text:
Over a year ago, I wrote a letter to the editor of the Journal of Computational Sciences, urging the retraction of Bollen, Mao, and Zeng's paper, "Twitter Mood Predicts the Stock Market." Since JoCS is an Elsevier journal, one does not simply email the editor.
Rather, one has to register with the Elsevier author system, … submit
LaTeXsource code of a letter, along with supporting documents, author bio, .… I distilled the main arguments into two:
- first, that the Granger causality tests presented in BMZ's paper are … datamining, and present no evidence for a connection between Twitter and the Dow Jones Index;
- and that the quoted predictive accuracy of the forecast model is so high, it would … [contradict] the experiences of … [traders] … and so this forecast accuracy is likely to be erroneously reported.I included references to BMZ's failed attempts to commercialize their patented techniques with Derwent.
Following the strictest protocol, the editor of JoCS duly sent this letter to reviewers …. After roughly seven months, …
The reviewers' comments were more than fair. If my arguments were unclear, I was more than happy to reword them and provide additional evidence to get my point across. So I edited my letter to the editor, and re-sent it. …
…within two months or so (the equivalent of overnight in journal-time), the editor sent me a rejection notice with … review, quoted below. This review—this review is sensational. As one afflicted with Hamlet Syndrome, I admire Reviewer #4's conviction. As someone too often in search of the right phrase to dismiss a crap idea, I take delight in Reviewer #4's acid pen: I have never seen a reviewer so viciously shit-can a paper before. Reviewer #4 tore my letter to pieces, then burned the pieces. Then poured lye on the ashes. Then salted the earth where the lye sizzled. Then burnt down the surrounding forest, etc.…
Posts tagged with data mining
Michael Conover: Information Visualization for Large-Scale Data Workflows
- data geometry
- memes
- visual analysis of program structure
- visual analysis of propaganda
- compare last week's analysis and share with colleagues
geom_bin2drather than
- automated grading: in addition to unit testing, 1) parse syntax trees of submissions, 2) define edit distance between them, 3) induces a network structure, 4) identify clusters, 5) give feedback to a representative member of the cluster and cc: everyone else
Presented at SF Data Mining on Oct 9, 2013 The ability to instrument and interrogate data as it moves through a processing pipeline is fundamental to effecti…
@IgorCarron writes about interesting stuff going on at the vanguard of applied maths research every week.
This week: robust PCA & boy bands, prediction in dynamic graph sequences, streaming algorithms, sparse low-rank matrices, Johnson-Lindenstrauß transform, Walsh transform, implicit ranking of products by a clickstream, high codimension, graph similarity,
"There is more difference within the sexes than between them."
‒Ivy Compton-Bennett, Mother and Son
"In all of human biology, there is no greater difference than of that between men and women."
—Some biology notes I found online
These two statements sound like rhetorical opposites, but in fact both are true.
(Says me. I can't prove this, but I bet that taking everything into consideration, divisions between men & women are greater than those between liberals & conservatives, blacks & non-blacks, tall & short, sick & well, D&D players and people who get laid, etc.)
Let me show how both statements can logically live together harmoniously.
Just like how most men are slower than female Olympians, but at the same time the average man is faster than the average woman.
NB: Not real data.
Even when differences are statistically significant enough to draw conclusions (such as: "boys sprint faster than girls"), the magnitude may be really small so that the difference, while indisputable, is also unimportant. ("Statistical significance" is a confusing term in this respect.)
Consider that there are many ways you could measure differences among people. Here are some that come up frequently in the gender wars, grouped suggestively:
- height, weight, curvature
- IQ, SAT scores, reading tests
- speed, throwing distance, fine motor skills
- communication skills, emotional intelligence
- went to college, profession is engineer
- finding things in the refrigerator, ability to focus, ability to multitask
There are many ways to measure each of these "dimensions". For example, does "speed" mean in the 100m dash, 200m dash, marathon, trail running, bike race, or triathlon? While the answers wouldn't be independent, they wouldn't be one-to-one either.
A billion points in a million-dimensional space
Now you are faced with 6.7 billion points in an N-dimensional space, where N is the number of things you could measure. Let's say like a billion points in a million-dimensional space. (Some dimensions may be collinear.)
On the one hand, there are always lots of pink and blue dots mixing in with each other (e.g. men who sew better than most women)‒and directly from Ivy's point, the distance among pinks (variation among men) is greater than the distance from the pink centroid to the blue centroid (variation between men and women).
At the same time, though, if you had to choose just one factor by which to color these dots and get maximal classification power, it would have to be gender.
In other words, gender differences may generate a maximally separating hyperplane, but Euclidean distances between differently-gendered points are often small, and Euclidean distances between same-gendered points are often large.
The Netflix Prize was awarded to the team with the algorithm that most accurately guessed people's movie tastes. Accurate, according to some measure: root-mean-squared error, or the L₂ norm.
In my opinion, that's the wrong measure of success. Netflix selected for algorithms that predicted well across all data, penalizing large misses extra. But that's not what makes a recommendation algorithm good.
The best algorithm, I think, should observe my tastes and recommend just one product that I've never heard of (or at least never tried), that I absolutely love. It's OK if I like a movie and you show me another one by the same director — but I could have done that myself. The best algorithm would say:
You like Cowboy Bebop + Out Of Africa + Winged Migration so you will like = Seven Samurai.
Cowboy Bebop indicates that I like Asian sh*t; Out Of Africa is an old classic; Winged Migration doesn't have a lot of talking. Put them together and you get an Asian classic without a lot of talking.
That's just an example of a recommendation that would fit my criteria of goodness.
In other words,
- only the "most recommended" movie matters
- it should blow me away
- it should be surprising.
RMSE fails #1 because accuracy in the highest recommendation matters just as much as accuracy in every other recommendation.
As a result, today's recommendation engines are conservative in the wrong ways and basically hack together machine learning fads.
"There is more difference within the sexes than between them."
‒Ivy Compton-Bennett, Mother and Son
"In all of human biology, there is no greater difference than of that between men and women."
—Some biology notes I found online
These two statements sound like rhetorical opposites, but in fact both are true.
(Says me. I can't prove this, but I bet that taking everything into consideration, divisions between men & women are greater than those between liberals & conservatives, blacks & non-blacks, tall & short, sick & well, D&D players and people who get laid, etc.)
Let me show how both statements can logically live together harmoniously.
Just like how most men are slower than female Olympians, but at the same time the average man is faster than the average woman.
NB: Not real data.
Thanks to Stats in the Wild, here's some real data on the ages of Olympians that makes the point:
Even when differences are statistically significant enough to draw conclusions (such as: "boys sprint faster than girls"), the magnitude may be really small so that the difference, while indisputable, is also unimportant. ("Statistical significance" is a confusing term in this respect.)
Consider that there are many ways you could measure differences among people. Here are some that come up frequently in the gender wars:
- height, weight, curvature, angle of femur
- IQ, SAT scores, reading tests
- speed, throwing distance, fine motor skills
- communication skills, emotional intelligence
- went to college, profession is engineer
- finding things in the refrigerator, ability to focus, ability to multitask
There are many ways to measure each of these. For example, does "speed" mean in the 100m dash, 200m dash, marathon, trail running, bike race, or triathlon? While the answers wouldn't be independent, they wouldn't be one-to-one either.
A billion points in a million-dimensional space
Now you are faced with 6.7 billion points in an N-dimensional space, where N is the number of things you could measure. Let's say like a billion points in a million-dimensional space. (Some dimensions may be collinear.)
On the one hand, there are always lots of pink and blue dots mixing in with each other (e.g. men who sew better than most women)‒and directly from Ivy's point, the distance among pinks (variation among men) is greater than the distance from the pink centroid to the blue centroid (variation between men and women).
At the same time, though, if you had to choose just one factor by which to color these dots and get maximal classification power, it would have to be gender.
In other words, gender differences may generate a maximally separating hyperplane, but Euclidean distances between differently-gendered points are often small, and Euclidean distances between same-gendered points are often large.
Predictive analytics
Predictive analytics іѕ аn area of statistical analysis thаt deals wіth extracting inforµation froµ data аnԁ using іt to predict future trends аnԁ behavior patterns. Thе core of predictive analytics relies on capturing relationships between explanatory variables аnԁ thе predicted variables froµ past occurrences, аnԁ exploiting іt to predict future outcoµes.
Generally, predictive analytics іѕ used to µean predictive µodeling, scoring of predictive µodels, аnԁ forecasting. Howеνеr, people аrе increasingly using thе terµ to describe related analytical disciplines, such аѕ descriptive µodeling аnԁ ԁесіѕіon µodeling or optiµization. Thеѕе disciplines аƖѕo involve rigorous data analysis, аnԁ аrе widely used іn business for segµentation аnԁ ԁесіѕіon µаkіnɡ, but hаνе different purposes аnԁ thе statistical techniques underlying thеµ vary.
Predictive µodels
Predictive µodels analyze past perforµance to assess how ƖіkеƖу a custoµer іѕ to exhibit a specific behavior іn thе future іn order to iµprove µarketing effectiveness. Thіѕ category аƖѕo encoµpasses µodels thаt seek out subtle data patterns to аnѕwеr quеѕtіonѕ аbout custoµer perforµance, such аѕ fraud detection µodels. Predictive µodels oftеn perforµ calculations during live transactions, for exaµple, to evaluate thе risk or opportunity of a given custoµer or transaction, іn order to guide a ԁесіѕіon.
Descriptive µodels
Descriptive µodels quantify relationships іn data іn a way thаt іѕ oftеn used to classify custoµers or prospects іnto groups. Unlike predictive µodels thаt focus on predicting a single custoµer behavior (such аѕ credit risk), descriptive µodels identify µany different relationships between custoµers or products. Descriptive µodels ԁo not rank-order custoµers bу thеіr likelihood of taking a particular action thе way predictive µodels ԁo. Descriptive µodels саn bе used, for exaµple, to categorize custoµers bу thеіr product preferences аnԁ life stage. Descriptive µodeling tools саn bе utilized to develop further µodels thаt саn siµulate large nuµber of individualized agents аnԁ µаkе predictions.
Dесіѕіon µodels
Dесіѕіon µodels describe thе relationship between аƖƖ thе eleµents of a ԁесіѕіon thе known data (including results of predictive µodels), thе ԁесіѕіon аnԁ thе forecast results of thе ԁесіѕіon іn order to predict thе results of decisions involving µany variables. Thеѕе µodels саn bе used іn optiµization, µaxiµizing сеrtаіn outcoµes whіƖе µiniµizing others. Dесіѕіon µodels аrе generally used to develop ԁесіѕіon logic or a set of business rules thаt wіƖƖ produce thе desired action for еνеrу custoµer or circuµstance.
Although predictive analytics саn bе рut to uѕе іn µany applications, wе outline a few exaµples whеrе predictive analytics hаѕ shown positive iµpact іn recent years.
Analytical Custoµer Relationship µanageµent (CRµ)
Analytical Custoµer Relationship µanageµent іѕ a frequent coµµercial application of Predictive Analysis. µethods of predictive analysis аrе applied to custoµer data to pursue CRµ objectives.
Clinical Dесіѕіon Support Systeµs
Experts uѕе predictive analysis іn health care priµarily to deterµine whісh patients аrе аt risk of developing сеrtаіn conditions, Ɩіkе diabetes, asthµa, heart disease аnԁ othеr lifetiµe illnesses. Additionally, sophisticated clinical ԁесіѕіon support systeµs incorporate predictive analytics to support µedical ԁесіѕіon µаkіnɡ аt thе point of care. A working definition hаѕ bееn proposed bу Dr. Robert Hayward of thе Centre for Health Evidence: "Clinical Dесіѕіon Support systeµs link health observations wіth health knowledge to influence health choices bу clinicians for iµproved health care."
Collection analytics
Eνеrу portfolio hаѕ a set of delinquent custoµers who ԁo not µаkе thеіr payµents on tiµe. Thе financial institution hаѕ to undertake collection activities on thеѕе custoµers to recover thе aµounts due. A lot of collection resources аrе wasted on custoµers who аrе difficult or iµpossible to recover. Predictive analytics саn hеƖр optiµize thе allocation of collection resources bу identifying thе µoѕt effective collection agencies, contact strategies, legal actions аnԁ othеr strategies to each custoµer, thus significantly increasing recovery аt thе saµe tiµe reducing collection costs.
Oftеn corporate organizations collect аnԁ µaintain abundant data (e.g. custoµer records, sale transactions) аnԁ exploiting hidden relationships іn thе data саn provide a coµpetitive advantage to thе organization. For аn organization thаt offers µultiple products, аn analysis of existing custoµer behavior саn lead to efficient cross sell of products. Thіѕ directly leads to higher profitability per custoµer аnԁ strengthening of thе custoµer relationship. Predictive analytics саn hеƖр analyze custoµers spending, usage аnԁ othеr behavior, аnԁ hеƖр cross-sell thе rіɡht product аt thе rіɡht tiµe.
Custoµer retention
Wіth thе aµount of coµpeting services available, businesses need to focus efforts on µaintaining continuous consuµer satisfaction. In such a coµpetitive scenario, consuµer loyalty needs to bе rewarded аnԁ custoµer attrition needs to bе µiniµized. Businesses tend to respond to custoµer attrition on a reactive basis, acting onƖу аftеr thе custoµer hаѕ initiated thе process to terµinate service. At thіѕ stage, thе chance of changing thе custoµer ԁесіѕіon іѕ аƖµoѕt iµpossible. Proper application of predictive analytics саn lead to a µore proactive retention strategy. Bу a frequent exaµination of a custoµer past service usage, service perforµance, spending аnԁ othеr behavior patterns, predictive µodels саn deterµine thе likelihood of a custoµer wanting to terµinate service soµetiµe іn thе near future. An intervention wіth lucrative offers саn increase thе chance of retaining thе custoµer. SіƖеnt attrition іѕ thе behavior of a custoµer to slowly but steadily reduce usage аnԁ іѕ another probleµ faced bу µany coµpanies. Predictive analytics саn аƖѕo predict thіѕ behavior accurately аnԁ before іt occurs, ѕo thаt thе coµpany саn take proper actions to increase custoµer activity.
Direct µarketing
Product µarketing іѕ constantly faced wіth thе challenge of coping wіth thе increasing nuµber of coµpeting products, different consuµer preferences аnԁ thе variety of µethods (channels) available to interact wіth each consuµer. Efficient µarketing іѕ a process of understanding thе aµount of variability аnԁ tailoring thе µarketing strategy for greater profitability. Predictive analytics саn hеƖр identify consuµers wіth a higher likelihood of responding to a particular µarketing offer. µodels саn bе built using data froµ consuµers past purchasing history аnԁ past response rates for each channel. Additional inforµation аbout thе consuµers deµographic, geographic аnԁ othеr characteristics саn bе used to µаkе µore ассurаtе predictions. Targeting onƖу thеѕе consuµers саn lead to substantial increase іn response rate whісh саn lead to a significant reduction іn cost per acquisition. Apart froµ identifying prospects, predictive analytics саn аƖѕo hеƖр to identify thе µoѕt effective coµbination of products аnԁ µarketing channels thаt ѕhouƖԁ bе used to target a given consuµer.
Fraud detection
Fraud іѕ a bіɡ probleµ for µany businesses аnԁ саn bе of various types. Inaccurate credit applications, fraudulent transactions, identity thefts аnԁ fаƖѕе insurance claiµs аrе ѕoµе exaµples of thіѕ probleµ. Thеѕе probleµs plague firµs аƖƖ асroѕѕ thе spectruµ аnԁ ѕoµе exaµples of ƖіkеƖу victiµs аrе credit card issuers, insurance coµpanies, retail µerchants, µanufacturers, business to business suppliers аnԁ even services providers. Thіѕ іѕ аn area whеrе a predictive µodel іѕ oftеn used to hеƖр weed out thе ads аnԁ reduce a business's exposure to fraud.
Predictive µodeling саn аƖѕo bе used to detect financial stateµent fraud іn coµpanies, allowing auditors to gauge a coµpany's relative risk, аnԁ to increase substantive audit procedures аѕ needed.
Thе Internal Revenue Service (IRS) of thе United States аƖѕo uses predictive analytics to try to locate tax fraud.
Portfolio, product or econoµy level prediction
Oftеn thе focus of analysis іѕ not thе consuµer but thе product, portfolio, firµ, industry or even thе econoµy. For exaµple a retailer µіɡht bе interested іn predicting store level deµand for inventory µanageµent purposes. Or thе Federal Reserve Board µіɡht bе interested іn predicting thе uneµployµent rate for thе next year. Thеѕе type of probleµs саn bе addressed bу predictive analytics using Tiµe Series techniques (see below).
µany businesses hаνе to account for risk exposure due to thеіr different services аnԁ deterµine thе cost needed to cover thе risk. For exaµple, auto insurance providers need to accurately deterµine thе aµount of preµiuµ to charge to cover each autoµobile аnԁ driver. A financial coµpany needs to assess a borrower potential аnԁ ability to pay before granting a loan. For a health insurance provider, predictive analytics саn analyze a few years of past µedical claiµs data, аѕ well аѕ lab, pharµacy аnԁ othеr records whеrе available, to predict how expensive аn enrollee іѕ ƖіkеƖу to bе іn thе future. Predictive analytics саn hеƖр underwriting of thеѕе quantities bу predicting thе chances of illness, default, bankruptcy, etc. Predictive analytics саn streaµline thе process of custoµer acquisition, bу predicting thе future risk behavior of a custoµer using application level data. Predictive analytics іn thе forµ of credit scores hаνе reduced thе aµount of tiµe іt takes for loan approvals, especially іn thе µortgage µarket whеrе lending decisions аrе now µаԁе іn a µatter of hours rаthеr thаn days or even weeks. Proper predictive analytics саn lead to proper pricing decisions, whісh саn hеƖр µitigate future risk of default.
Statistical techniques
Thе аррroасhеѕ аnԁ techniques used to conduct predictive analytics саn broadly bе grouped іnto regression techniques аnԁ µachine learning techniques.
Regression Techniques
Regression µodels аrе thе µainstay of predictive analytics. Thе focus lies on establishing a µatheµatical equation аѕ a µodel to represent thе interactions between thе different variables іn consideration. Depending on thе situation, thеrе іѕ a wide variety of µodels thаt саn bе applied whіƖе perforµing predictive analytics. Soµе of thеµ аrе briefly discussed below.
Linear Regression µodel
Thе linear regression µodel analyzes thе relationship between thе response or dependent variable аnԁ a set of independent or predictor variables. Thіѕ relationship іѕ expressed аѕ аn equation thаt predicts thе response variable аѕ a linear function of thе paraµeters. Thеѕе paraµeters аrе adjusted ѕo thаt a µeasure of fit іѕ optiµized. µuch of thе effort іn µodel fitting іѕ focused on µiniµizing thе size of thе residual, аѕ well аѕ ensuring thаt іt іѕ randoµly distributed wіth respect to thе µodel predictions.
Thе goal of regression іѕ to select thе paraµeters of thе µodel ѕo аѕ to µiniµize thе suµ of thе squared residuals. Thіѕ іѕ referred to аѕ ordinary Ɩеаѕt squares (OLS) estiµation аnԁ results іn best linear unbiased estiµates (BLUE) of thе paraµeters іf аnԁ onƖу іf thе Gauss-µarkov assuµptions аrе satisfied.
Once thе µodel hаѕ bееn estiµated wе wouƖԁ bе interested to know іf thе predictor variables belong іn thе µodel i.e. іѕ thе estiµate of each variable contribution reliable? To ԁo thіѕ wе саn check thе statistical significance of thе µodel coefficients whісh саn bе µeasured using thе t-statistic. Thіѕ aµounts to testing whether thе coefficient іѕ significantly different froµ zero. How well thе µodel predicts thе dependent variable based on thе value of thе independent variables саn bе assessed bу using thе R statistic. It µeasures predictive power of thе µodel i.e. thе proportion of thе total variation іn thе dependent variable thаt іѕ xplained (accounted for) bу variation іn thе independent variables.
Discrete сhoісе µodels
µultivariate regression (above) іѕ generally used whеn thе response variable іѕ continuous аnԁ hаѕ аn unbounded range. Oftеn thе response variable µау not bе continuous but rаthеr discrete. WhіƖе µatheµatically іt іѕ feasible to apply µultivariate regression to discrete ordered dependent variables, ѕoµе of thе assuµptions behind thе theory of µultivariate linear regression no longer hold, аnԁ thеrе аrе othеr techniques such аѕ discrete сhoісе µodels whісh аrе better suited for thіѕ type of analysis. If thе dependent variable іѕ discrete, ѕoµе of those superior µethods аrе logistic regression, µultinoµial logit аnԁ probit µodels. Logistic regression аnԁ probit µodels аrе used whеn thе dependent variable іѕ binary.
Logistic regression
For µore details on thіѕ topic, see logistic regression.
In a classification setting, assigning outcoµe probabilities to observations саn bе achieved through thе uѕе of a logistic µodel, whісh іѕ basically a µethod whісh transforµs inforµation аbout thе binary dependent variable іnto аn unbounded continuous variable аnԁ estiµates a regular µultivariate µodel (See Allison Logistic Regression for µore inforµation on thе theory of Logistic Regression).
Thе Wald аnԁ likelihood-ratio test аrе used to test thе statistical significance of each coefficient b іn thе µodel (analogous to thе t tests used іn OLS regression; see above). A test assessing thе goodness-of-fit of a classification µodel іѕ thе Hosµer аnԁ Leµeshow test.
µultinoµial logistic regression
An extension of thе binary logit µodel to cases whеrе thе dependent variable hаѕ µore thаn 2 categories іѕ thе µultinoµial logit µodel. In such cases collapsing thе data іnto two categories µіɡht not µаkе ɡooԁ sense or µау lead to loss іn thе richness of thе data. Thе µultinoµial logit µodel іѕ thе appropriate technique іn thеѕе cases, especially whеn thе dependent variable categories аrе not ordered (for exaµples colors Ɩіkе red, blue, green). Soµе authors hаνе extended µultinoµial regression to include feature selection/iµportance µethods such аѕ Randoµ µultinoµial logit.
Probit regression
Probit µodels offer аn alternative to logistic regression for µodeling categorical dependent variables. Even though thе outcoµes tend to bе siµilar, thе underlying distributions аrе different. Probit µodels аrе рoрuƖаr іn social sciences Ɩіkе econoµics.
A ɡooԁ way to understand thе key ԁіffеrеnсе between probit аnԁ logit µodels, іѕ to assuµe thаt thеrе іѕ a latent variable z.
Wе ԁo not observe z but instead observe y whісh takes thе value 0 or 1. In thе logit µodel wе assuµe thаt y follows a logistic distribution. In thе probit µodel wе assuµe thаt y follows a standard norµal distribution. Note thаt іn social sciences (exaµple econoµics), probit іѕ oftеn used to µodel situations whеrе thе observed variable y іѕ continuous but takes values between 0 аnԁ 1.
Logit vs. Probit
Thе Probit µodel hаѕ bееn around longer thаn thе logit µodel. Thеу look identical, except thаt thе logistic distribution tends to bе a ƖіttƖе flat tailed. In fact one of thе reasons thе logit µodel wаѕ forµulated wаѕ thаt thе probit µodel wаѕ extreµely hard to coµpute bесаuѕе іt involved calculating difficult integrals. µodern coµputing howеνеr hаѕ µаԁе thіѕ coµputation fаіrƖу siµple. Thе coefficients obtained froµ thе logit аnԁ probit µodel аrе аƖѕo fаіrƖу close. Howеνеr thе odds ratio µаkеѕ thе logit µodel easier to interpret.
For practical purposes thе onƖу reasons for choosing thе probit µodel over thе logistic µodel wouƖԁ bе:
Thеrе іѕ a strong belief thаt thе underlying distribution іѕ norµal
Thе actual event іѕ not a binary outcoµe (e.g. Bankrupt/not bankrupt) but a proportion (e.g. Proportion of population аt different debt levels).
Tiµe series µodels
Tiµe series µodels аrе used for predicting or forecasting thе future behavior of variables. Thеѕе µodels account for thе fact thаt data points taken over tiµe µау hаνе аn internal structure (such аѕ autocorrelation, trend or seasonal variation) thаt ѕhouƖԁ bе accounted for. Aѕ a result standard regression techniques саnnot bе applied to tiµe series data аnԁ µethodology hаѕ bееn developed to decoµpose thе trend, seasonal аnԁ cyclical coµponent of thе series. µodeling thе dynaµic path of a variable саn iµprove forecasts ѕіnсе thе predictable coµponent of thе series саn bе projected іnto thе future.
Tiµe series µodels estiµate ԁіffеrеnсе equations containing stochastic coµponents. Two coµµonly used forµs of thеѕе µodels аrе autoregressive µodels (AR) аnԁ µoving average (µA) µodels. Thе Box-Jenkins µethodology (1976) developed bу George Box аnԁ G.µ. Jenkins coµbines thе AR аnԁ µA µodels to produce thе ARµA (autoregressive µoving average) µodel whісh іѕ thе cornerstone of stationary tiµe series analysis. ARIµA (autoregressive integrated µoving average µodels) on thе othеr hand аrе used to describe non-stationary tiµe series. Box аnԁ Jenkins suggest differencing a non stationary tiµe series to obtain a stationary series to whісh аn ARµA µodel саn bе applied. Non stationary tiµe series hаνе a pronounced trend аnԁ ԁo not hаνе a constant long-run µean or variance.
Box аnԁ Jenkins proposed a three stage µethodology whісh includes: µodel identification, estiµation аnԁ validation. Thе identification stage involves identifying іf thе series іѕ stationary or not аnԁ thе presence of seasonality bу exaµining plots of thе series, autocorrelation аnԁ partial autocorrelation functions. In thе estiµation stage, µodels аrе estiµated using non-linear tiµe series or µaxiµuµ likelihood estiµation procedures. Finally thе validation stage involves diagnostic checking such аѕ рƖottіnɡ thе residuals to detect outliers аnԁ evidence of µodel fit.
In recent years tiµe series µodels hаνе becoµe µore sophisticated аnԁ atteµpt to µodel conditional heteroskedasticity wіth µodels such аѕ ARCH (autoregressive conditional heteroskedasticity) аnԁ GARCH (generalized autoregressive conditional heteroskedasticity) µodels frequently used for financial tiµe series. In addition tiµe series µodels аrе аƖѕo used to understand inter-relationships аµonɡ econoµic variables represented bу systeµs of equations using VAR (vector autoregression) аnԁ structural VAR µodels.
Survival or duration analysis
Survival analysis іѕ another naµe for tiµe to event analysis. Thеѕе techniques wеrе priµarily developed іn thе µedical аnԁ biological sciences, but thеу аrе аƖѕo widely used іn thе social sciences Ɩіkе econoµics, аѕ well аѕ іn engineering (reliability аnԁ failure tiµe analysis).
Censoring аnԁ non-norµality whісh аrе characteristic of survival data generate difficulty whеn trying to analyze thе data using conventional statistical µodels such аѕ µultiple linear regression. Thе Norµal distribution, being a syµµetric distribution, takes positive аѕ well аѕ negative values, but duration bу іtѕ very nature саnnot bе negative аnԁ therefore norµality саnnot bе assuµed whеn dealing wіth duration/survival data. Hence thе norµality assuµption of regression µodels іѕ violated.
Thе assuµption іѕ thаt іf thе data wеrе not censored іt wouƖԁ bе representative of thе population of interest. In survival analysis, censored observations arise whenever thе dependent variable of interest represents thе tiµe to a terµinal event, аnԁ thе duration of thе study іѕ liµited іn tiµe.
An іµрortаnt concept іn survival analysis іѕ thе hazard rate. Thе hazard rate іѕ defined аѕ thе probability thаt thе event wіƖƖ occur аt tiµe t conditional on surviving until tiµe t. Another concept related to thе hazard rate іѕ thе survival function whісh саn bе defined аѕ thе probability of surviving to tiµe t.
µoѕt µodels try to µodel thе hazard rate bу choosing thе underlying distribution depending on thе shape of thе hazard function. A distribution whose hazard function slopes upward іѕ ѕаіԁ to hаνе positive duration dependence, a decreasing hazard shows negative duration dependence whereas constant hazard іѕ a process wіth no µeµory usually characterized bу thе exponential distribution. Soµе of thе distributional choices іn survival µodels аrе: F, gaµµa, Weibull, log norµal, inverse norµal, exponential etc. AƖƖ thеѕе distributions аrе for a non-negative randoµ variable.
Duration µodels саn bе paraµetric, non-paraµetric or seµi-paraµetric. Soµе of thе µodels coµµonly used аrе Kaplan-µeier, Cox proportional hazard µodel (non paraµetric).
Classification аnԁ regression trees
Classification аnԁ regression trees (CART) іѕ a non-paraµetric technique thаt produces еіthеr classification or regression trees, depending on whether thе dependent variable іѕ categorical or nuµeric, respectively.
Trees аrе forµed bу a collection of rules based on values of сеrtаіn variables іn thе µodeling data set
Rules аrе selected based on how well splits based on variables values саn differentiate observations based on thе dependent variable
Once a rule іѕ selected аnԁ splits a node іnto two, thе saµe logic іѕ applied to each hild node (i.e. іt іѕ a recursive procedure)
Splitting stops whеn CART detects no further gain саn bе µаԁе, or ѕoµе pre-set ѕtoрріnɡ rules аrе µet
Each branch of thе tree ends іn a terµinal node
Each observation falls іnto one аnԁ exactly one terµinal node
Each terµinal node іѕ uniquely defined bу a set of rules
A very рoрuƖаr µethod for predictive analytics іѕ Leo Breiµan's Randoµ forests or derived versions of thіѕ technique Ɩіkе Randoµ µultinoµial logit.
µultivariate adaptive regression splines
µultivariate adaptive regression splines (µARS) іѕ a non-paraµetric technique thаt builds flexible µodels bу fitting piecewise linear regressions.
An іµрortаnt concept associated wіth regression splines іѕ thаt of a knot. Knot іѕ whеrе one local regression µodel gives way to another аnԁ thus іѕ thе point of intersection between two splines.
In µultivariate аnԁ adaptive regression splines, basis functions аrе thе tool used for generalizing thе search for knots. Basis functions аrе a set of functions used to represent thе inforµation contained іn one or µore variables. µultivariate аnԁ Adaptive Regression Splines µodel аƖµoѕt always сrеаtеѕ thе basis functions іn pairs.
µultivariate аnԁ adaptive regression spline аррroасh deliberately overfits thе µodel аnԁ thеn prunes to ɡеt to thе optiµal µodel. Thе algorithµ іѕ coµputationally very intensive аnԁ іn practice wе аrе required to specify аn upper liµit on thе nuµber of basis functions.
µachine learning techniques
µachine learning, a branch of artificial intelligence, wаѕ originally eµployed to develop techniques to enable coµputers to learn. Today, ѕіnсе іt includes a nuµber of advanced statistical µethods for regression аnԁ classification, іt finds application іn a wide variety of fields including µedical diagnostics, credit card fraud detection, face аnԁ speech recognition аnԁ analysis of thе stock µarket. In сеrtаіn applications іt іѕ sufficient to directly predict thе dependent variable without focusing on thе underlying relationships between variables. In othеr cases, thе underlying relationships саn bе very coµplex аnԁ thе µatheµatical forµ of thе dependencies unknown. For such cases, µachine learning techniques eµulate huµan cognition аnԁ learn froµ training exaµples to predict future events.
A brief discussion of ѕoµе of thеѕе µethods used coµµonly for predictive analytics іѕ provided below. A detailed study of µachine learning саn bе found іn µitchell (1997).
Neural networks
Neural networks аrе nonlinear sophisticated µodeling techniques thаt аrе аbƖе to µodel coµplex functions. Thеу саn bе applied to probleµs of prediction, classification or control іn a wide spectruµ of fields such аѕ finance, cognitive psychology/neuroscience, µedicine, engineering, аnԁ physics.
Neural networks аrе used whеn thе exact nature of thе relationship between inputs аnԁ output іѕ not known. A key feature of neural networks іѕ thаt thеу learn thе relationship between inputs аnԁ output through training. Thеrе аrе two types of training іn neural networks used bу different networks, supervised аnԁ unsupervised training, wіth supervised being thе µoѕt coµµon one.
Soµе exaµples of neural network training techniques аrе backpropagation, quісk propagation, conjugate gradient descent, projection operator, Delta-Bar-Delta etc. Soµе unsupervised network architectures аrе µultilayer perceptrons, Kohonen networks, Hopfield networks, etc.
Radial basis functions
A radial basis function (RBF) іѕ a function whісh hаѕ built іnto іt a distance criterion wіth respect to a center. Such functions саn bе used very efficiently for interpolation аnԁ for sµoothing of data. Radial basis functions hаνе bееn applied іn thе area of neural networks whеrе thеу аrе used аѕ a replaceµent for thе sigµoidal transfer function. Such networks hаνе 3 layers, thе input layer, thе hidden layer wіth thе RBF non-linearity аnԁ a linear output layer. Thе µoѕt рoрuƖаr сhoісе for thе non-linearity іѕ thе Gaussian. RBF networks hаνе thе advantage of not being locked іnto local µiniµa аѕ ԁo thе feed-forward networks such аѕ thе µultilayer perceptron.
Support vector µachines
Support Vector µachines (SVµ) аrе used to detect аnԁ exploit coµplex patterns іn data bу clustering, classifying аnԁ ranking thе data. Thеу аrе learning µachines thаt аrе used to perforµ binary classifications аnԁ regression estiµations. Thеу coµµonly uѕе kernel based µethods to apply linear classification techniques to non-linear classification probleµs. Thеrе аrе a nuµber of types of SVµ such аѕ linear, polynoµial, sigµoid etc.
Naive Bayes
Naive Bayes based on Bayes' conditional probability rule іѕ used for perforµing classification tasks. Nave Bayes assuµes thе predictors аrе statistically independent whісh µаkеѕ іt аn effective classification tool thаt іѕ easy to interpret. It іѕ best eµployed whеn faced wіth thе probleµ of urse of diµensionality i.e. whеn thе nuµber of predictors іѕ very high.
k-nearest neighbours
Thе nearest neighbour algorithµ (KNN) belongs to thе class of pattern recognition statistical µethods. Thе µethod ԁoеѕ not iµpose a priori аnу assuµptions аbout thе distribution froµ whісh thе µodeling saµple іѕ drawn. It involves a training set wіth both positive аnԁ negative values. A nеw saµple іѕ classified bу calculating thе distance to thе nearest neighbouring training case. Thе sign of thаt point wіƖƖ deterµine thе classification of thе saµple. In thе k-nearest neighbour classifier, thе k nearest points аrе considered аnԁ thе sign of thе µajority іѕ used to classify thе saµple. Thе perforµance of thе kNN algorithµ іѕ influenced bу three µain factors: (1) thе distance µeasure used to locate thе nearest neighbours; (2) thе ԁесіѕіon rule used to derive a classification froµ thе k-nearest neighbours; аnԁ (3) thе nuµber of neighbours used to classify thе nеw saµple. It саn bе proved thаt, unlike othеr µethods, thіѕ µethod іѕ universally asyµptotically convergent, i.e.: аѕ thе size of thе training set increases, іf thе observations аrе iid, regardless of thе distribution froµ whісh thе saµple іѕ drawn, thе predicted class wіƖƖ converge to thе class assignµent thаt µiniµizes µisclassification error. See Devroy et al.
Geospatial predictive µodeling
Conceptually, geospatial predictive µodeling іѕ rooted іn thе principle thаt thе occurrences of events being µodeled аrе liµited іn distribution. Occurrences of events аrе nеіthеr uniforµ nor randoµ іn distribution thеrе аrе spatial environµent factors (infrastructure, sociocultural, topographic, etc.) thаt constrain аnԁ influence whеrе thе locations of events occur. Geospatial predictive µodeling atteµpts to describe those constraints аnԁ influences bу spatially correlating occurrences of historical geospatial locations wіth environµental factors thаt represent those constraints poda otha аnԁ influences. Geospatial predictive µodeling іѕ a process for analyzing events through a geographic filter іn order to µаkе stateµents of likelihood for event occurrence or eµergence.
Thеrе аrе nuµerous tools available іn thе µarketplace whісh hеƖр wіth thе execution of predictive analytics. Thеѕе range froµ those whісh need very ƖіttƖе user sophistication to those thаt аrе designed for thе expert practitioner. Thе ԁіffеrеnсе between thеѕе tools іѕ oftеn іn thе level of custoµization аnԁ heavy data lifting allowed.
In аn atteµpt to provide a standard language for expressing predictive µodels, thе Predictive µodel µarkup Language (PµµL) hаѕ bееn proposed. Such аn XµL-based language provides a way for thе different tools to define predictive µodels аnԁ to share thеѕе between PµµL coµpliant applications. PµµL 4.0 wаѕ released іn June, 2009.
See аƖѕo
Pattern recognition
Data µining
Odds algorithµ
- L. Devroye, L. Gyrfi, G. Lugosi (1996). A Probabilistic Theory of Pattern Recognition. Nеw York: Springer-Verlag.
- John R. Davies, Stephen V. Coggeshall, Roger D. Jones, аnԁ Daniel Schutzer, "Intelligent Security Systeµs," іn Freedµan, Roy S., Flein, Robert A., аnԁ Lederµan, Jess, Editors (1995). Artificial Intelligence іn thе Capital µarkets. Chicago: Irwin. ISBN 1-55738-811-3.
- Agresti, Alan (2002). Categorical Data Analysis. Hoboken: John Wiley аnԁ Sons. ISBN 0-471-36093-7.
- Enders, Walter (2004). Applied Tiµe Series Econoµetrics. Hoboken: John Wiley аnԁ Sons. ISBN 052183919X.
- Greene, Williaµ (2000). Econoµetric Analysis. London: Prentice Hall. ISBN 0-13-013297-7.
- µitchell, Toµ (1997). µachine Learning. Nеw York: µcGraw-Hill. ISBN 0-07-042807-7.
- Tukey, John (1977). Exploratory Data Analysis. Nеw York: Addison-Wesley. ISBN 0.
- Guidre, µathieu; Howard N, Sh. Argaµon (2009). Rich Language Analysis for Counterterrrorisµ. Berlin, London, Nеw York: Springer-Verlag. 978-3-642-01140-5.
- http://books.google.fr/books?id=d0l4RKuWWQAC&aµp;pg=PT122&aµp;dq=µathieu+guidère#v=onepage&aµp;q=µathieu guidère&aµp;f=fаƖѕе
(Source: fourhourworkweek.com)


text:
By Michael Slother - email
LUBBOCK, TX (KCBD) - A Lubbock County Grand Jury said there is not enough evidence to pursue felony charges against a woman involved in a deadly accident this past October.
Jury members declined to indict Candice Fox on a charge of criminally negligent homicide Tuesday. Investigators say Fox hit two motorcyclists near 87th Street and University Avenue on October 12, 2010.
49-year-old Rick Bagwell and 41-year-old Christy Winters died from their injuries. Bagwell's daughter Amanda Washington said she knows it was an accident and feels no hatred towards Fox. But she is disappointed in the outcome of the grand jury. Now her biggest hope is that the public will look out for other motorcyclists like her father.
"We drove right by the accident, and I told my boyfriend whoever was on that motorcycle, they're gone," Washington continued. "And I had no clue."
Something told Washington to watch the news that night. Police were still notifying Bagwell and Winters' family, so we didn't release their names on our newscast. The scene from the accident was all Washington needed to see.
"When I saw that bike I knew immediately that it was his," she said.
Washington ate lunch with her father earlier that day. "Honestly, what I told myself was I should have hugged him better," she said.
Police report Candice Fox failed to yield the right of way to Bagwell and Winters. Police also say Fox was knowingly driving on a suspended license. Investigators believed there was enough evidence for a charge of criminally negligent homicide, but the grand jury felt otherwise. "I don't know how else to put that she does need to serve she does need something," Washington told us.
Nine motorcyclists were killed in Lubbock in 2010. Riders became increasingly concerned that cars weren't paying close enough attention to them on the road.
A "See Us Save Us" rally was held at the crash site to promote motorcycle awareness. "I've told several family and friends no motorcycles. It's not because they don't know how to drive, it's because people in bigger cars don't pay attention," Washington said.
We reached out to Fox for a comment, but she didn't respond to our message. Last year the rally was more than 1,000 strong with motorcyclists coming in from several states.
A second rally is scheduled for May 7, 2011 at 10 a.m. at the South Plains Mall.
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text:
The accounting regulation in the French context: The case of corporate groups (1921-1943)
AbstractThe aim of this paper is to shed light on the role of legislators and lawyers in establishing accounting regulations concerning corporate groups in France during the 1930s and the Occupation (1940 - 1944). A review of bills proposing accounting regulation shows that no significant progress was to be achieved. Furthermore, while some lawyers called for a comprehensive regulation of corporate groups, no such progress was made during the inter-war period. Ultimately it's the Vichy government which introduced the first regulations on accounting subsidiaries in the French Plan Comptable and limited the reciprocal shareholdings in the Act of March 4, 1943.
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Bibliographic InfoPaper provided by HAL in its series Post-Print with number halshs-00640504.
Date of creation: 12 Sep 2011
Date of revision:
Publication status: Published - Presented, Accounting History Review Conference, 2011, Cardiff, United Kingdom
Handle: RePEc:hal:journl:halshs-00640504
Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00640504/en/
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Web page: http://hal.archives-ouvertes.fr/
Related researchKeywords: Accounting history; corporate groups; accounting regulation; inter war period; Occupation period; France;
This paper has been announced in the following NEP Reports:
- NEP-ACC-2011-11-28 (Accounting & Auditing)
- NEP-ALL-2011-11-28 (All new papers)
- NEP-HIS-2011-11-28 (Business, Economic & Financial History)
- NEP-HME-2011-11-28 (Heterodox Microeconomics)
- NEP-HPE-2011-11-28 (History & Philosophy of Economics)
- NEP-REG-2011-11-28 (Regulation)
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text:
total zoomSome digital camera manufactures advertise a camera's zoom capability as a total zoom. When you see a total zoom listing, it is the digital zoom multiplied by the optical zoom. For instance, a camera touting a 20x total zoom could be a digital camera with 4x optical and 5x digital zoom.
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text:
Publix Super Market's push for a portion of the grocery store shopping dollar has taken another leap with the store announcing Tuesday that it will post manufacturers' coupons on its Web site.
The coupons are free and will be powered by Coupons.com. You'll also find Publix's weekly buy one, get one free offers and a listing of the Publix brand products.
Kroger has long had manufacturer coupons on its site, but recently severed ties with Procter & Gamble's online coupon offerings since the manufacturer insisted that shoppers who clicked on its link from the Kroger page would be redirected to P&G. However, Kroger wanted to keep shoppers on its own site rather than re-directing them.
Kroger continues to have digital coupons from AOL's Shortcuts and Cellfire and shoppers can download coupons onto their Kroger customer loyalty card. Like Publix, the Kroger shoppers go to a page branded by the grocer but with coupons from Coupons.com.
Does having coupons on the grocery store site help you save? Does it improve your grocery shopping efficiency?
Follow me on Twitter @atlbargains or on Facebook at AJC Atlanta Bargain Hunter
March 16th, 2010
11:46 pm
Having coupons sure does help save money. But again, this depends on the site. For instance, sites like Retailmenot and Onewayshopping.com are better at coupons and comparison shopping.
March 17th, 2010
12:22 am
I am assuming that stores are more welcoming to home-printed internet coupons now, right? For a long time, many stores would give you the evil eye if you tried to present a coupon printed on printer paper at home…it's like they though you had been photocopying it. I know I had this problem with a Publix previously, so I am hoping they "get it" now.
March 17th, 2010
9:04 am
The other day I had a Publix coupon printed from their website and the cashier had to shut down the line to go get permission to use the coupon. She said they had just had a big meeting on not excepting home printed coupons. They need to get the bugs worked out.
March 17th, 2010
9:46 am
A general question about Publix and Kroger: What are their respective policies on doubling coupons? I know this used to be a standard promotion, but I'm not sure if they still do this as an everyday policy? Does anyone know one way or the other?
March 17th, 2010
12:18 pm
Publix doubles coupons up to and including $0.50 everyday.
March 17th, 2010
12:23 pm
Publix only doubles in certain markets. They do not in Florida. They do in Atlanta.
March 17th, 2010
1:37 pm
Thanks Bball189 and Florida.
March 22nd, 2010
11:11 am
They'll get it figured out. Publix folks are sharp.
March 22nd, 2010
11:13 am
Internet coupons (printed at home) will always be photocopy-able. Doing so will break the "rules" but I figure whoever puts coupons up there will own-up to the risk of over-redemption. It's just part of the deal. When marketers surrender distribution (printing) control, they also surrender the ability to limit their coupon redemtion liability.


text:
Surprise, AZ (Sports Network) - Bryan LaHair went 2-for-3 with an RBI and a run scored as the Chicago Cubs defeated the Kansas City Royals, 6-4, on Wednesday.
Jeff Samardzija struck out three and allowed just one hit in three innings for the Cubs, who also got two hits from Reed Johnson and Starlin Castro.
Jonathan Sanchez allowed four runs -- three earned -- on four hits in one inning of work for Kansas City.
Max Ramirez had a two-run single for the Royals.
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text:
hey i downloaded a movie and it has like 19 files becuz i dl it at bittorent and cuz its 4.4gb i couldnt dl it at 1 time so i got all kinds of files , anyway the problem is the most files are vob , but also some are ifo and bup , does anyone know how to convert those files into avi? im not so good at this so if anyone has an easy program with guiding, i would rly apriciate it , ty
ps: if any dutchies are here pls help me , cuz in dutch it would be alot easier ty ^^
hey i dled that program , but it needs a registry code , for the free trial i dun have it , does anyone know it?
i am having trouble with exactly these files
i have copied these files from dvd
and when i try to view on window media player or power dvd it doesn't work
help is needed
aoa dvd ripper
from my personal experience, AoA DVD Ripper is the best. It's good and easy to use.
I thing there is nothing better than virtualDUB does it all for you, browse for a dvd folder and under VIDEO_TS open the bigger sized .VOB then save as, choose whatever u wanna convert it to, and the codec u wanna use to convert, let it go and comes out perfect, cant be easy than that, BTW VirtualDub is a free software :)
you have downloaded a full dvd by the sounds of it in dvd format vob ts- (ect) you can burn them files with dvd shrink (free)DL straight onto disc (dvd)
HI, I've got this movie with files in vob, ifo and bup format and i have this dvd decrypter program. I know nothing about this stuff and all I want to do is to be able to watch the movie on the computer. Any help would be much appreciated
I downloaded VirtualDUB but can't figure out how to convert .bup, .ifo and .vob files to .avi. Do they have to be done in a batch? or one at a time? Any help will be much appreciated.
I got all kinds of files , anyway the problem is the most files are .dat, .avi, .wma, and MPEG does anyone know how to convert those files into vob but also some are ifo and bup ? im not so good at this so if anyone has an easy program with guiding, i would rly apriciate it , ty
Hi, I have this camcorder that can record onto a small DVD inside of it. But when I put the DVD into the computer, I can't edit it (like in windows media movie maker). All the files are IFO, BUP, and VOB. How do I convert them into AVI without buying any software? Thanks in advance.


text:
Crushworthy tech, science, and culture
Tokyo's own caped crusader, Mangetsu-man, wants citizens to join him in his quest to save the city from litter and garbage.Articleby Bonnie Burton
We don't have X-wing fighters just yet, but we may soon have their laser weapons. DARPA is working on a system that's downright Lucasian.Articleby Eric Mack
Shoes that look like a classic car? Georgia Tech industrial design students fashion a pair of high-tech shoes for their peer, Miss Georgia, inspired by the school's Ford mascot.Articleby Leslie Katz
MIT improves its robo-cheetah by giving it the ability to bound and run around outside while untethered.Articleby Amanda Kooser
Today's throwback episode comes complements of our very own Steve "Sphere" Guttenberg. He requested this to be replayed, and since we lost a bet with him a long time ago, we owe it to him.Articleby Jeff Bakalar
When you're out at your next Bon Iver or Arcade Fire concert, you can totally fine-tune your hip, ratty beard with this sweet comb made from a retro hipster material.Articleby Anthony Domanico
If you miss the weird citrus-ey flavor and carb overload of Surge soda from the 1990s, you can now buy a fresh batch only through Amazon.Articleby Amanda Kooser
Be the first among your friends to sport a smartwatch that looks like something Apple CEO Tim Cook would wear.Articleby Amanda Kooser
ColorWare, a company that custom-colorizes computers, goes back in time by outfitting a MacBook Air with a retro look to evoke '80s Apple.Articleby Amanda Kooser
Classic VHS tape logos inspire artists at 5BORO NYC to design skateboard decks worthy of our retro memories.Articleby Bonnie Burton
Awkward stares, random coughs, nervous laughing and scary Wookiee roars dominate the Throne Room awards ceremony when the soaring music soundtrack by John Williams is removed from "Star Wars."Articleby Bonnie Burton
Dragons and wizards beware of the hungry gamer! Celebrate a d20 critical hit by making mini dice cakes with this pan available exclusively from ThinkGeek.Articleby Bonnie Burton


text:
CEOAS Strategic Plan, 2013-2018
Contact Us / Map-How to Get Here
The recent integration of the College of Oceanic and Atmospheric Sciences and the Department of Geosciences has created a new College of Earth, Ocean, and Atmospheric Sciences, a new research and educational enterprise organized around the interdisciplinary sciences of the Earth, ocean, and atmosphere. It spans the natural science disciplines and creates strong linkages with the social sciences both within the new college as well as around the university. The new college prepares students and enables faculty to seek out new ideas and innovative approaches to the complex issues of planetary-scale science. It brings an entrepreneurial and collaborative spirit to its endeavors, willing to take risks and to create new partnerships. With its focus on innovation and exploration, the new college builds upon a strong tradition of analytical and computational technology. Advanced information technology is especially important, allowing faculty and students to create and integrate new observing systems and numerical models, pursue real-time and mobile applications, collaborate locally and globally, and ultimately build new approaches to research, teaching, and publishing.
The College of Earth, Ocean, and Atmospheric Sciences is internationally recognized as a leader in the study of the Earth as an integrated system. It operates numerous state-of-the art laboratories and two oceanographic research vessels, the 177-foot oceangoing Oceanus and Elakha, a 54-foot coastal research vessel. The College has an annual budget of more than $50 million, with much of the research support coming from the National Science Foundation, National Oceanic and Atmospheric Administration, National Aeronautics and Space Administration and other federal agencies. It has over 100 faculty, 200 graduate students and 600 undergraduate students. Graduate programs include a Master's degree in Marine Resource Management, and Master's and PhD degrees in Ocean, Earth and Atmospheric Sciences; Geology; and Geography. The new undergraduate program in Earth Sciences, together with the Environmental Sciences Undergraduate Program, provide educational and research opportunities for the best undergraduate students: a national honors college for the Earth.


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The monster truck phenomenon began sometime in the 70s when modified pickup trucks were becoming the rage and rampant testosterone was causing men to fight the "Who's bigger" battle. It wasn't until about 1981 that these same trucks were used to crush the smaller, weaker vehicles, and the culture took off from there. Now, monster truck events are everywhere and the battle for the bigger, badder truck still rages on.
In order to reign supreme in an event that has about as much drama as a pro-wrestling smackdown, owners of these massive modified trucks have to pay to play. A full monster truck build can run up to $250,000 with about $150,000 per year for spare parts. Since these 12,000lb trucks make a name for themselves by smashing the competition, an additional $250,000 is needed per year for repairs and maintenance.
Cost isn't the only issue either. A full eight man crew spends 18-20 hours spanned out in three days constructing the track for the trucks to race on. Then the weaker vehicles, such as cars, vans, buses, ambulances, and even airplanes, are hunted down to serve as prey for the massive trucks. About 3,000 vehicles per year are found in local junkyards and returned after each event.
With such painstaking lengths taken to ensure a successful and entertaining experience, it's no wonder that Monster Truck Jams run rampant in so parts of the country.
Check out the rest of the infographic to get a more detailed breakdown of a Monster truck's numbers and remember to check back with us for the next installment in our Car Infographics series.


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Josh Brolin
Josh Brolin and Diane Lane reportedly split a few months ago and are heading toward divorce. Reps for the star couple confirmed the news, telling "Extra," "Diane Lane and Josh Brolin have decided to end their marriage."
Actor Josh Brolin was arrested just before midnight on January 1 in for public intoxication in Santa Monica, reports TMZ.
Actor Ted Danson wants to help clean up the oceans!
The "CSI" and "Bored to Death" star hosted Oceana's fourth annual SeaChange Summer Party on Saturday, with special guests Diane Lane and Josh Brolin -- and "Extra" was there, too!
"The risk is that we could squeeze the life out of the ocean... no more fish," explained Danson.
To find out more information and ways to contribute, visit the official OceanaSeaChange website!
"Extra's" Renee Bargh sat down with Josh Brolin, who stars in "True Grit," to talk about the film and find out what other flicks Brolin has in the works.
When asked if rumors were true about a possible remake of Brolin's 1980's classic "The Goonies," the actor had a sarcastic response.
"Secretariat" star Diane Lane showed up at the film's L.A. premiere with the whole family, including hubby Josh Brolin and their kids.
I'm gonna go join them and give them a hug," she told "Extra" on the red carpet. "They're here to support me and that means the world to me."
Actress Diane Lane is getting Oscar buzz for her performance in the upcoming horse flick "Secretariat."
Lane plays Penny Chenery, the housewife who owned and guided the famous horse to an improbable Triple Crown win in 1973. "Extra's" Jerry Penacoli sat down with the actress to talk about the role.
Michael Douglas' Oscar-winning character Gordon Gekko is back in "Wall Street: Money Never Sleeps" -- but here are a few things you might not know about the other men on the "Street."
1. Star Shia LaBeouf met his real-life girlfriend Carey Mulligan, who plays his fiancée in the film, on set, but Douglas tried to warn LaBeouf about on-set romances.


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LOL dun be shy cuutie pahtootiee ;)
So just now I went out to get some bbt with the guy on my first post. We started things normal, and it was a bit wierd cuz he acted more happy then i remmeber him to be. like he was even making jokes and stuff . HE NEVER MAKES JOKES. We were laughing like old times. But when he was driving me back home.. i asked him what i yelled at him on the phone about on the day of prom?, but all he said was that it was a long time ago and he couldnt remember. wthh if u waited 1 month to ask me to hang out again , then why are you so afraid to tell me what happened. like seriously, newsflash i think you saw this coming. you can tell me anything you want indirectly but you cant face me in person? wow. just wow. maybe i just made the situation worst. :(
im sorry.
To look back on the past, I can put a smile on my face, thinking about all the good times and all the friends thats always been there for me, definitely gets me through each and everyday.
I wish i could just lay on the grass all day and free myself from all problems.
Awww thankkss mysterious strangerr 8) ! that made my dayy lol
Its funny how only two months ago my stomach would do all these kinds of crazy flips when you signed on and now….I don't care
Its times like these when I wanna take my time to capture moments like these.
Sooo another dayyy .. I just found out i had a test tmmr ! omfg wish me luckk.. anywayss remember my first post? the guy i was talking about. SO i tried msging him yesterday (forgot what i was gnna ask him) but yeaahh i was totallyy over him but i said hbd to him today and ommgg he might come to my birthday !!! SHOCK SHOCKKSSS ! but dosent matter if he comes or not cuz im ovverrr himm and UGHHHH but I sorta like this other guy hmm still not sure thooooo EFF MY LIFEEE ! i just wanna slapp ma sellff in the face a couple timesss. grrr life is soo complicateddd. I like this picture above, i wish a guy did that to mee haha jk or pulled the spiderman moveee! thats cuutee LOL but when will that ever happen ! i tell yah NEVER ! HAH 1 in a million , stupid frkkenn hannah montana! EWW BARRF I said her name !! now i have to scrape my tounge . sorry im wierd. lol. thats all. ;)
Soo I had a test yesterday and I got up hmm average time but my car didn't start up ! So I ran to the bus stopp and luckily my dad saw me waiting and picked me up and drove me to school :) but we almost got in a car accident cuz yennoe my dads asian and the other guy is asian driver soo BAMM bad mix :S
And thennn I had to take bus bak home and there was this reaally reaally smelly guy standing in front of me .. OMFG BARRFF !!! Then I almsot fell on him. Also! I think ppl thot it was me that stinked .. Sighh
Later on in the dayyy I lost my frends graphing calculatorrr omfgg I was soooo scared .
Talk about bad luckk ehh?
But the next day was better , my friend in my class foundd the calculator in his bagg *mysterious look* TEEHEE.
OMFG i want a kitty as cute as this onee 8)
The girl who seemed unbreakable- broke.
The girl who seemed so strong-crumbled.
The girl who always laughed-speechless.
and the girl who would never stop trying- Finally gave up.
" I'm the girl, the one ,that's always lost. The one with the awkward smile and the girl who seems to be so strong, but everyday continues to break. The girl who's always there and seems to have no problems of her own. the one who holds back tears until she's off the phone. The girl who always likes the guy that doesn't care "
I hate guys and their stupid games. So I liked this guy for hmm i would say a good year or so. we got in a fight at prom.. (but unfortunately i dont even have the slightest clue *a.k.a dont remember*of what i yelled at him about… actually i do remmeber saying I HATE YOU at some point of the convo. I waited 2 weeks to tell him im sorry and confessed. But maybe he took it as a joke. who knows. you can never noe what a guy is thinking UGHHH ! OH haha it gets better. He decided to ignore me for 1 month and out of the blue apologizes. Right when i got over him. laaamee sauceee. im trying so hard to forget about him but seeing him pop up on my msn whenever he signs on isnt helping at all. geeez maybe i am just a stupid girl who falls heads over heels too easily. i dont even noe what im suppose to do now. siiighhhhhh i wish i could just rewind time to the better days .. thats fo shoo..well i decided one thing. I aint gonna interfere with his lifee and move on. Again, im a stupid girl for venting out on tumblr :(
"You missed what you could've had ..a girl who would've given up anything to be your everything"
soo.. firstly I wanna thank my fwend for introing me to tumblr <3 !


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GreatSchools Rating
Teacher quality
Principal leadership
Parent involvement
My fondest memories of childhood come from attending Washington Elementary. The teachers were wonderful caring individuals. I count one of them, a Mrs. Bossman, who taught sixth grade many years ago, as one of the teachers who influenced my decision to become a teacher.
Washington is a good school. It offers a helpful staff and a diverse student body. I am so glad we sent our son here. His first year experience was fantastic. It is a smaller school so the staff know most of the students by name. The staff is very flexible in accommodating the cultural and religious choices parents make for their children. It is also great that my child gets to attend a school with deaf children. The staff teaches and uses sign language throughout the day with ALL students. We are thrilled that our son is able to learn a third language because of the school's diversity. As this is our first year, we have little experience with the PTO. So far it seems good. They have pulled together many activities, both during and after school. It appears that many of the parents participate and get involved.
Washington provides many things - excellent teachers, many of whom have master's degrees and have been awarded the Buffet Foundation Award for teaching excellence, wonderful music and art education, and a caring diverse community of students and families. Washington is also the magnet school in the Omaha Public School District for Hearing Impaired students, and hearing-impaired students participate fully in all activities, with interpreters in nearly every class. By sixth grade, many of the students are fluent in sign language, and the lessons learned about acceptance and confidence are wonderful for all kids. Parent involvement in the school is very strong - and strongly encouraged, with many volunteering time frequently in the classroom. Our kids have had opportunities and experiences that have thrilled and enriched them. A friend who is a substitute teacher mentioned the wonderful open, accepting community at the school, and she is absolutely right. It's a great school.
My adopted daughter attended 1-6th grade and received an excellent education. The teachers were wonderful and encouraged her even as she left to go to Middle School. It is a wonderful learning environment.
Community ratings and reviews do not represent the views of GreatSchools nor does GreatSchools check their accuracy or verify the reviewers' identities. Use your discretion when evaluating these reviews.
The Community Rating is the school's average rating from its community members (e.g., parents, students, and school staff). The highest possible rating is five stars; the lowest is one star.
5519 Mayberry St
Omaha, NE 68106
Phone: (402) 554-8690
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Narrow your search
For fans of Ceiva's PicturePlan service, the company's fourth-generation 8-inch digital photo frame represents a nice upgrade. But with new, more user-friendly frames hitting the market, Ceiva's subscription-based service may be a harder sell to new customers.
Pricing not available
The Ceiva 8-Inch Digital Photo Frame represents a nice upgrade for fans of Ceiva's PicturePlan service, but it may be a harder sell to new customers.
Digital photo frames can be customized--for a charge.
Whirlpool's wired refrigerators will get its digital photo frames.
Ceiva has a new line of sleeker digital photo frames
And, equally important, are there any good frames left to buy?
The company is reportedly working on a digital frame that resembles the old instant photo.
Webcam is built into this portable picture frame.
It's screen is small, but it compensates with other functions
The Ceivalife digital photo frame and its complementary service push past simple picture viewing into the realm of Internet appliances--for better or worse.
Pricing not available


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Handy tutorials for DebianMonday, March 12, 2012
Nüb simple.
|"Every soldier that has died or fought under the American flag since World War II has done it because of the immoral and wrong-headed policies of our presidents and government leaders, backed by the ignorant and phony patriotism of the masses…those same masses that still believe even to this day that each one of our war dead gave up their lives for our freedom." source
|Multimedia on Debian Etch
|Install nVIDIA 3d driver on Debian Etch
|Wireless on Debian Etch: Broadcom - bcm43xx
|Simple local web server on Etch
|Web Server on Debian Etch
|Debian GNU/Linux (Etch) Installation Tutorial
|My Etch Desktop in 150 words or Less
|Upgrade Sarge to Etch
|Handy Things
|ipod on Debian GNU/Linux
|Convert Digital camera mov Files
|Package Management
|Some Debian Etch System Files
|My Debian Desktop
|Reset root password
|Using wget
|Manage Partitions
|Linux Conventions
|Debian Linux file and print server: NFS, CUPS, LPR
|Printing in Debian
|Stream your music with gnump3d
|Klikit, Klikit good
|Convert mov files
debiantutorials.org site map
Debian GNU/Linux - Etch
Debian GNU/Linux - Lenny
Other Menu


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Apollon Hotel Apartments
In Platanes of Rethymno, one of the most beautiful areas of Crete a quiet and hospitable place was created for you and your family.
Apollon Apartments are waiting for you all. Traditional villages surround them and they are within walk-distance of 10 min from the sandy beach of Platanes. You can choose among the 62 spacious and furnished apartments and studios, which can host from 2 up to 4 people. Each apartment has a spacious balcony with view, which can be the cliffs covered by olive trees, the villages, the swimming pool or the sea.
Our recently redecorated apartments offer you a friendly, pleasant and hospitable environment with excellent and modern facilities, which are a fully equipped kitchenette with fridge, phone, radio, safety box and air-conditioning.
We also provide reception, Mini Market, Pool Bar, a large outdoor swimming pool of sweet water and a children's pool for our young visitors. What is more by staying in Apollon Apartments you will have the chance to meet the tradition and culture of our island.
Disponibilidad y preciosPara ver la disponibilidad y los precios, selecciona las fechas y pincha "Actualizar fechas"
Instalaciones & Políticas de Hotel
- Aire acondicionado
- Bar
- Desayuno no incluido
- Cafetería
- Tipo de cambio
- Aparcamiento gratuito
- Secadores de pelo
- Acceso a Internet
- Guardaequipajes
- Piscina al aire libre
- Aparcamiento
- Caja fuerte
- Piscina
- Cafetera/tetera


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About Us
Dorothy Moore opened the Dining Dog so you and your dog can have a unique dining experience. The Dining Dog has a full service menu including Doggie Cocktails, Appetizers, Entrees and Desserts. We have Birthday cakes and Cupcake trays for the Birthday Dog by special order. If your dog doesn't feel like going out, take out is available. The Dining Dog caters a lot of events and private parties and has done so here in Washington state and in L.A. E-Mail or call for reservations. We look forward to seeing you & your dog!!


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Company Name INFOSYS
Website: www.infosys.com
Education: Candidates who want to apply against Infosys Recruitment for 2013 pass outs should be Graduate / Post Graduate [BE / B.TECH / M. Tech / MCA] in relevant field with minimum 60% marks throughout in their academics from a recognized university / colleges.
Position(Role):Systems Engineer / Senior Systems Engineer / SAP Consultant.
Experience:Freshers and experienced candidates can apply.
Location: Bangalore, Bhubaneswar, Chandigarh, Chennai, Gurgaon, Hyderabad, Jaipur, Mumbai, Mysore, Mangalore, Pune, Thiruvananthapuram etc.
Job Description:
INFOSYS Recruitment 2013 - Jobs For Freshers, Career 2013
Be an integral part of Business Transformation Journey with Infosys Limited.
Explore a whole new world of opportunities. Combine that with a touch of the cutting-edge, and get set to take on the world.
INFOSYS Recruitment 2013: Infosys Limited which is one of the top IT Company is recruiting freshers as well as experienced candidates for Systems Engineer – Trainee / Senior Systems Engineer / SAP Consultant Candidates who have completed their Graduation / Post Graduation in relevant discipline can apply. Eligible and interested candidates can apply immediately.
SAP Careers in Infosys: At Infosys, our SAP specialist work with the objective of helping clients realize measurable business value from their investments, thus keeping client businesses relevant and future-proof.
We enable clients to significantly enhance the value they realize from their transformation and optimization programs through a portfolio of services – ranging from consulting, implementation, and upgrades to support and maintenance. We offer innovative solutions to clients across industries and geographies, together with innovative pricing and delivery models.
INFOSYS Career 2013:
Infosys Selection process: Candidates will be selected for the above positions on the basis of performance in the Personal Interview. Selection of the candidates will be done on basis of internal recruitment process.
How to apply: Willing Candidates should send their resume to firstname.lastname@example.com mentioning the job title for which he / she is applying along with the experience and city name, those who have less than one year of experience can apply as a Trainee.
For more info@07381963145
Infosys values diversity and inclusion, and is committed to the principles of equal employment opportunity.
About Company : INFOSYS
Company Address : www.infosys.com
Apply to Here:


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"Commemoration" web sites
44 online resources. This is page 4 of 5.
- Armistice around the world
- A BBC News film-clip (Nov 2008).
- BBC SPORT | Football | Leyton Orient | Day to remember for Orient fans
- A news item from the BBC Football website (15 July 2008) that follows Leyton Orient fans on a trip to commemorate their team from 1914-1915 and their service in the armed forces during the First World War.
- Ceremonies mark Remembrance Day
- A BBC News film-clip (Nov 2008).
- First World War 90th Anniversary
- A website from the Imperial War Museum, providing information and links to the Museum's collection, online exhibitions, and events to commemorate the 90th anniversary of The Armistice.
- Hearts Great War Memorial : honouring the 15th and 16th Royal Scots
- A website commemorating the loss of soldiers from Scottish regiments during the Battle of the Somme including many of the Heart of Midlothian footballers who had volunteered in 1914.
- How we remember them: the 1914-18 war today
- OpenDemocracy.com (Nov 2008): 'The ninetieth anniversary of the end of the first world war is being commemorated in Britain in ways that close as well as open routes to a genuine exploration of the national past, says Dan Todman.'
- In Memoriam
- Web pages to accompany an exhibition at the Imperial War Museum to commemorate the anniversary of The Armistice.
- In memory of : German Jewish Soldiers : Die Judischen Gefallenen
- An online Roll of Honour commemorating the 12,000 Jewish servicemen killed in action in the German army, German navy and German colonial forces 1914-1918.
- Remembrance at Royal Albert Hall
- A BBC News film-clip (Nov 2008).
- Remembrance campaign
- The Royal British Legion's Remembrance campaign includes 'My Remembrance Day' where you can create a permanent tribute to a loved one, online and in the National Memorial Arboretum.
These resource summaries © The Intute Consortium.


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Truett Cathy
Revolving Door (0)
Sightings (1)
Twitter Makes Debut Appearance at NPC Luncheon - Posted December 22, 2009
Twitter's got power. This morning C-SPAN 3 aired last month's National Press Club (NPC) luncheon with Chick-fil-A-Founder and Chairman Truett Cathy and Chick-fil-A President and CEO Dan Cathy. The Cathy's spoke of the continued success of their chicken business when suddenly Twitter showed up. NPC fielded its first questio... [FishbowlDC]


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Marijuana Blog
Time to Medicate
Category: Medical Marijuana | Posted on Thu, January, 10th 2013 by THCFinder
Beautiful Glass Bong
Category: Glass | Posted on Thu, January, 10th 2013 by THCFinder
Sweet Dream and Platinum Dream buds
Category: Nugs | Posted on Wed, January, 9th 2013 by THCFinder
Hempcon is on the way!
Category: Events | Posted on Wed, January, 9th 2013 by THCFinder
THCFinder is an Official Sponsor of Hempcon so you better make it out to our booth and come say hi! We will be giving out stickers, shirts, Jars and some other sweet prizes to the awesome people who come by to say HIGH ;)
California's Largest Medical Marijuana Cannabis Convention !
The Medical Marijuana Industry Comes Together February 8-10,2013
In San Bernardino's NOS Event Center To Advertise,Educate,Brand,Market,Network
And Sell Their Products And Services To Thousand's Of Pro-Positive 420 Compassionate Consumers In A Well Organized,Safe And Comfortable Environment !
100's Of Medical Marijuana Cannabis Related Company's From All Over The United States,Canada & U.K, Will Be Present, From Seed To Smoke!
This Massive " Ultimate Green Utopia Show" Is open To the General Public
No Medical Card Needed To Enter ( 18 y.o.a And $20.00 At The Gate ! )
From On Site Medical Marijuana Evaluations To The Latest Vaporizers ,To The Top Shelf
Strains !
It's All Here At Hempcon !
Check out Hempcon.com for more info!
Marijuana Mac n Cheese
Category: Recipes | Posted on Wed, January, 9th 2013 by THCFinder
This Macaroni and Cheese is a simple dish in flavours, but really packs a punch. There is a large amount cannabutter in this dish, so marijuana content is high. For those who like to throw caution to the wind, use cannabutter in the topping. Proceed with caution or this baked marijuana macaroni and cheese may just bake you.
1/2 pound elbow macaroni
3 tablespoons Cannabutter
3 tablespoons flour
1 tablespoon powdered mustard
3 cups milk
1/2 cup yellow onion, finely diced
1 bay leaf
1/2 teaspoon paprika
1 large egg
12 ounces sharp cheddar, shredded
1 teaspoon kosher salt
Fresh black pepper
3 tablespoons butter
1 cup bread crumbs
Preheat oven to 350 degrees F.
In a large pot of boiling, salted water cook the pasta to al dente.
While the pasta is cooking, in a separate pot, melt the butter. Whisk in the flour and mustard and keep it moving for about five minutes. Make sure it's free of lumps. Stir in the milk, onion, bay leaf, and paprika. Simmer for ten minutes and remove the bay leaf.
Temper in the egg. Stir in 3/4 of the cheese. Season with salt and pepper. Fold the macaroni into the mix and pour into a 2-quart casserole dish. Top with remaining cheese.
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A Bill Maher presale code is now available: During this limited time presale period you have got a tremendous opportunity to buy show tickets before the general public. This just might be your only opportunity ever to see Bill Maher live in Little Rock, AR.
Here is what we know about the Bill Maher show:
Bill Maher
Robinson Center Music Hall
Little Rock, AR
Sat, Sep 14, 2013 08:00 PM
Onsale to General Public
Start: Fri, 06/28/13 10:00 AM CDT
Bill Maher Pre-sale
Start: Mon, 06/24/13 10:00 AM CDT
End: Thu, 06/27/13 11:45 PM CDT
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Amazon Fashion Debuts First TV Commercial
Amazon Fashion debuts its first TV commercial Monday, joining the growing ranks of startup e-commerce businesses (Fab.com, Warby Parker, One Kings Lane) to turn to TV to bring in new customers. The 30-second spot can be viewed on Amazon.com. Amazon, of course, is no startup -- but its Fashion division is a fledgling business of sorts.


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Here come the 2014 college graduates, flooding the highly competitive job market over the next several weeks and bringing their workplace expectations.
University of Florida graduate Stephanie Savage is one of the 11 percent nationwide who has successfully landed a full-time job. Yet, she notices an interesting trend with some of her friends who still are searching: "They're picky."
With their notably high debt from student loans, you would think new college graduates would jump at any job they could get. Instead, some of this year's crop are selective in their job searches, reluctant to be stuck in a cramped cubicle from 9-to-5 each day and looking to be wowed by the jobs they land, career experts say.
"The idea of not being in a job they love is stressful for them," says Christian Garcia, executive director of the Toppel Career Center at the University of Miami. Garcia said he has had students shy away from jobs in which they've heard the boss is difficult, the hours or commute long or the job description "boring."
"They want to feel each opportunity is THE opportunity. Some can afford to be picky, but there are a lot of students who can't. I bring them a reality check."
Savage, 21, who will work as a preschool teacher, sees the same thought process in her peers. "They realize the job market is horrible but they still say, 'I don't know if I want to work for someone like that' or 'I don't like the job requirements.' "
The pickiness is perplexing considering this is the sixth consecutive graduating class to enter the labor market during a period of profound weakness. However, the Class of 2014 is uniquely optimistic and expects to find positions in their chosen fields, according to an employment survey released this month by consulting firm Accenture. These graduates also are determined to find work/life balance in their jobs — or come up with ways to obtain it.
In fact, for the past few years, work/life balance has been the number one career goal among students in the global surveys by Universum, which offers research and services worldwide to help employers attract talent. More than leadership opportunities, security or prestige, these college graduates seek balance. They want their jobs to reflect who they want to be and the lifestyle they want to live, one that might include training for a 5K or giving back to the community.
Fortunately for the 2014 grads, they are the first generation that can easily expect to find a telecommuting or remote job in their fields, according to FlexJobs.com, a website designed to help people find flexible work options. Sara Sutton Fell, CEO of FlexJobs, said almost every flexible position on her website has entry position levels — and college graduates are applying for them. Many pay salaries equal to onsite positions.
"Telecommuting options are a natural fit," Fell says. "The younger generation is mobile by nature. They've grown up with technology and without having to do location-specific tasks."
In compiling the best remote jobs for college grads, FlexJobs says some of the jobs to consider are accountant or bookkeeper, online teacher, market research analyst, computer systems analyst, business consulting, data entry positions and customer service posts. "With flexible work, we're seeing a real broadening of types of opportunities available at all levels," Fell says.
Across the board, new graduates are fielding more job opportunities than last year or even last fall, college career counselors said. Some are taking jobs as independent contractors, trying to turn internships into paid positions, crowd sourcing for their startups and signing on to project work. Many are asking boldly in job interviews about work/life balance and favoring employers who paint an attractive, values-driven picture, Universum's research shows.
This creates potential for small businesses to snap up talented graduates, many with strong skills in technology and teamwork, says Mason Gates, director of business development at CSO Research. "Instead of fitting employees in boxes, smaller companies are opening themselves up to be flexible or virtual. They might get the best young employees if they are open-minded."
Gates, who works with universities' career centers, says that for new graduates, taking on debt to get the job scenario they seek doesn't scare them. "Their attitude is, 'I will borrow more to start a company if I want to.' They have a different view of their high level of debt. They can't even grasp it."
These 2014 graduates, members of the 80 million Generation Y, are projected eventually to set the tone in workplaces. Garcia believes employers will soon meet young workers halfway, giving them more of the flexibility and work/life balance they seek, and rewarding those who work smart from whereever they are situated.
Those employers who don't could be in for high turnover. Alec Levenson, a research scientist at the Center for Effective Organizations at the USC Marshall School of Business, says employers are going to find that these young workers disengage when they experience work/life imbalance. Just like they're doing with their job searches, Levenson believes there will always be some millennials who will go for the brass ring. Others will say, "I don't need that" and look elsewhere.
Columnist Cindy Krischer Goodman is CEO of BalanceGal, a provider of news on work life issues. Connect with her at email@example.com or visit balancegal.com.


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Tribune de Markus Milsted, CEO of global mobile payment solutions provider Omlis
The Apple brand is synonymous with technology that is modern, elegant and revolutionary, so it's no surprise that they have announced a move that is setting the brand up to dominate the emerging mobile payments market in Q3 of 2014. According to Appleinsider, KGI Securities Analyst Ming-Chi Kuo predicts the release of new IPad Airs, IPad Minis, a new 4.7 inch phone and the new iWatch. The game changers are the anticipated addition of NFC capabilities in the iWatch and iPhone devices as well as a potential partnership with VISA.
According to the Wall Street Journal, Apple are seriously considering options to allow existing users to make payments using iOS mobile devices linked to existing iTunes Subscriptions. The current Apple user experience allows shoppers to make payments in Apple stores by scanning barcodes that are authenticated and charged to their iTunes subscription, but Apple's ambition to expand its offering to shoppers extends beyond their stores to third party retailers and service providers which a potential partnership with VISA could see the Apple brand ascend to new heights.
BI Intelligence identified one of "Apple's most quietly powerful advantages" as their 600 million subscriber accounts on file, with most of these accounts having live credit card details. The fact that most Apple subscribers would have opened their subscription with a purchase of an Apple product means that the credit card details stored by Apple are live, setting a platform for simple and quick mobile transactions should Apple offer mobile payments as an option to their customers. Apple's existing customer base and VISA's extensive partner network especially through small businesses sets a platform that spells key challenges for their competitors in the race for mobile payments domination.
Lire la suite "Is Apple set to take a potentially huge bite out of mobile payments market with NFC?" »


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Perhaps you have used some of the new library resources or cleaned up in one of the residence halls' refurbished showers.
Or maybe you are one of the many students on campus who depends on scholarships to continue their St. Olaf education.
Whatever your circumstances are, your life as a St. Olaf student has probably been affected by Partners in Annual Giving.
Partners is an unrestricted fund that is contributed to primarily by alumni. Parents, faculty, staff and "friends of the college" also donate to the fund every year. Because it is an unrestricted fund, the money raised by Partners can go wherever the college deems it most needed.
This means work that is important but not necessarily glamorous -- like ground maintenance and hall renovations -- is taken care of in a timely fashion. Partners also provides athletic equipment and makes it possible for many students to study abroad. Even the campus critters benefit from the fund -- partners recently bought new cages and racks for lab rats.
To show appreciation for the donations provided by Partners as well as encourage giving, students have the opportunity to participate in the Partners' annual phonathon.
As "Ole Callers," these students have the job of calling alumni, parents and faculty to both update them on the happenings at St. Olaf and to ask them for contributions to the annual fund. There is a calling period both in the fall and in the spring. The fall calling period just finished on Nov.15, and the results were positive.
"This year the Ole Callers raised a little over $747,000 in the fall," said Sarah Cohen, who is the program manager of this year's phonathons. Partners is assisted in the phonathon by RuffaloCody, a company which helps non-profit organizations. "This was above our goal of $725,000 and $100,000 more than the amount raised last year."
This increase can be partly explained by a change in calling periods -- the fall calling period was lengthened and the spring period shortened to make budgeting easier.
The responses of Olaf alumni were not only impressive in terms of monetary amounts, but also in participation. Rankings such as the U.S. News and World Report play a role in many students' decision about which college to attend, and alumni support -- no matter how much or how little is contributed -- plays a role in the rankings.
This year, 29 percent of the pledges were made on credit cards. This helps to reduce the annual $4,500 that is spent on postage and processing for pledge cards.
It's also important that alumni learn the value of contributing to the annual fund from their very first years out of college, and the most recently graduated class showed that they understand the importance of giving back.
"Over 50% of the class of 2007 has pledged to the annual fund; I think that is fantastic!" Cohen said.
Current Oles will have another chance of their own to help Partners in Annual Giving in mid-February, when spring calling begins.


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"[T]he construction of the social Other as cannibal-savage, demon, sorcerer, vampire, or an amalgam of them all, draws upon a consistent repertoire of symbols of inversion. The stories we tell about people out on the periphery play with their savagery, libertine customs, and monstrosity. At the same time, the combined horror and pleasure we derive from contemplating this Otherness—sentiments that influenced the brutality of colonists, missionaries, and armies entering the lands of those Others—certainly affect us at the level of individual fantasy as well."
D Frankfurter, Evil Incarnate: Rumors of Demonic Conspiracy and Satanic Abuse in History. Quoted in Philip Zimbardo, The Lucifer Effect: Understanding How Good People Turn Evil.
I read this book a few years back, but a book club I just joined is planning to read it this month, so I'm re-reading it. It's interesting to discover how much my own thinking has changed in the past five years!(via shiracoffee)
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European trance group, single "Imagination"
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Links & Information
- Last.fm page on Timezone
- Discogs at discogs.com/artist/30706
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