Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EMPIRICAL EVALUATION OF METHODS FOR DE NOVO GENOME ASSEMBLY
Review round: 1
Reviewer: 3

Output:
Basic reporting: This manuscript reports on the state of genome assembly software and performs comparative testing on a number of such packages.  The introduction does a decent job of laying out an overview of the current state of assembly.  This section is followed by a "De novo assembly method" section which really seems to be part of the introduction in that it mostly describes major assembly algorithms in detail, but confusingly also seems to contain results figures.  I can't find a true "Methods" section and this is a significant issue as it prevents me from understanding the Results that are being presented.  Overall, I find this paper lands somewhere in-between a mini-review and a research article (but without a true Methods section) and doesn't live up to either label.

I find it difficult to make specific comments due to the lack of methods and unusual organization of the paper.  I will note that I found the author's choices of organisms to use for testing a bit limited as it included three bacteria, a yeast, and a very small plant genome.  The lack of metazoans or other larger eukaryotic organisms severely limits any ability to truly assess sequencer performance across organisms.
Experimental design: The experimental design is not described in any detail -- No Methods section is included.  A brief mention in the results that default settings were used for each software is neither sufficient -- nor likely wise -- as default settings are not applicable in all circumstances.  There is no indication of the source of data that is being used in the results section: importantly the details of what sequencing platform(s) each comes from, the average quality and depth of the data for each, etc is omitted completely.  The study also seems to employ all assembly software against each dataset with no differentiation of whether a given package is optimized for long or short-read data -- which seems misleading to present results in this way.
Validity of the findings: Validity cannot be assessed as the experimental design is not adequately explained.
Additional comments: None.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EMPIRICAL EVALUATION OF METHODS FOR DE NOVO GENOME ASSEMBLY
Review round: 2
Reviewer: 1

Output:
Basic reporting: The revised article has improved, and I have no further qualms about it.
Experimental design: Methods are well described and appropriate
Validity of the findings: Findings are well supported by the literature and data
Additional comments: I appreciate the revised manuscript.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GETTING NEW ALGORITHMIC RESULTS BY EXTENDING DISTANCE-HEREDITARY GRAPHS VIA SPLIT COMPOSITION
Review round: 1
Reviewer: 1

Output:
Basic reporting: The paper is well written and well presented.
Experimental design: The paper fit in the scope of this journal.
Validity of the findings: The results are interesting and as far as I can tell seem valid to me.
Additional comments: This paper deals with a generalization of distance hereditary graphs (DHG for short) and
some structural properties.

A graph is distance hereditary  if the distance between any two pair of vertices
is the same in the graph and all of its induced subgraph (until deconnection).

Along the years several characterizations of this class were obtains. Two of them
are particularly relevant in the context of this paper, the first one is the existence
of construction scheme. A graph is DHG if it can be obtained from a single vertex
by adding successively, either a pendant vertex, or true or false twin. The other one,
is the fact that DHG are completely decomposable with respect to split decomposition.

In this article, the authors generalizes the class of DHG by considering this two characterizations.
Namely, they put in use the split Composition operation. DHG, can be obtained by using split
composition, using as key elements P_3 and C_3. In their new generalization they add in the
list of key element the cycle on five vertices: C_5. By doing so, it allows to generalizes the
class.

Then they prove a series of structural results of the newly introduced class. They first shot that
the class is an hereditary class. Then they prove that this class also generalize the class of DHG
with respect to the metric aspect; namely they prove that the shortest distance between any two pair of vertices
in the induced subgraphs is at most twice the shortest distance in the original graphs.

Then they prove how to compute the stretch number  for graphs in this class. To do so they exploit the structure
of the split decomposition of the graphs.

Finally they obtain, using a framework developped by M. Rao. The framework allows to solve in polynomial
time a list of optimization problems, by considering the split decomposition. In this
class, since the prime nodes are of constant size. The framework can be successfully applied.
The also prove that the class considered is of bounded cliquewidth.

The paper contains interesting results and concepts.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GETTING NEW ALGORITHMIC RESULTS BY EXTENDING DISTANCE-HEREDITARY GRAPHS VIA SPLIT COMPOSITION
Review round: 1
Reviewer: 2

Output:
Basic reporting: This paper is an extended version of the following TAMC conference paper published in 2011 by one of the authors:

Cicerone, Serafino. "Using split composition to extend distance-hereditary graphs in a generative way." International Conference on Theory and Applications of Models of Computation. Springer, Berlin, Heidelberg, 2011.

Although it is relatively common for computer scientists to publish full papers that extend previously published conference papers, the extended versions are expected to have enough extra material to warrant an additional publication. Also, they are usually published within 1-2 years after the conference.

The introductory part of the paper under consideration leaves an impression that its main contribution is the detailed proofs of the statements from the 2011 paper. Indeed, lines 89-96 list the exact same results as the 2011 paper. The paper claims to introduce a new class of graphs, which certainly is not the case as the class was introduced (in the exact same way) in the 2011 paper.

My main concern though is the motivation. Why is the class Gen(*; P3, C3, C5) worth introducing and studying? The only sentence that addresses this issue is in line 82: "This consideration leads to redefining the main objective". I don't see, however, how the (somewhat natural) hierarchy DH(k) can be redefined using a single new class.

This concern of mine seems to be shared by the community -- the original 2011 paper has not received any citations (according to Google Scholar) in almost ten years since it was published.
Experimental design: This paper does not contain any experiments.
Validity of the findings: I have not checked all proofs very carefully (due to my concerns raised above) but those that I did look correct.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GETTING NEW ALGORITHMIC RESULTS BY EXTENDING DISTANCE-HEREDITARY GRAPHS VIA SPLIT COMPOSITION
Review round: 1
Reviewer: 3

Output:
Basic reporting: The paper seems very well written. I could not find any typo's or language mistakes. The presentation is clear and the references are stated properly. The figures are well done and the structure of the article is professional.
Experimental design: The problem studied by the authors is definitely interesting for the graph theory community. The authors define properly the problem and all the preliminary notions. Also, present a nice survey of related results.
Validity of the findings: The proofs presented in the paper seem correct to the best of my knowledge. However, due to limited review time, my review has low confidente. For such a long theoretical paper a more thorough review is needed.
Additional comments: In the paper "Getting new algorithmic results by extending distance-hereditary graphs via split composition" the authors introduce a new distance hereditary graph class Gen(*;P3;C3;C5) that is obtained by applying the split operation recursively starting from P3, C3 and C5. The authors show that the recognition problem for this new class can be solved in linear time. The recognition problem is: given a graph G, decide whether G belongs to Gen(*;P3;C3;C5). Then, they show some properties about graphs in sDH(2) (the graphs with stretch number less than 2) that are used to provide a linear time algorithm for computing the stretch number in any graph belonging to the class Gen(*;P3;C3;C5). Finally they show how known results can be exploited to solve some other combinatorial problems in the new class.

The paper is an extended version of a paper published in TAMC 2011. I found the paper interesting and I believe that is should be accepted for publication. The results are clearly of interest of the graph theory community. The paper seems well written and the authors put a lot of effort to properly define all the notions used. Moreover, I appreciate that the authors provide some intuition and present the high level approach before digging into details. However, due to the short review time, I was not able to check the proofs in detail.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GETTING NEW ALGORITHMIC RESULTS BY EXTENDING DISTANCE-HEREDITARY GRAPHS VIA SPLIT COMPOSITION
Review round: 1
Reviewer: 4

Output:
Basic reporting: The authors address possible connections between two generalizations of distance-hereditary graphs. One such generalization, rather natural, is the increasing hierarchy of classes DH(k), that contains all graphs whose all induced subgraphs are k-spanners of their vertex-set (w.r.t. the distances in the original graph). The other, more algorithmic, is based on split decomposition.

For that, a superclass of distance-hereditary graphs is defined and studied, based on split decomposition. The full link between the new class and distance-hereditary graphs is partly based on some properties of the latter, which the authors claim to be new.

The authors then prove that every graph in the new class (hereafter called C) is in DH(k) for some k < 2. Let us call sDH(2) the union of all the DH(k) for k < 2. Unfortunately, the authors observe that their approach with split decomposition cannot lead to a nice generation scheme for sDH(2) (in the sense that they are such graphs that are prime for split decomposition and of arbitrary size). However, they did prove that every graph of sDH(2) has some induced subgraph which belongs to the newly defined class C. Furthermore, this induced subgraph, called a core in the paper, is some sort of minimal certificate for the stretch of the graph (the stretch is the least k such that the graph is in DH(k) ).

The main algorithmic result of the paper is a linear-time algorithm for computing the stretch of any graph in C. Finally, the authors observe that due to a very general framework of Rao, several classic combinatorial (NP-hard) problems can be solved in polynomial time on their class C. In particular, all graphs in C have bounded clique-width.
Experimental design: Does not apply.
Validity of the findings: On the negative side, it should be noted that the new results on distance-hereditary graphs that are presented at the beginning of the paper stay very close to previous studies.

The result that every graph in sDH(2) has a ``core'' induced subgraph in the newly defined class C is somehow surprising. The proof is rather tedious, with a lot of intermediate calculations, but I found it very insightful about the internal structure of the graphs in sDH(2).

Regarding the main algorithmic result (computation of the stretch number within C). This result shows the tractability of the stretch number beyond the trivial case of distance-hereditary graphs (for which it equals one). Recall that on general graphs, this problem is NP-hard.The algorithm in itself is simple (dynamic programming on a split decomposition tree), but it requires a very ingenious way to store the output of subproblems. Such techniques might find applications elsewhere, for other resolution techniques based on split decomposition.

Finally, I want to mention that the authors should revise their abstract (and possibly some other parts of the paper) because they did NOT provide an algorithm for computing the clique-width of the graphs in C. They only proved it was bounded.
Additional comments: Overall, I enjoyed the paper and I recommand it for acceptance.

MINOR COMMENTS:

*p18 (14/26), l408, case 2: u1 is repeated twice in the definition of the path

*p22 (18/26), l468: typo: (y,a) instead of (y,b)

*In the legend of Figure 14: "whereas (m2,v′) it is not." => remove ``it''

*p24 (20/26), l502: typo: the the sequences

*The proof of Theorem 9 invokes the result of Theorem 6. However, the latter is only for Gen(*,P3,C3,C5), which is a more restricted case than the one discussed in the statement of Theorem 9.
This is probably just a bad copy/paste: this property is never used in the proof.

*Corollary 5 could be simplified by using (as Rao and others did) a split decomposition where all stars and cliques are further decomposed in C3 and P3.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GETTING NEW ALGORITHMIC RESULTS BY EXTENDING DISTANCE-HEREDITARY GRAPHS VIA SPLIT COMPOSITION
Review round: 2
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: no comment


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: PROVENANCE-AND MACHINE LEARNING-BASED RECOMMENDATION OF PARAMETER VALUES IN SCIENTIFIC WORKFLOWS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The paper has presented a parameter value recommendation method to suggest
values for workflow parameters based on user preferences.
The paper is well written and structured.
Experimental design: Result evaluation is sufficient.
Validity of the findings: It would be better to include a Discussion section, that compares the proposed methodology and results with the existing related studies. This will help to justify the validity and the novelty of the proposed study.
Additional comments: Few typos:
Equation (4) contains another numbering (1)

Name out the complete names of the parameter abbreviations using in the tables, with in the text description. (eg. Table 3, Table 4  - cnty, crval1)

Since the paper addresses a technology enhanced workflow management system, it would be better to consider latest related studies when comparing with the existing work. Since the paper will be published in 2021, better to consider latest related work/ applications (may be 5 years back)
For example, user feedback based rule-based recommendation systems were addressed in following references.
DOI: https://doi.org/10.1145/3018009.3018027
DOI: https://doi.org/10.1109/MERCon.2017.7980467
Some of the technology based workflow system studies in different domains can be found in
DOI= https://doi.org/10.1109/TNB.2018.2837122
DOI https://doi.org/10.3991/ijet.v13i12.8608
DOI: https://doi.org/10.1109/TALE.2018.8615134


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: PROVENANCE-AND MACHINE LEARNING-BASED RECOMMENDATION OF PARAMETER VALUES IN SCIENTIFIC WORKFLOWS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper proposes FReeP: Feature Recommender from Preferences for recommending values for parameters in scientific workflows considering the user's preferences. The paper describes the recommendation strategies behind FReep, putting in context the challenges and burden to tune parameters when designing and running scientific workflows. Beyond the fact that tuning implies a heavy lifting task, it is also a time-consuming task. Moreover, it consumes resources that can lead to economic cost when the workflow is executed on "pay as you go" architectures like the cloud. The problem and challenges addressed are clearly stated by the paper together with a background on scientific workflows. The proposed recommendation approach has been experimentally validated using existing data sets. The focus is given on the precision and recall of the recommended parameters. Yet, the possibly reduced overhead between non-recommendation based tuning and recommendation based is not discussed. The recommendation task is just an automatic test and error process; it will finally find the "right parameters" for the workflow activities (precision and recall). But what about resources consumption? What about explicability and tracking of the choice of parameters? How can these benefits of recommendation be measured? The related work is too short and superficial. What about existing work that addresses parameters tuning for ML algorithms, of course, this is not a recommendation process. Still, the automatic search of "right" parameters behind is related to the addressed recommendation task. This is deceiving. The paper also lacks concrete examples of scientific workflows (e.g., a use case) across the "theory" descriptions, particularly in the experiments section.
Experimental design: The paper experiments are designed to evaluate precision and recall of three recommendation cases for which the work proposes a solution: Discrete Domain, Discrete and Continuous Domain, Generic FReeP Recommendation Evaluation. They are done using provenance data sets and specific machine learning and AI algorithms as a reference that are often used in scientific workflows. The recommendation techniques are assessed concerning precision and recall metrics. The paper describes reasonably the experiment setting and the results. The experiment does not show a concrete scientific workflow that might include provenance data from different activities that might use different algorithms. The parameters of a given algorithm might depend on tunning the parameters of another activity's parameters in the workflow. In this sense, I find the experiments too ideal and too synthetic. What about resource consumption, does recommendation help save resource consumption when a workflow must be executed many times? What about the cost of recommendation in terms of resources? Is it shorter than the repetitive execution of a scientific workflow? This kind of assessment must be done to complete experiments and validate FReeP.
Validity of the findings: There is no doubt about the interest of FReeP for the design and execution of scientific workflows involving tasks that need important tunning. Learning from previous executions using provenance data that are already collected is smart and strategic. The different strategies behind the system correspond to the type of parameters tuning associated with many analytics algorithms. It seems that scientific workflows might use and combine different such algorithms across their tasks; the question is whether tasks are independent or whether the recommendation might change when analysing all the tasks of a workflow. Are the user preferences enough input for dealing with the recommendation? Or do the characteristics of data impact the parameters' choice and, therefore, on the possible ways of addressing recommendation?  Should recommendation not be interactive and user preferences are chosen or pondered by a scientist to guide recommendation?
Additional comments: The paper is a fair description of a recommendation solution for designing and tunning analytic activities composing scientific workflows. The strategy of using provenance data and exploiting them for guiding recommendation is smart. The paper needs the following modifications to consolidate it.
1.	A motivation example of a scientific workflow can illustrate the problem and the proposed recommendation solutions. Of course, the audience targeted by the paper is one that knows what a scientific workflow is yet there are types and families of such workflows that might use different analytics algorithms with other parameters tuning challenges. It is essential to clarify and put in perspective this aspect in the explanations and the description of the global recommendation provided by FReeP.
2.	Background. Sometimes the introduction of concepts focusses on a specific system or approach. For a background section, I suggest a more objective approach, either explaining why are chosen references enough for introducing concepts or selecting more references and synthesising different definitions and perspectives to build the section. The background or another section can give a taxonomy of scientific workflows and those that can best benefit specific parameters' recommendation. If parameters recommendation regards specific families of ML and AI, it must be clarified. I believe that different types of algorithms lead to additional provenance data and introduce other recommendation challenges. This type of discussion is missing in the paper.
3.	The paper is motivated by the fact that scientific workflow tuning requires running the workflows several times, which is time and resources consuming. Yet, the remainder of the paper and particularly experiments do not longer respond to this kind of "research questions". If the paper's purpose is not intended to answer these questions and do not motivate it with them or precise the "research questions" or aspects of the problem that you answer in it. In this sense, I also believe that precision and recall assess the recommended parameters by the three proposed strategies. It seems that the recommender automates the test-error process when designing a scientific workflow, so it is not surprising that it works. The question is how much overhead it creates, and whether it consumes fewer resources than repeating the execution of a workflow to tune parameters.
4.	Related work needs to be completed; it is too short and too general.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: PROVENANCE-AND MACHINE LEARNING-BASED RECOMMENDATION OF PARAMETER VALUES IN SCIENTIFIC WORKFLOWS
Review round: 1
Reviewer: 3

Output:
Basic reporting: **Clear and unambiguous, professional English used throughout.**

The article is reasonably well written.

**Literature references, sufficient field background/context provided.**

I am not an expert in the area, but I can't think of any references that are missing. If anything, there is an overabundance of background. The authors go into fine-grained detail on a number of topics, such as "SciCumulus" (lines 149-173) and collaborative filtering (lines 242-306) without providing any explanation for how these topics relate to their own work. For example, the authors devote over a page of their manuscript to explaining collaborative filtering, but don't explain how it relates to their method. The authors mention that this manuscript is a submission of a previously published conference paper which contained less background. If they feel that this level of detail is necessary to contextualize their contribution, they should make explicit references to how their model differs from the background. For example, "Collaborative filtering is a common recommendation paradigm... [~2 sentences of detail]. We do not use this method because X,Y,Z,. Instead, we contribute A,B,C"

**Professional article structure, figures, tables. Raw data shared.**

Figures 5,6,7,8,9,10 were very helpful and effectively communicated the method. Figure 11 should be improve (axes labels are too small, both heatmaps should use the same color scale). I recommend that the authors report their results to fewer significant figures in Tables 3 and 4.

The example in Table 1 is confusing. It might be easier to show four or five sample ballots, rather than the number of times a given ordering occured.

The authors provide a link to a GitHub repository with their code, but I can't find the provenance datasets.

**Self-contained with relevant results to hypotheses.**

Yes.

**Formal results should include clear definitions of all terms and theorems, and detailed proofs.**

N/A
Experimental design: ## Experimental Design

**Original primary research within Aims and Scope of the journal.**

Yes.

**Research question well defined, relevant & meaningful. It is stated how research fills an identified knowledge gap.**

After reading the paper I am still confused about the core research question. I understand that the authors intend to recommend appropriate hyperparameters  in scientific workflows, but to what end? Is the intent to recommend parameters that don't cause the workflow to crash (as line 82 suggests) or parameters that fit the users' prior preferences (as the experiments and name of the method imply)? Without this clarification I can't evaluate how meaningful the research question is.

**Rigorous investigation performed to a high technical & ethical standard.**

Yes.

**Methods described with sufficient detail & information to replicate.**

Yes.
Validity of the findings: ## Validity of the Findings

**Impact and novelty not assessed. Negative/inconclusive results accepted. Meaningful replication encouraged where rationale & benefit to literature is clearly stated.**

The findings are important and could be impactful to the scientific community. However, the aforementioned ambiguity around the paper's core research questions makes a more detailed evaluation of contributions difficult.

**All underlying data have been provided; they are robust, statistically sound, & controlled.**

The authors should add more detail about how their data was collected. Are all of these runs from the same user, or multiple users? If they are from the same user, then the paper loses some claim to generalizability, since there is no evidence that the model is robust to parameters drawn from different user distributions.  If they are from different users, then were validations folds split by user, or are samples from the sample user distributed across folds?

**Conclusions are well stated, linked to original research question & limited to supporting results.**

The conclusions could be better organized. I'd like to see a summary table or figure that lists the experiments the authors conducted and the key results. As is it's prohibitively difficult to scan the paper.

**Speculation is welcome, but should be identified as such.**

N/A
Additional comments: Thank you for your submission! I think supporting that scientific computing doesn't get enough attention from the computer science community and I'm glad to see (to me) new work in this space. I'd recommend that you:
1) Clarify the intent of your paper, and how it's supported by your experiments
2) Dramatically trim down your background, or better place it in the context of your paper
3) Better organize and highlight your results so that they can be digested in a quick read
I have attached an annotated manuscript. Please excuse my handwriting :)


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: PROVENANCE-AND MACHINE LEARNING-BASED RECOMMENDATION OF PARAMETER VALUES IN SCIENTIFIC WORKFLOWS
Review round: 2
Reviewer: 1

Output:
Basic reporting: It would be good, if the authors include some comparison tables (summary tables) of the related work, otherwise, it may become difficult to flow the textual description clearly.

Proof-read the paper for the improvements of writing comprehension.

The paper is improved and can be published.
Experimental design: Good
Validity of the findings: Sounds good.
Additional comments: It would be good, if the authors include some comparison tables (summary tables) of the related work, otherwise, it may become difficult to flow the textual description clearly.

Proof-read the paper for the improvements of writing comprehension.

The paper is improved and can be published.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: THE COEFFICIENT OF DETERMINATION R-SQUARED IS MORE INFORMATIVE THAN SMAPE, MAE, MAPE, MSE AND RMSE IN REGRESSION ANALYSIS EVALUATION
Review round: 1
Reviewer: 1

Output:
Basic reporting: No comment.
Experimental design: No comment.
Validity of the findings: No comment.
Additional comments: -The reviewer attaches a PDF document with some additional comments, suggestions and highlighted typos.
-The authors split their data into train and test sets. It would be interesting to see results with train, validation and test sets, for instance.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: THE COEFFICIENT OF DETERMINATION R-SQUARED IS MORE INFORMATIVE THAN SMAPE, MAE, MAPE, MSE AND RMSE IN REGRESSION ANALYSIS EVALUATION
Review round: 1
Reviewer: 2

Output:
Basic reporting: The manuscript follows the defined standards. Includes a thorough review of the literature, and contextualisation of the work within the state-of-the-art. Methods and experiments are described thoroughly. Results are clearly and transparently presented. Data is either provided or freely available online (Lichtinghagen dataset). Language is very good, with only some typos/mistakes to correct (e.g. "deeper description of for R2" on line 122, "despite of the ranges" on line 191).
Experimental design: The choice of R2 and SMAPE is well-justified based on informativeness, among all the other surveyed metrics. The experiments cover most aspects where R2 and SMAPE differ, especially the use-cases 1-5. The real medical scenario is interesting, but the manuscript would be much more complete if other real scenarios were included: other medical scenarios (e.g., COVID-19 cases prediction) or other real contexts (e.g., financial predictions).
Validity of the findings: The findings are valid. The use-cases and the medical experiment cover most differences between R2 and SMAPE and truly show the benefit of using R2. However, beyond the issue of the negative space discussed by the authors in the conclusion, no other drawbacks or possible limitations of R2 have been discussed. Perhaps additional experiments in other real scenarios or the future comparison with Huber metric Hδ, LogCosh loss, and Quantile Qγ would help unveil such downsides of R2.

Nevertheless, the lack of deeper discussion on these makes the paper appear quite one-sided (in favour of R2), and also leads to the absence of proposals to improve: what could be improved in R2, what desirable behaviours should the new R2 verify, how could we change R2 to achieve it? Since the paper is merely a comparison between R2 and SMAPE, that does not propose an improvement on either measure, at least it should include this deeper speculative discussion on what could be done to achieve an improved R2 metric.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: THE COEFFICIENT OF DETERMINATION R-SQUARED IS MORE INFORMATIVE THAN SMAPE, MAE, MAPE, MSE AND RMSE IN REGRESSION ANALYSIS EVALUATION
Review round: 1
Reviewer: 3

Output:
Basic reporting: Professional English: the writing of the article is mostly good professional English, with some minor errors.

Literature references: the article cited a good number of  original sources of information.

Article structure: the  article appears to follow common structured used for medical publications.

Self-contained: The authors  did  not make a clear statement about the central hypotheses of this article.

Formal results: No clear criteria was given in how to judge the different metrics.
Experimental design: The core of the work is to compare different quality metrics, however, since the authors did not establish a concrete standard, it is very hard to say which one is better.

Originality: poor.

Research question: not well defined

Rigor: anecdotal evaluation

Methods: lack of the key evaluation criteria
Validity of the findings: This is an anecdotal evaluation of five different quality metrics for regression, however, due to a lack of clear standard of comparison, it is hard to judge whether the conclusions are valid or not.
Additional comments: This article needs a clearly defined standard for comparing different quality metrics.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: THE COEFFICIENT OF DETERMINATION R-SQUARED IS MORE INFORMATIVE THAN SMAPE, MAE, MAPE, MSE AND RMSE IN REGRESSION ANALYSIS EVALUATION
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment.
Experimental design: No comment.
Validity of the findings: No comment.
Additional comments: The reviewer attaches a PDF document with some additional comments, suggestions and
highlighted typos.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: THE COEFFICIENT OF DETERMINATION R-SQUARED IS MORE INFORMATIVE THAN SMAPE, MAE, MAPE, MSE AND RMSE IN REGRESSION ANALYSIS EVALUATION
Review round: 2
Reviewer: 2

Output:
Basic reporting: No new comments to add.
Experimental design: No new comments to add.
Validity of the findings: No new comments to add.
Additional comments: Overall, the article is good and has been improved since the last review round.

The new scenario of children obesity prediction is exactly what I was looking for, and further illustrates the conclusions drawn by the authors regarding the superiority of R-squared.

Once again, it would be interesting to see a deeper and more insightful discussion on possible steps towards better measures, and I look forward to seeing it in future studies.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A SURVEY ON MODELING DYNAMIC BUSINESS PROCESSES
Review round: 1
Reviewer: 1

Output:
Basic reporting: The manuscript investigated the level of dynamicity of dynamic business process modeling as well as the implementation in different existing approaches. The authors presented a literature review of approaches to modeling business process and provide a comparative evaluation of their level of dynamicity. Also, they identified the level of description and refinement in the analyzed dynamic business process approaches.
The manuscript is interesting. It is well prepared and presented.
Experimental design: Article content is within the scope of the journal.
Validity of the findings: The aims, the objectives and the outline of research are clearly defined. The literature is properly referenced and cited.
Additional comments: -	Why the format of References’ citation differ? For example (Pesic & van der Aalst, 2006;Heinl et al., 1999) in Line 2020 and (2016b) in Line 203.

-	Authors mention that ‘Due to technical limitations only free access sources were chosen’. Did the authors sent some requests to some authors of non-free access papers to obtain some interesting papers fruitful to the survey?

-	Authors mention that one of the main results obtained during the survey of the selected papers consists of analysis of tools for DBP modeling and simulation. Why the authors did not go in depth for this point to deal with modeling languages and standards that cover the DBP?

-	In Line 398, authors mention that they deal with surveys examining BP dynamicity from different perspectives. I am asking if these survey papers should be analysed different from non-survey papers? Or the same manner should be adopted?

-	Authors mention briefly ‘process ontology’ but they do not compare proposed ontologies (richness and coverage). In the other hands, authors include context in the definition of DBP but do not enumerate how studied works deal with BP context (i.e, how they model and manage these contexts? Maybe by ontologies or other models?)

-	Same remarks applies for ‘rules’

-	Also in the definition of DBP, authors mention that ‘changes can be implemented with minimal delay’ Did the authors focus on this issue when analyzing and/or comparing existing works


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A SURVEY ON MODELING DYNAMIC BUSINESS PROCESSES
Review round: 1
Reviewer: 2

Output:
Basic reporting: - The structure of the article needs to be improved, many parts of the article are scattered.
- Previous work should be properly reviewed and the advantages of this article over them should be clearly stated
Experimental design: - The research question is well defined, but not well answered. It may not be clear to the readers what the authors are proposing, and how the solutions try to address the research question
- According to Table 6, 7 and 8, there is no source from recent years in the reviewed papers. Have sources been deleted by the authors? Or did they not exist? If they do not exist, it is suggested to revise the keywords.
- For previous works, advantages and disadvantages must be clear
- In the first part of the article, some views have been considered for the problem, but no specific classification has been done on their effective parameters. For example, implementation environments can be added to this category.
Validity of the findings: - The author should emphasize the advantages of this paper, more specifically, topic that introduced in this paper while not mentioned in other survey should be illustrated.
- Challenges and open issues must be clear.
- It is recommended that they be displayed as a percentage in the implementation and issues covered by the chart
Additional comments: he paper should be revised a lot and its structure and issues should be seriously re-examined


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A SURVEY ON MODELING DYNAMIC BUSINESS PROCESSES
Review round: 1
Reviewer: 3

Output:
Basic reporting: The review presented in this paper is limited to « open access » papers.

The study does not reference work which are very relevant for the study, example the contributions provided by Luca Sabatucci and Massimo Cossentino: Supporting Dynamic Workflows with Automatic Extraction of Goals from BPMN. ACM Trans. Auton. Adapt. Syst. 14(2): 7:1-7:38 (2019)

The pape is very long. While many tables and figures are put outside the paper, their content is an integral part of it. Many details could be removed from the paper, like  the method of searching and selectiong papers, data extraction, etc. It would be better that the authors synthetise the content of the figures and the tables prensented outside of the paper.
Experimental design: The related work provide global positioning to existing work, but does not stress individual positioning to work very close to the provided review.
Validity of the findings: The conclusion does not identify  future directions
Additional comments: The paper provides a very interesting review about modeling dynamic business process. The methodology is clear and well detailed and illustrated. Precise definitions and requirements about dynamic business processes have been given. Valuable conclusions have been also made. However, the paper does not consider interesting work very relevant to this study like those of Luca Sabatucci and Massimo Cossentino dealign with goal oriented dynamic modeling of BP.

In addition, the work fails to provide technical details about modeling of dynamic  business processes. Merely statistical data about the number of paper dealing with different aspects of dynamic business processes.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A SURVEY ON MODELING DYNAMIC BUSINESS PROCESSES
Review round: 2
Reviewer: 1

Output:
Basic reporting: All my remarks and suggestions have been well addressed by authors so that I recommend to accept the manuscript.
Experimental design: no comment
Validity of the findings: no comment
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A SURVEY ON MODELING DYNAMIC BUSINESS PROCESSES
Review round: 2
Reviewer: 2

Output:
Basic reporting: The changes requested by the reviewers have not been applied and most of the explanations have been added outside of the paper.  the paper has not changed much
Experimental design: many  the papers have been referred to in different places without a specific category, and it is suggested to consider a specific category for the articles that can be used by the reader
Validity of the findings: future directions has improved.
Additional comments: In my opinion, the opinions of the reviewers have not been applied correctly:
for reviewer 1:
Comment 1: In lines 94 to 106, the source of the Eshuis paper is addressed in several ways, one of which conforms to the standard. Please check the whole paper.
Comment 3: In some of the papers that have been reviewed, there has been a lot of scattering that suggests that the structure of the paper be controlled.
Reviewer 2:
Comment 1: It refers to the structure of the article and how to categorize the papers, many of them have been referred to in different places without a specific category, and it is suggested to consider a specific category for the articles that can be used by the reader.
Comment 4: Due to the length of the article process as well as the acceptance process and given that the publication of the article will take place in an optimistic state in 2021. It is better to update the resources so that the survey article can be used. Because now the article is for two years ago
Comment 5:Items that have been added like 353, 363 , 386, are not modified in the file, are not displayed in the changes, and are the same as before


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CHEST X-RAY PNEUMOTHORAX SEGMENTATION USING U-NET WITH EFFICIENTNET AND RESNET ARCHITECTURES
Review round: 1
Reviewer: 1

Output:
Basic reporting: The written manuscript is unambiguous. However, English should be revised and corrected further. Most of the errors are grammatically related.
And Specifically:
Too many words repetitions:
- Repetition and redundancy can cause problems at the level of either the entire paper or individual sentences.
- Use a variety of different transition words.
- Vary the structure and length of your sentences.
- Don't use the same pronoun to reference more than one antecedent.
Some sentences are too long: - Break up your sentences
Sentence Repetition:
- Avoid repetition at the sentence level
- Avoid sentences that restate the main point of the previous sentence. - Don’t restate points you’ve already made.
The introductory sections show the context, nevertheless, there should be a clear proposition for the research objective at the abstract section. Structure is clear, figures and tables are well stated and represented. Raw data are provided with the required descriptive metadata identifiers.
Experimental design: The novelty of the research is obvious as it proposes a novel end-to-end semantic segmentation model, named Ens4B-UNet, for medical images as Ensembles 4 U- Net architectures with pre-trained Backbone networks. All underlying data have been provided; they are robust, statistically sound, & controlled. The overall performance and results are accepted .
Validity of the findings: The research falls within the scope of the journal. The objectives and methodologies are clear and well defined. The used algorithms and methods are described with sufficient detail & information to replicate.
Conclusions and results are well stated with the required diagrams.
However, the authors are required to provide the Confusion matrix of the validated images.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CHEST X-RAY PNEUMOTHORAX SEGMENTATION USING U-NET WITH EFFICIENTNET AND RESNET ARCHITECTURES
Review round: 1
Reviewer: 2

Output:
Basic reporting: Proofreading is required. There are a lot of places with punctuation errors, capital letters usage, unnecessary question marks, and redundant latex tags.
Diagrams could be made visually more appealing especially Figure 14 and Figure 10.
Experimental design: The paper does add to the body of knowledge. It aptly lists out the research gap, targets a specific issue, and gives sufficiently enough design and experimentation.
Validity of the findings: The authors are working on a dataset from the public domain and are also sharing their standing against the other works done to solve the same problem. This confirms the validity of their work. They aptly link the conclusions to the claims made.
Additional comments: no comment


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CHEST X-RAY PNEUMOTHORAX SEGMENTATION USING U-NET WITH EFFICIENTNET AND RESNET ARCHITECTURES
Review round: 1
Reviewer: 3

Output:
Basic reporting: This paper is well organized and written. The paper proposes end-to-end semantic
segmentation model, named Ens4B-UNet, for medical images as Ensembles 4 U-Net
architectures with pre-trained model.

I recommend the change of the title to be reduced. I suggest "Chest x-ray pneumothorax segmentation using U-Net  and Efficient ResNet architecture.

The introduction needs to be reduce. Have only the main parts and concentrate the motivation and contributions.
Experimental design: -The Experimental results need more details about the segmented images.
-Investigate the IoU score in details.
-Statistical calculations are required such as variance, mean, median, and the resulting histograms.
-SNR, PSNR, Error rates are required to be determined for the segmented images.
Validity of the findings: -The confusion matrix parameters like accuracy , F1-score, Recall, Should be calculated.
-The Hyper parameter values should be decelerated.
- The output of the Curve results from the program needs to be investigated and shown.
Additional comments: -The related work need to enhanced more recent works should be listed in higher top journals.
-The introduction should be summarized.
-Experimental results need to be realized and illustrate the confusion matrix parameters like accuracy , F1-score, Recall, Should be calculated.- The Hyper parameter values should be decelerated.
- The output of the Curve results from the program needs to be investigated and shown


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CHEST X-RAY PNEUMOTHORAX SEGMENTATION USING U-NET WITH EFFICIENTNET AND RESNET ARCHITECTURES
Review round: 2
Reviewer: 1

Output:
Basic reporting: minor proof reading is required
Experimental design: no comment
Validity of the findings: no comment
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CHEST X-RAY PNEUMOTHORAX SEGMENTATION USING U-NET WITH EFFICIENTNET AND RESNET ARCHITECTURES
Review round: 2
Reviewer: 2

Output:
Basic reporting: well addressed
Experimental design: well addressed
Validity of the findings: Authors should be updated their introduction section by adding the most recent published papers and compare with the proposed methodology in the paper.
1- Kamal, K. C., Yin, Z., Wu, M., & Wu, Z. (2021). Evaluation of deep learning-based approaches for COVID-19 classification based on chest X-ray images. Signal, Image and Video Processing, 1-8.
2-Elzeki OM, Shams M, Sarhan S, Abd Elfattah M, Hassanien AE. 2021. COVID-19: a new deep learning computer-aided model for classification. PeerJ Comput. Sci. 7:e358 DOI 10.7717/peerj-cs.358
3-Sheykhivand, S., Mousavi, Z., Mojtahedi, S., Rezaii, T. Y., Farzamnia, A., Meshgini, S., & Saad, I. (2021). Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images. Alexandria Engineering Journal, 60(3), 2885-2903.
Additional comments: need minor revision


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: RAPID GLOBAL PATH PLANNING ALGORITHM FOR UNMANNED SURFACE VEHICLES IN LARGE-SCALE AND MULTI-ISLAND MARINE ENVIRONMENTS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The paper is well organized and is quite good from the English aspect. The introduction and background literature references are sufficient. Moreover, the shared Raw data supports the presented results. Finally, figures have good quality and tables are appropriately described.
Experimental design: The paper is into the scope of the journal. The contribution of the paper is clear, and it provides sufficient detail to replicate the proposed method.
Validity of the findings: The results of the paper show the effectiveness of the proposed approach. Moreover, a comparison against a basic approach is presented. The conclusions are well stated and connected to the original question investigated. However, a sentence of the conclusions is not clear. Comment to the author is:

1.- In the “Conclusions” section, the authors mention “Additionally, the execution time is sufficiently low in many global path planning applications of USVs”. Do you mean that the proposed algorithm execution time is low enough for global path planning applications? Please, discuss the common execution time for global path planning algorithms.
Additional comments: There are some minor problems that need attention. Comment and suggestion are:
1.- In Eq. (3), verify if there is an extra comma in T_(x_m x_i) > T_(x_m),T_(x_i).
2.- In Eq. (5), non-italic T is not defined.
3.- In line 179, verify the text “To The two-level SR grid maps are contained in the HSR and LSR grid maps.” I think “To” can be removed.
4.- In line 201, It seems to be missing the word “axis” for “X-“.
5.- In line 212, verify the text “This In the basic FM2 method,” I think “This” can be removed.
6.- Eq. (18) is hard to read because it is too small.

Some comments based on the “Instructions for Authors” of PeerJ are:
1.- In Fig. 10, the description of the Figures (A-B) should be included in the figure caption. Similarly, in Fig. 13, the description of the Figures (A-E) should be included in the figure caption.
2.- In Fig. 9, label each part with an uppercase letter. Then, the description of the Figures should be included in the caption.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: RAPID GLOBAL PATH PLANNING ALGORITHM FOR UNMANNED SURFACE VEHICLES IN LARGE-SCALE AND MULTI-ISLAND MARINE ENVIRONMENTS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The idea of the paper is interesting and relevant to the field. The introduction adequately describes the context and the related literature, in particular identifying some shortcomings of the FMM-based methods. However, in the last paragraph of the introduction, it must be clearly remarked the issues of the existing methods. It must be clarify if this is the first time that the IDC is introduced in an FMM method. At the beginning of the section “Related methods” it must be provided main references where the FMM method is detailed. The structure of the paper is good and the figures are relevant and of good quality. A remarkable issue is that the English writing can be improved and must be carefully revised.
Experimental design: The research reported in this work seems original, the research question is well defined and relevant. The proposed method is adequately described, although some aspects that will be described in the comments to the authors can be improved.
Validity of the findings: The results show the benefits of the proposed method in comparison to a basic FMM-based method in terms of flexibility to ensure a smooth and safe path. Some final questions about the computational efficiency must be clarified as will be specified in the comments to the authors.
Additional comments: The paper presents a global path planning algorithm for unmanned surface vehicles with time optimality requirements. The proposed method is based on the fast marching method, which has been improved to find better solutions in terms of safety and computational efficiency.

The idea of the paper is interesting and relevant to the field. The introduction adequately describes the context and the related literature, in particular identifying some shortcomings of the FMM-based methods. However, in the last paragraph of the introduction, it must be clearly remarked the issues of the existing methods. It must be clarify if this is the first time that the IDC is introduced in an FMM method. At the beginning of the section “Related methods” it must be provided main references where the FMM method is detailed. The structure of the paper is good and the figures are relevant and of good quality.

The research reported in this work seems original, the research question is well defined and relevant. The proposed method is adequately described, although some aspects must be better described or justified: 1) What is the importance to plan time-optimal paths in comparison to optimal paths in distance? At the end, the method modifies the paths according to the parameters of the IDC and time optimality is then missed. 2) It is not clear the effect of the vehicle dynamics (velocity, acceleration) over the final planned path. Equation (20) specifies a condition that the parameter Dsc must satisfy, but the results does not show how the dynamic parameters are taken into account in the method, since one expects that they are very important to find time-optimal paths. 3) Provide an interpretation of equation (1) besides of the definition of the variables. 4) Justify the need of the proposed method in comparison to the classical approach to inflate the obstacles size to guarantee to find collision free paths.

The results show the benefits of the proposed method in comparison to a basic FMM-based method in terms of flexibility to find a smooth and safe path. Regarding the reported results about computational efficiency, some issues must be addressed: 1) Clarify in the description of the proposed method, where exactly the method saves computational time with respect to the compared method. 2) Specify which stages of the proposed method are measured in the planning times reported in Table 4 (they must be called planning times instead of execution times). 3) It is not clear why these times varies from one run to another, clarify if there is some random process in the method that generates the difference in time. 4) Comment in the conclusions if the method can be extended to make replanning in execution time and what is the challenge to do it using this kind of methods.

Finally, a remarkable issue of the paper is that the English writing can be improved and must be carefully revised. For instance, 1) the second phrase of the abstract is not correct, 2) the word “grid” is incorrectly used most of the time, “cell” must be used in many cases. 3) In the paragraph starting in line 134, are the authors talking about the proposed method or the existing one? 4) Line 147, different behaviors… These kind of behaviors must be introduced to give a clearer notion. 5) Lines 179 and 212, among others.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: RAPID GLOBAL PATH PLANNING ALGORITHM FOR UNMANNED SURFACE VEHICLES IN LARGE-SCALE AND MULTI-ISLAND MARINE ENVIRONMENTS
Review round: 2
Reviewer: 1

Output:
Basic reporting: The paper is well organized and is quite good from the English aspect. The introduction and background literature references are sufficient. Moreover, the shared Raw data supports the presented results. Finally, figures have good quality and tables are appropriately described.
Experimental design: The paper is into the scope of the journal. The contribution of the paper is clear, and it provides sufficient detail to replicate the proposed method.
Validity of the findings: The results of the paper show the effectiveness of the proposed approach. Moreover, a comparison against a basic approach is presented. The conclusions are well stated and connected to the original question investigated.
Additional comments: The authors have followed the suggestions and comments to improve the manuscript quality. I have no further questions.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: RAPID GLOBAL PATH PLANNING ALGORITHM FOR UNMANNED SURFACE VEHICLES IN LARGE-SCALE AND MULTI-ISLAND MARINE ENVIRONMENTS
Review round: 2
Reviewer: 2

Output:
Basic reporting: The paper have been adequately improved and I only suggest to include disscussions about two points that were replied to this reviewer but not included in the manuscript. This is specified in the comments to the authors.
Experimental design: This reviewer is satisfied with the experimental design presented in the paper.
Validity of the findings: This reviewer is convinced of the validity of the findings presented in the paper.
Additional comments: The paper have been adequately improved and I only suggest to include disscussions about two points that were replied to this reviewer but not included in the manuscript:

-What is the importance to plan time-optimal paths in comparison to optimal paths in distance? At the end, the method modifies the paths according to the parameters of the IDC and time optimality is then missed. Some discussion about this point must be included in the manuscript as was answered to the reviewer.

-Justify the need of the proposed method in comparison to the classical approach to inflate the obstacles size to guarantee to find collision free paths. Some discussion about this point must be included in the manuscript as was answered to the reviewer.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF USING MOBILE AUGMENTED REALITY FOR SIMPLE INTEREST COMPUTATION IN A FINANCIAL MATHEMATICS COURSE
Review round: 1
Reviewer: 1

Output:
Basic reporting: Good language, easy to read, structure is fine but for a suggestion of revision in the details below.
Experimental design: Fine but but a few suggestions below.
Validity of the findings: Fine.
Additional comments: Instead of writing a lengthy text In prose, I provide a detailed list of comments and recommendations:
- The topic of your paper is extremely specific, yet it is quite interesting.
- You claim that students "show no interest in financial education" but looked at "undergraduates enrolled in financial mathematics courses". Why should anyone without an interest in finance take a course in financial mathematics? As part of not directly related degree programs? Please explicate.
- The hypotheses are fine. I do not think they should be placed in the introduction, though, where I would only expect the research question. I would develop the hypotheses in a section on research design.
- Nice to explicate your contributions.
- Your literature study is too short, particularly concerning general work on the use of VR / AE in education. For the VR side, I recommend the following article as a starting point:
Radianti, J., Majchrzak, T. A., Fromm, J., and Wohlgenannt, I. (2020): A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda, Computers & Education, 147, 103778, Elsevier
I think you did a great job regarding related studies, but you could put more detail into drawing the "broader picture" of related research activities.
- I am tempted to suggest renaming "Materials & Methods" to "Research Design", to include hypothesis building (possibly also adding justification for the different hypotheses), and to make it more a classical section on how the research is conceptualized and carried out.
- I think it would be nice to get more details on the development. You may consider adding a model of the tool.
- The survey detail should be described in more detail.
- Selection of the participants should be described in more detail.
- The presentation of the results is fine.
- The discussion should be much extended. I suggest to at least have subsections that
-- discuss the lessons learned from your study and how this related to the literature and your expectations,
-- give implications for research and state possible contributions to theory, thereby generalizing your findings beyond its narrow domain,
-- scrutinize implications for practice, such as advice for educators, and
-- name limitations of your work.
- You may also give further research directions.
- The reference list is surprisingly short for the topic at hand. I think you should check if you can relate to works that use AR for education, even if domains and settings are different. Quite possibly this can yield valuable insights.
- Figures that are vectors by source must be inserted in vectorized form. This applies to Figure 1, Figure 8, and Figure 9.
- The tables are very nice and helpful.
- The supplementary materials make a very good impression.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF USING MOBILE AUGMENTED REALITY FOR SIMPLE INTEREST COMPUTATION IN A FINANCIAL MATHEMATICS COURSE
Review round: 1
Reviewer: 2

Output:
Basic reporting: The English language is not clear enough. It contains grammatical or syntactic errors (highlighted in purple in attachment) or vague phrasings that are not sufficiently informative (highlighted in blue in attachment).

The set of references is extensive, however, the authors often do not clearly indicate which information or decision come from the literature (with or without adaptations) or are assumptions. For instance, the model in Figure 9 come from Hamidi & Chevoshi, with modification (omissions). References to the literature are sometimes unspecified (e.g., "recent studies" mentioned p.10 without citation). For instance, reference to Davis (1989) is missing:
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

Acronyms are used too often, and sometimes unnecessarily, without recapping their meaning. It makes it difficult to read the paper. The acronym for Perceived Ease of Use is inconsistent (PEOU Vs PEU). Finally, null p-values are reported (p = 0.000) which is misleading and inexact (better say p < 0.001).

Equations (1-6) are highly redundant, and may not reflect the equations used in practice, from a human perspective. Mentioning only equations (2) and (5-6) should be sufficient. The meaning of the equation terms should be stated in advanced, e.g., as an introduction to the topic at hand. In particular, the term "simple interest" is barely explained or understandable until the equations are shown.

Hypotheses are not sufficiently explained before being stated. For instance, it is unclear what "positive effects" mean until SEM is mentioned. As well, Hypotheses 12 mentions a threshold of 3.8 without any justification. It seems arbitrary until it is explained later.
Experimental design: The experimental design relies on solid statistics, however it does not provide specific insights into what makes the interface successful or not. There is no comment on the interface design itself. Furthermore, the UI design could be applied on simple computer screen, and Augmented Reality (AR) technology is not providing extra features. It may have a positive effect due to its novelty, but the interface may be more usable on simple computer screen.
This research omit such consideration, hence it is not possible to claim that the positive results are due to using AR or using the SICMAR design. Similar positive impacts may be observed using simple computer screens, compared to learning with a teacher.

Finally the experimental design has a crucial flaw. Students are first exposed to pedagogical content with a teacher, before they are again expose to contents on the same topic using SICMAR. No control group is set apart, and exposed again to pedagogical content without using SICMAR. Hence the observed positive impacts may be due to the students' learning curve, not to the use of SICMAR. Similar  positive impacts may be observed even if students had practiced again with a teacher.
Validity of the findings: The authors mention exaggerated claims and interpretations of their findings. It is most important to state the limitations of the study. Besides limitations due to the experimental design, the data analysis has additional limitations.

Other limitations:
- The text of the questionnaire contain English mistakes and is sometimes vague or difficult to read. The poor quality of the English language may have affected the study.  (e.g., misunderstanding, fatigue).
- The statistical analysis is extensive, and is sufficiently explained, but it remains quite difficult to read due to the phrasing and grammar.
- The individual data points could be plotted relatively easily, and would make it easier to review the findings.
- Answers to single questions (e.g., A1, A2, etc...) should be compared individually, i.e., answers with or without SICMAR.
- The formula to calculate the "Totals" in Tables 2, 3, 5 is not specified. Furthermore, it is incorrect to call these totals, as they are means (since their range remains within 1-5).

When analysis the grades of the exam:
- The text of the exam is not provided.
- The answers to individual questions are not analysed (e.g., to identify what is particularly difficult to learn)
- The progress of individual students is not analysed, just averages are provided. However, the author mention that some student grades have decreased with SICMAR (how many? by how much?).
Additional comments: This research investigates a promising technology that may enhance the learning process of students. However, the research design has crucial methodological limitations, and the findings are not specific enough to provide guidance or insights for future work (i.e., to inform the design such tools, rather than observing general improvements of student's motivations or exam results). To be more valuable, the research should be continued, e.g., with in-depth analyses of the answers to the exam and to the questionnaires, and by making a critical review of the interface design (i.e., in relation to the analysis of the exam and questionnaire).

The annotated document attached uses the following color code:
- Yellow: my own notes, please ignore these
- Blue: vague phrasing, to hard to understand or not informative enough
- Purple: English mistakes
- Pink: statements that are arguable from a scientific perspective, or that are not justified enough to be convincing.
- Green: Good points, but not all good points are highlighted.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF USING MOBILE AUGMENTED REALITY FOR SIMPLE INTEREST COMPUTATION IN A FINANCIAL MATHEMATICS COURSE
Review round: 2
Reviewer: 1

Output:
Basic reporting: Good language, easy to read, structure is fine.
Experimental design: Fine.
Validity of the findings: Fine.
Additional comments: Dear authors,

thank you for the revision and for the good overview of changes in the rebuttal document. I think you did an excellent job in commenting on and addressing the reviews.

The amount of changes is impressive. You obviously took the revision very serious, which is appreciated. Although it is somewhat uncommong to accept R1 after a major revision "as is", I recommend doing so. The only strong suggestion that I have is inserted Figures 6 to 9 in vectorized form (I am not sure about Figure 3, it might be possible as well).


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF USING MOBILE AUGMENTED REALITY FOR SIMPLE INTEREST COMPUTATION IN A FINANCIAL MATHEMATICS COURSE
Review round: 2
Reviewer: 2

Output:
Basic reporting: The English has (almost) no mistake, the references are complete, and the methods are described in detail. The sections on "Lessons learned" and "Limitations", and the additional literature review (incl. Table 1) are very good additions.

However, there are still sentences that are not precise enough (details below). It makes the discussion state claims with too large a scope, and that are not fully supported by the study in the paper. Namely:

- L.674-675, "Students use their fingers to insert the values and uses the markers to define the inputs and outputs. As a result, students' motivation to learn simple interest increases.": The paper provides no evidence that a specific way to use fingers is what increased motivation.

- L.678, "students perceived learning as a game": The paper does not provide evidence to this, i.e., no questions asked to participants targeted this aspect in particular. Perhaps oral was collected, but this is not reported.

- L.683-684, "students did not consider the contents of SICMAR as sufficient to keep all the attention": The absence of significant impact on attention, as measured with the questionnaire, cannot be directly linked to the sufficiency (sic) of content.

- L.715-716, "Students considered the [...list of features...] as the critical features to determine quality": The word "consider" is ambiguous. To be precise, students gave the highest quality scores to these features. It does not mean that they identified these as "critical features to determine quality". The authors of the paper are the ones determining quality using these features (and others in the questionnaire), perhaps students would consider other features as critical for quality.

Line by line details:
- L.65-66, "principal sum/balance": the terms can be unclear for a reader with no expertise in finance.
- L.154-155, "Qualitative research is the most common theory-base employed, followed by the nonparametric Wilcoxon signed-rank test": Comparing qualitative research with a statistical test is odd. What matters is what is tested, more than the type of test.
- L.192: the definition of "interest rate" is imprecise. In particular these words in [...] : "the amount charged [on top of] the principal [for the use of assets] (expressed as a [percentage])". The definition does not mention of the time dimension, and it's a percentage of what? Also equation (4) is not a percentage, but that's a detail. So it's rather, e.g., "a fraction/percentage of the Principal (charged) per unit of time".
- L.193: the definition of "time" is also imprecise, e.g., "the period of the [financial operation]" could be phrased as "the time period over which the interest rates apply/are charged".
- L.203, "Eqs. (1) to (6) are expressed in years": the interest rate is not expressed in years, i.e., it is not the unit. To be precise, one should rather say "use year as the time unit".
- L.297-298: "much quality" -> "good/sufficient quality"
- L. 333 & 670, "improves the user perception and interaction with the real world": This is rather vague, what is improved exactly?
- L. 336: "gadgets" -> "devices"
- L.362, "The context and world model subsystem includes...": I'm not sure why the terms "context" and "world model" are used, nor why the element listed thereafter fit together.
- L.420: "two five items tests" -> "two five-item tests".
- L.432, "translated": You should mention the language was Spanish, and so for the whole experiment.
- L.583, 584, 586: "were (..." -> "were: ..." and L.586 is missing "[the results] were".
- L. 596, "pre-test-post-test: pre-test and post-test.
- L.592, "3.33 times": it is vague, and the unit is not that of the grades (total of 100 points). The reader can only understand this number by looking at Fig. an dividing the mean by 20 (20 points per question). You should mention the "average grade of 66.6".
- L.602: "state" -> "stating"
- L.673, "the way on how" -> "the way in which"
- L.677 & 718: "determined" -> "expressed"?
- L.682: "bi-directional models" -> "2D virtual objects"
- L.698, 699, 704: "failed in/due the period conversion" -> "failed to convert the time unit" (3 occurrences)
- L.699-700 + 705-706: "not include" -> "not including/describing" and "not copy" -> "not copying"
- L.702, "questions 3-5" add "in Table 5" and/or "exam question". + "notable [that] the performance increase[s]".
- L.709: "qualified" -> "quantified"
- L.768: "some persons could be challenging using ICTs" -> "for some person it could be challenging to use ICTs" and "in-depth-analyzed" -> "analyzed in depth"
- L.775: "students that decrease the grade" -> "students which grade has decreased"
- L.776: "cero" -> "zero"
- L.781: "not using the hands" -> "not clicking on screens" (hand gestures are still needed.
- L.793: "conveys to conclude" -> "leads to concluding"
Experimental design: No further comment.

However, another detail concerns the type of mobile devices used with the AR app. Figure 5 shows a tablet, and I was under the impression that mobile phones were used. The type of device (e.g., screen size) can influence the results of the experiment. This should be clarified: e.g., did all students used a tablet? a phone? or a mix of both?
Validity of the findings: The section added on "Limitations" and the author's rebuttal seem to address most of my concerns. However, my concern with exaggerated claims holds, but I'm willing to consider that this is due to issues with how claims are written down (see section 1 above).

Furthermore, regarding the 36 students that were removed from the study (fro not completing the questionnaires): this is a considerable number (25% of the participants). This could impact the validity of the study. For instance, these students may have had issues with prototype, that could explain their incomplete answers to the questionnaires. If so, their negative feedback would not be reported (but the authors could check if their partial answers indicate such effect).
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CONVOLUTIONAL NEURAL NETWORK-BASED ENSEMBLE METHODS TO RECOGNIZE BANGLA HANDWRITTEN CHARACTER
Review round: 1
Reviewer: 1

Output:
Basic reporting: There are too many long paragraphs, and the text is not aligned at both ends, which affects reading.
Experimental design: The experimental design is good, and a large number of experiments have been conducted to verify the model.
Validity of the findings: The curves of images 3 and 4 are not very distinguishable, and the viewpoints mentioned in the article are not well drawn.
Table 8 for comparison with other studies hopes to be sorted for easy comparison.
Additional comments: Very meaningful work, but some details need to be revised. Great work!


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CONVOLUTIONAL NEURAL NETWORK-BASED ENSEMBLE METHODS TO RECOGNIZE BANGLA HANDWRITTEN CHARACTER
Review round: 1
Reviewer: 2

Output:
Basic reporting: This paper explores new methods of using ensemble on top of CNN-based feature extraction to improve Bangla character recognition (or classification in machine learning terms). The authors employ datasets used by previous work in literature and obtain better results as reported, with more classes considered. This work, along with others that consider other languages are very good contributions to many communities. In this first round of review, however, several flaws in the methods and experiments, if not also in others, are identified as below, and improvements are suggested to be made to make the paper better and more convincing.

English and format: While the use of English throughout the manuscript is professional, I suggest changing the following:
- Use of enumeration without using “etc”, maybe by replacing it with “such as”.
- Line 84, change to the format as instructed: (Smith, 2001a; Smith, 2001b)
- Line 481, use 500,000 instead of 500000. Similarly for lines 465 and 466, and other places with big numbers.
- Inconsistent uses of metric names, such as F1 in line 506 and f1 in 515 or in other places.

Introduction: while the authors provide much information, some suggestions to improve are made as follows:
- Reference for the first paragraph should be made about how significant Bangla is
- When stating Bangla is more difficult than other languages (which is a very strong claim indeed), the authors should present the comparison clearly, not assuming by looking at only the statistics of Bangla, readers should be able to agree. Such claims might or might not be true with various readers, for example, those are from English-, Chinese-, or Arabic-speaking countries.
- Another suggestion for comparison is to present a figure to illustrate how complex Bangla characters can be.

Literature:
- References should be added for well-known CNN architectures such as Resnet50 (from Kaiming He).
- Literature review does not clearly state the position of this paper: how this paper, in particular, is different from or similar to the previous work. This is important because it reinforces the contribution.
- When it comes to classifying characters only, this work is similar to the vast literature of recognizing, say English characters using HMM or LSTM with IAM, SD19, or other datasets. See for example https://arxiv.org/pdf/2008.08148.pdf. So I suggest the authors make a little review along this line of work to connect more of your paper to the community.
Experimental design: Methods (Section 3):
- Your model is very important. As a result, I suggest you describe the motivation as to why you choose to use such components, e.g, why CNN, why specific ensemble methods? Likewise, the authors need to answer many questions “why” about the choices of architectures.
- After that, the authors can describe the architecture in detail.
- However, sections 3.2 and 3.3 should be purged because they are common knowledge
- Section 3.1 should be placed in section 4 (at the beginning of it). Section 3 should be devoted to describing the model.
- Sections 3.5.1 and 3.5.2 have very long enumerations of components. Maybe the authors should trim it down to a small paragraph each or a small table each.

The research question of Bangla character recognition is useful and well-defined. However, there are the following suggestions to improve:
- First, section 3.1 should be moved to here to describe the datasets. Please state clearly which datasets you are using. For each such dataset, you need to compare it with previous work using it (at least one state-of-the-art baseline).
- Section 4.1 is not clear because the authors refer to only 1 dataset.
- References to Tensorflow/Keras need to be made.
- The use of PCA seems not well-motivated. This linear method would probably make the extracted features lose some information. To answer this question clearly, the authors should investigate the use of current architecture with and without PCA (e.g. in an ablation study). The reasons are two-fold:
1/ The drawback of PCA as said. Why don’t you use an FC layer to narrow down the classes, e.g. 2048 -> 1024 -> 112 as in normal usages of CNN? This is probably the easiest and most straightforward.
2/ Can PCA be implemented end-to-end along with your model, and how much slower it could be when combining with CNN? Usually, with high dimensional data, PCA is slow.
- Section 4.3, the formula in lines 513 to 516, and descriptions of related metrics are common knowledge and should be trimmed. If needed, make related references to those metrics.
- Table 8 is probably the most important result to present and should be made first and foremost. Other ablation studies such as with different architectures, optimizers, methods should be placed later.
- However, the results in Table 8 are questionable because it is needed to make a fair comparison between your methods and others, based on the same set of datasets (including splits between train/val/test). Important changes should be made:
1/ Compare your methods with others on their datasets (at least one good baselines, explain why you choose the baseline(s))
2/ Compare other methods with your current datasets (again, with a good baseline).
Validity of the findings: The authors employ widely used components of CNN, Ensemble, and PCA. However, they claim their combination is novel, which was made clear in the literature review. Nonetheless, they need to motivate their choices more convincingly. Experimental results should be made more clearly and in a more convincing way as suggested below.

Dataset: The authors adhere to PeerJ regulations by providing citations to datasets being used. However, the descriptions of datasets lack important characteristics such as:
- the resolutions and the format (RGB or not)
- the authors enumerate Bangla datasets without stating directly which datasets they are going to use in specific, which they should heavily focus on
Additional comments: The research question of Bangla character recognition is useful for the community and well-defined. However, your choices of architectures, their descriptions, and experiments should be further improved to make the paper more convincing.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: CONVOLUTIONAL NEURAL NETWORK-BASED ENSEMBLE METHODS TO RECOGNIZE BANGLA HANDWRITTEN CHARACTER
Review round: 2
Reviewer: 1

Output:
Basic reporting: The content of the article is clear, but article typesetting is not easy to read and may require post orchestration.
Experimental design: The experiments were well designed and largely validated.
Validity of the findings: The experimental results are clear and unambiguous.
Additional comments: Very meaningful work, but some details need to be revised. Great work!


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A-RESS NEW DYNAMIC AND SMART SYSTEM FOR RENEWABLE ENERGY SHARING PROBLEM
Review round: 1
Reviewer: 1

Output:
Basic reporting: (1) The presentation is clear and professional English  is acceptable.
(2) The references are incomplete and somewhat outdated. A more comprehensive and timely literature survey is desired.
(3) The article structure is acceptable.
Experimental design: 1 The topic of this paper fall in the Aims and Scope of the journal.
2 The knowledge gap is not clear.
Validity of the findings: The validity of the findings must be strengthened. More jobs should be done to verify the work.
Additional comments: This paper presents a-RESS new dynamic and smart system for renewable energy sharing problem. The simulation results are also provided. Here, there are some concerns of this reviewer:

Point-by-point list of major recommendations:
1 Author should highlight the research gaps and contribution of the proposed work by comparing the state of the art methods and recent studies.
2 In the introduction section, the literature review must be strengthened. The references is incomplete and somewhat outdated. A more comprehensive and timely literature survey is desired.
3 How scalable is the proposed approach?
4 The theoretical depth of this paper needs to be strengthened.
5 The proposed method might be sensitive to the values of its main controlling parameter. How did you tune the parameters? Please elaborate on that.
6 The computational cost of the proposed approach isn’t discussed in this work. The approach should be computationally efficient to be used in practical applications.
7 The novelty and contribution of the presented work need further justification. Authors need to add more results to thoroughly support the main findings.
8 Authors have not presented limitations of this work. How this work can be extended in future? Although authors have provided various comparative results, however, more details on how proposed phenomenon performs better results against baseline is still missing in the paper.
9 Please specify details of the computing platform and programming language used in this study.

Point-by-point list of minor recommendations:
10 The nomenclature should be included to help the reader to follow the paper conveniently.
11 The italic types of symbols in equations and the main text should be in the same expression.
12 Please improve the quality of figures completely to improve the readability of this paper.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A-RESS NEW DYNAMIC AND SMART SYSTEM FOR RENEWABLE ENERGY SHARING PROBLEM
Review round: 1
Reviewer: 2

Output:
Basic reporting: This article covers an important topic, however I have some considerable concerns:
1. The introduction of the article and research is poorly written, uses too many acronyms, does not define concepts, uses hardly any references, and also does not describe the justification of the research, nor does it clearly describe what the article is about. This needs to be updated.
2. The methodology and description of the approach and its application is better, but there are still many major questions. For example, how does the temporal dimension feature? All the demands and supplies should be a function of time, yet this is not clarified anywhere. What is the time step? This is important, especially for renewable energy given the limited predictability a long way into the future.
3. An Agent-Based Model should be described in some detail, such as by the ODD method, but this is not described here. Therefore, the method is not replicable in my mind unless this is fully described.
4. What data is being used as inputs?
Experimental design: The experimental design has not been clearly described, and I can't find information about important aspects such as sensitivity analysis
Validity of the findings: It is unclear exactly what the findings are, so I can't judge the validity.
Additional comments: Given that on the surface your method looks very useful, I suggest more effort is given to describing it in greater detail so that the validity and details can be evaluated adequately.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A-RESS NEW DYNAMIC AND SMART SYSTEM FOR RENEWABLE ENERGY SHARING PROBLEM
Review round: 2
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: I would like to thank the authors for this revised version since most of my concerns have been addressed. The paper deserves to be published after minor revisions:
1. Some references lack information such as volume number and page number. Please check and modified the references.
2 The current literature and technique review is still inadequate, and some important works are missing. Please refer to the following studies: "A pragmatic approach towards end-user engagement in the context of peer-to-peer energy sharing", "Optimal distributed generation planning in active distribution networks considering integration of energy storage", "Optimal scheduling of integrated demand response-enabled integrated energy systems with uncertain renewable generations: a Stackelberg game approach".
3 Although the manuscript is well written in terms of English, there are some (very few, indeed) grammatical errors. It is suggested to proofread the paper.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A-RESS NEW DYNAMIC AND SMART SYSTEM FOR RENEWABLE ENERGY SHARING PROBLEM
Review round: 2
Reviewer: 2

Output:
Basic reporting: The manuscript has been much improved and the language is clear and mostly unambiguous with good English throughout.

The paper is however severely lacking in references, especially in some sections. For example the Introduction is almost entirely lacking in references. This is critically important to address because the premise of the model needs to be established based on a real need. The methodology is now much better described. I am however missing further discussion about data. The data requirements are unclear and not fully specified, and unless this data can be found, the model will be useless.

The Related work section is a major improvement, but it needs to more clearly specify how this paper and model contributes something new. In clear and succinct language.

The ODD provides much needed added details and this is great.

The structure is now however much improved.
Experimental design: There is no clear research question or hypothesis stated.

Data is not adequately described.
Validity of the findings: I can't quite see how the experimental evaluation is clearly showing the usefulness of the approach. Who will use the model? Is this example representative of real planning examples? I do not consider that the experiment validates the hypothesis. What have you actually proven? It's not clear to me.
Additional comments: Again, the paper has some significant shortcomings that need to be addressed, but the article is now much improved.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A-RESS NEW DYNAMIC AND SMART SYSTEM FOR RENEWABLE ENERGY SHARING PROBLEM
Review round: 3
Reviewer: 1

Output:
Basic reporting: The paper is written in  clear, unambiguous, and professional English;
the literature references are sufficient;
the article structure is well organized,
Figures and tables are acceptable;
the manuscript includes all results relevant to the hypothesis;
the results include clear definitions of all terms and theorems, and detailed proofs.
Experimental design: This research is original primary research within Aims and Scope of the journal;
the research gap is well presented;
rigorous investigation has been performed to a high technical & ethical standard;
the methods are described with sufficient detail & information to replicate.
Validity of the findings: The findings are well verified;
all underlying data have been provided;
the conclusions are well stated.
Additional comments: After revision, this paper is well written and all my concerns have been properly addressed. I think this paper deserves to be published in the current form.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A-RESS NEW DYNAMIC AND SMART SYSTEM FOR RENEWABLE ENERGY SHARING PROBLEM
Review round: 3
Reviewer: 2

Output:
Basic reporting: The manuscript has now been thoroughly improved and I am satisfied with the revisions.
Experimental design: It's fine
Validity of the findings: It's fine
Additional comments: Thanks for your extensive changes and I think the article is good now. I still recommend that you go through to double check any grammar or editorial issues.