Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart Cities

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

 

This paper discussed the Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart Cities, the paper is well-written, however, I encourage authors to make the following changes to their manuscript.

 

1.      Introduction:

The paper's introduction should provide a clearer motivation and aim of the study. The authors could explain why the optimal placement and scheduling of electric vehicle charging stations (EVCSs) is important for promoting the adoption of electric vehicles (EVs) and reducing carbon emissions. Additionally, the introduction should provide a brief overview of the research gap that this study aims to address.

 

2.      Literature Review/Related Work:

The "Previous Approaches" section should be expanded to cover all areas related to the research problem. The authors could discuss existing research on EVCS placement and scheduling, including optimization techniques, machine learning algorithms, and other relevant approaches. This section should also provide a critical analysis of the existing literature, highlighting its strengths and limitations, and explaining how the current study builds upon and extends previous research.

 

3.      Research Methodology:

The "Research Methodology" section needs to be improved and restructured for clarity. The authors should explain why they chose linear regression and Support Vector Machine (SVM) as their machine learning algorithms, and why they believe these algorithms are best suited for solving the problem. Additionally, the section should provide more detail on the data used for training and testing the models, as well as the evaluation metrics used to measure their performance.

 

4.      Figure 4:

While the explanation of Figure 4 is clear, the authors should explain its importance in the context of the paper. Specifically, they could discuss how the figure illustrates the effectiveness of the linear regression model in predicting the optimal placement of EVCSs, and how this finding can be used to inform policy and strategy decisions.

 

5.      Discussion:

A new section called "Discussion" should be added to focus on discussing the findings and implications of the study. The authors could discuss the key takeaways from their analysis, including the identification of Texas as the most favorable state for optimal EVCS placement. They could also explore the implications of their findings for policymakers, industry stakeholders, and the general public. This section should also discuss any limitations of the study and suggest directions for future research.

 

6.      Conclusion:

 

The conclusion section should be rewritten to focus on the paper's results and future directions. The authors could summarize their main findings, highlighting the contribution of the study to the field of EVCS placement and scheduling. They could also discuss potential applications of their research, such as informing the development of policies and strategies to promote the adoption of EVs and reduce emissions. Finally, the authors could suggest directions for future research, building upon the findings of the current study.

Comments on the Quality of English Language

Fine.

Author Response

Thank you for giving us the opportunity to submit a revised draft of our manuscript titled Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart cities to Sustainability. We appreciate the time and efforts that you and the reviewers have dedicated to provide valuable feedback. We have been able to incorporate changes that reflected the majority of suggestions. All the suggested changes have been highlighted in the manuscript.

Here's is a point by point response to the reviewer’s comments and concerns. 

1. Introduction:

The paper's introduction should provide a clearer motivation and aim of the study. The authors could explain why the optimal placement and scheduling of electric vehicle charging stations (EVCSs) is important for promoting the adoption of electric vehicles (EVs) and reducing carbon emissions. Additionally, the introduction should provide a brief overview of the research gap that this study aims to address.

 Response: Thank you for your suggestion. We have now briefly described the aim of study and motivation. The importance of optimal placement of charging stations and the research gaps in literature are also elaborated in introduction section page #2, line 72-82 & 94-107.

2. Literature Review/Related Work:

The "Previous Approaches" section should be expanded to cover all areas related to the research problem. The authors could discuss existing research on EVCS placement and scheduling, including optimization techniques, machine learning algorithms, and other relevant approaches. This section should also provide a critical analysis of the existing literature, highlighting its strengths and limitations, and explaining how the current study builds upon and extends previous research.

 Response: By appreciating the author’s comment, we have now incorporated critical analysis of existing literature, its strength and limitation page #3 & 4, line 135-138 & 183-192.

3. Research Methodology:

The "Research Methodology" section needs to be improved and restructured for clarity. The authors should explain why they chose linear regression and Support Vector Machine (SVM) as their machine learning algorithms, and why they believe these algorithms are best suited for solving the problem. Additionally, the section should provide more detail on the data used for training and testing the models, as well as the evaluation metrics used to measure their performance.

Response: We appreciate the author’s comment, and the reason for using both the models is now described in the manuscript. The details regarding training and testing the model and evaluation matrices have also been modified, page #8,9,10 line 307-322, 380-393.

4. Figure 4:

While the explanation of Figure 4 is clear, the authors should explain its importance in the context of the paper. Specifically, they could discuss how the figure illustrates the effectiveness of the linear regression model in predicting the optimal placement of EVCSs, and how this finding can be used to inform policy and strategy decisions.

Response: Thank you for your suggestion. The suggested clarification regarding figure 4 has been added to the manuscript to identify the how this figure depicts the effectiveness of model of page #11, line 426-429.

5. Discussion:

A new section called "Discussion" should be added to focus on discussing the findings and implications of the study. The authors could discuss the key takeaways from their analysis, including the identification of Texas as the most favorable state for optimal EVCS placement. They could also explore the implications of their findings for policymakers, industry stakeholders, and the general public. This section should also discuss any limitations of the study and suggest directions for future research.

 Response: The discussion section has been added to the paper that depicts the key findings and implication, limitations and future prospects of the study, page# 18,19,20 lines 559-645. 

6. Conclusion:

The conclusion section should be rewritten to focus on the paper's results and future directions. The authors could summarize their main findings, highlighting the contribution of the study to the field of EVCS placement and scheduling. They could also discuss potential applications of their research, such as informing the development of policies and strategies to promote the adoption of EVs and reduce emissions. Finally, the authors could suggest directions for future research, building upon the findings of the current study.

Response: Agree, we have now updated the conclusion section as per the suggestions of the reviewer page # 20,21, line 647-679.

 

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

In overall, I see this paper is a source for a collective data and doesn’t introduce any beneficial results for the research community with no novelties. No optimality to the placement of charging stations is implemented. 

Comments on the Quality of English Language

Moderate changes are required

Author Response

Thank you for giving us the opportunity to submit a revised draft of our manuscript titled Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart cities to Sustainability. We appreciate the time and efforts that you and the reviewers have dedicated to provide valuable feedback. We have been able to incorporate changes that reflected the majority of suggestions. All the suggested changes have been highlighted in the manuscript.

Here's is a point by point response to the reviewer’s comments and concerns. 

1. Introduction:

The paper's introduction should provide a clearer motivation and aim of the study. The authors could explain why the optimal placement and scheduling of electric vehicle charging stations (EVCSs) is important for promoting the adoption of electric vehicles (EVs) and reducing carbon emissions. Additionally, the introduction should provide a brief overview of the research gap that this study aims to address.

 Response: Thank you for your suggestion. We have now briefly described the aim of study and motivation. The importance of optimal placement of charging stations and the research gaps in literature are also elaborated in introduction section page #2, line 72-82 & 94-107.

2. Literature Review/Related Work:

The "Previous Approaches" section should be expanded to cover all areas related to the research problem. The authors could discuss existing research on EVCS placement and scheduling, including optimization techniques, machine learning algorithms, and other relevant approaches. This section should also provide a critical analysis of the existing literature, highlighting its strengths and limitations, and explaining how the current study builds upon and extends previous research.

 Response: By appreciating the author’s comment, we have now incorporated critical analysis of existing literature, its strength and limitation page #3 & 4, line 135-138 & 183-192.

3. Research Methodology:

The "Research Methodology" section needs to be improved and restructured for clarity. The authors should explain why they chose linear regression and Support Vector Machine (SVM) as their machine learning algorithms, and why they believe these algorithms are best suited for solving the problem. Additionally, the section should provide more detail on the data used for training and testing the models, as well as the evaluation metrics used to measure their performance.

Response: We appreciate the author’s comment, and the reason for using both the models is now described in the manuscript. The details regarding training and testing the model and evaluation matrices have also been modified, page #8,9,10 line 307-322, 380-393.

4. Figure 4:

While the explanation of Figure 4 is clear, the authors should explain its importance in the context of the paper. Specifically, they could discuss how the figure illustrates the effectiveness of the linear regression model in predicting the optimal placement of EVCSs, and how this finding can be used to inform policy and strategy decisions.

Response: Thank you for your suggestion. The suggested clarification regarding figure 4 has been added to the manuscript to identify the how this figure depicts the effectiveness of model of page #11, line 426-429.

5. Discussion:

A new section called "Discussion" should be added to focus on discussing the findings and implications of the study. The authors could discuss the key takeaways from their analysis, including the identification of Texas as the most favorable state for optimal EVCS placement. They could also explore the implications of their findings for policymakers, industry stakeholders, and the general public. This section should also discuss any limitations of the study and suggest directions for future research.

 Response: The discussion section has been added to the paper that depicts the key findings and implication, limitations and future prospects of the study, page# 18,19,20 lines 559-645. 

6. Conclusion:

The conclusion section should be rewritten to focus on the paper's results and future directions. The authors could summarize their main findings, highlighting the contribution of the study to the field of EVCS placement and scheduling. They could also discuss potential applications of their research, such as informing the development of policies and strategies to promote the adoption of EVs and reduce emissions. Finally, the authors could suggest directions for future research, building upon the findings of the current study.

Response: Agree, we have now updated the conclusion section as per the suggestions of the reviewer page # 20,21, line 647-679.

 

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Paper Title: Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart Cities

This paper analyses some variables that could contribute to disparities in the accessibility of electric vehicles charging stations. These variables include e.g., the percentage of electric vehicles, the population density, the electricity sources. Data related to these variables are modelled by linear regressions and support vector machine methods. Some experiments were conducted in USA by using aggregated data of some countries. The results showed that Texas emerges as the most favourable state for the placement of electric vehicles.

In my opinion, the authors investigated a topic of interest for Sustainability. However, even if this paper is not ready for publication in its present form, a properly revised version that takes care of following concerns and drawbacks pointed out is potentially publishable in this journal. Therefore, I want to encourage authors to revise and resubmit the paper. This is because, I do find that the paper can benefit from more detailed explanations of several elements, which are detailed in the following comments.

This paper is not strongly motivated from the research viewpoint. After reading the Introduction, I’m confused about the need for this work. The authors are strongly suggested to enforce the motivations for this work and how this work is collocated in the context of the literature, being the issue of the optimal charging station placement a well-studied argument.

The brief literature review section reports some state-of-art works. However, the description of these works is too concise, since it not easy to enucleate the insight of each work presented and its results. That brings me to the question of what the contributions of your work are, which are not clear and well-established. What do authors propose as opposed to the current literature? Are the authors strictly relying on the existing literature? Did they propose some novelties? Are they proposing something new? I do not find any answer to these questions throughout the manuscript. I recommend the authors to better enucleate the novelties of this work. For instance, even if in section 3.1, the authors reported the research objectives, but the third and fourth points I did not see how these points were addressed in the manuscript.

In the literature review, the author did not included recent research about the variables for EV site selection https://doi.org/10.1016/j.scs.2022.104067; this comment is also applied  in section 4.1, because the authors state “By carefully considering factors…”, because it was unclear how this evaluation was applied.

At the end of the literature review, the gaps in the current literature should be emphasised to better understand how your paper could provide a viable solution for these gaps.

The authors should improve the presentation of their methodology since it is unclear. Just as an example, it is unclear how each models works together and why different models are considered. The flow chart is helpful, but it is unclear the need for different models. Please clarify. Moreover, to my knowledge machine learning methods have a phase of data training, besides data training and data test. Thus, I’m asking where is data validation?

Math could be improved by presenting first the variables, next the formulas. Moreover, there are different variables throughout the manuscript: to make the reading clearer and more pleasant, I recommend that you report them (together with their descriptions) in a summary table at the end of the paper. Moreover, some variables were not defined, e.g., which is TPA, TPB, etc.

In section results, where is the K-Nearest Neighbor in the methodological section? It was only recalled in section results.

In section conclusions, authors should provide more practical implications of this work and future works. In this way, a reader understands better two key aspects: the relevance to this work toward practitioners, and possible direction for further improvements.

 

Minor

Check the unit of measure of Table 1

 

What are the points in figure 10?

Comments on the Quality of English Language

Minor editing of English language required

Author Response

Thank you for giving us the opportunity to submit a revised draft of our manuscript titled Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart cities to Sustainability. We appreciate the time and efforts that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. We have been able to incorporate changes that reflected the majority of suggestions. All the suggested changes have been highlighted in the manuscript.

Comment: This paper is not strongly motivated from the research viewpoint. After reading the Introduction, I’m confused about the need for this work. The authors are strongly suggested to enforce the motivations for this work and how this work is collocated in the context of the literature, being the issue of the optimal charging station placement a well-studied argument.

Response: You have raised an important point here. We have now updated the introduction section to clear the motivation of this study, page #2,3, line 72-82, 94-124.

Comment: The brief literature review section reports some state-of-art works. However, the description of these works is too concise, since it not easy to enucleate the insight of each work presented and its results. That brings me to the question of what the contributions of your work are, which are not clear and well-established. What do authors propose as opposed to the current literature? Are the authors strictly relying on the existing literature? Did they propose some novelties? Are they proposing something new? I do not find any answer to these questions throughout the manuscript. I recommend the authors to better enucleate the novelties of this work. For instance, even if in section 3.1, the authors reported the research objectives, but the third and fourth points I did not see how these points were addressed in the manuscript.

In the literature review, the author did not included recent research about the variables for EV site selection https://doi.org/10.1016/j.scs.2022.104067; this comment is also applied  in section 4.1, because the authors state “By carefully considering factors…”, because it was unclear how this evaluation was applied.

At the end of the literature review, the gaps in the current literature should be emphasised to better understand how your paper could provide a viable solution for these gaps.

Response: By appreciating the authors comment, the literature section has been further modified by adding the more details of the previous approaches. All the concerns of author regarding the study motivation, novelty and gaps have now been discussed in the paper. The findings have also now modified according to the objectives Page3 ,4, lines 109-124 & 183-192.

Comment: The authors should improve the presentation of their methodology since it is unclear. Just as an example, it is unclear how each models works together and why different models are considered. The flow chart is helpful, but it is unclear the need for different models. Please clarify. Moreover, to my knowledge machine learning methods have a phase of data training, besides data training and data test. Thus, I’m asking where is data validation?

Response: We have now updated the methodology section and elaborated the reason behind the use of different machine learning models. Moreover, Model validation has also been updated as suggested by the reviewer, page 8,9 line 307-322, 380-393.

Comment: Math could be improved by presenting first the variables, next the formulas. Moreover, there are different variables throughout the manuscript: to make the reading clearer and more pleasant, I recommend that you report them (together with their descriptions) in a summary table at the end of the paper. Moreover, some variables were not defined, e.g., which is TPA, TPB, etc.

Response: thank you for your suggestion. We have now described all the variables and their description at the end of the manuscript. Moreover, the formulas have also been improved page 10,23.

Comment: In section results, where is the K-Nearest Neighbor in the methodological section? It was only recalled in section results.

Response: We apologize for this mistake. This mistake has been removed from the manuscript.

Comment: In section conclusions, authors should provide more practical implications of this work and future works. In this way, a reader understands better two key aspects: the relevance to this work toward practitioners, and possible direction for further improvements.

Response: We apologize for this mistake. This mistake has been removed from the manuscript.

 

Minor

Check the unit of measure of Table 1

What are the points in figure 10?

Response: We appreciate your concern but as these values in the table are the percentages calculated from the figure 4, there will be no unit of measures for these values. 

 

Comments on the Quality of English Language

Minor editing of English language required

The quality of English language has been improved as per the suggestion.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

This paper investigates the key variables that contribute to demographic disparities in the accessibility of EV charging stations (EVCSs). Also, this study analyze the impact of various factors, including EV percentage, geographic area, population density, available electric vehicle supply equipment (EVSE) ports, electricity sources, energy costs, per capita and average family income, traffic patterns, and climate, on the placement of EVCSs in nine selected U.S. states.

This paper is interesting but it can be improved subject to following comments.

1. Introduction section can be improved by reviewing these new published papers in MDPI.

A. Optimizing Electric Vehicle Operations for a Smart Environment: A Comprehensive Review

B. A comprehensive review of electric vehicles in energy systems: Integration with renewable energy sources, charging levels, different types, and standards

C. Risk assessment of industrial energy hubs and peer-to-peer heat and power transaction in the presence of electric vehicles

 

2. The novelty and contribution of this paper can be presented in the introduction section before last paragraph.

3. The uncertainty model of input data is not considered in the proposed model.

4. The obtained results should be compared with the previous methods.

5. A discussion is necessary in order to show the capability of proposed method.

6. What is the disadvantages of proposed method?

7. Reference list can be improved via new published papers.

Comments on the Quality of English Language

Minor editing of English language required.

Author Response

Thank you for giving us the opportunity to submit a revised draft of our manuscript titled Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart cities to Sustainability. We appreciate the time and efforts that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. We have been able to incorporate changes that reflected the majority of suggestions. All the suggested changes have been highlighted in the manuscript.

1. Introduction section can be improved by reviewing these new published papers in MDPI.
2. Optimizing Electric Vehicle Operations for a Smart Environment: A Comprehensive Review
3. A comprehensive review of electric vehicles in energy systems: Integration with renewable energy sources, charging levels, different types, and standards
4. Risk assessment of industrial energy hubs and peer-to-peer heat and power transaction in the presence of electric vehicles

Response: Thank you for pointing this out. We have now reviewed the suggested important articles suggested by the reviewer in the manuscript. 

2. The novelty and contribution of this paper can be presented in the introduction section before last paragraph.

Response: By appreciating the author’s comment, the novelty and contribution of this paper is briefly described in introduction section, page 3, line 109-124.

3. The uncertainty model of input data is not considered in the proposed model.

Response: The description of the uncertainty of input data is discussed in the paper page 8, line 297-304

4. The obtained results should be compared with the previous methods.

Response: The obtained results have now been compared with the previous methods in the discussion section in table 3. Page 19,20.

5. A discussion is necessary in order to show the capability of proposed method.

Response: The key findings and implications of the proposed method have been discussed in the discussion section as suggested by the reviewer page 19 line 566-618.

6. What is the disadvantages of proposed method?

Response: The disadvantage or limitations of the proposed models are now elaborated in manuscript page 20, line 619-628.

7. Reference list can be improved via new published papers.

Response: The reference list has been updated as per the suggestions.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

 

This paper is a source for a collective data and doesn’t introduce any beneficial results for the research community with no novelties.

No optimality to the placement of charging stations is implemented. 

Comments on the Quality of English Language

Moderate corrections van be done

Author Response

Reviewer 2

 Comment: This paper is a source for a collective data and doesn’t introduce any beneficial results for the research community with no novelties.

No optimality to the placement of charging stations is implemented. 

Response: Comment: By appreciating the reviewer’s comment, the research gaps in the literature has been highlighted at the end of literature, and the connection between the research gaps and the objectives of this study has also been mentioned, page #4, line 185-209. The beneficial results and Novelties of this study have now been discussed in the manuscript as suggested by the reviewer page 3, line 105-125.  

Thank you for pointing this out. The implementation of developed model for charging station placement by utilizing the key indicators as input data is indicated in figure 6 and 10. Figure 12 only demonstrates the position of already present charging stations in Texas, and figure 13 showed the already present and expected corridors and this study just made the comparison between the different states in terms of optimize placement and does not demonstrate the optimized placement in Texas. This study serves as the direction for the sustainable placement of EVCSs and the proposed models will also be assessed for individual states in near future.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

I went to the revised paper, the authors applied a few actions to my comments, but they ignored some others, therefore another round review is still mandatory if the authors want to publish in this journal. Therefore, the authors are strongly suggested to accurately revise and recheck their paper before resubmission.

I report my original comments (in italic) that authors did not consider or consider in a vague way. In not italic I report my answer.

·       In the literature review, the author did not included recent research about the variables for EV site selection https://doi.org/10.1016/j.scs.2022.104067; this comment is also applied  in section 4.1, because the authors state “By carefully considering factors…”, because it was unclear how this evaluation was applied.

 

This comment was ignored. I suggested an important paper that helps collect factors (or indicators) to select optimal station charging, but the authors neither cited it nor discussed. However, the authors of the paper under review call for factors (or indicators). Therefore, the previous paper should be mentioned, and clearly linked to the literature. Revise and adjust.

 

·       The authors should improve the presentation of their methodology since it is unclear. Just as an example, it is unclear how each models works together and why different models are considered. The flow chart is helpful, but it is unclear the need for different models. Please clarify. Moreover, to my knowledge machine learning methods have a phase of data training, besides data training and data test. Thus, I’m asking where is data validation?

 

Note that DATA VALIDATION is different from data training and data testing. The reviewer did not see where data validation is considered and faced in this paper. Moreover, data validation have another functions as opposed to data training and test. Revise and adjust.

 

·       Math could be improved by presenting first the variables, next the formulas. Moreover, there are different variables throughout the manuscript: to make the reading clearer and more pleasant, I recommend that you report them (together with their descriptions) in a summary table at the end of the paper. Moreover, some variables were not defined, e.g., which is TPA, TPB, etc.

 

 

While I appreciate the final table at the end, I did not see the action related to “Math could be improved by presenting first the variables, next the formulas”. In the revised manuscript, formulas are always reported before variable. Revise and adjust.

Author Response

Reviewer 3

I went to the revised paper, the authors applied a few actions to my comments, but they ignored some others, therefore another round review is still mandatory if the authors want to publish in this journal. Therefore, the authors are strongly suggested to accurately revise and recheck their paper before resubmission.

I report my original comments (in italic) that authors did not consider or consider in a vague way. In not italic I report my answer.

• In the literature review, the author did not included recent research about the variables for EV site selection https://doi.org/10.1016/j.scs.2022.104067; this comment is also applied  in section 4.1, because the authors state “By carefully considering factors…”, because it was unclear how this evaluation was applied.

This comment was ignored. I suggested an important paper that helps collect factors (or indicators) to select optimal station charging, but the authors neither cited it nor discussed. However, the authors of the paper under review call for factors (or indicators). Therefore, the previous paper should be mentioned, and clearly linked to the literature. Revise and adjust.

Comment: We apologize for this mistake. It is an interesting aspect to explore. Now, we have discussed the suggested paper in the manuscript in the literature as well as in the discussion section page #3,7 line 128-135 & 267-270.

• The authors should improve the presentation of their methodology since it is unclear. Just as an example, it is unclear how each models works together and why different models are considered. The flow chart is helpful, but it is unclear the need for different models. Please clarify. Moreover, to my knowledge machine learning methods have a phase of data training, besides data training and data test. Thus, I’m asking where is data validation?

 

Note that DATA VALIDATION is different from data training and data testing. The reviewer did not see where data validation is considered and faced in this paper. Moreover, data validation have another functions as opposed to data training and test. Revise and adjust.

Comment: We apologize for this mistake and by appreciating the reviewer’s comment, the reason behind the use of these two different models is elaborated in the study, page #10, 339-359. Also, data validation process for the machine learning models is also described in experimental section, page # 9, line 327-335.

 

• Math could be improved by presenting first the variables, next the formulas. Moreover, there are different variables throughout the manuscript: to make the reading clearer and more pleasant, I recommend that you report them (together with their descriptions) in a summary table at the end of the paper. Moreover, some variables were not defined, e.g., which is TPA, TPB, etc.

 

 

While I appreciate the final table at the end, I did not see the action related to “Math could be improved by presenting first the variables, next the formulas”. In the revised manuscript, formulas are always reported before variable. Revise and adjust.

Comment: We apologize for this mistake. The formulas have been improved as suggested by the reviewer by presenting variables before the formulas, page #9,10.

 

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

Accept in present form.

Author Response

Thanks

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

This work serves as a repository for aggregate data and presents no novel results that would be beneficial to the scientific community. 

Comments on the Quality of English Language

Moderate editing of English language required

Reviewer 3 Report

Comments and Suggestions for Authors

Now, the authors provided an acceptable paper.

 

Comments on the Quality of English Language

Minor editing of English language required