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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.

Title: GENE ONTOLOGY CAPSULE GAN: AN IMPROVED ARCHITECTURE FOR PROTEIN FUNCTION PREDICTION Review round: 1 Reviewer: 1

Basic reporting: The manuscript has been studied thoroughly and some recommendations for the authors are suggested , which are listed below: 1. In Figure 2, the author mentions a 9*9 input sequence in the detail design of the capsule network; nevertheless, the protein sequence is just one dimension. Please clarify this uncertainty. 2. Why did the authors use a capsule network at the GOCAPGAN discriminator level but not in the generator? 3. Figure 3 was not cited in the paper by the authors. 4. The authors mention in line 232 that they would consider an example of a disassembled boat, yet no visual picture of the boat is offered. Experimental design: All necessary details regarding experiments are already provided in a manuscript. Validity of the findings: The results reported by the author are aligned with the methodology discussed in a research article. Additional comments: No Additional Comments

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.

Title: GENE ONTOLOGY CAPSULE GAN: AN IMPROVED ARCHITECTURE FOR PROTEIN FUNCTION PREDICTION Review round: 1 Reviewer: 2

Basic reporting: The paper is self-contained and is written very well. Experimental design: The work is an extension of authors original work published earlier. The research questions are well defined and the proposed framework is described with sufficient details. Validity of the findings: Numerous experiments are carried out to validate the findings. Publicly available datasets were used in the study. Additional comments: The manuscript gives an improved concept of the author original work GOGAN. The authors introduced capsule network in GAN which lead to significant improvement in results. The improved technique was named GOCAPGAN. Introduction of the article contains all the important details and problem statement is given properly. The paper has already elaborated in detail that how utilization of capsule network can improve the results. Literature review is done in detail; methodology is written in such a way that it can easily be reproducible. Relevant tables and figures have been given. Conclusion and discussion properly relate the given solution with limitations in existing techniques. The grammar of the paper is in publishable form. Some minor modifications are given below: 1- As mentioned in the paper GOCAPGAN is an extension of GOGAN, however there are many similarities between GOCAPGAN and GOGAN, so it is suggested to update some content of GOCAPGAN. 2- How the values of Table 2 and Table 3 were achieved? 3- In results, what is the difference between Table 4 and Table 5?

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.

Title: GENE ONTOLOGY CAPSULE GAN: AN IMPROVED ARCHITECTURE FOR PROTEIN FUNCTION PREDICTION Review round: 1 Reviewer: 3

Basic reporting: Authors have researched and written GOCAPGAN articles whose primary objective is to predict protein functions using GANs. They have used residual blocks, standard CNN, and capsule networks in the GANs. The improved technique works better in results and the number of classes. The reviews of each section are given below: Abstract: The abstract of the submitted research paper is brief and displays all of the study article's material. The abstract is well organized, and it reports all of the findings. Introduction: The introduction is done correctly. The introduction begins with a protein overview, an explanation of protein functions, and a demonstration of the sequence-structure gap. What is the difference between GAN (with CNN) and GAN (with Capsule), and how does it solves your prediction problem? Literature Review: The writers conducted a study to compile background information and utilized current research articles to support the problem indicated in the introduction, however, include one or two recent literature reviews to complete it. Experimental design: Methodology: The authors have described their technique in depth. The method gives information for the proposed model provided in figures and tables. The presented method in this work can be easily reproducible from the images and details shown. However, the authors did not cite Figure 3 in the article. Validity of the findings: Results: The authors have supplied complete details regarding the dataset and hyperparameters. The authors performed rigorous testing and used different evaluation metrics and extensive testing. The source code of the implemented solution is available on GitHub. The authors need to explain why they did not include a hamming loss in Table 4. Additional comments: Discussion: The problem statement in the introduction is linked to the results, and the findings support the recommended solution to the problem. Conclusion: The conclusion gives a summary of the significant points throughout the article and supports the author’s claims The paper structure is sound and written in an acceptable way. The quality of the English written in the research paper is satisfactory for publication.

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.

Title: GENE ONTOLOGY CAPSULE GAN: AN IMPROVED ARCHITECTURE FOR PROTEIN FUNCTION PREDICTION Review round: 2 Reviewer: 1

Basic reporting: The article is written in English and is clear, unambiguous, technically correct text. The article conforms to professional standards of courtesy and expression. The article has sufficient introduction and background to demonstrate how the work fits into the broader field of knowledge. Relevant prior literature is appropriately referenced. Experimental design: Original primary research within Aims and Scope of the journal. Validity of the findings: All underlying data have been provided; they are robust, statistically sound, & controlled. Additional comments: All suggested changes are incorporated in updated article. The article meets the PeerJ criteria and should be accepted as is.

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.

Title: GENE ONTOLOGY CAPSULE GAN: AN IMPROVED ARCHITECTURE FOR PROTEIN FUNCTION PREDICTION Review round: 2 Reviewer: 2

Basic reporting: The authors have addressed all of my concerns. I have no further comments. Experimental design: Research questions are well defined and rigorous investigation has been performed. Validity of the findings: Results are validated on publicly available datasets. Code and datasets are provided on the GitHub. Additional comments: No additional comments

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.

Title: GENE ONTOLOGY CAPSULE GAN: AN IMPROVED ARCHITECTURE FOR PROTEIN FUNCTION PREDICTION Review round: 2 Reviewer: 3

Basic reporting: I am happy with the comments of round 1 being incorporated. The manuscript is relevant to the journal scope and has significant contributions—no further suggestion from my side. Therefore, I propose to accept it. Experimental design: Comments of round 1 are incorporated—no further changes are required from my side. Validity of the findings: Comments of round 1 are incorporated—no further changes are required from my side. Additional comments: Comments of round 1 are incorporated—no further changes are required from my side.

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.

Title: A GENETIC ALGORITHM-BASED ENERGY-AWARE MULTI-HOP CLUSTERING SCHEME FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS Review round: 1 Reviewer: 1

Basic reporting: This paper proposes a genetic algorithm-based energyaware multi-hop clustering (GA-EMC) scheme for heterogeneous WSNs (HWSNs). In HWSNs, all the nodes have varying initial energy and typically have an energy consumption restriction. A genetic algorithm determines the optimal CHs and their positions in the network. The fitness of chromosomes is calculated in terms of distance, optimal CHs, and the node's residual energy. Multi-hop communication improves energy efficiency in HWSNs. The areas near the sink are deployed with more supernodes far away from the sink to solve the hot spot problem in WSNs near the sink node. Results. Simulation results proclaim that the GA-EMC scheme achieves a more extended network lifetime, network stability and minimises delay than existing approaches in heterogeneous nature. Detailed comments are as follow: (1) MAC protocol has an important impact on network performance, and it is also an important research content of clustering networks. Therefore, I strongly suggest that the author discuss the recent MAC protocol in the relevant work. For example: A parallel joint optimized relay selection protocol for wake-up radio enabled WSNs," Physical Communication, vol. 47, 101320, august 2021. (2) Some problems have been addressed by the authors, the reviewer strongly suggests that the theoretical analysis of the system performance should be added to improve the quality of this paper.The author can found such work in:"heoretical analysis of the lifetime and energy hole in cluster based Wireless Sensor Networks[J],Journal of Parallel and Distributed Computing, 2011,71(10):1327-1355." (3) Authors are suggested to review more new and relevant research to support their research contribution.Many references in this paper are the work of more than 10 years ago. (4) I suggest that the author set up real experiments to test the performance of the prposed protocol. (5) The formulas in the text is incorrectly formatted，which should be align with the words instead of being upper than the words. (6) In fact, the work of this paper has been studied in many previous works. I also believe that the work done by the author is effective. However, the innovation of the paper is not strong, and almost all the work done in the paper can be found in the previous work. However, the author gives a PSO algorithm in detail, which can be used as a reference for relevant work. Therefore, it is suggested to give the author a chance to modify it to improve the quality of the paper. Experimental design: Please see the "Basic reporting". Validity of the findings: Please see the "Basic reporting". Additional comments: Please see the "Basic reporting".

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.

Title: A GENETIC ALGORITHM-BASED ENERGY-AWARE MULTI-HOP CLUSTERING SCHEME FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS Review round: 1 Reviewer: 2

Basic reporting: In this paper, a genetic algorithm-based energy-aware multi-hop clustering (GA-EMC) scheme for heterogeneous WSNs (HWSNs) is proposed. Genetic algorithm determines the optimal CHs and their positions in the network. The fitness of chromosomes is calculated in terms of distance, optimal CHs, and the node's residual energy. Multi-hop communication improves energy efficiency in HWSNs. Simulation results proclaim that the GA-EMC scheme achieves a more extended network lifetime, network stability and minimises delay than existing approaches in heterogeneous nature. This work is much meaningful, my comments are as follows: 1) Energy-efficient hierarchical clustering on IoT/WSNs is a very well-studied area with a lot of previous studies and over saturated. Therefore, there needs to be a very strong motivation and justification for the proposed approach not to repeat the previous contributions. 2) Given that there are tons of works in WSNs research, the related work should be written in such a way that the reader can see the differences of works in a Table and grasp the main assumptions/disadvantages of other approaches. In literature review, it is very important to summarize the advantages and disadvantages of existing work. 3) This work uses GA to optimize the energy consumption in WSNs, which have been deeply studied so far. Hence, the analysis in the paper on WSNs with GA is necessary, the following article is also appropriate choices: [1] X.-Y. Zhang, J. Zhang, Y.-J. Gong, Z.-H. Zhan, W.-N. Chen, and Y. Li, “Kuhn–Munkres parallel genetic algorithm for the set cover problem and its application to large-scale wireless sensor networks,” IEEE Trans. Evol. Comput., vol. 20, no. 5, pp. 695–710, Oct. 2016. [2] Y. Chang, X. Yuan, B. Li, D. Niyato, N. Al-Dhahir, "A Joint Unsupervised Learning and Genetic Algorithm Approach for Topology Control in Energy-Efficient Ultra-Dense Wireless Sensor Networks", Communications Letters IEEE, vol. 22, no. 11, pp. 2370-2373, 2018. [3] Y. Chang, X. Yuan, B. Li, D. Niyato, and N. Al-Dhahir, Machinelearning-based parallel genetic algorithms for multi-objective optimization in ultra-reliable low-latency WSNs, IEEE Access, vol. 7, pp. 4913–4926, 2019. 4) There can be the situation that some CHs are overloaded as they may have many nearby CMs. It might be good to state how this issue can be avoided. In addition, how to formulate the fitness in the optimization process? Experimental design: The simulation workload is enough, but the comparison algorithm needs to be added. Validity of the findings: Need enhancement. Additional comments: No additional comments

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.

Title: A GENETIC ALGORITHM-BASED ENERGY-AWARE MULTI-HOP CLUSTERING SCHEME FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS Review round: 1 Reviewer: 3

Basic reporting: Overall the paper is well-presented and clearly written in professional, unambiguous language. The topic has much significance. The novelty of the work and the contributions are clearly reported. I commend the authors for their technical correctness, extensive experimentation, and analysis. The performance of the proposed work has been compared with the state-of-the-art approaches which establish the validity of the proposed protocol. However, the authors are suggested to take into account the following issues for further improvement: 1. The introduction contains mostly older references. Hence, the authors are suggested to include a few recent research in this section. 2. The authors could present the existing research regarding multi-hop clustering schemes in WSNs according to the timeline so that a thorough gap analysis could be made. 3. The authors could list the frequently used symbols with their meaning in a table for convenience. 4. The authors are suggested to go through the entire manuscript thoroughly to correct grammatical mistakes. Experimental design: 1. What is the complexity of the proposed algorithm to execute it at runtime? 2. As mentioned in the text, the implementation of the proposed protocol would require a few additional control packet exchanges such as CH advertisement, JOIN message, control packets for next-hop CH selection, etc. It would be appreciable if a comprehensive analysis of control packet overhead for executing the proposed protocol at runtime is presented. 3. It would be better if the input and the output of the proposed GA-based Clustering Algorithm are also mentioned in the algorithm presentations 4. The authors could provide further details regarding experimental setup such as the transmission power used, the initial energy of the advanced nodes and supernodes, the radio model used, the transceiver used, etc. 5. What is the mode of operation of the proposed cluster selection technique? Does every node or any dedicated node will execute the GA-based Clustering Algorithm at runtime? Validity of the findings: 1. The authors could illustrate why the proposed protocol outperforms the existing works while explaining the findings of the experiments. 2. The sink positions could be included in Figure 8 for a better understanding of the findings. The authors may also give a separate plot for analyzing the performance of the proposed protocol for different sink positions. Additional comments: No additional comments

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.

Title: A GENETIC ALGORITHM-BASED ENERGY-AWARE MULTI-HOP CLUSTERING SCHEME FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS Review round: 2 Reviewer: 1

Basic reporting: The authors have addressed my concern and it can be accepted now. Experimental design: The authors have addressed my concern and it can be accepted now. Validity of the findings: The authors have addressed my concern and it can be accepted now. Additional comments: The authors have addressed my concern and it can be accepted now.

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.

Title: A GENETIC ALGORITHM-BASED ENERGY-AWARE MULTI-HOP CLUSTERING SCHEME FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS Review round: 2 Reviewer: 2

Basic reporting: This manuscript is good writing. Experimental design: Good. Validity of the findings: The proposed algorithm is enough innovative. Additional comments: I agree the responds from authors.

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.

Title: A GENETIC ALGORITHM-BASED ENERGY-AWARE MULTI-HOP CLUSTERING SCHEME FOR HETEROGENEOUS WIRELESS SENSOR NETWORKS Review round: 2 Reviewer: 3

Basic reporting: This revised paper is much better now. But it needs major revision due to the following reasons. 1. Please strictly follow this journal template, like alignment, section number etc. 2. Please cite reference papers with increasing references order. 3. In the related works part, it is not suggested to mention each reference paper with 1-2 setences, which is not meaningful. It is suggested to firstly classfy them into several types and then give explanation about their own work (uniqueness). 4. All tables and figures are missiong in the main pdf file. 5. All the symbols are not alligned well. 6. Please change "Where" to "where" and move it to the front on certain line below certain equations. 7. Acknowledgements part is missing. 8. Reference part is weak, and ref. 93 is missing. There are too many so-so references, which is not necessary. And more relevant papers about " energy efficiency and optimization for WSN" is suggested like below. --A PSO based Energy Efficient Coverage Control Algorithm for Wireless Sensor Networks, Computers Materials & Continua，vol.56, no.3, pp.433-446, 2018. --Optimal Coverage Multi-Path Scheduling Scheme with Multiple Mobile Sinks for WSNs, Computers, Materials & Continua, vol.62, no.2, 2020, pp.695-711. -- An Enhanced PEGASIS Algorithm with Mobile Sink Support for Wireless Sensor Networks, Wireless Communications & Mobile Computing, Volume 2018, Article ID 9472075, 2018. --Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G, IEEE Transactions on Industrial Informatics, vol.18, no.3, pp.1939-1948, 2022. --A novel fault tolerance energy-aware clustering method via social spider optimization (SSO) and fuzzy logic and mobile sink in wireless sensor networks (WSNs), Computer Systems Science and Engineering, vol. 35, no.6, pp. 477–494, 2020. --Global levy flight of cuckoo search with particle swarm optimization for effective cluster head selection in wireless sensor network, Intelligent Automation & Soft Computing, vol. 26, no.2, pp. 303–311, 2020. Experimental design: This revised paper is much better now. But it needs major revision due to the following reasons. 1. Please strictly follow this journal template, like alignment, section number etc. 2. Please cite reference papers with increasing references order. 3. In the related works part, it is not suggested to mention each reference paper with 1-2 setences, which is not meaningful. It is suggested to firstly classfy them into several types and then give explanation about their own work (uniqueness). 4. All tables and figures are missiong in the main pdf file. 5. All the symbols are not alligned well. 6. Please change "Where" to "where" and move it to the front on certain line below certain equations. 7. Acknowledgements part is missing. 8. Reference part is weak, and ref. 93 is missing. There are too many so-so references, which is not necessary. And more relevant papers about " energy efficiency and optimization for WSN" is suggested like below. --A PSO based Energy Efficient Coverage Control Algorithm for Wireless Sensor Networks, Computers Materials & Continua，vol.56, no.3, pp.433-446, 2018. --Optimal Coverage Multi-Path Scheduling Scheme with Multiple Mobile Sinks for WSNs, Computers, Materials & Continua, vol.62, no.2, 2020, pp.695-711. -- An Enhanced PEGASIS Algorithm with Mobile Sink Support for Wireless Sensor Networks, Wireless Communications & Mobile Computing, Volume 2018, Article ID 9472075, 2018. --Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G, IEEE Transactions on Industrial Informatics, vol.18, no.3, pp.1939-1948, 2022. --A novel fault tolerance energy-aware clustering method via social spider optimization (SSO) and fuzzy logic and mobile sink in wireless sensor networks (WSNs), Computer Systems Science and Engineering, vol. 35, no.6, pp. 477–494, 2020. --Global levy flight of cuckoo search with particle swarm optimization for effective cluster head selection in wireless sensor network, Intelligent Automation & Soft Computing, vol. 26, no.2, pp. 303–311, 2020. Validity of the findings: This revised paper is much better now. But it needs major revision due to the following reasons. 1. Please strictly follow this journal template, like alignment, section number etc. 2. Please cite reference papers with increasing references order. 3. In the related works part, it is not suggested to mention each reference paper with 1-2 setences, which is not meaningful. It is suggested to firstly classfy them into several types and then give explanation about their own work (uniqueness). 4. All tables and figures are missiong in the main pdf file. 5. All the symbols are not alligned well. 6. Please change "Where" to "where" and move it to the front on certain line below certain equations. 7. Acknowledgements part is missing. 8. Reference part is weak, and ref. 93 is missing. There are too many so-so references, which is not necessary. And more relevant papers about " energy efficiency and optimization for WSN" is suggested like below. --A PSO based Energy Efficient Coverage Control Algorithm for Wireless Sensor Networks, Computers Materials & Continua，vol.56, no.3, pp.433-446, 2018. --Optimal Coverage Multi-Path Scheduling Scheme with Multiple Mobile Sinks for WSNs, Computers, Materials & Continua, vol.62, no.2, 2020, pp.695-711. -- An Enhanced PEGASIS Algorithm with Mobile Sink Support for Wireless Sensor Networks, Wireless Communications & Mobile Computing, Volume 2018, Article ID 9472075, 2018. --Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G, IEEE Transactions on Industrial Informatics, vol.18, no.3, pp.1939-1948, 2022. --A novel fault tolerance energy-aware clustering method via social spider optimization (SSO) and fuzzy logic and mobile sink in wireless sensor networks (WSNs), Computer Systems Science and Engineering, vol. 35, no.6, pp. 477–494, 2020. --Global levy flight of cuckoo search with particle swarm optimization for effective cluster head selection in wireless sensor network, Intelligent Automation & Soft Computing, vol. 26, no.2, pp. 303–311, 2020. Additional comments: No additional comments

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.

Title: A NOVEL AUTOENCODER APPROACH TO FEATURE EXTRACTION WITH LINEAR SEPARABILITY FOR HIGH-DIMENSIONAL DATA Review round: 1 Reviewer: 1

Basic reporting: This work presents a novel method for feature extraction based on Mahalanobis distance defined by the covariance matrix between features. Some comments: - Abstract should be more clear - Separation of graphics from the sequence of the text makes it more difficult to read. - Highlight all assumptions and limitations of your work. - Conclusions should provide some lessons learnt. - Related works section does not mention recent research effors in new approaches to extract meaningful features. Authors are advised to refer to the following related articles to add some discussions: [1] Supervised contrastive learning over prototype-label embeddings for network intrusion detection, Information Fusion, 2022 [3] Effective Feature Extraction via Stacked Sparse Autoencoder to Improve Intrusion Detection System, IEEE Access, 2018 [3] A predictive hybrid reduced order model based on proper orthogonal decomposition combined with deep learning architectures, Expert Systems with Applications, 2022 Experimental design: The design of experiments and the ablation strategy seem correct Validity of the findings: The selection of different datasets and alternative models looks enough to validate the results Additional comments: No additional comments

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.

Title: A NOVEL AUTOENCODER APPROACH TO FEATURE EXTRACTION WITH LINEAR SEPARABILITY FOR HIGH-DIMENSIONAL DATA Review round: 1 Reviewer: 2

Basic reporting: no comment Experimental design: The experimental design of the authors can be accepted. Validity of the findings: The findings demonstrated by the authors are very interesting. Especiallly, distance metric-based methods are more suitable for extracting those features with linear separabilities from high-dimensional data than feature selection-based methods Additional comments: To extract feature from the data in a high-dimensional space, this paper proposed a novel autoencoder approach based on Mahalanobis distance metric of rescaling transformation. Through performing rescaling transformation on Mahalanobis distance metric, then the transformed Mahalanobis distance metric is introduced into the autoencoder, so as to improve the ability of feature extraction to the model. The issue is very interesting, and these findings are valuable. Moreover, the experiments and the results are acceptable through verifying the source code provided by the authors. Based on the studied problem and these findings, I recommend that this paper is acceptable. In addition, to highlight the studied problem and these findings, I suggest the title “A novel autoencoder approach to feature extraction with linear separability for high-dimensional data”

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.

Title: SOME METAHEURISTIC ALGORITHMS FOR SOLVING MULTIPLE CROSS-FUNCTIONAL TEAM SELECTION PROBLEMS Review round: 1 Reviewer: 1

Basic reporting: The highlighted Manuscript is a fair contribution for publication but requires minor improvement init Experimental design: In the abstract, clearly highlight the computational cost section either it time of execution or memory allocation In the proposed optimization model section, the proposed algo must highlight in tabular form Validity of the findings: State of the art comparison is missing in it , it must be a part of this manuscript Additional comments: In the abstract, clearly highlight the computational cost section either it time of execution or memory allocation In the proposed optimization model section, the proposed algo must highlight in tabular form State of the art comparison is missing in it , it must be a part of this manuscript Add few more references of 2019,2020 an 2021 Especially in context of computational cost

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.

Title: SOME METAHEURISTIC ALGORITHMS FOR SOLVING MULTIPLE CROSS-FUNCTIONAL TEAM SELECTION PROBLEMS Review round: 1 Reviewer: 2

Basic reporting: This paper concerns Some Metaheuristic Algorithms for Multiple Cross Functional Teams Selection Problem. We designed metaheuristic algorithms to solve the proposed model, including genetic algorithm (GA) and ant colony optimization (ACO). The authors also compare the developed algorithms with the MIQP-CPLEX solver on datasets of 500 programming contestants on 37skills to evaluate their effectiveness.    I found that the paper owns some new interests: - method is suitable. - the experimental results are quite clear. - datasets are good. - the results are quite promising. However, the paper also has some issues that the authors need to clarify: - The authors should explain why the existing methods in the literature cannot be applied or adjusted to solve the problem?.- The author should describe the GA and ACO in more detail. The author should show the interesting characters in two algorithms. I feel that the authors use the popular and general GA and ACO schemes though it is the first GA and ACO for the problem.- The comparison between the metaheuristic and the exact one is not realistic because they depend on two different types of algorithms. The results of exact algorithms are the optimal solution used to evaluate the efficiency of the metaheuristic.-GA1 is the authors' algorithm for a variant of the problem (Single Team Selection). The authors compare it with the GA of authors. I understand that the authors want to show that the GA algorithm in the paper can solve the variant of the problem well in the literature. The authors should explain the difference in the design of the two algorithms.- The authors should evaluate the efficiency of the proposed algorithm according to gap=(best.sol-OPT)/OPT* 100%. This formulation shows that the difference between the results of the metaheuristic with the optimal values. It is a common formulation used in the metaheuristic field.- The comparison needs to be done in a fair way. Two algorithms run on computers with the same configuration. The authors can count the fitness evaluations? The theoretical complexity is also considered.- Discussion should be added to highlight your contributions and results.  I think the paper has some interesting points. I can be considered to publish if the authors revise well. It should be a major revision. Experimental design: I have described it above Validity of the findings: I have described it above Additional comments: No additional comments

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.

Title: SOME METAHEURISTIC ALGORITHMS FOR SOLVING MULTIPLE CROSS-FUNCTIONAL TEAM SELECTION PROBLEMS Review round: 2 Reviewer: 1

Basic reporting: The manuscript under the title " Some Metaheuristic Algorithms for Multiple Cross-Functional Teams Selection Problem" seems a mature contribution. However, some minor concerns still exist in revised version. Furthermore, grammatical ambiguities exist in the revised version. Experimental design: 1. In Introduction, the background section requires more previous contributions that will be help for readers to understand the domain. Moreover, highlighted the existing problems in the literature is not. satisfactory 2. Authors must write the proposed algorithm in standard logical form and design the flow diagram for actual execution of the proposed algorithm. 3. The Claim of least computational cost is not properly incorporated in revised version . Authors must perform experiments for supporting this claim 4. In context of computational cost, authors must define the cost factor in terms of time of execution and space consumed by executed part. Moreover, authors needs to calculate the BIG O notion if authors claim the time factor in computation cost Validity of the findings: 1.The validation of results is not satisfactory , even no single pictorial representation of the results, authors need to improve the presentation of results section. 2. The state of the art comparison still confusing , authors need to improve the state of the art comparison portion. Additional comments: Authors need to improve the manuscript by fixing the above concerns

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.

Title: SOME METAHEURISTIC ALGORITHMS FOR SOLVING MULTIPLE CROSS-FUNCTIONAL TEAM SELECTION PROBLEMS Review round: 2 Reviewer: 2

Basic reporting: The authors revised all comments well. I think that the work can be published. Experimental design: All experiments are conducted well. Validity of the findings: no comment Additional comments: No additional comments

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.

Title: SOME METAHEURISTIC ALGORITHMS FOR SOLVING MULTIPLE CROSS-FUNCTIONAL TEAM SELECTION PROBLEMS Review round: 3 Reviewer: 1

Basic reporting: The revised manuscript under title " Some Metaheuristic Algorithms for Multiple Cross-Functional Teams Selection Problem" seems good in shape. Authors properly response all the highlighted concern . However, the computational complexity requires slightly improvement for final version of the paper. Please review the below points. 1. Authors must be incorporate the main contributions of the study in the end of introduction 2. In end of introduction section, authors highlight the rest of paper structure in organogram figure for better understanding the flow of the article Experimental design: 1. The conduction of table 2 for computational complexity requires to validate throufgh mathematical modeling. 2. Just presents Table 2 is not enough , authors need to highlight and discuss each step of BIG O notation for GA and ACO algorithm. Validity of the findings: Authors need to present the state of the art in tabular form and clearly discuss the significance of this research. Lastly, authors must highlight the future trends of this research that will be helpful for different research communities for proceeding of this research Additional comments: NA

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.

Title: NINE BEST PRACTICES FOR RESEARCH SOFTWARE REGISTRIES AND REPOSITORIES Review round: 1 Reviewer: 1

Basic reporting: The paper is generally well-written and easy to follow. In terms of literature references, some relevant software archives are not cited, for example, swMATH at https://swmath.org/ , main reference: Greuel, Gert-Martin, and Wolfram Sperber. "swMATH–an information service for mathematical software." International Congress on Mathematical Software. Springer, Berlin, Heidelberg, 2014 and some other archives are cited but only with URLs rather than also with the relevant literature references, e.g, Software Heritage is only cited via URL instead of referencing: Di Cosmo, Roberto, and Stefano Zacchiroli. "Software heritage: Why and how to preserve software source code." iPRES 2017-14th International Conference on Digital Preservation. 2017 similarly, figshare is only mentioned with URL instead of also referencing, among others: Thelwall, Mike, and Kayvan Kousha. "Figshare: a universal repository for academic resource sharing?." Online Information Review (2016). Both swMATH and Software Heritage should also be mentioned in the introduction, together with Zenodo (that does have a proper citation) and FigShare. In the introduction, I recommend to anticipate the introduction of the terminology of "resources and collections", because it is really tiresome to mention "registries and repositories", up to that point in the paper. Also, the authors should probably decide between "resources" and "collections" and be consistent about that. In section 2, Background, "RDA" and "FORCE11" needs references, as they might not be familiar to all readers. When mentioning "tools have been developed to facilitate depositing research data", other platforms should be mentioned, such as Zenodo, Software Heritage, and other services like the HAL preprint service that now supports depositing source code as well. At the end of the section, I find it incorrect to say that you "address the needs of domain software registries and repositories", because you are just providing guidelines. Maybe you can tone down this claim a little. Regarding the presentation of the best practice, it is hard to cross-reference the concrete example of each best practice to the end in the appendix. I recommend including at least 1-2 examples *inline* in the main paper text just after each best practice, and cross-reference the appendix for *other* examples. That way the main text of the paper become self-contained (and more interesting!) and the appendix can be consulted only for those readers who want more. (This is a comment critique/suggestion that applies to all best practices, as they all have examples; which is definitely a good thing!) As a minor point, the author list is inconsistent between the submission system and the paper; the latter also includes "Task Force on Best Practices for Software Registries, and SciCodes Consortium". As these are not proper authors, they should not be listed as such, but rather included in the acknowledgments. Experimental design: Section 3 is a bit disappointing, in the sense that it reads like poorly presented results of a survey. You should document what were *all* the questions asked, not just a few of them ("questions [...] included") and detail what answers you got in the usual way (descriptive statistics, etc.), otherwise it would be hard to assess the pertinence of the methodology followed to arrive at the guidelines, and this would appear to be just a position paper by the authors. Validity of the findings: About the specific best practices: 4.1: the wording is weird, the main point is the first one ("What is accepted"), the other two points feel just redundant restatement of the same notion ("what is not accepted" -> complement of the first point; and "notable exceptions" -> which is still a part of the notion of "what is accepted"). Maybe you should recommend that resources operators just focus on the properties/criteria of the artifacts that are acceptable, rather than restating the same notion in different ways. 4.3: the wording of "required and optional metadata" is weird, because it centers on the fact that metadata comes "from software contributors". Shouldn't this be worded as "required and optional metadata expected for deposited software"? Metadata are about the software, and the operators should care that they exist, no matter who contribute them. 4.4 "Also, particular care should be taken to maintain the consistency of this policy with the citation policies for the registry or repository." -> I have no idea what this means, it should be better explained/clarified in the text. 4.5 "share your metadata schema" -> "share" should be "publish" or "document", as it's really about making it public, not sharing with others. "This practice when implemented should specify:" -> drop "when implemented", which feels like a truism that could be said for any of the best practices. 4.6 this best practice is almost entirely worded about metadata, and that seems incorrect to me. The conditions of use are relevant for both metadata and the data itself (e.g., actual software, for software repositories). The text of this should be generalized to cover both scenarii on equal footing, maybe adopting the syntactic convention of "(meta)data" when talking about both, as the FAIR Principles do. 4.7 include passages like (emphasis mine) "Additionally, one *can* list explicitly the third-party tools" and "a mechanism by which users can request the removal of such information *may* be described". In a guideline document, I have a hard time understanding what those two modal verbs mean. Should the resource operators include those information or not? I recommend that the authors take a stance on this point. (Or else describe the precise semantics of the various modal verbs use, e.g., in the style of RFC 2119.) All this would make the guidelines much more actionable for resource operators. 4.8 When discussing taking offline data and archival, I consider there is an important omission: the requirement of documenting the backup strategy (which commonly goes under the notion of "retention policy") and how the archive reacts to legal takedown notices (e.g., due to DMCA in the US or, in Europe, equivalent legislation as well as GDPR). 4.9 When mentioning the Zenodo example, it would be nice to mention in the paper to where data will be migrated, in addition to the fact that they will be migrated. Additional comments: No additional comments

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.

Title: NINE BEST PRACTICES FOR RESEARCH SOFTWARE REGISTRIES AND REPOSITORIES Review round: 1 Reviewer: 2

Basic reporting: no comment Experimental design: no comment Validity of the findings: no comment Additional comments: I really appreciate the efforts by the Task Force of FORCE11 SCIWG to come up with the nine best practices for researching software registries and repositories, as well as the clear, well-structured report presented here that provides sufficient context to justify its significance. I have only a few minor comments listed below. - In lines 151–155, the authors mention that the Task Force gathered information from its members to learn more about each resource and identify overlapping practices. I would encourage the authors to provide a simple visualization of their survey results as the basis for developing best practices. - Similar to the previous point, the authors mention in lines 483–486 that they observe different adoption rates for best practices upon internal discussion. It would be great if the authors could provide some simple statistics (preferably with visualizations) to let the reader know the status quo. - Lastly, since the authors mention in lines 487–490 that their effort complements and aligns well with recent guidelines developed for data repositories, it would be interesting to learn the actual similarities and differences between best practices developed by the two communities. Overall, the nine best practices proposed here are quite comprehensive and tackle many important issues within the broader research community. I look forward to future impact tracking and assessments undertaken by SciCodes.

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.

Title: NINE BEST PRACTICES FOR RESEARCH SOFTWARE REGISTRIES AND REPOSITORIES Review round: 2 Reviewer: 1

Basic reporting: no comment Experimental design: no comment Validity of the findings: no comment Additional comments: I would like to first commend the authors' efforts in addressing the reviewers' questions in detail and revising their manuscript accordingly. While I'm overall satisfied with the revision, if I had to be picky, I would suggest the authors integrate what is currently in Appendix C into the Methodology section. Both Reviewer #1 and I urged the authors to provide descriptive statistics and/or visualization of their initial survey results to substantiate the empirical grounds of this paper, but the rewritten Methodology section primarily supplies procedural details rather than survey details we have requested. For instance, lines 154--156 can be re-written as: Participants introduced themselves and their resources by providing some basic information, including repository name, starting year, number of records, target audience (discipline-specific or general), as well as services provided (e.g., support of software citation, software deposits, and doi minting). Figure/Table 1 presents an overview of the responses. Question | Yes | No | Other --- | --- | --- | --- Q1 | raw count (%) | raw count (%) | raw count (%) Q2 | raw count (%) | raw count (%) | raw count (%) You can then briefly comment on the results and direct readers to Appendix C for the full list of questions and other summaries of the results if available (e.g., distribution of supported unique identifier types, number of records, and years when the repository started operating). On a second thought, it seems more appropriate to use a table instead of a figure to present the results, which saves space, but the final decision should be at the authors' discretion. If a figure is still preferred, I would encourage the authors to experiment with other types of visualization such as a stacked bar chart or a divergent stacked bar chart. The rationale is that we know the responses for each question sum to 30 anyway, and there are only three possible answers for each (Yes/No/Other), so there is no real benefit of having separate bars to represent possible answers for each question. Other minor points - The quotation marks in lines 1018--1019 do not look right, possibly an issue related to LaTex.

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.

Title: NINE BEST PRACTICES FOR RESEARCH SOFTWARE REGISTRIES AND REPOSITORIES Review round: 3 Reviewer: 1

Basic reporting: As a general comment for the authors and editors, there seems to be a process failure here. I have reviewed v0 of this paper and I'm not reviewing v2. There seem to have been a v1 in between, which I have not reviewed. As a consequence of that I have seen neither the tracked changes between v0 and v1, nor the rebuttal for v1 (which presumably included author answers to my initial remarks). Hence in this review I'm solely pointing out which parts of my initial review for v0 are still not addressed. This is not due to a fault of the authors, but of the review process. Still, as a reviewer, I have to insist on the points for which I have received neither an answer nor a change. ----------------- Regarding basic reporting, the only remaining unaddressed point is this: > Regarding the presentation of the best practice, it is hard to cross-reference the concrete example of each best practice to the end in the appendix. I recommend including at least 1-2 examples *inline* in the main paper text just after each best practice, and cross-reference the appendix for *other* examples. That way the main text of the paper become self-contained (and more interesting!) and the appendix can be consulted only for those readers who want more. (This is a comment critique/suggestion that applies to all best practices, as they all have examples; which is definitely a good thing!) Experimental design: No remaining unaddressed points from my initial review remains about experimental design. It's all good! Validity of the findings: The following points of my initial review for v0 remains unaddressed (and are in fact the main reason why I am recommending a major revision): > 4.1: the wording is weird, the main point is the first one ("What is accepted"), the other two points feel just redundant restatement of the same notion ("what is not accepted" -> complement of the first point; and "notable exceptions" -> which is still a part of the notion of "what is accepted"). Maybe you should recommend that resources operators just focus on the properties/criteria of the artifacts that are acceptable, rather than restating the same notion in different ways. > 4.4 "Also, particular care should be taken to maintain the consistency of this policy with the citation policies for the registry or repository." -> I have no idea what this means, it should be better explained/clarified in the text. > 4.5 "share your metadata schema" -> "share" should be "publish" or "document", as it's really about making it public, not sharing with others. > 4.6 this best practice is almost entirely worded about metadata, and that seems incorrect to me. The conditions of use are relevant for both metadata and the data itself (e.g., actual software, for software repositories). The text of this should be generalized to cover both scenarii on equal footing, maybe adopting the syntactic convention of "(meta)data" when talking about both, as the FAIR Principles do. > 4.8 When discussing taking offline data and archival, I consider there is an important omission: the requirement of documenting the backup strategy (which commonly goes under the notion of "retention policy") and how the archive reacts to legal takedown notices (e.g., due to DMCA in the US or, in Europe, equivalent legislation as well as GDPR). Additional comments: Other than the above points, the authors did a good job at improving the paper. Thanks a lot for addressing all the (other) points I had raised in my initial review. I'm looking forward to this article finalization.

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.

Title: NINE BEST PRACTICES FOR RESEARCH SOFTWARE REGISTRIES AND REPOSITORIES Review round: 3 Reviewer: 2

Basic reporting: no comment Experimental design: no comment Validity of the findings: no comment Additional comments: I noticed that the time of the inaugural Task Force meeting (February 2019) is different from the date shown in the Table 1 caption (November 2019). I was wondering if this was a random mistake or if the responses were actually collected later. Other than that, all the previous comments have been adequately addressed, and the manuscript can be accepted in its current form.

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.

Title: DATA AUGMENTATION AND DEEP NEURAL NETWORKS FOR THE CLASSIFICATION OF PAKISTANI RACIAL SPEAKERS RECOGNITION Review round: 1 Reviewer: 1

Basic reporting: In this study, the authors present a data augmentation method that shifts the pitch, uses multiple window sizes, stretches the time, and adds white noise to the original audio. The presented subject is undoubtedly attractive. Just the presented study might be somewhat weak in innovation. Frankly, the proposed approach might not be technically sound. Experimental design: Transfer from previous research to deep neural networks, more like an MLP (multilayer perceptron), which stacks too many “Dropout” and “ReLU” layers, which might be somewhat unintelligible. Data augmentation for fitting deep learning has been well-known efficacy most of the time. Validity of the findings: Problem formation of this study might not be credible. Therefore, the authors are required to address the potential of the presented study based on speech emotion recognition. Particularly, making necessary efforts to let the presented novelties much more recognizable by other scholars. Additional comments: None

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.

Title: DATA AUGMENTATION AND DEEP NEURAL NETWORKS FOR THE CLASSIFICATION OF PAKISTANI RACIAL SPEAKERS RECOGNITION Review round: 1 Reviewer: 2

Basic reporting: The paper addresses an interesting problem of Speech Emotion Recognition. Leveraging Deep Neural Networks, it proposes a technique to classify multiple Urdu language accent speakers. While the evaluation and analysis of the proposal show promising results, the language and structure (elaborated in **Additional Comment**) of the paper makes it extremely hard to read thus hindering fluency and comprehension. I really appreciate the authors' efforts to share the code with the research community. I believe this will help further research and reproducibility of the proposed technique. It would be more beneficial if the author share the dataset (**Augmented Dataset**) for end-to-end reproducibility of the results. Experimental design: No comment Validity of the findings: Although the authors reported the results of the analysis, a comparison with related work would really help the validation of the findings. Also, it would be interesting to validate the results in different multilingual settings with lower vs. high pitches of multiple speakers etc. Additional comments: Language, Structure and Sign-posting: The lack of structure, use of confusing language, and absence of sign-posting made this paper a bit harder to read. For instance, in the abstract, you first need to clearly define the problem and mention why it is important to solve it. You also need to sign-post your take on related work and the need for an improved, efficient mechanism to solve the problem. You then need to structure and briefly present your technique and salient features (i.e., some results). At the end you need to highlight the key takeaway(s) from your research. The aforementioned structure could be followed throughout the (sub)sections of the paper. From the abstract, it is not clear how and why SER is a complex issue? For clearer readability, perhaps, you may define SER before terming it as a complex issue. Once defined, you can then pin-point the complexity and attribute it to the main component(s) in SER. What do you mean by limited database? Do you mean a limited number of speech emotion dataset? You need to clarify why **seven**-layer framework was employed? Why not less or greater than **seven** a layer framework was used? Introduction: Please structure your introduction as per suggestion mentioned above. Please consider restructuring the last paragraph of Introduction. For instance, "This report (--> paper) is divided .... about the conclusion of the research outcomes." could be a separate paragraph. What do you mean by "numerous investigations"? Is numerous equals 10, 100, 1,000, etc? Related Work: - "Many countries ..." need to be correctly sign-posted. Countries do no research. Rather researchers investigate problems. Having too many references without proper discussion or structure of the reference is concerning. Please avoid tangential references and cite the key, related work. Data Augmentation I think this section should be renamed as Data Manipulation as some techniques such as "Pitch Shifting" can not be termed as data augmentation technique. "Pitch Shifting" is a perturbation technique rather than data augmentation. Please duplicate references e.g.,: Please consider restructuring this section as the first paragraph is way too long and hard to read. Methodology: What does **0:42* represented in Table 2 (in Column, "Duration per sample")? Please keep consistency when reporting numbers or data in tables. Salamon, J. and Bello, J. P. (2016). Deep convolutional neural networks and data augmentation for environmental sound classification. CoRR, abs/1608.04363. Salamon, J. and Bello, J. P. (2017a). Deep convolutional neural networks and data augmentation for environmental sound classification. IEEE Signal Processing Letters, 24(3):279–283. Salamon, J. and Bello, J. P. (2017b). Deep convolutional neural networks and data augmentation for environmental sound classification. IEEE Signal Processing Letters, 24(3):279283. - And the following Damskgg, E.-P. and Vlimki, V. (2017a). Audio time stretching using fuzzy classification of spectral bins. Applied Sciences, 7(12):1293. Damskgg, E.-P. and Vlimki, V. (2017b). Audio time stretching using fuzzy classification of spectral bins. Applied Sciences, 7(12). Misc: It would be great if you could minimize the use of **passive voice**. In most of well-written, readable CS paper use **active voice** for improved communication. Please align Table 7 with text-width size. You may reduce the width of column # 1 and column # 3.

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.

Title: CAUSAL GRAPH EXTRACTION FROM NEWS: A COMPARATIVE STUDY OF TIME-SERIES CAUSALITY LEARNING TECHNIQUES Review round: 1 Reviewer: 1

Basic reporting: A good article which presents a novel framework for extracting causal graphs from digital text media that are selected from a domain under analysis by applying specially developed information retrieval and natural language processing methods. The framework is applied to the New York Times dataset, which covers news for a period of 246 months. The proposed analysis offers valuable insights into the problems of identifying topic-relevant variables from large volumes of news and learning causal graphs from time series. A. Normally, the Abstract and beginning of an introduction section contain the problems in the existing approaches followed by the solution but in this article, the problem statement is somehow not discussed. B. In the introduction, the proposed work starts from line 48 then in between (lines 53-55) the works of the other authors came. - It will be nice to have if existing work is discussed in one place followed by proposed work. In this way, the reader will have a good understanding of the work. C. The employed dataset is consisting of 246 month period. - Why not this period is mentioned in years. So that each reader doesn’t have to calculate it. D. How research questions have been formulated/reached? Normally, this is done after an extensive literature review but in this article, it seems some sort of reverse engineering is being done e.g., research questions are mapped to literature. E. In the related work section, existing research is being discussed but shortcomings of each work are not highlighted. These shortcomings ultimately lead to research questions. F. Figure 2 can be improved. At the moment, it is a bit congested. E.g., step 2 and step 5 converge at a point that is not very clear to the reader. G. Line # 200, a topic is said to be relevant if it contains mention - This is a big assumption because it is not necessary to have mentioned it in all cases. H. Line # 221, what is BERT embeddings? I. Line # 248, the selected topic has the highest number of mentions in the corpus. - Is this a biased input to the proposed framework? What if the selected topic has the lowest number of mentions? How proposed framework will behave in this scenario? J. Why scale-free and random forward DAGs are used? K. The conclusion section contains the summary of the paper in the first two paragraphs which should not be there because this is repeating stuff again and again. L. In future work, integration of this work with some visual tools is mentioned. - For example? Experimental design: Experimental design is aligned with the proposed methodology with enough details to reproduce the results. For example, the code written in python language with sufficient comments is made public for use: https://cs.uns.edu.ar/~mmaisonnave/resources/causality/code/ Maisonnave et al 2020 - Event Detection.ipynb - Colaboratory (google.com) Use case evaluation.ipynb - Colaboratory (google.com) Validity of the findings: All underlying data have been provided with a well-stated discussion. Economic Relevant News from The Guardian - Mendeley Data Maisonnave et al 2020 - FDD paper.ipynb - Colaboratory (google.com) Additional comments: No additional comments

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.

Title: CAUSAL GRAPH EXTRACTION FROM NEWS: A COMPARATIVE STUDY OF TIME-SERIES CAUSALITY LEARNING TECHNIQUES Review round: 1 Reviewer: 2

Basic reporting: The paper presents a framework for extracting causal graphs from digital text media. It consist of 8 steps that goes from analyzing the text of news to filter topical-relevant sentences, discover events and construct time series to learn a causal structure among variables. The framework is a valuable contribution for the area as it describe all the process starting from raw text to achieve an actual graph structure of events, providing a concrete technique for each of the steps so that it can be effectively operationalized. The paper is in general well-written and explained. There are some issues that can be improved regarding organization. First, the place of the section “Causal structure learning” is a little misleading, since such learning is just a part of the framework and the last step (not yet introduced at that point), also only mentions existing state-of-the-art algorithms, I think it can be place in the description of step 8 or later. Second, in each step of the framework, although a technique is chosen and described, it would be interesting to mention other alternatives that can take their place in the framework and justify the selection. Other details: - in step 1 it is mention the use of n-grams, but the examples only have single terms. (e.g. United, States). Why not 2-grams for instance? or NER entities? - the role of Beta within the framework in step 2 should be clarified, which is the rationale of its value in the framework? In this setting, it is preferred descriptive or discriminative terms? - in step 3, the event trigger consist of a single word? Which is the effect of using a unique word in this context of a huge volume of texts? - step 5, the elbow method provide a suggestion for the number of clusters, it this done automatically? All clusters are considered or some small ones can be discarded? - in the case study, it said “sixteen variables”, should be 6? Experimental design: The experimentation with a framework such as the one proposed by the authors is difficult because of the lack of ground truth. Therefore, the evaluation with the Iran case study, which was used previously for illustrating the example is valuable. I think the data generated for the case study should be also considered a contribution of the work. The evaluation with synthetic data of the causal learning technique is again a little out of the focus of the paper, as it only proves which learning algorithms works well with the generated synthetic data, but it is not really the type of data used in the framework. Therefore, it looks more a general evaluation of algorithms unrelated to the framework itself. Validity of the findings: The findings are interesting and demonstrate that the framework can be operationalized and used to analyze real data. Some additional comments to help to highlight the paper contribution: - the practical implications of the framework can be discussed, probably in the conclusions. As it can be a valuable tool for analysis, potential scenarios and uses can be identified. - another aspect to discuss is the level of user intervention that is needed for using the framework, the iterations required and setting of parameters, also some guidelines for their application can be provided - as the paper introduced some research questions at the beginning it would be important to go back to them in the discussion/conclusions to summarize the findings Additional comments: No additional comments

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.

Title: CAUSAL GRAPH EXTRACTION FROM NEWS: A COMPARATIVE STUDY OF TIME-SERIES CAUSALITY LEARNING TECHNIQUES Review round: 2 Reviewer: 1

Basic reporting: Looking good now. Experimental design: Ok. Validity of the findings: Fine. Additional comments: 12 questions were raised related to basic reporting. In the revision, most of them are addressed. I think, document is good to go now.

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.

Title: CAUSAL GRAPH EXTRACTION FROM NEWS: A COMPARATIVE STUDY OF TIME-SERIES CAUSALITY LEARNING TECHNIQUES Review round: 2 Reviewer: 2

Basic reporting: The paper presents a framework for extracting causal graphs from digital text media, considering the analysis of big volumes of text. The contribution is interesting and the resulting framework provides a good starting point for experimentation with causal learning from social media. The revised version of the paper has been improved regarding clarity of the contribution, analysis of research questions and implications of the work. I still think that the related works section should highlight further the advantages of the approach and potential applications which are not covered by previous works in the literature. The description of the main steps of the frame work have also been improved, making more clear the scope of the individual techniques and their alternatives. Experimental design: The experimental evaluation performed with real world data is valuable and provide evidence that the framework can perform well when applied to real data. The authors also clarify the role of the evaluation of synthetic data as a first step to discard some options. Validity of the findings: The findings have been validated with the experimental evaluation on real-world data. The revised version also discuss the conclusions regarding the research questions as asked and the practical implications of the work presented. Additional comments: The authors have addressed all my concerns in this revised version, I think the paper has been considerably improved.

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.

Title: MOBILE PHONE ENABLED MENTAL HEALTH MONITORING TO ENHANCE DIAGNOSIS FOR SEVERITY ASSESSMENT OF BEHAVIOURS: A REVIEW Review round: 1 Reviewer: 1

Basic reporting: The article meets the appropriate standards. Extensive references, the writing is clear and tables and figures are adequate. Experimental design: The study design is correct. But it is necessary to explain in more detail the selection criteria of the chosen literature. It should also go deeper into the characteristics of the non-selected literature. They must justify the selective criteria regarding the databases used and those not used. For example, why haven't you used The Web of Science or Scopus? And offer information on the name of the publications with articles on the subject, with data on the number of publications per year, etc. Validity of the findings: It is necessary to compare results with other similar existing studies. Emphasizing the coincidences and divergences on the results obtained. A critical reflection on the limitations of smartphones and passive devices to analyze personal health data is also necessary. Attention to bioethical limits, privacy, and confidentiality. Do you start from the fact that the smartphone user freely allows being monitored? The use of smartphones for diagnostic evaluation has social, economic, and cultural limitations. Authors should keep this fact in mind. It is not possible to generalize passive monitoring to produce data in athletes when we refer to data monitoring in cases of people with medical pathologies or social inclusion problems. Sick or socially vulnerable people have different behaviors. I suggest a greater emphasis on the discussion of the results and the limitations of the study carried out. Additional comments: No additional comments

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.

Title: MOBILE PHONE ENABLED MENTAL HEALTH MONITORING TO ENHANCE DIAGNOSIS FOR SEVERITY ASSESSMENT OF BEHAVIOURS: A REVIEW Review round: 1 Reviewer: 2

Basic reporting: 1. Literature in the field of public health has moved away from using the term “mental disorder” and towards “mental health issues” to avoid stigmatizing those affected. I would recommend adapting this language (e.g., in the abstract). 2. Kindly review the full manuscript for grammatical errors and sentence structure. In some areas the language is inconsistent (i.e., use of terms depression vs. psychological health issues) and can be simplified (i.e., lines 96-97). 3. The results organization is unclear and difficult to follow. The manuscript would benefit from clearly outlining the scoping review goal and specific sub-questions to enable this format to be followed in the results. 4. Overall, the manuscript text can be tightened to align more closely with the subheadings and avoid repetition throughout. For example, the purpose of digital tools for mental health assessment does not need to be repeated in the ‘Search Strategy’ subsection as this has been established in the Introduction. 5. Typically scoping reviews include a review of the grey literature. Given the focus on peer-reviewed literature, this could be categorized as a systematic review. Experimental design: 1. References are required in the first paragraph (lines 89-91). 2. The search strategy section can be more clearly organized to remind the reader of the key research question for the scoping review, search parameters (date range, databases), and inclusion and exclusion criteria. Currently information like the timeline (Jan 2015-Dec 2020) is repeated twice. 3. The additional rationale provided in the first few sentences is already in the introduction, and is not required again in this section. 4. Please note how many reviewers participated in the article screening process, and how/if any disagreements in the shortlist were resolved (i.e. consensus exercise). Validity of the findings: 1. Line 130 is unclear, what is “explicit human contact with the monitoring system?” 2. Please describe Figure 2 in greater detail. How was the framework compiled? Why is it organized as such? What do the acronyms used under Self-Report stand for? 3. The results can be organized for a clearer presentation. Additional text (i.e., lines 142-145, 288-290) distract from the results and should only be noted in the discussion section. 4. Please bold the first row in all Tables to distinguish the column headers. Additional comments: Abstract: 1. The second sentence is unclear, how does the severity of mental health issues lead to observations of people through smartphones? The point about potential for smartphone-based data collection in the abstract can be communicated more concisely to improve clarity. Introduction 1. The introduction requires references for many of the statements made in the first paragraph. Please review lines 36-53 and include references throughout. 2. Line 84 notes “estimating depression” however the introduction suggests that a range of psychiatric conditions are included in this review. Please refine the language based on the scoping review focus. 3. Two goals are mentioned in the Introduction (lines 68 and again on lines 80-81). This section would benefit from organizing to indicate perhaps the overarching goal (i.e., to develop a framework) informed by a scoping review. The text currently framed as the scoping review goal could be reformatting as the primary research question of the review. The list provided on lines 72-78 can be reformatted as objectives. Discussion 1. Tables and figures are typically not placed in the Discussion section. Please move Tables 9 and 10 to the Results section and revise the discussion accordingly. Conclusions 1. The conclusion section makes no mention of mental health issues which is meant to be the focus of this systematic review.

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.

Title: MOBILE PHONE ENABLED MENTAL HEALTH MONITORING TO ENHANCE DIAGNOSIS FOR SEVERITY ASSESSMENT OF BEHAVIOURS: A REVIEW Review round: 2 Reviewer: 1

Basic reporting: What doe it mean by the statement at lines 93-94 and a number of research articles selected from the various databases to “fine” the research work. Please carefully read the article and remove these major mistakes. Table 1 seems to be ambiguous, can you elaborate on how this table has been formed? Your search query resulted in 943 manuscripts, but I am unable to find any automatic way to filter out these articles, have you read them manually and then selected the shortlisted articles or what? Please explain Please write the complete name of figures in texti e.g. Fig might not be appropriate. At some places, it is complete e.g at line 138. Please make sure it should be consistent. Please explain the steps in figure 1, the data flow diagram. All the steps were performed manually? The literature review article should be a comprehensive study of relevant studies and their findings and recommendations for the readers. Unfortunately, these things seem to be lacking in the current article There are lots of typos and grammatical mistakes; some of them are as follows This physiological issues needs to be consistently observed on the people, could be. These physiological issues need to be consistently observed in the people …. Thus, the aim of this comprehensive work concentrates on the literature work done so far in the prediction of mental heath issues, what is “heath” in this one ? Experimental design: What doe it mean by the statement at lines 93-94 and a number of research articles selected from the various databases to “fine” the research work. Please carefully read the article and remove these major mistakes. Table 1 seems to be ambiguous, can you elaborate on how this table has been formed? Your search query resulted in 943 manuscripts, but I am unable to find any automatic way to filter out these articles, have you read them manually and then selected the shortlisted articles or what? Please explain Please write the complete name of figures in texti e.g. Fig might not be appropriate. At some places, it is complete e.g at line 138. Please make sure it should be consistent. Please explain the steps in figure 1, the data flow diagram. All the steps were performed manually? The literature review article should be a comprehensive study of relevant studies and their findings and recommendations for the readers. Unfortunately, these things seem to be lacking in the current article There are lots of typos and grammatical mistakes; some of them are as follows This physiological issues needs to be consistently observed on the people, could be. These physiological issues need to be consistently observed in the people …. Thus, the aim of this comprehensive work concentrates on the literature work done so far in the prediction of mental heath issues, what is “heath” in this one ? Validity of the findings: What doe it mean by the statement at lines 93-94 and a number of research articles selected from the various databases to “fine” the research work. Please carefully read the article and remove these major mistakes. Table 1 seems to be ambiguous, can you elaborate on how this table has been formed? Your search query resulted in 943 manuscripts, but I am unable to find any automatic way to filter out these articles, have you read them manually and then selected the shortlisted articles or what? Please explain Please write the complete name of figures in text e.g. Fig might not be appropriate. At some places, it is complete e.g at line 138. Please make sure it should be consistent. Please explain the steps in figure 1, the data flow diagram. All the steps were performed manually? The literature review article should be a comprehensive study of relevant studies and their findings and recommendations for the readers. Unfortunately, these things seem to be lacking in the current article There are lots of typos and grammatical mistakes; some of them are as follows This physiological issues needs to be consistently observed on the people, could be. These physiological issues need to be consistently observed in the people …. Thus, the aim of this comprehensive work concentrates on the literature work done so far in the prediction of mental heath issues, what is “heath” in this one ? Additional comments: this paper needs serious level improvements for re-consideration

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.

Title: MOBILE PHONE ENABLED MENTAL HEALTH MONITORING TO ENHANCE DIAGNOSIS FOR SEVERITY ASSESSMENT OF BEHAVIOURS: A REVIEW Review round: 3 Reviewer: 1

Basic reporting: the author have made no change in Table1 , as track version and updated version is not showing at least. my question was to make it clear, they wrote in rebuttal but makes no changes in the actual table ???Thanks for your comments. We used search queries to retrieve 6 databases. Figure 1 depicts the steps we use followed to include the articles which meet the selection criteria. Please see Figure 1 for more details., another ambiguous answer, the actual comment was Your search query resulted in 943 manuscripts, but I am unable to find any automatic way to filter out these articles, have you read them manually and then selected the shortlisted articles or what? Please explain manual scanning of 963 articles seems to be a very hectic and tedious task, and almost impossible it is difficult to judge why the authors have added RELEVANT WORKS section ? figure 4 is not properly cited please re-structure the overall document in a proper article hierarchy and then resubmit Experimental design: the author have made no change in Table1 , as track version and updated version is not showing at least. my question was to make it clear, they wrote in rebuttal but makes no changes in the actual table ???Thanks for your comments. We used search queries to retrieve 6 databases. Figure 1 depicts the steps we use followed to include the articles which meet the selection criteria. Please see Figure 1 for more details., another ambiguous answer, the actual comment was Your search query resulted in 943 manuscripts, but I am unable to find any automatic way to filter out these articles, have you read them manually and then selected the shortlisted articles or what? Please explain manual scanning of 963 articles seems to be a very hectic and tedious task, and almost impossible it is difficult to judge why the authors have added RELEVANT WORKS section ? figure 4 is not properly cited please re-structure the overall document in a proper article hierarchy and then resubmit Validity of the findings: the author have made no change in Table1 , as track version and updated version is not showing at least. my question was to make it clear, they wrote in rebuttal but makes no changes in the actual table ???Thanks for your comments. We used search queries to retrieve 6 databases. Figure 1 depicts the steps we use followed to include the articles which meet the selection criteria. Please see Figure 1 for more details., another ambiguous answer, the actual comment was Your search query resulted in 943 manuscripts, but I am unable to find any automatic way to filter out these articles, have you read them manually and then selected the shortlisted articles or what? Please explain manual scanning of 963 articles seems to be a very hectic and tedious task, and almost impossible it is difficult to judge why the authors have added RELEVANT WORKS section ? figure 4 is not properly cited please re-structure the overall document in a proper article hierarchy and then resubmit Additional comments: the author have made no change in Table1 , as track version and updated version is not showing at least. my question was to make it clear, they wrote in rebuttal but makes no changes in the actual table ???Thanks for your comments. We used search queries to retrieve 6 databases. Figure 1 depicts the steps we use followed to include the articles which meet the selection criteria. Please see Figure 1 for more details., another ambiguous answer, the actual comment was Your search query resulted in 943 manuscripts, but I am unable to find any automatic way to filter out these articles, have you read them manually and then selected the shortlisted articles or what? Please explain manual scanning of 963 articles seems to be a very hectic and tedious task, and almost impossible it is difficult to judge why the authors have added RELEVANT WORKS section ? figure 4 is not properly cited please re-structure the overall document in a proper article hierarchy and then resubmit

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.

Title: IS GENDER-BASED VIOLENCE A CONFLUENCE OF CULTURE? EMPIRICAL EVIDENCE FROM SOCIAL MEDIA Review round: 1 Reviewer: 1

Basic reporting: The topic of research is really interesting. But I found a few lacking in the paper. Experimental design: The author didn't mention the flow chart of the proposed work. Proposed work must explain step by step according to the flow chart. Secondly, What is the novelty of this work Third, whether this entire work is study or research work. Somewhere author mentions it's as a study and somewhere he mentions it's a study. Kindly go with a strong proofread of your paper. Validity of the findings: Not satisfactory Additional comments: Once again author must revise this manuscript and submit it again.

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.

Title: IS GENDER-BASED VIOLENCE A CONFLUENCE OF CULTURE? EMPIRICAL EVIDENCE FROM SOCIAL MEDIA Review round: 1 Reviewer: 2

Basic reporting: Paper is clear and understandable. Format and structure of the manuscript is very clear. Experimental design: Experimental methodology is discussed very clearly. No need for any updation. Validity of the findings: Novelty exist in the paper, which impact to the credibility of the author. Additional comments: Again appreciating the work done by the author. Nice work and structured manuscript.

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.

Title: IS GENDER-BASED VIOLENCE A CONFLUENCE OF CULTURE? EMPIRICAL EVIDENCE FROM SOCIAL MEDIA Review round: 1 Reviewer: 3

Basic reporting: 1. Authors are required to improve the English language and some sentence structures need to be updated. 2 In some sections authors have written too many paragraphs for expressing their views. Need to update the style with some professional writing style. 3 Provide expanded from of abbreviations wherever used for the first time. 4. Make your Introduction section more technical than in the current form it just focuses on the basics of fog computing. Experimental design: 1- The calculation of the fitness value is not clarified in the proposed method. 2- More details are needed to clarify the proposed method flow chart. 3-Please check the proofreading of the paper Validity of the findings: 4-The quality of the article should be improved by giving more details about the contribution 5- The problem formulation part is not well-organized and the added value must be well described Additional comments: 6- The references are applicable but are not sufficient

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.

Title: IS GENDER-BASED VIOLENCE A CONFLUENCE OF CULTURE? EMPIRICAL EVIDENCE FROM SOCIAL MEDIA Review round: 2 Reviewer: 1

Basic reporting: 1.Given header keywords in Table 1, together with any heading, and all table perimeter names. 2. Authors have improved the language. 3. References have been updated to include some more recently published work. Figures are OK. Experimental design: The authors have carried out the various experiments as per identified problem statement. Validity of the findings: 5. They have updated the methodology section accordingly. Additional comments: No additional comments

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.

Title: HIGH-DIMENSIONAL NORMALIZED DATA PROFILES FOR TESTING DERIVATIVE-FREE OPTIMIZATION ALGORITHMS Review round: 1 Reviewer: 1

Basic reporting: - Mathematical notation in page 2 is not standard in the DFO literature. Please use widely-used mathematical notation. - Capitalize the first letter in "equation" - "The HNM algorithm proved to deliver better performance than the traditional NM algorithm, represented by a famous Matlab function, known as ”fminsearch” Musafer and Mahmood (2018)". fminsearch has not been proposed by Musafer and Mahmood (2018), it is the classic NM algorithm. - "From the table, ...". Please provide references to all figures/tables. - The English language can be improved. Some examples where the language could be improved include lines 222 and 292 – the current phrasing makes comprehension difficult. - A readme file is needed in the Supplemental_File.zip in order to be able to find out where to find the codes and problem files. Experimental design: - "The standard parameter values for usual delta d_u and for zero term delta d_z are chosen 0.05 and 0.00025 respectively". Please justify. - The test functions have not been presented in the text. More importantly, all these problems have only a few variables. The authors need to consider much larger problems. - What's the purpose of the computational study? Why not compare against efficient DFO algorithms (e.g., NOMAD)? Validity of the findings: No comment Additional comments: The paper is interesting. However, I am confused about its scope. Looking at the title of the paper (High-dimensional normalized data profiles for testing derivative-free optimization algorithms), I would expect that the authors propose a new tool (similar to data profiles) for comparing DFO algorithms. However, this is not the case since the authors are proposing five sequences of trigonometric simplex designs for high dimensional unconstrained optimization problems. Therefore, the authors need to focus on this and only present normalized data profiles as a mean to compare their algorithm. Thus, I believe that the authors need to restructure their paper in order to make this clear. Finally, the computational results are weak. The authors need to consider larger problems and other DFO algorithms to compare with. Other issues - Mathematical notation in page 2 is not standard in the DFO literature. Please use widely-used mathematical notation. - Capitalize the first letter in "equation" - "The standard parameter values for usual delta d_u and for zero term delta d_z are chosen 0.05 and 0.00025 respectively". Please justify. - "The HNM algorithm proved to deliver better performance than the traditional NM algorithm, represented by a famous Matlab function, known as ”fminsearch” Musafer and Mahmood (2018)". fminsearch has not been proposed by Musafer and Mahmood (2018), it is the classic NM algorithm. - The test functions have not been presented in the text. More importantly, all these problems have only a few variables. The authors need to consider much larger problems. - What's the purpose of the computational study? Why not compare against efficient DFO algorithms (e.g., NOMAD)? - "From the table, ...". Please provide references to all figures/tables. - The English language can be improved. Some examples where the language could be improved include lines 222 and 292 – the current phrasing makes comprehension difficult. - A readme file is needed in the Supplemental_File.zip in order to be able to find out where to find the codes and problem files.

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.

Title: HIGH-DIMENSIONAL NORMALIZED DATA PROFILES FOR TESTING DERIVATIVE-FREE OPTIMIZATION ALGORITHMS Review round: 1 Reviewer: 2

Basic reporting: The prose of the article requires significant revision in order for it to meet the requirement for use of clear and unambiguous English. There are frequent grammatical errors and use of terms which are, to my experience, non-standard with respect to the common language of the mathematical sciences. A non-exhaustive list of some of the errors with proposed corrections is included in the “General comments for the author”. The structure of the article also requires revision. For example, the first two paragraphs of the Discussion (starting Line 251) introduce the Genetic Nelder Mead (GNM) algorithm and provide the only summary of the author’s Multidirectional Trigonometric Nelder Mead (MTNM) algorithm. The Discussion section should be limited to the interpretation of the author’s work, in the context of previously presented background information, as much as possible. As the GNM algorithm is a core component of the author’s evaluation of the MTNM algorithm and the proposed data profile (Equation (25)), I believe that it should be more prominently introduced in the article’s introduction. References should also be provided to justify the choice of the GNM algorithm over other Nelder Mead variants for use as a point of comparison. References should also be provided for the sentence starting on Line 220. The minimisation example starting on Line 49 requires further explnation. While I do find the chosen topic (surgical grafts in cardiology) to be interesting, it is not clear with respect to what variables the objective function is defined. There are a number of small issues with the Figures and Table presented in this article: • Figure 1: Sublabel “A” has an identical to the variable “A” present in Figure 1 A and B. The parameters $d$, $d_l$ and $Th$ are not defined. The axes of the plot Figure 1 A are not labelled. • Table 1 performs a comparison which I do not believe to be an accurate communication of the work of Fajfar et al (see Section 2). • Figure 2, 3, 4 and 5: As data profiler variables are defined in the accompanying description, the axes of the plots may use ds(*), W, Y and T (sec) as the axes labels (suggestion). It is not clear how parameter Y is an “estimate” of the objective function, as the function should be computed up to the limits of numerical precision at each point. I suspect “estimates” refers to the number of “evaluations”. • Figure 5 A and B: It is difficult follow the lines for each solver without zooming in considerably. The authors have provided code for 6 of the 36 functions comprising test set proposed by More´ et al. I was able to execute this code to verify this limited subset of the author’s results. However, code should be provided for the complete suite of test functions. Finally there are a number of, mostly small, mathematical omissions or errors: • Line 51: The domain and range of $f$ is not defined. In the context of the Nelder Mead algorithm, the generalised objective function is typically $f: \mathbb{R}^n \rightarrow \mathbb{R}$ such that for, $f(x)$, $x \in \mathbb{R}^n $. • Line 101 presents an ordering of vertex pairs, this is incorrect in light of the ordering described on the previous line. The ordering should be notated in a manner equivalent to: $A=f(v_1) < B=f(v_2) < C = f(v_3)…$ • Line 152: If the values for $delta_u$ and $\delta_z$ have been arrived at through the authors’ practical experience, they should state so, if there is a formal or historical justification for these parameter values, it should be explained. • Equation (25): Parameter “Z” refers to the “number of machines”. The term “number of machines” is ambiguous. I assume, however, that the authors are referring to the number of CPU cores. Experimental design: The author’s present two original contributions: 1. Firstly, a modified version of the Nelder Mead algorithm, the MTNM algorithm, utilizes a set of 5 distinct solvers which work independently to identify the objective function minimum. These simplexes introduce different rotational ‘shifts’ through modification of the functions governing the placement of new simplex vertices at each iteration. An early stopping criterion is used to abort solvers which are failing to converge. The MTNM algorithm is shown to outperform solvers developed via the GNM algorithm in some cases. Of particular note is its performance in high dimensions, for example, when minimising the Quadratic (24) problem. 2. Secondly, a higher dimensional data profiler function by which to evaluate the performance of two dissimilar solvers operating on the same problem set. It introduces dimensions associated with wall time, number of simplex evaluations and number of CPUs. However, there are a number of significant issues with the experimental design: • It is not clear why the GNM algorithm has been chosen as a point of comparison. In the referenced paper, Fajfar et al outline a generic algorithm (GNM) for the evolution (or “hyper-optimisation”) of alternative Nelder Mead simplexes. They arrived at 5 candidates and present a single “optimal solver” (solver 1). Conversely, the authors propose an algorithm that uses an ensemble of 5 solvers. • Table 1 implies that the GNM algorithm is an ‘ensemble’ Nelder Mead solver when that is not the case. This also occurs on Line 306 where it is stated that the GNM algorithm requires about 12 hours to complete using 20 CPU cores. These values are taken from the time reported by Fajfar et al for completion of their genetic evolution algorithm, not optimisation of the standard test problems of More´ et al. • The data presented by Fajfar et al does not allow for a comparison of their solvers with the MTNM algorithm using the author’s defined data profile. • The addition of the T, W and Z parameters require further justification, as it stands, I have the following concerns: o The Nelder Mead, and modified Nelder Mead, algorithms presented in these articles require $n + 1$ function evaluations per iteration, where $n$ is the number of objective function parameters. The early stopping test employed by the MTNM algorithms results in a meaningful difference between the number of simplex evaluations and function evaluations, but this is certainly not the case in general. o While comparison of $W$ and $Y$ is perhaps useful for exploring how the number of ‘active’ MTNM simplexes changes with respect to the number of objective function evaluations, the overall performance of the algorithm is still almost entirely dependent on the number of objective function evaluations alone. Dependence on $W$ could only arise through the use of simplexes with distinct algorithmic complexity. If there is a measurable difference in the algorithmic complexity of the 5 MTNM solvers, the authors should demonstrate this by way of proofs or numerical experiments. o The algorithm wall-time, $T$, is not generalizable due to its dependence on the particular computer hardware used and the state of the host computer. Furthermore, for $T$ to be independent of $Y$, there must exist a significant (non-constant) overhead associated with the solvers that are independent of the number of function evaluations. However, as any such time overhead will necessarily result from the algorithmic complexity of the simplex construction step (see above), the $T$ and $W$ parameters do not seem to present independent dimensions for data profiling. o The number of CPUs, $Z$, was not used by the authors in their evaluation of the MTNM algorithm and I am unsure of how it relates to the NM algorithm in general. The most common target for parallelization techniques in the context of numerical optimisation problems is the objective function as it is (almost always) the most computationally expensive step. For $Z$ to be relevant the authors should present an optimisation algorithm that follows an alternative parallelization scheme. Validity of the findings: The authors present interesting results with respect to the performance of the MTNM solver, however, exploration of these results is hampered by issues in the experimental design (see Section 2). Unforteuently, it is not possible to easily validate all of the author’s findings and reliance on externally sourced data (from the referenced paper by Fajfar et al) is an additional barrier to replication. Additional comments: Below are some suggested grammatical corrections and comments relating to the prose of the submitted article: Line 18: “…through an angle <that> designates…” Line 37: “<We are> motived by…” Line 47: “<It seems a fact> that if a problem can be described as a mathematical expression, then at some point we will be <required> to minimize it or tune <its> independent variables at a <minimum>”. Line 59: “…reflections over the <changing> landscape of <the> mathematical problems until the coordinates of the minimum point <can> be obtained…” Line 66: “…the simplex becomes <increasingly> distorted <with each iteration>, generating different geometrical formations that are less effective <than> the <original> simplex design.” Line 69: “…the sequence of simplexes <to> converge to a non-stationary point.” Line 75: “The rest of this paper is organised as follow<s>.” “presents the theory of <the> sequential design of trigonometric Nelder-Mead algorithms<s>…” Line 76, 97 Figure 1 A: “…the vector theory” -> “vector theory” Line 78: “…and presents <the> multidimensional…” Line 83: “…the theory of <the> Hassan…” Line 86: “<This is different from the> traditional NM algorithm…” (suggestion) Line 93: “…the generat<ed> sequence of triangular simplexes are guaranteed not only have different shapes but <to> also they have different directions<.> <These characteristics lead to> better performance than the traditional hyperplanes simplex.” “ Note that <to> find the reflected point D we add the vectors $H$ and $d$<, as shown in Figure 1 A.> ” Line 106: “Now is we consider two combinations or more”: It is not clear what sort of combinations we are considering. Line 107: “..multiple components of <the> triangular HNM simplex…” Line 114: “In fact, the HNM algorithm is designed to deform its simplex in a way that introduces nonlinear movement, by incorporating a rotation<al> <shift at> each iteration.” (suggestion) Line 115: “After all axial components of the Th point are updated to see whether the new Th is better than C to be replaced or not.” The above sentence and, possibly the one before, would be better positioned before the concluding paragraph as they outline key aspects to the HNM algorithm. Line 122: “…approximation to a solution, generating different geometrical configurations…” Line 123: “…build the initial simplex with <edges of > equal length …” Line 129: “The risk is that<,> if the initial simplex is perpendicular to an optimal solution, then the algorithm…” Line 132: “…initial simplex with the NM method…” (suggested) Line 134: “…the generat<ed> sequence of…” Line 134: “One of the problems is that the generating sequence of simplexes should be consistently scaled with respect to the best vertex obtained and restart the simplex around the best observed results.” This sentence is difficult to parse as “One of the problems” is closely followed by “should be”. The first phase is a negative imperative, while the second phrase is a positive imperative. A clearer sentence could start “One of the problems is that the generated sequence of simplexes is not scaled with respect to the best vertex…” or, perhaps, “Ideally the generated sequence of simplexes should be scaled with respect to the best vertex…”. Line 138: “”Alternatively, the most popular way to initialize a simplex is Pfeffers´ method <(Baudin, 2009).> <This approach scales> the initial simplex <based on the starting point, $X_0$>. The initial vertex is set to v1 = x0, and the remaining vertices <are> obtained as follows,” The paragraph starting Line 141: Please present a brief argument as to why Equation (15) leads to improved starting points. The last sentence does not deductively follow from the Equation definition. Line 145: “On contrary, our solution depends on allowing the components of the reflected vertex to <transform non-uniformly with each iteration of the simplex>. Line 154: New paragraph at “In this test, we are more interested in launching multiple sequences of trigonometric simplex designs with different…” Line 158: “This procedure reinforces the standard Pfeffers´ method of creating a simplex with additional designs.” The above sentence could be safely removed. Line 158: I suggested that the sentence starting on this line, and the one following, be reworked. The first sentence makes a definite claim as to the effectiveness of the multidirectional simplexes without providing justification, it is also not clear what “effective” means in the context. Finally, instead of “mathematical landscape”, I suggest the term “solution space” or “the domain of the objective function”. In the following sentence, it is not clear (to me) if the proposed methods seek to rotate the simplexes such that they have a unique starting direction or a unique direction with each iteration. For example, see the following rephrasing: “<We will demonstrate that our> proposed multidirectional simplexes <converge to a minimum with a smaller> number of simplex gradient estimates <as compared to the previously discussed methods of simplex design>. <Key to this outcome is the> shifting <of> points associated with the highest, the second-highest, or the lowest values of the objective function with a displacement that <generates simplexes with> distinct directions.” Line 163: One of the potential designs <multiplies> the odd<-indexed> variables of odd-<indexed> vertices by (-1) Line 167: “…even components of x0,” Line 168: “…specified edge lengths and orientation…” All simplex edge lengths and orientations are specified in some manner. Are the specifications those goals outlined in the paragraph starting on Line 145? Line 169: “…by multiplying (-1) the parameters…” Is the (-1) a typo? “usual delta” and “zero term delta” -> “$\delta_u$ and $\delta_0” Line 170: “…the absolute value <of the components of $x_0$ and> and subtracting or adding to adjust the simplex orientation…” Line 171: “…and can be modified as needed…” By what criteria are the position vectors added or subtracted? Line 173: “…as well as the slope…” The slope with respect to what function and what point points? “Therefore, a window of size 10 points…” The choice of 10 points does not deductively follow from the previous sentence, why 2, 4, or 100? If the window size is a hypermeter derived from your practical experience please make that choice clear. Line 176: “…the direction vector, which designates the direction of the simplex…” -> “the direction of the simplex” Line 178: “For the particular <case>,” Line 189: Non-deductive therefore. The phrase "Therefore" should only when drawing a logical link between ideas. Line 190: “tools” -> “metrics” or “figures of merit”, “similar algorithms,” -> “the considered algorithms.” “Which are summarized as follows: <the> accuracy of the algorithm compared to the actual minima, <the wall-time to convergence>, the number of function evaluations, the number of simplex evaluations, and identification of the best sequence of trigonometric simplex design. Line 194 to 200: “The main reason for designing the set of functions”: It is not clear how the set of functions relates to the previously mentioned testing guidelines. I suggest that the authors make the link explicit (e.g. “These guidelines utilize a set of functions…) or place this discussion after the subsequent sentence. Line 207: What is “short-term” behaviour in this context? Line: “launch” -> “launches” Line 209: It is not clear to me how the individual solvers “cooperate” to find an optimal solution. As it stands I do not think they share information beyond their common starting point, $x_0$, is this correct? Line 233: “All computational experiments were carried out on an i5 CPU (4 Cores at1.8 GHz) and 4 GB of RAM. We used C# to implement the MTNM algorithm and carry out the experiments.”

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.

Title: HIGH-DIMENSIONAL NORMALIZED DATA PROFILES FOR TESTING DERIVATIVE-FREE OPTIMIZATION ALGORITHMS Review round: 2 Reviewer: 1

Basic reporting: The authors have addressed all my comments. Experimental design: The authors addressed most of my comments. However, they did not address the most important two issues: - The test functions have not been presented in the text. More importantly, all these problems have only a few variables. The authors need to consider much larger problems. The authors state in their response that they want to be consistent with the literature in terms of the number of variables and use the same total number of variables of in order to be able to compare computational results. It is OK to include these problems in order to compare the results with the literature. However, it would add more value to the paper to also include larger problems. - Why not compare against efficient DFO algorithms (e.g., NOMAD)? The authors state that they choose GNMa because GNMa is one of the best algorithms that utilizes the test functions of (Moré et al., 1981) and utilizes normalized data profiles that involves one dimension (simplex evaluations). It is OK to use GNMa for the aforementioned reasons. However, why not use the state-of-the-art DFO algorithms, like NOMAD? Validity of the findings: The authors have addressed all my comments. Additional comments: The authors have addressed all my comments.

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.

Title: HIGH-DIMENSIONAL NORMALIZED DATA PROFILES FOR TESTING DERIVATIVE-FREE OPTIMIZATION ALGORITHMS Review round: 2 Reviewer: 2

Basic reporting: The overall prose of the article has improved but significant proofreading and revision of some paragraphs are required in order to meet the criteria of clear and unambiguous professional English. Identified typos and suggested re-phrasing are included in 'Additional comments', however, I am certain that the list is non-exhaustive. Experimental design: No comment. Validity of the findings: No comment. Additional comments: The experimental design is outlined clearly and the authors' original contributions are clearly defined. The authors introduce the Multidirectional Trigonometric Nelder Mead (MTNM) algorithm, which utilises an ensemble of five simplexes developed through variation to the simplex of the Hassan Nelder Mead Algorithm. The performance of this algorithm is assessed against the Genetic Nelder Meader (GNM) algorithm, which provides a single simplex derived through genetic programming. To compare their ensemble solver to this algorithm the authors proposed a high-dimensional normalised data profile that takes into account the number of cost-function variables, cost function evaluations, simplex evaluations, wall-time and CPU count. The authors provide sufficient background and references, have addressed previously identified issues in their diagrams and have shared the code needed to reproduce their original numerical results. The article is self-contained, presents results relevant to the hypotheses and includes clear definitions of all terms. Overall, I am happy with the authors' response to feedback, in particular, their discussion of the data profile dimensions in "Detailed Analysis of the Five Solvers". Below are a number of identified typos and small suggestions: Line 32: it’s -> their Line 39: We are motivated to notice -> We are motivated by the observation Line 40: For example, data profiles -> For example, some data profilers Line 45: Thus, the proposed multidimensional data profiles are more compact and effective in allocating a computational budget for different levels of accuracy. Instead of 'Thus' perhaps say 'We argue that' or 'Numerical results indicate that'. Line 75: NAa -> NMa Line 77: with best -> with the best Line 80: that is hybridizing -> that hybridizes Line 81: Instead of using a restricted NM simplex to only one traditional design, the authors evolve NMa genetically to produce deterministic simplexes that can develop adaptive vertices through generations. The sentence needs to be rewritten (simplified). Line 86: and basically -> and that, basically, the Line 93: upgrade the data profiles Which data profiles? Line 98: of trigonometric -> of the trigonometric Line 111: When the next simplexes are characterized by different reflections, the HNMa performs not only similar reflections to that of the original simplex of the NMa, but also others with different orientations determined by the collection of non-isometric features. -> When different reflections characterize the next simplex, the HNMa performs similar reflections to that of the original simplex of the NMa and others with different orientations determined by the collection of non-isometric features. Line 114: guaranteed to search the solution space of mathematical problems” -> guaranteed to search a higher proportion of the solution space Line 118: calculated at the vertices -> calculated at vertices Line 119: in ascending with -> in ascending order with Line 120: $and$ -> and Line 122: The need for Th arises when the HNMa performs a reflection in an axial component, it replaces the value of the axial component of the Th. This sentence is not clear, please rewrite it. Line 142: in extraction one -> in the extraction of one Line 145 Therefore, the optimization solution of the HNMa not only reflects the opposite side of the simplex through the worse vertex, but also leads to implement various reflections that are determined by the collection of extracted features. -> Therefore, the optimization solution of the HNMa reflects the opposite side of the simplex through the worse vertex and leads to the implementation of reflections determined by the collection of extracted features. Line 152: Solutions to the HNMa help extract the optimal characteristics of the non-isometric reflections in the reflected vertex and produce simplexes that lead to faster convergence rates than the original triangular simplex of the NMa. Line 177 and 178: “ -> `` Line 242: (in second), -> (in seconds) Line 247: optimization classes -> optimization class. Line 292: A simplex in some cases explores the neighborhood to update its threshold, but do not move only if the threshold is good enough to replace the worst point. Grammatically, 'Do not' should probably be 'Does not'. However, the sentence makes more sense if 'but do not move' is changed to 'but moves'. Please rework this sentence. Line 296: In this way, the HNMa mimics the amoeba style of maneuvering to move from one point to another when approaching a minimal point. -> In this way, the HNMa mimics an amoeba style of maneuvering from one point to another when approaching a minimal point. Line 304: “ -> `` Line 334: using 20 of 2.66 GHz -> using twenty 2.66 Ghz Line 358: For example, MTNMa performs better to determine a solution to Quadratic (16) then Quadratic (8) in Table 1. -> For example, MTNMa performs better when optimizing Quadratic (16) as compared to Quadratic (8) in Table 1. Line 359: While in other cases, the MTNMa generates fewer number of simplexes to approximate a particular solution for high dimensions than for less dimensions. -> While in other cases, the MTNMa generates fewer simplexes to approximate a particular solution for high dimensions than for lower dimensions. Line 371: such environment.-> such an environment Line 378: provide a complementary -> provide complementary Line 396: requires the best possible reduction has to equal -> : requires that the best possible reduction has to equal Line 407: By analyzing those five solvers of multi-directional trigonometric simplex designs, we have conducted further tests, which reveal that further evaluations are important to make decision on which solver should be used when there is a limited computational budget. -> We have conducted further tests by analyzing the five multi-directional trigonometric simplex solver designs. These reveal that higher dimensional data profiles are essential to deciding which solver should be used with a limited computational budget. Line 410: solvers (1 and 5) already catch up, approximately after overtaking 400 simplex evaluations -> solvers (1 and 5) catch up after approximately 400 simplex evaluations Line 417: This forms a strong argument that how a solver, in some cases, may always require a large number of simplex gradients but may have the potential to take less time to solve 100% of the test problems and improve the performance. -> This forms a strong argument as to how a solver, in some cases, may require a larger number of simplex gradients but may have the potential to take less time to solve 100% of the test problems. Line 447: In the situation where Solver2 stands out as being the best of the five solvers, because certainly it requires not only less function evaluations but also less computational time than the other solvers. -> In this situation, Solver2 stands out as being the best of the five solvers because it requires fewer function evaluations and less computational time than the other solvers. The paragraph starting on Line 451: Regarding the statement on Line 452. While different mathematical problems are parallelizable to differing extents, I would argue that the significance of Z is more immediately dependant on whether the CF is implemented (or perhaps compiled) as a parallel function, whether the solver is implemented as a parallel algorithm and the effectiveness of the chosen parallelisation methods. I suggest that this paragraph be simplified, for example: The number of CPUs (Z) was not examined in our evaluation of the MTNMa and is included in formula (22) for completeness. This dimension is significant if an optimiser is deployed in a distributed environment such as Amazon Web Services (AWS). In such a case, the number of nodes in the virtual cluster is an important aspect of the computational budget and the inclusion of Z assists in the allocation of optimal numbers of CPUs for different solvers and for specific levels of accuracy. Line 471: rotation property determined -> rotation determined Line 471: To examine the performance of multiple solvers simultaneously, a linear model with a window of size 10 samples is suggested as the criteria that is used to make decision whether a solver is aborted or continued based on the direction vector of the window. -> When executing multiple solvers simultaneously, a linear model with a window of size 10 samples is suggested as the criteria by which a solver is aborted or continued based on the direction vector of the window. Line 474: We also showed in this research that using the data profile as a function for allocating the computational budget and examining the relative performance of multiple solvers based only on the simplex gradients (one dimension) is not appropriate when the evaluation is expensive. -> We also showed in this research that using a data profile based only on the number of simplex gradients (one dimension) for allocation of the computational budget and examination of the relative performance of multiple solvers is not appropriate when cost-function (?) evaluation is expensive.

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.

Title: HIGH-DIMENSIONAL NORMALIZED DATA PROFILES FOR TESTING DERIVATIVE-FREE OPTIMIZATION ALGORITHMS Review round: 3 Reviewer: 1

Basic reporting: The authors have addressed all of my comments. Experimental design: The authors have addressed all of my comments. Validity of the findings: The authors have addressed all of my comments. Additional comments: The authors have addressed all of my comments.

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.

Title: MITIGATION OF BLOCK WITHHOLDING ATTACK BASED ON ZERO-DETERMINANT STRATEGY Review round: 1 Reviewer: 1

Basic reporting: I recommend to (also) display the revenue of the independent miners in an additional Figure 4(c). Could mention, at least as outlook / room for further consideration: Would mining difficulty adjustment (after 14 days) adjust pool revenue facing a block withholding attack? Section "ZD strategy" (from 7/17, line 225) actually lacks a precise and compact definition of a "ZD strategy": Lines 245/246 on page 8/17 do provide some conditions ("If the strategy selected by X satisfies ... This is the ZD strategy"), yet unclear what set of candidate "strategies" (which then do or do not fulfil the conditions) X can select from. Conclusions sections very short. Should also summarize restrictions (e.g.: for the case of two pools) and outline further work. Should define all abbreviations on first mention (TFT = Tit for tat? WSLS=?) Should use a small space (typically "\," in LaTeX) between number and unit (10mins ->10 mins, 300BTC -> 300 BTC). "Pool1"/"Pool2" should use subscript für index values ("Pool$_1$"). Experimental design: Usual not to find experiments replicated. Would expect multiple runs of 100 (or 500) steps each and variance reviewed. If not, should (at least) argue why - according to the authors - this is not necessary. Validity of the findings: no comment Additional comments: no (furher) comment

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.

Title: MITIGATION OF BLOCK WITHHOLDING ATTACK BASED ON ZERO-DETERMINANT STRATEGY Review round: 1 Reviewer: 2

Basic reporting: This paper deduces the calculation formula of the actual income of the mining pool when the block withholding attack is launched. The ensemble strategy, extortion strategy and the proposed adaptive strategy of ZD are studied. Then, the mitigation of block interception attack based on ensemble strategy, extortion strategy and zero-determinant adaptive strategy is theoretically studied. The authors also selected and simulated 30 sets of game strategies to illustrate changes in the pool's returns. Experimental design: Although this paper is structurally complete and logically clear, there are a few problems in the manuscript, which needs the author to modify for being accepted. The problems in the manuscript are shown below in detail. 1. In the abstract section, the author should make clear which works are his own, rather than linearly describe the prose structure of the work. 2. Some formulas are not in the same format as (11) (15). Authors should proofread carefully to ensure that all formulas are in the same format. 3. In some of the figures, it is difficult to see the specific situation corresponding to Y as shown in Figure 6 and Figure 7. The author should make corresponding changes to make the figure clearer. 4. In the conclusion part, the author should make a concise summary of each chapter in the conclusion, clarifying his own contribution. 5. The following major workings are missing in the references: Multiple cloud storage mechanism based on blockchain in smart homes; Novel vote scheme for decision-making feedback based on blockchain in internet of vehicles. Validity of the findings: Although this paper is structurally complete and logically clear, there are a few problems in the manuscript, which needs the author to modify for being accepted. The problems in the manuscript are shown below in detail. 1. In the abstract section, the author should make clear which works are his own, rather than linearly describe the prose structure of the work. 2. Some formulas are not in the same format as (11) (15). Authors should proofread carefully to ensure that all formulas are in the same format. 3. In some of the figures, it is difficult to see the specific situation corresponding to Y as shown in Figure 6 and Figure 7. The author should make corresponding changes to make the figure clearer. 4. In the conclusion part, the author should make a concise summary of each chapter in the conclusion, clarifying his own contribution. 5. The following major workings are missing in the references: Multiple cloud storage mechanism based on blockchain in smart homes; Novel vote scheme for decision-making feedback based on blockchain in internet of vehicles. Additional comments: No additional comments

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.

Title: MITIGATION OF BLOCK WITHHOLDING ATTACK BASED ON ZERO-DETERMINANT STRATEGY Review round: 1 Reviewer: 3

Basic reporting: In this manuscript, the authors investigated block withholding attack in blockchain based on game theory. They consider the situation that only two mining pools exist and one or both pools attack each other. By calculating revenue of each mining pool, they pointed out that choosing whether it attacks the other pool or not is similar to choice of action in the prisoner's dilemma game. Then, they investigated zero-determinant (ZD) strategies in the iterated prisoner's dilemma (IPD) game, and showed that an adaptive ZD strategy promotes cooperation between pools. Although their idea about applying ZD strategies to blockchain mining is interesting, I think that the current version should not be published. The reason is that, whereas the first part "Mining dilemma analysis" is significant as an application of game theory, the second part "ZD strategy" does not contain any novel results. They just investigated ZD strategies in IPD, which have already been studied by many researchers, and the paper does not advance our understanding at all. I think that the problem comes from the fact that the authors reduced their model to IPD, which is too simple, although action in their original model is the continuous parameter $r_i$. I recommend that the authors investigate ZD strategies in their mining game without reducing it to IPD. In research on ZD strategies, McAvoy and Hauert extended ZD strategies to continuous action space [PNAS 113(13), 3573 (2016)]. I think that this paper is useful for improving their manuscript. In addition, as a minor comment, their survey on ZD strategies is not sufficient. There are many papers which should be mentioned in "Related works". For example, *ZD alliance [Hilbe, Wu, Traulsen, Nowak, PNAS 111(46), 16425 (2014)] *ZD strategies in noisy games [Hao, Rong, Zhou, Phys. Rev. E 91, 052803 (2015)] *ZD strategies in games with a discount factor [Hilbe, Traulsen, Sigmund, Games and Economic Behavior 92, 41 (2015)] *Extension to alternating games [McAvoy, Hauert, Theoretical Population Biology 113, 13 (2017)] *Consistency and independence of ZD strategies [Ueda, Tanaka, PLoS ONE 15(4), e0230973 (2020)] *Extension to memory-$n$ strategies [Ueda, Royal Society Open Science 8, 202186 (2021)] I hope that the authors resubmit a revised version. Experimental design: no comment Validity of the findings: no comment Additional comments: No additional comments

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.

Title: MITIGATION OF BLOCK WITHHOLDING ATTACK BASED ON ZERO-DETERMINANT STRATEGY Review round: 2 Reviewer: 1

Basic reporting: Revised paper is much improved and can be accepted now. Experimental design: Revised paper is much improved and can be accepted now. Validity of the findings: Revised paper is much improved and can be accepted now. Additional comments: No additional comments

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.

Title: MITIGATION OF BLOCK WITHHOLDING ATTACK BASED ON ZERO-DETERMINANT STRATEGY Review round: 2 Reviewer: 2

Basic reporting: The authors sincerely addressed my comments or explained the novelty of their work in their rebuttal. Now I understand that the innovation of their work is an application of zero-determinant strategies to block withholding attack, and recommend an acceptance. Experimental design: no comment Validity of the findings: no comment Additional comments: No additional comments

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.

Title: ALIGNING RESTRICTED ACCESS DATA WITH FAIR: A SYSTEMATIC REVIEW Review round: 1 Reviewer: 1

Basic reporting: 1. To date, it remains unclear how sensitive data should be managed, accessed, and analysed (Cox et al., 2016). - 6-year-old statement is given to express today’s situation 2. Is there any solid ground behind the selection of Eligibility criteria? 3. Condition four of the eligibility criteria is not present in a vast number of articles? 4. The corpus of publications resulting from the query was exported to Rayyan - Why this specific tool is being used? - This tool was presented in 2016. Do we have any latest tool available in this context? - Comparative analysis is required for the selection of such tool from the list of available tools - It is seemed that the proposed work is heavily depending on this tool. What if this tool is removed / replaced with some other tool? - Which specific version of the tool is used? 5. In the context of this research, the cycle has been slightly modified to better suit our results and to bring more awareness to also the stages when the data is processed, as well as the steps required after the data is used. - If there is no other reason of modifying data lifecycle management then it seems a bit biased to modify the process. - Secondly, what alteration has been made? 6. TRL levels details are missing. 7. Line 244 to 251 can be better represented in a tabular form. 8. What is OWL ontology and why it is being used here? 9. An RDF ontology was generated to describe the Data Methods subclass hierarchy. - Is there any alternate to the above representation? - Why do we need this step? Is the review of broad and cross-disciplinary interest and within the scope of the journal? - Yes Has the field been reviewed recently? If so, is there a good reason for this review (different point of view, accessible to a different audience, etc.)? - No, the authors claim is that this is the first study of this type. Does the Introduction introduce the subject and make it clear who the audience is/what the motivation is? - Yes, up to some extent. Experimental design: Methods described with sufficient detail & information to replicate. - No, with the provided details it will be difficult to reduce the result because it is working on the result of google scholar. At different time, google scholar will return different papers. This will affect the result. Is the Survey Methodology consistent with a comprehensive, unbiased coverage of the subject? If not, what is missing? Are sources cited? Quoted or paraphrased as appropriate? - Yes Is the review organized logically into coherent paragraphs/subsections? - Yes Validity of the findings: Is there a well-developed and supported argument that meets the goals set out in the Introduction? - In this context, goals are not being set out in the introduction. Does the Conclusion identify unresolved questions / gaps / future directions? - There is a limitation heading found in the article in this regard. Overall, this article is divided into two parts: - Domain / problem introduction - Proposed Solution First part is being presented very well. Covering subject area well e.g., introduction, problem statement, background etc. but when it comes to problem solution then some weak technical stuff is being observed e.g., Methods, eligibility criteria etc. The Results section contains nothing but the detailed explanation of the selected dataset. Similarly, the outcome of the paper is heavily depended on the selected dataset. E.g., different input articles will have different results. Additional comments: No additional comments

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.

Title: ALIGNING RESTRICTED ACCESS DATA WITH FAIR: A SYSTEMATIC REVIEW Review round: 1 Reviewer: 2

Basic reporting: The paper analyzes various practices being followed in the research community to meet the data sharing proposed by FAIR principles. The manuscript provides a detailed survey of key mechanisms involved in applying FAIR principles on restricted research data. Experimental design: The identified research questions look appropriate however the utility of RQ2 and RQ3 should be further elaborated, i.e., how research community may take advantage of proposed categorization and whether the mature practices can be converted into some kind of standards or standard operation procedures or not? The records show that majority of the papers are unable to meet the criteria set by the submitted manuscript and 40 articles are selected for investigation of research questions. Theses number suggests that research community is either not aware of FAIR or the principles are not believed to improve the quality of research. A survey may be used to contact the authors of the excluded papers to verify the intention of no following FAIR principles. It is suggested to target papers that have received awards in conferences or journals in the study as most of the conferences consider reproducibility as key condition for such awards. Also it can be found out whether compliance of FAIR principles is a requirement for the such awards or not? Recently a few journals have appeared that particularity target publication of datasets (Data in Brief). Authors may consider including journal or conference based criteria to evaluate further the research questions. Validity of the findings: A comprehensive discussion has been provided based on the collected data along with limitations, however authors apparently have relied on the reader for developing the inferences related to the research questions. It is suggested to provide crisp response to the research questions particularly RQ2 and RQ3. Authors have discussed the aspect of anonymization of data however it is suggested to investigate the aspect keeping finer granularity in mind, i.e., what kind of anonymization principles should be or already part of FAIR? Table 2 provides fields of research categories and no example can be found that belongs to multiple fields. As the manuscript is submitted in a computer science journal, it is therefore suggested to make effort to find a few paper that belong to either core computer science or its constituents field, i.e. communication networks, social network analysis, software project management etc that usually include research works involving sharing of data. Additional comments: No additional comments

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.

Title: A HIGH-PERFORMANCE, HARDWARE-BASED DEEP LEARNING SYSTEM FOR DISEASE DIAGNOSIS Review round: 1 Reviewer: 1

Basic reporting: The paper proposes a novel methodology to diagnose cancer. The abstract should be verified in order to remove the grammatical errors. Which type of cancer and from which organ has to be explained in detail. The abstract states that the proposed system can also detect diseases from the heart. This sentence can be removed or the evidence for this sentence could be included. Table 1 must be shown in the introduction section as it is not related to the literature review. Rather, a summary of the literature can be included as a separate table in this section. The proposed solution can be written as Proposed Methodology More details can be included in the Basic ANN Operation as it plays a major role in this paper. Experimental design: It will be well if the experiments were done for the proposed system. A table explaining the values of TP, FP, and TN for the input data should be included. Validity of the findings: Table 3: Comparison of Various Neural Networks in terms of Classification Accuracy has to be rewritten so that it can be easily understandable to the readers. Additional comments: No additional comments

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.

Title: A HIGH-PERFORMANCE, HARDWARE-BASED DEEP LEARNING SYSTEM FOR DISEASE DIAGNOSIS Review round: 1 Reviewer: 2

Basic reporting: More points have to be included based on the complete methodology and results The sentence “Moreover, the system is reconfigurable and can be programmed to classify any sample into one of two classes” has to be justified as the classification is nowhere shown throughout the manuscript. The sentence “The system can predict about 63.5 million cancer samples in a second” has to be justified as the results were not shown in the results and discussion section. Rather, it is shown only in the abstract and also in the conclusion. Experimental design: An experiment has to be done in order to depict the prediction of 63.5 million cancer samples in a second. Also, a tabulation has to be framed to analyze the prediction accuracy. Validity of the findings: It will be well if executed results of image samples were shown in the results and discussion section so that the proposed methodology seems to be executed. Additional comments: No additional comments

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.

Title: A HIGH-PERFORMANCE, HARDWARE-BASED DEEP LEARNING SYSTEM FOR DISEASE DIAGNOSIS Review round: 1 Reviewer: 3

Basic reporting: The paper proposed a hardware implementation for the cancer diagnosis problem. However, the contribution is not clear in the hardware methodologies that are introduced 1- The proposed architecture is very weak and has no enough contribution as in Figure 3: Proposed ANN Topology 2- The proposed system is not clear from Figure 6: Internal Structure of the Proposed Hardware System. 3- Figures 4,5, and 7 are not clear. Experimental design: 1- The experiments should include several cancer datasets and evaluate the performance between them 2- The splitting technique is very weak, I think you should use 10 folds cross-validation to get fair comparison. 3- The training parameters needs to be illustrated why u choose these parameters The learning rate is kept equal to 1/3 . The momentum is equal to 0.9. The data is processed in batches in order to achieve high accuracy; the batch size used in the proposed system is 100. Validity of the findings: The paper did not contribute enough to be published in the journal and needs to high modification level Additional comments: No additional comments

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.

Title: A HIGH-PERFORMANCE, HARDWARE-BASED DEEP LEARNING SYSTEM FOR DISEASE DIAGNOSIS Review round: 1 Reviewer: 4

Basic reporting: Authors have proposed a hardware-based deep learning system for cancer diagnosis. The research problem selected by author(s) is timely and important to be addressed. The overall structure and organization of the paper are satisfactory, and the paper qualifies for an above-average up-to-date bibliography. However, there are a few issues that are required to be addressed by the authors. 1) The main problem with this paper is coherency. In many paragraphs, sentences are not written coherently. 2) Why the title is specific to Cancer Diseases? Authors have also claimed the ability of the proposed scheme to predict the presence of other diseases. So, the title should be a hardware-based deep learning system for disease diagnosis. 3) Authors are encouraged to improve the abstract by focusing only on the most significant details that are unique to their proposal. Authors have simply claimed in the abstract that “In this context, we propose a hardware-based neural network that can predict the presence of cancer in humans with 98.23% accuracy.” But they didn’t mention the features of their system that help to gain an accuracy of 98.23%. Authors are advised to write their significant contributions clearly. Moreover, in the abstract, it has been mentioned that the proposed system is about 5 to 16 times cheaper and at least four times speedier than many other contemporary systems? What is meant by many? Not clear. 4) Authors have several times used the term hardware friendly but have not described it. For example, in the abstract and other sections, it is stated “this is why scientists have come up with functions that are not only accurate but are friendly to hardware platforms”. What is meant by friendly to hardware platforms? Any reference? 5) “Conventional activation functions such as sigmoid and hyperbolic tangent (TanH) yield high accuracy but are not suitable for hardware implementations. This is because they involve division and many other hardware-inefficient operations.” Authors have mentioned this fact, but without reference(s). Experimental design: 6) It seems there is no need for this sentence “To know more about efficient implementation of neural networks on edge devices, the reader is referred to [11].” Is the implementation of neural networks on edge devices is related to the authors’ work? 7) Authors have claimed “this is the reason why we adopt these functions for implementation in the proposed system. Adopted these functions for implementation of what? in the proposed system. It is not clear here. 8) A summary or comparison table of proposed techniques discussed in the literature review is not available. 9) Details in paragraphs 2, 3, and 4 of Section 1 are not coherent. It is highly recommended to re-write these paragraphs to highlight your contribution. Validity of the findings: 10) The required level of accuracy, speed, etc. depends on the underlying application, as shown in Table 1. Delay is not mentioned and how this line is related to the other lines of this paragraph. Again, authors are advised to be coherent in writing paragraphs. 11) Section 3 proposed solution starts with the working of the proposed system but authors must add text about the proposed techniques here. What is the proposed system, components, and working? 12) “Data Preprocessing” heading is not required and the text under this heading should be adjusted in section 3.1. 13) Figure 4 is not clear. 14) Figure 6 should be discussed in section 3.2. 15) The proposed algorithm is compared with other state-of-the-art algorithms in terms of classification accuracy, throughput, and implementation cost. Which state-of the art algorithms? Names? 16) The proposed system consumes only 983 slice registers, 2655 slice look-up tables, 234 DSP48 elements, and 33 block random access memories (BRAMs). But why? It has not been mentioned. 17) It can be seen from Table 4 and Table 5 that the proposed system is about 5-16 times cheaper and at least four times speedier than most modern systems. What modern systems? Mention features of your proposed solutions that make these results better. 18) Future work or extension is not clear. Just one line has been mentioned, “In future, more complex datasets can be chosen for better diagnosis.” This is not enough to say what is meant by complex datasets? Additional comments: No additional comments

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.

Title: A HIGH-PERFORMANCE, HARDWARE-BASED DEEP LEARNING SYSTEM FOR DISEASE DIAGNOSIS Review round: 2 Reviewer: 1

Basic reporting: All requirements have been revised satisfactorily. Experimental design: All requirements have been revised satisfactorily. Validity of the findings: All requirements have been revised satisfactorily. Additional comments: No additional comments

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.

Title: A HIGH-PERFORMANCE, HARDWARE-BASED DEEP LEARNING SYSTEM FOR DISEASE DIAGNOSIS Review round: 2 Reviewer: 2

Basic reporting: All comments have been addressed Experimental design: All comments have been addressed Validity of the findings: All comments have been addressed Additional comments: All comments have been addressed

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.

Title: A HIGH-PERFORMANCE, HARDWARE-BASED DEEP LEARNING SYSTEM FOR DISEASE DIAGNOSIS Review round: 2 Reviewer: 3

Basic reporting: Authors revised the paper, so all comments were met Experimental design: Authors revised the paper, so all comments were met Validity of the findings: Authors revised the paper, so all comments were met Additional comments: No additional comments

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.

Title: ENERGY EFFICIENT SERVICE PLACEMENT IN FOG COMPUTING Review round: 1 Reviewer: 1

Basic reporting: 1. Authors are required to improve the English language and some sentence structures need to be updated. 2. Some cited references are very old of year 2012 3. Overall article structure is good. 4. Hypotheses and results are OK and shared with the RAW data. 5. In some sections authors have written too many paragraphs for expressing their views. Need to update the style with some professional writing style. 6. Provide expanded from of abbreviations wherever used for the first time. Experimental design: Here, authors have proposed an improved version of JAYA approach for optimal placement of modules that minimizes the energy consumption of a fog landscape. They have analyzed the performance in terms of energy consumption, network usage, delays and execution time. - Authors need to provide the details about the JAYA approach. As authors have cited that this approach is published @ref[19] but this publication is not a standard one and there is a doubt that the journal is a predatory journal. Authors are required to update this citation with some published/ cited with some standard publisher. - Make your Introduction section more technical than in the current form it just focuses on the basics of fog computing. - What is the worst-case time complexity of the modified JAYA approach and previously published JAYA approach. - In the literature survey, authors are discussing vehicular communication.... why?? - Kindly refer the following work for further improvement in the literature survey section 10.1109/ISPCC53510.2021.9609479 10.4018/IJKSS.2020100102 - Why authors have not applied any MCDM based approach for the allocation of resources and services in the Fog landscape? - Equation(3) is a general equation and computes the energy consumption. But how the Eq 2 has been derived? - In the figure 2, there is a flaw in the flowchart. As the output from the first decision box irrespective of the condition whether it is true or false is becoming the input for the next level.....Why?? - What is the purpose of Figure 3?/ - Figure 4 doesn't include the unit of energy consumption. - Provide the latency comparison of all the approaches. Validity of the findings: Obtained results are valid. Additional comments: NIL

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.

Title: ENERGY EFFICIENT SERVICE PLACEMENT IN FOG COMPUTING Review round: 1 Reviewer: 2

Basic reporting: The paper is generally well-written and reasonably structured. Experimental design: The authors have explained their system model and the proposed algorithm algorithm very well. However, they need to further clarify some points such as: - The complexity of the proposed algorithms are not analysed. - Some details about where (on edge-devices, on gateways, in cloud?) the proposed algorithms are run are also needed. Also, it is unclear how these algorithms are triggered to run. The algorithms are run every time a new application appears? Some details are needed; Validity of the findings: The authors have simulated several representative scenarios. However, they need to compare their results to other relevant examples such as the Edgeward algorithm inherently built within the iFogSim simulator. In addition, they are kindly requested to compare their work to other closely related efforts such as the fowling papers: https://dl.acm.org/doi/10.1145/3344341.3368795 https://link.springer.com/article/10.1007/s12652-021-02910-w - For the results shown in Fig. 4, the authors are requested to show the percent decrease in energy dissipation as compared to each existing algorithm. In addition, it can be notices that the EPSO algorithm has achieved very close numbers to the proposed algorithm. In other words, they have mentioned that they have achieved 31% average improvement considering the Cloud-only algorithm which is considered as a naïve benchmark in presence of a bulk of recently proposed application placement algorithms. Moreover, they have less that 3% improvement as compared to the EPSO algorithm. In addition, they need to compare their results to other closely related efforts such as the aforementioned two papers. - Overall, the performance of the proposed algorithms is relatively close to that of the EPSO algorithm. Hence, the authors need to show what significant advantages their proposed algorithm can achieve. Additional comments: No additional comments

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.

Title: ENERGY EFFICIENT SERVICE PLACEMENT IN FOG COMPUTING Review round: 2 Reviewer: 1

Basic reporting: Authors have improved the language. References have been updated that includes some more recently published work Figures are OK. Experimental design: The authors have carried out the various experiments as per identified problem statement. They have updated the methodology section accordingly. Validity of the findings: The proposed solution is novel and supported by results and comparative studies with previous approaches. Additional comments: No additional comments

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.

Title: IMPROVED GENETIC ALGORITHM OPTIMIZED LSTM MODEL AND ITS APPLICATION IN SHORT-TERM TRAFFIC FLOW PREDICTION Review round: 1 Reviewer: 1

Basic reporting: In this paper, author presented an improved genetic algorithm (OGA) to optimize long-term and short-term memory neural network (LSTM). However, there are some limitations that must be addressed as follows. 1. Some sentences in abstract are very lengthy (for example see sentence 1). These sentences should be changed to make the abstract more attractive for readers. 2. In Introduction section, it is difficult to understand the novelty of the presented research work. This section should be modified carefully. In addition, the main contribution should be presented in the form of bullets. 3. Different existing application of traffic events or traffic flow should be discussed. In addition, the most recent work about Deep learning-based traffic events or traffic flow should be discussed as follows (‘Traffic accident detection and condition analysis based on social networking data’, ‘Fuzzy Ontology and LSTM-Based Text Mining: A Transportation Network Monitoring System for Assisting Travel’, and ‘Transportation sentiment analysis using word embedding and ontology-based topic modeling’, and ‘Fuzzy ontology-based sentiment analysis of transportation and city feature reviews for safe traveling’.). 4. Equations should be discussed deeply. 5. LSTM is not properly discussed in Section 4. What about Bi-LSTM? 6. Captions of the Figures not self-explanatory. The caption of figures should be self-explanatory, and clearly explaining the figure. Extend the description of the mentioned figures to make them self-explanatory. 7. The whole manuscript should be thoroughly revised in order to improve its English. 8. More details should be included in future work. Experimental design: no comment Validity of the findings: no comment Additional comments: No additional comments

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.

Title: IMPROVED GENETIC ALGORITHM OPTIMIZED LSTM MODEL AND ITS APPLICATION IN SHORT-TERM TRAFFIC FLOW PREDICTION Review round: 1 Reviewer: 2

Basic reporting: The work is technically sound and has potential merit for publication. However, major revisions are needed to make it worth publishable. Experimental design: The experimental section, in particular, the setup and parameters being used, needs further explanation. Validity of the findings: The experiments seem inline, valid, and consistent with previous findings. However, the evaluation section is written well. However, it is not clear how the simulations were performed? Which optimization tool was used? Furthermore, the evaluation metrics should be briefly described. Additional comments: I have the following comments and suggestions to further improve the quality of the work: 1) The abstract is not concise enough to sketch the entire theme, in particular, the results of the manuscript. Also, there were some serious grammar issues that should be corrected. 2) Furthermore, the introduction section needs considerable effort (concise and brief). The problem being investigated should be described clearly. The introduction, e.g., should lead the way throughout the paper. In addition, the benefits coming from this paper should be made clearer in the introduction and throughout the paper. - The entire introduction section is written in two paragraphs, while the first paragraph has been ended with a semi-colon (full stop needed) - Furthermore, briefly describe the major contributions in bullet form, just before the organization paragraph. - The final paragraph of the introduction section should be the organization flow. 3) I suggest adding a separate section that illustrates the related work. Various sections in the paper should be moved to this section. Moreover, a summary of the related work should be sketched into a table with respect to their characteristics. The authors should put their proposal into this table for easy comparison. This will make it clearer to readers and they will be able to see what was missing in the literature; and how this is addressed in this paper. 4) Moreover, It would be better to add all notations in a Table for easy understanding. 5) The organization of the paper should be improved. For example, Sec. 5 has the proposed technique as well as results. I suggest putting them into two separate sections. 6) Does the results shown in various tables and figures refer to multiple runs (average)? In the latter case, I will suggest adding standard deviation bars. The reason behind this is to ensure that whether the results overlap with the closest rivals or not. 7) How about the time and space complexity of the proposed algorithms? 8) The evaluation section is written well. However, it is not clear how the simulations were performed? Which optimization tool was used? The experimental section, in particular, the setup and parameters being used, needs further explanation. Furthermore, the evaluation metrics should be briefly described. 9) I suggest adding pseudo-code for the proposed algorithm. Various procedures in the algorithm needs explanation. I suggest step-by-step details of the algorithm. 10) English can be improved. Proofreading should ensure the appropriate use of grammar, tenses, and punctuations. Longer sentences should be converted into smaller ones. Many words are missing their articles (the, a, an). Many punctuation characters are missing, and some are redundant.

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.

Title: IMPROVED GENETIC ALGORITHM OPTIMIZED LSTM MODEL AND ITS APPLICATION IN SHORT-TERM TRAFFIC FLOW PREDICTION Review round: 2 Reviewer: 1

Basic reporting: The authors have addressed my comments properly. Therefore, this paper can be accepted in its present form. Experimental design: no comment Validity of the findings: no comment Additional comments: No additional comments

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.

Title: IMPROVED GENETIC ALGORITHM OPTIMIZED LSTM MODEL AND ITS APPLICATION IN SHORT-TERM TRAFFIC FLOW PREDICTION Review round: 2 Reviewer: 2

Basic reporting: The revised version is much better than the original submission. However, structure of the manuscript should be improved. Experimental design: The authors have improved their experimental discussion in the revision stage. Validity of the findings: The manuscript is well written, and the conclusions are supported by the experiments. Additional comments: Please address the following comments: 1) I suggest adding a paragraph that describes the organization of the paper in the introduction section. Usually, this should appear just after the contribution list. 2) Furthermore, some sections are not numbered, while others are labeled incorrectly. I suggest that authors be consistent all over the paper. 3) The paper desires proofreading and substantial struggles to correct grammar, linguistic, and punctuation errors. I cannot list them all, but the majority are punctuation mistakes. Some sentences do not make sense at all and should be rephrased.

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.

Title: IMPROVED GENETIC ALGORITHM OPTIMIZED LSTM MODEL AND ITS APPLICATION IN SHORT-TERM TRAFFIC FLOW PREDICTION Review round: 3 Reviewer: 1

Basic reporting: Well improved. Experimental design: Well written. Validity of the findings: The revised version has potential merit for publication. Additional comments: N/A

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.

Title: THE ACCURACY OF RANDOM FOREST PERFORMANCE CAN BE IMPROVED BY CONDUCTING A FEATURE SELECTION WITH A BALANCING STRATEGY Review round: 1 Reviewer: 1

Basic reporting: no comment Experimental design: no comment Validity of the findings: no comment Additional comments: 1. According to the Abstract and Introduction sections, the purpose of this paper is to improve the accuracy and processing speed of random forest, but the actual research only reflects the accuracy and does not analyze the processing speed improvement. 2. The parameters or hyperparameters of machine learning algorithm also have a great impact on the accuracy of the model. This work mainly studies the influence and improvement methods of feature screening and unbalanced data on the model accuracy of random forest, but does not study the influence of algorithm parameter or hyperparameter optimization methods (such as Bayesian hyperparameter optimization, refer to sun et al. 2020, 2021, Doi: 10.1016/j.geomorph.2020.107201, Doi: 10.1016/j.enggeo.2020.105972), and the present work cannot cover the subject. It is suggested to add "feature selection" and "SMOTE" to modify the title. 3. Does the features selection methods proposed in this work have comparative advantages with the widely used recursive feature elimination (RFE) methods, such as Zhou et al. (2021) used in DOI: 10.1016 / j.gsf. 2021.101211? 4. For the Conceptual method and Epilepsy data sets, the model effect is not good with lower accuracy and F1 score, whether it is improved or not. The possible causes should be analyzed in the discussion section. 5. There are meaningless to use broken lines in figure 2-4. It is suggested to change broken lines to histograms. 6. The number of factors of each data set by using each feature selection method are recommended to be expressed in a table. 7. Compared with table 2, the expression of conclusion a and b is inaccurate and confusing, which is recommended to be modified. 8. Table cs-68916-7_CNAE in the Supplemental Files seems incomplete, missing feature X1. 9. It is strongly recommended to add the content of the Discussion section. 10. See the Attachment PDF File for other writing errors.

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.

Title: THE ACCURACY OF RANDOM FOREST PERFORMANCE CAN BE IMPROVED BY CONDUCTING A FEATURE SELECTION WITH A BALANCING STRATEGY Review round: 1 Reviewer: 2

Basic reporting: This paper proposes a method to improve accuracy performance in random forest. Some important comments: 1. The main contribution of this paper is not explained, for example the difference with previous studies. 2. Explanation of the flow of thought on how IG uses the standard deviation (SD) as a threshold, because the standard deviation is a measure of the spread of data, not the concentration of data. Is the purpose of using SD as a threshold described in the paper the same as the research of Sindhu and Radha, 2020? 3. In line 66, it is explained that the IG threshold using the standard deviation is less successful in determining the threshold when considering data balance, then in this study using the median. How to explain the flow of thought? 4. It is necessary to explain the flow of thought why IG needs to be transformed using FFT, then to determine the threshold only use the real part. What does the real and imaginary part after the FFT process represent? Experimental design: 1. In this study using several unbalanced datasets, for performance measurement why only use accuracy, it is better to add others. 2. Why for data separation using k-fold cross validation, not using a certain proportion between training and testing? 3. In Figure 1, a flow chart that explains the SMOTE process for those with more than two classes, needs to be described in more detail, preferably with an example. Validity of the findings: 1. In Figure 4, the term first-SMOTE appears, what does it mean, where is it explained? 2. In the results and discussion, the results obtained need to be explained more comprehensively based on the results of previous studies. For example in Figure 4A, why does the dermatology-first smote accuracy decrease sharply using the median threshold. Additional comments: 1. Split data using K-Fold validation instead of K-Folt validation (typo) 2. It should be added in the background, the difference between the current research and previous research conducted by the researcher (it can be described as a kind of research roadmap). 3. In the conclusion section, write a comprehensive conclusion, not just in the form of points without the connection between points.

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.

Title: THE ACCURACY OF RANDOM FOREST PERFORMANCE CAN BE IMPROVED BY CONDUCTING A FEATURE SELECTION WITH A BALANCING STRATEGY Review round: 2 Reviewer: 1

Basic reporting: 1) I think the 3 references mentioned in Concern #2 and # 3 of the last review comments should be added to the references to elaborate the research background in the Introduction section. Experimental design: None Validity of the findings: 2) Due to feature selection and SMOTE are common model optimization method in machine learning, it suggested to further strengthen the major contribution of this work concern on the influence and improvement methods of feature selection and SMOTE on the model accuracy and processing speed of random forest in the Introduction and Discussion section. Additional comments: None

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.

Title: THE ACCURACY OF RANDOM FOREST PERFORMANCE CAN BE IMPROVED BY CONDUCTING A FEATURE SELECTION WITH A BALANCING STRATEGY Review round: 2 Reviewer: 2

Basic reporting: All previous concerns have been addressed. Experimental design: The corrections have been done as per requirement. Validity of the findings: All suggestions have been fulfilled Additional comments: The authors must improve the grammar of English writing

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.

Title: THE ACCURACY OF RANDOM FOREST PERFORMANCE CAN BE IMPROVED BY CONDUCTING A FEATURE SELECTION WITH A BALANCING STRATEGY Review round: 3 Reviewer: 1

Basic reporting: All previous concerns have been addressed. Experimental design: None Validity of the findings: All previous concerns have been addressed. Additional comments: None

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.

Title: FG-DROID: GROUPING BASED FEATURE SIZE REDUCTION FOR ANDROID MALWARE DETECTION Review round: 1 Reviewer: 1

Basic reporting: The English language used in the paper is not up to publishable academic standards. The abstract is written in the past tense. Apart from numerous grammatical mistakes, there are many spelling mistakes in the paper. What makes it worst, the text written from lines 174 to 177 is in some other language (possibly Turkish). The above-mentioned mistakes prove that the author did not bother to proofread the paper before submission. This is unacceptable. The literature review skeleton is good. However, a lot of language mistakes make it difficult to follow. Moreover, a comparison table of the reviewed papers should be included. Figure 5 (Pseudo Code): It appears that the Pseudocode is generated through some automated tool. Convert it to write it in standard algorithm notations. The current form is unacceptable, Experimental design: Needs to be reconsidered Validity of the findings: The author proposes a reduced feature set (using just 11 static features) that is enough for classification tasks for Android malware and Benign apps. Moreover, the author claims that there is no need for an extended feature set for the classification task. I have some concerns in this regard: 1) Most of the literature published in the Android malware detection domain use significantly big feature sets for malware detection and classification tasks. The proposed techniques (I can not mention a single here because there are loads of them) have claimed up to 99% detection accuracy by using larger feature sets. Moreover, a lot of them are using fairly big datasets as compared to this study. How would you compare your results with them? 2) Another concern is about adversarial evasion attacks. A small feature set is more vulnerable to evasion attacks than compared to a diverse feature set. Have you considered it? 3) I can see that this study uses around 6k malware and 900+ benign samples. How can you justify this distribution? Normally, balanced datasets are employed. However, in real-world situations, malware samples are always less than benign, therefore, an unbalanced dataset (more benign and less malware still makes sense (As used in Drebin)). 4) You have used Drebin and Genome datasets. Just to let you know that all the malware samples in Genome are already a part of the Drebin dataset. Therefore no need to use the Genome as a separate dataset. 5) Drebin dataset is now obsolete. The apps in Drebin were gathered from 2010-to 2012. That's a decade old now. Please consider new datasets. A good option would be to use KronoDroid (2021). 6) Figure 8 is an example of poor presentation of results. Additional comments: Although the paper should be rejected, however, I am suggesting a major revision at this stage point. All my concerns should be addressed one by one in rebuttal for further considereation.

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.

Title: FG-DROID: GROUPING BASED FEATURE SIZE REDUCTION FOR ANDROID MALWARE DETECTION Review round: 1 Reviewer: 2

Basic reporting: The English language should be improved to ensure that an international audience can clearly understand your text. Their are too many grammatical mistakes, the article need to go through proofreading Introduction should be rewrite again Missing sentences in Line 16 This has resulted in the undesired installation of Android apks that violate user privacy or malicious ??? Line 32 it -> It, Also, too many use of 'it' in paragraph Line 45 ->When malicious applications Access user mobil devices - correct it Line 51 ->suffiecient -> correct it sufficient Line 55 -> Malware detection mechanism in different types have been proposed to address this (WHAT IS THIS?? IN THIS SENTENCE)need in the security mechanism. These (?) are signature-based approach ... Line 79 wit -> with Experimental design: Line 238 While adding to the csv file, malicious and benign applications were labeled. Please explain How the data is labeled in Figure 2 Line 241 The processing steps shown in Figure-2 were carried out by means of an automatic code, and it is a very fast feature extraction process. How this process is fast? please explain in detail Automatic Feature Extraction and Pre-processing section need to be explain properly. Things are overlapping and explained shortly. Validity of the findings: Explain how FG-droid is efficient as mentioned in contribution? Line 427 -> While some of these obtained features contribute positively to the classification performance, some may have no effect at all, and some may have a deteriorating effect. Explain How? What are their limitations? What have you achieved? Additional comments: In this study, FG-Droid, a machine-learning based classifier, using the method of grouping the features obtained by static analysis, was proposed. It was created because of experiments with Machine learning (ML), DNN, RNN, LSTM and GRU based models using Drebin, Genome and Arslan datasets. However, Clear, unambiguous, professional English language is missing throughout the paper. Overall the structure of the paper need to be modified again. Experimental evaluation with other studies are missing in terms of novelty.

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.

Title: FG-DROID: GROUPING BASED FEATURE SIZE REDUCTION FOR ANDROID MALWARE DETECTION Review round: 2 Reviewer: 1

Basic reporting: I strongly recommend the authors to re-write the last sentence in the abstract. The word "thanks to" should be replaced. Apart from that, the paper satisfies the publication standards. Experimental design: Good Validity of the findings: Justified Additional comments: The author has put a lot of effort to enhance the quality of the work. I am happy to accept the paper for publication.

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.

Title: A RETROSPECTIVE STUDY OF 3D DEEP LEARNING APPROACH INCORPORATING COORDINATE INFORMATION TO IMPROVE THE SEGMENTATION OF PRE- AND POST-OPERATIVE ABDOMINAL AORTIC ANEURYSM Review round: 1 Reviewer: 1

Basic reporting: a. Clear and unambiguous, professional English used throughout. The paper is generally well-written and easy to follow, despite some sentences are confusing and need revisions: Line 252-253 (“The experiments were implemented using the PyTorch (v1.8.0) deep learning library with Tensorflow backend in Python”) is confusing as PyTorch and TensorFlow are two different DL libraries, and as far as I know, TensorFlow cannot be used as backend of PyTorch; Line 273-274 (“… the non-contrast and contrast-enhanced datasets in consecutive arrays were combined in another experiment”) says there is “another experiment”, please make it clear which experiment is referred to here. b. Literature references, sufficient field background/context provided. The paper introduces sufficient background on AAA segmentation. However, while coordinating information and transfer learning are the two main techniques of this paper, the related work section only briefly introduces them. As they are not originally proposed by the authors, it is important to provide more details on these two methods. Also, in lines 156-157 (ResNet is a kind of popular network that has been proven effective in medical data), ResNet deserves a more detailed explanation, and reference should be provided on the claim that it is effective in medical data. c. Professional article structure, figures, tables. Raw data shared. Figure 5 training curve is hard to read. Increasing the resolution of the font is encouraged. d. Self-contained with relevant results to hypotheses. No comment. e. Formal results should include clear definitions of all terms and theorems and detailed proofs. No comment. Experimental design: a. Original primary research within the Aims and Scope of the journal. No comment. b. Research question well defined, relevant & meaningful. It is stated how research fills an identified knowledge gap. The paper conducts extensive experiments on the proposed coordinate integration methods. As the use of positional encoding is a hot topic in computer vision, how does the proposed scheme compare to other positional encoding method, for example, the fixed positional encoding in [1] (use sinusoid to encode the position) or learnable positional encoding? [1] Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł. and Polosukhin, I., 2017. Attention is all you need. Advances in neural information processing systems, 30. c. Rigorous investigation performed to a high technical & ethical standard. No comment. d. Methods described with sufficient detail & information to replicate. Line 233 is suggested to change into “the input data for CNN will be two or four”. Validity of the findings: a. Impact and novelty not assessed. Meaningful replication encouraged where rationale & benefit to literature is clearly stated. No comment b. All underlying data have been provided; they are robust, statistically sound, & controlled. No comment. c. Conclusions are well stated, linked to original research question & limited to supporting results. c.1: In table 2, we can see that the integration of coordinate information as an additional input only has marginal improvement over the baseline UNet. For example, in the contrast-enhanced dataset the DSC and JSC improvement is less than 0.2% in UNet. This challenges the main contribution of this paper. On the other hand, the coordinate information significantly improves the performance of DenseVoxNet, and the authors explain in line 376-379 that coordinate information make the network converges easier. I would suggest investigating further on this direction. c.2: The author states that the main limitation of CNN-based methods is the limited size of input data, due to the GPU memory constraints. The common practice in medical deep learning is to use patch-based inference, which means a 512x512x64 volume can be patched into multiple, e.g. 256x256x32 patches so as to maintain the original resolution. In this paper, the authors choose to scale down the image volume. Additional comments: This paper proposes incorporating voxel position as an additional input for AAA segmentation. The paper needs more work on the related work section, including how the proposed coordinate encoding scheme compared to previous works, and why the scheme would be a good fit for the problem as well as transfer learning. The authors conduct extensive experiments on various network architectures, nevertheless, the improvement is marginal over the baseline UNet. Also, the novelty of the proposed method is insufficient and most of the work is derivative. I suggest looking at more methods to incorporate positional information, e.g. in multiple layers, or a better encoding scheme.

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.

Title: A RETROSPECTIVE STUDY OF 3D DEEP LEARNING APPROACH INCORPORATING COORDINATE INFORMATION TO IMPROVE THE SEGMENTATION OF PRE- AND POST-OPERATIVE ABDOMINAL AORTIC ANEURYSM Review round: 1 Reviewer: 2

Basic reporting: This paper presents a new 3D AAA segmentation approach that incorporates coordinate information to improve the segmentation results. The authors have tested the proposed method on various network architectures, including UNet, AG-DSV-UNet, VNet, ResNetMed, and DenseVoxNet, and transfer learning from a network pre-trained on the pre-operative dataset to post-operative EVAR. 1. The authors didn't explain how to obtain the coordinate information for test images, which was critical to applying the proposed method in real-world applications. We usually use prediction methods for unseen images in practice, and obtaining coordinate information for these images could be difficult. ** Please provide the related explanation in the paper. 2. Some recently published related works are not referred to and compared in the paper. For example [1] Wang, Yan, Florent Seguro, Evan Kao, Yue Zhang, Farshid Faraji, Chengcheng Zhu, Henrik Haraldsson, Michael Hope, David Saloner, and Jing Liu. "Segmentation of lumen and outer wall of abdominal aortic aneurysms from 3D black-blood MRI with a registration based geodesic active contour model." Medical image analysis 40 (2017): 1-10. [2] Salvi, Anish, Ender Finol, and Prahlad G. Menon. "Convolutional Neural Network-based Segmentation of Abdominal Aortic Aneurysms." In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 2629-2632. IEEE, 2021. [3] Dziubich, Tomasz, Paweł Białas, Łukasz Znaniecki, Joanna Halman, and Jakub Brzeziński. "Abdominal aortic aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks." In ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium, pp. 158-168. Springer, Cham, 2020. [4] Wang, Yan, Florent Seguro, Evan Kao, Yue Zhang, Farshid Faraji, Chengcheng Zhu, Henrik Haraldsson, Michael Hope, David Saloner, and Jing Liu. "Segmentation of lumen and outer wall of abdominal aortic aneurysms from 3D black-blood MRI with a registration based geodesic active contour model." Medical image analysis 40 (2017): 1-10. ** Please read and cite these papers accordingly in your paper. Experimental design: 1. No validation set is created and used in transfer learning so it is unclear to me how do the authors tune the model hyper-parameters in this case. Please describe it in detail in the paper. 2. Please provide a detailed definition of dice score, including how to compute it. Validity of the findings: no comment Additional comments: No additional comments

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.

Title: EFFECTIVE ATTRIBUTED NETWORK EMBEDDING WITH INFORMATION BEHAVIOR EXTRACTION Review round: 1 Reviewer: 1

Basic reporting: Throughout the manuscript, this paper uses clear and unambiguous professional English. Although adequate literature references and field background/context are provided, the literature discussion is missing a few related works. The proposed method is self-contained, with results correlating to hypotheses. The formal results should contain precise definitions of all terms and theorems, as well as detailed proofs. Experimental design: Numerous evaluation results corroborate the proposed method. The research question is clearly defined, pertinent, and meaningful. It is stated how research fills a knowledge gap that has been identified. Extensive investigation conducted to the highest technical and ethical standards. Methods described in sufficient detail and detail to permit replication. Validity of the findings: The underlying experimental results have been provided in its entirety; they are robust, statistically sound, and well-controlled. Conclusions are succinct, relevant to the original research question, and limited to supporting data. Additional comments: This manuscript is written in clear and unambiguous professional English throughout. While adequate references to the literature and background/context of the field are provided, the literature discussion is missing a few related works [1,2,3,4,5]. The proposed method is self-contained and produces results that are consistent with hypotheses. All terms and theorems should have precise definitions in the formal results, as well as detailed proofs. [1] WebFormer: The Web-page Transformer for Structure Information Extraction---WWW 2022 [2] A vector-based representation to enhance head pose estimation---WACV 2021 [3] Sg-net: Spatial granularity network for one-stage video instance segmentation---CVPR 2021 [4] DenserNet: Weakly supervised visual localization using multi-scale feature aggregation---AAAI 2021 [5] Video object detection for autonomous driving: Motion-aid feature calibration---Neurocomputing 2021

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.

Title: EFFECTIVE ATTRIBUTED NETWORK EMBEDDING WITH INFORMATION BEHAVIOR EXTRACTION Review round: 1 Reviewer: 2

Basic reporting: This manuscript captures the structural and attribute features of the network using existing network embedding algorithms, and proposes the TNE model to extract additional information behavior features. Finally, the link prediction performance of the network is improved. 1.The number of references in the past three years (2019-2022) is only two, and it is recommended to add more latest references. Experimental design: 1. In EXPERIMENTS, the latest comparison algorithm is from 2017, and it is recommended to add newer algorithms for comparison. 2.From the descriptions of Section 3 and Section 4, it can be seen that the extraction of node information behavior features requires additional topic information. From the experiment, the topic information seems to be the category information of the node. That is, in Table 2, the algorithm of the manuscript is supervised, while the algorithm used for comparison is unsupervised, that seems unfair. It is recommended to add some supervised/semi-supervised graph neural network, such as GAT, GIN, for comparison (the amount of information (category information) used should be consistent). 3.The overall performance of the algorithm is improved, but the increase in time complexity caused by adding information behavior features is worrying, such as the calculation of parameters \alpha. It is recommended to add time complexity analysis, including elaboration of the average number of cycles (convergence rate) of the ISR algorithm. 4.The number of topics in Zhihu described in Table 1 is empty, what is the basis for setting the number of topics as 13 in the experiment? 5.It is recommended to include a graph of the Importance Score distribution of nodes in the experiment to eliminate the concern that the importance may all be clustered into a very small number of nodes. 6.The manuscript adds Parameter sensitivity analysis, that is good. In the analysis of the topic number j, it is best to add a description of the implementation, for example, for nodes with unknown topics, how are they handled in the ISR algorithm? Validity of the findings: no comment Additional comments: 1.The manuscript does not mention the algorithms incorporating information behavior in INTRODUCTION or RELATED WORK, which seems to imply that this manuscript is the first network embedding work that incorporates information behavior. Is this true? If so, please state clearly in ABSTRACT and INTROCUCTION. If not, please add the description of the corresponding algorithms, and add the comparative experiment of some corresponding algorithms in the experimental section. 2.Are the information behavior features and node categories the same? If so, a large number of related papers have proposed, that adding information behavior features cannot be a bright spot. If not, does the dataset in the experiment reflect the difference between them?

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.

Title: EFFECTIVE ATTRIBUTED NETWORK EMBEDDING WITH INFORMATION BEHAVIOR EXTRACTION Review round: 1 Reviewer: 3

Basic reporting: This paper presents an embedding method of attribute network through ISR algorithm and topic sensitive embedding matrix. Then, the above embedding is spliced into the embedding obtained by the existing characterization methods through appropriate methods. In this paper, experiments are conducted to verify the effectiveness of the method. However, this paper also has some issues. 1. The main purpose of this method is to obtain the embedding of attribute network, but it is not compared with the latest attribute network embedding methods. It is suggested to add relevant baseline algorithms, such as GCN[1], GAT[2] and AM-GCN[3]. 2. There are lots of advanced attributed network embedding methods that should be discussed in the related work, such as MAGNN[4], FAME[5]. 3. The datasets used in this paper are relatively small, and efficiency verification should be carried out on large-scale datasets. 4. Ablation experiments should be conducted to verify the effectiveness of model components. [1] Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR. [2] Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio. 2018. Graph Attention Networks. In ICLR. [3] Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, and Jian Pei. 2020. Am-gcn: Adaptive multi-channel graph convolutional networks. In KDD. 1243–1253. [4] Xinyu Fu, Jiani Zhang, Ziqiao Meng, and Irwin King. 2020. Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding. In WWW. 2331–2341. [5] Zhijun Liu, Chao Huang, Yanwei Yu, Baode Fan, and Junyu Dong. 2020. Fast Attributed Multiplex Heterogeneous Network Embedding. In CIKM. 995–1004. Experimental design: no comment Validity of the findings: no comment Additional comments: no comment

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.

Title: EFFECTIVE ATTRIBUTED NETWORK EMBEDDING WITH INFORMATION BEHAVIOR EXTRACTION Review round: 2 Reviewer: 1

Basic reporting: This is a revised manuscript and the authors have revised most of the comments raised by the reviewers. The quality of manuscript has been signficantly improved. Experimental design: Experimental evaluation has been improved. Validity of the findings: The proposed TNE model improves the performance of existing embedding models. Additional comments: NA

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.

Title: AWARENESS OF SECURITY AND PRIVACY SETTINGS IN VIDEO CONFERENCING APPS AMONG FACULTY DURING THE COVID-19 PANDEMIC Review round: 1 Reviewer: 1

Basic reporting: This study investigated security and privacy awareness among academics in Saudi Arabia relating to the use of video conferencing apps. Authors theoretical claim seems to be acceptable but there is no novelty in the work. The authors try to replicate the same story throughout the paper. Experimental design: A survey experiment research design is employed in this paper Validity of the findings: There are few experimental findings in the paper and it is not sufficient. Need more experimental analysis on the data. Additional comments: No additional comments

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.

Title: AWARENESS OF SECURITY AND PRIVACY SETTINGS IN VIDEO CONFERENCING APPS AMONG FACULTY DURING THE COVID-19 PANDEMIC Review round: 1 Reviewer: 2

Basic reporting: No comment Experimental design: Since video conference apps are common among all kinds of professions and why this survey is targeted at academicians? What is the logic behind the calculation of the security awareness score? Is this study proposes any particular application as a safer one out of this study? Validity of the findings: The considered sample size should have been higher to come to one conclusion. Possibility of having high bias due to the non respondents and sample size age group wise findings should have been included What was the duration of data collection? Collection through WhatsApp, LinkedIn, Telegram, and Twitter is a viable way to reach academicians? What is being considered as Non-STEM category as Math and Science also considered in STEM category Additional comments: Results based discussion should be much more elaborated based on the findings The metrics used should be properly explained Sample questionnaire can be included

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.

Title: AWARENESS OF SECURITY AND PRIVACY SETTINGS IN VIDEO CONFERENCING APPS AMONG FACULTY DURING THE COVID-19 PANDEMIC Review round: 1 Reviewer: 3

Basic reporting: This study examines the factors that influence academics' actual awareness of security and privacy in relation to videoconferencing apps. The data are based on a recent survey and PLS-SEM is used. This is a timeless study and SEM is appropriate. Some results are not plausible. For example, the results that perceived security awareness is negatively related to actual security and privacy awareness are a bit strange. The document needs improvement in all aspects. Below there are a number of comments that must be addressed Main comments Introduction: Please try to improve the description of the purpose of the research. Please add one sentence on the data and methods used (PLS-SEM). Please also clearly state the contribution of the research. Is it the first study on privacy and security issues of video conferencing apps? Conceptual background: Section 2 “e-learning in Saudi Arabia” should be improved. The paragraph on internet speed does not fit. Section: Video conferencing in online learning. Please cite more recent references. Video conferencing apps greatly improved. References from 1976 are not helpful here. The theoretical background must be improved: Privacy issues cannot be explained by privacy concerns (see H3). There is a correlation by definition. The theoretical framework is inadequate. Think clearly about what is the dependent variable and what is the independent variable. From my point of view there are too many hypotheses. Experimental design: PLS-SEM cannot estimate causal relationships. What you estimate are correlations. You need to be more careful in the interpretation of results (e.g., not writing ”x impacts y ”, or ”has effect on ”) and generally create awareness that a correlation does not necessarily indicate causation. Apart from acknowledging that endogeneity might be present, there are also ways to deal with endogeneity, such as instrumental variables, control function approaches, propensity score matching, experiments and natural experiments. Hair et al. (2020) note that four conditions must be met to assume causality: (1) Time sequence —the cause must occur prior to the effect; (2) Covariance —changes in the hypothesized independent variable are associated with changes in the dependent variable; (3) Non-spurious associations — the relationship is not due to other variables that may affect cause and effect; and (4) Theoretical support — a logical explanation for the relationship. Reference Hair, J. F., Jr , Howard, M. C. , & Nitzl, C. (2020a). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109 , 101–110 . Pesämaa, O., Zwikael, O., HairJr, J., & Huemann, M. (2021). Publishing quantitative papers with rigor and transparency. International Journal of Project Management, 39(3), 217-222 Validity of the findings: Method: PLS-SEM is used. Yes it is correct that PLS-SEM is estimated by least squares. Please add information on the stata command. Robustness checks are missing. Please report some validity tests (Degree of correlation between constructs, Path significance -Assesses how strongly two constructs relate to each other, Coefficient of determination - Measure of the predictive accuracy of the structural model, Effect size- Measure of the impact of the exogenous construct on the endogenous one, Predictive relevance - Measure of a model's predictive power and Robustness checks). The article needs to be thoroughly edited and proofread by a qualified language editor. There is an illogical flow of ideas and a lack of coherence. Sections are disjointed without any link between them. Additional comments: no comment.

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.

Title: AWARENESS OF SECURITY AND PRIVACY SETTINGS IN VIDEO CONFERENCING APPS AMONG FACULTY DURING THE COVID-19 PANDEMIC Review round: 2 Reviewer: 1

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

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.

Title: AWARENESS OF SECURITY AND PRIVACY SETTINGS IN VIDEO CONFERENCING APPS AMONG FACULTY DURING THE COVID-19 PANDEMIC Review round: 2 Reviewer: 2

Basic reporting: The comments are given in the previous review are addressed by the authors Experimental design: Ok Validity of the findings: Ok Additional comments: Nil

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.

Title: AWARENESS OF SECURITY AND PRIVACY SETTINGS IN VIDEO CONFERENCING APPS AMONG FACULTY DURING THE COVID-19 PANDEMIC Review round: 2 Reviewer: 3

Basic reporting: Some of the hypotheses are trivial and self-explanatory: check them out: Perceived security awareness has a higher awareness of the security and privacy settings of video conferencing apps. I suggest to de-emphasise this. . Experimental design: "We used a survey experiment to determine " Please rewrite. This paper applied PLS-SEM to a stand alone survey. This is not an experimental design. Validity of the findings: PLS-SEM Please report all the needed validity tests for the measurement and structural model. This part is not complete. Additional comments: Please follow the style guidelines Alammary, A., A. Carbone, and J. Sheard. 2016. “Blended Learning in Higher Education: Delivery Methods Selection.” In Twenty-Fourth European Conference on Information Systems (ECIS 2016). İstanbul,Turkey. Alammary, Ali, Moneer Alshaikh, and Areej Alhogail. 2021. “The Impact of the COVID-19 Pandemic on the Adoption of e-Learning among Academics in Saudi Arabia.” Behaviour & Information Technology, September, 1–23. https://doi.org/10.1080/0144929x.2021.1973106

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.

Title: AWARENESS OF SECURITY AND PRIVACY SETTINGS IN VIDEO CONFERENCING APPS AMONG FACULTY DURING THE COVID-19 PANDEMIC Review round: 3 Reviewer: 1

Basic reporting: The revised version looks good to me Conclusions Please provide information on the limitations The text is not always smooth. The language can be improved. See an example: Privacy concerns are significantly associated with higher awareness only for STEM faculty, while attitudes toward ICT for teaching and learning is negatively associated with such awareness among faculty with more than 10 years of experience. -> Privacy concerns are significantly associated with higher awareness only among teachers of STEM subjects, while attitudes towards ICT for teaching and learning are negatively associated with such awareness among teachers with more than 10 years of experience. Experimental design: PLS-SEM is standard. All tests are reported Validity of the findings: OK Additional comments: No additional comments

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.

Title: AN EMPIRICAL BAYES APPROACH TO STOCHASTIC BLOCKMODELS AND GRAPHONS: SHRINKAGE ESTIMATION AND MODEL SELECTION Review round: 1 Reviewer: 1

Basic reporting: The papers appears to meet all the basic reporting requirements of the journal. Regarding the literature review, I only have one minor concern (see bullet point #1 in my list in the section ‘Additional comments’). Experimental design: The papers appears to meet all the experimental design requirements of the journal. Validity of the findings: The papers appears to meet all the requirements of the journal around validity of the findings. Additional comments: The paper proposes a simple yet effective empirical Bayes estimator for the block connectivity matrix in stochastic blockmodel, conditional on an estimate of the community structure. The authors also discuss implications of their work in terms of graphon estimation, using the stochastic blockmodel approximation to graphons. The paper is well presented and the methodologies clearly explained. The methods presented in this article are particularly relevant for the communities interested in network analysis and community detection, therefore I believe the paper would fit well within the aims and scope of the journal. Some of my main concerns are summarised below: 1. The problem of correctly selecting the number of communities K is mentioned, but existing methods for estimation of K are not discussed. I believe a brief literature review on criteria for model selection should be included, considering that this is one of the central aspects of the work. For example, in the context of spectral graph clustering, a good reference for this would be Yang et al. (JCGS, 2021). 2. Page 4, before equation (12) — A Jeffreys prior is chosen for the partition probabilities, but no discussion is provided on the reasoning behind this choice and potential implications. What is the effect of the prior parameters \tau on the performance of the estimation procedure for K? It would be good to comment on this (maybe examining limit cases such as \tau to 0 or to infinity — or via simulations). 3. The simulations presented in the section ‘Results / Simulation’ (page 7 onwards) are fairly simple: the simulated networks are strongly assortative and the block connectivity probabilities are highly homogeneous. It is reasonable and expected to see a shrinkage estimator to have a better performance under this scenario. It would be interesting to see how the performance changes when heterogeneous block connectivity probabilities are used (maybe adding such additional simulations to the supplementary material). 4. Lines 182 and 188, page 8 — The two simulation scenarios are referred to as ‘dense’ and ‘sparse’. Commonly, sparsity for graphs is defined as the number of nodes grows to infinity and the number of edges grows sub-quadratically (see e.g. Caron and Fox, JRSSB, 2017). Here, the term ‘sparse’ appears to be used instead to mean that the setting for model 2 is just sparser than model 1. I believe that this should be clarified to avoid confusion for the readers. It might be appropriate to simply report the expected edge density under the two parameter settings, to better appreciate the difference between the two simulations. 5. The ‘Real data examples’ section on page 15 onwards assumes that the node labels available for the email network and political blogs network are actually representative of network connectivity. Often in real world networks, the assumption of a stochastic blockmodel is limiting, since it assumes extremely simple IID binomial within-community degree distributions — degree-corrected stochastic blockmodel (Karrer and Newman, 2011) might therefore be appropriate in the presence of within-community degree heterogeneity. Since the labels are used to assess the effectiveness of the proposed methodologies, would it be possible to evaluate (maybe via hypothesis testing) whether the blocks obtained from the available labels are representative of a stochastic blockmodel? In my opinion, this would make the real data analysis more convincing. 6. The choice of possible values of K for the email network appears to be only between 30 and 50. Many times in practice much smaller numbers of communities are sought. It would be interesting to see the performance of the models also for K starting from 1 as in the political blogs example, if possible. Minor details: The hyperreferences in the PDF document are not displayed correctly — see e.g. Figure ?? on page 5, line 130; (Section ) on page 7, lines 175-176. References: - Caron, F. and Fox, E.B. (2017), Sparse graphs using exchangeable random measures. J. R. Stat. Soc. B, 79: 1295-1366. https://doi.org/10.1111/rssb.12233 - Congyuan Yang, Carey E. Priebe, Youngser Park & David J. Marchette (2021) Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering, Journal of Computational and Graphical Statistics, 30:2, 422-441, DOI: 10.1080/10618600.2020.1824870 - B Karrer, MEJ Newman (2011), Stochastic blockmodels and community structure in networks, Physical Review E 83 (1), 016107

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.

Title: AN EMPIRICAL BAYES APPROACH TO STOCHASTIC BLOCKMODELS AND GRAPHONS: SHRINKAGE ESTIMATION AND MODEL SELECTION Review round: 1 Reviewer: 2

Basic reporting: The article is mostly well-written, however there are a few sentences which are not clear (please see specific comments below) and improvements can be made in the section on future work. The literature cited is relevant however it does not reflect the breadth of research done on the topic. Thus, I would recommend the authors to find the latest articles on this topic without necessarily restricting to Bayesian techniques. More can be done to provide a deeper context to the problem. A simple example illustrating the requirement for shrinkage with existing graphon estimation techniques say would be helpful. The paper is structured well and figures, tables etc are clear. Experimental design: The research question is well defined and meaningful, however, as mentioned above, a specific example would be helpful in providing context and understanding the relevance of the shrinkage problem. Investigations have been performed via simulations and two data sets (please see specific comments regarding this). The description of methods used for simulations and data analysis should be further clarified with the exact steps mentioned clearly. Validity of the findings: Benefit to literature is clearly stated but is not fully evident from existing analyses and presentation. Some further work and a clear reporting should help confirm the validity of the findings and also make the contribution of wider interest. Additional comments: Specific comments: p.1. line 40: clarify symmetry/undirected networks p.2, line 74: `Empirical Bayes method is usually seen to have better performance when estimating many similar and variable quantities' : -What does 'similar' and 'variable' mean exactly and why is this the case briefly? - p.2, line 76: How `small' is the network size that you refer to here? -p.5, line 130: missing figure number (??). Please check carefully throughout the document for referencing. -p.7, line 175-176: labels of sections missing -p.15, line 267-8: need rephrasing it seems. Not clear. -p.2, around eqn 2.: is it assumed that n nodes are divided into K blocks, each allowed to be of a different size? If yes, please include it in the description here. -p.5, line 130: Can there be scenarios where L-BFGS may not succeed in finding the global maxim? Please comment on this in the paper. -p.6: what is the motivation for using ICL (and e.g. not Bayes factors)? p.11: simulations on graphon estimation. What does the graphon model look like? Can a heatmap be included? Results using another graphon example with a different structure would be useful (google scholar results for `graphon estimation' brings up latest articles, many of which report simulation comparisons for a variety of graphon structures). p.11, line 247: the performance of your method over competing methods is reported to be significant in the sparse case. Is this expected? If so, why? - With only the K specified, how are the sizes of different clusters determined ( if they are assumed to be unequal in general)? - In practice multiple labelings of nodes (i.e. different Z's) may be available from different clustering methods. What is the best way to proceed given this? - How sensitive is your approach to different Z's in practice? This is not clear from the simulations. - How may the range of K determined in practice? For example, why is K chosen to be at least 30 and at most 50 in the first data example? - What are the labels z's in eqn (25). It is mentioned that these are 'known labels of the nodes' - what does this mean exactly? Are these the ground truth labels or labels estimated from an existing graph clustering algorithm? My main concern is the simulation and data analyses reported to validate the findings. The MSEs can give a different picture and sometimes be deceptive. I would recommend plotting heatmaps of the estimates from each method directly for a visual confirmation that all methods are working as expected. Further, I understand that this is a Bayesian technique and thus it is fair to include comparisons with other Bayesian methods, however given the vast literature on this topic, it is important that the proposed method is compared with atleast one other non-Bayesian approach (e.g. network histogram of Olhede & Wolfe, 2014 is commonly used). Secondly, why is it fair to use the department-wise labels as the ground truth in the first data example? There may be clusters based on multiple attributes or a combination of them and it is difficult to define ground truth based on node attributes in general. Is there a justification for this approach in this particular case/data set? One of the commonly used methods is to compare the mean squared prediction errors (as in recent graphon estimation papers in statistics for example). It would be useful to see the values that the shrinkage parameter assumes to get insights on what determines estimation of connection probabilities in the two data sets. It would be useful to report the estimated shrinkage \eta's if possible.

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.

Title: AN EMPIRICAL BAYES APPROACH TO STOCHASTIC BLOCKMODELS AND GRAPHONS: SHRINKAGE ESTIMATION AND MODEL SELECTION Review round: 2 Reviewer: 1

Basic reporting: The papers appears to meet all the basic reporting requirements of the journal. Experimental design: The papers appears to meet all the experimental design requirements of the journal. Validity of the findings: The papers appears to meet all the basic validity of the findings requirements of the journal. Additional comments: The revised version of the manuscript addressed the concerns that I expressed in my previous review. I thank the authors for implementing the suggested edits.

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.

Title: ENSEMBLE OF ADAPTED CONVOLUTIONAL NEURAL NETWORKS (CNN) METHODS FOR CLASSIFYING COLON HISTOPATHOLOGICAL IMAGES Review round: 1 Reviewer: 1

Basic reporting: Your work is good, but there are many typos. The English of the article should be checked by an expert. I've marked some of the misspellings in the PDF. I added a comment. You must comply with the warnings. The abstract article is a little weak compared to its content. It should summarize the article in full. Shapes must be developed. All suggested citations should be included. There are too many repeated citations in the article. The article should be rearranged as incoming. Experimental design: The Experimental Result section of the article is a bit weak compared to the other sections. This section is the heart of the article. This is the part that belongs to you. Therefore, this section should be developed. The resolution of the figures should be increased. The biggest shortcoming is that there is no confusion matrix. There are calculations, but there are no confusion matrices used to make these calculations. Add at least the confusion matrix of the model you propose (the most successful model, E-CNN). Include the ROC curve if possible. These will enable the reader to better understand and evaluate the article. Validity of the findings: As stated in the previous comments, more detailed analysis is required to prove the validity of the findings. Additional comments: Correct the article by considering the warnings and comments in the PDF uploaded to the system. Also take into account the comments made in general.

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.

Title: ENSEMBLE OF ADAPTED CONVOLUTIONAL NEURAL NETWORKS (CNN) METHODS FOR CLASSIFYING COLON HISTOPATHOLOGICAL IMAGES Review round: 1 Reviewer: 2

Basic reporting: Figures' quality is not enough. (For more detail, see attachments) Experimental design: The methods, especially how the ensemble learning was applied in this study, was not explained in detail. (For more detail, see attachments) Validity of the findings: The experimental results (training length of networks) is not enough to compare methods. It was not provided how many samples were used to compute the statistical p-values. (For more detail, see attachments) Additional comments: The motivation of this study is promising. However, it is not easy to make sure of the superiority of the proposed model with such short training.

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.

Title: ENSEMBLE OF ADAPTED CONVOLUTIONAL NEURAL NETWORKS (CNN) METHODS FOR CLASSIFYING COLON HISTOPATHOLOGICAL IMAGES Review round: 1 Reviewer: 3

Basic reporting: The paper has some drawbacks: 1. The overview of the related papers should be expanded. It's a very popular research area. I suggest the authors evaluate these papers related to Transfer Learning and Ensemble Learning Techniques: https://www.nature.com/articles/s41598-021-93783-8 https://ieeexplore.ieee.org/document/9107128 2. The presentation of Figures 7, 8 should be improved. Experimental design: What image preprocessing technique do the author use? The authors should present confusion matrices for each dataset. Validity of the findings: The authors used only one dataset for testing and validation. It's not enough. Additional comments: No additional comments

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.

Title: ENSEMBLE OF ADAPTED CONVOLUTIONAL NEURAL NETWORKS (CNN) METHODS FOR CLASSIFYING COLON HISTOPATHOLOGICAL IMAGES Review round: 2 Reviewer: 1

Basic reporting: All requested corrections have been carefully made. The article can be published in my opinion. Experimental design: All requested corrections have been carefully made. The article can be published in my opinion. Validity of the findings: All requested corrections have been carefully made. The article can be published in my opinion. Additional comments: All requested corrections have been carefully made. The article can be published in my opinion.

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.

Title: ENSEMBLE OF ADAPTED CONVOLUTIONAL NEURAL NETWORKS (CNN) METHODS FOR CLASSIFYING COLON HISTOPATHOLOGICAL IMAGES Review round: 2 Reviewer: 2

Basic reporting: The manuscript meets this journal's standards Experimental design: The manuscript meets this journal's standards Validity of the findings: The manuscript meets this journal's standards Additional comments: No additional comments

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.

Title: ENSEMBLE OF ADAPTED CONVOLUTIONAL NEURAL NETWORKS (CNN) METHODS FOR CLASSIFYING COLON HISTOPATHOLOGICAL IMAGES Review round: 2 Reviewer: 3

Basic reporting: The authors addressed all my comments. The paper can be accepted in the present form. Experimental design: - Validity of the findings: - Additional comments: -

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.

Title: SFEDCHAIN: BLOCKCHAIN-BASED FEDERATED LEARNING SCHEME FOR SECURE DATA SHARING IN DISTRIBUTED ENERGY STORAGE NETWORKS Review round: 1 Reviewer: 1

Basic reporting: This paper provides a comprehensive review of research work on privacy-preserving data sharing in the introduction and related literature, and introduces the importance of secure joint modeling in distributed energy storage networks. This paper innovatively proposes a scheme called SFedChain based on blockchain and federated learning to realize the safe sharing of data in distributed energy storage network, which has strong practicability and logic. This paper is innovative in application, considers the scenario of data sharing in distributed energy storage networks, and expounds the importance of data privacy protection. In terms of method and theoretical innovation, this paper realizes efficient joint modeling by combining federated learning to transform data sharing problems into machine learning problems, and uses blockchain technology to record to ensure security, making it more practical. In joint modeling, it is logical to ensure the security and improve the accuracy of joint modeling through the designed encryption parameter upload review mechanism and reputation-based dynamic weight consensus protocol. The experimental results demonstrate the effectiveness and applicability of the method. The research problem in this paper is meaningful, and the method is innovative. The sequence structure is clear and the paper has a good organization structure. However, the manuscript still needs to be modified before it is published. I have several questions listed as follows: 1)There are some Language problems and typos or grammar errors in this manuscript. Many of them could cause difficulties to the readers. 2)The author proposes to use the consortium chain to trace the source of the joint modeling process. Why does this article apply the consortium chain instead of the public chain or private chain? Please give the author a detailed explanation. 3)In the simulation of the attack experiment in Figure 9, the authors should give a more detailed experimental setup. Experimental design: In order to solve the problem of effective data management in the distributed energy storage network, this paper establishes a multi-party data security sharing and privacy protection mechanism, and effectively solves the possible threats to the model through a series of security analysis. This paper uses real benchmark data sets and conducts comparative test analysis to verify that the improved blockchain consensus mechanism and incentive algorithm can effectively improve the accuracy of federated learning. By simulating different proportions of attack intensities, the anti-interference ability of the model is verified. The method has certain novelty. Validity of the findings: In the experimental part of this paper, the theoretical results are reasonable. For the proposed threat model, a reliable solution is provided through security analysis. At the same time, benchmark experiments and comparative verifications demonstrate the effectiveness and robustness of the model, and realize the secure sharing and privacy protection of data in distributed energy storage networks. Additional comments: No additional comments

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.

Title: SFEDCHAIN: BLOCKCHAIN-BASED FEDERATED LEARNING SCHEME FOR SECURE DATA SHARING IN DISTRIBUTED ENERGY STORAGE NETWORKS Review round: 1 Reviewer: 2

Basic reporting: In this work, the authors have proposed a deep learning scheme called SFedChain in distributed energy storage networks to ensure the secure sharing of data between distributed devices and improve the training accuracy of federated learning models. In the new scheme, the three-in-one blockchain architecture is designed for on-chain storage and computation of a large number of model parameters, which is different from the current small-capacity data storage method mainly based on ledgers. It provides an effective solution to the big data storage bottleneck problem of model training parameters in energy storage scenarios. In addition, this scheme designs a secure federated learning model to ensure the security of power data sharing among distributed energy storage nodes. It also solves the problem of aggregator single-point failure and malicious attack in traditional federated learning, and effectively improves the accuracy of the joint model through the designed dynamic weight method. Finally, a series of safety analysis proved the reliability of the scheme. Comparative experiments and performance analysis show the efficiency and anti-interference of the scheme. This paper is well–written. The proposed scheme is quite rational and has a rigorous theoretical reasoning process. The originality is clear. The technology adopted is advanced. The objective evaluation results are reported. The solution is suitable for problem solving in distributed energy storage networks. Hence I would like to recommend to accept the paper for publication. Experimental design: The experimental design is good. Validity of the findings: The findings are valid. Additional comments: 1, In the first paragraph of chapter 1, the “blockchain” is written as “blockchian”. Please proofread carefully. 2, In section 2 of chapter 2, the explanation of 〖ID〗_DH and 〖ID〗_TR are not given when it appears at the first time. 3, In chapter INTRODUCTION, page 2, line 99 - "privacy", use capital "P". Line 118, "In Section 2, We give implementation", Use the small letter "we". 4, The text in Figure 1 is too small, please use a high-quality vector image and adjust the font size.

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.

Title: SFEDCHAIN: BLOCKCHAIN-BASED FEDERATED LEARNING SCHEME FOR SECURE DATA SHARING IN DISTRIBUTED ENERGY STORAGE NETWORKS Review round: 2 Reviewer: 1

Basic reporting: I have no comment. Experimental design: I have no comment. Validity of the findings: I have no comment. Additional comments: No additional comments

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.

Title: FAST AND ACCURATE FACE RECOGNITION SYSTEM USING MORSCMS-LBP ON EMBEDDED CIRCUITS Review round: 1 Reviewer: 1

Basic reporting: Fails in 'Professional article structure, figures, tables. Raw data shared'. All the figures and tables are not embedded in the manuscript. So this manuscript is very hard to read and understand. Experimental design: no comment Validity of the findings: Fails in 'All underlying data have been provided; they are robust, statistically sound, & controlled'. The proposed method was only compard with SOTA methods on the Grimace dataset. Compared with other SOTA methods, how about the performance on the Faces 95 and Faces 96 datasets? Additional comments: All the figures and tables are not embedded in the manuscript. So this manuscript is very hard to read and understand. The proposed method was only compard with SOTA methods on the Grimace dataset. Compared with other SOTA methods, how about the performance on the Faces 95 and Faces 96 datasets?

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.

Title: FAST AND ACCURATE FACE RECOGNITION SYSTEM USING MORSCMS-LBP ON EMBEDDED CIRCUITS Review round: 1 Reviewer: 2

Basic reporting: The English language using is a little poor, and this paper t is very hard to read and understand. The authors may miss the related latest work, such as: Video-based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2021.3067464 Experimental design: None Validity of the findings: The authors may miss the compared results on the Faces 95 and Faces 96 datasets. Additional comments: None