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

Input:
Title: CHANNEL STATE INFORMATION ESTIMATION FOR 5G WIRELESS COMMUNICATION SYSTEMS: RECURRENT NEURAL NETWORKS APPROACH
Review round: 2
Reviewer: 1

Output:
Basic reporting: My previous demand:
"The most crucial lines in the paper are: 188-191 & 223-224. They are telling the contribution proposed by the authors; however, they all can be expanded by adding some flow charts, further explanation, etc."

Author response:
"Authors think that main contributions are declared enough before, through, and after these lines."

Based on my previous review, I had indicated the main contribution explanatory paragraphs and demanded: "however, they all can be expanded by adding some flow charts, further explanation, etc." Visually, it is better to add a "motivation of the study of things." This does not mean "Authors think that main contributions are declared enough before, though, and after these lines." as you have claimed.

--------------------------------------------------

My previous question:
The complexity section does not give critical feedback.

Author response:
This section represents a complementary study for this type of work. The section presents much valuable information, such as training time and the feed-forward pass and feedback pass operations complexity for BiLSTM, and LSTM-based estimators.

You indicate O(w) -> O(2w) when it becomes “Bidirectional”. What does this bring to the reader? One can guess that if the direction of data processing in a network increases, the timing will also; plus, this is not a new finding. The formulation you utilize; I am not familiar with, please see:
- http://cse.iitkgp.ac.in/~psraja/FNNs%20,RNNs%20,LSTM%20and%20BLSTM.pdf
- https://arxiv.org/pdf/2103.08212.pdf

Besides, Table 6 is filled with some ratios? What is ":" operator for?
If you could find a proper citation for your highlight on the complexity, giving a cite is welcomed.

--------------------------------------------------

My previous question:
Line 192-197: Did you decide on this structure based on any preliminary experiments? Or some of the previous efforts (even though you claim to be the first on this structure; maybe you inspired by any LSTM-based communication system.) Why a structure like that? This should be technically explained in this paragraph.

Author response:
Yes, I decided on this structure based on preliminary experiments and some of the previous efforts. Kindly refer to Ref. [12]. Kindly refer to "Revised manuscript" file.

Then, why not clearly include this inspiration in the place where the first time the network architecture is mentioned (If I am not wrong, Ref. 12 is Liao et al. is only occurring in the introduction)
Experimental design: My previous question:
The repeatedly highlighted Adam optimization has no big impact on the overall contribution. What about RMSProp, AdaGrad, etc.?

Author response:
The use of both RMSProp, AdaGrad, and other optimization algorithms such Adadelta, Adagrad, AMSgrad, AdaMax and Nadam is suggested in the future work section. Kindly refer to "Future work".

I do not agree with the authors to save some information for future work; at the end of the day, these issues are not mitigated and the reader still does not know anything about other optimizers. It is better to put a comparison results (if saying repeatedly about Adam’s optimizer), or do not highlight too much of Adam's optimization. Nevertheless, for my overall expectation, as you will see at the end, the comparison result is more expected.
Validity of the findings: My one other previous demand is still not clear:
I did not get the point of using BiLSTM instead of LSTM. Why/How your system requires a bidirectional movement on the timeline?

Author response:
All obtained results demonstrate the superior performance of BiLSTM-based estimators compared with conventional estimators and LSTM-based estimators, so the study recommends using BiLSTM-based estimators, especially at low signal-to-noise ratios.

Still, it seems to me “it has been tried and the results are like”. I am asking more mathematical perspective, what are the signal properties of LSTM & BiLSTM; why a bidirectional movement is required on a communication system as indicated. Are there any other advantages at least to use BiLSTM? Each and every day a new NN algorithm is being proposed; next time one other researcher can try enhanced BiLSTM, etc., but this does not seem to be a contribution; at least in your paper, more than the experimental results, one can infer why and how to construct a communication system based on BiLSTM. (For instance, at least you may include an Appendix (diagram, UML, or flowchart) by showing your code structure; thereby giving the related math becomes visually possible)
Additional comments: For the author response:
“Since the behavior of neural networks relies on different factors such as the network structure, the learning algorithm, loss functions, the activation functions used in each node, etc.,”

I agree for a research paper to include preliminary insights for the NN & Comm. Syst. collaborations; however, as you have given with your previous paper as you have shared, a thorough inspection on all these parameters is required. There are “different factors” as you have said; however, I cannot catch the main summary of all these factors as I had demanded with my sentences starting “For the further efforts of this paper, I strongly suggest”. You have taken it as a future work; however, my main aim is for this current paper.

Therefore, I still believe that a complete summary of the performance related to the indicated factors should be given. I believe this is the only way to increase the contribution of your paper. You may present a summary of all your experiments (by even increasing) showing the effects of all different loss functions, optimizers, learning rate, network size, etc. At least, you may choose one single architecture like BiLSTM 8, and make a table of all NN dynamics.

By the way, thank you very much for the heat map tables, now, I believe that the related results are clearer.


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

Input:
Title: CHANNEL STATE INFORMATION ESTIMATION FOR 5G WIRELESS COMMUNICATION SYSTEMS: RECURRENT NEURAL NETWORKS APPROACH
Review round: 2
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: The manuscript is well written and all the required editions are done.


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

Input:
Title: CHANNEL STATE INFORMATION ESTIMATION FOR 5G WIRELESS COMMUNICATION SYSTEMS: RECURRENT NEURAL NETWORKS APPROACH
Review round: 3
Reviewer: 1

Output:
Basic reporting: All issues related to the previous round have been resolved by the authors.
Experimental design: All issues related to the previous round have been resolved by the authors.
Validity of the findings: All issues related to the previous round have been resolved by the authors.
Additional comments: No additional comments


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

Input:
Title: SSMFN: A FUSED SPATIAL AND SEQUENTIAL DEEP LEARNING MODEL FOR METHYLATION SITE PREDICTION
Review round: 1
Reviewer: 1

Output:
Basic reporting: 1)　Please attention to some word mistakes, such as “swift and effectively” and “performers” in the abstract. Please check the words and grammar of the whole paper again.
2)　The Fig. 3 can be more professional and informative drawn by specialized tools, such as PlotNeuralNet.
Experimental design: Comparative experiments are not sufficient. Please give more results compared with other methods on more datasets.
Validity of the findings: １）I think that fusing CNN and LSTM branch with a weighted operation is more rational. Please give reasons for simple summation.
２）DeepRMethylSite uses one hot encoding, where each amino acid is defined as a 20 length vector, with only one of the 20 bits as 1. And SSMFN uses an embedding layer with 21 neurons to encode different amino acids. What is the difference of those two representations and advantages of SSMFN?
Additional comments: This paper proposes a neural network model which combines CNN and LSTM to extract spatial and sequential information from amino acid sequences, respectively. The writing structure is reasonable, but there are some problems. Please see the detailed comments above.


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

Input:
Title: SSMFN: A FUSED SPATIAL AND SEQUENTIAL DEEP LEARNING MODEL FOR METHYLATION SITE PREDICTION
Review round: 1
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: 1.	We note that your model achieves good results, but the explanation of the structure of the model is not sufficient, and we hope it can be improved.

2.	For Figure2, we would like you to have more visual representations and less textual representations.

3.	You can try to center the content in Table1 to make it look more beautiful.

4.	The literature review of the manuscript need to be improved by comparing similar papers. Thus, the readers can compare the results of various works and the main novelty of this paper can be easily identified.


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

Input:
Title: SSMFN: A FUSED SPATIAL AND SEQUENTIAL DEEP LEARNING MODEL FOR METHYLATION SITE PREDICTION
Review round: 2
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: All my concerns and questions have been addressed, and I recommend the acceptance of the paper。


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

Input:
Title: SSMFN: A FUSED SPATIAL AND SEQUENTIAL DEEP LEARNING MODEL FOR METHYLATION SITE PREDICTION
Review round: 2
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: Authors  provide a manuscript presenting their works about methylation site prediction for proteins. This is a well written manuscript, the authors tried to use deep learning method solve the problem, the proposed deep network architecture seems working well on the prediction, achieved a better accuracy than peer methods. It would be helpful to improve the following researches of the functional and conformational changes of a protein. However, there still have a few suggestions:

1, As we all know, the position-specific scoring matrix (PSSM) is widely used as an effective representation of protein feature for a variety of protein-related problems. The authors should explain why this feature is not used.

2.  The authors have to create a web server or submit all the source codes to github for reproducing the results.

3. The LSTM layer often followed by self-attention mechanism，I think this can help to improve the predictive performance.

4. The draft needs proofread.


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

Input:
Title: DERIVATIVE-FREE OPTIMIZATION ADVERSARIAL ATTACKS FOR GRAPH CONVOLUTIONAL NETWORKS
Review round: 1
Reviewer: 1

Output:
Basic reporting: This research article proposed a black-box adversarial attack framework based on Derivative-Free Optimization (DFO) and a direct attack algorithm (DFDA) using Nevergrad library to classify adversarial attacks on graph nodes. Authors have used Cora, Citeseer and Polblogs data sets for the experimental evaluation. The proposed work achieved an average attack success rate of more than 95%.
Experimental design: The introduction part is well written. The contribution of the proposed work has been highlighted precisely. Authors are suggested to shift the related work after the Introduction part. Related work is well written. Proposed work is well defined using the algorithm. The dataset used for the experimental evaluation is also well explained. All the results obtained are well explained by using various evaluation parameters. Authors are suggested to include future work in the conclusion section.

Authors have used the experimental parameters, namely, target model, node ID, number of target nodes, resource budget, perturbation type, constraint size, scenario, and DFOer. Authors are suggested to give the order of these parameters based on their importance towards classifying adversarial attacks on graph nodes, after the experimental evaluation.
Validity of the findings: This research article proposed a black-box adversarial attack framework based on Derivative-Free Optimization (DFO) and a direct attack algorithm (DFDA) using Nevergrad library to classify adversarial attacks on graph nodes. The paper is well written. The proposed methodology, data set, and results discussed are well written. The paper is suitable to be published in this journal after incorporating minor changes suggested.
Additional comments: No Comments


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

Input:
Title: DERIVATIVE-FREE OPTIMIZATION ADVERSARIAL ATTACKS FOR GRAPH CONVOLUTIONAL NETWORKS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The authors studied adversarial attacks to Graph Convolutional Networks. As a result, the authors proposed a black-box adversarial attack framework based on derivative-free optimization and implemented a direct attack algorithm. The results showed that their proposal outperformed the baseline method Nettack.

The manuscript is literature supported.

This paper is nicely written, well-organized, and easy to read.

- Line 43 > uppercase
- Line 235 > “DeeoRobust” - DeepRobust
- Figure 3, 4, 5 and 6  should be improved. In overall the labels are too small.
Experimental design: Source code, examples and data sources were provided.

Python was used as programming language, which helps to reach a bigger audience.

The authors performed an extensive experimental study comparing both performance and execution time, which is welcome.
Validity of the findings: The authors provided an extended discussion about the results and their proposal won the 91% of  the time by an acceptable margin in Table 12.

The proposal reduced the execution time in almost the half.
Additional comments: No additional comments


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

Input:
Title: DERIVATIVE-FREE OPTIMIZATION ADVERSARIAL ATTACKS FOR GRAPH CONVOLUTIONAL NETWORKS
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors have addressed the comments suggested.
Experimental design: Authors were suggested to include future work. Also authors were suggested to give the order of the parameters based on their importance towards classifying adversarial attacks on graph nodes, after the experimental evaluation.

Authors have included the future work and mentioned about the importance of parameters.
Validity of the findings: The paper may be accepted in the current state.
Additional comments: I congratulate and appreciate the efforts of the authors in preparing the manuscript. I wish them very best for their future research work.


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

Input:
Title: DERIVATIVE-FREE OPTIMIZATION ADVERSARIAL ATTACKS FOR GRAPH CONVOLUTIONAL NETWORKS
Review round: 2
Reviewer: 2

Output:
Basic reporting: The authors have improved the manuscript following the suggestions made by the reviewers.

The manuscript is acceptable in its current form.
Experimental design: -
Validity of the findings: -
Additional comments: No additional comments


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

Input:
Title: A NOVEL FEW-SHOT LEARNING BASED MULTI-MODALITY FUSION MODEL FOR COVID-19 RUMOR DETECTION FROM ONLINE SOCIAL MEDIA
Review round: 1
Reviewer: 1

Output:
Basic reporting: This paper tends to tackle a very important niche in the topic of rumour detection. Although from the methodological perspective, the dataset and the techniques are novel, there are issues regarding the context that need to be clearly addressed:
1- Several places throughout the paper require citation. It is necessary to refer to the manuscripts that support the claimed statements (e.g., line 65,66,71, etc.)
2-     Some of the statements are very strong. For instance, despite what is strongly claimed in line 84-85 as early works, there are plenty of high-quality studies focusing on that approach [3][6]. Such a claim could be agreed upon only if it was supported by a comprehensive literature review or set of references.
3-     There is an assumption in this paper that rumour is either unverified or false (The first line of the introduction). Rumours are unverified in some context, and they are not accompanied by substantial evidence for at least some group of people [1] thus if we know that a message is false, then it should not be called rumour anymore.
4-     The second paragraph of the introduction is not accurate. What is explained as SDQC support classification is in fact the stance detection which along with rumour detection, rumour tracking and veracity detection constitute the rumour resolution system [2].
5-     The second and third paragraphs are semantically disconnected and difficult to follow. The earlier paragraph is about the conceptual phases of the rumour resolution system and the latter one is about the methodological approach (with an emphasis on feature extraction) toward rumour detection.
6-     One of the major missing pieces is the gap analysis and the problem formulation. What is expected here is a thorough review of the rumour detection literature in a way that directs readers toward the gap. Here the literature review is unrelated to the gap. For instance, there are several studies on early rumour detection [3] which I expected to see here because this paper aims to flag upcoming rumours as soon as possible without spending time to collect data on the same rumour and that is exactly what early rumour detection system does. Another topic that is expected to be investigated in the literature review is cross-domain rumour detection [4][5]. One of the other missing approaches is rumour detection using context-independent features. Such features are independent of a particular incident and could be used across different domains [5].
7-     Another shortcoming is the lack of transparency about the data collection process. Questions such as when did you collect the data? how do the readers retrieve the data and get access to the data points? what keywords did you use to build the queries and collect data? are unanswered. Besides, the events (rumours and non-rumours) are expected to be fully described. The current explanation of the events is quite broad and uninformative.
8-     When the dataset is introduced (line 293) the term “instance” is used. Does this term refer to a single message (similar to a tweet on Twitter)? Because not all the readers are Weibo users, it would be helpful to show an example of a post on Weibo visually.
9-     Based on my understanding the equivalent terms for Twitter’s reply and retweet in Weibo are comment and repost. If that is correct, then why did you decide to regard the retweets in the PHEME dataset as comments and not repost (line 310-311)?
10-  How does the annotation by the Sina Weibo community management centre work (line 159)? What kind of labels a post/datapoint may receive?
11- There are some typos and grammatical issues (e.g,. the first column of Table 1)

[1] Nicholas Difonzo and Prashant Bordia. Rumors influence: Toward a dynamic social impact theory of rumor. Frontiers of social psychology. New York, NY, US:
Psychology Press, 2007, pp. 271–295
[2] A. Zubiaga et al. “Detection and Resolution of Rumours in Social Media”. In: ACM Computing Surveys 51.2 (Feb. 2018), pp. 1–36. DOI: 10.1145/3161603
[3] Kwon, S., Cha, M., & Jung, K. (2017). Rumor detection over varying time windows. PloS one, 12(1), e0168344.
[4] Sicilia, R., Merone, M., Valenti, R., Cordelli, E., D’Antoni, F., De Ruvo, V., ... & Soda, P. (2018, December). Cross-topic rumour detection in the health domain. In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2056-2063). IEEE.
[5] Fard, A. E., Mohammadi, M., & van de Walle, B. (2020, June). Detecting Rumours in Disasters: An Imbalanced Learning Approach. In International Conference on Computational Science (pp. 639-652). Springer, Cham.
[6] Sicilia, R., Giudice, S. L., Pei, Y., Pechenizkiy, M., & Soda, P. (2018). Twitter rumour detection in the health domain. Expert Systems with Applications, 110, 33-40.
Experimental design: The proposed method is novel and the experiments are well explained; however, there are two issues regarding the robustness of this study:
1-     Based on the experimentation setting (line 311-313), you used 3-fold cross-validation. How come you chose three splits here? Why not 5 or 10? You need to justify your decision.
2-     For the PHEME dataset, You decided to use #Ferguson unrest, #Ottawa shooting, #Sydney siege as the training and validation set and #Charlie Hebdo shooting, #Germanwings plane crash for the testing (line 303-307). Like the previous point, this decision is not justified as well. One quick fix for both is to do sensitivity analysis by running new experiments. For the k-fold cross-validation issue, this means to run the new experiments when k=3,5, 10 and show to what degree the results change by increasing the number of splits. For the second issue, it means to use different datasets for training-validation and test and show how much the results are dependent on the choice of train-validation-test sets.
Additionally and as I explained before, a coherent chain of related work, research gap, and research questions are absent in this paper. Hence although the experiments and few-shot learning based approach toward rumour detection is very well explained, they are not based on a crystal clear motivation (which comes from an in-depth literature review and subsequent gap identification)
Validity of the findings: The methodological aspect of this study is quite novel and tends to address a very important challenge in automatic rumour detection systems.
Additional comments: No additional comments


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

Input:
Title: A NOVEL FEW-SHOT LEARNING BASED MULTI-MODALITY FUSION MODEL FOR COVID-19 RUMOR DETECTION FROM ONLINE SOCIAL MEDIA
Review round: 1
Reviewer: 2

Output:
Basic reporting: See General Comments for the Author.
Experimental design: See General Comments for the Author.
Validity of the findings: See General Comments for the Author.
Additional comments: The spread of rumors will cause the panic of the public and place considerable losses on the economy and other aspects of society. To solve the rumor detection problem on social media, the authors proposed a few-shot learning-based multi-modality fusion model named COMFUSE, including text embeddings modules with pre-trained BERT model, feature extraction module with multilayer Bi-GRUs, multi-modality feature fusion module with a fusion layer, and meta-learning based few-shot learning paradigm for rumor detection. Although the writing is unambiguous, this paper lacks sufficient experiments to verify its contribution. Some concerns are listed as follows:

1.	The authors should illustrate the innovation of the proposed model. The modules used in this paper are all based on existing models such as BERT, Bi-GRUs, without any innovative technologies proposed in this paper.

2.	The latest baseline for comparison in this paper was proposed in 2018, the authors need to compare the proposed method with more recent baselines.

3.	In many related works, such as Bian et al. 2020, Ma et al. 2019, and Liu et al. 2019 cited in the paper, have a rumor early detection experiment. They use very few tweets posted before the early detection deadline as the training set, the models proposed in these papers are tested on the test set, and good detection effects are also obtained. I think the method proposed in this paper should compare with these methods.

4.	This paper uses a pre-training model to improve the accuracy of rumor detection. I wonder if this BERT model can be applied to other methods based on textual content of tweets, and can these methods also be significantly improved, even more than the Bi-GRUs based model proposed in this paper?

5.	The author should use experimental results to show that rumor detection results are insensitive to different pad sizes of posts and comments.

6.	Do not use the same notation for different definitions in the paper, such as b and T.

7.	In Table 1, why are MH370, College entrance exams, …, Rabies COVID-19 relevant, and Zhong Nanshan, Wuhan are irrelevant?

In short, the writing is clear but the model lacks innovation. And this paper lacks sufficient experiments to verify its contribution. I suggest that the paper should be greatly modified to make it more acceptable.


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

Input:
Title: A NOVEL FEW-SHOT LEARNING BASED MULTI-MODALITY FUSION MODEL FOR COVID-19 RUMOR DETECTION FROM ONLINE SOCIAL MEDIA
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors took good care of my comments in the first round of review about literature review and restructuring the paper and I have no further comments and questions.
Experimental design: I don't have any other comments for this section.
Validity of the findings: I don't have any other comments for this section.
Additional comments: No additional comments


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

Input:
Title: A NOVEL FEW-SHOT LEARNING BASED MULTI-MODALITY FUSION MODEL FOR COVID-19 RUMOR DETECTION FROM ONLINE SOCIAL MEDIA
Review round: 2
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: The authors have revised the manuscript as suggested. I have no further comments and recommend accepting this paper.


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

Input:
Title: EFFICIENT PROCESSING OF COMPLEX XSD USING HIVE AND SPARK
Review round: 1
Reviewer: 1

Output:
Basic reporting: The authors have a good structure for the paper,  however, there are grammatical errors and sentence construction errors in multiple places. I have described a few examples below

"However, a more common approach in that works involves the simplest examples of XML documents, even though, the real data sets are composed of complex schemas that include nested arrays and structures."
"The reporting tool used is Spark SQL but no details about the implementation are presented."
"With the purpose of reducing the lack of methods for processing XML files with complex schemas, in this study we present our approach based on three main methods: (1) catalog, (2) deserialization, and (3) positional explode."

 I would recommend them to correct these
Experimental design: The problem statement that the authors are trying to solve is not clearly stated.
Are they trying to compare big data frameworks on fast they can process complex XSD or are they trying to prove that their approach based on cataloging, deserialization and positional explode is superior to other approaches in the related work?
if they are trying to do the former, they need to consider several performance characteristics. Big data frameworks usually run on clusters, not on a single nodes.
Apache spark version used (1.6.0) is outdated and retired, I would recommend the authors to use Apache Spark 3.0 since its performance is almost that in 1.6.0
The same goes for Apache Hive. For end customers, the reason to do internal tables and external tables are very different, however, that choice does affect performance. The authors have not disclosed whether while using internal tables, their results are affected by caching in Hive.
Validity of the findings: While the authors prove that their approach of catalog, deserialization and positional explode works in Big Data Frameworks, they have not compared that with other approaches for XML parsing that the related works have described

The authors have not explored why Hive or Spark performs better. When they mention Hive performs better for queries to extract individual values or attributes, what is the reason behind this? They need to explore the open-source code to understand what is the root cause. This would improve the validity of their findings.
Additional comments: Please compare with the latest version of the big data frameworks since they are more up-to date and the scan processing time is shorter there.
Please explore deeper into the frameworks to find the reasons for your findings
Also explore big data cluster results


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

Input:
Title: EFFICIENT PROCESSING OF COMPLEX XSD USING HIVE AND SPARK
Review round: 1
Reviewer: 2

Output:
Basic reporting: I appreciate authors for their research contribution. The paper is well-organized and contributes to novel research work which falls in Computer Science Research domain of the journal.

1. Few sentences which need to be re framed/reexamined as some how these sentences meaning is not clear. Line numbers are mentioned below:
46-48
193-194
273-274
280-281
307-308

2. I found some of the fundamental papers related to work done. Authors can check and include these in related work or wherever it seems suitable:

Dmitry Vasilenko, “An Empirical Study on XML Schema Idiosyncrasies in Big Data Processing”, in International Journal on Computer Science and Engineering, October 2015.
Dmitry Vasilenko, Mahesh Kurapati,.” Efficient Processing of XML Documents in Hadoop Map Reduce, IJCSE, 2014, Vol.6, No.9,p.329–333.
Song Kunfang and Hongwei Lu, “Efficient Querying Distributed Big-XML Data using MapReduce”, Int. J. Grid High Perform. Comput. 8, 3 (July 2016), 70–79. DOI:https://doi.org/10.4018/IJGHPC.2016070105
Experimental design: 1.  At line number 444-445- I request if you can elaborate or reference why it is needed to create the raw table at first?

2. Please discuss which type of queries have been selected to evaluate the proposed algorithm. Also, mention whether the same type of queries can be applicable for other application datasets?
Validity of the findings: No Comment
Additional comments: 1. The paper is devoted to important task of Big Data. The authors have presented query processing algorithms for complex XML files. The practical value of article is good.

2. The proposed algorithms can be further tested on different size big datasets to validate them for implementation on real big datasets.

3. For further research, authors can take benchmark datasets and queries.

All the best.


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

Input:
Title: EFFICIENT PROCESSING OF COMPLEX XSD USING HIVE AND SPARK
Review round: 2
Reviewer: 1

Output:
Basic reporting: I appreciate authors for working on all observations. The proof reading of document further ensure clear and unambiguous  English. Hence, the re submission is acceptable for publishing purpose.
Experimental design: Since, authors have answered all observations in detail, I am satisfied with the improved version of document. No more questions from my side.
Validity of the findings: All findings are validated properly. No further queries.
Additional comments: All previously given observations are considered and corrected in re-submission by authors. .All the best for future endeavors.


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 1
Reviewer: 1

Output:
Basic reporting: The paper introduces an adaptive block encryption scheme. This system is based on product, exponent and modulo operation on a finite field. At the heart of this algorithm lies an innovative and robust trapdoor function that operates in the Galois Field and is responsible for the superior speed and security offered by it. Prime number theorem plays a fundamental role in this system, to keep unwelcome adversaries at bay. This is a self-adjusting cryptosystem that autonomously optimizes the system parameters thereby reducing effort on the user's side while enhancing the level of security. This paper provides an extensive analysis on a few notable attributes of this cryptosystem such as it's exponential rise in security with an increase in the length of plaintext while simultaneously ensuring that the operations are carried out in feasible runtime. Additionally, an experimental analysis is also performed to to study the trends and relations between the different parameters of the cryptosystem including a few edge cases.
Experimental design: no comment
Validity of the findings: no comment
Additional comments: 1. Please improve overall readability of the paper.
2. The objectives of this paper need to be polished.
3. Introduction is poorly written.
4. Relevant literature review of latest similar research studies on the topic at hand must be
discussed.
5. Result section need to be polished.
6. There are some grammar and typo errors.
7. Improve the quality of figures
8. Define all the variables before using
The authors can cite the following
1.A Novel PCA-Firefly based XGBoost classification model for Intrusion Detection in Networks using GPU
2. Fake Review Classification Using Supervised Machine Learning


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 1
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: In this paper, the authors designed a novel symmetric encryption method based on finite field. Although the proposed protocol has no obvious mistakes and question, some revisions are still needed for this paper. The authors may refer to the following comments for revision.

1.  Related work part cannot be found in this paper.

2. No comparative experiments conducted, the authors should compare their proposed protocol with other similiar encryption protocol in terms of computation cost and other metrics.

3. Some typos and grammar errors exist in this paper, the authors should double check the paper.

4. More supplementary references should be used in the manuscript. For authors' convenience, we list the related references as follows.
1. Song J, Zhong Q, Wang W, et al. FPDP: Flexible privacy-preserving data publishing scheme for smart agriculture. IEEE Sensors Journal, 2020, doi: 10.1109/JSEN.2020.3017695.
2. Wang W, Su C. Ccbrsn: a system with high embedding capacity for covert communication in bitcoin//IFIP International Conference on ICT Systems Security and Privacy Protection. Springer, Cham, 2020: 324-337.
3. Wang W, Huang H, Zhang L, et al. Secure and efficient mutual authentication protocol for smart grid under blockchain. Peer-to-Peer Networking and Applications, 2020: 1-13.
4. Zhang L, Zou Y, Wang W, et al. Resource Allocation and Trust Computing for Blockchain-Enabled Edge Computing System. Computers \& Security, 2021: 102249.
5. Zhang L, Zhang Z, Wang W, et al. Research on a Covert Communication Model Realized by Using Smart Contracts in Blockchain Environment. IEEE Systems Journal, doi: 10.1109/JSYST.2021.3057333.


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 1
Reviewer: 3

Output:
Basic reporting: Professional English is required to improve the paper before publication.

Literature review is not sufficient. Latest and related paper like enhancement of the Cryptosystem should be compared with https://ieeexplore.ieee.org/abstract/document/6294370
How Big data and cryptography should be analysed with https://www.mdpi.com/2079-9292/8/11/1331
You can apply optimization approach
https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2797

Figures need improvement
Equations are not numbered
More clarity in results needed
Experimental design: Research questions need to be refined
Methods okay in mathematical analysis
Validity of the findings: Findings are okay
Conclusion can be improved
Additional comments: Professional English is required to improve the paper before publication.

Literature review is not sufficient. Latest and related paper like enhancement of the Cryptosystem should be compared with https://ieeexplore.ieee.org/abstract/document/6294370
How Big data and cryptography should be analysed with https://www.mdpi.com/2079-9292/8/11/1331

Figures need improvement
Equations are not numbered
More clarity in results needed
Research questions need to be refined
Methods okay in mathematical analysis


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 2
Reviewer: 1

Output:
Basic reporting: paper introduces an adaptive block encryption scheme. This system is
based on product, exponent, and modulo operation on a finite field. At the heart of this algorithm lies
an innovative and robust trapdoor function that operates in the Galois Field and is responsible for the
superior speed and security offered by it. Prime number theorem plays a fundamental role in this system,
to keep unwelcome adversaries at bay. This is a self-adjusting cryptosystem that autonomously optimizes
the system parameters thereby reducing effort on the user’s side while enhancing the level of security.
This paper provides an extensive analysis of a few notable attributes of this cryptosystem such as its
exponential rise in security with an increase in the length of plaintext while simultaneously ensuring that
the operations are carried out in feasible runtime. Additionally, an experimental analysis is also performed
to study the trends and relations between the cryptosystem parameters, including a few edge cases
Experimental design: .
Validity of the findings: .
Additional comments: •	In Introduction section, the drawbacks of each conventional technique should be described clearly.
•	Introduction needs to explain the main contributions of the work more clearly.
•	The authors should emphasize the difference between other methods to clarify the position of this work further.
•	The Wide ranges of applications need to be addressed in Introductions
•	The objective of the research should be clearly defined in the last paragraph of the introduction section.
•	Add the advantages of the proposed system in one quoted line for justifying the proposed approach in the Introduction section.

In preprocessing the authors can refer the following
A Novel PCA-Firefly based XGBoost classification model for Intrusion Detection in Networks using GPU
An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 2
Reviewer: 2

Output:
Basic reporting: The authors have well addressed my comments, so it is ready for publication now
Experimental design: The authors have well addressed my comments, so it is ready for publication now
Validity of the findings: The authors have well addressed my comments, so it is ready for publication now
Additional comments: The authors have well addressed my comments, so it is ready for publication now


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 2
Reviewer: 3

Output:
Basic reporting: The Paper is improved but lack recent References

Contribution is still lacking at the end of Introduction

Figures still not clear enough. Some further improvement needed
Experimental design: improved
Validity of the findings: Improved
Additional comments: The Paper is improved but lack recent References
Add
https://www.mdpi.com/1424-8220/20/9/2609

Contribution is still lacking at the end of Introduction

Figures still not clear enough. Some further improvement needed


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 3
Reviewer: 1

Output:
Basic reporting: The authors have addressed all of my comments, paper can be accepted in the current form. Thank you for giving me this opportunity.
Experimental design: Good
Validity of the findings: Good
Additional comments: The authors have addressed all of my comments, paper can be accepted in the current form. Thank you for giving me this opportunity.


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 3
Reviewer: 2

Output:
Basic reporting: The authors have addressed all the comments. The paper can be accepted for publication.
Experimental design: The authors have addressed all the comments. The paper can be accepted for publication.
Validity of the findings: The authors have addressed all the comments. The paper can be accepted for publication.
Additional comments: The authors have addressed all the comments. The paper can be accepted for publication.


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

Input:
Title: AN ADAPTIVE CRYPTOSYSTEM ON A FINITE FIELD
Review round: 3
Reviewer: 3

Output:
Basic reporting: The work has been improved, but in view of the Case study penetration testing models evaluation: how many case studies and how many testers are required?
Experimental design: The work has been improved, but in view of the Case study penetration testing models evaluation: how many case studies and how many testers are required?
Validity of the findings: Improved
Additional comments: The work has been improved, but in view of the Case study penetration testing models evaluation: how many case studies and how many testers are required?


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

Input:
Title: EMERGING IOT DOMAINS, CURRENT STANDINGS AND OPEN RESEARCH CHALLENGES: A REVIEW
Review round: 1
Reviewer: 1

Output:
Basic reporting: The quality of the presentation significantly weakens this manuscript. The number of references is enough, while the importance of the proposed IoT domains and the current solutions to the proposed challenges are missing.
Experimental design: The authors summarize the research status and challenges in several IoT domains, IoNT, IoST, IoUT, and SIoT. Actually, there are many survey papers on IoT research, but few on these domains.
Validity of the findings: Actually, the topic of this paper is interesting and would attract more attention from the community. However, I am concerned that do these IoT domains really matter? The importance of these IoT domains discussed in this manuscript should be highlighted. The paper lacks a more thorough discussion of what decisive role the mentioned IoT domains will play in the future and what are the crucial effects that they will achieve.
Additional comments: The authors summarize the research status and challenges in several IoT domains, IoNT, IoST, IoUT, and SIoT. Actually, there are many survey papers on IoT research, but few on these domains. The topic of this paper is interesting and would attract more attention from the community. However, I have some comments as follows.
(1) Do these IoT domains really matter? The importance of these IoT domains discussed in this manuscript should be highlighted. The paper lacks a more thorough discussion of what decisive role the mentioned IoT domains will play in the future and what are the crucial effects that they will achieve.
(2) This manuscript should be improved by including more recent papers and high cited journals regarding the solutions of relevant challenges proposed in this manuscript such as:
(2019) Smart Contract-Based Access Control for the Internet of Things. IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1594-1605.
(2019) A Hierarchical Sharding Protocol for Multi-Domain IoT Blockchains. ICC 2019, pp. 1-6.
(2021) Attribute-Based Access Control for Smart Cities: A Smart-Contract-Driven Framework. IEEE Internet of Things Journal, vol. 8, no. 8, pp. 6372-6384.
(3) I think the writing style/clarity needs more effort before it is published. Indeed, I found the paper extremely difficult to read, due not only to the poor grammar used throughout but also the unclear structure of the argument being put across. The authors are suggested to check through the paper and correct typo and grammatical errors carefully.


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

Input:
Title: EMERGING IOT DOMAINS, CURRENT STANDINGS AND OPEN RESEARCH CHALLENGES: A REVIEW
Review round: 1
Reviewer: 2

Output:
Basic reporting: Grammar can be improved in lines 14, 15, 16 and 17.

Excerpt: "Current 5G and Edge computing advancements, set to open a new frontier for cutting-edge connectivity on IoT platforms. In recent years, a broad spectrum of communication systems, covering a variety of domains has evolved. Such a heterogenous technology integration inhibits adoption and standardization challenges."

Similarly, line 28-29 may be reworded.

It is recommended that entire article should be reviewed with the help of a technical writer to ironing out such issues.
Experimental design: Comment 1:
While the article has focussed on only on emerging domains, if a concise viewpoint is added for "established" domains, it will add value to the article. With 5G, many of the established domains will also undergo a cycle of innovation in the areas of communication and integration.

Comment 2:
In the abstract in line 22-24, I get that the paper is directed towards providing a single and sufficient source of information to the concerned researchers on various aspects of emerging IoT ecosystems. But in line 141, the article states that it addresses only the "architecture, communications, and integration aspects". I think it would be helpful if this scope is included in the abstract as well.

Comment 3:
Line 587, 588 states that "However, security, privacy, and trustworthiness are the most significant and most challenging factors that will slow down this domain’s growth and systems in general."

While the article has given due coverage to security and trustworthiness topics, it seems light on the "Privacy". Could you please add a new section addressing it, or maybe address it within the existing sections.
Validity of the findings: In the conclusion section, it will be helpful to add a future direction or future work.
Additional comments: I thank the authors for collating data from a wide set of sources on the emerging technology and presenting it in an structured manner. Please find below few comments that will help it improve it and make it useful to the readers.


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

Input:
Title: EMERGING IOT DOMAINS, CURRENT STANDINGS AND OPEN RESEARCH CHALLENGES: A REVIEW
Review round: 1
Reviewer: 3

Output:
Basic reporting: Overall it is a well-written article - covering an important aspect of the emerging IoT system. The author's aim is to provide a single and sufficient source of information to the concerned researchers on various aspects of emerging IoT ecosystems. All sections are well covered except Open Challenges in SIoT Domain. I believe, security and data privacy is one of the major issues in the wide spread deployment of IoT in different domains. Given the importance of security and data privacy, I feel this section is way too brief. Not only it is brief, but many recent important articles are not cited in this section. Some of these papers are: 1) Securing the internet of things (IoT): A security taxonomy for IoT 2) Identifying the attack surface for IoT network, 3)Threat model for securing internet of things (IoT) network at device-level.
Experimental design: Overall, a well-designed research methodology was adopted by the authors. No changes are required.
Validity of the findings: The results/conclusions drawn based on the provided data/facts are reasonable.
Additional comments: Overall, a good read - covering many different aspects of IoT. Please extend **Open Challenges in SIoT Domain** section by including a discussion on some of the recently published papers.


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

Input:
Title: EMERGING IOT DOMAINS, CURRENT STANDINGS AND OPEN RESEARCH CHALLENGES: A REVIEW
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors summarize the research status and challenges in several IoT domains, IoNT, IoST, IoUT, and SIoT.
Experimental design: This paper meets the topics of this journal.
Validity of the findings: The topic of this paper is interesting and would attract more attention from the community.
Additional comments: The author has done a good job of revising the paper.


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

Input:
Title: SERVICE HUMANOID ROBOTICS: A NOVEL INTERACTIVE SYSTEM BASED ON BIONIC-COMPANIONSHIP FRAMEWORK
Review round: 1
Reviewer: 1

Output:
Basic reporting: The paper proposed a novel interactive system based on the bionic-companionship framework. On the basis of ensuring the dynamic environment sensitivity of the interactive system in the humanoid service robot, the neural image capture technology in deep learning is adopted to improve the experience experiment of human-computer interaction. The results show that the proposed method improves the system performance to a certain extent.  The writing structure is reasonable, clearly organized, the diagrams and formulas are standardized. Some minor problems of this manuscript should be revised.
1.	More newest references should be cited.
2.	The English writing should be polished
Experimental design: The experimental design is resonalbe, and the results and analysis are convicing.
Validity of the findings: The proposed method is  innovative.Conclusions are well stated.
Additional comments: The paper proposeD a novel interactive system based on the bionic-companionship framework. On the basis of ensuring the dynamic environment sensitivity of the interactive system in the humanoid service robot, the neural image capture technology in deep learning is adopted to improve the experience experiment of human-computer interaction. The results show that the proposed method improves the system performance to a certain extent. The thesis is somewhat innovative. The writing structure is reasonable, clearly organized, the diagrams and formulas are standardized, and the experimental results and analysis are sufficient. Some minor problems of this manuscript should be revised.
1.	More newest references should be cited.
2.	The English writing should be polished


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

Input:
Title: SERVICE HUMANOID ROBOTICS: A NOVEL INTERACTIVE SYSTEM BASED ON BIONIC-COMPANIONSHIP FRAMEWORK
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper is well presented with a clear structure. The literature references are sufficient in the field. The raw data and source codes have been shared.
Experimental design: The research question is well defined. The study aims to improve the current HRI interaction of the HSRs by integrating a deep learning-based NIC model into the system. The general system framework has presented clearly in the method section. However, as the crucial component (model) in the system, more details related to the NIC are desirable. E.g. the training protocol used in the experiments, the way to combine the visual cues of CNN and textual cues in the LSMT for image captioning.
Validity of the findings: The authors provided some qualitative analysis and preliminary tests in the paper to validate the initial performance of the proposed HRI framework. However, those testing cases should have been well defined as a part of experiments. E.g. it would be better that the cases/scenarios could be explicitly designed within a controlled environment, e.g. covering different scenes, human/object, indoor/outdoor environment, etc. Moreover, the validation should include some quantitative analysis in the study.
Additional comments: This paper presented a general bionic-companionship framework for HSRs to enhance HRI, where a classic NIC model was introduced into the system with other models (e.g. motion, language/voice, emotion). The paper is easy to read with a clear structure and written. Specific suggestions related to the method and analysis are as follows:
•	As the NIC model is the critical component in the proposed framework, more details related to the NIC should be described, e.g. Optimizer, training protocol, fusion strategy etc.
•	Although the authors have presented some preliminary tests in this study, the design of testing cases needs to be described and justified. Meanwhile, both quantitative and qualitative analyses are desirable to validate the framework. The NIC model could be validated separately before deploying to the entire system.
•	The abbreviation NRC presents in line 65 should be clarified, Human-Robot Collaboration (HRC)?


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

Input:
Title: SERVICE HUMANOID ROBOTICS: A NOVEL INTERACTIVE SYSTEM BASED ON BIONIC-COMPANIONSHIP FRAMEWORK
Review round: 1
Reviewer: 3

Output:
Basic reporting: This paper touches upon a very attractive and promising area of human-robot-interaction which could be a potent, cross-disciplinary research domain in future robotics. In its current form, the paper need to be significantly improved. I would suggest the authors to take my comments into consideration, and address my concerns.

Basically, the presentation of this paper is partially ambiguous on its originality and significance, which I will point out later in details.

The literature covers well the main focus of this paper. However, it is insufficient to be inclusive for readers/researchers from wider communities. Besides that, the authors need to double-check the format of references.

Generally speaking, this paper is well organised and written. However, the figures presentation is absolutely the shortcoming of this research paper. The authors should make great efforts for such improvement.

The differences between this paper and a recent conference paper (with a very similar topic) by the authors upon any further investigation, or perspectives, or new methods, contributions...should be more obviously highlighted in the Abstract and Introduction.

The validation of the proposed results is reasonable as to my understanding. Some details are yet missing to articulate the main results.
Experimental design: As to me, the experimental design should comprise more cases to verify the interactive system. I can only pick up one effective testing result which is casually presented. In other words, I feel the experiment is incomplete. I would like to see any further, interesting result from the robot actions when interacting within the stated "social dynamic environment".

The method has been simply, clearly formulated which looks reasonable and correct to me.
Validity of the findings: The main contribution should be more highlighted. In the present presentation, I read several times at some sections that I still find some difficulty to grab quickly the novelty and contribution of this paper. The authors should improve it to be easy to follow.
Additional comments: General comments:
1. Basic Perspective
This paper touches upon a very attractive and promising area of human-robot-interaction which could be a potent, cross-disciplinary research domain in future robotics. In its current form, the paper need to be significantly improved. I would suggest the authors to take my comments into consideration, and address my concerns.

Basically, the presentation of this paper is partially ambiguous on its originality and significance, which I will point out later in details.

The literature covers well the main focus of this paper. However, it is insufficient to be inclusive for readers/researchers from wider communities. Besides that, the authors need to double-check the format of references.

Generally speaking, this paper is well organised and written. However, the figures presentation is absolutely the shortcoming of this research paper. The authors should make great efforts for such improvement.

The differences between this paper and a recent conference paper (with a very similar topic) by the authors upon any further investigation, or perspectives, or new methods, contributions...should be more obviously highlighted in the Abstract and Introduction.

The validation of the proposed results is reasonable as to my understanding. Some details are yet missing to articulate the main results.

2. Experiment and Method
As to me, the experimental design should comprise more cases to verify the interactive system. I can only pick up one effective testing result which is casually presented. In other words, I feel the experiment is incomplete. I would like to see any further, interesting result from the robot actions when interacting within the stated "social dynamic environment".

The method has been simply, clearly formulated which looks reasonable and correct to me.

3. Contribution
The main contribution should be more highlighted. In the present presentation, I read several times at some sections that I still find some difficulty to grab quickly the novelty and contribution of this paper. The authors should improve it to be easy to follow. Listing crucial points one by one is an usual way to summarise the significance and improve the readability.

Detailed comments:
This paper proposes an attractive idea on designing an interactive system in service humanoid robots by introducing the widely applied  neural image capturing in deep learning. The robot, in this case, could respond effectively to dynamic social environment.

I have the following concerns and comments in details:

Major concerns:

1. A major concern is about the statement of  "bionic-companionship". As to me, deep learning or called deep neural learning is not a fully bionic pathway to Artificial Intelligence. Here the term "bionic" may mislead authors. To my understanding, bionics, more or less, should draw some inspirations from biological systems for some embodiments in engineering systems and technology. I did not see very clear evidence for this point. How would your service robot behave, or interact with humans resembling a biological entity?

2. Figure presentation needs to be SIGNIFICANTLY changed and improved. Even when I zoom in, I cannot see clearly the embedded information (Fig. 5). Could you also replace Fig. 3 with a more structural model illustration on NIC ? Fig. 1 could be separated into two sub-figures.

3. Related work is insufficient. Considering convincing readers from wider communities, it is better to see some additional points:
(1) Research milestones in HSRs
(2) Differences (including SoTA systems, and challenges) between the research focusing on industrial robotics and HSRs which have been stressed in the Abstract
(3) Emergence of challenges and methods when bridging HRI to HSR

4. Experiments - It is good to see the interesting, preliminary testing results in Fig. 6. However, how does this result reflect your statement of dealing with social dynamic environment?

5. Clarifying the significance - I found some repetitions with the authors' recent conference paper. What is the main extension of this journal paper? Either deeper/more systematic investigation or new proposed method?

Small recommendations:

1. Abstract:
(1) "The problem and quality of human-robot interaction (HRI) has become a widely debated topic in academia." - Could you extend it a bit more to say what exactly the major problem is?
(2) Could you emphasise more the main contribution DIFFERENTLY to previous works?
(3) "changes in the interactive environment" - ambiguous, what kinds of changes?

2. Introduction:
(1) "high-risk service and interactive tasks" - for some examples?
(2) Maybe I missed some info, what is the "HRC" herein short for?
(3) How do the authors define the "social dynamic environment", empirically? or with any standard? This is important as to be addressed by the proposed system.
(4) I would like to see the organization of the rest of this paper at the end of Introduction.

3. I would like the authors to elaborate on the methods with more details.


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

Input:
Title: SERVICE HUMANOID ROBOTICS: A NOVEL INTERACTIVE SYSTEM BASED ON BIONIC-COMPANIONSHIP FRAMEWORK
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors have significantly improved the manuscript according to the reviewer's comments. I'm happy with the authors' responses to my comments, including clarification of the NIC model as well as its evaluation with more testing cases and scenarios.
Experimental design: The research question is well defined. The experimental design is justified with concise implementation. More descriptions are added in the revision for clarification.
Validity of the findings: The method evaluation section has been improved significantly, more testings of method robustness are added, and both quantitative and qualitative analyses are presented. The conclusion can be drawn from the reported results.
Additional comments: There are many improvements based on the reviewers' comments in this version. I'm happy with the authors' responses and corresponding revisions to my comments.


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

Input:
Title: SERVICE HUMANOID ROBOTICS: A NOVEL INTERACTIVE SYSTEM BASED ON BIONIC-COMPANIONSHIP FRAMEWORK
Review round: 2
Reviewer: 2

Output:
Basic reporting: The authors have carefully revised the manuscript regarding my suggestions. My major concerns on Figure representations have been also well addressed. The quality in its current form is acceptable.
Experimental design: The experiments are clear to show the advantages. I found the supplementary video is very helpful to understand the main work.
Validity of the findings: This work is technically sound.
Additional comments: I would appreciate the consideration of my recommendations for improving this paper in its previous form. The authors have made great efforts on revising this paper into details. My major concerns on the figure representations have been addressed. The major and minor points have been considered, enhanced and clarified. I found the supplementary video very helpful for the understanding of main work. I do NOT have further points for another round of revision. Therefore, I would fully support the publication of this research paper.


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

Input:
Title: COMPARISON OF MACHINE LEARNING TECHNIQUES TO HANDLE IMBALANCED COVID-19 CBC DATASETS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The authors follow all the suggested guidances: clear and unambiguous, professional English used throughout; literature references, sufficient field background/context provided; professional article structure, figures, tables; raw data shared; self-contained with relevant results to hypotheses; and formal results should include clear definitions of all terms and theorems, and detailed proofs.
Experimental design: The authors also follow the guidance of this area: original primary research within Aims and Scope of the journal; Research question well defined, relevant & meaningful; rigorous investigation performed to a high technical & ethical standard; and methods described with sufficient detail & information to replicate.
Validity of the findings: The authors again follow the guidelines: all underlying data have been provided; and the conclusions are well stated, linked to original research question & limited to supporting results.
Additional comments: This is a study of a public database of covid-19 in Brazil with the objective of comparing various techniques of data rebalancing. This is a strategy routinely carried out in most health studies, since the imbalance between classes is frequent in this area. The article does not bring new insights to the area, but it is technically correct and provides a good tutorial on recent practical applications of machine learning algorithms.

The major problem is the quality of the database provided. Although the data comes from renowned health institutions in Brazil, there have been several reports of inconsistencies in this database, which is the reason why many ML groups have avoided using them. For example, the positive class for covid-19 is not expected to be 40 times more prevalent than the negative (as in the case of HSL), even if only symptomatic cases are tested.

The authors address this issue by analyzing the bivariate distribution of variables according to the two classes. I believe that in this case it would be more appropriate to use statistical analysis to compare whether the variables have similar distributions for the three centers, regardless of the outcome.

Another important issue is that the authors present the results of several predictive metrics, but not the one most used in machine learning models (AUROC). I believe this metric should be used as the main result of the analysis.


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

Input:
Title: COMPARISON OF MACHINE LEARNING TECHNIQUES TO HANDLE IMBALANCED COVID-19 CBC DATASETS
Review round: 1
Reviewer: 2

Output:
Basic reporting: I strongly suggest a review in English for the article. Some adjustments are necessary to avoid long and redundant sentences. These adjustments will make the article more straightforward and easier to read.

The database used has information on a large number of patient samples from a highly mixed population. The authors can discuss more deeply the influence of this kind of variability in obtaining predictive models. Likewise, they can describe the strengths and weaknesses of this variability in obtaining predictive models with good performance.

The manuscript is not in exactly the same format suggested by the Journal. There is no discussion session. The discussion took place in the results session.
Experimental design: Thinking about different reference values between men and women, as well, the age impact on the CBC values, did you evaluate the impact of adding sex information as a feature?

In addition to eliminating samples that did not have all CBC records, and using the complete blood count of the PCR date, was any other manipulation of the data done by the authors? It was not clear in the text whether the authors did extra preprocessing of the datasets.

In line 137 the authors described the features and scale. Were the scales the same among the 3 datasets? Did the authors perform any scale process in these datasets?

The time period during which these data sets were collected isn't mentioned, were the records collected over which period of time?

How the authors defined the positive diagnosis for SARS Cov 2 is not described in the manuscript. Was the COVID-19 class defined using RT-PCR result?

Is the y column in the datasets the SARS Cov 2 classification? The authors can describe the class definition with more details.
Validity of the findings: The authors did not present any statistical test showing whether there is or not  a significant difference between the assessments obtained with each method and/or algorithm. I recommend the addiction of the statistical test results. This information will help to better guide the discussion.  Furthermore, in this way the evaluation does not appear to be only qualitative or even arbitrary.

Starting in line 214 the authors discuss the possible influence of seasonal fluctuations and, sometimes, extreme circadian regulations in the datasets variability. However, the datasets were obtained from a population from the same country. Therefore, it would be interesting  to make clear the characteristics of this population. Subsequently, describe the possible influence of seasonal fluctuations and extreme circadian regulations, mainly on datasets obtained from different populations.

Line 548:“Both issues could be tackled in the future using feature selection
Line 549: (3; 48) or algorithms for explainable artificial intelligence (100; 76; 5).” The authors discuss the need for feature selection mainly for the interpretability of models obtained with Multi-Layer Perceptron (MLP). However, at no time do they discuss the possibility of applying feature selection methods to improve the predictive performance of the model. Or even to simplify the model, and consequently reduce the use of computational resources.
Additional comments: Main comment:
The study is interesting, mainly, due to the need for more accessible alternatives for prioritizing patients to perform the RT-PCR test. The CBC is an interesting biological information base. In addition, the database used has information on a large number of patient samples from a highly mixed population. What makes the datasets valuable.  However, the authors found many differences between the classification results obtained with the 3 datasets. In this way, they could have explored the possibility of obtaining predictive models from the integration of the 3 datasets. I understand the limitation and the difficulty of this approach, especially when dealing with such diverse distributions, but it could be a good complement to the work. Show the impact of generalization and the increase in the number of samples on the performance of predictive models. In order to assist other researchers in decision making. They can decide to use only a single dataset obtained from the same institution, or to use more datasets to define their predictive covid-19 models.

Comments:
The time period during which these data sets were collected isn't mentioned, were the records collected over which period of time?

In the line 65 and 66 the authors talked about some works, but you mentioned only one.
“and some works suggest routine blood tests as a potential diagnostic tool for 66 COVID-19 (40).“ The authors can fix the phrase or add more references to the sentence.

Line 73: “Recently, artificial intelligence techniques, especially Machine Learning (ML), have been employed to analyze CBC data and assist in screening of patients with suspected COVID-19 infection (99; 101; 47; 1;7; 19; 60; 96)”. The authors cite in the text several studies using CBC data to COVID-19 patients screening, but they did not describe the findings of these works. Besides, they also do not discuss how the findings of the other authors corroborate their findings in this work.

Figure 4: I suggest that the authors arrange the distribution of the t-SNE visualization. Place each sampling method in a line and each dataset in a column. This will make it easier to compare sampling methods between datasets. So, instead of having 5 rows and 4 columns, the Figure would have 6 rows and 3 columns.

Supplementary figures comparing the same sampling method and the same algorithm for the different datasets could be interesting. It would make visualization easier when comparing datasets and not just methods.

In the same sense, a stacked Bar Chart showing the number of samples and the proportion of positive and negative COVID-19 records would be interesting. This figure would facilitate the reader's understanding of the number of samples and their distribution among the datasets.

Minor changes:

In the datasets available in: https://github.com/sbcblab/sampling-covid/blob/main/AE/DATA The features sexo and idade, are written in portuguese. Please, translate to english for keeping all features in the same pattern.
Line 103: typo: “TEchnique”
Line 116: “more than ≈ 13 million cases” The ≈ is not necessary and the numbers are more than 14 millions in this moment.
Line 138: typo: “pla-telets
Line 141: typo: “red blo-od”
Line 142:  typo: “% Eosino-phils”
Line: 143 “Patients with incomplete (missing data) or no data available for the above parameters were not included in the present analysis. For patients with more than a single test result available, a unique hemogram test was used, with the selection based on the blood test date - same-day results to the PCR-test collection date was adopted as a reference, or the day closest to this date.”  These sentences must be rewritten to facilitate the reader's understanding.
Line 198:  typo: “FLEU-RY”
Line 261: “the identification of different diseases prognoses, such as cancer (39; 48) and COVID-19 (7)”. It would be interesting to cite more examples.
Line 300:  ”Similar results were highlighted in other reviews (3)”. It would be better to cite more reviews or write in the singular.
Line 330:  “Since defining features for splitting the decision tree is directly related to the training model performance, dealing with imbalanced datasets is essential to improve the model performance, avoiding bias towards the majority class.” The meaning of the phrase at first reading seems controversial. It makes us believe that they want to use the unbalanced data, and not deal with the date in order to correct this imbalance. A slight adjustment in English would avoid this mistake on the part of the reader.
401 typo: “Synthetic Minority Over-sampling Technique (SMO-TE)”
Line 559:  It would be better to remove the citation in the conclusion topic
Line 561:  It would be better to remove the citation in the conclusion topic
F1 Score sometimes is written with a different font and sometimes not.


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

Input:
Title: COMPARISON OF MACHINE LEARNING TECHNIQUES TO HANDLE IMBALANCED COVID-19 CBC DATASETS
Review round: 1
Reviewer: 3

Output:
Basic reporting: The manuscript is clear, very well written and organized. It explores the pros and cons of different machine learning techniques to handle imbalanced biological datasets (in this case, focused on blood sampling related to COVID19).
The literature references are adequate, and the background information is detailed enough for non-experts to understand the work presented. All figures are clear and informative, summarizing the results and the overall strategy employed. All definitions necessary are presented in a clear fashion.
Experimental design: The research question is clearly stated, and well grounded by the literature cited.
It fills a gap in the knowledge regarding machine learning applied to clinical data and diagnostics. All methods are clearly stated.
Validity of the findings: The results are sound and the conclusions are clearly stated. All data required to support the conclusions is presented in the article.
Additional comments: This is a very well written article, dealing with a critical step in the use of machine learning for diagnostic purposes.

I see only minor points to be corrected:
l. 3 (title): define CBC
l. 29: change "to CBC" to "for CBC"
l. 31: change "evaluated" to "evaluate"
l. 61: change "most optimal" to "optimal"
l. 68: remove nominal reference
l. 91: change "applications of different" to "applications on different"
l. 142: remove dash from "Eosino-phils"
l. 161: change "founds" to "funds"
l. 190: change "Complementary" to "Complementarily"
l. 198: remove dash from "FLEU-RY"
l. 207: change "too" to "as well"
l. 212: remove nominal reference
l. 214: remove nominal reference
l. 234: change "allows a more" to "allows for a more"
l. 397: remove dash from "ab-out"
l. 428: remove "issue"
l. 483: change "the best and accurate" to "the best and most accurate"
l. 496, 505, 542: change "Sars-Cov-2" to "SARS-CoV-2"
l. 574: change "point-out" to "point out"
l. 577: change "carefulness to be taken" to "carefulness must be taken"


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

Input:
Title: COMPARISON OF MACHINE LEARNING TECHNIQUES TO HANDLE IMBALANCED COVID-19 CBC DATASETS
Review round: 2
Reviewer: 1

Output:
Basic reporting: The same as my previous report, as the manuscript was not significantly changed.
Experimental design: The same as my previous report, as the manuscript was not significantly changed.
Validity of the findings: The same as my previous report, as the manuscript was not significantly changed.
Additional comments: The authors unfortunately did not improve the quality of the article regarding any of my three main concerns:
1 - There are known issues regarding the quality of the dataset, that have been noticed by other groups that have given up on using this dataset. For example, the positive class for covid-19 is not expected to be 40 times more prevalent than the negative (as in the case of HSL). The authors need to need to make this clearer throughout the manuscript, especially in the conclusion.
2- The authors should perform statistical analysis to compare whether the variables have similar distributions for the three centers, regardless of the outcome. All that the authors have provided in the manuscript are visual comparisons according to the classes.
3- The authors need to use the area under the ROC curve (AUROC) the main metric, as it is the standard in machine learning studies. It is fine to add the other ones for specific analyzes, but the AUROC should be the main metric to allow for comparisons with other studies.


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

Input:
Title: COMPARISON OF MACHINE LEARNING TECHNIQUES TO HANDLE IMBALANCED COVID-19 CBC DATASETS
Review round: 2
Reviewer: 2

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


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

Input:
Title: COMPARISON OF MACHINE LEARNING TECHNIQUES TO HANDLE IMBALANCED COVID-19 CBC DATASETS
Review round: 2
Reviewer: 3

Output:
Basic reporting: The authors have addressed all points raised by this reviewer.
Experimental design: No comment.
Validity of the findings: No comment.
Additional comments: The authors have addressed all points raised by this reviewer (as well as those raised by two other reviewers). I consider the revised manuscript adequate for publication.


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

Input:
Title: TOPIC2FEATURES: A NOVEL FRAMEWORK TO CLASSIFY NOISY AND SPARSE TEXTUAL DATA USING LDA TOPIC DISTRIBUTIONS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The language of the manuscript is clear and unambiguous. The paper is structured well, including figures, tables and shared raw data.
Experimental design: The research questions are well defined, meaningful and relevant.
Validity of the findings: The experimental results are well stated.
Additional comments: In this paper, a novel classification scheme based on LDA topic modelling has been presented to classify noisy and sparse textual data. In general, the paper is structured well and contributes to the literature. However, a number of issues listed below should be taken into consideration to improve the content of the paper:
1- The language of the manuscript should be enhanced.
2- The manuscript lacks of discussing recent studies (2020-2021 papers) on LDA2vec.
3- The empirical results should include statistical validity tests.


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

Input:
Title: TOPIC2FEATURES: A NOVEL FRAMEWORK TO CLASSIFY NOISY AND SPARSE TEXTUAL DATA USING LDA TOPIC DISTRIBUTIONS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The authors present a text classification scheme enriched with LDA-based features.
Overall, the manuscript was ambiguous at some sections (see attached PDF), however, the overall idea is clear.

The references are clearly provided, however, please re-check that the citation style is consistent (sometimes you have just numbers, e.g., (14)).

Article structure is OK, with the exception of some low-res images.
Experimental design: The authors evaluate their method first by exploring different hyperparameter settings that offer sufficient performance. In the second step, they compare to existing baselines. The first part is done adequately, however, I have concerns related to the second part of the evaluation.

Here, the authors compare their method to "baselines", however it remains unclear whether they actually run the experiments against the baseline methods or just picked up performances from the literature. In the latter case, please additionally clarify why the results are comparable. Furthermore, I would suggest using at least one of the following baselines other researchers are familliar with, so it is clear that your method actually works:
1.) doc2vec + LR (scikit-learn)
2.) BERT (end-to-end)
3.) BERT (sentence-bert) + LR (scikit-learn)

Comparison against these could shed additional light on whether the proposed method performs well (and when). Finally, the number of data sets could be larger, you are only exploring the reviews, however I would be willing to believe there is potential if the proper comparisons are conducted.
Validity of the findings: The findings are in alignment with the empirical evaluation as it stands -> the proposed method is superior to others. One problem I have with the claim is statistical significance claim: You claim that the results are significantly bettter. I saw no statistical tests being conducted to verify/prove this claim.

Conclusions could be longer (see attached PDF).
Additional comments: I've left numerous comments also in the attached PDF, which will hopefully improve the manuscript's quality.


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

Input:
Title: TOPIC2FEATURES: A NOVEL FRAMEWORK TO CLASSIFY NOISY AND SPARSE TEXTUAL DATA USING LDA TOPIC DISTRIBUTIONS
Review round: 1
Reviewer: 3

Output:
Basic reporting: The article is a proposal on framework called Topic2features. Generally, it has been well-written in terms of paper organization and writing style. The framework has been described in detail, has been tested with amazon dataset, and yet has been compared and evaluated with few algorithms and benchmark.

I have no major issues to accep the paper as it is.
Experimental design: accceptable
Validity of the findings: acceptable
Additional comments: Very good paper, and well written.


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

Input:
Title: TOPIC2FEATURES: A NOVEL FRAMEWORK TO CLASSIFY NOISY AND SPARSE TEXTUAL DATA USING LDA TOPIC DISTRIBUTIONS
Review round: 1
Reviewer: 4

Output:
Basic reporting: The paper proposed a novel framework topic2features (T2F) to deal with short and
sparse data using the topic distributions of hidden topics gathered from the dataset and converting them into features to build a supervised classifier.

It seems that the merit of the study is very interesting and it contains a novel of a new approach of representation that is based on topics instead of a bag of words.
The authors fail to give a clear idea of the main approach of this study. The approach is described a very vague and it is hard to get how the topics were used in a vector space.
The study needs to be improved dramatically with more description of the algorithm using pseudocode or more clear workflows and figures.
I will not be able to judge the content of the study without a clear understanding of the novelty of topic representations. This section should be improved.
Also, I would suggest to the author to send the article for English proof before resubmitting it.
Experimental design: The study  shows satisfactory experiments
Validity of the findings: I will not be able to judge the content of the study without a clear understanding of the novelty of topic representations. This section should be improved.
Additional comments: Line 287 : might me should be "might be"
Figure 6 should be replaced with a more clear image or just replace with a regular table.
Figure 7 should be replaced with a more clear image or just replace with a regular table.


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

Input:
Title: TOPIC2FEATURES: A NOVEL FRAMEWORK TO CLASSIFY NOISY AND SPARSE TEXTUAL DATA USING LDA TOPIC DISTRIBUTIONS
Review round: 2
Reviewer: 1

Output:
Basic reporting: The manuscript in its second round is clear and unambiguous. I have a concern about English as it seems that the English is very simple and needs to be improved to a higher level.
The structure of the article is easy to follow, while it includes many figures that help to understand the idea of the algorithm.
Experimental design: The research question is wee defined and relevant. The article explains nicely the solution to the given question.
Validity of the findings: The article presents performance and validation approaches that were applied to the suggested algorithm.
The results are statistically sound.
Additional comments: line 375: and -> should be just and
line 261 I would use a number instead of no
The authors supposed to use mathematical styling in writing the mathematical phrases and equations. As such KI in line 299, line 310


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

Input:
Title: AN AUTOMATED METHOD TO ENRICH CONSUMER HEALTH VOCABULARIES USING GLOVE WORD EMBEDDINGS AND AN AUXILIARY LEXICAL RESOURCE
Review round: 1
Reviewer: 1

Output:
Basic reporting: See general comments
Experimental design: See general comments
Validity of the findings: See general comments
Additional comments: The topic of consumer health vocabulary enrichment is interesting. The followings are issues needed to be addressed.

	the significance of the work should be highlighted at the beginning.
	justification about the use of similarity metric.
	comparisons of the similarities and differences in different algorithms used should be provided, and also link this with the results.
	What are the research and practice implications? This should be included in the discussion section.
	Most references are out-of-date, that is, published five years ago. More recent works in this field (that is, published in recent five years, particularly 2020-2021) should be added. Also, some references have incomplete compilation, e.g., missing volume/issue/page numbering.
	double-check both definition and usage of acronyms: every acronym should be defined only once (at the first occurrence) and always used afterwards (except for the abstract). There are mistakes in this issue. For example, NLP.
	the manuscript presents some bad English constructions and grammar mistakes: a professional language editing and careful proofread is strongly needed to sufficiently improve the paper's presentation quality.


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

Input:
Title: AN AUTOMATED METHOD TO ENRICH CONSUMER HEALTH VOCABULARIES USING GLOVE WORD EMBEDDINGS AND AN AUXILIARY LEXICAL RESOURCE
Review round: 1
Reviewer: 2

Output:
Basic reporting: The article describes an automatic method to enrich consumer health vocabularies such as OAC CHV and MedLine Plus, through GloVe word embeddings and wordNet. It is an extension of previous work from [1], including additional datasets for evaluation, but it should be detailed.
The article uses an unambiguous text, but there are a few typos:
•	Line 95: vice versa, These
•	Line 122: refers instead of refer.
•	Some double spaces between lines 322 and 335.
•	Use of the CHV acronym on the abstract but not on the text.
The article structure is also great, but some of the pictures seem not to be very relevant (3a and 3b)

[1] Ibrahim, M., Gauch, S., Salman, O., & Alqahatani, M. (2020). Enriching consumer health vocabulary using enhanced GloVe word embedding. arXiv preprint arXiv:2004.00150.
Experimental design: The article perfectly fits the scope of the journal. It contains a very complete state of the art with a very rigorous and technical investigation following relevant technologies.
The article is an extension of previous work including additional datasets for evaluation, but it must be detailed to clarify the new points.
Validity of the findings: No comment.
Additional comments: The article presents an automated method for enriching consumer health vocabularies through GloVe and wordNet word embeddings. It is a great investigation perfectly documented in this article, as it is shown on the quality of the state of the art and the good results obtained. I should only note a few small comments for publication, as well as suggest the possibility of using the UMLS semantic types to improve the semantics of the extensions.


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

Input:
Title: A COMPARATIVE ANALYSIS ON QUESTION CLASSIFICATION TASK BASED ON DEEP LEARNING APPROACHES
Review round: 1
Reviewer: 1

Output:
Basic reporting: In this manuscript, the authors investigate three-to-five deep learning approaches based on 10-fold cross-validation for question classification tasks in the Turkish language. Kindly suggestions:

Better to move the problem statement (lines 61-65, 78-80) to the right section related to the methodology of this study.

The equations 2-7 with regard to LSTM (long short term memory), and the equations 8-11 about GRU (gated recurrent unit), might contribute limited knowledge.

The setup of the section “METHODOLOGY & RESULTS” might appear a bit unreasonable. That is because the proposed approach and focused novelties should be further improved to facilitate the recognition of other scholars.

The first technique of Wored2vec might not have been well introduced in the context. Further clarification would be grateful.
Experimental design: It's hard to ignore that the section of experiments might not have been well structured. That is to say, the arrangement of this article ought to be further enhanced before the next submission.
Validity of the findings: The novelties of the presented study should be further highlighted in preparing the future version of this manuscript. That might be because innovation is the gold criteria to recognize the most promising study.
Additional comments: The authors have told us a story about their focus on the basis of their deep literature investigation.