelerated, discrete time random walk model for simulating reactive transport in porous media using colocation probability function based reaction methods
NASA Astrophysics Data System (ADS)
Barnard, J. M.; Augarde, C. E.
The simulation of reactions in flow through unsaturated porous media is a more complicated process when using particle tracking based models than in continuum based models. In the fomer particles are reacted on an individual particle-to-particle basis using either deterministic or probabilistic methods. This means that particle tracking methods, especially when simulations of reactions are included, are computationally intensive as the reaction simulations require tens of thousands of nearest neighbour searches per time step. Despite this, particle tracking methods merit further study due to their ability to eliminate numerical dispersion, to simulate anomalous transport and incomplete mixing of reactive solutes. A new model has been developed using discrete time random walk particle tracking methods to simulate reactive mass transport in porous media which includes a variation of colocation probability function based methods of reaction simulation from those presented by Benson & Meerschaert (2008). Model development has also included code acceleration via graphics processing units (GPUs). The nature of particle tracking methods means that they are well suited to parallelization using GPUs. The architecture of GPUs is single instruction - multiple data (SIMD). This means that only one operation can be performed at any one time but can be performed on multiple data simultaneously. This allows for significant speed gains where long loops of independent operations are performed. Computationally expensive code elements, such the nearest neighbour searches required by the reaction simulation, are therefore prime targets for GPU acceleration.
Multilevel and Diverse Classrooms
ERIC Educational Resources Information Center
Baurain, Bradley, Ed.; Ha, Phan Le, Ed.
The benefits and advantages of classroom practices incorporating unity-in-diversity and diversity-in-unity are what "Multilevel and Diverse Classrooms" is all about. Multilevel classrooms--also known as mixed-ability or heterogeneous classrooms--are a fact of life in ESOL programs around the world. These classrooms are often not only multilevel…
Multilevel Mixture Factor Models
ERIC Educational Resources Information Center
Varriale, Roberta; Vermunt, Jeroen K.
Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure. These Multilevel Factor Models (MFMs)…
Mediation from Multilevel to Structural Equation Modeling
MacKinnon, David P.; Valente, Matthew J.
Background/Aims The purpose of this article is to outline multilevel structural equation modeling (MSEM) for mediation analysis of longitudinal data. The introduction of mediating variables can improve experimental and nonexperimental studies of child growth in several ways as discussed throughout this article. Single-mediator individual-level and multilevel mediation models illustrate several current issues in the estimation of mediation with longitudinal data. The strengths of incorporating structural equation modeling (SEM) with multilevel mediation modeling are described. Summary and Key Messages Longitudinal mediation models are pervasive in many areas of research including child growth. Longitudinal mediation models are ideally modeled as repeated measurements clustered within individuals. Further, the combination of MSEM and SEM provides an ideal approach for several reasons, including the ability to assess effects at different levels of analysis, incorporation of measurement error and possible random effects that vary across individuals. PMID:25413658
Multilevel modeling in psychosomatic medicine research.
Myers, Nicholas D; Brincks, Ahnalee M; Ames, Allison J; Prado, Guillermo J; Penedo, Frank J; Benedict, Catherine
The primary purpose of this study is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The article begins with a general introduction to multilevel modeling. Multilevel regression modeling at two levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated data sets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive-behavioral stress management intervention in prostate cancer. PMID:23107843
Multilevel Modeling in Psychosomatic Medicine Research
Myers, Nicholas D.; Brincks, Ahnalee M.; Ames, Allison J.; Prado, Guillermo J.; Penedo, Frank J.; Benedict, Catherine
The primary purpose of this manuscript is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The manuscript begins with a general introduction to multilevel modeling. Multilevel regression modeling at two-levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated datasets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including: communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive behavioral stress management intervention in prostate cancer. PMID:23107843
An adaptive multi-level simulation algorithm for stochastic biological systems
Lester, C. Giles, M. B.; Baker, R. E.; Yates, C. A.
Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, "Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics," SIAM Multiscale Model. Simul. 10(1), 146–179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the
Multilevel filtering elliptic preconditioners
NASA Technical Reports Server (NTRS)
Kuo, C. C. Jay; Chan, Tony F.; Tong, Charles
A class of preconditioners is presented for elliptic problems built on ideas borrowed from the digital filtering theory and implemented on a multilevel grid structure. They are designed to be both rapidly convergent and highly parallelizable. The digital filtering viewpoint allows the use of filter design techniques for constructing elliptic preconditioners and also provides an alternative framework for understanding several other recently proposed multilevel preconditioners. Numerical results are presented to assess the convergence behavior of the new methods and to compare them with other preconditioners of multilevel type, including the usual multigrid method as preconditioner, the hierarchical basis method and a recent method proposed by Bramble-Pasciak-Xu.
Multilevel resistive information storage and retrieval
Lohn, Andrew; Mickel, Patrick R.
The present invention relates to resistive random-access memory (RRAM or ReRAM) systems, as well as methods of employing multiple state variables to form degenerate states in such memory systems. The methods herein allow for precise write and read steps to form multiple state variables, and these steps can be performed electrically. Such an approach allows for multilevel, high density memory systems with enhanced information storage capacity and simplified information retrieval.
Element Agglomeration Algebraic Multilevel Monte-Carlo Library
ElagMC is a parallel C++ library for Multilevel Monte Carlo simulations with algebraically constructed coarse spaces. ElagMC enables Multilevel variance reduction techniques in the context of general unstructured meshes by using the specialized element-based agglomeration techniques implemented in ELAG (the Element-Agglomeration Algebraic Multigrid and Upscaling Library developed by U. Villa and P. Vassilevski and currently under review for public release). The ElabMC library can support different type of deterministic problems, including mixed finite element discretizations of subsurface flow problems.
Methods for testing theory and evaluating impact in randomized field trials
Brown, C. Hendricks; Wang, Wei; Kellam, Sheppard G.; Muthén, Bengt O.; Petras, Hanno; Toyinbo, Peter; Poduska, Jeanne; Ialongo, Nicholas; Wyman, Peter A.; Chamberlain, Patricia; Sloboda, Zili; MacKinnon, David P.; Windham, Amy
Randomized field trials provide unique opportunities to examine the effectiveness of an intervention in real world settings and to test and extend both theory of etiology and theory of intervention. These trials are designed not only to test for overall intervention impact but also to examine how impact varies as a function of individual level characteristics, context, and across time. Examination of such variation in impact requires analytical methods that take into account the trial's multiple nested structure and the evolving changes in outcomes over time. The models that we describe here merge multilevel modeling with growth modeling, allowing for variation in impact to be represented through discrete mixtures—growth mixture models—and nonparametric smooth functions—generalized additive mixed models. These methods are part of an emerging class of multilevel growth mixture models, and we illustrate these with models that examine overall impact and variation in impact. In this paper, we define intent-to-treat analyses in group-randomized multilevel field trials and discuss appropriate ways to identify, examine, and test for variation in impact without inflating the Type I error rate. We describe how to make causal inferences more robust to misspecification of covariates in such analyses and how to summarize and present these interactive intervention effects clearly. Practical strategies for reducing model complexity, checking model fit, and handling missing data are discussed using six randomized field trials to show how these methods may be used across trials randomized at different levels. PMID:18215473
The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models
ERIC Educational Resources Information Center
Schoeneberger, Jason A.
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Asymptotic behavior of joint distributions of characteristics of a pair of randomly chosen individuals in discrete-time Fisher-Wright models with mutations and drift.
Bobrowski, Adam; Kimmel, Marek
This is a continuation of the series of articles (C.R. Rao, D.N. Shanbhag (Eds.), Handbook of Statistics 19: Stochastic Processes: Theory and Methods, Elsevier Science, Amsterdam, 2001 (Chapter 8); Math. Biosci. 175 (2002) 83; Math. Meth. Appl. Sci. 26 (2003) 1587; Adv. Appl. Probab. 36 (2004) 57) devoted to a study of the interplay between two of the main forces of population genetics, mutations and drift, in the Fisher-Wright model. We provide discrete-time versions of theorems describing asymptotic behavior of joint distributions of characteristics of a pair of individuals in this model; their continuous-time counterparts were presented in the previous papers. Furthermore, we show that imbalance index, introduced in Kimmel et al. (Genetics 148 (1998) 1921) and King et al. (Mol. Biol. Evol. 17(12) (2000) 1895) in the context of continuous-time models, may also be used in discrete-time models to detect past population growth. PMID:15560913
NASA Astrophysics Data System (ADS)
Vivaldi, Franco
The concept of resonance has been instrumental to the study of Hamiltonian systems with divided phase space. One can also define such systems over discrete spaces, which have a finite or countable number of points, but in this new setting the notion of resonance must be re-considered from scratch. I review some recent developments in the area of arithmetic dynamics which outline some salient features of linear and nonlinear stable (elliptic) orbits over a discrete space, and also underline the difficulties that emerge in their analysis.
NASA Astrophysics Data System (ADS)
Vivaldi, Franco
The concept of resonance has been instrumental to the study of Hamiltonian systems with divided phase space. One can also define such systems over discrete spaces, which have a finite or countable number of points, but in this new setting the notion of resonance must be re-considered from scratch. I review some recent developments in the area of arithmetic dynamics which outline some salient features of linear and nonlinear stable (elliptic) orbits over a discrete space, and also underline the difficulties that emerge in their analysis.
Multilevel Interventions: Measurement and Measures
Charns, Martin P.; Alligood, Elaine C.; Benzer, Justin K.; Burgess, James F.; Mcintosh, Nathalie M.; Burness, Allison; Partin, Melissa R.; Clauser, Steven B.
Background Multilevel intervention research holds the promise of more accurately representing real-life situations and, thus, with proper research design and measurement approaches, facilitating effective and efficient resolution of health-care system challenges. However, taking a multilevel approach to cancer care interventions creates both measurement challenges and opportunities. Methods One-thousand seventy two cancer care articles from 2005 to 2010 were reviewed to examine the state of measurement in the multilevel intervention cancer care literature. Ultimately, 234 multilevel articles, 40 involving cancer care interventions, were identified. Additionally, literature from health services, social psychology, and organizational behavior was reviewed to identify measures that might be useful in multilevel intervention research. Results The vast majority of measures used in multilevel cancer intervention studies were individual level measures. Group-, organization-, and community-level measures were rarely used. Discussion of the independence, validity, and reliability of measures was scant. Discussion Measurement issues may be especially complex when conducting multilevel intervention research. Measurement considerations that are associated with multilevel intervention research include those related to independence, reliability, validity, sample size, and power. Furthermore, multilevel intervention research requires identification of key constructs and measures by level and consideration of interactions within and across levels. Thus, multilevel intervention research benefits from thoughtful theory-driven planning and design, an interdisciplinary approach, and mixed methods measurement and analysis. PMID:22623598
Recent developments in multilevel optimization
NASA Technical Reports Server (NTRS)
Vanderplaats, Garret N.; Kim, D.-S.
Recent developments in multilevel optimization are briefly reviewed. The general nature of the multilevel design task, the use of approximations to develop and solve the analysis design task, the structure of the formal multidiscipline optimization problem, a simple cantilevered beam which demonstrates the concepts of multilevel design and the basic mathematical details of the optimization task and the system level are among the topics discussed.
Cross-Classification Multilevel Logistic Models in Psychometrics
ERIC Educational Resources Information Center
Van den Noortgate, Wim; De Boeck, Paul; Meulders, Michel
In IRT models, responses are explained on the basis of person and item effects. Person effects are usually defined as a random sample from a population distribution. Regular IRT models therefore can be formulated as multilevel models, including a within-person part and a between-person part. In a similar way, the effects of the items can be…
Multilevel Methods for the Poisson-Boltzmann Equation
NASA Astrophysics Data System (ADS)
Holst, Michael Jay
We consider the numerical solution of the Poisson -Boltzmann equation (PBE), a three-dimensional second order nonlinear elliptic partial differential equation arising in biophysics. This problem has several interesting features impacting numerical algorithms, including discontinuous coefficients representing material interfaces, rapid nonlinearities, and three spatial dimensions. Similar equations occur in various applications, including nuclear physics, semiconductor physics, population genetics, astrophysics, and combustion. In this thesis, we study the PBE, discretizations, and develop multilevel-based methods for approximating the solutions of these types of equations. We first outline the physical model and derive the PBE, which describes the electrostatic potential of a large complex biomolecule lying in a solvent. We next study the theoretical properties of the linearized and nonlinear PBE using standard function space methods; since this equation has not been previously studied theoretically, we provide existence and uniqueness proofs in both the linearized and nonlinear cases. We also analyze box-method discretizations of the PBE, establishing several properties of the discrete equations which are produced. In particular, we show that the discrete nonlinear problem is well-posed. We study and develop linear multilevel methods for interface problems, based on algebraic enforcement of Galerkin or variational conditions, and on coefficient averaging procedures. Using a stencil calculus, we show that in certain simplified cases the two approaches are equivalent, with different averaging procedures corresponding to different prolongation operators. We also develop methods for nonlinear problems based on a nonlinear multilevel method, and on linear multilevel methods combined with a globally convergent damped-inexact-Newton method. We derive a necessary and sufficient descent condition for the inexact-Newton direction, enabling the development of extremely
Multilevel structural equation models for assessing moderation within and across levels of analysis.
Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J
Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record PMID:26651982
Muir, William M; Bijma, P; Schinckel, A
An experiment was conducted comparing multilevel selection in Japanese quail for 43 days weight and survival with birds housed in either kin (K) or random (R) groups. Multilevel selection significantly reduced mortality (6.6% K vs. 8.5% R) and increased weight (1.30 g/MG K vs. 0.13 g/MG R) resulting in response an order of magnitude greater with Kin than Random. Thus, multilevel selection was effective in reducing detrimental social interactions, which contributed to improved weight gain. The observed rates of response did not differ significantly from expected, demonstrating that current theory is adequate to explain multilevel selection response. Based on estimated genetic parameters, group selection would always be superior to any other combination of multilevel selection. Further, near optimal results could be attained using multilevel selection if 20% of the weight was on the group component regardless of group composition. Thus, in nature the conditions for multilevel selection to be effective in bringing about social change maybe common. In terms of a sustainability of breeding programs, multilevel selection is easy to implement and is expected to give near optimal responses with reduced rates of inbreeding as compared to group selection, the only requirement is that animals be housed in kin groups. PMID:23730755
A Primer on Multilevel Modeling
ERIC Educational Resources Information Center
Hayes, Andrew F.
Multilevel modeling (MLM) is growing in use throughout the social sciences. Although daunting from a mathematical perspective, MLM is relatively easy to employ once some basic concepts are understood. In this article, I present a primer on MLM, describing some of these principles and applying them to the analysis of a multilevel data set on…
Multilevel Modeling of Social Segregation
ERIC Educational Resources Information Center
Leckie, George; Pillinger, Rebecca; Jones, Kelvyn; Goldstein, Harvey
The traditional approach to measuring segregation is based upon descriptive, non-model-based indices. A recently proposed alternative is multilevel modeling. The authors further develop the argument for a multilevel modeling approach by first describing and expanding upon its notable advantages, which include an ability to model segregation at a…
NASA Astrophysics Data System (ADS)
Wuensche, Andrew
DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.
A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks.
Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias
We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest. PMID:18624656
Methods for testing theory and evaluating impact in randomized field trials: intent-to-treat analyses for integrating the perspectives of person, place, and time.
Brown, C Hendricks; Wang, Wei; Kellam, Sheppard G; Muthén, Bengt O; Petras, Hanno; Toyinbo, Peter; Poduska, Jeanne; Ialongo, Nicholas; Wyman, Peter A; Chamberlain, Patricia; Sloboda, Zili; MacKinnon, David P; Windham, Amy
Randomized field trials provide unique opportunities to examine the effectiveness of an intervention in real world settings and to test and extend both theory of etiology and theory of intervention. These trials are designed not only to test for overall intervention impact but also to examine how impact varies as a function of individual level characteristics, context, and across time. Examination of such variation in impact requires analytical methods that take into account the trial's multiple nested structure and the evolving changes in outcomes over time. The models that we describe here merge multilevel modeling with growth modeling, allowing for variation in impact to be represented through discrete mixtures--growth mixture models--and nonparametric smooth functions--generalized additive mixed models. These methods are part of an emerging class of multilevel growth mixture models, and we illustrate these with models that examine overall impact and variation in impact. In this paper, we define intent-to-treat analyses in group-randomized multilevel field trials and discuss appropriate ways to identify, examine, and test for variation in impact without inflating the Type I error rate. We describe how to make causal inferences more robust to misspecification of covariates in such analyses and how to summarize and present these interactive intervention effects clearly. Practical strategies for reducing model complexity, checking model fit, and handling missing data are discussed using six randomized field trials to show how these methods may be used across trials randomized at different levels. PMID:18215473
Discrete Fractional Diffusion Equation of Chaotic Order
NASA Astrophysics Data System (ADS)
Wu, Guo-Cheng; Baleanu, Dumitru; Xie, He-Ping; Zeng, Sheng-Da
Discrete fractional calculus is suggested in diffusion modeling in porous media. A variable-order fractional diffusion equation is proposed on discrete time scales. A function of the variable order is constructed by a chaotic map. The model shows some new random behaviors in comparison with other variable-order cases.
Multi-level adaptive finite element methods. 1: Variation problems
NASA Technical Reports Server (NTRS)
Brandt, A.
A general numerical strategy for solving partial differential equations and other functional problems by cycling between coarser and finer levels of discretization is described. Optimal discretization schemes are provided together with very fast general solvers. It is described in terms of finite element discretizations of general nonlinear minimization problems. The basic processes (relaxation sweeps, fine-grid-to-coarse-grid transfers of residuals, coarse-to-fine interpolations of corrections) are directly and naturally determined by the objective functional and the sequence of approximation spaces. The natural processes, however, are not always optimal. Concrete examples are given and some new techniques are reviewed. Including the local truncation extrapolation and a multilevel procedure for inexpensively solving chains of many boundary value problems, such as those arising in the solution of time-dependent problems.
Su, Gui-Jia
A multilevel DC link inverter and method for improving torque response and current regulation in permanent magnet motors and switched reluctance motors having a low inductance includes a plurality of voltage controlled cells connected in series for applying a resulting dc voltage comprised of one or more incremental dc voltages. The cells are provided with switches for increasing the resulting applied dc voltage as speed and back EMF increase, while limiting the voltage that is applied to the commutation switches to perform PWM or dc voltage stepping functions, so as to limit current ripple in the stator windings below an acceptable level, typically 5%. Several embodiments are disclosed including inverters using IGBT's, inverters using thyristors. All of the inverters are operable in both motoring and regenerating modes.
A fractional-factorial probabilistic-possibilistic optimization framework for planning water resources management systems with multi-level parametric interactions.
Wang, S; Huang, G H; Zhou, Y
In this study, a multi-level factorial-vertex fuzzy-stochastic programming (MFFP) approach is developed for optimization of water resources systems under probabilistic and possibilistic uncertainties. MFFP is capable of tackling fuzzy parameters at various combinations of α-cut levels, reflecting distinct attitudes of decision makers towards fuzzy parameters in the fuzzy discretization process based on the α-cut concept. The potential interactions among fuzzy parameters can be explored through a multi-level factorial analysis. A water resources management problem with fuzzy and random features is used to demonstrate the applicability of the proposed methodology. The results indicate that useful solutions can be obtained for the optimal allocation of water resources under fuzziness and randomness. They can help decision makers to identify desired water allocation schemes with maximized total net benefits. A variety of decision alternatives can also be generated under different scenarios of water management policies. The findings from the factorial experiment reveal the interactions among design factors (fuzzy parameters) and their curvature effects on the total net benefit, which are helpful in uncovering the valuable information hidden beneath the parameter interactions affecting system performance. A comparison between MFFP and the vertex method is also conducted to demonstrate the merits of the proposed methodology. PMID:26922500
Multilevel techniques for nonelliptic problems
NASA Technical Reports Server (NTRS)
Jespersen, D. C.
Multigrid and multilevel methods are extended to the solution of nonelliptic problems. A framework for analyzing these methods is established. A simple nonelliptic problem is given, and it is shown how a multilevel technique can be used for its solution. Emphasis is on smoothness properties of eigenvectors and attention is drawn to the possibility of conditioning the eigensystem so that eigenvectors have the desired smoothness properties.
Multilevel multiple imputation: A review and evaluation of joint modeling and chained equations imputation.
Enders, Craig K; Mistler, Stephen A; Keller, Brian T
Although missing data methods have advanced in recent years, methodologists have devoted less attention to multilevel data structures where observations at level-1 are nested within higher-order organizational units at level-2 (e.g., individuals within neighborhoods; repeated measures nested within individuals; students nested within classrooms). Joint modeling and chained equations imputation are the principal imputation frameworks for single-level data, and both have multilevel counterparts. These approaches differ algorithmically and in their functionality; both are appropriate for simple random intercept analyses with normally distributed data, but they differ beyond that. The purpose of this paper is to describe multilevel imputation strategies and evaluate their performance in a variety of common analysis models. Using multiple imputation theory and computer simulations, we derive 4 major conclusions: (a) joint modeling and chained equations imputation are appropriate for random intercept analyses; (b) the joint model is superior for analyses that posit different within- and between-cluster associations (e.g., a multilevel regression model that includes a level-1 predictor and its cluster means, a multilevel structural equation model with different path values at level-1 and level-2); (c) chained equations imputation provides a dramatic improvement over joint modeling in random slope analyses; and (d) a latent variable formulation for categorical variables is quite effective. We use a real data analysis to demonstrate multilevel imputation, and we suggest a number of avenues for future research. (PsycINFO Database Record PMID:26690775
Multilevel fusion exploitation
NASA Astrophysics Data System (ADS)
Lindberg, Perry C.; Dasarathy, Belur V.; McCullough, Claire L.
This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Command (USASSDC) to develop, test, and demonstrate sensor fusion algorithms for target recognition. The purpose of the project was to exploit the use of sensor fusion at all levels (signal, feature, and decision levels) and all combinations to improve target recognition capability against tactical ballistic missile (TBM) targets. These algorithms were trained with simulated radar signatures to accurately recognize selected TBM targets. The simulated signatures represent measurements made by two radars (S-band and X- band) with the targets at a variety of aspect and roll angles. Two tests were conducted: one with simulated signatures collected at angles different from those in the training database and one using actual test data. The test results demonstrate a high degree of recognition accuracy. This paper describes the training and testing techniques used; shows the fusion strategy employed; and illustrates the advantages of exploiting multi-level fusion.
Multilevel turbulence simulations
Tziperman, E.
The authors propose a novel method for the simulation of turbulent flows, that is motivated by and based on the Multigrid (MG) formalism. The method, called Multilevel Turbulence Simulations (MTS), is potentially more efficient and more accurate than LES. In many physical problems one is interested in the effects of the small scales on the larger ones, or in a typical realization of the flow, and not in the detailed time history of each small scale feature. MTS takes advantage of the fact that the detailed simulation of small scales is not needed at all times, in order to make the calculation significantly more efficient, while accurately accounting for the effects of the small scales on the larger scale of interest. In MTS, models of several resolutions are used to represent the turbulent flow. The model equations in each coarse level incorporate a closure term roughly corresponding to the tau correction in the MG formalism that accounts for the effects of the unresolvable scales on that grid. The finer resolution grids are used only a small portion of the simulation time in order to evaluate the closure terms for the coarser grids, while the coarse resolution grids are then used to accurately and efficiently calculate the evolution of the larger scales. The methods efficiency relative to direct simulations is of the order of the ratio of required integration time to the smallest eddies turnover time, potentially resulting in orders of magnitude improvement for a large class of turbulence problems.
Multilevel analysis in road safety research.
Dupont, Emmanuelle; Papadimitriou, Eleonora; Martensen, Heike; Yannis, George
Hierarchical structures in road safety data are receiving increasing attention in the literature and multilevel (ML) models are proposed for appropriately handling the resulting dependences among the observations. However, so far no empirical synthesis exists of the actual added value of ML modelling techniques as compared to other modelling approaches. This paper summarizes the statistical and conceptual background and motivations for multilevel analyses in road safety research. It then provides a review of several ML analyses applied to aggregate and disaggregate (accident) data. In each case, the relevance of ML modelling techniques is assessed by examining whether ML model formulations (i) allow improving the fit of the model to the data, (ii) allow identifying and explaining random variation at specific levels of the hierarchy considered, and (iii) yield different (more correct) conclusions than single-level model formulations with respect to the significance of the parameter estimates. The evidence reviewed offers different conclusions depending on whether the analysis concerns aggregate data or disaggregate data. In the first case, the application of ML analysis techniques appears straightforward and relevant. The studies based on disaggregate accident data, on the other hand, offer mixed findings: computational problems can be encountered, and ML applications are not systematically necessary. The general recommendation concerning disaggregate accident data is to proceed to a preliminary investigation of the necessity of ML analyses and of the additional information to be expected from their application. PMID:23769622
A New Approach for Estimating a Nonlinear Growth Component in Multilevel Modeling
ERIC Educational Resources Information Center
Tolvanen, Asko; Kiuru, Noona; Leskinen, Esko; Hakkarainen, Kai; Inkinen, Mikko; Lonka, Kirsti; Salmela-Aro, Katariina
This study presents a new approach to estimation of a nonlinear growth curve component with fixed and random effects in multilevel modeling. This approach can be used to estimate change in longitudinal data, such as day-of-the-week fluctuation. The motivation of the new approach is to avoid spurious estimates in a random coefficient regression…
Multilevel Green's function interpolation method for scattering from composite metallic and dielectric objects.
Shi, Yan; Wang, Hao Gang; Li, Long; Chan, Chi Hou
A multilevel Green's function interpolation method based on two kinds of multilevel partitioning schemes--the quasi-2D and the hybrid partitioning scheme--is proposed for analyzing electromagnetic scattering from objects comprising both conducting and dielectric parts. The problem is formulated using the surface integral equation for homogeneous dielectric and conducting bodies. A quasi-2D multilevel partitioning scheme is devised to improve the efficiency of the Green's function interpolation. In contrast to previous multilevel partitioning schemes, noncubic groups are introduced to discretize the whole EM structure in this quasi-2D multilevel partitioning scheme. Based on the detailed analysis of the dimension of the group in this partitioning scheme, a hybrid quasi-2D/3D multilevel partitioning scheme is proposed to effectively handle objects with fine local structures. Selection criteria for some key parameters relating to the interpolation technique are given. The proposed algorithm is ideal for the solution of problems involving objects such as missiles, microstrip antenna arrays, photonic bandgap structures, etc. Numerical examples are presented to show that CPU time is between O(N) and O(N log N) while the computer memory requirement is O(N). PMID:18830332
ERIC Educational Resources Information Center
Ghezzi, Patrick M.
The advantages of emphasizing discrete trials "teaching" over discrete trials "training" are presented first, followed by a discussion of discrete trials as a method of teaching that emerged historically--and as a matter of necessity for difficult learners such as those with autism--from discrete trials as a method for laboratory research. The…
Multilevel solvers of first-order system least-squares for Stokes equations
Lai, Chen-Yao G.
Recently, The use of first-order system least squares principle for the approximate solution of Stokes problems has been extensively studied by Cai, Manteuffel, and McCormick. In this paper, we study multilevel solvers of first-order system least-squares method for the generalized Stokes equations based on the velocity-vorticity-pressure formulation in three dimensions. The least-squares functionals is defined to be the sum of the L{sup 2}-norms of the residuals, which is weighted appropriately by the Reynolds number. We develop convergence analysis for additive and multiplicative multilevel methods applied to the resulting discrete equations.
Multilevel codes and multistage decoding
NASA Astrophysics Data System (ADS)
Calderbank, A. R.
Imai and Hirakawa have proposed (1977) a multilevel coding method based on binary block codes that admits a staged decoding procedure. Here the coding method is extended to coset codes and it is shown how to calculate minimum squared distance and path multiplicity in terms of the norms and multiplicities of the different cosets. The multilevel structure allows the redundancy in the coset selection procedure to be allocated efficiently among the different levels. It also allows the use of suboptimal multistage decoding procedures that have performance/complexity advantages over maximum-likelihood decoding.
Multilevel Ensemble Transform Particle Filtering
NASA Astrophysics Data System (ADS)
Gregory, Alastair; Cotter, Colin; Reich, Sebastian
This presentation extends the Multilevel Monte Carlo variance reduction technique to nonlinear filtering. In particular, Multilevel Monte Carlo is applied to a certain variant of the particle filter, the Ensemble Transform Particle Filter (ETPF). A key aspect is the use of optimal transport methods to re-establish correlation between coarse and fine ensembles after resampling; this controls the variance of the estimator. Numerical examples present a proof of concept of the effectiveness of the proposed method, demonstrating significant computational cost reductions (relative to the single-level ETPF counterpart) in the propagation of ensembles.
A General Multilevel SEM Framework for Assessing Multilevel Mediation
ERIC Educational Resources Information Center
Preacher, Kristopher J.; Zyphur, Michael J.; Zhang, Zhen
Several methods for testing mediation hypotheses with 2-level nested data have been proposed by researchers using a multilevel modeling (MLM) paradigm. However, these MLM approaches do not accommodate mediation pathways with Level-2 outcomes and may produce conflated estimates of between- and within-level components of indirect effects. Moreover,…
Multi-level methods and approximating distribution functions
NASA Astrophysics Data System (ADS)
Wilson, D.; Baker, R. E.
Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie's direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie's direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146-179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.
Comparing Spatial and Multilevel Regression Models for Binary Outcomes in Neighborhood Studies
Xu, Hongwei
The standard multilevel regressions that are widely used in neighborhood research typically ignore potential between-neighborhood correlations due to underlying spatial processes, and hence produce inappropriate inferences about neighborhood effects. In contrast, spatial models make estimations and predictions across areas by explicitly modeling the spatial correlations among observations in different locations. A better understanding of the strengths and limitations of spatial models as compared to the standard multilevel model is needed to improve the research on neighborhood and spatial effects. This research systematically compares model estimations and predictions for binary outcomes between (distance- and lattice-based) spatial and the standard multilevel models in the presence of both within- and between-neighborhood correlations, through simulations. Results from simulation analysis reveal that the standard multilevel and spatial models produce similar estimates of fixed effects, but different estimates of random effects variances. Both the standard multilevel and pure spatial models tend to overestimate the corresponding random effects variances, compared to hybrid models when both non-spatial within neighborhood and spatial between-neighborhood effects exist. Spatial models also outperform the standard multilevel model by a narrow margin in case of fully out-of-sample predictions. Distance-based spatial models provide extra spatial information and have stronger predictive power than lattice-based models under certain circumstances. These merits of spatial modeling are exhibited in an empirical analysis of the child mortality data from 1880 Newark, New Jersey. PMID:25284905
Three-dimensional discrete ordinates reactor assembly calculations on GPUs
Evans, Thomas M; Joubert, Wayne; Hamilton, Steven P; Johnson, Seth R; Turner, John A; Davidson, Gregory G; Pandya, Tara M
In this paper we describe and demonstrate a discrete ordinates sweep algorithm on GPUs. This sweep algorithm is nested within a multilevel comunication-based decomposition based on energy. We demonstrated the effectiveness of this algorithm on detailed three-dimensional critical experiments and PWR lattice problems. For these problems we show improvement factors of 4 6 over conventional communication-based, CPU-only sweeps. These sweep kernel speedups resulted in a factor of 2 total time-to-solution improvement.
Multilevel algorithms for nonlinear optimization
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia; Dennis, J. E., Jr.
Multidisciplinary design optimization (MDO) gives rise to nonlinear optimization problems characterized by a large number of constraints that naturally occur in blocks. We propose a class of multilevel optimization methods motivated by the structure and number of constraints and by the expense of the derivative computations for MDO. The algorithms are an extension to the nonlinear programming problem of the successful class of local Brown-Brent algorithms for nonlinear equations. Our extensions allow the user to partition constraints into arbitrary blocks to fit the application, and they separately process each block and the objective function, restricted to certain subspaces. The methods use trust regions as a globalization strategy, and they have been shown to be globally convergent under reasonable assumptions. The multilevel algorithms can be applied to all classes of MDO formulations. Multilevel algorithms for solving nonlinear systems of equations are a special case of the multilevel optimization methods. In this case, they can be viewed as a trust-region globalization of the Brown-Brent class.
Generalized Multilevel Structural Equation Modeling
ERIC Educational Resources Information Center
Rabe-Hesketh, Sophia; Skrondal, Anders; Pickles, Andrew
A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent…
Simulations Of Nanomagnet Clusters With Perpendicular Uniaxial Anisotropy For Multilevel Data Storage
NASA Astrophysics Data System (ADS)
Xiao, Qijun; Krotkov, Robert; Tuominen, Mark
Digital data storage technology generally relies on a binary storage paradigm. In this work we explore a different scheme that exploits the stepwise, multilevel total magnetization of a small cluster of interacting nanomagnets. The magnetization of a cluster can be resolved more easily than that of a single nanomagnet, due to the larger lateral size. Micromagnetic simulations, based on the Landau-Lifshitz-Gilbert (LLG) equation with parameters representative of Co3Pt, reveal that magnetostatic interactions within a cluster produce a rich multilevel magnetic response, each level providing a stable remanent magnetization state. This work describes simulations used to investigate a multilevel data storage unit based on a hexagonal cluster of interacting uniaxial single domain nanomagnets. The accessibility and stability of the discrete magnetization states are studied. The switching properties of the nanomagnet clusters can be tuned by modifying the geometry, providing the ability to engineer desirable magnetic properties.
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε–2) or (ε–2(lnε)2), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε–3) for direct simulation Monte Carlo or binary collision methods.more » We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10–5. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.« less
Multilevel Monte Carlo simulation of Coulomb collisions
Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε–2) or (ε–2(lnε)2), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε–3) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10–5. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.
Tree Ensembles on the Induced Discrete Space.
Yildiz, Olcay Taner
Decision trees are widely used predictive models in machine learning. Recently, K -tree is proposed, where the original discrete feature space is expanded by generating all orderings of values of k discrete attributes and these orderings are used as the new attributes in decision tree induction. Although K -tree performs significantly better than the proper one, their exponential time complexity can prohibit their use. In this brief, we propose K -forest, an extension of random forest, where a subset of features is selected randomly from the induced discrete space. Simulation results on 17 data sets show that the novel ensemble classifier has significantly lower error rate compared with the random forest based on the original feature space. PMID:26011897
Efficacy of a Multi-level Intervention to Reduce Injecting and Sexual Risk Behaviors among HIV-Infected People Who Inject Drugs in Vietnam: A Four-Arm Randomized Controlled Trial
Go, Vivian F.; Frangakis, Constantine; Minh, Nguyen Le; Latkin, Carl; Ha, Tran Viet; Mo, Tran Thi; Sripaipan, Teerada; Davis, Wendy W.; Zelaya, Carla; Vu, Pham The; Celentano, David D.; Quan, Vu Minh
Introduction Injecting drug use is a primary driver of HIV epidemics in many countries. People who inject drugs (PWID) and are HIV infected are often doubly stigmatized and many encounter difficulties reducing risk behaviors. Prevention interventions for HIV-infected PWID that provide enhanced support at the individual, family, and community level to facilitate risk-reduction are needed. Methods 455 HIV-infected PWID and 355 of their HIV negative injecting network members living in 32 sub-districts in Thai Nguyen Province were enrolled. We conducted a two-stage randomization: First, sub-districts were randomized to either a community video screening and house-to-house visits or standard of care educational pamphlets. Second, within each sub-district, participants were randomized to receive either enhanced individual level post-test counseling and group support sessions or standard of care HIV testing and counseling. This resulted in four arms: 1) standard of care; 2) community level intervention; 3) individual level intervention; and 4) community plus individual intervention. Follow-up was conducted at 6, 12, 18, and 24 months. Primary outcomes were self-reported HIV injecting and sexual risk behaviors. Secondary outcomes included HIV incidence among HIV negative network members. Results Fewer participants reported sharing injecting equipment and unprotected sex from baseline to 24 months in all arms (77% to 4% and 24% to 5% respectively). There were no significant differences at the 24-month visit among the 4 arms (Wald = 3.40 (3 df); p = 0.33; Wald = 6.73 (3 df); p = 0.08). There were a total of 4 HIV seroconversions over 24 months with no significant difference between intervention and control arms. Discussion Understanding the mechanisms through which all arms, particularly the control arm, demonstrated both low risk behaviors and low HIV incidence has important implications for policy and prevention programming. Trial Registration ClinicalTrials.gov NCT
Modeling Repeatable Events Using Discrete-Time Data: Predicting Marital Dissolution
ERIC Educational Resources Information Center
Teachman, Jay
I join two methodologies by illustrating the application of multilevel modeling principles to hazard-rate models with an emphasis on procedures for discrete-time data that contain repeatable events. I demonstrate this application using data taken from the 1995 National Survey of Family Growth (NSFG) to ascertain the relationship between multiple…
Discreteness inducing coexistence
NASA Astrophysics Data System (ADS)
dos Santos, Renato Vieira
Consider two species that diffuse through space. Consider further that they differ only in initial densities and, possibly, in diffusion constants. Otherwise they are identical. What happens if they compete with each other in the same environment? What is the influence of the discrete nature of the interactions on the final destination? And what are the influence of diffusion and additive fluctuations corresponding to random migration and immigration of individuals? This paper aims to answer these questions for a particular competition model that incorporates intra and interspecific competition between the species. Based on mean field theory, the model has a stationary state dependent on the initial density conditions. We investigate how this initial density dependence is affected by the presence of demographic multiplicative noise and additive noise in space and time. There are three main conclusions: (1) Additive noise favors denser populations at the expense of the less dense, ratifying the competitive exclusion principle. (2) Demographic noise, on the other hand, favors less dense populations at the expense of the denser ones, inducing equal densities at the quasi-stationary state, violating the aforementioned principle. (3) The slower species always suffers the more deleterious effects of statistical fluctuations in a homogeneous medium.
Multi-Level Adaptive Techniques (MLAT) for singular-perturbation problems
NASA Technical Reports Server (NTRS)
Brandt, A.
The multilevel (multigrid) adaptive technique, a general strategy of solving continuous problems by cycling between coarser and finer levels of discretization is described. It provides very fast general solvers, together with adaptive, nearly optimal discretization schemes. In the process, boundary layers are automatically either resolved or skipped, depending on a control function which expresses the computational goal. The global error decreases exponentially as a function of the overall computational work, in a uniform rate independent of the magnitude of the singular-perturbation terms. The key is high-order uniformly stable difference equations, and uniformly smoothing relaxation schemes.
Principles of Discrete Time Mechanics
NASA Astrophysics Data System (ADS)
Jaroszkiewicz, George
1. Introduction; 2. The physics of discreteness; 3. The road to calculus; 4. Temporal discretization; 5. Discrete time dynamics architecture; 6. Some models; 7. Classical cellular automata; 8. The action sum; 9. Worked examples; 10. Lee's approach to discrete time mechanics; 11. Elliptic billiards; 12. The construction of system functions; 13. The classical discrete time oscillator; 14. Type 2 temporal discretization; 15. Intermission; 16. Discrete time quantum mechanics; 17. The quantized discrete time oscillator; 18. Path integrals; 19. Quantum encoding; 20. Discrete time classical field equations; 21. The discrete time Schrodinger equation; 22. The discrete time Klein-Gordon equation; 23. The discrete time Dirac equation; 24. Discrete time Maxwell's equations; 25. The discrete time Skyrme model; 26. Discrete time quantum field theory; 27. Interacting discrete time scalar fields; 28. Space, time and gravitation; 29. Causality and observation; 30. Concluding remarks; Appendix A. Coherent states; Appendix B. The time-dependent oscillator; Appendix C. Quaternions; Appendix D. Quantum registers; References; Index.
Single Versus Multilevel Fusion, For Single Level Degenerative Spondylolisthesis And Multilevel Lumbar Stenosis. Four-Year Results of the Spine Patient Outcomes Research Trial
Smorgick, Yossi; Park, Daniel K.; Baker, Kevin C; Lurie, Jon D.; Tosteson, Tor D.; Zhao, Wenyan; Herkowitz, Harry; Fischgrund, Jeffrey S; Weinstein, James N.
Study design A subanalysis study. Objective To compare surgical outcomes and complications of multi level decompression and single level fusion to multi level decompression and multi level fusion for patients with multilevel lumbar stenosis and single level degenerative spondylolisthesis. Summary of Background Data In patients with degenerative spondylolisthesis who are treated surgically, decompression and fusion provides a better clinical outcome than decompression alone. Surgical treatment for multilevel lumbar stenosis and degenerative spondylolisthesis typically includes decompression and fusion of the spondylolisthesis segment and decompression with or without fusion for the other stenotic segments. To date, no study has compared the results of these two surgical options for single level degenerative spondylolisthesis with multilevel stenosis. Methods The results from a multicenter randomized and observational study, the Spine Patient Outcomes Research Trial (SPORT) comparing multilevel decompression and single level fusion and multi level decompression and multi level fusion for spinal stenosis with spondylolisthesis, were analyzed. The primary outcomes measures were the Bodily Pain and Physical Function scales of the Medical Outcomes Study 36-item Short-Form General Health Survey (SF-36) and the modified Oswestry Disability Index at 1,2, 3 and 4 years postoperatively. Secondary analysis consisted of stenosis bothersomeness index, low back pain bothersomeness, leg pain, patient satisfaction, and self-rated progress. Results Overall 207 patients were enrolled to the study, 130 had multlilevel decompression with one level fusion and 77 patients had multi level decompression and multi-level fusion. For all primary and secondary outcome measures, there were no statistically significant differences in surgical outcomes between the two surgical techniques. However, operative time and intraoperative blood loss were significantly higher in the multilevel fusion
"Using Power Tables to Compute Statistical Power in Multilevel Experimental Designs"
ERIC Educational Resources Information Center
Konstantopoulos, Spyros
Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…
A Multilevel Investigation of Relationships between Australian Teachers' Career Stages and Locus of Control
ERIC Educational Resources Information Center
McCormick, John; Barnett, Kerry
Purpose: The purpose of this paper was to posit and test hypotheses concerned with relationships between teachers' demographics, locus of control and career stages. Design/methodology/approach: A sample consisting of 416 Australian non-executive high school teachers was gathered from 40 randomly selected high schools. Multilevel regression…
Within-Cluster and Across-Cluster Matching with Observational Multilevel Data
ERIC Educational Resources Information Center
Kim, Jee-Seon; Steiner, Peter M.; Hall, Courtney; Thoemmes, Felix
When randomized experiments cannot be conducted in practice, propensity score (PS) techniques for matching treated and control units are frequently used for estimating causal treatment effects from observational data. Despite the popularity of PS techniques, they are not yet well studied for matching multilevel data where selection into treatment…
A cell-local finite difference discretization of the low-order quasidiffusion equations for neutral particle transport on unstructured quadrilateral meshes
Wieselquist, William A.; Anistratov, Dmitriy Y.; Morel, Jim E.
We present a quasidiffusion (QD) method for solving neutral particle transport problems in Cartesian XY geometry on unstructured quadrilateral meshes, including local refinement capability. Neutral particle transport problems are central to many applications including nuclear reactor design, radiation safety, astrophysics, medical imaging, radiotherapy, nuclear fuel transport/storage, shielding design, and oil well-logging. The primary development is a new discretization of the low-order QD (LOQD) equations based on cell-local finite differences. The accuracy of the LOQD equations depends on proper calculation of special non-linear QD (Eddington) factors from a transport solution. In order to completely define the new QD method, a proper discretization of the transport problem is also presented. The transport equation is discretized by a conservative method of short characteristics with a novel linear approximation of the scattering source term and monotonic, parabolic representation of the angular flux on incoming faces. Analytic and numerical tests are used to test the accuracy and spatial convergence of the non-linear method. All tests exhibit O(h{sup 2}) convergence of the scalar flux on orthogonal, random, and multi-level meshes.
Electrolytic plating apparatus for discrete microsized particles
Mayer, Anton
Method and apparatus are disclosed for electrolytically producing very uniform coatings of a desired material on discrete microsized particles. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with a powered cathode for a time sufficient for such to occur.
Electroless plating apparatus for discrete microsized particles
Mayer, Anton
Method and apparatus are disclosed for producing very uniform coatings of a desired material on discrete microsized particles by electroless techniques. Agglomeration or bridging of the particles during the deposition process is prevented by imparting a sufficiently random motion to the particles that they are not in contact with each other for a time sufficient for such to occur.
Bayesian approach to global discrete optimization
Mockus, J.; Mockus, A.; Mockus, L.
We discuss advantages and disadvantages of the Bayesian approach (average case analysis). We present the portable interactive version of software for continuous global optimization. We consider practical multidimensional problems of continuous global optimization, such as optimization of VLSI yield, optimization of composite laminates, estimation of unknown parameters of bilinear time series. We extend Bayesian approach to discrete optimization. We regard the discrete optimization as a multi-stage decision problem. We assume that there exists some simple heuristic function which roughly predicts the consequences of the decisions. We suppose randomized decisions. We define the probability of the decision by the randomized decision function depending on heuristics. We fix this function with exception of some parameters. We repeat the randomized decision several times at the fixed values of those parameters and accept the best decision as the result. We optimize the parameters of the randomized decision function to make the search more efficient. Thus we reduce the discrete optimization problem to the continuous problem of global stochastic optimization. We solve this problem by the Bayesian methods of continuous global optimization. We describe the applications to some well known An problems of discrete programming, such as knapsack, traveling salesman, and scheduling.
Conducting Multilevel Analyses in Medical Education
ERIC Educational Resources Information Center
Zyphur, Michael J.; Kaplan, Seth A.; Islam, Gazi; Barsky, Adam P.; Franklin, Michael S.
A significant body of education literature has begun using multilevel statistical models to examine data that reside at multiple levels of analysis. In order to provide a primer for medical education researchers, the current work gives a brief overview of some issues associated with multilevel statistical modeling. To provide an example of this…
A Multilevel Assessment of Differential Item Functioning.
ERIC Educational Resources Information Center
Shen, Linjun
A multilevel approach was proposed for the assessment of differential item functioning and compared with the traditional logistic regression approach. Data from the Comprehensive Osteopathic Medical Licensing Examination for 2,300 freshman osteopathic medical students were analyzed. The multilevel approach used three-level hierarchical generalized…
Multilevel Interventions: Study Design and Analysis Issues
Gross, Cary P.; Zaslavsky, Alan M.; Taplin, Stephen H.
Multilevel interventions, implemented at the individual, physician, clinic, health-care organization, and/or community level, increasingly are proposed and used in the belief that they will lead to more substantial and sustained changes in behaviors related to cancer prevention, detection, and treatment than would single-level interventions. It is important to understand how intervention components are related to patient outcomes and identify barriers to implementation. Designs that permit such assessments are uncommon, however. Thus, an important way of expanding our knowledge about multilevel interventions would be to assess the impact of interventions at different levels on patients as well as the independent and synergistic effects of influences from different levels. It also would be useful to assess the impact of interventions on outcomes at different levels. Multilevel interventions are much more expensive and complicated to implement and evaluate than are single-level interventions. Given how little evidence there is about the value of multilevel interventions, however, it is incumbent upon those arguing for this approach to do multilevel research that explicates the contributions that interventions at different levels make to the desired outcomes. Only then will we know whether multilevel interventions are better than more focused interventions and gain greater insights into the kinds of interventions that can be implemented effectively and efficiently to improve health and health care for individuals with cancer. This chapter reviews designs for assessing multilevel interventions and analytic ways of controlling for potentially confounding variables that can account for the complex structure of multilevel data. PMID:22623596
Structural optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, J.; James, B.; Dovi, A.
A method is described for decomposing an optimization problem into a set of subproblems and a coordination problem which preserves coupling between the subproblems. The method is introduced as a special case of multilevel, multidisciplinary system optimization and its algorithm is fully described for two level optimization for structures assembled of finite elements of arbitrary type. Numerical results are given for an example of a framework to show that the decomposition method converges and yields results comparable to those obtained without decomposition. It is pointed out that optimization by decomposition should reduce the design time by allowing groups of engineers, using different computers to work concurrently on the same large problem.
On the relation between traditional iterative methods and modern multilevel/domain decomposition methods
Griebel, M.
In recent years, it has turned out that many modern iterative algorithms (multigrid schemes, multilevel preconditioners, domain decomposition methods etc.) for solving problems resulting from the discretization of PDEs can be interpreted as additive (Jacobi-like) or multiplicative (Gauss-Seidel-like) subspace correction methods. The key to their analysis is the study of certain metric properties of the underlying splitting of the discretization space V into a sum of subspaces V{sub j}, j = 1{hor_ellipsis}, J resp. of the variational problem on V into auxiliary problems on these subspaces. Here, the author proposes a modified approach to the abstract convergence theory of these additive and multiplicative Schwarz iterative methods, that makes the relation to traditional iteration methods more explicit. To this end he introduces the enlarged Hilbert space V = V{sub 0} x {hor_ellipsis} x V{sub j} which is nothing else but the usual construction of the Cartesian product of the Hilbert spaces V{sub j} and use it now in the discretization process. This results in an enlarged, semidefinite linear system to be solved instead of the usual definite system. Then, modern multilevel methods as well as domain decomposition methods simplify to just traditional (block-) iteration methods. Now, the convergence analysis can be carried out directly for these traditional iterations on the enlarged system, making convergence proofs of multilevel and domain decomposition methods more clear, or, at least, more classical. The terms that enter the convergence proofs are exactly the ones of the classical iterative methods. It remains to estimate them properly. The convergence proof itself follow basically line by line the old proofs of the respective traditional iterative methods. Additionally, new multilevel/domain decomposition methods are constructed straightforwardly by now applying just other old and well known traditional iterative methods to the enlarged system.
A multilevel Cartesian non-uniform grid time domain algorithm
Meng Jun; Boag, Amir; Lomakin, Vitaliy; Michielssen, Eric
A multilevel Cartesian non-uniform grid time domain algorithm (CNGTDA) is introduced to rapidly compute transient wave fields radiated by time dependent three-dimensional source constellations. CNGTDA leverages the observation that transient wave fields generated by temporally bandlimited and spatially confined source constellations can be recovered via interpolation from appropriately delay- and amplitude-compensated field samples. This property is used in conjunction with a multilevel scheme, in which the computational domain is hierarchically decomposed into subdomains with sparse non-uniform grids used to obtain the fields. For both surface and volumetric source distributions, the computational cost of CNGTDA to compute the transient field at N{sub s} observation locations from N{sub s} collocated sources for N{sub t} discrete time instances scales as O(N{sub t}N{sub s}logN{sub s}) and O(N{sub t}N{sub s}log{sup 2}N{sub s}) in the low- and high-frequency regimes, respectively. Coupled with marching-on-in-time (MOT) time domain integral equations, CNGTDA can facilitate efficient analysis of large scale time domain electromagnetic and acoustic problems.
Morris, J; Johnson, S
The Distinct Element Method (also frequently referred to as the Discrete Element Method) (DEM) is a Lagrangian numerical technique where the computational domain consists of discrete solid elements which interact via compliant contacts. This can be contrasted with Finite Element Methods where the computational domain is assumed to represent a continuum (although many modern implementations of the FEM can accommodate some Distinct Element capabilities). Often the terms Discrete Element Method and Distinct Element Method are used interchangeably in the literature, although Cundall and Hart (1992) suggested that Discrete Element Methods should be a more inclusive term covering Distinct Element Methods, Displacement Discontinuity Analysis and Modal Methods. In this work, DEM specifically refers to the Distinct Element Method, where the discrete elements interact via compliant contacts, in contrast with Displacement Discontinuity Analysis where the contacts are rigid and all compliance is taken up by the adjacent intact material.
Multigrid and multilevel domain decomposition for unstructured grids
Chan, T.; Smith, B.
Multigrid has proven itself to be a very versatile method for the iterative solution of linear and nonlinear systems of equations arising from the discretization of PDES. In some applications, however, no natural multilevel structure of grids is available, and these must be generated as part of the solution procedure. In this presentation the authors will consider the problem of generating a multigrid algorithm when only a fine, unstructured grid is given. Their techniques generate a sequence of coarser grids by first forming an approximate maximal independent set of the vertices and then applying a Cavendish type algorithm to form the coarser triangulation. Numerical tests indicate that convergence using this approach can be as fast as standard multigrid on a structured mesh, at least in two dimensions.
Synchronous Discrete Harmonic Oscillator
Antippa, Adel F.; Dubois, Daniel M.
We introduce the synchronous discrete harmonic oscillator, and present an analytical, numerical and graphical study of its characteristics. The oscillator is synchronous when the time T for one revolution covering an angle of 2{pi} in phase space, is an integral multiple N of the discrete time step {delta}t. It is fully synchronous when N is even. It is pseudo-synchronous when T/{delta}t is rational. In the energy conserving hyperincursive representation, the phase space trajectories are perfectly stable at all time scales, and in both synchronous and pseudo-synchronous modes they cycle through a finite number of phase space points. Consequently, both the synchronous and the pseudo-synchronous hyperincursive modes of time-discretization provide a physically realistic and mathematically coherent, procedure for dynamic, background independent, discretization of spacetime. The procedure is applicable to any stable periodic dynamical system, and provokes an intrinsic correlation between space and time, whereby space-discretization is a direct consequence of background-independent time-discretization. Hence, synchronous discretization moves the formalism of classical mechanics towards that of special relativity. The frequency of the hyperincursive discrete harmonic oscillator is ''blue shifted'' relative to its continuum counterpart. The frequency shift has the precise value needed to make the speed of the system point in phase space independent of the discretizing time interval {delta}t. That is the speed of the system point is the same on the polygonal (in the discrete case) and the circular (in the continuum case) phase space trajectories.
Comparison of Estimation Procedures for Multilevel AR(1) Models.
Krone, Tanja; Albers, Casper J; Timmerman, Marieke E
To estimate a time series model for multiple individuals, a multilevel model may be used. In this paper we compare two estimation methods for the autocorrelation in Multilevel AR(1) models, namely Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo. Furthermore, we examine the difference between modeling fixed and random individual parameters. To this end, we perform a simulation study with a fully crossed design, in which we vary the length of the time series (10 or 25), the number of individuals per sample (10 or 25), the mean of the autocorrelation (-0.6 to 0.6 inclusive, in steps of 0.3) and the standard deviation of the autocorrelation (0.25 or 0.40). We found that the random estimators of the population autocorrelation show less bias and higher power, compared to the fixed estimators. As expected, the random estimators profit strongly from a higher number of individuals, while this effect is small for the fixed estimators. The fixed estimators profit slightly more from a higher number of time points than the random estimators. When possible, random estimation is preferred to fixed estimation. The difference between MLE and Bayesian estimation is nearly negligible. The Bayesian estimation shows a smaller bias, but MLE shows a smaller variability (i.e., standard deviation of the parameter estimates). Finally, better results are found for a higher number of individuals and time points, and for a lower individual variability of the autocorrelation. The effect of the size of the autocorrelation differs between outcome measures. PMID:27242559
Comparison of Estimation Procedures for Multilevel AR(1) Models
Krone, Tanja; Albers, Casper J.; Timmerman, Marieke E.
To estimate a time series model for multiple individuals, a multilevel model may be used. In this paper we compare two estimation methods for the autocorrelation in Multilevel AR(1) models, namely Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo. Furthermore, we examine the difference between modeling fixed and random individual parameters. To this end, we perform a simulation study with a fully crossed design, in which we vary the length of the time series (10 or 25), the number of individuals per sample (10 or 25), the mean of the autocorrelation (−0.6 to 0.6 inclusive, in steps of 0.3) and the standard deviation of the autocorrelation (0.25 or 0.40). We found that the random estimators of the population autocorrelation show less bias and higher power, compared to the fixed estimators. As expected, the random estimators profit strongly from a higher number of individuals, while this effect is small for the fixed estimators. The fixed estimators profit slightly more from a higher number of time points than the random estimators. When possible, random estimation is preferred to fixed estimation. The difference between MLE and Bayesian estimation is nearly negligible. The Bayesian estimation shows a smaller bias, but MLE shows a smaller variability (i.e., standard deviation of the parameter estimates). Finally, better results are found for a higher number of individuals and time points, and for a lower individual variability of the autocorrelation. The effect of the size of the autocorrelation differs between outcome measures. PMID:27242559
Carlsten, B.E.; Haynes, W.B.
The authors theoretically and numerically investigate the operation and behavior of the discrete monotron oscillator, a novel high-power microwave source. The discrete monotron differs from conventional monotrons and transit time oscillators by shielding the electron beam from the monotron cavity`s RF fields except at two distinct locations. This makes the discrete monotron act more like a klystron than a distributed traveling wave device. As a result, the oscillator has higher efficiency and can operate with higher beam powers than other single cavity oscillators and has more stable operation without requiring a seed input signal than mildly relativistic, intense-beam klystron oscillators.
Multilevel Latent Class Models with Dirichlet Mixing Distribution
Di, Chong-Zhi; Bandeen-Roche, Karen
Summary Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social science and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we consider multilevel latent class models, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data. PMID:20560936
Planarization of metal films for multilevel interconnects
Tuckerman, D.B.
In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration. 6 figs.
Planarization of metal films for multilevel interconnects
Tuckerman, David B.
In the fabrication of multilevel integrated circuits, each metal layer is anarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Planarization of metal films for multilevel interconnects
Tuckerman, David B.
In the fabrication of multilevel integrated circuits, each metal layer is anarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Planarization of metal films for multilevel interconnects
Tuckerman, D.B.
In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Planarization of metal films for multilevel interconnects
Tuckerman, D.B.
In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping lase pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.
Bound-state eigenenergy outside and inside the continuum for unstable multilevel systems
NASA Astrophysics Data System (ADS)
Miyamoto, Manabu
The eigenvalue problem for the dressed bound state of unstable multilevel systems is examined both outside and inside the continuum, based on the N -level Friedrichs model, which describes the couplings between the discrete levels and the continuous spectrum. It is shown that a bound-state eigenenergy always exists below each of the discrete levels that lie outside the continuum. Furthermore, by strengthening the couplings gradually, the eigenenergy corresponding to each of the discrete levels inside the continuum finally emerges. On the other hand, the absence of the eigenenergy inside the continuum is proved in weak but finite coupling regimes, provided that each of the form factors that determine the transition between some definite level and the continuum does not vanish at that energy level. An application to the spontaneous emission process for the hydrogen atom interacting with the electromagnetic field is demonstrated.
ERIC Educational Resources Information Center
Peters, James V.
Using the methods of finite difference equations the discrete analogue of the parabolic and catenary cable are analysed. The fibonacci numbers and the golden ratio arise in the treatment of the catenary.
Discretizations of axisymmetric systems
NASA Astrophysics Data System (ADS)
Frauendiener, Jörg
In this paper we discuss stability properties of various discretizations for axisymmetric systems including the so-called cartoon method which was proposed by Alcubierre et al. for the simulation of such systems on Cartesian grids. We show that within the context of the method of lines such discretizations tend to be unstable unless one takes care in the way individual singular terms are treated. Examples are given for the linear axisymmetric wave equation in flat space.
Scalable Adaptive Multilevel Solvers for Multiphysics Problems
Xu, Jinchao
In this project, we investigated adaptive, parallel, and multilevel methods for numerical modeling of various real-world applications, including Magnetohydrodynamics (MHD), complex fluids, Electromagnetism, Navier-Stokes equations, and reservoir simulation. First, we have designed improved mathematical models and numerical discretizaitons for viscoelastic fluids and MHD. Second, we have derived new a posteriori error estimators and extended the applicability of adaptivity to various problems. Third, we have developed multilevel solvers for solving scalar partial differential equations (PDEs) as well as coupled systems of PDEs, especially on unstructured grids. Moreover, we have integrated the study between adaptive method and multilevel methods, and made significant efforts and advances in adaptive multilevel methods of the multi-physics problems.
Multilevel summation methods for efficient evaluation of long-range pairwise interactions in atomistic and coarse-grained molecular simulation.
Bond, Stephen D.
The availability of efficient algorithms for long-range pairwise interactions is central to the success of numerous applications, ranging in scale from atomic-level modeling of materials to astrophysics. This report focuses on the implementation and analysis of the multilevel summation method for approximating long-range pairwise interactions. The computational cost of the multilevel summation method is proportional to the number of particles, N, which is an improvement over FFTbased methods who's cost is asymptotically proportional to N logN. In addition to approximating electrostatic forces, the multilevel summation method can be use to efficiently approximate convolutions with long-range kernels. As an application, we apply the multilevel summation method to a discretized integral equation formulation of the regularized generalized Poisson equation. Numerical results are presented using an implementation of the multilevel summation method in the LAMMPS software package. Preliminary results show that the computational cost of the method scales as expected, but there is still a need for further optimization.
Algebraic dynamic multilevel (ADM) method for fully implicit simulations of multiphase flow in porous media
NASA Astrophysics Data System (ADS)
Cusini, Matteo; van Kruijsdijk, Cor; Hajibeygi, Hadi
This paper presents the development of an algebraic dynamic multilevel method (ADM) for fully implicit simulations of multiphase flow in homogeneous and heterogeneous porous media. Built on the fine-scale fully implicit (FIM) discrete system, ADM constructs a multilevel FIM system describing the coupled process on a dynamically defined grid of hierarchical nested topology. The multilevel adaptive resolution is determined at each time step on the basis of an error criterion. Once the grid resolution is established, ADM employs sequences of restriction and prolongation operators in order to map the FIM system across the considered resolutions. Several choices can be considered for prolongation (interpolation) operators, e.g., constant, bilinear and multiscale basis functions, all of which form partition of unity. The adaptive multilevel restriction operators, on the other hand, are constructed using a finite-volume scheme. This ensures mass conservation of the ADM solutions, and as such, the stability and accuracy of the simulations with multiphase transport. For several homogeneous and heterogeneous test cases, it is shown that ADM applies only a small fraction of the full FIM fine-scale grid cells in order to provide accurate solutions. The sensitivity of the solutions with respect to the employed fraction of grid cells (determined automatically based on the threshold value of the error criterion) is investigated for all test cases. ADM is a significant step forward in the application of dynamic local grid refinement methods, in the sense that it is algebraic, allows for systematic mapping across different scales, and applicable to heterogeneous test cases without any upscaling of fine-scale high resolution quantities. It also develops a novel multilevel multiscale method for FIM multiphase flow simulations in natural subsurface formations.
Alternative Methods for Assessing Mediation in Multilevel Data: The Advantages of Multilevel SEM
ERIC Educational Resources Information Center
Preacher, Kristopher J.; Zhang, Zhen; Zyphur, Michael J.
Multilevel modeling (MLM) is a popular way of assessing mediation effects with clustered data. Two important limitations of this approach have been identified in prior research and a theoretical rationale has been provided for why multilevel structural equation modeling (MSEM) should be preferred. However, to date, no empirical evidence of MSEM's…
Discrete Newtonian cosmology: perturbations
NASA Astrophysics Data System (ADS)
Ellis, George F. R.; Gibbons, Gary W.
In a previous paper (Gibbons and Ellis 2014 Discrete Newtonian cosmology Class. Quantum Grav. 31 025003), we showed how a finite system of discrete particles interacting with each other via Newtonian gravitational attraction would lead to precisely the same dynamical equations for homothetic motion as in the case of the pressure-free Friedmann-Lemaître-Robertson-Walker cosmological models of general relativity theory, provided the distribution of particles obeys the central configuration equation. In this paper we show that one can obtain perturbed such Newtonian solutions that give the same linearized structure growth equations as in the general relativity case. We also obtain the Dmitriev-Zel'dovich equations for subsystems in this discrete gravitational model, and show how it leads to the conclusion that voids have an apparent negative mass.
Simulation of correlated discrete Weibull variables: A proposal and an implementation in the R environment
NASA Astrophysics Data System (ADS)
Barbiero, Alessandro
Researchers in applied sciences are often concerned with multivariate random variables. In particular, multivariate discrete data often arise in many fields (statistical quality control, biostatistics, failure analysis, etc). Here we consider the discrete Weibull distribution as an alternative to the popular Poisson random variable and propose a procedure for simulating correlated discrete Weibull random variables, with marginal distributions and correlation matrix assigned by the user. The procedure indeed relies upon the gaussian copula model and an iterative algorithm for recovering the proper correlation matrix for the copula ensuring the desired correlation matrix on the discrete margins. A simulation study is presented, which empirically shows the performance of the procedure.
Anterior decompression and fusion versus posterior laminoplasty for multilevel cervical compressive myelopathy.
Liu, Xuzhou; Wang, Hehui; Zhou, Zhilai; Jin, Anmin
The optimal surgical strategy for anterior or posterior approaches remains controversial for multilevel cervical compressive myelopathy caused by multisegment cervical spondylotic myelopathy (MCSM) or ossification of the posterior longitudinal ligament (OPLL). A systematic review and meta-analysis was conducted evaluating the clinical results of anterior decompression and fusion (ADF) compared with posterior laminoplasty for patients with multilevel cervical compressive myelopathy. PubMed, Embase, and the Cochrane Library were searched for randomized controlled trials and nonrandomized cohort studies conducted from 1990 to May 2013 comparing ADF with posterior laminoplasty for the treatment of multilevel cervical compressive myelopathy due to MCSM or OPLL. The following outcome measures were extracted: Japanese Orthopedic Association (JOA) score, recovery rate, complication rate, reoperation rate, blood loss, and operative time. Subgroup analysis was conducted according to the mean number of surgical segments. Eleven studies were included in the review, all of which were prospective or retrospective cohort studies with relatively low quality indicated by GRADE Working Group assessment. A definitive conclusion could not be reached regarding which surgical approach is more effective for the treatment of multilevel cervical compressive myelopathy. Although ADF was associated with better postoperative neural function than posterior laminoplasty in the treatment of multilevel cervical compressive myelopathy due to MCSM or OPLL, there was no apparent difference in the neural function recovery rate between the 2 approaches. Higher rates of surgery-related complication and reoperation should be taken into consideration when ADF is used for patients with multilevel cervical compressive myelopathy. The surgical trauma associated with corpectomy was significantly higher than that associated with posterior laminoplasty. PMID:24679196
Statistical power of multilevel modelling in dental caries clinical trials: a simulation study.
Burnside, G; Pine, C M; Williamson, P R
Outcome data from dental caries clinical trials have a naturally hierarchical structure, with surfaces clustered within teeth, clustered within individuals. Data are often aggregated into the DMF index for each individual, losing tooth- and surface-specific information. If these data are to be analysed by tooth or surface, allowing exploration of effects of interventions on different teeth and surfaces, appropriate methods must be used to adjust for the clustered nature of the data. Multilevel modelling allows analysis of clustered data using individual observations without aggregating data, and has been little used in the field of dental caries. A simulation study was conducted to investigate the performance of multilevel modelling methods and standard caries increment analysis. Data sets were simulated from a three-level binomial distribution based on analysis of a caries clinical trial in Scottish adolescents, with varying sample sizes, treatment effects and random tooth level effects based on trials reported in Cochrane reviews of topical fluoride, and analysed to compare the power of multilevel models and traditional analysis. 40,500 data sets were simulated. Analysis showed that estimated power for the traditional caries increment method was similar to that for multilevel modelling, with more variation in smaller data sets. Multilevel modelling may not allow significant reductions in the number of participants required in a caries clinical trial, compared to the use of traditional analyses, but investigators interested in exploring the effect of their intervention in more detail may wish to consider the application of multilevel modelling to their clinical trial data. PMID:24216573
Discrete breathers in crystals
NASA Astrophysics Data System (ADS)
Dmitriev, S. V.; Korznikova, E. A.; Baimova, Yu A.; Velarde, M. G.
It is well known that periodic discrete defect-containing systems, in addition to traveling waves, support vibrational defect-localized modes. It turned out that if a periodic discrete system is nonlinear, it can support spatially localized vibrational modes as exact solutions even in the absence of defects. Since the nodes of the system are all on equal footing, it is only through the special choice of initial conditions that a group of nodes can be found on which such a mode, called a discrete breather (DB), will be excited. The DB frequency must be outside the frequency range of the small-amplitude traveling waves. Not resonating with and expending no energy on the excitation of traveling waves, a DB can theoretically conserve its vibrational energy forever provided no thermal vibrations or other perturbations are present. Crystals are nonlinear discrete systems, and the discovery in them of DBs was only a matter of time. It is well known that periodic discrete defect-containing systems support both traveling waves and vibrational defect-localized modes. It turns out that if a periodic discrete system is nonlinear, it can support spatially localized vibrational modes as exact solutions even in the absence of defects. Because the nodes of the system are all on equal footing, only a special choice of the initial conditions allows selecting a group of nodes on which such a mode, called a discrete breather (DB), can be excited. The DB frequency must be outside the frequency range of small-amplitude traveling waves. Not resonating with and expending no energy on the excitation of traveling waves, a DB can theoretically preserve its vibrational energy forever if no thermal vibrations or other perturbations are present. Crystals are nonlinear discrete systems, and the discovery of DBs in them was only a matter of time. Experimental studies of DBs encounter major technical difficulties, leaving atomistic computer simulations as the primary investigation tool. Despite
NASA Astrophysics Data System (ADS)
Arzano, Michele; Kowalski-Glikman, Jerzy
We construct discrete symmetry transformations for deformed relativistic kinematics based on group valued momenta. We focus on the specific example of κ-deformations of the Poincaré algebra with associated momenta living on (a sub-manifold of) de Sitter space. Our approach relies on the description of quantum states constructed from deformed kinematics and the observable charges associated with them. The results we present provide the first step towards the analysis of experimental bounds on the deformation parameter κ to be derived via precision measurements of discrete symmetries and CPT.
Students' Misconceptions about Random Variables
ERIC Educational Resources Information Center
Kachapova, Farida; Kachapov, Ilias
This article describes some misconceptions about random variables and related counter-examples, and makes suggestions about teaching initial topics on random variables in general form instead of doing it separately for discrete and continuous cases. The focus is on post-calculus probability courses. (Contains 2 figures.)
Applications of cascade multilevel inverters.
Peng, Fang-zen; Qian, Zhao-ming
Cascade multilevel inverters have been developed for electric utility applications. A cascade M-level inverter consists of (M-1)/2 H-bridges in which each bridge's dc voltage is supported by its own dc capacitor. The new inverter can: (1) generate almost sinusoidal waveform voltage while only switching one time per fundamental cycle; (2) dispense with multi-pulse inverters' transformers used in conventional utility interfaces and static var compensators; (3) enables direct parallel or series transformer-less connection to medium- and high-voltage power systems. In short, the cascade inverter is much more efficient and suitable for utility applications than traditional multi-pulse and pulse width modulation (PWM) inverters. The authors have experimentally demonstrated the superiority of the new inverter for power supply, (hybrid) electric vehicle (EV) motor drive, reactive power (var) and harmonic compensation. This paper summarizes the features, feasibility, and control schemes of the cascade inverter for utility applications including utility interface of renewable energy, voltage regulation, var compensation, and harmonic filtering in power systems. Analytical, simulated, and experimental results demonstrated the superiority of the new inverters. PMID:14566981
Multilevel Complex Networks and Systems
NASA Astrophysics Data System (ADS)
Caldarelli, Guido
Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h0>h1 ...>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less
GPU-based Multilevel Clustering.
Chiosa, Iurie; Kolb, Andreas
The processing power of parallel co-processors like the Graphics Processing Unit (GPU) are dramatically increasing. However, up until now only a few approaches have been presented to utilize this kind of hardware for mesh clustering purposes. In this paper we introduce a Multilevel clustering technique designed as a parallel algorithm and solely implemented on the GPU. Our formulation uses the spatial coherence present in the cluster optimization and hierarchical cluster merging to significantly reduce the number of comparisons in both parts . Our approach provides a fast, high quality and complete clustering analysis. Furthermore, based on the original concept we present a generalization of the method to data clustering. All advantages of the meshbased techniques smoothly carry over to the generalized clustering approach. Additionally, this approach solves the problem of the missing topological information inherent to general data clustering and leads to a Local Neighbors k-means algorithm. We evaluate both techniques by applying them to Centroidal Voronoi Diagram (CVD) based clustering. Compared to classical approaches, our techniques generate results with at least the same clustering quality. Our technique proves to scale very well, currently being limited only by the available amount of graphics memory. PMID:20421676
Multilevel Intervention Research: Lessons Learned and Pathways Forward
Taplin, Stephen H.; Foster, Mary K.; Fagan, Pebbles; Kaluzny, Arnold D.
This summary reflects on this monograph regarding multilevel intervention (MLI) research to 1) assess its added value; 2) discuss what has been learned to date about its challenges in cancer care delivery; and 3) identify specific ways to improve its scientific soundness, feasibility, policy relevance, and research agenda. The 12 submitted chapters, and discussion of them at the March 2011 multilevel meeting, were reviewed and discussed among the authors to elicit key findings and results addressing the questions raised at the outset of this effort. MLI research is underrepresented as an explicit focus in the cancer literature but may improve implementation of studies of cancer care delivery if they assess contextual, organizational, and environmental factors important to understanding behavioral and/or system-level interventions. The field lacks a single unifying theory, although several psychological or biological theories are useful, and an ecological model helps conceptualize and communicate interventions. MLI research designs are often complex, involving nonlinear and nonhierarchical relationships that may not be optimally studied in randomized designs. Simulation modeling and pilot studies may be necessary to evaluate MLI interventions. Measurement and evaluation of team and organizational interventions are especially needed in cancer care, as are attention to the context of health-care reform, eHealth technology, and genomics-based medicine. Future progress in MLI research requires greater attention to developing and supporting relevant metrics of level effects and interactions and evaluating MLI interventions. MLI research holds an unrealized promise for understanding how to improve cancer care delivery. PMID:22623606
Multilevel intervention research: lessons learned and pathways forward.
Clauser, Steven B; Taplin, Stephen H; Foster, Mary K; Fagan, Pebbles; Kaluzny, Arnold D
This summary reflects on this monograph regarding multilevel intervention (MLI) research to 1) assess its added value; 2) discuss what has been learned to date about its challenges in cancer care delivery; and 3) identify specific ways to improve its scientific soundness, feasibility, policy relevance, and research agenda. The 12 submitted chapters, and discussion of them at the March 2011 multilevel meeting, were reviewed and discussed among the authors to elicit key findings and results addressing the questions raised at the outset of this effort. MLI research is underrepresented as an explicit focus in the cancer literature but may improve implementation of studies of cancer care delivery if they assess contextual, organizational, and environmental factors important to understanding behavioral and/or system-level interventions. The field lacks a single unifying theory, although several psychological or biological theories are useful, and an ecological model helps conceptualize and communicate interventions. MLI research designs are often complex, involving nonlinear and nonhierarchical relationships that may not be optimally studied in randomized designs. Simulation modeling and pilot studies may be necessary to evaluate MLI interventions. Measurement and evaluation of team and organizational interventions are especially needed in cancer care, as are attention to the context of health-care reform, eHealth technology, and genomics-based medicine. Future progress in MLI research requires greater attention to developing and supporting relevant metrics of level effects and interactions and evaluating MLI interventions. MLI research holds an unrealized promise for understanding how to improve cancer care delivery. PMID:22623606
ERIC Educational Resources Information Center
Sharp, Karen Tobey
This paper cites information received from a number of sources, e.g., mathematics teachers in two-year colleges, publishers, and convention speakers, about the nature of discrete mathematics and about what topics a course in this subject should contain. Note is taken of the book edited by Ralston and Young which discusses the future of college…
Momentum conservation in Multi-Level Multi-Domain (MLMD) simulations
NASA Astrophysics Data System (ADS)
Innocenti, M. E.; Beck, A.; Markidis, S.; Lapenta, G.
Momentum conservation and self-forces reduction are challenges for all Particle-In-Cell (PIC) codes using spatial discretization schemes which do not fulfill the requirement of translational invariance of the grid Green's function. We comment here on the topic applied to the recently developed Multi-Level Multi-Domain (MLMD) method. The MLMD is a semi-implicit method for PIC plasma simulations. The multi-scale nature of plasma processes is addressed by using grids with different spatial resolutions in different parts of the domain.
Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.
Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie
In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. PMID:26722989
A multilevel preconditioner for domain decomposition boundary systems
Bramble, J.H.; Pasciak, J.E.; Xu, Jinchao.
In this note, we consider multilevel preconditioning of the reduced boundary systems which arise in non-overlapping domain decomposition methods. It will be shown that the resulting preconditioned systems have condition numbers which be bounded in the case of multilevel spaces on the whole domain and grow at most proportional to the number of levels in the case of multilevel boundary spaces without multilevel extensions into the interior.
Multilevel modelling of clustered grouped survival data using Cox regression model: an application to ART dental restorations.
Wong, May C M; Lam, K F; Lo, Edward C M
In some controlled clinical trials in dental research, multiple failure time data from the same patient are frequently observed that result in clustered multiple failure time. Moreover, the treatments are often delivered by more than one operator and thus the multiple failure times are clustered according to a multilevel structure when the operator effects are assumed to be random. In practice, it is often too expensive or even impossible to monitor the study subjects continuously, but they are examined periodically at some regular pre-scheduled visits. Hence, discrete or grouped clustered failure time data are collected. The aim of this paper is to illustrate the use of the Monte Carlo Markov chain (MCMC) approach and non-informative prior in a Bayesian framework to mimic the maximum likelihood (ML) estimation in a frequentist approach in multilevel modelling of clustered grouped survival data. A three-level model with additive variance components model for the random effects is considered in this paper. Both the grouped proportional hazards model and the dynamic logistic regression model are used. The approximate intra-cluster correlation of the log failure times can be estimated when the grouped proportional hazards model is used. The statistical package WinBUGS is adopted to estimate the parameter of interest based on the MCMC method. The models and method are applied to a data set obtained from a prospective clinical study on a cohort of Chinese school children that atraumatic restorative treatment (ART) restorations were placed on permanent teeth with carious lesions. Altogether 284 ART restorations were placed by five dentists and clinical status of the ART restorations was evaluated annually for 6 years after placement, thus clustered grouped failure times of the restorations were recorded. Results based on the grouped proportional hazards model revealed that clustering effect among the log failure times of the different restorations from the same child was
Exploring Discretization Error in Simulation-Based Aerodynamic Databases
NASA Technical Reports Server (NTRS)
Aftosmis, Michael J.; Nemec, Marian
This work examines the level of discretization error in simulation-based aerodynamic databases and introduces strategies for error control. Simulations are performed using a parallel, multi-level Euler solver on embedded-boundary Cartesian meshes. Discretization errors in user-selected outputs are estimated using the method of adjoint-weighted residuals and we use adaptive mesh refinement to reduce these errors to specified tolerances. Using this framework, we examine the behavior of discretization error throughout a token database computed for a NACA 0012 airfoil consisting of 120 cases. We compare the cost and accuracy of two approaches for aerodynamic database generation. In the first approach, mesh adaptation is used to compute all cases in the database to a prescribed level of accuracy. The second approach conducts all simulations using the same computational mesh without adaptation. We quantitatively assess the error landscape and computational costs in both databases. This investigation highlights sensitivities of the database under a variety of conditions. The presence of transonic shocks or the stiffness in the governing equations near the incompressible limit are shown to dramatically increase discretization error requiring additional mesh resolution to control. Results show that such pathologies lead to error levels that vary by over factor of 40 when using a fixed mesh throughout the database. Alternatively, controlling this sensitivity through mesh adaptation leads to mesh sizes which span two orders of magnitude. We propose strategies to minimize simulation cost in sensitive regions and discuss the role of error-estimation in database quality.
Winkler, Anderson M.; Webster, Matthew A.; Vidaurre, Diego; Nichols, Thomas E.; Smith, Stephen M.
Under weak and reasonable assumptions, mainly that data are exchangeable under the null hypothesis, permutation tests can provide exact control of false positives and allow the use of various non-standard statistics. There are, however, various common examples in which global exchangeability can be violated, including paired tests, tests that involve repeated measurements, tests in which subjects are relatives (members of pedigrees) — any dataset with known dependence among observations. In these cases, some permutations, if performed, would create data that would not possess the original dependence structure, and thus, should not be used to construct the reference (null) distribution. To allow permutation inference in such cases, we test the null hypothesis using only a subset of all otherwise possible permutations, i.e., using only the rearrangements of the data that respect exchangeability, thus retaining the original joint distribution unaltered. In a previous study, we defined exchangeability for blocks of data, as opposed to each datum individually, then allowing permutations to happen within block, or the blocks as a whole to be permuted. Here we extend that notion to allow blocks to be nested, in a hierarchical, multi-level definition. We do not explicitly model the degree of dependence between observations, only the lack of independence; the dependence is implicitly accounted for by the hierarchy and by the permutation scheme. The strategy is compatible with heteroscedasticity and variance groups, and can be used with permutations, sign flippings, or both combined. We evaluate the method for various dependence structures, apply it to real data from the Human Connectome Project (HCP) as an example application, show that false positives can be avoided in such cases, and provide a software implementation of the proposed approach. PMID:26074200
Incorporating Mobility in Growth Modeling for Multilevel and Longitudinal Item Response Data.
Choi, In-Hee; Wilson, Mark
Multilevel data often cannot be represented by the strict form of hierarchy typically assumed in multilevel modeling. A common example is the case in which subjects change their group membership in longitudinal studies (e.g., students transfer schools; employees transition between different departments). In this study, cross-classified and multiple membership models for multilevel and longitudinal item response data (CCMM-MLIRD) are developed to incorporate such mobility, focusing on students' school change in large-scale longitudinal studies. Furthermore, we investigate the effect of incorrectly modeling school membership in the analysis of multilevel and longitudinal item response data. Two types of school mobility are described, and corresponding models are specified. Results of the simulation studies suggested that appropriate modeling of the two types of school mobility using the CCMM-MLIRD yielded good recovery of the parameters and improvement over models that did not incorporate mobility properly. In addition, the consequences of incorrectly modeling the school effects on the variance estimates of the random effects and the standard errors of the fixed effects depended upon mobility patterns and model specifications. Two sets of large-scale longitudinal data are analyzed to illustrate applications of the CCMM-MLIRD for each type of school mobility. PMID:26881961
Automatic multilevel medical image annotation and retrieval.
Mueen, A; Zainuddin, R; Baba, M Sapiyan
Image retrieval at the semantic level mostly depends on image annotation or image classification. Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. To address first issue, multilevel features are extracted to construct the feature vector, which represents the contents of the image. To address second issue, domain-dependent concept hierarchy is constructed for interpretation of image semantic concepts. To address third issue, automatic multilevel code generation is proposed for image classification and multilevel image annotation. We make use of the existing image annotation to address second and third issues. Our experiments on a specific domain of X-ray images have given encouraging results. PMID:17846834
The discrete regime of flame propagation
NASA Astrophysics Data System (ADS)
Tang, Francois-David; Goroshin, Samuel; Higgins, Andrew
The propagation of laminar dust flames in iron dust clouds was studied in a low-gravity envi-ronment on-board a parabolic flight aircraft. The elimination of buoyancy-induced convection and particle settling permitted measurements of fundamental combustion parameters such as the burning velocity and the flame quenching distance over a wide range of particle sizes and in different gaseous mixtures. The discrete regime of flame propagation was observed by substitut-ing nitrogen present in air with xenon, an inert gas with a significantly lower heat conductivity. Flame propagation in the discrete regime is controlled by the heat transfer between neighbor-ing particles, rather than by the particle burning rate used by traditional continuum models of heterogeneous flames. The propagation mechanism of discrete flames depends on the spa-tial distribution of particles, and thus such flames are strongly influenced by local fluctuations in the fuel concentration. Constant pressure laminar dust flames were observed inside 70 cm long, 5 cm diameter Pyrex tubes. Equally-spaced plate assemblies forming rectangular chan-nels were placed inside each tube to determine the quenching distance defined as the minimum channel width through which a flame can successfully propagate. High-speed video cameras were used to measure the flame speed and a fiber optic spectrometer was used to measure the flame temperature. Experimental results were compared with predictions obtained from a numerical model of a three-dimensional flame developed to capture both the discrete nature and the random distribution of particles in the flame. Though good qualitative agreement was obtained between model predictions and experimental observations, residual g-jitters and the short reduced-gravity periods prevented further investigations of propagation limits in the dis-crete regime. The full exploration of the discrete flame phenomenon would require high-quality, long duration reduced gravity environment
Formulation and Application of the Generalized Multilevel Facets Model
ERIC Educational Resources Information Center
Wang, Wen-Chung; Liu, Chih-Yu
In this study, the authors develop a generalized multilevel facets model, which is not only a multilevel and two-parameter generalization of the facets model, but also a multilevel and facet generalization of the generalized partial credit model. Because the new model is formulated within a framework of nonlinear mixed models, no efforts are…
Multilevel transport solution of LWR reactor cores
Jose Ignacio Marquez Damian; Cassiano R.E. de Oliveira; HyeonKae Park
This work presents a multilevel approach for the solution of the transport equation in typical LWR assemblies and core configurations. It is based on the second-order, even-parity formulation of the transport equation, which is solved within the framework provided by the finite element-spherical harmonics code EVENT. The performance of the new solver has been compared with that of the standard conjugate gradient solver for diffusion and transport problems on structured and unstruc-tured grids. Numerical results demonstrate the potential of the multilevel scheme for realistic reactor calculations.
Discreteness induced extinction
NASA Astrophysics Data System (ADS)
dos Santos, Renato Vieira; da Silva, Linaena Méricy
Two simple models based on ecological problems are discussed from the point of view of non-equilibrium statistical mechanics. It is shown how discrepant may be the results of the models that include spatial distribution with discrete interactions when compared with the continuous analogous models. In the continuous case we have, under certain circumstances, the population explosion. When we take into account the finiteness of the population, we get the opposite result, extinction. We will analyze how these results depend on the dimension d of the space and describe the phenomenon of the "Discreteness Inducing Extinction" (DIE). The results are interpreted in the context of the "paradox of sex", an old problem of evolutionary biology.
Discretization of Continuous Time Discrete Scale Invariant Processes: Estimation and Spectra
NASA Astrophysics Data System (ADS)
Rezakhah, Saeid; Maleki, Yasaman
Imposing some flexible sampling scheme we provide some discretization of continuous time discrete scale invariant (DSI) processes which is a subsidiary discrete time DSI process. Then by introducing some simple random measure we provide a second continuous time DSI process which provides a proper approximation of the first one. This enables us to provide a bilateral relation between covariance functions of the subsidiary process and the new continuous time processes. The time varying spectral representation of such continuous time DSI process is characterized, and its spectrum is estimated. Also, a new method for estimation time dependent Hurst parameter of such processes is provided which gives a more accurate estimation. The performance of this estimation method is studied via simulation. Finally this method is applied to the real data of S & P500 and Dow Jones indices for some special periods.
Discrete Gust Model for Launch Vehicle Assessments
NASA Technical Reports Server (NTRS)
Leahy, Frank B.
Analysis of spacecraft vehicle responses to atmospheric wind gusts during flight is important in the establishment of vehicle design structural requirements and operational capability. Typically, wind gust models can be either a spectral type determined by a random process having a wide range of wavelengths, or a discrete type having a single gust of predetermined magnitude and shape. Classical discrete models used by NASA during the Apollo and Space Shuttle Programs included a 9 m/sec quasi-square-wave gust with variable wavelength from 60 to 300 m. A later study derived discrete gust from a military specification (MIL-SPEC) document that used a "1-cosine" shape. The MIL-SPEC document contains a curve of non-dimensional gust magnitude as a function of non-dimensional gust half-wavelength based on the Dryden spectral model, but fails to list the equation necessary to reproduce the curve. Therefore, previous studies could only estimate a value of gust magnitude from the curve, or attempt to fit a function to it. This paper presents the development of the MIL-SPEC curve, and provides the necessary information to calculate discrete gust magnitudes as a function of both gust half-wavelength and the desired probability level of exceeding a specified gust magnitude.
A paradigm for discrete physics
Noyes, H.P.; McGoveran, D.; Etter, T.; Manthey, M.J.; Gefwert, C.
An example is outlined for constructing a discrete physics using as a starting point the insight from quantum physics that events are discrete, indivisible and non-local. Initial postulates are finiteness, discreteness, finite computability, absolute nonuniqueness (i.e., homogeneity in the absence of specific cause) and additivity.
Bootstrap confidence intervals in multi-level simultaneous component analysis.
Timmerman, Marieke E; Kiers, Henk A L; Smilde, Age K; Ceulemans, Eva; Stouten, Jeroen
Multi-level simultaneous component analysis (MLSCA) was designed for the exploratory analysis of hierarchically ordered data. MLSCA specifies a component model for each level in the data, where appropriate constraints express possible similarities between groups of objects at a certain level, yielding four MLSCA variants. The present paper discusses different bootstrap strategies for estimating confidence intervals (CIs) on the individual parameters. In selecting a proper strategy, the main issues to address are the resampling scheme and the non-uniqueness of the parameters. The resampling scheme depends on which level(s) in the hierarchy are considered random, and which fixed. The degree of non-uniqueness depends on the MLSCA variant, and, in two variants, the extent to which the user exploits the transformational freedom. A comparative simulation study examines the quality of bootstrap CIs of different MLSCA parameters. Generally, the quality of bootstrap CIs appears to be good, provided the sample sizes are sufficient at each level that is considered to be random. The latter implies that if more than a single level is considered random, the total number of observations necessary to obtain reliable inferential information increases dramatically. An empirical example illustrates the use of bootstrap CIs in MLSCA. PMID:18086338
The understanding on the evolution of stress-induced gate leakage in high-k dielectric metal-oxide-field-effect transistor by random-telegraph-noise measurement
NASA Astrophysics Data System (ADS)
Hsieh, E. R.; Chung, Steve S.
The evolution of gate-current leakage path has been observed and depicted by RTN signals on metal-oxide-silicon field effect transistor with high-k gate dielectric. An experimental method based on gate-current random telegraph noise (Ig-RTN) technique was developed to observe the formation of gate-leakage path for the device under certain electrical stress, such as Bias Temperature Instability. The results show that the evolution of gate-current path consists of three stages. In the beginning, only direct-tunnelling gate current and discrete traps inducing Ig-RTN are observed; in the middle stage, interaction between traps and the percolation paths presents a multi-level gate-current variation, and finally two different patterns of the hard or soft breakdown path can be identified. These observations provide us a better understanding of the gate-leakage and its impact on the device reliability.
Constructions of Factorizable Multilevel Hadamard Matrices
NASA Astrophysics Data System (ADS)
Matsufuji, Shinya; Fan, Pingzhi
Factorization of Hadamard matrices can provide fast algorithm and facilitate efficient hardware realization. In this letter, constructions of factorizable multilevel Hadamard matrices, which can be considered as special case of unitary matrices, are inverstigated. In particular, a class of ternary Hadamard matrices, together with its application, is presented.
BER estimation for multilevel modulation formats
NASA Astrophysics Data System (ADS)
Louchet, Hadrien; Kuzmin, Konstantin; Koltchanov, Igor; Richter, André
We review existing BER estimation methods and propose alternative methods to assess the performance of multilevel modulation formats with both direct and coherent detection. The impact of digital signal processing (DSP) on the BER estimation procedure is discussed for the latter case. The different approaches are illustrated by simulating exemplary transmission systems.
Single-Level and Multilevel Mediation Analysis
ERIC Educational Resources Information Center
Tofighi, Davood; Thoemmes, Felix
Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…
New multilevel codes over GF(q)
NASA Technical Reports Server (NTRS)
Wu, Jiantian; Costello, Daniel J., Jr.
Set partitioning to multi-dimensional signal spaces over GF(q), particularly GF sup q-1(q) and GF sup q (q), and show how to construct both multi-level block codes and multi-level trellis codes over GF(q). Two classes of multi-level (n, k, d) block codes over GF(q) with block length n, number of information symbols k, and minimum distance d sub min greater than or = d, are presented. These two classes of codes use Reed-Solomon codes as component codes. They can be easily decoded as block length q-1 Reed-Solomon codes or block length q or q + 1 extended Reed-Solomon codes using multi-stage decoding. Many of these codes have larger distances than comparable q-ary block codes, as component codes. Low rate q-ary convolutional codes, work error correcting convolutional codes, and binary-to-q-ary convolutional codes can also be used to construct multi-level trellis codes over GF(q) or binary-to-q-ary trellis codes, some of which have better performance than the above block codes. All of the new codes have simple decoding algorithms based on hard decision multi-stage decoding.
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Engineering applications of heuristic multilevel optimization methods
NASA Technical Reports Server (NTRS)
Barthelemy, Jean-Francois M.
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Using Multilevel Modeling in Counseling Research
ERIC Educational Resources Information Center
Lynch, Martin F.
This conceptual and practical overview of multilevel modeling (MLM) for researchers in counseling and development provides guidelines on setting up SPSS to perform MLM and an example of how to present the findings. It also provides a discussion on how counseling and developmental researchers can use MLM to address their own research questions.…
Multilevel Factor Models for Ordinal Variables
ERIC Educational Resources Information Center
Grilli, Leonardo; Rampichini, Carla
This article tackles several issues involved in specifying, fitting, and interpreting the results of multilevel factor models for ordinal variables. First, the problem of model specification and identification is addressed, outlining parameter interpretation. Special attention is devoted to the consequences on interpretation stemming from the…
Efficiently Exploring Multilevel Data with Recursive Partitioning
ERIC Educational Resources Information Center
Martin, Daniel P.; von Oertzen, Timo; Rimm-Kaufman, Sara E.
There is an increasing number of datasets with many participants, variables, or both, in education and other fields that often deal with large, multilevel data structures. Once initial confirmatory hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform…
A Practical Guide to Multilevel Modeling
ERIC Educational Resources Information Center
Peugh, James L.
Collecting data from students within classrooms or schools, and collecting data from students on multiple occasions over time, are two common sampling methods used in educational research that often require multilevel modeling (MLM) data analysis techniques to avoid Type-1 errors. The purpose of this article is to clarify the seven major steps…
Multilevel training of binary morphological operators.
Hirata, Nina S T
The design of binary morphological operators that are translation-invariant and locally defined by a finite neighborhood window corresponds to the problem of designing Boolean functions. As in any supervised classification problem, morphological operators designed from training sample also suffer from overfitting. Large neighborhood tends to lead to performance degradation of the designed operator. This work proposes a multi-level design approach to deal with the issue of designing large neighborhood based operators. The main idea is inspired from stacked generalization (a multi-level classifier design approach) and consists in, at each training level, combining the outcomes of the previous level operators. The final operator is a multi-level operator that ultimately depends on a larger neighborhood than of the individual operators that have been combined. Experimental results show that two-level operators obtained by combining operators designed on subwindows of a large window consistently outperforms the single-level operators designed on the full window. They also show that iterating two-level operators is an effective multi-level approach to obtain better results. PMID:19229085
The Economic Cost of Homosexuality: Multilevel Analyses
ERIC Educational Resources Information Center
Baumle, Amanda K.; Poston, Dudley, Jr.
This article builds on earlier studies that have examined "the economic cost of homosexuality," by using data from the 2000 U.S. Census and by employing multilevel analyses. Our findings indicate that partnered gay men experience a 12.5 percent earnings penalty compared to married heterosexual men, and a statistically insignificant earnings…
Numerical valuation of discrete double barrier options
NASA Astrophysics Data System (ADS)
Milev, Mariyan; Tagliani, Aldo
In the present paper we explore the problem for pricing discrete barrier options utilizing the Black-Scholes model for the random movement of the asset price. We postulate the problem as a path integral calculation by choosing approach that is similar to the quadrature method. Thus, the problem is reduced to the estimation of a multi-dimensional integral whose dimension corresponds to the number of the monitoring dates. We propose a fast and accurate numerical algorithm for its valuation. Our results for pricing discretely monitored one and double barrier options are in agreement with those obtained by other numerical and analytical methods in Finance and literature. A desired level of accuracy is very fast achieved for values of the underlying asset close to the strike price or the barriers. The method has a simple computer implementation and it permits observing the entire life of the option.
Discrete scale invariance in supercritical percolation
NASA Astrophysics Data System (ADS)
Schröder, Malte; Chen, Wei; Nagler, Jan
Recently it has been demonstrated that the connectivity transition from microscopic connectivity to macroscopic connectedness, known as percolation, is generically announced by a cascade of microtransitions of the percolation order parameter (Chen et al 2014 Phys. Rev. Lett. 112 155701). Here we report the discovery of macrotransition cascades which follow percolation. The order parameter grows in discrete macroscopic steps with positions that can be randomly distributed even in the thermodynamic limit. These transition positions are, however, correlated and follow scaling laws which arise from discrete scale invariance (DSI) and non self-averaging, both traditionally unrelated to percolation. We reveal the DSI in ensemble measurements of these non self-averaging systems by rescaling of the individual realizations before averaging.
Multilevel method for modeling large-scale networks.
Safro, I. M.
Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from
Integrating Space with Place in Health Research: A Multilevel Spatial Investigation Using Child Mortality in 1880 Newark, New Jersey
Xu, Hongwei; Logan, John R.; Short, Susan E.
Research on neighborhoods and health increasingly acknowledges the need to conceptualize, measure, and model spatial features of social and physical environments. In ignoring underlying spatial dynamics, we run the risk of biased statistical inference and misleading results. In this paper, we propose an integrated multilevel-spatial approach for Poisson models of discrete responses. In an empirical example of child mortality in 1880 Newark, New Jersey, we compare this multilevel-spatial approach with the more typical aspatial multilevel approach. Results indicate that spatially-defined egocentric neighborhoods, or distance-based measures, outperform administrative areal units, such as census units. In addition, although results did not vary by specific definitions of egocentric neighborhoods, they were sensitive to geographic scale and modeling strategy. Overall, our findings confirm that adopting a spatial-multilevel approach enhances our ability to disentangle the effect of space from that of place, and point to the need for more careful spatial thinking in population research on neighborhoods and health. PMID:24763980
Performance of a parallel algebraic multilevel preconditioner for stabilized finite element semiconductor device modeling
Lin, Paul T. Shadid, John N.; Sala, Marzio; Tuminaro, Raymond S.; Hennigan, Gary L.; Hoekstra, Robert J.
In this study results are presented for the large-scale parallel performance of an algebraic multilevel preconditioner for solution of the drift-diffusion model for semiconductor devices. The preconditioner is the key numerical procedure determining the robustness, efficiency and scalability of the fully-coupled Newton-Krylov based, nonlinear solution method that is employed for this system of equations. The coupled system is comprised of a source term dominated Poisson equation for the electric potential, and two convection-diffusion-reaction type equations for the electron and hole concentration. The governing PDEs are discretized in space by a stabilized finite element method. Solution of the discrete system is obtained through a fully-implicit time integrator, a fully-coupled Newton-based nonlinear solver, and a restarted GMRES Krylov linear system solver. The algebraic multilevel preconditioner is based on an aggressive coarsening graph partitioning of the nonzero block structure of the Jacobian matrix. Representative performance results are presented for various choices of multigrid V-cycles and W-cycles and parameter variations for smoothers based on incomplete factorizations. Parallel scalability results are presented for solution of up to 10{sup 8} unknowns on 4096 processors of a Cray XT3/4 and an IBM POWER eServer system.
Performance of a parallel algebraic multilevel preconditioner for stabilized finite element semiconductor device modeling
NASA Astrophysics Data System (ADS)
Lin, Paul T.; Shadid, John N.; Sala, Marzio; Tuminaro, Raymond S.; Hennigan, Gary L.; Hoekstra, Robert J.
In this study results are presented for the large-scale parallel performance of an algebraic multilevel preconditioner for solution of the drift-diffusion model for semiconductor devices. The preconditioner is the key numerical procedure determining the robustness, efficiency and scalability of the fully-coupled Newton-Krylov based, nonlinear solution method that is employed for this system of equations. The coupled system is comprised of a source term dominated Poisson equation for the electric potential, and two convection-diffusion-reaction type equations for the electron and hole concentration. The governing PDEs are discretized in space by a stabilized finite element method. Solution of the discrete system is obtained through a fully-implicit time integrator, a fully-coupled Newton-based nonlinear solver, and a restarted GMRES Krylov linear system solver. The algebraic multilevel preconditioner is based on an aggressive coarsening graph partitioning of the nonzero block structure of the Jacobian matrix. Representative performance results are presented for various choices of multigrid V-cycles and W-cycles and parameter variations for smoothers based on incomplete factorizations. Parallel scalability results are presented for solution of up to 108 unknowns on 4096 processors of a Cray XT3/4 and an IBM POWER eServer system.
NASA Astrophysics Data System (ADS)
Kotulski, Zbigniew; Szczepaski, Janusz
In the paper we propose a new method of constructing cryptosystems utilising a nonpredictability property of discrete chaotic systems. We formulate the requirements for such systems to assure their safety. We also give examples of practical realisation of chaotic cryptosystems, using a generalisation of the method presented in [7]. The proposed algorithm of encryption and decryption is based on multiple iteration of a certain dynamical chaotic system. We assume that some part of the initial condition is a plain message. As the secret key we assume the system parameter(s) and additionally another part of the initial condition.
National INFOSEC technical baseline: multi-level secure systems
Anderson, J P
The purpose of this report is to provide a baseline description of the state of multilevel processor/processing to the INFOSEC Research Council and at their discretion to the R&D community at large. From the information in the report, it is hoped that the members of the IRC will be aware of gaps in MLS research. A primary purpose is to bring IRC and the research community members up to date on what is happening in the MLS arena. The review will attempt to cover what MLS products are still available, and to identify companies who still offer MLS products. We have also attempted to identify requirements for MLS by interviewing senior officers of the Intelligence community as well as those elements of DoD and DOE who are or may be interested in procuring MLS products for various applications. The balance of the report consists of the following sections; a background review of the highlights of the developments of MLS, a quick summary of where we are today in terms of products, installations, and companies who are still in the business of supplying MLS systems [or who are developing MLS system], the requirements as expressed by senior members of the Intelligence community and DoD and DOE, issues and unmet R&D challenges surrounding MLS, and finally a set of recommended research topics.
A global multilevel atmospheric model using a vector semi-Lagrangian finite-difference scheme. I - Adiabatic formulation
NASA Technical Reports Server (NTRS)
Bates, J. R.; Moorthi, S.; Higgins, R. W.
An adiabatic global multilevel primitive equation model using a two time-level, semi-Lagrangian semi-implicit finite-difference integration scheme is presented. A Lorenz grid is used for vertical discretization and a C grid for the horizontal discretization. The momentum equation is discretized in vector form, thus avoiding problems near the poles. The 3D model equations are reduced by a linear transformation to a set of 2D elliptic equations, whose solution is found by means of an efficient direct solver. The model (with minimal physics) is integrated for 10 days starting from an initialized state derived from real data. A resolution of 16 levels in the vertical is used, with various horizontal resolutions. The model is found to be stable and efficient, and to give realistic output fields. Integrations with time steps of 10 min, 30 min, and 1 h are compared, and the differences are found to be acceptable.
Pulse-modulated multilevel data storage in an organic ferroelectric resistive memory diode
Lee, Jiyoul; van Breemen, Albert J. J. M.; Khikhlovskyi, Vsevolod; Kemerink, Martijn; Janssen, Rene A. J.; Gelinck, Gerwin H.
We demonstrate multilevel data storage in organic ferroelectric resistive memory diodes consisting of a phase-separated blend of P(VDF-TrFE) and a semiconducting polymer. The dynamic behaviour of the organic ferroelectric memory diode can be described in terms of the inhomogeneous field mechanism (IFM) model where the ferroelectric components are regarded as an assembly of randomly distributed regions with independent polarisation kinetics governed by a time-dependent local field. This allows us to write and non-destructively read stable multilevel polarisation states in the organic memory diode using controlled programming pulses. The resulting 2-bit data storage per memory element doubles the storage density of the organic ferroelectric resistive memory diode without increasing its technological complexity, thus reducing the cost per bit. PMID:27080264
Pulse-modulated multilevel data storage in an organic ferroelectric resistive memory diode
NASA Astrophysics Data System (ADS)
Lee, Jiyoul; van Breemen, Albert J. J. M.; Khikhlovskyi, Vsevolod; Kemerink, Martijn; Janssen, Rene A. J.; Gelinck, Gerwin H.
We demonstrate multilevel data storage in organic ferroelectric resistive memory diodes consisting of a phase-separated blend of P(VDF-TrFE) and a semiconducting polymer. The dynamic behaviour of the organic ferroelectric memory diode can be described in terms of the inhomogeneous field mechanism (IFM) model where the ferroelectric components are regarded as an assembly of randomly distributed regions with independent polarisation kinetics governed by a time-dependent local field. This allows us to write and non-destructively read stable multilevel polarisation states in the organic memory diode using controlled programming pulses. The resulting 2-bit data storage per memory element doubles the storage density of the organic ferroelectric resistive memory diode without increasing its technological complexity, thus reducing the cost per bit.
Multilevel Mechanisms of Implementation Strategies in Mental Health: Integrating Theory, Research, and Practice.
Williams, Nathaniel J
A step toward the development of optimally effective, efficient, and feasible implementation strategies that increase evidence-based treatment integration in mental health services involves identification of the multilevel mechanisms through which these strategies influence implementation outcomes. This article (a) provides an orientation to, and rationale for, consideration of multilevel mediating mechanisms in implementation trials, and (b) systematically reviews randomized controlled trials that examined mediators of implementation strategies in mental health. Nine trials were located. Mediation-related methodological deficiencies were prevalent and no trials supported a hypothesized mediator. The most common reason was failure to engage the mediation target. Discussion focuses on directions to accelerate implementation strategy development in mental health. PMID:26474761
NASA Astrophysics Data System (ADS)
Calogero, Francesco
The original continuous-time ''goldfish'' dynamical system is characterized by two neat formulas, the first of which provides the N Newtonian equations of motion of this dynamical system, while the second provides the solution of the corresponding initial-value problem. Several other, more general, solvable dynamical systems ''of goldfish type'' have been identified over time, featuring, in the right-hand (''forces'') side of their Newtonian equations of motion, in addition to other contributions, a velocity-dependent term such as that appearing in the right-hand side of the first formula mentioned above. The solvable character of these models allows detailed analyses of their behavior, which in some cases is quite remarkable (for instance isochronous or asymptotically isochronous). In this paper we introduce and discuss various discrete-time dynamical systems, which are as well solvable, which also display interesting behaviors (including isochrony and asymptotic isochrony) and which reduce to dynamical systems of goldfish type in the limit when the discrete-time independent variable l=0,1,2,... becomes the standard continuous-time independent variable t, 0≤t<∞.
Discrete Pathophysiology is Uncommon in Patients with Nonspecific Arm Pain
Kortlever, Joost T.P.; Janssen, Stein J.; Molleman, Jeroen; Hageman, Michiel G.J.S.; Ring, David
Background: Nonspecific symptoms are common in all areas of medicine. Patients and caregivers can be frustrated when an illness cannot be reduced to a discrete pathophysiological process that corresponds with the symptoms. We therefore asked the following questions: 1) Which demographic factors and psychological comorbidities are associated with change from an initial diagnosis of nonspecific arm pain to eventual identification of discrete pathophysiology that corresponds with symptoms? 2) What is the percentage of patients eventually diagnosed with discrete pathophysiology, what are those pathologies, and do they account for the symptoms? Methods: We evaluated 634 patients with an isolated diagnosis of nonspecific upper extremity pain to see if discrete pathophysiology was diagnosed on subsequent visits to the same hand surgeon, a different hand surgeon, or any physician within our health system for the same pain. Results: There were too few patients with discrete pathophysiology at follow-up to address the primary study question. Definite discrete pathophysiology that corresponded with the symptoms was identified in subsequent evaluations by the index surgeon in one patient (0.16% of all patients) and cured with surgery (nodular fasciitis). Subsequent doctors identified possible discrete pathophysiology in one patient and speculative pathophysiology in four patients and the index surgeon identified possible discrete pathophysiology in four patients, but the five discrete diagnoses accounted for only a fraction of the symptoms. Conclusion: Nonspecific diagnoses are not harmful. Prospective randomized research is merited to determine if nonspecific, descriptive diagnoses are better for patients than specific diagnoses that imply pathophysiology in the absence of discrete verifiable pathophysiology. PMID:27517064
Noyes, H.P. ); Starson, S. )
Discrete physics, because it replaces time evolution generated by the energy operator with a global bit-string generator (program universe) and replaces fields'' with the relativistic Wheeler-Feynman action at a distance,'' allows the consistent formulation of the concept of signed gravitational charge for massive particles. The resulting prediction made by this version of the theory is that free anti-particles near the surface of the earth will fall'' up with the same acceleration that the corresponding particles fall down. So far as we can see, no current experimental information is in conflict with this prediction of our theory. The experiment crusis will be one of the anti-proton or anti-hydrogen experiments at CERN. Our prediction should be much easier to test than the small effects which those experiments are currently designed to detect or bound. 23 refs.
Discrete Sibson interpolation.
Park, Sung W; Linsen, Lars; Kreylos, Oliver; Owens, John D; Hamann, Bernd
Natural-neighbor interpolation methods, such as Sibson's method, are well-known schemes for multivariate data fitting and reconstruction. Despite its many desirable properties, Sibson's method is computationally expensive and difficult to implement, especially when applied to higher-dimensional data. The main reason for both problems is the method's implementation based on a Voronoi diagram of all data points. We describe a discrete approach to evaluating Sibson's interpolant on a regular grid, based solely on finding nearest neighbors and rendering and blending d-dimensional spheres. Our approach does not require us to construct an explicit Voronoi diagram, is easily implemented using commodity three-dimensional graphics hardware, leads to a significant speed increase compared to traditional approaches, and generalizes easily to higher dimensions. For large scattered data sets, we achieve two-dimensional (2D) interpolation at interactive rates and 3D interpolation (3D) with computation times of a few seconds. PMID:16509383
Discrete Pearson distributions
Bowman, K.O.; Shenton, L.R.; Kastenbaum, M.A.
These distributions are generated by a first order recursive scheme which equates the ratio of successive probabilities to the ratio of two corresponding quadratics. The use of a linearized form of this model will produce equations in the unknowns matched by an appropriate set of moments (assumed to exist). Given the moments we may find valid solutions. These are two cases; (1) distributions defined on the non-negative integers (finite or infinite) and (2) distributions defined on negative integers as well. For (1), given the first four moments, it is possible to set this up as equations of finite or infinite degree in the probability of a zero occurrence, the sth component being a product of s ratios of linear forms in this probability in general. For (2) the equation for the zero probability is purely linear but may involve slowly converging series; here a particular case is the discrete normal. Regions of validity are being studied. 11 refs.
Immigration and Prosecutorial Discretion
Apollonio, Dorie; Lochner, Todd; Heddens, Myriah
Immigration has become an increasingly salient national issue in the US, and the Department of Justice recently increased federal efforts to prosecute immigration offenses. This shift, however, relies on the cooperation of US attorneys and their assistants. Traditionally federal prosecutors have enjoyed enormous discretion and have been responsive to local concerns. To consider how the centralized goal of immigration enforcement may have influenced federal prosecutors in regional offices, we review their prosecution of immigration offenses in California using over a decade's worth of data. Our findings suggest that although centralizing forces influence immigration prosecutions, individual US attorneys' offices retain distinct characteristics. Local factors influence federal prosecutors' behavior in different ways depending on the office. Contrary to expectations, unemployment rates did not affect prosecutors' willingness to pursue immigration offenses, nor did local popular opinion about illegal immigration. PMID:26146530
Discrete stability in stochastic programming
Lepp, R.
In this lecture we study stability properties of stochastic programs with recourse where the probability measure is approximated by a sequence of weakly convergent discrete measures. Such discrete approximation approach gives us a possibility to analyze explicitly the behavior of the second stage correction function. The approach is based on modern functional analytical methods of an approximation of extremum problems in function spaces, especially on the notion of the discrete convergence of vectors to an essentially bounded measurable function.
Translating multilevel theory into multilevel research: Challenges and opportunities for understanding the social determinants of psychiatric disorders
Dunn, Erin C.; Masyn, Katherine E.; Yudron, Monica; Jones, Stephanie M.; Subramanian, S.V.
The observation that features of the social environment, including family, school, and neighborhood characteristics, are associated with individual-level outcomes has spurred the development of dozens of multilevel or ecological theoretical frameworks in epidemiology, public health, psychology, and sociology, among other disciplines. Despite the widespread use of such theories in etiological, intervention, and policy studies, challenges remain in bridging multilevel theory and empirical research. This paper set out to synthesize these challenges and provide specific examples of methodological and analytical strategies researchers are using to gain a more nuanced understanding of the social determinants of psychiatric disorders, with a focus on children's mental health. To accomplish this goal, we begin by describing multilevel theories, defining their core elements, and discussing what these theories suggest is needed in empirical work. In the second part, we outline the main challenges researchers face in translating multilevel theory into research. These challenges are presented for each stage of the research process. In the third section, we describe two methods being used as alternatives to traditional multilevel modeling techniques to better bridge multilevel theory and multilevel research. These are: (1) multilevel factor analysis and multilevel structural equation modeling; and (2) dynamic systems approaches. Through its review of multilevel theory, assessment of existing strategies, and examination of emerging methodologies, this paper offers a framework to evaluate and guide empirical studies on the social determinants of child psychiatric disorders as well as health across the lifecourse. PMID:24469555
Computational modeling and multilevel cancer control interventions.
Morrissey, Joseph P; Lich, Kristen Hassmiller; Price, Rebecca Anhang; Mandelblatt, Jeanne
This chapter presents an overview of computational modeling as a tool for multilevel cancer care and intervention research. Model-based analyses have been conducted at various "beneath the skin" or biological scales as well as at various "above the skin" or socioecological levels of cancer care delivery. We review the basic elements of computational modeling and illustrate its applications in four cancer control intervention areas: tobacco use, colorectal cancer screening, cervical cancer screening, and racial disparities in access to breast cancer care. Most of these models have examined cancer processes and outcomes at only one or two levels. We suggest ways these models can be expanded to consider interactions involving three or more levels. Looking forward, a number of methodological, structural, and communication barriers must be overcome to create useful computational models of multilevel cancer interventions and population health. PMID:22623597
Multilevel Inverters for Electric Vehicle Applications
Habetler, T.G.; Peng, F.Z.; Tolbert, L.M.
This paper presents multilevel inverters as an application for all-electric vehicle (EV) and hybrid-electric vehicle (HEV) motor drives. Diode-clamped inverters and cascaded H-bridge inverters, (1) can generate near-sinusoidal voltages with only fundamental frequency switching; (2) have almost no electromagnetic interference (EMI) and common-mode voltage; and (3) make an EV more accessible/safer and open wiring possible for most of an EV'S power system. This paper explores the benefits and discusses control schemes of the cascade inverter for use as an EV motor drive or a parallel HEV drive and the diode-clamped inverter as a series HEV motor drive. Analytical, simulated, and experimental results show the superiority of these multilevel inverters for this new niche.
Extended digital image correlation method for analysis of discrete discontinuity
NASA Astrophysics Data System (ADS)
Deb, Debasis; Bhattacharjee, Sudipta
Finite element based multilevel extended digital image correlation (X-DIC) method is applied to obtain displacement distribution of an object having a discrete discontinuity. The principle of multilevel X-DIC method is described in the paper and results are verified using numerically generated images. The deformed images are developed with a pre-existing discontinuity surface across the image for tensile or shear displacements or rotations. Several cubical rock samples are also compressed under uniaxial loading conditions until fractures are developed in the post-failure region. Images of a speckled face of this experiment are analyzed using the proposed X-DIC method with increment of loading for determination of displacement before and after cracks are developed in the sample. The results of this study show that X-DIC technique is capable of capturing damaged zone(s) and displacement jump across the discontinuity plane as well as indicating the onset of failure of rock sample. This method demonstrates the applicability to investigate object failure mechanism for the entire surface of the sample in a non-contact manner.
Automatic Multilevel Parallelization Using OpenMP
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Jost, Gabriele; Yan, Jerry; Ayguade, Eduard; Gonzalez, Marc; Martorell, Xavier; Biegel, Bryan (Technical Monitor)
In this paper we describe the extension of the CAPO parallelization support tool to support multilevel parallelism based on OpenMP directives. CAPO generates OpenMP directives with extensions supported by the NanosCompiler to allow for directive nesting and definition of thread groups. We report first results for several benchmark codes and one full application that have been parallelized using our system.
Automatic Multilevel Parallelization Using OpenMP
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Jost, Gabriele; Yan, Jerry; Ayguade, Eduard; Gonzalez, Marc; Martorell, Xavier; Biegel, Bryan (Technical Monitor)
In this paper we describe the extension of the CAPO (CAPtools (Computer Aided Parallelization Toolkit) OpenMP) parallelization support tool to support multilevel parallelism based on OpenMP directives. CAPO generates OpenMP directives with extensions supported by the NanosCompiler to allow for directive nesting and definition of thread groups. We report some results for several benchmark codes and one full application that have been parallelized using our system.
Voltage balanced multilevel voltage source converter system
Peng, F.Z.; Lai, J.S.
Disclosed is a voltage balanced multilevel converter for high power AC applications such as adjustable speed motor drives and back-to-back DC intertie of adjacent power systems. This converter provides a multilevel rectifier, a multilevel inverter, and a DC link between the rectifier and the inverter allowing voltage balancing between each of the voltage levels within the multilevel converter. The rectifier is equipped with at least one phase leg and a source input node for each of the phases. The rectifier is further equipped with a plurality of rectifier DC output nodes. The inverter is equipped with at least one phase leg and a load output node for each of the phases. The inverter is further equipped with a plurality of inverter DC input nodes. The DC link is equipped with a plurality of rectifier charging means and a plurality of inverter discharging means. The plurality of rectifier charging means are connected in series with one of the rectifier charging means disposed between and connected in an operable relationship with each adjacent pair of rectifier DC output nodes. The plurality of inverter discharging means are connected in series with one of the inverter discharging means disposed between and connected in an operable relationship with each adjacent pair of inverter DC input nodes. Each of said rectifier DC output nodes are individually electrically connected to the respective inverter DC input nodes. By this means, each of the rectifier DC output nodes and each of the inverter DC input nodes are voltage balanced by the respective charging and discharging of the rectifier charging means and the inverter discharging means. 15 figs.
Voltage balanced multilevel voltage source converter system
Peng, Fang Zheng; Lai, Jih-Sheng
A voltage balanced multilevel converter for high power AC applications such as adjustable speed motor drives and back-to-back DC intertie of adjacent power systems. This converter provides a multilevel rectifier, a multilevel inverter, and a DC link between the rectifier and the inverter allowing voltage balancing between each of the voltage levels within the multilevel converter. The rectifier is equipped with at least one phase leg and a source input node for each of the phases. The rectifier is further equipped with a plurality of rectifier DC output nodes. The inverter is equipped with at least one phase leg and a load output node for each of the phases. The inverter is further equipped with a plurality of inverter DC input nodes. The DC link is equipped with a plurality of rectifier charging means and a plurality of inverter discharging means. The plurality of rectifier charging means are connected in series with one of the rectifier charging means disposed between and connected in an operable relationship with each adjacent pair of rectifier DC output nodes. The plurality of inverter discharging means are connected in series with one of the inverter discharging means disposed between and connected in an operable relationship with each adjacent pair of inverter DC input nodes. Each of said rectifier DC output nodes are individually electrically connected to the respective inverter DC input nodes. By this means, each of the rectifier DC output nodes and each of the inverter DC input nodes are voltage balanced by the respective charging and discharging of the rectifier charging means and the inverter discharging means.
On the effectiveness of multilevel selection.
Goodnight, Charles J
Experimental studies of group selection show that higher levels of selection act on indirect genetic effects, making the response to group and community selection qualitatively different from that of individual selection. This suggests that multilevel selection plays a key role in the evolution of supersocial societies. Experiments showing the effectiveness of community selection indicate that we should consider the possibility that selection among communities may be important in the evolution of supersocial species. PMID:27562604
Multilevel sparse functional principal component analysis.
Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S
We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions. PMID:24872597
Multilevel sparse functional principal component analysis
Di, Chongzhi; Crainiceanu, Ciprian M.; Jank, Wolfgang S.
We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions. PMID:24872597
Fluctuations and discreteness in diffusion limited growth
NASA Astrophysics Data System (ADS)
Devita, Jason P.
This thesis explores the effects of fluctuations and discreteness on the growth of physical systems where diffusion plays an important role. It focuses on three related problems, all dependent on diffusion in a fundamental way, but each with its own unique challenges. With diffusion-limited aggregation (DLA), the relationship between noisy and noise-free Laplacian growth is probed by averaging the results of noisy growth. By doing so in a channel geometry, we are able to compare to known solutions of the noise-free problem. We see that while the two are comparable, there are discrepancies which are not well understood. In molecular beam epitaxy (MBE), we create efficient computational algorithms, by replacing random walkers (diffusing atoms) with approximately equivalent processes. In one case, the atoms are replaced by a continuum field. Solving for the dynamics of the field yields---in an average sense---the dynamics of the atoms. In the other case, the atoms are treated as individual random-walking particles, but the details of the dynamics are changed to an (approximately) equivalent set of dynamics. This approach involves allowing adatoms to take long hops. We see approximately an order of magnitude speed up for simulating island dynamics, mound growth, and Ostwald ripening. Some ideas from the study of MBE are carried over to the study of front propagation in reaction-diffusion systems. Many of the analytic results about front propagation are derived from continuum models. It is unclear, however, that these results accurately describe the properties of a discrete system. It is reasonable to think that discrete systems will converge to the continuum results when sufficiently many particles are included. However, computational evidence of this is difficult to obtain, since the interesting properties tend to depend on a power law of the logarithm of the number of particles. Thus, the number of particles included in simulations must be exceedingly large. By
Analysis of stochastic effects in Kaldor-type business cycle discrete model
NASA Astrophysics Data System (ADS)
Bashkirtseva, Irina; Ryashko, Lev; Sysolyatina, Anna
We study nonlinear stochastic phenomena in the discrete Kaldor model of business cycles. A numerical parametric analysis of stochastically forced attractors (equilibria, closed invariant curves, discrete cycles) of this model is performed using the stochastic sensitivity functions technique. A spatial arrangement of random states in stochastic attractors is modeled by confidence domains. The phenomenon of noise-induced transitions "chaos-order" is discussed.
Discrete Mathematics and Curriculum Reform.
ERIC Educational Resources Information Center
Kenney, Margaret J.
Defines discrete mathematics as the mathematics necessary to effect reasoned decision making in finite situations and explains how its use supports the current view of mathematics education. Discrete mathematics can be used by curriculum developers to improve the curriculum for students of all ages and abilities. (SLD)
Discrete Mathematics and Its Applications
ERIC Educational Resources Information Center
Oxley, Alan
The article gives ideas that lecturers of undergraduate Discrete Mathematics courses can use in order to make the subject more interesting for students and encourage them to undertake further studies in the subject. It is possible to teach Discrete Mathematics with little or no reference to computing. However, students are more likely to be…
Continuous limit of discrete quantum walks
NASA Astrophysics Data System (ADS)
M N, Dheeraj; Brun, Todd A.
Quantum walks can be defined in two quite distinct ways: discrete-time and continuous-time quantum walks (DTQWs and CTQWs). For classical random walks, there is a natural sense in which continuous-time walks are a limit of discrete-time walks. Quantum mechanically, in the discrete-time case, an additional "coin space" must be appended for the walk to have nontrivial time evolution. Continuous-time quantum walks, however, have no such constraints. This means that there is no completely straightforward way to treat a CTQW as a limit of a DTQW, as can be done in the classical case. Various approaches to this problem have been taken in the past. We give a construction for walks on d -regular, d -colorable graphs when the coin flip operator is Hermitian: from a standard DTQW we construct a family of discrete-time walks with a well-defined continuous-time limit on a related graph. One can think of this limit as a "coined" continuous-time walk. We show that these CTQWs share some properties with coined DTQWs. In particular, we look at a spatial search by a DTQW over the two-dimensional (2D) torus (a grid with periodic boundary conditions) of size √{N }×√{N } , where it was shown that a coined DTQW can search in time O (√{N }logN ) , but a standard CTQW takes Ω (N ) time to search for a marked element. The continuous limit of the DTQW search over the 2D torus exhibits the O (√{N }logN ) scaling, like the coined walk it is derived from. We also look at the effects of graph symmetry on the limiting walk, and show that the properties are similar to those of the DTQW as shown in Krovi and Brun, Phys. Rev. A 75, 062332 (2007), 10.1103/PhysRevA.75.062332.
Interventional tool tracking using discrete optimization.
Heibel, Hauke; Glocker, Ben; Groher, Martin; Pfister, Marcus; Navab, Nassir
This work presents a novel scheme for tracking of motion and deformation of interventional tools such as guide-wires and catheters in fluoroscopic X-ray sequences. Being able to track and thus to estimate the correct positions of these tools is crucial in order to offer guidance enhancement during interventions. The task of estimating the apparent motion is particularly challenging due to the low signal-to-noise ratio (SNR) of fluoroscopic images and due to combined motion components originating from patient breathing and tool interactions performed by the physician. The presented approach is based on modeling interventional tools with B-splines whose optimal configuration of control points is determined through efficient discrete optimization. Each control point corresponds to a discrete random variable in a Markov random field (MRF) formulation where a set of labels represents the deformation space. In this context, the optimal curve corresponds to the maximum a posteriori (MAP) estimate of the MRF energy. The main motivation for employing a discrete approach is the possibility to incorporate a multi-directional search space which is robust to local minima. This is of particular interest for curve tracking under large deformation. This work analyzes feasibility of employing efficient first-order MRFs for tracking. In particular it shows how to achieve a good compromise between energy approximations and computational efficiency. Experimental results suggest to define both the external and internal energy in terms of pairwise potential functions. The method was successfully applied to the tracking of guide-wires in fluoroscopic X-ray sequences of several hundred frames which requires extremely robust techniques. Comparisons with state-of-the-art guide-wire tracking algorithms confirm the effectiveness of the proposed method. PMID:23232412
Resistance controllability and variability improvement in a TaO{sub x}-based resistive memory for multilevel storage application
Prakash, A. E-mail: email@example.com Song, J.; Hwang, H. E-mail: email@example.com; Deleruyelle, D.; Bocquet, M.
In order to obtain reliable multilevel cell (MLC) characteristics, resistance controllability between the different resistance levels is required especially in resistive random access memory (RRAM), which is prone to resistance variability mainly due to its intrinsic random nature of defect generation and filament formation. In this study, we have thoroughly investigated the multilevel resistance variability in a TaO{sub x}-based nanoscale (<30 nm) RRAM operated in MLC mode. It is found that the resistance variability not only depends on the conductive filament size but also is a strong function of oxygen vacancy concentration in it. Based on the gained insights through experimental observations and simulation, it is suggested that forming thinner but denser conductive filament may greatly improve the temporal resistance variability even at low operation current despite the inherent stochastic nature of resistance switching process.
A Multilevel-Based Study of School Policy for Tobacco Control in Relation to Cigarette Smoking among Children in Elementary Schools: Gender Differences
ERIC Educational Resources Information Center
Huang, Hsiao-Ling; Chen, Fu-Li; Hsu, Chih-Cheng; Yen, Yea-Yin; Chen, Ted; Huang, Cheng-Ming; Shi, Hon-Yi; Hu, Chih-Yang; Lee, Chien-Hung
The aim was to comprehensively examine school-based tobacco policy status, implementation and students' perceived smoking at school in regard to gender-specific differences in smoking behavior. We conducted a multilevel-based study to assess two-level effects for smoking among 2350 grades three to six students in 26 randomly selected elementary…
Estimation of Indirect Effects in the Presence of Unmeasured Confounding for the Mediator-Outcome Relationship in a Multilevel 2-1-1 Mediation Model
ERIC Educational Resources Information Center
Talloen, Wouter; Moerkerke, Beatrijs; Loeys, Tom; De Naeghel, Jessie; Van Keer, Hilde; Vansteelandt, Stijn
To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within…
Huang, Z. )
We examine an interesting scenario to solve the domain-wall problem recently suggested by Preskill, Trivedi, Wilczek, and Wise. The effective potential is calculated in the presence of the QCD axial anomaly. It is shown that some discrete symmetries such as {ital CP} and {ital Z}{sub 2} can be anomalous due to a so-called {ital K} term induced by instantons. We point out that the {ital Z}{sub 2} domain-wall problem in the two-doublet standard model can be resolved by two types of solutions: the {ital CP}-conserving one and the {ital CP}-breaking one. In the first case, there exist two {ital Z}{sub 2}-related local minima whose energy splitting is provided by the instanton effect. In the second case, there is only one unique vacuum so that the domain walls do not form at all. The consequences of this new source of {ital CP} violation are discussed and shown to be well within the experimental limits in weak interactions.
Khan, M M; Varma, M P; Cleland, J; O'Kane, H O; Webb, S W; Mulholland, H C; Adgey, A A
Data concerning 17 consecutive patients with discrete subaortic stenosis are recorded. Twelve patients underwent operative resection of the obstructing lesion. Of these all except one were symptomatic and all had electrocardiographic evidence of left ventricular hypertrophy or left ventricular hypertrophy with strain. They had a peak resting systolic left ventricular outflow tract gradient of greater than 50 mmHg as predicted from the combined cuff measurement of systolic blood pressure and the echocardiographically estimated left ventricular systolic pressure and/or as determined by cardiac catheterisation. The outflow tract gradient as predicted from M-mode echocardiography and peak systolic pressure showed close correlation with that measured at cardiac catheterisation or operation. During the postoperative follow-up from one month to 11 years, of 11 patients, one patient required a further operation for recurrence of the obstruction four years after the initial operation. All patients are now asymptomatic. Five patients have not had an operation. The left ventricular outflow tract gradient as assessed at the time of cardiac catheterisation was greater than 50 mmHg. One patient has been lost to follow-up. The remaining four have been followed from four to eight years and have remained asymptomatic and the electrocardiograms have remained unchanged. Careful follow-up of all patients is essential with continuing clinical assessment, electrocardiograms, M-mode and two-dimensional echocardiograms, and if necessary cardiac catheterisation. Prophylaxis against bacterial endocarditis is also essential. Images PMID:6457617
Direct molecular identification of Trypanosoma cruzi Discrete Typing Units in domestic and peridomestic Triatoma infestans and Triatoma sordida from the Argentine Chaco
SUMMARY We assessed the distribution of Trypanosoma cruzi Discrete Typing Units (DTUs) in domestic and peridomestic Triatoma infestans and Triatoma sordida specimens collected in a well-defined rural area in Pampa del Indio, northeastern Argentina. Microscopically-positive bugs were randomly selected with a multi-level sampling design, and DTUs were identified using direct PCR strategies. TcVI predominated in 61% of 69 T. infestans and in 56% of 9 T. sordida. TcV was the secondary DTU in T. infestans (16%) and was found in one T. sordida specimen (11%). Three T. sordida (33%) were found infected with TcI, a DTU also identified in local Didelphis albiventris opossums. Mixed DTU infections occurred rarely (5%) and were detected both directly from the bugs' rectal ampoule and parasite cultures. The identified DTUs and bug collection sites of T. infestans were significantly associated. Bugs infected with TcV were almost exclusively captured in domiciles whereas those with TcVI were found similarly in domiciles and peridomiciles. All mixed infections occurred in domiciles. TcV-infected bugs fed more often on humans than on dogs, whereas TcVI-infected bugs showed the reverse pattern. T. sordida is a probable sylvatic vector of TcI linked to D. albiventris, and could represent a secondary vector of TcVI and TcV in the domestic/peridomestic cycle. PMID:23036510
Alternatives to Multilevel Modeling for the Analysis of Clustered Data
ERIC Educational Resources Information Center
Huang, Francis L.
Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…
Matching Strategies for Observational Data with Multilevel Structure
ERIC Educational Resources Information Center
Steiner, Peter M.
Given the different possibilities of matching in the context of multilevel data and the lack of research on corresponding matching strategies, the author investigates two main research questions. The first research question investigates the advantages and disadvantages of different matching strategies that can be pursued with multilevel data…
A Multilevel Analysis of Parental Discipline and Child Antisocial Behavior
ERIC Educational Resources Information Center
Stoolmiller, Mike; Snyder, Jim
We demonstrate graphical and analytical methods for multilevel (2- and 3-level) models using the analysis of observed microsocial interaction between parent-child dyads as an example. We also present multilevel path diagrams and argue that while not as compact as equations, path diagrams may communicate results better to a wider audience. The…
Multilevel Higher-Order Item Response Theory Models
ERIC Educational Resources Information Center
Huang, Hung-Yu; Wang, Wen-Chung
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
How does psychotherapy work? A case study in multilevel explanation.
Roache, Rebecca
Multilevel explanations abound in psychiatry. However, formulating useful such explanations is difficult or (some argue) impossible. I point to several ways in which Lane et al. successfully use multilevel explanations to advance understanding of psychotherapeutic effectiveness. I argue that the usefulness of an explanation depends largely on one's purpose, and conclude that this point has been inadequately recognised in psychiatry. PMID:26050687
The discrete variational derivative method based on discrete differential forms
NASA Astrophysics Data System (ADS)
Yaguchi, Takaharu; Matsuo, Takayasu; Sugihara, Masaaki
As is well known, for PDEs that enjoy a conservation or dissipation property, numerical schemes that inherit this property are often advantageous in that the schemes are fairly stable and give qualitatively better numerical solutions in practice. Lately, Furihata and Matsuo have developed the so-called "discrete variational derivative method" that automatically constructs energy preserving or dissipative finite difference schemes. Although this method was originally developed on uniform meshes, the use of non-uniform meshes is of importance for multi-dimensional problems. On the other hand, the theories of discrete differential forms have received much attention recently. These theories provide a discrete analogue of the vector calculus on general meshes. In this paper, we show that the discrete variational derivative method and the discrete differential forms by Bochev and Hyman can be combined. Applications to the Cahn-Hilliard equation and the Klein-Gordon equation on triangular meshes are provided as demonstrations. We also show that the schemes for these equations are H1-stable under some assumptions. In particular, one for the nonlinear Klein-Gordon equation is obtained by combination of the energy conservation property and the discrete Poincaré inequality, which are the temporal and spacial structures that are preserved by the above methods.
Understanding Statistical Power in Cluster Randomized Trials: Challenges Posed by Differences in Notation and Terminology
ERIC Educational Resources Information Center
Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael
Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…
Evolution of neuroarchitecture, multi-level analyses and calibrative reductionism
Berntson, Gary G.; Norman, Greg J.; Hawkley, Louise C.; Cacioppo, John T.
Evolution has sculpted the incredibly complex human nervous system, among the most complex functions of which extend beyond the individual to an intricate social structure. Although these functions are deterministic, those determinants are legion, heavily interacting and dependent on a specific evolutionary trajectory. That trajectory was directed by the adaptive significance of quasi-random genetic variations, but was also influenced by chance and caprice. With a different evolutionary pathway, the same neural elements could subserve functions distinctly different from what they do in extant human brains. Consequently, the properties of higher level neural networks cannot be derived readily from the properties of the lower level constituent elements, without studying these elements in the aggregate. Thus, a multi-level approach to integrative neuroscience may offer an optimal strategy. Moreover, the process of calibrative reductionism, by which concepts and understandings from one level of organization or analysis can mutually inform and 'calibrate' those from other levels (both higher and lower), may represent a viable approach to the application of reductionism in science. This is especially relevant in social neuroscience, where the basic subject matter of interest is defined by interacting organisms across diverse environments. PMID:23386961
Evolution of neuroarchitecture, multi-level analyses and calibrative reductionism.
Berntson, Gary G; Norman, Greg J; Hawkley, Louise C; Cacioppo, John T
Evolution has sculpted the incredibly complex human nervous system, among the most complex functions of which extend beyond the individual to an intricate social structure. Although these functions are deterministic, those determinants are legion, heavily interacting and dependent on a specific evolutionary trajectory. That trajectory was directed by the adaptive significance of quasi-random genetic variations, but was also influenced by chance and caprice. With a different evolutionary pathway, the same neural elements could subserve functions distinctly different from what they do in extant human brains. Consequently, the properties of higher level neural networks cannot be derived readily from the properties of the lower level constituent elements, without studying these elements in the aggregate. Thus, a multi-level approach to integrative neuroscience may offer an optimal strategy. Moreover, the process of calibrative reductionism, by which concepts and understandings from one level of organization or analysis can mutually inform and 'calibrate' those from other levels (both higher and lower), may represent a viable approach to the application of reductionism in science. This is especially relevant in social neuroscience, where the basic subject matter of interest is defined by interacting organisms across diverse environments. PMID:23386961
Exact discretization by Fourier transforms
NASA Astrophysics Data System (ADS)
Tarasov, Vasily E.
A discretization of differential and integral operators of integer and non-integer orders is suggested. New type of differences, which are represented by infinite series, is proposed. A characteristic feature of the suggested differences is an implementation of the same algebraic properties that have the operator of differentiation (property of algebraic correspondence). Therefore the suggested differences are considered as an exact discretization of derivatives. These differences have a property of universality, which means that these operators do not depend on the form of differential equations and the parameters of these equations. The suggested differences operators allows us to have difference equations whose solutions are equal to the solutions of corresponding differential equations. The exact discretization of the derivatives of integer orders is given by the suggested differences of the same integer orders. Similarly, the exact discretization of the Riesz derivatives and integrals of integer and non-integer order is given by the proposed fractional differences of the same order.
Novel approach to data discretization
NASA Astrophysics Data System (ADS)
Borowik, Grzegorz; Kowalski, Karol; Jankowski, Cezary
Discretization is an important preprocessing step in data mining. The data discretization method involves determining the ranges of values for numeric attributes, which ultimately represent discrete intervals for new attributes. The ranges for the proposed set of cuts are analyzed, in order to obtain a minimal set of ranges while retaining the possibility of classification. For this purpose, a special discernibility function can be constructed as a conjunction of alternative cuts set for each pair of different objects of different decisions- cuts discern these objects. However, the data mining methods based on discernibility matrix are insufficient for large databases. The purpose of this paper is the idea of implementation of a new data discretization algorithm that is based on statistics of attribute values and that avoids building the discernibility matrix explicitly. Evaluation of time complexity has shown that the proposed method is much more efficient than currently available solutions for large data sets.
Chaos in Periodic Discrete Systems
NASA Astrophysics Data System (ADS)
Shi, Yuming; Zhang, Lijuan; Yu, Panpan; Huang, Qiuling
This paper focuses on chaos in periodic discrete systems, whose state space may vary with time. Some close relationships between some chaotic dynamical behaviors of a periodic discrete system and its autonomous induced system are given. Based on these relationships, several criteria of chaos are established and some sufficient conditions for no chaos are given for periodic discrete systems. Further, it is shown that a finite-dimensional linear periodic discrete system is not chaotic in the sense of Li-Yorke or Wiggins. In particular, an interesting problem of whether nonchaotic rules may generate a chaotic system is studied, with some examples provided, one of which surprisingly shows that a composition of globally asymptotically stable maps can be chaotic. In addition, some properties of sign pattern matrices of non-negative square matrices are given for convenience of the study.
Microscopic derivation of discrete hydrodynamics.
Español, Pep; Anero, Jesús G; Zúñiga, Ignacio
By using the standard theory of coarse graining based on Zwanzig's projection operator, we derive the dynamic equations for discrete hydrodynamic variables. These hydrodynamic variables are defined in terms of the Delaunay triangulation. The resulting microscopically derived equations can be understood, a posteriori, as a discretization on an arbitrary irregular grid of the Navier-Stokes equations. The microscopic derivation provides a set of discrete equations that exactly conserves mass, momentum, and energy and the dissipative part of the dynamics produces strict entropy increase. In addition, the microscopic derivation provides a practical implementation of thermal fluctuations in a way that the fluctuation-dissipation theorem is satisfied exactly. This paper points toward a close connection between coarse-graining procedures from microscopic dynamics and discretization schemes for partial differential equations. PMID:20059064
Ambient changes in tracer concentrations from a multilevel monitoring system in Basalt
Bartholomay, Roy C.; Twining, Brian V.; Rose, Peter E.
Starting in 2008, a 4-year tracer study was conducted to evaluate ambient changes in groundwater concentrations of a 1,3,6-naphthalene trisulfonate tracer that was added to drill water. Samples were collected under open borehole conditions and after installing a multilevel groundwater monitoring system completed with 11 discrete monitoring zones within dense and fractured basalt and sediment layers in the eastern Snake River aquifer. The study was done in cooperation with the U.S. Department of Energy to test whether ambient fracture flow conditions were sufficient to remove the effects of injected drill water prior to sample collection. Results from thief samples indicated that the tracer was present in minor concentrations 28 days after coring, but was not present 6 months after coring or 7 days after reaming the borehole. Results from sampling the multilevel monitoring system indicated that small concentrations of the tracer remained in 5 of 10 zones during some period after installation. All concentrations were several orders of magnitude lower than the initial concentrations in the drill water. The ports that had remnant concentrations of the tracer were either located near sediment layers or were located in dense basalt, which suggests limited groundwater flow near these ports. The ports completed in well-fractured and vesicular basalt had no detectable concentrations.
NASA Astrophysics Data System (ADS)
Cooper, Colin; Frieze, Alan
The aim of this article is to discuss some of the notions and applications of random walks on finite graphs, especially as they apply to random graphs. In this section we give some basic definitions, in Section 2 we review applications of random walks in computer science, and in Section 3 we focus on walks in random graphs.
Multilevel Risk Models for Retrospective Age-of-Onset Data: School Children's First Cigarette.
ERIC Educational Resources Information Center
Pickles, Andrew; Pickering, Kevin; Taylor, Colin; Sutton, Stephen; Yang, Shuying
Describes a random effects discrete time survival model that addresses problems of measurement error and sample design complexities. Demonstrates the effectiveness of the model in an analysis of retrospective report data on the age of onset of smoking from two cross-sectional school-based studies. (JPB)
Hybrid multilevel sparse reconstruction for a whole domain bioluminescence tomography using adaptive finite element.
Yu, Jingjing; He, Xiaowei; Geng, Guohua; Liu, Fang; Jiao, L C
Quantitative reconstruction of bioluminescent sources from boundary measurements is a challenging ill-posed inverse problem owing to the high degree of absorption and scattering of light through tissue. We present a hybrid multilevel reconstruction scheme by combining the ability of sparse regularization with the advantage of adaptive finite element method. In view of the characteristics of different discretization levels, two different inversion algorithms are employed on the initial coarse mesh and the succeeding ones to strike a balance between stability and efficiency. Numerical experiment results with a digital mouse model demonstrate that the proposed scheme can accurately localize and quantify source distribution while maintaining reconstruction stability and computational economy. The effectiveness of this hybrid reconstruction scheme is further confirmed with in vivo experiments. PMID:23533542
Implementation of Hybrid V-Cycle Multilevel Methods for Mixed Finite Element Systems with Penalty
NASA Technical Reports Server (NTRS)
Lai, Chen-Yao G.
The goal of this paper is the implementation of hybrid V-cycle hierarchical multilevel methods for the indefinite discrete systems which arise when a mixed finite element approximation is used to solve elliptic boundary value problems. By introducing a penalty parameter, the perturbed indefinite system can be reduced to a symmetric positive definite system containing the small penalty parameter for the velocity unknown alone. We stabilize the hierarchical spatial decomposition approach proposed by Cai, Goldstein, and Pasciak for the reduced system. We demonstrate that the relative condition number of the preconditioner is bounded uniformly with respect to the penalty parameter, the number of levels and possible jumps of the coefficients as long as they occur only across the edges of the coarsest elements.
Lasing and transport in a multilevel double quantum dot system coupled to a microwave oscillator
NASA Astrophysics Data System (ADS)
Karlewski, Christian; Heimes, Andreas; Schön, Gerd
We study a system of two quantum dots, each with several discrete levels, which are coherently coupled to a microwave oscillator. They are attached to electronic leads and coupled to a phonon bath, both leading to inelastic processes. For a simpler system with a single level in each dot it has been shown that a population inversion can be created by electron tunneling, which in a resonance situation leads to lasing-type properties of the oscillator. In the multilevel system several resonance situations may arise, some of them relying on a sequence of tunneling processes which also involve nonresonant, inelastic transitions. The resulting photon number in the oscillator and the current-voltage characteristic are highly sensitive to these properties and accordingly can serve as a probe for microscopic details.
Multilevel-3D Bit Patterned Magnetic Media with 8 Signal Levels Per Nanocolumn
Amos, Nissim; Butler, John; Lee, Beomseop; Shachar, Meir H.; Hu, Bing; Tian, Yuan; Hong, Jeongmin; Garcia, Davil; Ikkawi, Rabee M.; Haddon, Robert C.; Litvinov, Dmitri; Khizroev, Sakhrat
This letter presents an experimental study that shows that a 3rd physical dimension may be used to further increase information packing density in magnetic storage devices. We demonstrate the feasibility of at least quadrupling the magnetic states of magnetic-based data storage devices by recording and reading information from nanopillars with three magnetically-decoupled layers. Magneto-optical Kerr effect microscopy and magnetic force microscopy analysis show that both continuous (thin film) and patterned triple-stack magnetic media can generate eight magnetically-stable states. This is in comparison to only two states in conventional magnetic recording. Our work further reveals that ferromagnetic interaction between magnetic layers can be reduced by combining Co/Pt and Co/Pd multilayers media. Finally, we are showing for the first time an MFM image of multilevel-3D bit patterned media with 8 discrete signal levels. PMID:22808105
Multilevel converters for large electric drives
Tolbert, L.M.; Peng, F.Z.
Traditional two-level high frequency pulse width modulation (PWM) inverters for motor drives have several problems associated with their high frequency switching which produces common-mode voltage and high voltage change (dV/dt) rates to the motor windings. Multilevel inverters solve these problems because their devices can switch at a much lower frequency. Two different multilevel topologies are identified for use as a converter for electric drives, a cascade inverter with separate dc sources and a back-to-back diode clamped converter. The cascade inverter is a natural fit for large automotive all electric drives because of the high VA ratings possible and because it uses several levels of dc voltage sources which would be available from batteries or fuel cells. The back to back diode damped converter is ideal where a source of ac voltage is available such as a hybrid electric vehicle. Simulation and experimental results show the superiority of these two converters over PWM based drives.
The treatment for multilevel noncontiguous spinal fractures
Lian, Xiao Feng; Hou, Tie Sheng; Yuan, Jian Dong; Jin, Gen Yang; Li, Zhong Hai
We report the outcome of 30 patients with multilevel noncontiguous spinal fractures treated between 2000 and 2005. Ten cases were treated conservatively (group A), eight cases were operated on at only one level (group B), and 12 cases were treated surgically at both levels (group C). All cases were followed up for 14–60 months (mean 32 months). Initial mobilisation with a wheelchair or crutches in group A was 9.2±1.1 weeks, which was significantly longer than groups B and C with 6.8±0.7 weeks and 3.1±0.4 weeks, respectively. Operative time and blood loss in group C were significantly more than group B. The neurological deficit improved in six cases in group A (60%), six in group B (75%) and eight in group C (80%). Correction of kyphotic deformity was significantly superior in groups C and B at the operated level, and increasing deformity occurred in groups A and B at the non-operated level. From the results we believe that three treatment strategies were suitable for multilevel noncontiguous spinal fractures, and individualised treatment should be used in these patients. In the patients treated surgically, the clinical and radiographic outcomes are much better. PMID:17043863
Discrete analysis of stochastic NMR.II
NASA Astrophysics Data System (ADS)
Wong, S. T. S.; Rods, M. S.; Newmark, R. D.; Budinger, T. F.
Stochastic NMR is an efficient technique for high-field in vivo imaging and spectroscopic studies where the peak RF power required may be prohibitively high for conventional pulsed NMR techniques. A stochastic NMR experiment excites the spin system with a sequence of RF pulses where the flip angles or the phases of the pulses are samples of a discrete stochastic process. In a previous paper the stochastic experiment was analyzed and analytic expressions for the input-output cross-correlations, average signal power, and signal spectral density were obtained for a general stochastic RF excitation. In this paper specific cases of excitation with random phase, fixed flip angle, and excitation with two random components in quadrature are analyzed. The input-output cross-correlation for these two types of excitations is shown to be Lorentzian. Line broadening is the only spectral distortion as the RF excitation power is increased. The systematic noise power is inversely proportional to the number of data points N used in the spectral reconstruction. The use of a complete maximum length sequence (MLS) may improve the signal-to-systematic-noise ratio by 20 dB relative to random binary excitation, but peculiar features in the higher-order autocorrelations of MLS cause noise-like distortion in the reconstructed spectra when the excitation power is high. The amount of noise-like distortion depends on the choice of the MLS generator.
Direct handling of equality constraints in multilevel optimization
NASA Technical Reports Server (NTRS)
Renaud, John E.; Gabriele, Gary A.
In recent years there have been several hierarchic multilevel optimization algorithms proposed and implemented in design studies. Equality constraints are often imposed between levels in these multilevel optimizations to maintain system and subsystem variable continuity. Equality constraints of this nature will be referred to as coupling equality constraints. In many implementation studies these coupling equality constraints have been handled indirectly. This indirect handling has been accomplished using the coupling equality constraints' explicit functional relations to eliminate design variables (generally at the subsystem level), with the resulting optimization taking place in a reduced design space. In one multilevel optimization study where the coupling equality constraints were handled directly, the researchers encountered numerical difficulties which prevented their multilevel optimization from reaching the same minimum found in conventional single level solutions. The researchers did not explain the exact nature of the numerical difficulties other than to associate them with the direct handling of the coupling equality constraints. The coupling equality constraints are handled directly, by employing the Generalized Reduced Gradient (GRG) method as the optimizer within a multilevel linear decomposition scheme based on the Sobieski hierarchic algorithm. Two engineering design examples are solved using this approach. The results show that the direct handling of coupling equality constraints in a multilevel optimization does not introduce any problems when the GRG method is employed as the internal optimizer. The optimums achieved are comparable to those achieved in single level solutions and in multilevel studies where the equality constraints have been handled indirectly.
Distributed Relaxation for Conservative Discretizations
NASA Technical Reports Server (NTRS)
Diskin, Boris; Thomas, James L.
A multigrid method is defined as having textbook multigrid efficiency (TME) if the solutions to the governing system of equations are attained in a computational work that is a small (less than 10) multiple of the operation count in one target-grid residual evaluation. The way to achieve this efficiency is the distributed relaxation approach. TME solvers employing distributed relaxation have already been demonstrated for nonconservative formulations of high-Reynolds-number viscous incompressible and subsonic compressible flow regimes. The purpose of this paper is to provide foundations for applications of distributed relaxation to conservative discretizations. A direct correspondence between the primitive variable interpolations for calculating fluxes in conservative finite-volume discretizations and stencils of the discretized derivatives in the nonconservative formulation has been established. Based on this correspondence, one can arrive at a conservative discretization which is very efficiently solved with a nonconservative relaxation scheme and this is demonstrated for conservative discretization of the quasi one-dimensional Euler equations. Formulations for both staggered and collocated grid arrangements are considered and extensions of the general procedure to multiple dimensions are discussed.
Towards the development of multilevel-multiagent diagnostic aids
Stratton, R.C.; Jarrell, D.B.
Presented here is our methodology for developing automated aids for diagnosing faults in complex systems. We have designed these aids as multilevel-multiagent diagnostic aids based on principles that should be generally applicable to any complex system. In this methodology, multilevel'' refers to information models described at successful levels of abstraction that are tied together in such a way that reasoning is directed to the appropriate level as determined by the problem solving requirements. The concept of multiagent'' refers to the method of information processing within the multilevel model network; each model in the network is an independent information processor, i.e., an intelligent agent. 19 refs., 15 figs., 9 tabs.
Discrete dipole approximation simulation of bead enhanced diffraction grating biosensor
NASA Astrophysics Data System (ADS)
Arif, Khalid Mahmood
We present the discrete dipole approximation simulation of light scattering from bead enhanced diffraction biosensor and report the effect of bead material, number of beads forming the grating and spatial randomness on the diffraction intensities of 1st and 0th orders. The dipole models of gratings are formed by volume slicing and image processing while the spatial locations of the beads on the substrate surface are randomly computed using discrete probability distribution. The effect of beads reduction on far-field scattering of 632.8 nm incident field, from fully occupied gratings to very coarse gratings, is studied for various bead materials. Our findings give insight into many difficult or experimentally impossible aspects of this genre of biosensors and establish that bead enhanced grating may be used for rapid and precise detection of small amounts of biomolecules. The results of simulations also show excellent qualitative similarities with experimental observations.
A Bayesian approach to functional-based multilevel modeling of longitudinal data: applications to environmental epidemiology
Berhane, Kiros; Molitor, Nuoo-Ting
Flexible multilevel models are proposed to allow for cluster-specific smooth estimation of growth curves in a mixed-effects modeling format that includes subject-specific random effects on the growth parameters. Attention is then focused on models that examine between-cluster comparisons of the effects of an ecologic covariate of interest (e.g. air pollution) on nonlinear functionals of growth curves (e.g. maximum rate of growth). A Gibbs sampling approach is used to get posterior mean estimates of nonlinear functionals along with their uncertainty estimates. A second-stage ecologic random-effects model is used to examine the association between a covariate of interest (e.g. air pollution) and the nonlinear functionals. A unified estimation procedure is presented along with its computational and theoretical details. The models are motivated by, and illustrated with, lung function and air pollution data from the Southern California Children's Health Study. PMID:18349036
Extinction Dynamics and Evolution of a Survivability-Based Multi-Level Food-Web Model
NASA Astrophysics Data System (ADS)
Berger, B. W.; Boulter, C. J.
A multi-level evolution model where forced extinctions occur throughout the system based on a species fitness value (or survivability) is developed that is essentially the fusion of the evolution model of Bak and Sneppen and the food-web model of Amaral and Meyer. This model is found to describe the fossil record and behave as a self-organized critical system with a power law exponent of approximately 2, but is also found to be remarkably similar to a model that causes the forced extinctions randomly throughout the system. To explain this result we show that fitness is nearly randomly distributed with a slight peak in forced extinction (due to fitness) in the middle levels. These findings lend strong support to the hypothesis that coextinction effects (propagated through a food-web) provide a robust explanation of the fossil record, independent of the mechanism for species competition.
Discretion or discretions? Delineating professional discretion: the case of English medical practice.
Cheraghi-Sohi, Sudeh; Calnan, Michael
There has much debate about the extent to which professional discretion has been challenged by recent organisational changes such as through the new forms of governance associated with the introduction of the principles of the New Public Management (NPM) into health systems and other public sector services. What appears to be missing from these debates is a detailed analysis of the concept of professional discretion itself. This paper attempts to fill this gap by delineating the key concepts of professional discretion evident in the literature and exploring their significance in an empirical study of the influence of the 2004 new general medical services contract (nGMS) and the introduction of the Quality and Outcomes Framework (QOF), a prescriptive pay-for-performance system designed to standardise the quality of care provision in general medical practice in the United Kingdom. The study adopted a longitudinal design using semi-structured interviews with general practitioners (GPs, N = 62) working in the English National Health Service (NHS) between 2007 and 2009. A multi-dimensional conception of discretion was used to explore how GP discretion might have been influenced by contractual changes and in particular, QOF. The findings suggest that through a complex interplay of factors, a post-QOF reduction in GP discretion was identifiable, highlighting different potential sources of constraint such as in the social, organisational and economic dimensions of discretion. The evidence also suggested the emergence of a new form of organisational medical professionalism within general practice characterised by standardisation, bureaucracy and performance management. PMID:24034951
Multilevel domain decomposition for electronic structure calculations
Barrault, M. . E-mail: email@example.com; Cances, E. . E-mail: firstname.lastname@example.com; Hager, W.W. . E-mail: email@example.com; Le Bris, C. . E-mail: email@example.com
We introduce a new multilevel domain decomposition method (MDD) for electronic structure calculations within semi-empirical and density functional theory (DFT) frameworks. This method iterates between local fine solvers and global coarse solvers, in the spirit of domain decomposition methods. Using this approach, calculations have been successfully performed on several linear polymer chains containing up to 40,000 atoms and 200,000 atomic orbitals. Both the computational cost and the memory requirement scale linearly with the number of atoms. Additional speed-up can easily be obtained by parallelization. We show that this domain decomposition method outperforms the density matrix minimization (DMM) method for poor initial guesses. Our method provides an efficient preconditioner for DMM and other linear scaling methods, variational in nature, such as the orbital minimization (OM) procedure.
Cantilevered multilevel LIGA devices and methods
Morales, Alfredo Martin; Domeier, Linda A.
In the formation of multilevel LIGA microstructures, a preformed sheet of photoresist material, such as polymethylmethacrylate (PMMA) is patterned by exposure through a mask to radiation, such as X-rays, and developed using a developer to remove the exposed photoresist material. A first microstructure is then formed by electroplating metal into the areas from which the photoresist has been removed. Additional levels of microstructure are added to the initial microstructure by covering the first microstructure with a conductive polymer, machining the conductive polymer layer to reveal the surface of the first microstructure, sealing the conductive polymer and surface of the first microstructure with a metal layer, and then forming the second level of structure on top of the first level structure. In such a manner, multiple layers of microstructure can be built up to allow complex cantilevered microstructures to be formed.
Structural optimization by generalized, multilevel decomposition
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, J.; James, B. B.; Riley, M. F.
The developments toward a general multilevel optimization capability and results for a three-level structural optimization are described. The method partitions a structure into a number of substructuring levels where each substructure corresponds to a subsystem in the general case of an engineering system. The method is illustrated by a portal framework that decomposes into individual beams. Each beam is a box that can be further decomposed into stiffened plates. Substructuring for this example spans three different levels: (1) the bottom level of finite elements representing the plates; (2) an intermediate level of beams treated as substructures; and (3) the top level for the assembled structure. The three-level case is now considered to be qualitatively complete.
Evolution of cooperation by multilevel selection.
Traulsen, Arne; Nowak, Martin A
We propose a minimalist stochastic model of multilevel (or group) selection. A population is subdivided into groups. Individuals interact with other members of the group in an evolutionary game that determines their fitness. Individuals reproduce, and offspring are added to the same group. If a group reaches a certain size, it can split into two. Faster reproducing individuals lead to larger groups that split more often. In our model, higher-level selection emerges as a byproduct of individual reproduction and population structure. We derive a fundamental condition for the evolution of cooperation by group selection: if b/c > 1 + n/m, then group selection favors cooperation. The parameters b and c denote the benefit and cost of the altruistic act, whereas n and m denote the maximum group size and the number of groups. The model can be extended to more than two levels of selection and to include migration. PMID:16829575
Aristoff, David; Lelièvre, Tony; Mayne, Christopher G.; Teo, Ivan
Adaptive Multilevel Splitting (AMS) is a replica-based rare event sampling method that has been used successfully in high-dimensional stochastic simulations to identify trajectories across a high potential barrier separating one metastable state from another, and to estimate the probability of observing such a trajectory. An attractive feature of AMS is that, in the limit of a large number of replicas, it remains valid regardless of the choice of reaction coordinate used to characterize the trajectories. Previous studies have shown AMS to be accurate in Monte Carlo simulations. In this study, we extend the application of AMS to molecular dynamics simulations and demonstrate its effectiveness using a simple test system. Our conclusion paves the way for useful applications, such as molecular dynamics calculations of the characteristic time of drug dissociation from a protein target. PMID:26005670
Multi-level coupled cluster theory
Myhre, Rolf H.; Koch, Henrik; Sánchez de Merás, Alfredo M. J.
We present a general formalism where different levels of coupled cluster theory can be applied to different parts of the molecular system. The system is partitioned into subsystems by Cholesky decomposition of the one-electron Hartree-Fock density matrix. In this way the system can be divided across chemical bonds without discontinuities arising. The coupled cluster wave function is defined in terms of cluster operators for each part and these are determined from a set of coupled equations. The total wave function fulfills the Pauli-principle across all borders and levels of electron correlation. We develop the associated response theory for this multi-level coupled cluster theory and present proof of principle applications. The formalism is an essential tool in order to obtain size-intensive complexity in the calculation of local molecular properties.
Earning potential in multilevel marketing enterprises
NASA Astrophysics Data System (ADS)
Legara, Erika Fille; Monterola, Christopher; Juanico, Dranreb Earl; Litong-Palima, Marisciel; Saloma, Caesar
Government regulators and other concerned citizens warily view multilevel marketing enterprises (MLM) because of their close operational resemblance to exploitative pyramid schemes. We analyze two types of MLM network architectures - the unilevel and binary, in terms of growth behavior and earning potential among members. We show that network growth decelerates after reaching a size threshold, contrary to claims of unrestricted growth by MLM recruiters. We have also found that the earning potential in binary MLM's obey the Pareto "80-20" rule, implying an earning opportunity that is strongly biased against the most recent members. On the other hand, unilevel MLM's do not exhibit the Pareto earning distribution and earning potential is independent of member position in the network. Our analytical results agree well with field data taken from real-world MLM's in the Philippines. Our analysis is generally valid and can be applied to other MLM architectures.
Affective Balance, Team Prosocial Efficacy and Team Trust: A Multilevel Analysis of Prosocial Behavior in Small Groups.
Cuadrado, Esther; Tabernero, Carmen
Little research has focused on how individual- and team-level characteristics jointly influence, via interaction, how prosocially individuals behave in teams and few studies have considered the potential influence of team context on prosocial behavior. Using a multilevel perspective, we examined the relationships between individual (affective balance) and group (team prosocial efficacy and team trust) level variables and prosocial behavior towards team members. The participants were 123 students nested in 45 small teams. A series of multilevel random models was estimated using hierarchical linear and nonlinear modeling. Individuals were more likely to behave prosocially towards in-group members when they were feeling good. Furthermore, the relationship between positive affective balance and prosocial behavior was stronger in teams with higher team prosocial efficacy levels as well as in teams with higher team trust levels. Finally, the relevance of team trust had a stronger influence on behavior than team prosocial efficacy. PMID:26317608
Affective Balance, Team Prosocial Efficacy and Team Trust: A Multilevel Analysis of Prosocial Behavior in Small Groups
Cuadrado, Esther; Tabernero, Carmen
Little research has focused on how individual- and team-level characteristics jointly influence, via interaction, how prosocially individuals behave in teams and few studies have considered the potential influence of team context on prosocial behavior. Using a multilevel perspective, we examined the relationships between individual (affective balance) and group (team prosocial efficacy and team trust) level variables and prosocial behavior towards team members. The participants were 123 students nested in 45 small teams. A series of multilevel random models was estimated using hierarchical linear and nonlinear modeling. Individuals were more likely to behave prosocially towards in-group members when they were feeling good. Furthermore, the relationship between positive affective balance and prosocial behavior was stronger in teams with higher team prosocial efficacy levels as well as in teams with higher team trust levels. Finally, the relevance of team trust had a stronger influence on behavior than team prosocial efficacy. PMID:26317608
Geometry of discrete quantum computing
NASA Astrophysics Data System (ADS)
Hanson, Andrew J.; Ortiz, Gerardo; Sabry, Amr; Tai, Yu-Tsung
Conventional quantum computing entails a geometry based on the description of an n-qubit state using 2n infinite precision complex numbers denoting a vector in a Hilbert space. Such numbers are in general uncomputable using any real-world resources, and, if we have the idea of physical law as some kind of computational algorithm of the universe, we would be compelled to alter our descriptions of physics to be consistent with computable numbers. Our purpose here is to examine the geometric implications of using finite fields Fp and finite complexified fields \\mathbf {F}_{p^2} (based on primes p congruent to 3 (mod4)) as the basis for computations in a theory of discrete quantum computing, which would therefore become a computable theory. Because the states of a discrete n-qubit system are in principle enumerable, we are able to determine the proportions of entangled and unentangled states. In particular, we extend the Hopf fibration that defines the irreducible state space of conventional continuous n-qubit theories (which is the complex projective space \\mathbf {CP}^{2^{n}-1}) to an analogous discrete geometry in which the Hopf circle for any n is found to be a discrete set of p + 1 points. The tally of unit-length n-qubit states is given, and reduced via the generalized Hopf fibration to \\mathbf {DCP}^{2^{n}-1}, the discrete analogue of the complex projective space, which has p^{2^{n}-1} (p-1)\\,\\prod _{k=1}^{n-1} ( p^{2^{k}}+1) irreducible states. Using a measure of entanglement, the purity, we explore the entanglement features of discrete quantum states and find that the n-qubit states based on the complexified field \\mathbf {F}_{p^2} have pn(p - 1)n unentangled states (the product of the tally for a single qubit) with purity 1, and they have pn + 1(p - 1)(p + 1)n - 1 maximally entangled states with purity zero.
Analysis of Multilevel Pressure Transient Data at the Illinois Basin - Decatur Project
NASA Astrophysics Data System (ADS)
Strandli, Christin W.; Mehnert, Edward; Benson, Sally M.
Based on numerical studies in TOUH2/ECO2N and analyses of multilevel (depth-discrete) pressure transient data at the Illinois Basin - Decatur Project (IBDP), this study demonstrates methods for using multilevel pressure transient data as a means to further characterize the storage formation and for monitoring carbon dioxide (CO2) and displaced brine migration. By incorporating multilevel pressure monitoring into the monitoring program, additional information is available that can be used to minimize and manage potential risk associated with CO2 and displaced brine migration to shallower depths. Previously, we used simulated pressure data from numerical studies in TOUGH2/ECO2N to identify diagnostics for reservoir structure (layering and anisotropy) and CO2 plume migration. In particular, we found that important insights can be obtained by: 1) normalizing the pressure buildups to the pressure buildup at the depth of injection, and 2) calculating vertical pressure gradients normalized to the initial hydrostatic pressure gradient. Soon after the start of injection, pressure buildups normalized to the pressure buildup at the depth of injection and vertical pressure gradients normalized to the initial hydrostatic pressure gradient are diagnostic of reservoir structure, and over time provide information on the height of the CO2 plume. In this study, the identified diagnostics are applied to the pressure transient data at the IBDP, where the Westbay* multilevel groundwater characterization and monitoring system was installed in a deep in-zone verification well (2,000 m) to measure the pressure buildup at multiple depths within the Mt. Simon storage reservoir and above the Eau Claire Formation (primary seal) during CO2 injection. Using the diagnostic tools, we are able to correctly identify the height of the CO2 plume. Specifically, the multilevel pressure transient data alone indicate that the CO2 plume remains largely confined to the 23-24 m interval into which it is
Novel multilevel inverter carrier-based PWM method
Tolbert, L.M.; Habetler, T.G.
The advent of the transformerless multilevel inverter topology has brought forth various pulsewidth modulation (PWM) schemes as a means to control the switching of the active devices in each of the multiple voltage levels in the inverter. An analysis of how existing multilevel carrier-based PWM affects switch utilization for the different levels of a diode-clamped inverter is conducted. Two novel carrier-based multilevel PWM schemes are presented which help to optimize or balance the switch utilization in multilevel inverters. A 10-kW prototype six-level diode-clamped inverter has been built and controlled with the novel PWM strategies proposed in this paper to act as a voltage-source inverter for a motor drive.
Squeezed light from conventionally pumped multi-level lasers
NASA Technical Reports Server (NTRS)
Ralph, T. C.; Savage, C. M.
We have calculated the amplitude squeezing in the output of several conventionally pumped multi-level lasers. We present results which show that standard laser models can produce significantly squeezed outputs in certain parameter ranges.
Integrated structure/control law design by multilevel optimization
NASA Technical Reports Server (NTRS)
Gilbert, Michael G.; Schmidt, David K.
A new approach to integrated structure/control law design based on multilevel optimization is presented. This new approach is applicable to aircraft and spacecraft and allows for the independent design of the structure and control law. Integration of the designs is achieved through use of an upper level coordination problem formulation within the multilevel optimization framework. The method requires the use of structure and control law design sensitivity information. A general multilevel structure/control law design problem formulation is given, and the use of Linear Quadratic Gaussian (LQG) control law design and design sensitivity methods within the formulation is illustrated. Results of three simple integrated structure/control law design examples are presented. These results show the capability of structure and control law design tradeoffs to improve controlled system performance within the multilevel approach.
Multilevel Atomic Coherent States and Atomic Holomorphic Representation
NASA Technical Reports Server (NTRS)
Cao, Chang-Qi; Haake, Fritz
The notion of atomic coherent states is extended to the case of multilevel atom collective. Based on atomic coherent states, a holomorphic representation for atom collective states and operators is defined. An example is given to illustrate its application.
Metal complex modified azo polymers for multilevel organic memories
NASA Astrophysics Data System (ADS)
Ma, Yong; Chen, Hong-Xia; Zhou, Feng; Li, Hua; Dong, Huilong; Li, You-Yong; Hu, Zhi-Jun; Xu, Qing-Feng; Lu, Jian-Mei
Multilevel organic memories have attracted considerable interest due to their high capacity of data storage. Despite advances, the search for multilevel memory materials still remains a formidable challenge. Herein, we present a rational design and synthesis of a class of polymers containing an azobenzene-pyridine group (PAzo-py) and its derivatives, for multilevel organic memory storage. In this design, a metal complex (M(Phen)Cl2, M = Cu, Pd) is employed to modify the HOMO-LUMO energy levels of azo polymers, thereby converting the memory state from binary to ternary. More importantly, this approach enables modulating the energy levels of azo polymers by varying the coordination metal ions. This makes the achievement of high performance multilevel memories possible. The ability to tune the bandgap energy of azo polymers provides new exciting opportunities to develop new materials for high-density data storage.Multilevel organic memories have attracted considerable interest due to their high capacity of data storage. Despite advances, the search for multilevel memory materials still remains a formidable challenge. Herein, we present a rational design and synthesis of a class of polymers containing an azobenzene-pyridine group (PAzo-py) and its derivatives, for multilevel organic memory storage. In this design, a metal complex (M(Phen)Cl2, M = Cu, Pd) is employed to modify the HOMO-LUMO energy levels of azo polymers, thereby converting the memory state from binary to ternary. More importantly, this approach enables modulating the energy levels of azo polymers by varying the coordination metal ions. This makes the achievement of high performance multilevel memories possible. The ability to tune the bandgap energy of azo polymers provides new exciting opportunities to develop new materials for high-density data storage. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr00871a
Reduced discretization error in HZETRN
Slaba, Tony C.; Blattnig, Steve R.; Tweed, John
The deterministic particle transport code HZETRN is an efficient analysis tool for studying the effects of space radiation on humans, electronics, and shielding materials. In a previous work, numerical methods in the code were reviewed, and new methods were developed that further improved efficiency and reduced overall discretization error. It was also shown that the remaining discretization error could be attributed to low energy light ions (A < 4) with residual ranges smaller than the physical step-size taken by the code. Accurately resolving the spectrum of low energy light particles is important in assessing risk associated with astronaut radiation exposure. In this work, modifications to the light particle transport formalism are presented that accurately resolve the spectrum of low energy light ion target fragments. The modified formalism is shown to significantly reduce overall discretization error and allows a physical approximation to be removed. For typical step-sizes and energy grids used in HZETRN, discretization errors for the revised light particle transport algorithms are shown to be less than 4% for aluminum and water shielding thicknesses as large as 100 g/cm{sup 2} exposed to both solar particle event and galactic cosmic ray environments.
Some discrete multiple orthogonal polynomials
NASA Astrophysics Data System (ADS)
Arvesú, J.; Coussement, J.; van Assche, W.
In this paper, we extend the theory of discrete orthogonal polynomials (on a linear lattice) to polynomials satisfying orthogonality conditions with respect to r positive discrete measures. First we recall the known results of the classical orthogonal polynomials of Charlier, Meixner, Kravchuk and Hahn (T.S. Chihara, An Introduction to Orthogonal Polynomials, Gordon and Breach, New York, 1978; R. Koekoek and R.F. Swarttouw, Reports of the Faculty of Technical Mathematics and Informatics No. 98-17, Delft, 1998; A.F. Nikiforov et al., Classical Orthogonal Polynomials of a Discrete Variable, Springer, Berlin, 1991). These polynomials have a lowering and raising operator, which give rise to a Rodrigues formula, a second order difference equation, and an explicit expression from which the coefficients of the three-term recurrence relation can be obtained. Then we consider r positive discrete measures and define two types of multiple orthogonal polynomials. The continuous case (Jacobi, Laguerre, Hermite, etc.) was studied by Van Assche and Coussement (J. Comput. Appl. Math. 127 (2001) 317-347) and Aptekarev et al. (Multiple orthogonal polynomials for classical weights, manuscript). The families of multiple orthogonal polynomials (of type II) that we will study have a raising operator and hence a Rodrigues formula. This will give us an explicit formula for the polynomials. Finally, there also exists a recurrence relation of order r+1 for these multiple orthogonal polynomials of type II. We compute the coefficients of the recurrence relation explicitly when r=2.
Multi-level Monte Carlo Methods for Efficient Simulation of Coulomb Collisions
NASA Astrophysics Data System (ADS)
Ricketson, Lee
We discuss the use of multi-level Monte Carlo (MLMC) schemes--originally introduced by Giles for financial applications--for the efficient simulation of Coulomb collisions in the Fokker-Planck limit. The scheme is based on a Langevin treatment of collisions, and reduces the computational cost of achieving a RMS error scaling as ɛ from O (ɛ-3) --for standard Langevin methods and binary collision algorithms--to the theoretically optimal scaling O (ɛ-2) for the Milstein discretization, and to O (ɛ-2 (logɛ)2) with the simpler Euler-Maruyama discretization. In practice, this speeds up simulation by factors up to 100. We summarize standard MLMC schemes, describe some tricks for achieving the optimal scaling, present results from a test problem, and discuss the method's range of applicability. This work was performed under the auspices of the U.S. DOE by the University of California, Los Angeles, under grant DE-FG02-05ER25710, and by LLNL under contract DE-AC52-07NA27344.
Multi-level bandwidth efficient block modulation codes
NASA Technical Reports Server (NTRS)
Lin, Shu
The multilevel technique is investigated for combining block coding and modulation. There are four parts. In the first part, a formulation is presented for signal sets on which modulation codes are to be constructed. Distance measures on a signal set are defined and their properties are developed. In the second part, a general formulation is presented for multilevel modulation codes in terms of component codes with appropriate Euclidean distances. The distance properties, Euclidean weight distribution and linear structure of multilevel modulation codes are investigated. In the third part, several specific methods for constructing multilevel block modulation codes with interdependency among component codes are proposed. Given a multilevel block modulation code C with no interdependency among the binary component codes, the proposed methods give a multilevel block modulation code C which has the same rate as C, a minimum squared Euclidean distance not less than that of code C, a trellis diagram with the same number of states as that of C and a smaller number of nearest neighbor codewords than that of C. In the last part, error performance of block modulation codes is analyzed for an AWGN channel based on soft-decision maximum likelihood decoding. Error probabilities of some specific codes are evaluated based on their Euclidean weight distributions and simulation results.
Discrete implementations of scale transform
NASA Astrophysics Data System (ADS)
Djurdjanovic, Dragan; Williams, William J.; Koh, Christopher K.
Scale as a physical quantity is a recently developed concept. The scale transform can be viewed as a special case of the more general Mellin transform and its mathematical properties are very applicable in the analysis and interpretation of the signals subject to scale changes. A number of single-dimensional applications of scale concept have been made in speech analysis, processing of biological signals, machine vibration analysis and other areas. Recently, the scale transform was also applied in multi-dimensional signal processing and used for image filtering and denoising. Discrete implementation of the scale transform can be carried out using logarithmic sampling and the well-known fast Fourier transform. Nevertheless, in the case of the uniformly sampled signals, this implementation involves resampling. An algorithm not involving resampling of the uniformly sampled signals has been derived too. In this paper, a modification of the later algorithm for discrete implementation of the direct scale transform is presented. In addition, similar concept was used to improve a recently introduced discrete implementation of the inverse scale transform. Estimation of the absolute discretization errors showed that the modified algorithms have a desirable property of yielding a smaller region of possible error magnitudes. Experimental results are obtained using artificial signals as well as signals evoked from the temporomandibular joint. In addition, discrete implementations for the separable two-dimensional direct and inverse scale transforms are derived. Experiments with image restoration and scaling through two-dimensional scale domain using the novel implementation of the separable two-dimensional scale transform pair are presented.
Dark energy from discrete spacetime.
Trout, Aaron D
Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT) model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, [Formula: see text] in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies. PMID:24312502
Class of discrete Gabor expansion
NASA Astrophysics Data System (ADS)
Li, Shidong; Healy, Dennis M., Jr.
We present a new approach to studying a discrete Gabor expansion (DGE). We show that, in general, DGE is not the usual biorthogonal decomposition, but belongs to a larger and looser decomposition scheme which we call pseudo frame decomposition. It includes the DGE scheme proposed as a special case. The standard dual frame decomposition is also a special case. We derive algorithms using techniques for Gabor sequences to compute 'biorthogonal' sequences through proper matrix representation. Our algorithms involve solutions to a linear system to obtain the 'biorthogonal' windows. This approach provides a much broader mathematical view of the DGE, and therefore, establishes a wider mathematical foundation towards the theory of DGE. The general algorithm derived also provides a whole class of discrete Gabor expansions, among which 'good' ones can be generated. Simulation results are also provided.
Systoles in discrete dynamical systems
NASA Astrophysics Data System (ADS)
Fernandes, Sara; Grácio, Clara; Ramos, Carlos Correia
The fruitful relationship between Geometry and Graph Theory has been explored by several authors benefiting also the Theory of discrete dynamical systems seen as Markov chains in graphs. In this work we will further explore the relation between these areas, giving a geometrical interpretation of notions from dynamical systems. In particular, we relate the topological entropy with the systole, here defined in the context of discrete dynamical systems. We show that for continuous interval maps the systole is trivial; however, for the class of interval maps with one discontinuity point the systole acquires relevance from the point of view of the dynamical behavior. Moreover, we define the geodesic length spectrum associated to a Markov interval map and we compute the referred spectrum in several examples.
Dark Energy from Discrete Spacetime
Trout, Aaron D.
Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT) model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies. PMID:24312502
A FORTRAN Program for Discrete Discriminant Analysis
ERIC Educational Resources Information Center
Boone, James O.; Brewer, James K.
A Fortran program is presented for discriminant analysis of discrete variables. The program assumes discrete, nominal data with no distributional, variance-covariance assumptions. The program handles a maximum of fifty predictor variables and twelve outcome groups. (Author/JKS)
Efficient genetic algorithms using discretization scheduling.
McLay, Laura A; Goldberg, David E
In many applications of genetic algorithms, there is a tradeoff between speed and accuracy in fitness evaluations when evaluations use numerical methods with varying discretization. In these types of applications, the cost and accuracy vary from discretization errors when implicit or explicit quadrature is used to estimate the function evaluations. This paper examines discretization scheduling, or how to vary the discretization within the genetic algorithm in order to use the least amount of computation time for a solution of a desired quality. The effectiveness of discretization scheduling can be determined by comparing its computation time to the computation time of a GA using a constant discretization. There are three ingredients for the discretization scheduling: population sizing, estimated time for each function evaluation and predicted convergence time analysis. Idealized one- and two-dimensional experiments and an inverse groundwater application illustrate the computational savings to be achieved from using discretization scheduling. PMID:16156928
Anomalies and Discrete Chiral Symmetries
Creutz, M.
The quantum anomaly that breaks the U(1) axial symmetry of massless multi-flavored QCD leaves behind a discrete flavor-singlet chiral invariance. With massive quarks, this residual symmetry has a close connection with the strong CP-violating parameter theta. One result is that if the lightest quarks are degenerate, then a first order transition will occur when theta passes through pi. The resulting framework helps clarify when the rooting prescription for extrapolating in the number of flavors is valid.
Discrete vortex representation of magnetohydrodynamics
Kinney, R.; Tajima, T.; Petviashvili, N.; McWilliams, J.C.
We present an alternative approach to statistical analysis of an intermittent ideal MHD fluid in two dimensions, based on the hydrodynamical discrete vortex model applied to the Elsasser variables. The model contains negative temperature states which predict the formation of magnetic islands, but also includes a natural limit under which the equilibrium states revert to the familiar twin-vortex states predicted by hydrodynamical turbulence theories. Numerical dynamical calculations yield equilibrium spectra in agreement with the theoretical predictions.
Discrete-contact nanowire photovoltaics
NASA Astrophysics Data System (ADS)
Chitambar, Michelle J.; Wen, Wen; Maldonado, Stephen
A series of finite-element simulations have been performed to assess the operational characteristics of a new semiconductor nanowire solar cell design operating under high-level injection conditions. Specifically, the steady-state current-voltage behavior of a cylindrical silicon (Si) nanowire with a series of discrete, ohmic-selective contacts under intense sunlight illumination was investigated. The scope of the analysis was limited to only the factors that impact the net internal quantum yield for solar to electricity conversion. No evaluations were performed with regards to optical light trapping in the modeled structures. Several aspects in a discrete-contact nanowire device that could impact operation were explored, including the size and density of ohmic-selective contacts, the size of the nanowire, the electronic quality and conductivity of the nanowire, the surface defect density of the nanowire, and the type of ohmic selectivity employed at each contact. The analysis showed that there were ranges of values for each parameter that supported good to excellent photoresponses, with certain combinations of experimentally attainable material properties yielding internal energy conversion efficiencies at the thermodynamic limit for a single junction cell. The merits of the discrete-contact nanowire cell were contrasted with "conventional" nanowire photovoltaic cells featuring a uniform conformal contact and also with planar point-contact solar cells. The unique capacity of the discrete-contact nanowire solar cell design to operate at useful energy conversion efficiencies with low quality semiconductor nanowires (i.e., possessing short charge-carrier lifetimes) with only light doping is discussed. This work thus defines the impetus for future experimental work aimed at developing this photovoltaic architecture.
Multilevel Cross-dependent Binary Longitudinal Data
Staicu, Ana-Maria; Carroll, Raymond J.
We provide insights into new methodology for the analysis of multilevel binary data observed longitudinally, when the repeated longitudinal measurements are correlated. The proposed model is logistic functional regression conditioned on three latent processes describing the within- and between-variability, and describing the cross-dependence of the repeated longitudinal measurements. We estimate the model components without employing mixed-effects modeling but assuming an approximation to the logistic link function. The primary objectives of this paper are to highlight the challenges in the estimation of the model components, to compare two approximations to the logistic regression function, linear and exponential, and to discuss their advantages and limitations. The linear approximation is computationally efficient whereas the exponential approximation applies for rare events functional data. Our methods are inspired by and applied to a scientific experiment on spectral backscatter from long range infrared light detection and ranging (LIDAR) data. The models are general and relevant to many new binary functional data sets, with or without dependence between repeated functional measurements. PMID:24131242
Gaussian translation operator in a multilevel scheme
NASA Astrophysics Data System (ADS)
Hansen, Thorkild B.; Borries, Oscar
A multilevel computation scheme for time-harmonic fields in three dimensions will be formulated with a new Gaussian translation operator that decays exponentially outside a circular cone centered on the line connecting the source and observation groups. This Gaussian translation operator is directional and diagonal with its sharpness determined by a beam parameter. When the beam parameter is set to zero, the Gaussian translation operator reduces to the standard fast multipole method translation operator. The directionality of the Gaussian translation operator makes it possible to reduce the number of plane waves required to achieve a given accuracy. The sampling rate can be determined straightforwardly to achieve any desired accuracy. The use of the computation scheme will be illustrated through a near-field scanning problem where the far-field pattern of a source is determined from near-field measurements with a known probe. Here the Gaussian translation operator improves the condition number of the matrix equation that determines the far-field pattern. The Gaussian translation operator can also be used when the probe pattern is known only in one hemisphere, as is common in practice. Also, the Gaussian translation operator will be used to solve the scattering problem of the perfectly conducting sphere.
Multilevel relaxation phenomena and population trapping
Hioe, F.T.
This final report summarizes the main results of our work supported by DOE since 1982. A list of 45 publications supported by this DOE Grant is attached at the end of this report. The use and exploitation of the SU(N) dynamic symmetry to the study of the dynamics of laser-atom interaction was the starting point of our research work under this DOE Grant, and is our most original contribution to the field of quantum electrodynamics. Many results of general and special interests have been derived and developed from this starting point and the following is a summary of them: (1) We have introduced a set of simple relations based on the principle of unitary invariance which has proved to be useful for the study of the dynamics of a quantum system involving coupling. (2) We have found various specific conditions under which (a) we may have trapped population, or (b) we may send laser pulses through a multilevel atomic medium without attenuation. (3) We have found a remarkably efficient method for optimal state selective multiphoton population transfer, that employs two or more spatially overlapping lasers arranged in an unconventional sequence which we called counterintuitive''. A recent suggestion by Profs. P. Marte, P. Zoller and J.L. Hall to use this counterintuitive method for atomic beam deflections promises to make this remarkably effective procedure to become an important method in atomic interferometry.
Experiments in encoding multilevel images as quadtrees
NASA Technical Reports Server (NTRS)
Lansing, Donald L.
Image storage requirements for several encoding methods are investigated and the use of quadtrees with multigray level or multicolor images are explored. The results of encoding a variety of images having up to 256 gray levels using three schemes (full raster, runlength and quadtree) are presented. Although there is considerable literature on the use of quadtrees to store and manipulate binary images, their application to multilevel images is relatively undeveloped. The potential advantage of quadtree encoding is that an entire area with a uniform gray level may be encoded as a unit. A pointerless quadtree encoding scheme is described. Data are presented on the size of the quadtree required to encode selected images and on the relative storage requirements of the three encoding schemes. A segmentation scheme based on the statistical variation of gray levels within a quadtree quadrant is described. This parametric scheme may be used to control the storage required by an encoded image and to preprocess a scene for feature identification. Several sets of black and white and pseudocolor images obtained by varying the segmentation parameter are shown.
Analysis of biomedical data with multilevel glyphs
Background This paper presents multilevel data glyphs optimized for the interactive knowledge discovery and visualization of large biomedical data sets. Data glyphs are three- dimensional objects defined by multiple levels of geometric descriptions (levels of detail) combined with a mapping of data attributes to graphical elements and methods, which specify their spatial position. Methods In the data mapping phase, which is done by a biomedical expert, meta information about the data attributes (scale, number of distinct values) are compared with the visual capabilities of the graphical elements in order to give a feedback to the user about the correctness of the variable mapping. The spatial arrangement of glyphs is done in a dimetric view, which leads to high data density, a simplified 3D navigation and avoids perspective distortion. Results We show the usage of data glyphs in the disease analyser a visual analytics application for personalized medicine and provide an outlook to a biomedical web visualization scenario. Conclusions Data glyphs can be successfully applied in the disease analyser for the analysis of big medical data sets. Especially the automatic validation of the data mapping, selection of subgroups within histograms and the visual comparison of the value distributions were seen by experts as an important functionality. PMID:25079119
The genetical theory of multilevel selection
Gardner, A
The theory of multilevel selection (MLS) is beset with conceptual difficulties. Although it is widely agreed that covariance between group trait and group fitness may arise in the natural world and drive a response to 'group selection', ambiguity exists over the precise meaning of group trait and group fitness and as to whether group selection should be defined according to changes in frequencies of different types of individual or different types of group. Moreover, the theory of MLS has failed to properly engage with the problem of class structure, which greatly limits its empirical application to, for example, social insects whose colonies are structured into separate age, sex, caste and ploidy classes. Here, I develop a genetical theory of MLS, to address these problems. I show that taking a genetical approach facilitates a decomposition of group-level traits – including reproductive success – into the separate contributions made by each constituent individual, even in the context of so-called emergence. However, I uncover a novel problem with the group-oriented approach: in many scenarios, it may not be possible to express a meaningful covariance between trait and fitness at the level of the social group, because the group's constituents belong to separate, irreconcilable classes. PMID:25475922
A magnetic synapse: multilevel spin-torque memristor with perpendicular anisotropy
Lequeux, Steven; Sampaio, Joao; Cros, Vincent; Yakushiji, Kay; Fukushima, Akio; Matsumoto, Rie; Kubota, Hitoshi; Yuasa, Shinji; Grollier, Julie
Memristors are non-volatile nano-resistors which resistance can be tuned by applied currents or voltages and set to a large number of levels. Thanks to these properties, memristors are ideal building blocks for a number of applications such as multilevel non-volatile memories and artificial nano-synapses, which are the focus of this work. A key point towards the development of large scale memristive neuromorphic hardware is to build these neural networks with a memristor technology compatible with the best candidates for the future mainstream non-volatile memories. Here we show the first experimental achievement of a multilevel memristor compatible with spin-torque magnetic random access memories. The resistive switching in our spin-torque memristor is linked to the displacement of a magnetic domain wall by spin-torques in a perpendicularly magnetized magnetic tunnel junction. We demonstrate that our magnetic synapse has a large number of intermediate resistance states, sufficient for neural computation. Moreover, we show that engineering the device geometry allows leveraging the most efficient spin torque to displace the magnetic domain wall at low current densities and thus to minimize the energy cost of our memristor. Our results pave the way for spin-torque based analog magnetic neural computation. PMID:27539144
An Integrative, Multilevel, and Transdisciplinary Research Approach to Challenges of Work, Family, and Health
Bray, Jeremy W.; Kelly, Erin L.; Hammer, Leslie B.; Almeida, David M.; Dearing, James W.; King, Rosalind B.; Buxton, Orfeu M.
Recognizing a need for rigorous, experimental research to support the efforts of workplaces and policymakers in improving the health and wellbeing of employees and their families, the National Institutes of Health and the Centers for Disease Control and Prevention formed the Work, Family & Health Network (WFHN). The WFHN is implementing an innovative multisite study with a rigorous experimental design (adaptive randomization, control groups), comprehensive multilevel measures, a novel and theoretically based intervention targeting the psychosocial work environment, and translational activities. This paper describes challenges and benefits of designing a multilevel and transdisciplinary research network that includes an effectiveness study to assess intervention effects on employees, families, and managers; a daily diary study to examine effects on family functioning and daily stress; a process study to understand intervention implementation; and translational research to understand and inform diffusion of innovation. Challenges were both conceptual and logistical, spanning all aspects of study design and implementation. In dealing with these challenges, however, the WFHN developed innovative, transdisciplinary, multi-method approaches to conducting workplace research that will benefit both the research and business communities. PMID:24618878
Integrated all-photonic non-volatile multi-level memory
NASA Astrophysics Data System (ADS)
Ríos, Carlos; Stegmaier, Matthias; Hosseini, Peiman; Wang, Di; Scherer, Torsten; Wright, C. David; Bhaskaran, Harish; Pernice, Wolfram H. P.
Implementing on-chip non-volatile photonic memories has been a long-term, yet elusive goal. Photonic data storage would dramatically improve performance in existing computing architectures by reducing the latencies associated with electrical memories and potentially eliminating optoelectronic conversions. Furthermore, multi-level photonic memories with random access would allow for leveraging even greater computational capability. However, photonic memories have thus far been volatile. Here, we demonstrate a robust, non-volatile, all-photonic memory based on phase-change materials. By using optical near-field effects, we realize bit storage of up to eight levels in a single device that readily switches between intermediate states. Our on-chip memory cells feature single-shot readout and switching energies as low as 13.4 pJ at speeds approaching 1 GHz. We show that individual memory elements can be addressed using a wavelength multiplexing scheme. Our multi-level, multi-bit devices provide a pathway towards eliminating the von Neumann bottleneck and portend a new paradigm in all-photonic memory and non-conventional computing.
An Integrative, Multilevel, and Transdisciplinary Research Approach to Challenges of Work, Family, and Health.
Bray, Jeremy W; Kelly, Erin L; Hammer, Leslie B; Almeida, David M; Dearing, James W; King, Rosalind B; Buxton, Orfeu M
Recognizing a need for rigorous, experimental research to support the efforts of workplaces and policymakers in improving the health and wellbeing of employees and their families, the National Institutes of Health and the Centers for Disease Control and Prevention formed the Work, Family & Health Network (WFHN). The WFHN is implementing an innovative multisite study with a rigorous experimental design (adaptive randomization, control groups), comprehensive multilevel measures, a novel and theoretically based intervention targeting the psychosocial work environment, and translational activities. This paper describes challenges and benefits of designing a multilevel and transdisciplinary research network that includes an effectiveness study to assess intervention effects on employees, families, and managers; a daily diary study to examine effects on family functioning and daily stress; a process study to understand intervention implementation; and translational research to understand and inform diffusion of innovation. Challenges were both conceptual and logistical, spanning all aspects of study design and implementation. In dealing with these challenges, however, the WFHN developed innovative, transdisciplinary, multi-method approaches to conducting workplace research that will benefit both the research and business communities. PMID:24618878
A magnetic synapse: multilevel spin-torque memristor with perpendicular anisotropy.
Lequeux, Steven; Sampaio, Joao; Cros, Vincent; Yakushiji, Kay; Fukushima, Akio; Matsumoto, Rie; Kubota, Hitoshi; Yuasa, Shinji; Grollier, Julie
Memristors are non-volatile nano-resistors which resistance can be tuned by applied currents or voltages and set to a large number of levels. Thanks to these properties, memristors are ideal building blocks for a number of applications such as multilevel non-volatile memories and artificial nano-synapses, which are the focus of this work. A key point towards the development of large scale memristive neuromorphic hardware is to build these neural networks with a memristor technology compatible with the best candidates for the future mainstream non-volatile memories. Here we show the first experimental achievement of a multilevel memristor compatible with spin-torque magnetic random access memories. The resistive switching in our spin-torque memristor is linked to the displacement of a magnetic domain wall by spin-torques in a perpendicularly magnetized magnetic tunnel junction. We demonstrate that our magnetic synapse has a large number of intermediate resistance states, sufficient for neural computation. Moreover, we show that engineering the device geometry allows leveraging the most efficient spin torque to displace the magnetic domain wall at low current densities and thus to minimize the energy cost of our memristor. Our results pave the way for spin-torque based analog magnetic neural computation. PMID:27539144
Symmetric Discrete Orthonormal Stockwell Transform
NASA Astrophysics Data System (ADS)
Wang, Yanwei; Orchard, Jeff
The Stockwell Transform (ST) is a time-frequency signal decomposition that is gaining in popularity, likely because of its direct relation with the Fourier Transform (FT). A discrete and non-redundant version of the ST, denoted the Discrete Orthonormal Stockwell Transform (DOST), has made the use of the ST more feasible. However, the matrix multiplication required by the DOST can still be a formidable computation, especially for high-dimensional data. Moreover, the symmetric property of the ST and FT is not present in the DOST. In this paper, we investigate a new Symmetric Discrete Orthonormal Stockwell Transform (SDOST) that still keeps the non-redundant multiresolution features of the DOST, while maintaining a symmetry property similar to that of the FT. First, we give a brief introduction for the ST and the DOST. Then we analyze the DOST coefficients and modify the transform to get a symmetric version. A small experiment shows that the SDOST has kept the abilities of the DOST and demonstrates the advantage of symmetry when applying the SDOST.
Interference in discrete Wigner functions
Cormick, Cecilia; Paz, Juan Pablo
We analyze some features of the class of discrete Wigner functions that was recently introduced by Gibbons et al. [Phys. Rev. A 70, 062101 (2004)] to represent quantum states of systems with power-of-prime dimensional Hilbert spaces. We consider ''cat'' states obtained as coherent superpositions of states with positive Wigner function; for such states we show that the oscillations of the discrete Wigner function typically spread over the entire discrete phase space (including the regions where the two interfering states are localized). This is a generic property, which is in sharp contrast with the usual attributes of Wigner functions that make them useful candidates to display the existence of quantum coherence through oscillations. However, it is possible to find subsets of cat states with a natural phase-space representation, in which the oscillatory regions remain localized. We show that this can be done for interesting families of stabilizer states used in quantum error-correcting codes, and illustrate this by analyzing the phase-space representation of the five-qubit error-correcting code.
The rigorous stochastic matrix multiplication scheme for the calculations of reduced equilibrium density matrices of open multilevel quantum systems
NASA Astrophysics Data System (ADS)
Chen, Xin
Understanding the roles of the temporary and spatial structures of quantum functional noise in open multilevel quantum molecular systems attracts a lot of theoretical interests. I want to establish a rigorous and general framework for functional quantum noises from the constructive and computational perspectives, i.e., how to generate the random trajectories to reproduce the kernel and path ordering of the influence functional with effective Monte Carlo methods for arbitrary spectral densities. This construction approach aims to unify the existing stochastic models to rigorously describe the temporary and spatial structure of Gaussian quantum noises. In this paper, I review the Euclidean imaginary time influence functional and propose the stochastic matrix multiplication scheme to calculate reduced equilibrium density matrices (REDM). In addition, I review and discuss the Feynman-Vernon influence functional according to the Gaussian quadratic integral, particularly its imaginary part which is critical to the rigorous description of the quantum detailed balance. As a result, I establish the conditions under which the influence functional can be interpreted as the average of exponential functional operator over real-valued Gaussian processes for open multilevel quantum systems. I also show the difference between the local and nonlocal phonons within this framework. With the stochastic matrix multiplication scheme, I compare the normalized REDM with the Boltzmann equilibrium distribution for open multilevel quantum systems.
The rigorous stochastic matrix multiplication scheme for the calculations of reduced equilibrium density matrices of open multilevel quantum systems
Chen, Xin
Understanding the roles of the temporary and spatial structures of quantum functional noise in open multilevel quantum molecular systems attracts a lot of theoretical interests. I want to establish a rigorous and general framework for functional quantum noises from the constructive and computational perspectives, i.e., how to generate the random trajectories to reproduce the kernel and path ordering of the influence functional with effective Monte Carlo methods for arbitrary spectral densities. This construction approach aims to unify the existing stochastic models to rigorously describe the temporary and spatial structure of Gaussian quantum noises. In this paper, I review the Euclidean imaginary time influence functional and propose the stochastic matrix multiplication scheme to calculate reduced equilibrium density matrices (REDM). In addition, I review and discuss the Feynman-Vernon influence functional according to the Gaussian quadratic integral, particularly its imaginary part which is critical to the rigorous description of the quantum detailed balance. As a result, I establish the conditions under which the influence functional can be interpreted as the average of exponential functional operator over real-valued Gaussian processes for open multilevel quantum systems. I also show the difference between the local and nonlocal phonons within this framework. With the stochastic matrix multiplication scheme, I compare the normalized REDM with the Boltzmann equilibrium distribution for open multilevel quantum systems.
Observability of discretized partial differential equations
NASA Technical Reports Server (NTRS)
Cohn, Stephen E.; Dee, Dick P.
It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.
NASA Astrophysics Data System (ADS)
ajansen; kwhitefoot; panteltje1; edprochak; sudhakar, the
In reply to the physicsworld.com news story "How to make a quantum random-number generator from a mobile phone" (16 May, http://ow.ly/xFiYc, see also p5), which describes a way of delivering random numbers by counting the number of photons that impinge on each of the individual pixels in the camera of a Nokia N9 smartphone.
Comparison of discrete multi-tone and pulse amplitude modulation for beyond 100 Gbps short-reach application
NASA Astrophysics Data System (ADS)
Nishihara, Masato; Kai, Yutaka; Tanaka, Toshiki; Takahara, Tomoo; Li, Lei; Yan, Weizhen; Liu, Bo; Tao, Zhenning; Rasmussen, Jens C.
Advanced multi-level modulation is an attractive modulation technique for beyond 100 Gbps short reach optical transmission system. Above all, discrete multi-tone (DMT) technique and pulse amplitude modulation (PAM) technique are the strong candidates. We compared the 100 Gbps transmission characteristics of DMT and PAM by simulation and experiment. The comparison was done by using same devices and only the digital signal processing was changed. We studied the transmission distance dependence for 0.5 to 40 km and the impact of the frequency responses of the optical devices. Finally we discuss the features of the both modulation techniques.
On the spectral and conservation properties of nonlinear discretization operators
NASA Astrophysics Data System (ADS)
Fauconnier, D.; Dick, E.
Following the study of Pirozzoli [1], the objective of the present work is to provide a detailed theoretical analysis of the spectral properties and the conservation properties of nonlinear finite difference discretizations. First, a Nonlinear Spectral Analysis (NSA) is proposed in order to study the statistical behavior of the modified wavenumber of a nonlinear finite difference operator, for a large set of synthetic scalar fields with prescribed energy spectrum and random phase. Second, the necessary conditions for local and global conservation of momentum and kinetic energy are derived and verified for nonlinear discretizations. Because the nonlinear mechanisms result in a violation of the energy conservation conditions, the NSA is used to quantify the energy imbalance. Third, the effect of aliasing errors due to the nonlinearity is analyzed. Finally, the theoretical observations are verified for two simple, thought relevant, numerical simulations.
Discrete neural dynamic programming in wheeled mobile robot control
NASA Astrophysics Data System (ADS)
Hendzel, Zenon; Szuster, Marcin
In this paper we propose a discrete algorithm for a tracking control of a two-wheeled mobile robot (WMR), using an advanced Adaptive Critic Design (ACD). We used Dual-Heuristic Programming (DHP) algorithm, that consists of two parametric structures implemented as Neural Networks (NNs): an actor and a critic, both realized in a form of Random Vector Functional Link (RVFL) NNs. In the proposed algorithm the control system consists of the DHP adaptive critic, a PD controller and a supervisory term, derived from the Lyapunov stability theorem. The supervisory term guaranties a stable realization of a tracking movement in a learning phase of the adaptive critic structure and robustness in face of disturbances. The discrete tracking control algorithm works online, uses the WMR model for a state prediction and does not require a preliminary learning. Verification has been conducted to illustrate the performance of the proposed control algorithm, by a series of experiments on the WMR Pioneer 2-DX.
Statistics of primordial density perturbations from discrete seed masses
NASA Technical Reports Server (NTRS)
Scherrer, Robert J.; Bertschinger, Edmund
The statistics of density perturbations for general distributions of seed masses with arbitrary matter accretion is examined. Formal expressions for the power spectrum, the N-point correlation functions, and the density distribution function are derived. These results are applied to the case of uncorrelated seed masses, and power spectra are derived for accretion of both hot and cold dark matter plus baryons. The reduced moments (cumulants) of the density distribution are computed and used to obtain a series expansion for the density distribution function. Analytic results are obtained for the density distribution function in the case of a distribution of seed masses with a spherical top-hat accretion pattern. More generally, the formalism makes it possible to give a complete characterization of the statistical properties of any random field generated from a discrete linear superposition of kernels. In particular, the results can be applied to density fields derived by smoothing a discrete set of points with a window function.
Multilevel Workflow System in the ATLAS Experiment
NASA Astrophysics Data System (ADS)
Borodin, M.; De, K.; Garcia Navarro, J.; Golubkov, D.; Klimentov, A.; Maeno, T.; Vaniachine, A.; ATLAS Collaboration
The ATLAS experiment is scaling up Big Data processing for the next LHC run using a multilevel workflow system comprised of many layers. In Big Data processing ATLAS deals with datasets, not individual files. Similarly a task (comprised of many jobs) has become a unit of the ATLAS workflow in distributed computing, with about 0.8M tasks processed per year. In order to manage the diversity of LHC physics (exceeding 35K physics samples per year), the individual data processing tasks are organized into workflows. For example, the Monte Carlo workflow is composed of many steps: generate or configure hard-processes, hadronize signal and minimum-bias (pileup) events, simulate energy deposition in the ATLAS detector, digitize electronics response, simulate triggers, reconstruct data, convert the reconstructed data into ROOT ntuples for physics analysis, etc. Outputs are merged and/or filtered as necessary to optimize the chain. The bi-level workflow manager - ProdSys2 - generates actual workflow tasks and their jobs are executed across more than a hundred distributed computing sites by PanDA - the ATLAS job-level workload management system. On the outer level, the Database Engine for Tasks (DEfT) empowers production managers with templated workflow definitions. On the next level, the Job Execution and Definition Interface (JEDI) is integrated with PanDA to provide dynamic job definition tailored to the sites capabilities. We report on scaling up the production system to accommodate a growing number of requirements from main ATLAS areas: Trigger, Physics and Data Preparation.
Multilevel summation method for electrostatic force evaluation.
Hardy, David J; Wu, Zhe; Phillips, James C; Stone, John E; Skeel, Robert D; Schulten, Klaus
The multilevel summation method (MSM) offers an efficient algorithm utilizing convolution for evaluating long-range forces arising in molecular dynamics simulations. Shifting the balance of computation and communication, MSM provides key advantages over the ubiquitous particle–mesh Ewald (PME) method, offering better scaling on parallel computers and permitting more modeling flexibility, with support for periodic systems as does PME but also for semiperiodic and nonperiodic systems. The version of MSM available in the simulation program NAMD is described, and its performance and accuracy are compared with the PME method. The accuracy feasible for MSM in practical applications reproduces PME results for water property calculations of density, diffusion constant, dielectric constant, surface tension, radial distribution function, and distance-dependent Kirkwood factor, even though the numerical accuracy of PME is higher than that of MSM. Excellent agreement between MSM and PME is found also for interface potentials of air–water and membrane–water interfaces, where long-range Coulombic interactions are crucial. Applications demonstrate also the suitability of MSM for systems with semiperiodic and nonperiodic boundaries. For this purpose, simulations have been performed with periodic boundaries along directions parallel to a membrane surface but not along the surface normal, yielding membrane pore formation induced by an imbalance of charge across the membrane. Using a similar semiperiodic boundary condition, ion conduction through a graphene nanopore driven by an ion gradient has been simulated. Furthermore, proteins have been simulated inside a single spherical water droplet. Finally, parallel scalability results show the ability of MSM to outperform PME when scaling a system of modest size (less than 100 K atoms) to over a thousand processors, demonstrating the suitability of MSM for large-scale parallel simulation. PMID:25691833
A robust multilevel simultaneous eigenvalue solver
NASA Technical Reports Server (NTRS)
Costiner, Sorin; Taasan, Shlomo
Multilevel (ML) algorithms for eigenvalue problems are often faced with several types of difficulties such as: the mixing of approximated eigenvectors by the solution process, the approximation of incomplete clusters of eigenvectors, the poor representation of solution on coarse levels, and the existence of close or equal eigenvalues. Algorithms that do not treat appropriately these difficulties usually fail, or their performance degrades when facing them. These issues motivated the development of a robust adaptive ML algorithm which treats these difficulties, for the calculation of a few eigenvectors and their corresponding eigenvalues. The main techniques used in the new algorithm include: the adaptive completion and separation of the relevant clusters on different levels, the simultaneous treatment of solutions within each cluster, and the robustness tests which monitor the algorithm's efficiency and convergence. The eigenvectors' separation efficiency is based on a new ML projection technique generalizing the Rayleigh Ritz projection, combined with a technique, the backrotations. These separation techniques, when combined with an FMG formulation, in many cases lead to algorithms of O(qN) complexity, for q eigenvectors of size N on the finest level. Previously developed ML algorithms are less focused on the mentioned difficulties. Moreover, algorithms which employ fine level separation techniques are of O(q(sub 2)N) complexity and usually do not overcome all these difficulties. Computational examples are presented where Schrodinger type eigenvalue problems in 2-D and 3-D, having equal and closely clustered eigenvalues, are solved with the efficiency of the Poisson multigrid solver. A second order approximation is obtained in O(qN) work, where the total computational work is equivalent to only a few fine level relaxations per eigenvector.
Multilevel Summation Method for Electrostatic Force Evaluation
The multilevel summation method (MSM) offers an efficient algorithm utilizing convolution for evaluating long-range forces arising in molecular dynamics simulations. Shifting the balance of computation and communication, MSM provides key advantages over the ubiquitous particle–mesh Ewald (PME) method, offering better scaling on parallel computers and permitting more modeling flexibility, with support for periodic systems as does PME but also for semiperiodic and nonperiodic systems. The version of MSM available in the simulation program NAMD is described, and its performance and accuracy are compared with the PME method. The accuracy feasible for MSM in practical applications reproduces PME results for water property calculations of density, diffusion constant, dielectric constant, surface tension, radial distribution function, and distance-dependent Kirkwood factor, even though the numerical accuracy of PME is higher than that of MSM. Excellent agreement between MSM and PME is found also for interface potentials of air–water and membrane–water interfaces, where long-range Coulombic interactions are crucial. Applications demonstrate also the suitability of MSM for systems with semiperiodic and nonperiodic boundaries. For this purpose, simulations have been performed with periodic boundaries along directions parallel to a membrane surface but not along the surface normal, yielding membrane pore formation induced by an imbalance of charge across the membrane. Using a similar semiperiodic boundary condition, ion conduction through a graphene nanopore driven by an ion gradient has been simulated. Furthermore, proteins have been simulated inside a single spherical water droplet. Finally, parallel scalability results show the ability of MSM to outperform PME when scaling a system of modest size (less than 100 K atoms) to over a thousand processors, demonstrating the suitability of MSM for large-scale parallel simulation. PMID:25691833
A Longitudinal Multilevel Study of Individual Characteristics and Classroom Norms in Explaining Bullying Behaviors.
Sentse, Miranda; Veenstra, René; Kiuru, Noona; Salmivalli, Christina
This three-wave longitudinal study was set out to examine the interplay between individual characteristics (social standing in the classroom) and descriptive and injunctive classroom norms (behavior and attitudes, respectively) in explaining subsequent bullying behavior, defined as initiating, assisting, or reinforcing bullying. The target sample contained fourth- to sixth-grade students (n = 2,051) who attended the control schools in the Finnish evaluation of the KiVa antibullying program. Random slope multilevel analyses revealed that, over time, higher popularity or rejection, or lower acceptance were associated with increases in bullying behaviors, especially in classrooms with a high descriptive bullying norm. In contrast, the injunctive norm did not moderate the associations between social standing and engagement in bullying, except for children high on popularity. Theoretical and practical implications of the results are discussed. PMID:25370007
Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.
Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S
We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects. PMID:25697370
Exact and approximate ensemble treatments of thermal pairing in a multilevel model
Hung, N. Quang; Dang, N. Dinh
A systematic comparison is conducted for pairing properties of finite systems at nonzero temperature as predicted by the exact solutions of the pairing problem embedded in three principal statistical ensembles, as well as the unprojected (FTBCS1+SCQRPA) and Lipkin+Nogami projected (FTLN1+SCQRPA) theories that include the quasiparticle number fluctuation and coupling to pair vibrations within the self-consistent quasiparticle random-phase approximation. The numerical calculations are performed for the pairing gap, total energy, heat capacity, entropy, and microcanonical temperature within the doubly folded equidistant multilevel pairing model. The FTLN1+SCQRPA predictions agree best with the exact grand-canonical results. In general, all approaches clearly show that the superfluid-normal phase transition is smoothed out in finite systems. A novel formula is suggested for extracting the empirical pairing gap in reasonable agreement with the exact canonical results.
Unprotected sex among heterosexually active homeless men: results from a multi-level dyadic analysis.
Kennedy, David P; Wenzel, Suzanne L; Brown, Ryan; Tucker, Joan S; Golinelli, Daniela
HIV is a serious public health problem for homeless populations. Homeless men who have sex with women have received less attention in the HIV risk literature than other homeless populations. This research uses multi-level modeling to investigate the context of unprotected sex among heterosexually active homeless men in the Skid Row area of Los Angeles. Based on interviews with 305 randomly selected men who discussed 665 of their recent female sexual relationships, this project investigates the correlates of unprotected sex during the past 6 months at the partnership, individual, and social network levels. Several different measures of relationship closeness and lack of communication about HIV/condoms were associated with unprotected sex. Controlling for relationship factors, men's negative attitudes towards condoms, mental health, and higher number of male sex partners also were associated with having unprotected sex with female partners. We discuss the implications of these findings for health interventions. PMID:23212852
Socioemotional, Personality, and Biological Development: Illustrations from a Multilevel Developmental Psychopathology Perspective on Child Maltreatment.
Cicchetti, Dante
Developmental theories can be affirmed, challenged, and augmented by incorporating knowledge about atypical ontogenesis. Investigations of the biological, socioemotional, and personality development in individuals with high-risk conditions and psychopathological disorders can provide an entrée into the study of system organization, disorganization, and reorganization. This article examines child maltreatment to illustrate the benefit that can be derived from the study of individuals subjected to nonnormative caregiving experiences. Relative to an average expectable environment, which consists of a species-specific range of environmental conditions that support adaptive development among genetically normal individuals, maltreating families fail to provide many of the experiences that are required for normal development. Principles gleaned from the field of developmental psychopathology provide a framework for understanding multilevel functioning in normality and pathology. Knowledge of normative developmental processes provides the impetus to design and implement randomized control trial (RCT) interventions that can promote resilient functioning in maltreated children. PMID:26726964
Study of Multi-level Characteristics for 3D Vertical Resistive Switching Memory
Bai, Yue; Wu, Huaqiang; Wu, Riga; Zhang, Ye; Deng, Ning; Yu, Zhiping; Qian, He
Three-dimensional (3D) integration and multi-level cell (MLC) are two attractive technologies to achieve ultra-high density for mass storage applications. In this work, a three-layer 3D vertical AlOδ/Ta2O5-x/TaOy resistive random access memories were fabricated and characterized. The vertical cells in three layers show good uniformity and high performance (e.g. >1000X HRS/LRS windows, >1010 endurance cycles, >104 s retention times at 125°C). Meanwhile, four level MLC is demonstrated with two operation strategies, current controlled scheme (CCS) and voltage controlled scheme (VCS). The switching mechanism of 3D vertical RRAM cells is studied based on temperature-dependent transport characteristics. Furthermore, the applicability of CCS and VCS in 3D vertical RRAM array is compared using resistor network circuit simulation. PMID:25047906
Interface-induced two-step RESET for filament-based multi-level resistive memory
NASA Astrophysics Data System (ADS)
Yuan, Fang; Shen, Shanshan; Zhang, Zhigang; Pan, Liyang; Xu, Jun
In this paper, a two-step RESET switching behavior of Ag/Al2O3/HfO2/Pt bilayer resistive random access memory (RRAM) devices is investigated. The interface between the two oxide layers is responsible for the special two-step RESET switching. When the conducting filaments have ruptured in the lower layer, the interface can protect the Ag ions of the filaments from breaking in the upper layer due to the trapped charges or defects at the interface. Therefore, a stable middle resistance state (MRS) is realized and the device exhibits a terrace-like I-V curve during the RESET operations. A filament-based switching mechanism combined with the electron hopping theory is proposed to explain the physical nature of the two-step RESET behavior. Furthermore, a good multi-level resistive switching performance with excellent endurance and retention reliability is obtained.
Study of multi-level characteristics for 3D vertical resistive switching memory.
Bai, Yue; Wu, Huaqiang; Wu, Riga; Zhang, Ye; Deng, Ning; Yu, Zhiping; Qian, He
Three-dimensional (3D) integration and multi-level cell (MLC) are two attractive technologies to achieve ultra-high density for mass storage applications. In this work, a three-layer 3D vertical AlOδ/Ta2O5-x/TaOy resistive random access memories were fabricated and characterized. The vertical cells in three layers show good uniformity and high performance (e.g. >1000X HRS/LRS windows, >10(10) endurance cycles, >10(4) s retention times at 125°C). Meanwhile, four level MLC is demonstrated with two operation strategies, current controlled scheme (CCS) and voltage controlled scheme (VCS). The switching mechanism of 3D vertical RRAM cells is studied based on temperature-dependent transport characteristics. Furthermore, the applicability of CCS and VCS in 3D vertical RRAM array is compared using resistor network circuit simulation. PMID:25047906
Multilevel animal societies can emerge from cultural transmission.
Cantor, Maurício; Shoemaker, Lauren G; Cabral, Reniel B; Flores, César O; Varga, Melinda; Whitehead, Hal
Multilevel societies, containing hierarchically nested social levels, are remarkable social structures whose origins are unclear. The social relationships of sperm whales are organized in a multilevel society with an upper level composed of clans of individuals communicating using similar patterns of clicks (codas). Using agent-based models informed by an 18-year empirical study, we show that clans are unlikely products of stochastic processes (genetic or cultural drift) but likely originate from cultural transmission via biased social learning of codas. Distinct clusters of individuals with similar acoustic repertoires, mirroring the empirical clans, emerge when whales learn preferentially the most common codas (conformism) from behaviourally similar individuals (homophily). Cultural transmission seems key in the partitioning of sperm whales into sympatric clans. These findings suggest that processes similar to those that generate complex human cultures could not only be at play in non-human societies but also create multilevel social structures in the wild. PMID:26348688
Parametric Multi-Level Tiling of Imperfectly Nested Loops
Hartono, Albert; Baskaran, Muthu M.; Bastoul, Cedric; Cohen, Albert; Krishnamoorthy, Sriram; Norris, Boyana; Ramanujam, J.; Sadayappan, Ponnuswamy
Tiling is a critical loop transformation for generating high-performance code on modern architectures. Efficient generation of multilevel tiled code is essential to exploit several levels of parallelism and/or to maximize data reuse in deep memory hierarchies. Tiled loops with parameterized tile sizes (not compile time constants) facilitate runtime feedback and dynamic optimizations used in iterative compilation and automatic tuning. The existing parametric multilevel tiling approach has focused on transformation for perfectly nested loops, where all assignment statements are contained inside the innermost loop of a loop nest. Previous solutions to tiling for imperfect loop nests are limited to the case where tile sizes are fixed. In this paper, we present an approach to parameterized multilevel tiling for imperfectly nested loops. Our tiling algorithm generates loops that iterate over full rectangular tiles that are amenable for potential compiler optimizations such as register tiling. Experimental results using a number of computational benchmarks demonstrate the effectiveness of our tiling approach.
A multilevel memetic algorithm for large SAT-encoded problems.
Bouhmala, Noureddine
Many researchers have focused on the satisfiability problem and on many of its variants due to its applicability in many areas of artificial intelligence. This NP-complete problem refers to the task of finding a satisfying assignment that makes a Boolean expression evaluate to True. In this work, we introduce a memetic algorithm that makes use of the multilevel paradigm. The multilevel paradigm refers to the process of dividing large and difficult problems into smaller ones, which are hopefully much easier to solve, and then work backward toward the solution of the original problem, using a solution from a previous level as a starting solution at the next level. Results comparing the memetic with and without the multilevel paradigm are presented using problem instances drawn from real industrial hardware designs. PMID:22540191
Multilevel animal societies can emerge from cultural transmission
Cantor, Maurício; Shoemaker, Lauren G.; Cabral, Reniel B.; Flores, César O.; Varga, Melinda; Whitehead, Hal
Multilevel societies, containing hierarchically nested social levels, are remarkable social structures whose origins are unclear. The social relationships of sperm whales are organized in a multilevel society with an upper level composed of clans of individuals communicating using similar patterns of clicks (codas). Using agent-based models informed by an 18-year empirical study, we show that clans are unlikely products of stochastic processes (genetic or cultural drift) but likely originate from cultural transmission via biased social learning of codas. Distinct clusters of individuals with similar acoustic repertoires, mirroring the empirical clans, emerge when whales learn preferentially the most common codas (conformism) from behaviourally similar individuals (homophily). Cultural transmission seems key in the partitioning of sperm whales into sympatric clans. These findings suggest that processes similar to those that generate complex human cultures could not only be at play in non-human societies but also create multilevel social structures in the wild. PMID:26348688
Multi-level Hierarchical Poly Tree computer architectures
NASA Technical Reports Server (NTRS)
Padovan, Joe; Gute, Doug
Based on the concept of hierarchical substructuring, this paper develops an optimal multi-level Hierarchical Poly Tree (HPT) parallel computer architecture scheme which is applicable to the solution of finite element and difference simulations. Emphasis is given to minimizing computational effort, in-core/out-of-core memory requirements, and the data transfer between processors. In addition, a simplified communications network that reduces the number of I/O channels between processors is presented. HPT configurations that yield optimal superlinearities are also demonstrated. Moreover, to generalize the scope of applicability, special attention is given to developing: (1) multi-level reduction trees which provide an orderly/optimal procedure by which model densification/simplification can be achieved, as well as (2) methodologies enabling processor grading that yields architectures with varying types of multi-level granularity.
Mediation and Spillover Effects in Group-Randomized Trials with Application to the 4Rs Evaluation
ERIC Educational Resources Information Center
VanderWeele, Tyler J.; Hong, Guanglei; Jones, Stephanie M.; Brown, Joshua L.
In this paper the authors extend recent work on mediation in a multilevel setting and on causal inference under interference among units to develop a template for the mediation analysis of group randomized educational interventions. The present work will contribute to the literature on interference, in particular on interference in the context of…
Examples of Mixed-Effects Modeling with Crossed Random Effects and with Binomial Data
ERIC Educational Resources Information Center
Quene, Hugo; van den Bergh, Huub
Psycholinguistic data are often analyzed with repeated-measures analyses of variance (ANOVA), but this paper argues that mixed-effects (multilevel) models provide a better alternative method. First, models are discussed in which the two random factors of participants and items are crossed, and not nested. Traditional ANOVAs are compared against…
The Effect of Perceived Instructional Effectiveness on Student Loyalty: A Multilevel Structural Equation Model
ERIC Educational Resources Information Center
Simsek, Gulhayat Golbasi; Noyan, Fatma
Social sciences research often entails the analysis of data with a multilevel structure. An example of multilevel data is containing measurement on university students nested within instructors. This paper concentrates on multilevel analysis of structural equation modeling with educational data. Data used in this study were gathered from 17647…
Multilevel Modeling: Applications to Research on the Assessment of Student Learning, Engagement, and Developmental Outcomes
ERIC Educational Resources Information Center
Chen, Pu-Shih Daniel; Cragg, Kristina
Understanding the suitability of multilevel modeling in the context of institutional research (IR) may ease the doubts of some IR professionals. However, the need for training on how to conduct and report multilevel modeling analysis remains. A major roadblock hindering the proliferation of multilevel modeling in IR is the perception that…
Multilevel SEM Strategies for Evaluating Mediation in Three-Level Data
ERIC Educational Resources Information Center
Preacher, Kristopher J.
Strategies for modeling mediation effects in multilevel data have proliferated over the past decade, keeping pace with the demands of applied research. Approaches for testing mediation hypotheses with 2-level clustered data were first proposed using multilevel modeling (MLM) and subsequently using multilevel structural equation modeling (MSEM) to…
Driven discrete time quantum walks
NASA Astrophysics Data System (ADS)
Hamilton, Craig S.; Barkhofen, Sonja; Sansoni, Linda; Jex, Igor; Silberhorn, Christine
We introduce the driven discrete time quantum walk (QW), where walkers are added during the walk instead of only at the beginning. This leads to interference in walker number and very different dynamics when compared to the original QW. These dynamics have two regimes, which we illustrate using the one-dimensional line. Then, we explore a search application which has certain advantages over current search protocols, namely that it does not require a complicated initial state nor a specific measurement time to observe the marked state. Finally, we describe a potential experimental implementation using existing technology.
Discrete Signal Processing on Graphs: Sampling Theory
NASA Astrophysics Data System (ADS)
Chen, Siheng; Varma, Rohan; Sandryhaila, Aliaksei; Kovacevic, Jelena
We propose a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory. We show that perfect recovery is possible for graph signals bandlimited under the graph Fourier transform. The sampled signal coefficients form a new graph signal, whose corresponding graph structure preserves the first-order difference of the original graph signal. For general graphs, an optimal sampling operator based on experimentally designed sampling is proposed to guarantee perfect recovery and robustness to noise; for graphs whose graph Fourier transforms are frames with maximal robustness to erasures as well as for Erd\\H{o}s-R\\'enyi graphs, random sampling leads to perfect recovery with high probability. We further establish the connection to the sampling theory of finite discrete-time signal processing and previous work on signal recovery on graphs. To handle full-band graph signals, we propose a graph filter bank based on sampling theory on graphs. Finally, we apply the proposed sampling theory to semi-supervised classification on online blogs and digit images, where we achieve similar or better performance with fewer labeled samples compared to previous work.
Profiling hospitals based on emergency readmission: a multilevel transition modelling approach.
Demir, Eren; Chaussalet, Thierry; Adeyemi, Shola; Toffa, Sam
Emergency readmission is seen as an important part of the United Kingdom government policy to improve the quality of care that patients receive. In this context, patients and the public have the right to know how well different health organizations are performing. Most methods for profiling estimate the expected numbers of adverse outcomes (e.g. readmission, mortality) for each organization. A number of statistical concerns have been raised, such as the differences in hospital sizes and the unavailability of relevant data for risk adjustment. Having recognized these statistical concerns, a new framework known as the multilevel transition model is developed. Hospital specific propensities of the first, second and further readmissions are considered to be measures of performance, where these measures are used to define a new performance index. During the period 1997 and 2004, the national (English) hospital episodes statistics dataset comprise more than 5 million patient readmissions. Implementing a multilevel model using the complete population dataset could possibly take weeks to estimate the parameters. To resolve the problem, we extract 1000 random samples from the original data, where each random sample is likely to lead to differing hospital performance measures. For computational efficiency a Grid implementation of the model is developed. Analysing the output from the full 1000 sample, we noticed that 4 out of the 5 worst performing hospitals treating cancer patients were in London. These hospitals are known to be the leading NHS Trusts in England, providing diverse range of services to complex patients, and therefore it is inevitable to expect higher numbers of emergency readmissions. PMID:21612839
Element Agglomeration Algebraic Multilevel Monte-Carlo Library
ElagMC is a parallel C++ library for Multilevel Monte Carlo simulations with algebraically constructed coarse spaces. ElagMC enables Multilevel variance reduction techniques in the context of general unstructured meshes by using the specialized element-based agglomeration techniques implemented in ELAG (the Element-Agglomeration Algebraic Multigrid and Upscaling Library developed by U. Villa and P. Vassilevski and currently under review for public release). The ElabMC library can support different type of deterministic problems, including mixed finite element discretizationsmore » of subsurface flow problems.« less
Unconventional Coding Technique Applied to Multi-Level Polarization Modulation
NASA Astrophysics Data System (ADS)
Rutigliano, G. G.; Betti, S.; Perrone, P.
A new technique is proposed to improve information confidentiality in optical-fiber communications without bandwidth consumption. A pseudorandom vectorial sequence was generated by a dynamic system algorithm and used to codify a multi-level polarization modulation based on the Stokes vector. Optical-fiber birefringence, usually considered as a disturbance, was exploited to obfuscate the signal transmission. At the receiver end, the same pseudorandom sequence was generated and used to decode the multi-level polarization modulated signal. The proposed scheme, working at the physical layer, provides strong information security without introducing complex processing and thus latency.
Discreteness effects in population dynamics
NASA Astrophysics Data System (ADS)
Guevara Hidalgo, Esteban; Lecomte, Vivien
We analyse numerically the effects of small population size in the initial transient regime of a simple example population dynamics. These effects play an important role for the numerical determination of large deviation functions of additive observables for stochastic processes. A method commonly used in order to determine such functions is the so-called cloning algorithm which in its non-constant population version essentially reduces to the determination of the growth rate of a population, averaged over many realizations of the dynamics. However, the averaging of populations is highly dependent not only on the number of realizations of the population dynamics, and on the initial population size but also on the cut-off time (or population) considered to stop their numerical evolution. This may result in an over-influence of discreteness effects at initial times, caused by small population size. We overcome these effects by introducing a (realization-dependent) time delay in the evolution of populations, additional to the discarding of the initial transient regime of the population growth where these discreteness effects are strong. We show that the improvement in the estimation of the large deviation function comes precisely from these two main contributions.
An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models
Li, J.; Gray, B.R.; Bates, D.M.
Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.
Multilevel Resistance Programming in Conductive Bridge Resistive Memory
NASA Astrophysics Data System (ADS)
Mahalanabis, Debayan
This work focuses on the existence of multiple resistance states in a type of emerging non-volatile resistive memory device known commonly as Programmable Metallization Cell (PMC) or Conductive Bridge Random Access Memory (CBRAM), which can be important for applications such as multi-bit memory as well as non-volatile logic and neuromorphic computing. First, experimental data from small signal, quasi-static and pulsed mode electrical characterization of such devices are presented which clearly demonstrate the inherent multi-level resistance programmability property in CBRAM devices. A physics based analytical CBRAM compact model is then presented which simulates the ion-transport dynamics and filamentary growth mechanism that causes resistance change in such devices. Simulation results from the model are fitted to experimental dynamic resistance switching characteristics. The model designed using Verilog-a language is computation-efficient and can be integrated with industry standard circuit simulation tools for design and analysis of hybrid circuits involving both CMOS and CBRAM devices. Three main circuit applications for CBRAM devices are explored in this work. Firstly, the susceptibility of CBRAM memory arrays to single event induced upsets is analyzed via compact model simulation and experimental heavy ion testing data that show possibility of both high resistance to low resistance and low resistance to high resistance transitions due to ion strikes. Next, a non-volatile sense amplifier based flip-flop architecture is proposed which can help make leakage power consumption negligible by allowing complete shutdown of power supply while retaining its output data in CBRAM devices. Reliability and energy consumption of the flip-flop circuit for different CBRAM low resistance levels and supply voltage values are analyzed and compared to CMOS designs. Possible extension of this architecture for threshold logic function computation using the CBRAM devices as re
Multilevel methods for transport equations in diffusive regimes
NASA Technical Reports Server (NTRS)
Manteuffel, Thomas A.; Ressel, Klaus
We consider the numerical solution of the single-group, steady state, isotropic transport equation. An analysis by means of the moment equations shows that a discrete ordinate S(sub N) discretization in direction (angle) with a least squares finite element discretization in space does not behave properly in the diffusion limit. A scaling of the S(sub N) equations is introduced so that the least squares discretization has the correct diffusion limit. For the resulting discrete system a full multigrid algorithm was developed.
Convergence Time towards Periodic Orbits in Discrete Dynamical Systems
San Martín, Jesús; Porter, Mason A.
We investigate the convergence towards periodic orbits in discrete dynamical systems. We examine the probability that a randomly chosen point converges to a particular neighborhood of a periodic orbit in a fixed number of iterations, and we use linearized equations to examine the evolution near that neighborhood. The underlying idea is that points of stable periodic orbit are associated with intervals. We state and prove a theorem that details what regions of phase space are mapped into these intervals (once they are known) and how many iterations are required to get there. We also construct algorithms that allow our theoretical results to be implemented successfully in practice. PMID:24736594
Convergence time towards periodic orbits in discrete dynamical systems.
San Martín, Jesús; Porter, Mason A
We investigate the convergence towards periodic orbits in discrete dynamical systems. We examine the probability that a randomly chosen point converges to a particular neighborhood of a periodic orbit in a fixed number of iterations, and we use linearized equations to examine the evolution near that neighborhood. The underlying idea is that points of stable periodic orbit are associated with intervals. We state and prove a theorem that details what regions of phase space are mapped into these intervals (once they are known) and how many iterations are required to get there. We also construct algorithms that allow our theoretical results to be implemented successfully in practice. PMID:24736594
Quantum random walks do not need a coin toss
Patel, Apoorva; Raghunathan, K.S.; Rungta, Pranaw
Classical randomized algorithms use a coin toss instruction to explore different evolutionary branches of a problem. Quantum algorithms, on the other hand, can explore multiple evolutionary branches by mere superposition of states. Discrete quantum random walks, studied in the literature, have nonetheless used both superposition and a quantum coin toss instruction. This is not necessary, and a discrete quantum random walk without a quantum coin toss instruction is defined and analyzed here. Our construction eliminates quantum entanglement between the coin and the position degrees of freedom from the algorithm, and the results match those obtained with a quantum coin toss instruction.
NASA Technical Reports Server (NTRS)
Messaro. Semma; Harrison, Phillip
Ares I Zonal Random vibration environments due to acoustic impingement and combustion processes are develop for liftoff, ascent and reentry. Random Vibration test criteria for Ares I Upper Stage pyrotechnic components are developed by enveloping the applicable zonal environments where each component is located. Random vibration tests will be conducted to assure that these components will survive and function appropriately after exposure to the expected vibration environments. Methodology: Random Vibration test criteria for Ares I Upper Stage pyrotechnic components were desired that would envelope all the applicable environments where each component was located. Applicable Ares I Vehicle drawings and design information needed to be assessed to determine the location(s) for each component on the Ares I Upper Stage. Design and test criteria needed to be developed by plotting and enveloping the applicable environments using Microsoft Excel Spreadsheet Software and documenting them in a report Using Microsoft Word Processing Software. Conclusion: Random vibration liftoff, ascent, and green run design & test criteria for the Upper Stage Pyrotechnic Components were developed by using Microsoft Excel to envelope zonal environments applicable to each component. Results were transferred from Excel into a report using Microsoft Word. After the report is reviewed and edited by my mentor it will be submitted for publication as an attachment to a memorandum. Pyrotechnic component designers will extract criteria from my report for incorporation into the design and test specifications for components. Eventually the hardware will be tested to the environments I developed to assure that the components will survive and function appropriately after exposure to the expected vibration environments.
Observers for discrete-time nonlinear systems
NASA Astrophysics Data System (ADS)
Grossman, Walter D.
Observer synthesis for discrete-time nonlinear systems with special applications to parameter estimation is analyzed. Two new types of observers are developed. The first new observer is an adaptation of the Friedland continuous-time parameter estimator to discrete-time systems. The second observer is an adaptation of the continuous-time Gauthier observer to discrete-time systems. By adapting these observers to discrete-time continuous-time parameter estimation problems which were formerly intractable become tractable. In addition to the two newly developed observers, two observers already described in the literature are analyzed and deficiencies with respect to noise rejection are demonstrated. Improved versions of these observers are proposed and their performance demonstrated. The issues of discrete-time observability, discrete-time system inversion, and optimal probing are also addressed.
The Pitfalls of Ignoring Multilevel Design in National Datasets.
ERIC Educational Resources Information Center
Roberts, J. Kyle
This paper examines the differences between multilevel modeling and weighted ordinary least squares (OLS) regression for analyzing data from the National Educational Longitudinal Study 1988 (NELS:88). The final sample consisted of 718 students in 298 schools. Eighteen variables from the NELS:88 dataset were used, with the dependent variable being…
Multiple Imputation of Multilevel Missing Data-Rigor versus Simplicity
ERIC Educational Resources Information Center
Drechsler, Jörg
Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…
Multilevel Mediation Modeling in Group-Based Intervention Studies.
ERIC Educational Resources Information Center
Krull, Jennifer L.; MacKinnon, David P.
Proposes and evaluates a method to test for mediation in multilevel data sets formed when an intervention administered to groups is designed to produce change in individual mediator and outcome variables. Applies the method to the ATLAS intervention designed to decrease steroid use among high school football players. (SLD)
Attachment, Autonomy, and Emotional Reliance: A Multilevel Model
ERIC Educational Resources Information Center
Lynch, Martin F.
This article reports a test of a multilevel model investigating how attachment security and autonomy contribute to emotional reliance, or the willingness to seek interpersonal support. Participants ("N" = 247) completed online measures of attachment, autonomy, emotional reliance, and vitality with respect to several everyday…
School Climate and Psychosomatic Health: A Multilevel Analysis
ERIC Educational Resources Information Center
Modin, Bitte; Ostberg, Viveca
This study examined the importance of aspects of the school climate for adolescents' psychosomatic health using multilevel modelling. Analyses were based on 18,571 ninth-grade students distributed over 1,026 classes and 284 schools in the greater Stockholm area in 2004 and 2006. Both individual- and contextual-level associations between aspects of…
Examining Elementary Social Studies Marginalization: A Multilevel Model
ERIC Educational Resources Information Center
Fitchett, Paul G.; Heafner, Tina L.; Lambert, Richard G.
Utilizing data from the National Center for Education Statistics Schools and Staffing Survey (SASS), a multilevel model (Hierarchical Linear Model) was developed to examine the association of teacher/classroom and state level indicators on reported elementary social studies instructional time. Findings indicated that state testing policy was a…
Service Learning: An Example of Multilevel School Social Work Practice
ERIC Educational Resources Information Center
McKay, Cassandra; Johnson, Annette
School social work interventions that address social and emotional learning are often confined to micro-level practice. Yet the social work profession thrives on multilevel practice in all settings (micro, as well as macro). School social workers can play a pivotal role in engaging youth to become prosocial participants of their school and…
Hierarchical Data Structures, Institutional Research, and Multilevel Modeling
ERIC Educational Resources Information Center
O'Connell, Ann A.; Reed, Sandra J.
Multilevel modeling (MLM), also referred to as hierarchical linear modeling (HLM) or mixed models, provides a powerful analytical framework through which to study colleges and universities and their impact on students. Due to the natural hierarchical structure of data obtained from students or faculty in colleges and universities, MLM offers many…
Concorde and Discord: The Art of Multilevel Modelling
ERIC Educational Resources Information Center
Hutchison, Dougal; Schagen, Ian
A recent issue of "International Journal of Research & Methods in Education" (IJRME) contained a challenging article by Stephen Gorard ["The Dubious Benefits of Multi-Level Modelling," "International Journal of Research & Method in Education," Vol. 30 (2), p221-236 (2007)] in which he attacks aspects of current practice in statistical modelling,…
Smart RTI: A Next-Generation Approach to Multilevel Prevention
ERIC Educational Resources Information Center
Fuchs, Douglas; Fuchs, Lynn S.; Compton, Donald L.
During the past decade, responsiveness to intervention (RTI) has become popular among many practitioners as a means of transforming schooling into a multilevel prevention system. Popularity aside, its successful implementation requires ambitious intent, a comprehensive structure, and coordinated service delivery. An effective RTI also depends on…
New multi-level codes over GF(q)
NASA Technical Reports Server (NTRS)
Wu, Jiantian; Costello, Daniel J., Jr.
Set partitioning to multi-dimensional signal spaces over GF(q), particularly GF sup q-1(q) and GF sup q (q), and show how to construct both multi-level block codes and multi-level trellis codes over GF(q). Two classes of multi-level (n, k, d) block codes over GF(q) with block length n, number of information symbols k, and minimum distance d sub min greater than or = d, are presented. These two classes of codes use Reed-Solomon codes as component codes. They can be easily decoded as block length q-1 Reed-Solomon codes or block length q or q + 1 extended Reed-Solomon codes using multi-stage decoding. Many of these codes have larger distances than comparable q-ary block codes, as component codes. Low rate q-ary convolutional codes, work error correcting convolutional codes, and binary-to-q-ary convolutional codes can also be used to construct multi-level trellis codes over GF(q) or binary-to-q-ary trellis codes, some of which have better performance than the above block codes. All of the new codes have simple decoding algorithms based on hard decision multi-stage decoding.
Exploring the Nature of Divergent Thinking: A Multilevel Analysis
ERIC Educational Resources Information Center
Kuhn, Jorg-Tobias; Holling, Heinz
In this study, a large sample with a clustered data structure from an educational context was utilized to analyze the relationship between cognitive abilities, school type, gender, and divergent thinking. The sample comprised 1098 students in 55 classrooms. A sequence of nested multilevel regression analyses revealed that processing capacity, as a…
Criminal Victimization and Crime Risk Perception: A Multilevel Longitudinal Study
ERIC Educational Resources Information Center
Russo, Silvia; Roccato, Michele; Vieno, Alessio
In a national sample of the Italian population, surveyed four times between October 2002 and January 2007 (N = 2,008), we performed a multilevel longitudinal study aimed at predicting the increase in crime risk perception as a function of three families of independent variables, respectively lying at the within individual level (direct…
Social Capital and Health: A Review of Prospective Multilevel Studies
Murayama, Hiroshi; Fujiwara, Yoshinori; Kawachi, Ichiro
Background This article presents an overview of the concept of social capital, reviews prospective multilevel analytic studies of the association between social capital and health, and discusses intervention strategies that enhance social capital. Methods We conducted a systematic search of published peer-reviewed literature on the PubMed database and categorized studies according to health outcome. Results We identified 13 articles that satisfied the inclusion criteria for the review. In general, both individual social capital and area/workplace social capital had positive effects on health outcomes, regardless of study design, setting, follow-up period, or type of health outcome. Prospective studies that used a multilevel approach were mainly conducted in Western countries. Although we identified some cross-sectional multilevel studies that were conducted in Asian countries, including Japan, no prospective studies have been conducted in Asia. Conclusions Prospective evidence from multilevel analytic studies of the effect of social capital on health is very limited at present. If epidemiologic findings on the association between social capital and health are to be put to practical use, we must gather additional evidence and explore the feasibility of interventions that build social capital as a means of promoting health. PMID:22447212
The Formation of Parent-School Trust: A Multilevel Analysis
ERIC Educational Resources Information Center
Adams, Curt M.; Forsyth, Patrick B.; Mitchell, Roxanne M.
Purpose: The authors' focus was on understanding antecedents of parent trust toward schools. Two questions guided the inquiry: Is there a systematic difference in parent-school trust across schools? If so, what organizational conditions predict between-school variability in parent-school trust? Research Methods/Approach: Using multilevel modeling,…
Sex Differences in Science Achievement: A Multilevel Analysis.
ERIC Educational Resources Information Center
Young, Deidra J.; Fraser, Barry J.
The assertion that girls and boys in single-sex schools outperform their peers attending coeducational schools was investigated in this study with particular reference to physics achievement. The relationship between the school, the home and the student's performance in physics was also explored tentatively using multilevel analysis. The average…
Multilevel Analysis of Student Pathways to Higher Education
ERIC Educational Resources Information Center
You, Sukkyung; Nguyen, Julie
This study examined the relationship between academic preparation and post-secondary educational outcomes. To uncover the factors that influence secondary-level school course-taking patterns and outcomes, multi-level modelling was conducted using data from a nationally representative sample of US secondary-level school students from the Education…
Neighborhoods and Child Maltreatment: A Multi-Level Study.
ERIC Educational Resources Information Center
Coulton, Claudia; Korbin, Jill; Su, Marilyn
This study explores the influence of neighborhood conditions on child maltreatment. Unlike previous studies conducted with protective services data aggregated to neighborhoods, this study uses a self-report measure of child abuse potential and controls for individual risk factors in a multilevel model. The survey was completed by an adult residing…
The Dubious Benefits of Multi-Level Modeling
ERIC Educational Resources Information Center
Gorard, Stephen
This paper presents an argument against the wider adoption of complex forms of data analysis, using multi-level modeling (MLM) as an extended case study. MLM was devised to overcome some deficiencies in existing datasets, such as the bias caused by clustering. The paper suggests that MLM has an unclear theoretical and empirical basis, has not led…
A Multilevel Evaluation of a Comprehensive Child Abuse Prevention Program
ERIC Educational Resources Information Center
Lawson, Michael A.; Alameda-Lawson, Tania; Byrnes, Edward C.
Objectives: The purpose of this study is to examine the extent to which participation in a county-wide prevention program leads to improvements in protective factors associated with child abuse prevention (CAP) and whether improvements in measured protective factors relate to decreased odds of child abuse. Method: Using multilevel growth modeling,…
Gender, Reasoning Ability, and Scholastic Achievement: A Multilevel Mediation Analysis
ERIC Educational Resources Information Center
Kuhn, Jorg-Tobias; Holling, Heinz
The present study investigated gender differences in scholastic achievement (school grades in sciences and languages) as mediated by reasoning ability in a large sample with a clustered data structure from an educational context. Whereas girls outperformed boys in languages, boys excelled in sciences and reasoning. Multilevel analyses indicated a…
Determinants of Academic Entrepreneurship Behavior: A Multilevel Model
ERIC Educational Resources Information Center
Llano, Joseph Anthony
It is well established that universities encourage the acquisition and dissemination of new knowledge among university community members and beyond. However, what is less well understood is how universities encourage entrepreneurial (opportunity discovery, evaluation, and exploiting) behavior. This research investigated a multilevel model of the…
Multilevel metallization method for fabricating a metal oxide semiconductor device
NASA Technical Reports Server (NTRS)
Hollis, B. R., Jr.; Feltner, W. R.; Bouldin, D. L.; Routh, D. E. (Inventor)
An improved method is described of constructing a metal oxide semiconductor device having multiple layers of metal deposited by dc magnetron sputtering at low dc voltages and low substrate temperatures. The method provides multilevel interconnections and cross over between individual circuit elements in integrated circuits without significantly reducing the reliability or seriously affecting the yield.
People Are Variables Too: Multilevel Structural Equations Modeling
ERIC Educational Resources Information Center
Mehta, Paras D.; Neale, Michael C.
The article uses confirmatory factor analysis (CFA) as a template to explain didactically multilevel structural equation models (ML-SEM) and to demonstrate the equivalence of general mixed-effects models and ML-SEM. An intuitively appealing graphical representation of complex ML-SEMs is introduced that succinctly describes the underlying model and…
Organizational Design in High Schools: A Multilevel Analysis.
ERIC Educational Resources Information Center
Rowan, Brian; And Others
Reviews research on the effectiveness of supportive leadership, teacher participation in decision making, and staff collaboration. Investigates conditions that promote or impede the implementation of these practices by using a multilevel statistical model. Finds significant variance between public and Catholic schools, as well as within-school…
Help Seeking in Online Collaborative Groupwork: A Multilevel Analysis
ERIC Educational Resources Information Center
Du, Jianxia; Xu, Jianzhong; Fan, Xitao
This study examined predictive models for students' help seeking in the context of online collaborative groupwork. Results from multilevel analysis revealed that most of the variance in help seeking was at the individual student level, and multiple variables at the individual level were predictive of help-seeking behaviour. Help seeking was…
Multilevel Modeling: Overview and Applications to Research in Counseling Psychology
ERIC Educational Resources Information Center
Kahn, Jeffrey H.
Multilevel modeling (MLM) is rapidly becoming the standard method of analyzing nested data, for example, data from students within multiple schools, data on multiple clients seen by a smaller number of therapists, and even longitudinal data. Although MLM analyses are likely to increase in frequency in counseling psychology research, many readers…
Illustration of a Multilevel Model for Meta-Analysis
ERIC Educational Resources Information Center
de la Torre, Jimmy; Camilli, Gregory; Vargas, Sadako; Vernon, R. Fox
In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…
Needs-Based Curriculum Development Process: A Multilevel Conception
ERIC Educational Resources Information Center
Mehrmohammadi, Mahmoud
Needs assessment has been regarded as a critical stage in the curriculum development process. However, theoretical efforts aiming at proper formulation of this stage are disappointingly rare in the curriculum literature. This article is based on the recognition of this fact and proposes a multilevel conception of needs assessment in the curriculum…
Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures
NASA Technical Reports Server (NTRS)
Biegel, Bryan A. (Technical Monitor); Jost, G.; Jin, H.; Labarta J.; Gimenez, J.; Caubet, J.
Parallel programming paradigms include process level parallelism, thread level parallelization, and multilevel parallelism. This viewgraph presentation describes a detailed performance analysis of these paradigms for Shared Memory Architecture (SMA). This analysis uses the Paraver Performance Analysis System. The presentation includes diagrams of a flow of useful computations.
Homework Purposes Reported by Secondary School Students: A Multilevel Analysis
ERIC Educational Resources Information Center
Xu, Jianzhong
The author examined purposes for doing homework as perceived by 969 eighth-grade students from 52 classes and 831 11th-grade students from 45 classes. Through an exploratory factor analysis, 15 homework purposes were reduced to a 3-factor structure: peer-oriented, adult-oriented, and learning-oriented reasons. A series of 3 multilevel models were…
Outward Bound Outcome Model Validation and Multilevel Modeling
ERIC Educational Resources Information Center
Luo, Yuan-Chun
This study was intended to measure construct validity for the Outward Bound Outcomes Instrument (OBOI) and to predict outcome achievement from individual characteristics and course attributes using multilevel modeling. A sample of 2,340 participants was collected by Outward Bound USA between May and September 2009 using the OBOI. Two phases of…
Hierarchical Logistic Regression: Accounting for Multilevel Data in DIF Detection
ERIC Educational Resources Information Center
French, Brian F.; Finch, W. Holmes
The purpose of this study was to examine the performance of differential item functioning (DIF) assessment in the presence of a multilevel structure that often underlies data from large-scale testing programs. Analyses were conducted using logistic regression (LR), a popular, flexible, and effective tool for DIF detection. Data were simulated…
Multilevel Modeling of Science Achievement in the Timss Participating Countries
ERIC Educational Resources Information Center
Mohammadpour, Ebrahim; Shekarchizadeh, Ahmadreza; Kalantarrashidi, Shojae Aldin
The authors aimed to investigate the variability in science achievement as a function of student-, school- and country-level factors. Achievement scores of 134,123 eighth-grade students from 4,511 schools of 29 countries who participated in the 2007 Trends in International Mathematics and Science Study were analyzed. Multilevel modeling results…
Using Multilevel Modeling in Language Assessment Research: A Conceptual Introduction
ERIC Educational Resources Information Center
Barkaoui, Khaled
This article critiques traditional single-level statistical approaches (e.g., multiple regression analysis) to examining relationships between language test scores and variables in the assessment setting. It highlights the conceptual, methodological, and statistical problems associated with these techniques in dealing with multilevel or nested…
Multigrid methods for isogeometric discretization.
Gahalaut, K P S; Kraus, J K; Tomar, S K
We present (geometric) multigrid methods for isogeometric discretization of scalar second order elliptic problems. The smoothing property of the relaxation method, and the approximation property of the intergrid transfer operators are analyzed. These properties, when used in the framework of classical multigrid theory, imply uniform convergence of two-grid and multigrid methods. Supporting numerical results are provided for the smoothing property, the approximation property, convergence factor and iterations count for V-, W- and F-cycles, and the linear dependence of V-cycle convergence on the smoothing steps. For two dimensions, numerical results include the problems with variable coefficients, simple multi-patch geometry, a quarter annulus, and the dependence of convergence behavior on refinement levels [Formula: see text], whereas for three dimensions, only the constant coefficient problem in a unit cube is considered. The numerical results are complete up to polynomial order [Formula: see text], and for [Formula: see text] and [Formula: see text] smoothness. PMID:24511168
Discrete modelling of drapery systems
NASA Astrophysics Data System (ADS)
Thoeni, Klaus; Giacomini, Anna
Drapery systems are an efficient and cost-effective measure in preventing and controlling rockfall hazards on rock slopes. The simplest form consists of a row of ground anchors along the top of the slope connected to a horizontal support cable from which a wire mesh is suspended down the face of the slope. Such systems are generally referred to as simple or unsecured draperies (Badger and Duffy 2012). Variations such as secured draperies, where a pattern of ground anchors is incorporated within the field of the mesh, and hybrid systems, where the upper part of an unsecured drapery is elevated to intercept rockfalls originating upslope of the installation, are becoming more and more popular. This work presents a discrete element framework for simulation of unsecured drapery systems and its variations. The numerical model is based on the classical discrete element method (DEM) and implemented into the open-source framework YADE (Šmilauer et al., 2010). The model takes all relevant interactions between block, drapery and slope into account (Thoeni et al., 2014) and was calibrated and validated based on full-scale experiments (Giacomini et al., 2012).The block is modelled as a rigid clump made of spherical particles which allows any shape to be approximated. The drapery is represented by a set of spherical particle with remote interactions. The behaviour of the remote interactions is governed by the constitutive behaviour of the wire and generally corresponds to a piecewise linear stress-strain relation (Thoeni et al., 2013). The same concept is used to model wire ropes. The rock slope is represented by rigid triangular elements where material properties (e.g., normal coefficient of restitution, friction angle) are assigned to each triangle. The capabilities of the developed model to simulate drapery systems and estimate the residual hazard involved with such systems is shown. References Badger, T.C., Duffy, J.D. (2012) Drapery systems. In: Turner, A.K., Schuster R
Multigrid methods for isogeometric discretization
Gahalaut, K.P.S.; Kraus, J.K.; Tomar, S.K.
We present (geometric) multigrid methods for isogeometric discretization of scalar second order elliptic problems. The smoothing property of the relaxation method, and the approximation property of the intergrid transfer operators are analyzed. These properties, when used in the framework of classical multigrid theory, imply uniform convergence of two-grid and multigrid methods. Supporting numerical results are provided for the smoothing property, the approximation property, convergence factor and iterations count for V-, W- and F-cycles, and the linear dependence of V-cycle convergence on the smoothing steps. For two dimensions, numerical results include the problems with variable coefficients, simple multi-patch geometry, a quarter annulus, and the dependence of convergence behavior on refinement levels ℓ, whereas for three dimensions, only the constant coefficient problem in a unit cube is considered. The numerical results are complete up to polynomial order p=4, and for C0 and Cp-1 smoothness. PMID:24511168
Classicality in discrete Wigner functions
Cormick, Cecilia; Galvao, Ernesto F.; Gottesman, Daniel; Paz, Juan Pablo; Pittenger, Arthur O.
Gibbons et al., [Phys. Rev. A 70, 062101 (2004)] have recently defined discrete Wigner functions W to represent quantum states in a Hilbert space with finite dimension. We show that such a class of Wigner functions W can be defined so that the only pure states having non-negative W for all such functions are stabilizer states, as conjectured by Galvao, [Phys. Rev. A 71, 042302 (2005)]. We also show that the unitaries preserving non-negativity of W for all definitions of W in the class form a subgroup of the Clifford group. This means pure states with non-negative W and their associated unitary dynamics are classical in the sense of admitting an efficient classical simulation scheme using the stabilizer formalism.
Determinant Expressions for Discrete Integrable Maps
NASA Astrophysics Data System (ADS)
Sogo, Kiyoshi
Explicit formulas for several discrete integrable maps with periodic boundary condition are obtained, which give the sequential time developments in a form of the quotient of successive determinants of tri-diagonal matrices. We can expect that such formulas make the corresponding numerical simulations simple and stable. The cases of discrete Lotka-Volterra and discrete KdV equations are demonstrated by using the common algorithm computing determinants of tri-diagonal matrices.
Multilevel optimisation of aerospace and lightweight structures incorporating postbuckling effects
NASA Astrophysics Data System (ADS)
Qu, Shuang
The optimisation of aerospace structures is a very complex problem, due to the hundreds of design variables a multidisciplinary optimisation may contain, so that multilevel optimisation is required. This thesis presents the recent developments to the multilevel optimisation software VICONOPT MLO, which is a multilevel optimisation interface between the well established analysis and design software packages VICONOPT and MSC/NASTRAN. The software developed is called VICONOPT MLOP (Multilevel Optimisation with Postbuckling), and allows for postbuckling behaviour, using analysis based on the Wittrick-Williams algorithm. The objective of this research is to enable a more detailed insight into the multilevel optimisation and postbuckling behaviour of a complex structure. In VICONOPT MLOP optimisation problems, individual panels of the structural model are allowed to buckle before the design load is reached. These panels continue to carry load with differing levels of reduced stiffness. VICONOPT MLOP creates new MSC/NASTRAN data files based on this reduced stiffness data and iterates through analysis cycles to converge on an appropriate load re-distribution. Once load convergence has been obtained with an appropriate criterion, the converged load distribution is used as a starting point in the optimisation of the constituent panels, i.e. a new design cycle is started, in which the updated ply thicknesses for each panel are calculated by VICONOPT and returned to MSC/NASTRAN through VICONOPT MLOP. Further finite element analysis of the whole structure is then carried out to determine the new stress distributions in each panel. The whole process is repeated until a mass convergence criterion is met. A detailed overview of the functionality of VICONOPT MLOP is presented in the thesis. A case study is conducted into the multilevel optimisation of a composite aircraft wing, to demonstrate the capabilities of VICONOPT MLOP and identify areas for future studies. The results of
A discrete event method for wave simulation
Nutaro, James J
This article describes a discrete event interpretation of the finite difference time domain (FDTD) and digital wave guide network (DWN) wave simulation schemes. The discrete event method is formalized using the discrete event system specification (DEVS). The scheme is shown to have errors that are proportional to the resolution of the spatial grid. A numerical example demonstrates the relative efficiency of the scheme with respect to FDTD and DWN schemes. The potential for the discrete event scheme to reduce numerical dispersion and attenuation errors is discussed.
Scalar discrete nonlinear multipoint boundary value problems
NASA Astrophysics Data System (ADS)
Rodriguez, Jesus; Taylor, Padraic
In this paper we provide sufficient conditions for the existence of solutions to scalar discrete nonlinear multipoint boundary value problems. By allowing more general boundary conditions and by imposing less restrictions on the nonlinearities, we obtain results that extend previous work in the area of discrete boundary value problems [Debra L. Etheridge, Jesus Rodriguez, Periodic solutions of nonlinear discrete-time systems, Appl. Anal. 62 (1996) 119-137; Debra L. Etheridge, Jesus Rodriguez, Scalar discrete nonlinear two-point boundary value problems, J. Difference Equ. Appl. 4 (1998) 127-144].
Mixed-Effects Logistic Regression Models for Indirectly Observed Discrete Outcome Variables
ERIC Educational Resources Information Center
Vermunt, Jeroen K.
A well-established approach to modeling clustered data introduces random effects in the model of interest. Mixed-effects logistic regression models can be used to predict discrete outcome variables when observations are correlated. An extension of the mixed-effects logistic regression model is presented in which the dependent variable is a latent…
Large discrete resistance jump at grain boundary in copper nanowire
Li, An-Ping; Kim, Tae Hwan; Zhang, Xiaoguang; Nicholson, Don M; Evans III, Boyd Mccutchen; Kulkarni, Nagraj S; Kenik, Edward A; Radhakrishnan, Balasubramaniam
Copper is the current interconnect metal of choice in integrated circuits. As interconnect dimensions decrease, the resistivity of copper increases dramatically because of electron scattering from surfaces, impurities, and grain boundaries (GBs), and threatens to stymie continued device scaling. Lacking direct measurements of individual scattering sources, understanding of the relative importance of these scattering mechanisms has largely been relied on semi-empirical modeling. Here we present the first attempt to measure and calculate individual GB resistances in copper nanowires with a one-to-one correspondence to the GB structure. Four-probe scanning tunneling microscope measurements show discrete resistance jumps across high-angle random GBs and negligibly small resistances across coincidence boundaries. The latter is substantiated by first-principles calculations, while the former is consistent with the prediction of an intrinsic high resistance for random boundaries from a free-electron boundary scattering model. Such a big difference between these GBs provides vital information for nanoscale interconnect technology.
Wang, Sijian; Nan, Bin; Rosset, Saharon; Zhu, Ji
We propose a computationally intensive method, the random lasso method, for variable selection in linear models. The method consists of two major steps. In step 1, the lasso method is applied to many bootstrap samples, each using a set of randomly selected covariates. A measure of importance is yielded from this step for each covariate. In step 2, a similar procedure to the first step is implemented with the exception that for each bootstrap sample, a subset of covariates is randomly selected with unequal selection probabilities determined by the covariates' importance. Adaptive lasso may be used in the second step with weights determined by the importance measures. The final set of covariates and their coefficients are determined by averaging bootstrap results obtained from step 2. The proposed method alleviates some of the limitations of lasso, elastic-net and related methods noted especially in the context of microarray data analysis: it tends to remove highly correlated variables altogether or select them all, and maintains maximal flexibility in estimating their coefficients, particularly with different signs; the number of selected variables is no longer limited by the sample size; and the resulting prediction accuracy is competitive or superior compared to the alternatives. We illustrate the proposed method by extensive simulation studies. The proposed method is also applied to a Glioblastoma microarray data analysis. PMID:22997542
Nonlinear resonant phenomena in multilevel quantum systems
NASA Astrophysics Data System (ADS)
Hicke, Christian
We study nonlinear resonant phenomena in two-level and multilevel quantum systems. Our results are of importance for applications in the areas of quantum control, quantum computation, and quantum measurement. We present a method to perform fault-tolerant single-qubit gate operations using Landau-Zener tunneling. In a single Landau-Zoner pulse, the qubit transition frequency is varied in time so that it passes through the frequency of a radiation field. We show that a simple three-pulse sequence allows eliminating errors in the gate up to the third order in errors in the qubit energies or the radiation frequency. We study the nonlinear transverse response of a spin S > 1/2 with easy-axis anisotropy. The coherent transverse response displays sharp dips or peaks when the modulation frequency is adiabatically swept through multiphoton resonance. The effect is a consequence of a certain conformal property of the spin dynamics in a magnetic field for the anisotropy energy ∝ S2z . The occurrence of the dips or peaks is determined by the spin state. Their shape strongly depends on the modulation amplitude. Higher-order anisotropy breaks the symmetry, leading to sharp steps in the transverse response as function of frequency. The results bear on the dynamics of molecular magnets in a static magnetic field. We show that a modulated large-spin system has special symmetry. In the presence of dissipation it leads to characteristic nonlinear effects. They include abrupt switching between transverse magnetization branches with varying modulating field without hysteresis and a specific pattern of switching in the presence of multistability and hysteresis. Along with steady forced vibrations the transverse spin components can display transient vibrations at a combination of the Larmor frequency and a slower frequency determined by the anisotropy energy. The analysis is based on a microscopic theory that takes into account relaxation mechanisms important for single
Implementing abstract multigrid or multilevel methods
NASA Technical Reports Server (NTRS)
Douglas, Craig C.
Multigrid methods can be formulated as an algorithm for an abstract problem that is independent of the partial differential equation, domain, and discretization method. In such an abstract setting, problems not arising from partial differential equations can be treated. A general theory exists for linear problems. The general theory was motivated by a series of abstract solvers (Madpack). The latest version was motivated by the theory. Madpack now allows for a wide variety of iterative and direct solvers, preconditioners, and interpolation and projection schemes, including user callback ones. It allows for sparse, dense, and stencil matrices. Mildly nonlinear problems can be handled. Also, there is a fast, multigrid Poisson solver (two and three dimensions). The type of solvers and design decisions (including language, data structures, external library support, and callbacks) are discussed. Based on the author's experiences with two versions of Madpack, a better approach is proposed. This is based on a mixed language formulation (C and FORTRAN + preprocessor). Reasons for not using FORTRAN, C, or C++ (individually) are given. Implementing the proposed strategy is not difficult.
Contemporary anthropogenic silver cycle: a multilevel analysis.
Johnson, Jeremiah; Jirikowic, Julie; Bertram, Marlen; van Beers, D; Gordon, R B; Henderson, Kathryn; Klee, R J; Lanzano, Ted; Lifset, R; Oetjen, Lucia; Graedel, T E
Anthropogenic cycling of silver in 1997 is presented using three discrete governmental units: 64 countries encompassing what we believe to be over 90% of global silver flows, 9 world regions, and the entire planet. Using material flow analysis (MFA) techniques, the country level cycles are aggregated to produce the regional cycles, which are used to form a "best estimate" global cycle. Interesting findings include the following: (1) several silver-mining countries export ore and concentrate but also import silver-containing semiproducts and products; (2) the level of development for a country, as indicated by the gross domestic product, is a fair indicator of silver use, but several significant outliers exist; (3) the countries with the greatest mine production include Mexico, the United States, Peru, and China, whereas the United States, Japan, India, Germany, and Italy lead in the fabrication and manufacture of products; (4) North America and Europe's use of silver products exceed that of other regions on a per capita basis; (5) global silver discards, including tailings and separation waste, totaled approximately 57% of the silver mined; (6) approximately 57% of the silver entering waste management globally is recycled; and (7) the amount of silver entering landfills globally is comparable to the amount found in tailings. The results of this MFA lay the basis for further analysis, which in turn can offer insight into natural resource policy, the characterization of environmental impact, and better resource management. PMID:16047806
A multilevel analysis of factors affecting pocket probing depth in patients responding differently to periodontal treatment.
Axtelius, B; Söderfeldt, B; Attström, R
3 distinct levels are involved in the periodontal inflammatory process: site, tooth, and individual. By focusing attention on the levels in the population, multilevel or hierarchical modelling (MLM) enables the researcher to understand where and how the effects at the levels involved are occurring. The aim of this paper is therefore to analyse the progression of periodontal disease using analytical models that consider the level hierarchy. 22 patients with periodontitis, in previous reports described as either non-responsive or responsive to periodontal treatment, were investigated. In the multilevel modelling method (MLM), the site pocket probing depth (PPD) is summarised in 3 parameters: the overall mean, the between-individual variance, and the within-individual, between-site variance. The model can readily be extended to include independent variables for sites, teeth and individuals. If these variables are important determinants of PPD, their inclusion in the model will lead to a reduction in residual variances between sites, teeth and individuals. The PPDs were used for construction of a PPD change variable (cPPD). This variable, together with the final registrations of PPD (fPPD) alone, were used as dependent variables in the MLM. Independent predictor variables, 12 on site-level, 3 on tooth-level, and 19 on individual-level, were constructed. The total number of sites assessed was 2236 distributed on 559 teeth in 22 subjects. Initially, a fixed, fully unconditional model (models A and E) was assessed, where no predictor variables were specified at any level. Different random-intercept models (B-D, F-H) were then calculated where the independent variables were inserted in blocks relating to each level. The variance components at all 3 levels were significantly larger than zero. This indicates that MLM is recommended for analysing the present data. The inserted predictors showed 100% sensitivity relating to the subject-level variance. Subsequent testing of the
Bounds for the price of discrete arithmetic Asian options
NASA Astrophysics Data System (ADS)
Vanmaele, M.; Deelstra, G.; Liinev, J.; Dhaene, J.; Goovaerts, M. J.
In this paper the pricing of European-style discrete arithmetic Asian options with fixed and floating strike is studied by deriving analytical lower and upper bounds. In our approach we use a general technique for deriving upper (and lower) bounds for stop-loss premiums of sums of dependent random variables, as explained in Kaas et al. (Ins. Math. Econom. 27 (2000) 151-168), and additionally, the ideas of Rogers and Shi (J. Appl. Probab. 32 (1995) 1077-1088) and of Nielsen and Sandmann (J. Financial Quant. Anal. 38(2) (2003) 449-473). We are able to create a unifying framework for European-style discrete arithmetic Asian options through these bounds, that generalizes several approaches in the literature as well as improves the existing results. We obtain analytical and easily computable bounds. The aim of the paper is to formulate an advice of the appropriate choice of the bounds given the parameters, investigate the effect of different conditioning variables and compare their efficiency numerically. Several sets of numerical results are included. We also discuss hedging using these bounds. Moreover, our methods are applicable to a wide range of (pricing) problems involving a sum of dependent random variables.
Discretization vs. Rounding Error in Euler's Method
ERIC Educational Resources Information Center
Borges, Carlos F.
Euler's method for solving initial value problems is an excellent vehicle for observing the relationship between discretization error and rounding error in numerical computation. Reductions in stepsize, in order to decrease discretization error, necessarily increase the number of steps and so introduce additional rounding error. The problem is…
Discrete/PWM Ballast-Resistor Controller
NASA Technical Reports Server (NTRS)
King, Roger J.
Circuit offers low switching loss and automatic compensation for failure of ballast resistor. Discrete/PWM ballast-resistor controller improved shunt voltage-regulator circuit designed to supply power from high-resistance source to low-impedance bus. Provides both coarse discrete voltage levels (by switching of ballast resistors) and continuous fine control of voltage via pulse-width modulation.
Discreteness and Gradience in Intonational Contrasts.
ERIC Educational Resources Information Center
Gussenhoven, Carlos
Three experimental techniques that can be used to investigate the gradient of discrete nature of intonational differences, the semantic task, the imitation task, and the pitch range task are discussed and evaluated. It is pointed out that categorical perception is a sufficient but not a necessary, property of phonological discreteness. (Author/VWL)
Current Density and Continuity in Discretized Models
ERIC Educational Resources Information Center
Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard
Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…
Strategies for handling spatial uncertainty due to discretization
NASA Astrophysics Data System (ADS)
Windholz, Thomas Karl
Geographic information systems (GISs) allow users to analyze geographic phenomena within areas of interest that lead to an understanding of their relationships and thus provide a helpful tool in decision-making. Neglecting the inherent uncertainties in spatial representations may result in undesired misinterpretations. There are several sources of uncertainty contributing to the quality of spatial data within a GIS: imperfections (e.g., inaccuracy and imprecision) and effects of discretization. An example for discretization in the thematic domain is the chosen number of classes to represent a spatial phenomenon (e.g., air temperature). In order to improve the utility of a GIS an inclusion of a formal data quality model is essential. A data quality model stores, specifies, and handles the necessary data required to provide uncertainty information for GIS applications. This dissertation develops a data quality model that associates sources of uncertainty with units of information (e.g., measurement and coverage) in a GIS. The data quality model provides a basis to construct metrics dealing with different sources of uncertainty and to support tools for propagation and cross-propagation. Two specific metrics are developed that focus on two sources of uncertainty: inaccuracy and discretization. The first metric identifies a minimal resolvable object size within a sampled field of a continuous variable. This metric, called detectability, is calculated as a spatially varying variable. The second metric, called reliability, investigates the effects of discretization on reliability. This metric estimates the variation of an underlying random variable and determines the reliability of a representation. It is also calculated as a spatially varying variable. Subsequently, this metric is used to assess the relationship between the influence of the number of sample points versus the influence of the degree of variation on the reliability of a representation. The results of this
Multilevel Spatial Structure Impacts on the Pollination Services of Comarum palustre (Rosaceae)
Somme, Laurent; Mayer, Carolin; Jacquemart, Anne-Laure
Habitat destruction and fragmentation accelerate pollinator decline, consequently disrupting ecosystem processes such as pollination. To date, the impacts of multilevel spatial structure on pollination services have rarely been addressed. We focused on the effects of population spatial structure on the pollination services of Comarum palustre at three levels (i.e. within-population, between-populations and landscape). For three years, we investigated 14 Belgian populations, which differed in their within-population flower density, population surface, closure (i.e. proportion of the population edge that consisted of woody elements) and isolation (i.e. percentage of woody area cover within a 500 m radius from the population centre). We tested whether these spatial characteristics impact on pollinator abundance and visitation rate and thus, reproductive success of C. palustre. Insects were observed in 15 randomly-chosen plots in each population. We tested for pollen limitation with supplemental hand-cross pollination. Bumble bees and solitary bees were the major pollinators through all populations. Within populations, plots with high flower densities attracted high numbers of bumble bees and other insects. High bumble bee and solitary bee abundance was observed in populations presenting high proportions of woody edges and in populations within landscapes presenting high proportions of woody areas. Seed set resulting from open pollination varied with bumble bee and solitary bee visitation rate, leading to increased pollen limitation when pollinators were scarce. Since the reproductive success depended on the visitation rate of the main pollinators, which depended on multilevel spatial structure, wetland management plans should pay special attention to favour a mosaic of biotopes, including nesting sites and food resources for insects. This study particularly supports the relevance of a mix wetlands and woody habitats to bees. PMID:24915450
Social capital and dental pain in Brazilian northeast: a multilevel cross-sectional study
Background There is limited evidence on possible associations between social determinants and dental pain. This study investigated the relationship of neighborhood and individual social capital with dental pain in adolescents, adults and the elderly. Methods A population-based multilevel study was conducted involving 624 subjects from 3 age groups: 15–19, 35–44 and 65–74 years. They were randomly selected from 30 census tracts in three cities in the State of Paraíba, Brazil. A two-stage cluster sampling was used considering census tracts and households as sampling units. The outcome of study was the presence of dental pain in the last 6 months. Information on dental pain, demographic, socio-economic, health-related behaviors, use of dental services, self-perceived oral health and social capital measures was collected through interviews. Participants underwent a clinical examination for assessment of dental caries. Neighborhood social capital was evaluated using aggregated measures of social trust, social control, empowerment, political efficacy and neighborhood safety. Individual social capital assessment included bonding and bridging social capital. Multilevel logistic regression was used to test the relationship of neighborhood and individual social capital with dental pain after sequential adjustment for covariates. Results Individuals living in neighborhoods with high social capital were 52% less likely to report dental pain than those living in neighborhoods with low social capital (OR = 0.48, 95% CI = 0.27-0.85). Bonding social capital (positive interaction) was independently associated with dental pain (OR = 0.88, 95% CI = 0.80-0.91). Last dental visit, self-perceived oral health and number of decayed teeth were also significantly associated with dental pain. Conclusions Our findings suggest that contextual and individual social capital are independently associated with dental pain. PMID:23289932
Multilevel spatial structure impacts on the pollination services of Comarum palustre (Rosaceae).
Somme, Laurent; Mayer, Carolin; Jacquemart, Anne-Laure
Habitat destruction and fragmentation accelerate pollinator decline, consequently disrupting ecosystem processes such as pollination. To date, the impacts of multilevel spatial structure on pollination services have rarely been addressed. We focused on the effects of population spatial structure on the pollination services of Comarum palustre at three levels (i.e. within-population, between-populations and landscape). For three years, we investigated 14 Belgian populations, which differed in their within-population flower density, population surface, closure (i.e. proportion of the population edge that consisted of woody elements) and isolation (i.e. percentage of woody area cover within a 500 m radius from the population centre). We tested whether these spatial characteristics impact on pollinator abundance and visitation rate and thus, reproductive success of C. palustre. Insects were observed in 15 randomly-chosen plots in each population. We tested for pollen limitation with supplemental hand-cross pollination. Bumble bees and solitary bees were the major pollinators through all populations. Within populations, plots with high flower densities attracted high numbers of bumble bees and other insects. High bumble bee and solitary bee abundance was observed in populations presenting high proportions of woody edges and in populations within landscapes presenting high proportions of woody areas. Seed set resulting from open pollination varied with bumble bee and solitary bee visitation rate, leading to increased pollen limitation when pollinators were scarce. Since the reproductive success depended on the visitation rate of the main pollinators, which depended on multilevel spatial structure, wetland management plans should pay special attention to favour a mosaic of biotopes, including nesting sites and food resources for insects. This study particularly supports the relevance of a mix wetlands and woody habitats to bees. PMID:24915450
Discrete elements method of neutral particle transport
Mathews, K.A.
A new discrete elements (L/sub N/) transport method is derived and compared to the discrete ordinates S/sub N/ method, theoretically and by numerical experimentation. The discrete elements method is more accurate than discrete ordinates and strongly ameliorates ray effects for the practical problems studied. The discrete elements method is shown to be more cost effective, in terms of execution time with comparable storage to attain the same accuracy, for a one-dimensional test case using linear characteristic spatial quadrature. In a two-dimensional test case, a vacuum duct in a shield, L/sub N/ is more consistently convergent toward a Monte Carlo benchmark solution than S/sub N/, using step characteristic spatial quadrature. An analysis of the interaction of angular and spatial quadrature in xy-geometry indicates the desirability of using linear characteristic spatial quadrature with the L/sub N/ method.
Active control of turbomachine discrete tones
NASA Astrophysics Data System (ADS)
Fleeter, Sanford
This paper was directed at active control of discrete frequency noise generated by subsonic blade rows through cancellation of the blade row interaction generated propagating acoustic waves. First discrete frequency noise generated by a rotor and stator in a duct was analyzed to determine the propagating acoustic pressure waves. Then a mathematical model was developed to analyze and predict the active control of discrete frequency noise generated by subsonic blade rows through cancellation of the propagating acoustic waves, accomplished by utilizing oscillating airfoil surfaces to generate additional control propagating pressure waves. These control waves interact with the propagating acoustic waves, thereby, in principle, canceling the acoustic waves and thus, the far field discrete frequency tones. This model was then applied to a fan exit guide vane to investigate active airfoil surface techniques for control of the propagating acoustic waves, and thus the far field discrete frequency tones, generated by blade row interactions.
Discrete breathers in graphane: Effect of temperature
NASA Astrophysics Data System (ADS)
Baimova, J. A.; Murzaev, R. T.; Lobzenko, I. P.; Dmitriev, S. V.; Zhou, Kun
The discrete breathers in graphane in thermodynamic equilibrium in the temperature range 50-600 K are studied by molecular dynamics simulation. A discrete breather is a hydrogen atom vibrating along the normal to a sheet of graphane at a high amplitude. As was found earlier, the lifetime of a discrete breather at zero temperature corresponds to several tens of thousands of vibrations. The effect of temperature on the decay time of discrete breathers and the probability of their detachment from a sheet of graphane are studied in this work. It is shown that closely spaced breathers can exchange energy with each other at zero temperature. The data obtained suggest that thermally activated discrete breathers can be involved in the dehydrogenation of graphane, which is important for hydrogen energetics.
Prasad, L.; Rao, R.
We present an efficient multi-scale scheme to adaptively approximate the continuous (or densely sampled) contour of a planar shape at varying resolutions. The notion of shape is intimately related to the notion of contour, and the efficient representation of the contour of a shape is vital to a computational understanding of the shape. Any polygonal approximation of a planar smooth curve is equivalent to a piecewise constant approximation of the parameterized X and Y coordinate functions of a discrete point set obtained by densely sampling the curve. Using the Haar wavelet transform for the piecewise approximation yields a hierarchical scheme in which the size of the approximating point set is traded off against the morphological accuracy of the approximation. Our algorithm compresses the representation of the initial shape contour to a sparse sequence of points in the plane defining the vertices of the shape's polygonal approximation. Furthermore, it is possible to control the overall resolution of the approximation by a single, scale-independent parameter.
Seipin Is a Discrete Homooligomer†
Binns, Derk; Lee, SungKyung; Hilton, Christopher L.; Jiang, Qiu-Xing; Goodman, Joel M.
Seipin is a transmembrane protein that resides in the endoplasmic reticulum and concentrates at junctions between the ER and cytosolic lipid droplets. Mutations in the human seipin gene, including the missense mutation A212P, lead to congenital generalized lipodystrophy (CGL), characterized by the lack of normal adipose tissue and accumulation of fat in liver and muscles. In both yeast and CGL patient fibroblasts, seipin is required for normal lipid droplet morphology; in its absence droplets appear to bud abnormally from the ER. Here we report the first purification and physical characterization of seipin. Yeast seipin is in a large discrete protein complex. Affinity purification demonstrated that seipin is the main if not exclusive protein in the complex. Detergent sucrose gradients in H2O, and D2O and gel filtration were used to determine the size of the seipin complex and account for detergent binding. Both seipin-myc13 (seipin fused to 13 tandem copies of the myc epitope) expressed from the endogenous promoter and overexpressed seipin-mCherry form ~500 kDa proteins consisting of about 9 copies of seipin. The yeast orthologue of the human A212P allele forms only smaller complexes and is unstable; we hypothesize that this accounts for its null phenotype in humans. Seipin appears as a toroid by negative staining electron microscopy. We speculate that seipin plays at least a structural role in organizing droplets or in communication between droplets and ER. PMID:21062080
Do high-commitment work systems affect creativity? A multilevel combinational approach to employee creativity.
Chang, Song; Jia, Liangding; Takeuchi, Riki; Cai, Yahua
In this article, some information about the data used in the article and a citation were not included. The details of the corrections are provided.] This study uses 3-level, 2-wave time-lagged data from a random sample of 55 high-technology firms, 238 teams, and 1,059 individuals in China to investigate a multilevel combinational model of employee creativity. First, we hypothesize that firm (macrolevel) high-commitment work systems are conducive to individual (microlevel) creativity. Furthermore, we hypothesize that this positive crosslevel main impact may be combined with middle-level (mesolevel) factors, including team cohesion and team task complexity, such that the positive impact of firm high-commitment work systems on individual creativity is stronger when team cohesion is high and the team task more complex. The findings from random coefficient modeling analyses provide support for our hypotheses. These sets of results offer novel insight into how firms can use macrolevel and mesolevel contextual variables in a systematic manner to promote employee creativity in the workplace, despite its complex nature. PMID:24490963
Fast and accurate analysis of large-scale composite structures with the parallel multilevel fast multipole algorithm.
Ergül, Özgür; Gürel, Levent
Accurate electromagnetic modeling of complicated optical structures poses several challenges. Optical metamaterial and plasmonic structures are composed of multiple coexisting dielectric and/or conducting parts. Such composite structures may possess diverse values of conductivities and dielectric constants, including negative permittivity and permeability. Further challenges are the large sizes of the structures with respect to wavelength and the complexities of the geometries. In order to overcome these challenges and to achieve rigorous and efficient electromagnetic modeling of three-dimensional optical composite structures, we have developed a parallel implementation of the multilevel fast multipole algorithm (MLFMA). Precise formulation of composite structures is achieved with the so-called "electric and magnetic current combined-field integral equation." Surface integral equations are carefully discretized with piecewise linear basis functions, and the ensuing dense matrix equations are solved iteratively with parallel MLFMA. The hierarchical strategy is used for the efficient parallelization of MLFMA on distributed-memory architectures. In this paper, fast and accurate solutions of large-scale canonical and complicated real-life problems, such as optical metamaterials, discretized with tens of millions of unknowns are presented in order to demonstrate the capabilities of the proposed electromagnetic solver. PMID:23456127
Compatible Spatial Discretizations for Partial Differential Equations
Arnold, Douglas, N, ed.
From May 11--15, 2004, the Institute for Mathematics and its Applications held a hot topics workshop on Compatible Spatial Discretizations for Partial Differential Equations. The numerical solution of partial differential equations (PDE) is a fundamental task in science and engineering. The goal of the workshop was to bring together a spectrum of scientists at the forefront of the research in the numerical solution of PDEs to discuss compatible spatial discretizations. We define compatible spatial discretizations as those that inherit or mimic fundamental properties of the PDE such as topology, conservation, symmetries, and positivity structures and maximum principles. A wide variety of discretization methods applied across a wide range of scientific and engineering applications have been designed to or found to inherit or mimic intrinsic spatial structure and reproduce fundamental properties of the solution of the continuous PDE model at the finite dimensional level. A profusion of such methods and concepts relevant to understanding them have been developed and explored: mixed finite element methods, mimetic finite differences, support operator methods, control volume methods, discrete differential forms, Whitney forms, conservative differencing, discrete Hodge operators, discrete Helmholtz decomposition, finite integration techniques, staggered grid and dual grid methods, etc. This workshop seeks to foster communication among the diverse groups of researchers designing, applying, and studying such methods as well as researchers involved in practical solution of large scale problems that may benefit from advancements in such discretizations; to help elucidate the relations between the different methods and concepts; and to generally advance our understanding in the area of compatible spatial discretization methods for PDE. Particular points of emphasis included: + Identification of intrinsic properties of PDE models that are critical for the fidelity of numerical
Is random access memory random?
NASA Technical Reports Server (NTRS)
Denning, P. J.
Most software is contructed on the assumption that the programs and data are stored in random access memory (RAM). Physical limitations on the relative speeds of processor and memory elements lead to a variety of memory organizations that match processor addressing rate with memory service rate. These include interleaved and cached memory. A very high fraction of a processor's address requests can be satified from the cache without reference to the main memory. The cache requests information from main memory in blocks that can be transferred at the full memory speed. Programmers who organize algorithms for locality can realize the highest performance from these computers.
Nonresonant interaction of ultrashort electromagnetic pulses with multilevel quantum systems
NASA Technical Reports Server (NTRS)
Belenov, E.; Isakov, V.; Nazarkin, A.
Some features of the excitation of multilevel quantum systems under the action of electromagnetic pulses which are shorter than the inverse frequency of interlevel transitions are considered. It is shown that the interaction is characterized by a specific type of selectivity which is not connected with the resonant absorption of radiation. The simplest three-level model displays the inverse population of upper levels. The effect of an ultrashort laser pulse on a multilevel molecule was regarded as an instant reception of the oscillation velocity by the oscillator and this approach showed an effective excitation and dissociation of the molecule. The estimations testify to the fact that these effects can be observed using modern femtosecond lasers.
Improved Bat Algorithm Applied to Multilevel Image Thresholding
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
On the Multilevel Solution Algorithm for Markov Chains
NASA Technical Reports Server (NTRS)
Horton, Graham
We discuss the recently introduced multilevel algorithm for the steady-state solution of Markov chains. The method is based on an aggregation principle which is well established in the literature and features a multiplicative coarse-level correction. Recursive application of the aggregation principle, which uses an operator-dependent coarsening, yields a multi-level method which has been shown experimentally to give results significantly faster than the typical methods currently in use. When cast as a multigrid-like method, the algorithm is seen to be a Galerkin-Full Approximation Scheme with a solution-dependent prolongation operator. Special properties of this prolongation lead to the cancellation of the computationally intensive terms of the coarse-level equations.
Learning in multilevel games with incomplete information. II.
Zhou, J; Billard, E; Lakshmivarahan, S
Multilevel games are abstractions of situations where decision makers are distributed in a network environment. In Part I of this paper, the authors present several of the challenging problems that arise in the analysis of multilevel games. In this paper a specific set up is considered where the two games being played are zero-sum games and where the decision makers use the linear reward-inaction algorithm of stochastic learning automata. It is shown that the effective game matrix is decided by the willingness and the ability to cooperate and is a convex combination of two zero-sum game matrices. Analysis of the properties of this effective game matrix and the convergence of the decision process shows that players tend toward noncooperation in these specific environments. Simulation results illustrate this noncooperative behavior. PMID:18252309
Multi-level Hybrid Cache: Impact and Feasibility
Zhang, Zhe; Kim, Youngjae; Ma, Xiaosong; Shipman, Galen M; Zhou, Yuanyuan
Storage class memories, including flash, has been attracting much attention as promising candidates fitting into in today's enterprise storage systems. In particular, since the cost and performance characteristics of flash are in-between those of DRAM and hard disks, it has been considered by many studies as an secondary caching layer underneath main memory cache. However, there has been a lack of studies of correlation and interdependency between DRAM and flash caching. This paper views this problem as a special form of multi-level caching, and tries to understand the benefits of this multi-level hybrid cache hierarchy. We reveal that significant costs could be saved by using Flash to reduce the size of DRAM cache, while maintaing the same performance. We also discuss design challenges of using flash in the caching hierarchy and present potential solutions.
Multilevel Research and the Challenges of Implementing Genomic Medicine
Coates, Ralph J.; Fennell, Mary L.; Glasgow, Russell E.; Scheuner, Maren T.; Schully, Sheri D.; Williams, Marc S.; Clauser, Steven B.
Advances in genomics and related fields promise a new era of personalized medicine in the cancer care continuum. Nevertheless, there are fundamental challenges in integrating genomic medicine into cancer practice. We explore how multilevel research can contribute to implementation of genomic medicine. We first review the rapidly developing scientific discoveries in this field and the paucity of current applications that are ready for implementation in clinical and public health programs. We then define a multidisciplinary translational research agenda for successful integration of genomic medicine into policy and practice and consider challenges for successful implementation. We illustrate the agenda using the example of Lynch syndrome testing in newly diagnosed cases of colorectal cancer and cascade testing in relatives. We synthesize existing information in a framework for future multilevel research for integrating genomic medicine into the cancer care continuum. PMID:22623603
Multilevel factors affecting quality: examples from the cancer care continuum.
Zapka, Jane; Taplin, Stephen H; Ganz, Patricia; Grunfeld, Eva; Sterba, Katherine
The complex environmental context must be considered as we move forward to improve cancer care and, ultimately, patient and population outcomes. The cancer care continuum represents several care types, each of which includes multiple technical and communication steps and interfaces among patients, providers, and organizations. We use two case scenarios to 1) illustrate the variability, diversity, and interaction of factors from multiple levels that affect care quality and 2) discuss research implications and provide hypothetical examples of multilevel interventions. Each scenario includes a targeted literature review to illustrate contextual influences upon care and sets the stage for theory-informed interventions. The screening case highlights access issues in older women, and the survivorship case illustrates the multiple transition challenges faced by patients, families, and organizations. Example interventions show the potential gains of implementing intervention strategies that work synergistically at multiple levels. While research examining multilevel intervention is a priority, it presents numerous study design, measurement, and analytic challenges. PMID:22623591
Improved bat algorithm applied to multilevel image thresholding.
Alihodzic, Adis; Tuba, Milan
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
On the multi-level solution algorithm for Markov chains
Horton, G.
We discuss the recently introduced multi-level algorithm for the steady-state solution of Markov chains. The method is based on the aggregation principle, which is well established in the literature. Recursive application of the aggregation yields a multi-level method which has been shown experimentally to give results significantly faster than the methods currently in use. The algorithm can be reformulated as an algebraic multigrid scheme of Galerkin-full approximation type. The uniqueness of the scheme stems from its solution-dependent prolongation operator which permits significant computational savings in the evaluation of certain terms. This paper describes the modeling of computer systems to derive information on performance, measured typically as job throughput or component utilization, and availability, defined as the proportion of time a system is able to perform a certain function in the presence of component failures and possibly also repairs.
Intraclass Correlations and Covariate Outcome Correlations for Planning Two-and Three-Level Cluster-Randomized Experiments in Education
ERIC Educational Resources Information Center
Hedges, Larry V.; Hedberg, E. C.
Background: Cluster-randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…
Intraclass Correlations and Covariate Outcome Correlations for Planning 2 and 3 Level Cluster Randomized Experiments in Education
ERIC Educational Resources Information Center
Hedges, Larry V.; Hedberg, Eric C.
Background: Cluster randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…
Human Papillomavirus Vaccine Coverage Among Females Aged 11 to 17 in Texas Counties: An Application of Multilevel, Small Area Estimation
Eberth, Jan M.; Hossain, Md Monir; Tiro, Jasmin A.; Zhang, Xingyou; Holt, James B.; Vernon, Sally W.
Background Local data are often used to plan and evaluate public health interventions and policy. With increasingly fewer public resources to collect sufficient data to support direct estimation of local outcomes, methods for deriving small area estimates are vital. The purpose of this study is to describe the county-level geographic distribution of human papillomavirus (HPV) vaccine coverage among adolescent females in Texas using multilevel small area estimation. Methods Multilevel (individual, county, public health region) random-intercept logit models were fit to HPV vaccination data (≥1 dose Gardasil) from the 2008 Behavioral Risk Factor Surveillance System. Using the parameter estimates from the final model, we simulated 10,000 data sets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county. Results County-level coverage estimates ranged from 7% to 29%, compared with the state average of 18% (95% confidence interval [CI], 13.59–21.88). Many Southwestern border and metropolitan counties exhibited high coverage estimates. Low coverage estimates were noted in the Panhandle, Southeastern border region, and Northeast. Significant correlations were observed between HPV vaccination and Hispanic ethnicity, county poverty, and public health region poverty. Conclusion Harnessing the flexibility of multilevel small area models to estimate HPV vaccine coverage at the county level, we have provided data that may inform the development of health education programs/policies, the provision of health services, and the planning of new research studies. Additionally, we have provided a framework for modeling other health outcomes at the county level using national survey data. PMID:23481692
Laminoplasty versus laminectomy and fusion for multilevel cervical myelopathy: a meta-analysis of clinical and radiological outcomes.
Lee, Chang-Hyun; Lee, Jaebong; Kang, James D; Hyun, Seung-Jae; Kim, Ki-Jeong; Jahng, Tae-Ahn; Kim, Hyun-Jib
OBJECT Posterior cervical surgery, expansive laminoplasty (EL) or laminectomy followed by fusion (LF), is usually performed in patients with multilevel (≥ 3) cervical spondylotic myelopathy (CSM). However, the superiority of either of these techniques is still open to debate. The aim of this study was to compare clinical outcomes and postoperative kyphosis in patients undergoing EL versus LF by performing a meta-analysis. METHODS Included in the meta-analysis were all studies of EL versus LF in adults with multilevel CSM in MEDLINE (PubMed), EMBASE, and the Cochrane library. A random-effects model was applied to pool data using the mean difference (MD) for continuous outcomes, such as the Japanese Orthopaedic Association (JOA) grade, the cervical curvature index (CCI), and the visual analog scale (VAS) score for neck pain. RESULTS Seven studies comprising 302 and 290 patients treated with EL and LF, respectively, were included in the final analyses. Both treatment groups showed slight cervical lordosis and moderate neck pain in the baseline state. Both groups were similarly improved in JOA grade (MD 0.09, 95% CI -0.37 to 0.54, p = 0.07) and neck pain VAS score (MD -0.33, 95% CI -1.50 to 0.84, p = 0.58). Both groups evenly lost cervical lordosis. In the LF group lordosis seemed to be preserved in long-term follow-up studies, although the difference between the 2 treatment groups was not statistically significant. CONCLUSIONS Both EL and LF lead to clinical improvement and loss of lordosis evenly. There is no evidence to support EL over LF in the treatment of multilevel CSM. Any superiority between EL and LF remains in question, although the LF group shows favorable long-term results. PMID:25815808
A highly efficient SDRAM controller supporting variable-length burst access and batch process for discrete reads
NASA Astrophysics Data System (ADS)
Li, Nan; Wang, Junzheng
A highly efficient Synchronous Dynamic Random Access Memory (SDRAM) controller supporting variable-length burst access and batch process for discrete reads is proposed in this paper. Based on the Principle of Locality, command First In First Out (FIFO) and address range detector are designed within this controller to accelerate its responses to discrete read requests, which dramatically improves the average Effective Bus Utilization Ratio (EBUR) of SDRAM. Our controller is finally verified by driving the Micron 256-Mb SDRAM MT48LC16M16A2. Successful simulation and verification results show that our controller exhibits much higher EBUR than do most existing designs in case of discrete reads.
Boundaries, kinetic properties, and final domain structure of plane discrete uniform Poisson-Voronoi tessellations with von Neumann neighborhoods
NASA Astrophysics Data System (ADS)
Korobov, A.
Discrete random tessellations appear not infrequently in describing nucleation and growth transformations. Generally, several non-Euclidean metrics are possible in this case. Previously [A. Korobov, Phys. Rev. B 76, 085430 (2007)] continual analogs of such tessellations have been studied. Here one of the simplest discrete varieties of the Kolmogorov-Johnson-Mehl-Avrami model, namely, the model with von Neumann neighborhoods, has been examined per se, i.e., without continualization. The tessellation is uniform in the sense that domain boundaries consist of tiles. Similarities and distinctions between discrete and continual models are discussed.
Multilevel interventions and racial/ethnic health disparities.
Gorin, Sherri Sheinfeld; Badr, Hoda; Krebs, Paul; Prabhu Das, Irene
To examine the impact of multilevel interventions (with three or more levels of influence) designed to reduce health disparities, we conducted a systematic review and meta-analysis of interventions for ethnic/racial minorities (all except non-Hispanic whites) that were published between January 2000 and July 2011. The primary aims were to synthesize the findings of studies evaluating multilevel interventions (three or more levels of influence) targeted at ethnic and racial minorities to reduce disparities in their health care and obtain a quantitative estimate of the effect of multilevel interventions on health outcomes among these subgroups. The electronic database PubMed was searched using Medical Subject Heading terms and key words. After initial review of abstracts, 26 published studies were systematically reviewed by at least two independent coders. Those with sufficient data (n = 12) were assessed by meta-analysis and examined for quality using a modified nine-item Physiotherapy Evidence Database coding scheme. The findings from this descriptive review suggest that multilevel interventions have positive effects on several health behavior outcomes, including cancer prevention and screening, as well improving the quality of health-care system processes. The weighted average effect size across studies for all health behavior outcomes reported at the individual participant level (k = 17) was odds ratio (OR) = 1.27 (95% confidence interval [CI] = 1.11 to 1.44); for the outcomes reported by providers or organizations, the weighted average effect size (k = 3) was OR = 2.53 (95% CI = 0.82 to 7.81). Enhanced application of theories to multiple levels of change, novel design approaches, and use of cultural leveraging in intervention design and implementation are proposed for this nascent field. PMID:22623602
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The present paper fully decomposes the system into structural and control subsystem designs and produces an improved design. Theory, implementation, and results for the method are presented and compared with the benchmark example.
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The system is fully decomposed into structural and control subsystem designs and an improved design is produced. Theory, implementation, and results for the method are presented and compared with the benchmark example.
An efficient multilevel optimization method for engineering design
NASA Technical Reports Server (NTRS)
Vanderplaats, G. N.; Yang, Y. J.; Kim, D. S.
An efficient multilevel deisgn optimization technique is presented. The proposed method is based on the concept of providing linearized information between the system level and subsystem level optimization tasks. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to use. The disadvantage is that the coupling between subsystems is not dealt with in a precise mathematical manner.
Organolead Halide Perovskites for Low Operating Voltage Multilevel Resistive Switching.
Choi, Jaeho; Park, Sunghak; Lee, Joohee; Hong, Kootak; Kim, Do-Hong; Moon, Cheon Woo; Park, Gyeong Do; Suh, Junmin; Hwang, Jinyeon; Kim, Soo Young; Jung, Hyun Suk; Park, Nam-Gyu; Han, Seungwu; Nam, Ki Tae; Jang, Ho Won
Organolead halide perovskites are used for low-operating-voltage multilevel resistive switching. Ag/CH3 NH3 PbI3 /Pt cells exhibit electroforming-free resistive switching at an electric field of 3.25 × 10(3) V cm(-1) for four distinguishable ON-state resistance levels. The migration of iodine interstitials and vacancies with low activation energies is responsible for the low-electric-field resistive switching via filament formation and annihilation. PMID:27192161
Doubly Latent Multilevel Analyses of Classroom Climate: An Illustration
ERIC Educational Resources Information Center
Morin, Alexandre J. S.; Marsh, Herbert W.; Nagengast, Benjamin; Scalas, L. Francesca
Many classroom climate studies suffer from 2 critical problems: They (a) treat climate as a student-level (L1) variable in single-level analyses instead of a classroom-level (L2) construct in multilevel analyses; and (b) rely on manifest-variable models rather than on latent-variable models that control measurement error at L1 and L2, and sampling…
Sericin for resistance switching device with multilevel nonvolatile memory.
Wang, Hong; Meng, Fanben; Cai, Yurong; Zheng, Liyan; Li, Yuangang; Liu, Yuanjun; Jiang, Yueyue; Wang, Xiaotian; Chen, Xiaodong
Resistance switching characteristics of natural sericin protein film is demonstrated for nonvolatile memory application for the first time. Excellent memory characteristics with a resistance OFF/ON ratio larger than 10(6) have been obtained and a multilevel memory based on sericin has been achieved. The environmentally friendly high performance biomaterial based memory devices may hold a place in the future of electronic device development. PMID:23893500
A multi-level method for sparse linear systems
Shapira, Y.
A multi-level method for the solution of sparse linear systems is introduced. The definition of the method is based on data from the coefficient matrix alone. An upper bound for the condition number is available for certain symmetric positive definite (SPD) problems. Numerical experiments confirm the analysis and illustrate the efficiency of the method for diffusion problems with discontinuous coefficients with discontinuities which are not aligned with the coarse meshes.
On codes with multi-level error-correction capabilities
NASA Technical Reports Server (NTRS)
Lin, Shu
In conventional coding for error control, all the information symbols of a message are regarded equally significant, and hence codes are devised to provide equal protection for each information symbol against channel errors. However, in some occasions, some information symbols in a message are more significant than the other symbols. As a result, it is desired to devise codes with multilevel error-correcting capabilities. Another situation where codes with multi-level error-correcting capabilities are desired is in broadcast communication systems. An m-user broadcast channel has one input and m outputs. The single input and each output form a component channel. The component channels may have different noise levels, and hence the messages transmitted over the component channels require different levels of protection against errors. Block codes with multi-level error-correcting capabilities are also known as unequal error protection (UEP) codes. Structural properties of these codes are derived. Based on these structural properties, two classes of UEP codes are constructed.
Cascaded H-bridge multilevel inverter for renewable energy generation
NASA Astrophysics Data System (ADS)
Pandey, Ravikant; Nath Tripathi, Ravi; Hanamoto, Tsuyoshi
In this paper cascaded H-bridge multilevel inverter (CHBMLI) has been investigated for the application of renewable energy generation. Energy sources like solar, wind, hydro, biomass or combination of these can be manipulated to obtain alternative sources for renewable energy generation. These renewable energy sources have different electrical characteristics like DC or AC level so it is challenging to use generated power by connecting to grid or load directly. The renewable energy source require specific power electronics converter as an interface for conditioning generated power .The multilevel inverter can be utilized for renewable energy sources in two different modes, the power generation mode (stand-alone mode), and compensator mode (statcom). The performance of the multilevel inverter has been compared with two level inverter. In power generation mode CHBMLI supplies the active and reactive power required by the different loads. For operation in compensator mode the indirect current control based on synchronous reference frame theory (SRFT) ensures the grid operating in unity power factor and compensate harmonics and reactive power.
Flexible Job Shop Scheduling with Multi-level Job Structures
NASA Astrophysics Data System (ADS)
Jang, Yang-Ja; Kim, Ki-Dong; Jang, Seong-Yong; Park, Jinwoo
This paper deals with a scheduling problem in a flexible job shop with multi-level job structures where end products are assembled from sub-assemblies or manufactured components. For such shops MRP (Material Requirement Planning) logic is frequently used to synchronize and pace the production activities for the required parts. However, in MRP, the planning of operational-level activities is left to short term scheduling. So, we need a good scheduling algorithm to generate feasible schedules taking into account shop floor characteristics and multi-level job structures used in MRP. In this paper, we present a GA (Genetic Algorithm) solution for this complex scheduling problem based on a new gene to reflect the machine assignment, operation sequences and the levels of the operations relative to final assembly operation. The relative operation level is the control parameter that paces the completion timing of the components belonging to the same branch in the multi-level job hierarchy. We compare the genetic algorithm with several dispatching rules in terms of total tardiness and the genetic algorithm shows outstanding performance for about forty modified standard job-shop problem instances.
Building Xperience: a multilevel alcohol and drug prevention intervention.
Diamond, Sarah; Schensul, Jean J; Snyder, Leslie B; Bermudez, Alessandro; D'Alessandro, Nicole; Morgan, Damion Sincere
"Xperience" is an innovative alcohol and drug prevention program that has adopted a multilevel, community-based strategy to promote drug-and-alcohol free social activities, venues and norms among urban youth ages 14-20. The intervention aims to strengthen protective factors and reduce risk factors for alcohol and other substance use among high school age youth by addressing multiple factors at the individual, peer, community and city level. The purpose of this paper is to discuss the process of building the different levels of this intervention during the 3-year formative phase. We will explain: (1) Why we chose to adopt a multilevel and participatory strategy, (2) Formative research leading to the intervention model, (3) The theoretical framework underlying the methodology, (4) Pilot intervention development (Years One and Two), (5) Current program methods and outcome goals, and lastly, (6) Some of the lessons learned, goals achieved, and plans for the future. This descriptive account of building a multilevel intervention aims to serve as a useful guide for others wishing to develop similar approaches, and for theorizing about some of the common challenges involved in this process. PMID:19381797
On the equivalence of the discrete nonlinear Schrödinger equation and the discrete isotropic Heisenberg magnet
NASA Astrophysics Data System (ADS)
Hoffmann, Tim
The equivalence of the discrete isotropic Heisenberg magnet (IHM) model and the discrete nonlinear Schrödinger equation (NLSE) given by Ablowitz and Ladik is shown. This is used to derive the equivalence of their discretization with the one by Izgerin and Korepin. Moreover a doubly discrete IHM is presented that is equivalent to Ablowitz' and Ladiks doubly discrete NLSE.
Discrete symmetries and de Sitter spacetime
Cotăescu, Ion I. Pascu, Gabriel
Aspects of the ambiguity in defining quantum modes on de Sitter spacetime using a commuting system composed only of differential operators are discussed. Discrete symmetries and their actions on the wavefunction in commonly used coordinate charts are reviewed. It is argued that the system of commuting operators can be supplemented by requiring the invariance of the wavefunction to combined discrete symmetries- a criterion which selects a single state out of the α-vacuum family. Two such members of this family are singled out by particular combined discrete symmetries- states between which exists a well-known thermality relation.
Discrete flavour symmetries from the Heisenberg group
NASA Astrophysics Data System (ADS)
Floratos, E. G.; Leontaris, G. K.
Non-abelian discrete symmetries are of particular importance in model building. They are mainly invoked to explain the various fermion mass hierarchies and forbid dangerous superpotential terms. In string models they are usually associated to the geometry of the compactification manifold and more particularly to the magnetised branes in toroidal compactifications. Motivated by these facts, in this note we propose a unified framework to construct representations of finite discrete family groups based on the automorphisms of the discrete and finite Heisenberg group. We focus in particular, on the PSL2 (p) groups which contain the phenomenologically interesting cases.
High-accuracy discrete positioning device
NASA Technical Reports Server (NTRS)
Brooks, John J. (Inventor)
An article (30) is controllably and precisely positioned at one of three discrete locations defined by a linkage. The positioning apparatus includes two independently driven cranks (34, 42), with a link (50) pivotably connected between the two cranks (34, 42). Another connector (44) is pivotably connected between one of the cranks (34 or 42) and the article (30) to be positioned. The cranks (34, 42) are rotationally adjusted so that the pivot points (52, 54) of the link (50) are collinear with the axes of rotation of the cranks (40, 48), thereby defining one of the three discrete locations. Additional cranks and links can be provided to define additional discrete locations.
Variable-speed wind power system with improved energy capture via multilevel conversion
Erickson, Robert W.; Al-Naseem, Osama A.; Fingersh, Lee Jay
A system and method for efficiently capturing electrical energy from a variable-speed generator are disclosed. The system includes a matrix converter using full-bridge, multilevel switch cells, in which semiconductor devices are clamped to a known constant DC voltage of a capacitor. The multilevel matrix converter is capable of generating multilevel voltage wave waveform of arbitrary magnitude and frequencies. The matrix converter can be controlled by using space vector modulation.
Unfolding and effective bandstructure calculations as discrete real- and reciprocal-space operations
NASA Astrophysics Data System (ADS)
Boykin, Timothy B.; Ajoy, Arvind; Ilatikhameneh, Hesameddin; Povolotskyi, Michael; Klimeck, Gerhard
In recent years, alloy electronic structure calculations based on supercell Brillouin zone unfolding have become popular. There are a number of formulations of the method which on the surface might appear different. Here we show that a discrete real-space description, based on discrete Fourier transforms, is fully general. Furthermore, such an approach can more easily show the effects of alloy scattering. We present such a method for treating the random alloy problem. This treatment features straightforward mathematics and a transparent physical interpretation of the calculated effective (i.e., approximate) energy bands.
Investigation of physical implementation of one-way quantum repeaters with multilevel systems
NASA Astrophysics Data System (ADS)
Muralidharan, Sreraman; Zou, Chang-Ling; Li, Linshu; Wen, Jianming; Jiang, Liang
Error correcting codes of multilevel systems have been shown to be resource efficient for the correction of erasure errors. One way quantum repeaters based on multilevel systems offer ultrafast key generation rates, while consuming lower resources than qubit based schemes (arXiv:1504.08054). On the other hand, they are technologically demanding. Here, we identify the key technological requirements needed for the implementation of quantum repeaters with multilevel systems and propose different experimental techniques that can be used to overcome the difficulties. We propose a generalized Duan-Kimble scheme for the generation of error correcting codes of multilevel systems with time-bin qudits.
Incorporating a multilevel perspective into occupational stress research: theoretical, methodological, and practical implications.
Bliese, Paul D; Jex, Steve M
In recent years, scholars in organizational behavior and public health have recognized the value of multilevel modeling. This article draws from both of these fields to illustrate the benefits of incorporating a multilevel perspective into the study of occupational stress. The authors identify key multilevel issues in occupational stress in terms of (a) individual-level analyses, (b) group-level analyses, and (c) cross-level analyses. They integrate the theoretical points with statistical models to help illustrate how one can test multilevel occupational stress propositions. PMID:12148957
High-Density, High-Bandwidth, Multilevel Holographic Memory
NASA Technical Reports Server (NTRS)
Chao, Tien-Hsin
A proposed holographic memory system would be capable of storing data at unprecedentedly high density, and its data transfer performance in both reading and writing would be characterized by exceptionally high bandwidth. The capabilities of the proposed system would greatly exceed even those of a state-of-the art memory system, based on binary holograms (in which each pixel value represents 0 or 1), that can hold .1 terabyte of data and can support a reading or writing rate as high as 1 Gb/s. The storage capacity of the state-of-theart system cannot be increased without also increasing the volume and mass of the system. However, in principle, the storage capacity could be increased greatly, without significantly increasing the volume and mass, if multilevel holograms were used instead of binary holograms. For example, a 3-bit (8-level) hologram could store 8 terabytes, or an 8-bit (256-level) hologram could store 256 terabytes, in a system having little or no more size and mass than does the state-of-the-art 1-terabyte binary holographic memory. The proposed system would utilize multilevel holograms. The system would include lasers, imaging lenses and other beam-forming optics, a block photorefractive crystal wherein the holograms would be formed, and two multilevel spatial light modulators in the form of commercially available deformable-mirror-device spatial light modulators (DMDSLMs) made for use in high speed input conversion of data up to 12 bits. For readout, the system would also include two arrays of complementary metal oxide/semiconductor (CMOS) photodetectors matching the spatial light modulators. The system would further include a reference-beam sterring device (equivalent of a scanning mirror), containing no sliding parts, that could be either a liquid-crystal phased-array device or a microscopic mirror actuated by a high-speed microelectromechanical system. Time-multiplexing and the multilevel nature of the DMDSLM would be exploited to enable writing
Computation of scattering matrix elements of large and complex shaped absorbing particles with multilevel fast multipole algorithm
NASA Astrophysics Data System (ADS)
Wu, Yueqian; Yang, Minglin; Sheng, Xinqing; Ren, Kuan Fang
Light scattering properties of absorbing particles, such as the mineral dusts, attract a wide attention due to its importance in geophysical and environment researches. Due to the absorbing effect, light scattering properties of particles with absorption differ from those without absorption. Simple shaped absorbing particles such as spheres and spheroids have been well studied with different methods but little work on large complex shaped particles has been reported. In this paper, the surface Integral Equation (SIE) with Multilevel Fast Multipole Algorithm (MLFMA) is applied to study scattering properties of large non-spherical absorbing particles. SIEs are carefully discretized with piecewise linear basis functions on triangle patches to model whole surface of the particle, hence computation resource needs increase much more slowly with the particle size parameter than the volume discretized methods. To improve further its capability, MLFMA is well parallelized with Message Passing Interface (MPI) on distributed memory computer platform. Without loss of generality, we choose the computation of scattering matrix elements of absorbing dust particles as an example. The comparison of the scattering matrix elements computed by our method and the discrete dipole approximation method (DDA) for an ellipsoid dust particle shows that the precision of our method is very good. The scattering matrix elements of large ellipsoid dusts with different aspect ratios and size parameters are computed. To show the capability of the presented algorithm for complex shaped particles, scattering by asymmetry Chebyshev particle with size parameter larger than 600 of complex refractive index m = 1.555 + 0.004 i and different orientations are studied.
The discrete-time compensated Kalman filter
NASA Technical Reports Server (NTRS)
Lee, W. H.; Athans, M.
A suboptimal dynamic compensator to be used in conjunction with the ordinary discrete time Kalman filter was derived. The resultant compensated Kalman Filter has the property that steady state bias estimation errors, resulting from modelling errors, were eliminated.
Running Parallel Discrete Event Simulators on Sierra
Barnes, P. D.; Jefferson, D. R.
In this proposal we consider porting the ROSS/Charm++ simulator and the discrete event models that run under its control so that they run on the Sierra architecture and make efficient use of the Volta GPUs.
Motion of Discrete Interfaces Through Mushy Layers
NASA Astrophysics Data System (ADS)
Braides, Andrea; Solci, Margherita
We study the geometric motion of sets in the plane derived from the homogenization of discrete ferromagnetic energies with weak inclusions. We show that the discrete sets are composed by a `bulky' part and an external `mushy region' composed only of weak inclusions. The relevant motion is that of the bulky part, which asymptotically obeys to a motion by crystalline mean curvature with a forcing term, due to the energetic contribution of the mushy layers, and pinning effects, due to discreteness. From an analytical standpoint, it is interesting to note that the presence of the mushy layers implies only a weak and not strong convergence of the discrete motions, so that the convergence of the energies does not commute with the evolution. From a mechanical standpoint it is interesting to note the geometrical similarity of some phenomena in the cooling of binary melts.
A discrete control model of PLANT
NASA Technical Reports Server (NTRS)
Mitchell, C. M.
A model of the PLANT system using the discrete control modeling techniques developed by Miller is described. Discrete control models attempt to represent in a mathematical form how a human operator might decompose a complex system into simpler parts and how the control actions and system configuration are coordinated so that acceptable overall system performance is achieved. Basic questions include knowledge representation, information flow, and decision making in complex systems. The structure of the model is a general hierarchical/heterarchical scheme which structurally accounts for coordination and dynamic focus of attention. Mathematically, the discrete control model is defined in terms of a network of finite state systems. Specifically, the discrete control model accounts for how specific control actions are selected from information about the controlled system, the environment, and the context of the situation. The objective is to provide a plausible and empirically testable accounting and, if possible, explanation of control behavior.
Motion of Discrete Interfaces Through Mushy Layers
NASA Astrophysics Data System (ADS)
Braides, Andrea; Solci, Margherita
We study the geometric motion of sets in the plane derived from the homogenization of discrete ferromagnetic energies with weak inclusions. We show that the discrete sets are composed by a `bulky' part and an external `mushy region' composed only of weak inclusions. The relevant motion is that of the bulky part, which asymptotically obeys to a motion by crystalline mean curvature with a forcing term, due to the energetic contribution of the mushy layers, and pinning effects, due to discreteness. From an analytical standpoint, it is interesting to note that the presence of the mushy layers implies only a weak and not strong convergence of the discrete motions, so that the convergence of the energies does not commute with the evolution. From a mechanical standpoint it is interesting to note the geometrical similarity of some phenomena in the cooling of binary melts.
Discrete Element Modeling of Drop Tests
NASA Astrophysics Data System (ADS)
Wang, Yuannian; Tonon, Fulvio
A discrete element code with impact model has been developed and calibrated to simulate the dynamic behavior of rock materials, with special regard to rock fragmentation upon impact during rock-fall analysis. The paper summarizes the discrete element code, the calibration algorithms developed to identify the model microparameters, and the impact model. Experimental work on drop tests is then used to validate the code on modeling impact fragmentation. It has been found that the developed discrete element code and impact model can reasonably simulate rock fragmentation in drop tests. The use of the discrete element code and impact model can provide good reference results in evaluating impact fragmentation in rock-fall analysis.
Comparing the Discrete and Continuous Logistic Models
ERIC Educational Resources Information Center
Gordon, Sheldon P.
The solutions of the discrete logistic growth model based on a difference equation and the continuous logistic growth model based on a differential equation are compared and contrasted. The investigation is conducted using a dynamic interactive spreadsheet. (Contains 5 figures.)
Reducing Neuronal Networks to Discrete Dynamics
Terman, David; Ahn, Sungwoo; Wang, Xueying; Just, Winfried
We consider a general class of purely inhibitory and excitatory-inhibitory neuronal networks, with a general class of network architectures, and characterize the complex firing patterns that emerge. Our strategy for studying these networks is to first reduce them to a discrete model. In the discrete model, each neuron is represented as a finite number of states and there are rules for how a neuron transitions from one state to another. In this paper, we rigorously demonstrate that the continuous neuronal model can be reduced to the discrete model if the intrinsic and synaptic properties of the cells are chosen appropriately. In a companion paper [1], we analyze the discrete model. PMID:18443649
Dynamic discretization method for solving Kepler's equation
NASA Astrophysics Data System (ADS)
Feinstein, Scott A.; McLaughlin, Craig A.
Kepler's equation needs to be solved many times for a variety of problems in Celestial Mechanics. Therefore, computing the solution to Kepler's equation in an efficient manner is of great importance to that community. There are some historical and many modern methods that address this problem. Of the methods known to the authors, Fukushima's discretization technique performs the best. By taking more of a system approach and combining the use of discretization with the standard computer science technique known as dynamic programming, we were able to achieve even better performance than Fukushima. We begin by defining Kepler's equation for the elliptical case and describe existing solution methods. We then present our dynamic discretization method and show the results of a comparative analysis. This analysis will demonstrate that, for the conditions of our tests, dynamic discretization performs the best.
Asymptotics of a Discrete-Time Particle System Near a Reflecting Boundary
NASA Astrophysics Data System (ADS)
Kuan, Jeffrey
We examine a discrete-time Markovian particle system on ℕ×ℤ+ introduced in Defosseux (arXiv:
Conceptualizing and Estimating Process Speed in Studies Employing Ecological Momentary Assessment Designs: A Multilevel Variance Decomposition Approach
Shiyko, Mariya P.; Ram, Nilam
Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread, questions are arising about the frequency of data sampling, with direct implications for participants' burden and researchers' ability to capture and study dynamic processes. Traditionally, spectral analytic techniques are used for time series data to identify process speed. However, the nature of EMA data, often collected with fewer than 100 measurements per person, sampled at randomly spaced intervals, and replete with planned and unplanned missingness, precludes application of traditional spectral analytic techniques. Building on principles of variance partitioning used in the generalizability theory of measurement and spectral analysis, we illustrate the utility of multilevel variance decompositions for isolating process speed in EMA-type data. Simulation and empirical data from a smoking-cessation study are used to demonstrate the method and to evaluate the process speed of smoking urges and quitting self-efficacy. Results of the multilevel variance decomposition approach can inform process-oriented theory and future EMA study designs. PMID:22707796
Hybrid surgery versus anterior cervical discectomy and fusion for multilevel cervical degenerative disc diseases: a meta-analysis.
Tian, Peng; Fu, Xin; Li, Zhi-Jun; Sun, Xiao-Lei; Ma, Xin-Long
The objective of this meta-analysis is to compare hybrid surgery (HS) and cervical discectomy and fusion (ACDF) for multilevel cervical degenerative disc diseases (DDD). Systematic searches of all published studies through March 2015 were identified from Cochrane Library, Medline, PubMed, Embase, ScienceDirect, CNKI, WANFANG DATA and CQVIP. Randomized controlled trials (RCTs) and non-RCTs involving HS and ACDF for multilevel DDD were included. All literature was searched and assessed by two independent reviewers according to the standard of Cochrane systematic review. Data of functional and radiological outcomes in two groups were pooled, which was then analyzed by RevMan 5.2 software. One RCT and four non-RCTs encompassing 160 patients met the inclusion criteria. Meta-analysis revealed significant differences in blood loss (p = 0.005), postoperative C2-C7 ROM (p = 0.002), ROM of superior adjacent segment (p < 0.00001) and ROM of inferior adjacent segment (p = 0.0007) between the HS group and the ACDF group. No significant differences were found regarding operation time (p = 0.75), postoperative VAS (p = 0.18) and complications (p = 0.73) between the groups. Hybrid surgery demonstrated excellent clinical efficacy and radiological results. Postoperative C2-C7 ROM was closer to the physiological status. No decrease in the ROM of the adjacent segment was noted in the hybrid surgery group. PMID:26307360
Intergenerational Transmission of Maltreatment: A Multilevel Examination
Leve, Leslie D.; Khurana, Atika; Reich, Emily B.
Despite the commonly held belief that there is a high degree of intergenerational continuity in maltreatment, studies to date suggest a mixed pattern of findings. One reason for the variance in findings may be related to the measurement approach used, which includes a range of self-report and official indicators of maltreatment and both cross-sectional and longitudinal designs. This study attempted to shed light on the phenomenon of intergenerational continuity of maltreatment by examining multiple indicators of perpetration of maltreatment in young adults and multiple risk factors across different levels within an individual's social ecology. The sample included 166 women who had been placed in out-of-home care as adolescents (>85% had a substantiated maltreatment incident) and followed into young adulthood, and included three waves of adolescent data and six waves of young adult data collected across 10 years. The participants were originally recruited during adolescence as part of a randomized controlled trial examining the efficacy of the Treatment Foster Care Oregon intervention. Analyses revealed weak to modest associations between the three indicators of perpetration of maltreatment in young adulthood, i.e., official child welfare records, self-reported child welfare system involvement, and self-reported maltreatment (r = .03–.51). Further, different patterns of prediction emerged as a function of the measurement approach. Adolescent delinquency was a significant predictor of subsequent self-reported child welfare contact, and young adult partner risk was a significant predictor of perpetration of maltreatment as indexed by both official child welfare records and self-reported child welfare contact. In addition, women who were originally assigned to the intervention condition reported perpetrating less maltreatment during young adulthood. Implications for measurement and interventions related to reducing the risk for intergenerational transmission of
Intergenerational transmission of maltreatment: A multilevel examination.
Leve, Leslie D; Khurana, Atika; Reich, Emily B
Despite the commonly held belief that there is a high degree of intergenerational continuity in maltreatment, studies to date suggest a mixed pattern of findings. One reason for the variance in findings may be related to the measurement approach used, which includes a range of self-report and official indicators of maltreatment and both cross-sectional and longitudinal designs. This study attempted to shed light on the phenomenon of intergenerational continuity of maltreatment by examining multiple indicators of perpetration of maltreatment in young adults and multiple risk factors across different levels within an individual's social ecology. The sample included 166 women who had been placed in out-of-home care as adolescents (>85% had a substantiated maltreatment incident) and followed into young adulthood, and included three waves of adolescent data and six waves of young adult data collected across 10 years. The participants were originally recruited during adolescence as part of a randomized controlled trial examining the efficacy of the Treatment Foster Care Oregon intervention. Analyses revealed weak to modest associations among the three indicators of perpetration of maltreatment in young adulthood, that is, official child welfare records, self-reported child welfare system involvement, and self-reported maltreatment (r = .03-.51). Further, different patterns of prediction emerged as a function of the measurement approach. Adolescent delinquency was a significant predictor of subsequent self-reported child welfare contact, and young adult partner risk was a significant predictor of perpetration of maltreatment as indexed by both official child welfare records and self-reported child welfare contact. In addition, women who were originally assigned to the intervention condition reported perpetrating less maltreatment during young adulthood. Implications for measurement and interventions related to reducing the risk for intergenerational transmission of risk
Eigenforms, Discrete Processes and Quantum Processes
NASA Astrophysics Data System (ADS)
Kauffman, Louis H.
This essay is a discussion of the concept of eigenform, due to Heinz von Foerster, and its relationship with discrete physics and quantum mechanics. We interpret the square root of minus one as a simple oscillatory process - a clock, and as an eigenform. By taking a generalization of this identification of i as a clock and eigenform, we show how quantum mechanics emerges from discrete physics.
Separable two-dimensional discrete Hartley transform
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Poirson, Allen
Bracewell has proposed the Discrete Hartley Transform (DHT) as a substitute for the Discrete Fourier Transform (DFT), particularly as a means of convolution. Here, it is shown that the most natural extension of the DHT to two dimensions fails to be separate in the two dimensions, and is therefore inefficient. An alternative separable form is considered, corresponding convolution theorem is derived. That the DHT is unlikely to provide faster convolution than the DFT is also discussed.
`t Hooft anomaly matching for discrete symmetries
Csaki, C.; Murayama, Hitoshi |
The authors show how to extend the `t Hooft anomaly matching conditions to discrete symmetries. They check these discrete anomally matching conditions on several proposed low-energy spectra of certain strongly interacting gauge theories. The excluded examples include the proposed chirally symmetric vacuum of pure N = 1 supersymmetric yang-Mills theories, certain non-supersymmetric confining theories and some self-dual N = 1 supersymmetric theories based on exceptional groups.