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All concerns raised by the reviewers have been satisfactorily addressed; I am therefore pleased to inform you that your work has now been accepted for publication in PeerJ Computer Science.
Please be advised that you cannot add or remove authors or references post-acceptance, regardless of the reviewers' request(s).
Thank you for submitting your work to this journal. I look forward to your continued contributions on behalf of the Editors of PeerJ Computer Science.
With kind regards,
[# PeerJ Staff Note - this decision was reviewed and approved by Yilun Shang, a 'PeerJ Computer Science' Section Editor covering this Section #]
The paper is well-written in clear and unambiguous, professional English. Literature references and field background/context are now sufficient. The article structure, figures, tables, and raw data sharing are professional.
The research question is well-defined and relevant, and the paper clearly states how it fills an identified knowledge gap. The investigation is rigorous and performed to a high technical and ethical standard. The methods are described in sufficient detail to replicate.
The data provided is robust, statistically sound, and controlled. The conclusions are well-stated and linked to the original research question. The paper has addressed the previous concerns regarding the impact and novelty of the findings.
The author has addressed all my previous concerns, and the paper's structure and organization have been improved to better highlight the achievement of the stated goals.
The Authors incorporated my suggestions. i recommend this paper for publishing in this journal.
The Authors incorporated my suggestions. i recommend this paper for publishing in this journal.
The Authors incorporated my suggestions. i recommend this paper for publishing in this journal.
The Authors incorporated my suggestions. i recommend this paper for publishing in this journal.
I have received reviews of your manuscript from scholars who are experts on the cited topic. They find the topic interesting; however, several concerns regarding experimental results, literature review, and comparisons with current approaches must be addressed. These issues require a major revision. Please refer to the reviewers’ comments at the end of this letter; you will see that they advise you to revise your manuscript. If you are prepared to undertake the work required, I would be pleased to reconsider my decision. Please submit a list of changes or a rebuttal against each point that is being raised when you submit your revised manuscript.
Thank you for considering PeerJ Computer Science for the publication of your research.
With kind regards,
The paper appears well-written in professional English. References are present, but consider adding more context about the chosen field. The structure seems appropriate, but some figures could be improved.
1. Line 172: Define "biofunctionalized SPR-TFBG sensor" and explain its role in disease detection within the dataset description.
2. Line 180-185: Clarify the meaning of "PBS, 02ul, 08ul, 32ul, and 128ul" in the context of the experiment.
Figures:
1. Figures 8 & 9: Consider replacing text-based flowcharts with visual aids like signal waveforms or symbols for better clarity.
2. Figures 1, 5 & 7: These figures seem redundant. If they all convey the same concept of federated learning structure, choose one and improve it with more details or combine the best aspects of each figure.
The research question (enhancing communication and privacy) seems relevant to the journal's scope, but originality needs further assessment.
1. The paper focuses heavily on the dataset, feature selection, and performance evaluation, but the core aim (improving communication and privacy) needs more emphasis in the main body.
2. While the machine learning aspects are interesting, the impact on wireless channels and privacy enhancement within the federated learning framework needs clearer explanation and results.
1. The data provided is robust and statistical sound.
2. The results could be more convincing if the paper focused more on the challenges of enhancing wireless channels and improving privacy, as stated in the abstract and introduction.
3. The conclusions are well-stated, but the impact and novelty of the findings are not fully assessed.
The overall contribution of the paper seems sound, but the structure and organization could be improved to better highlight the achievement of the stated goals.
• The basic reporting of the manuscript is clear. The motivation could be enhanced. The English language used is clear and the manuscript is quite easy to follow. The structure of the paper conforms to PeerJ standards. Figures are labeled correctly and in high quality. The literature study used or Federated Learning in Healthcare looks quite old. There are still some more profound works that are not reviewed in this work. Research gaps are missing in this manuscript and authors should have claimed the contribution after highlighting the research issues of existing techniques. The paper should give depth analysis.
The experimental setup can be improved. The proposed method is not compared with the state-of-the-art/related works in terms of experimentation, results, and suitability.
It looks that some significant findings were observed. However, the findings can be evaluated after clarifying the models.
It looks that some significant findings were observed. However, the findings can be evaluated after clarifying the models.
1- Comparison with existing studies is not properly addressed.
2- Redundancy still exists throughout in the paper
3- The resource link of experiments and datasets should be shared.
4- The Literature review is very limited. Please add some latest literature
5- Proof reading need again, still there are missing terms and symbol .
6- Authors need to remove the duplication in terms of displaying data.
7- Authors need to improve several figures such as Figure 3 etc.
8- Revise the abstract according to the results and claims
As above
As above
as above
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