Next Article in Journal
A Graph Representation Learning Algorithm for Low-Order Proximity Feature Extraction to Enhance Unsupervised IDS Preprocessing
Next Article in Special Issue
Cross-Layer and SDN Based Routing Scheme for P2P Communication in Vehicular Ad-Hoc Networks
Previous Article in Journal
Comparisons of Scotopic/Photopic Ratios Using 2- and 10-Degree Spectral Sensitivity Curves
Previous Article in Special Issue
On the Determination of Meshed Distribution Networks Operational Points after Reinforcement
 
 
Article
Peer-Review Record

Locating Multiple Sources of Contagion in Complex Networks under the SIR Model

Appl. Sci. 2019, 9(20), 4472; https://doi.org/10.3390/app9204472
by Xiang Li 1, Yangyang Liu 1, Chengli Zhao 1,*, Xue Zhang 1 and Dongyun Yi 1,2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Appl. Sci. 2019, 9(20), 4472; https://doi.org/10.3390/app9204472
Submission received: 5 September 2019 / Revised: 8 October 2019 / Accepted: 18 October 2019 / Published: 22 October 2019
(This article belongs to the Special Issue Implementation of Vehicular Cloud Networks Using Wireless Sensor)

Round 1

Reviewer 1 Report

The manuscript presents a really interesting and exhaustive investigation of locating multiple sources of contagion in complex networks, through the approach namely Potential Concentration Label Method.

#The structure of the manuscript is really clear and all the sections are presented in a good way.

#The manuscript is well-written, clear and concise, and English is comprehensible and satisfactory. 

#The model and the methodology referred to the approach and the comparison analysis with other benchmark methods,  result in a pretty easy one and simulation and the test appear correct.

#The figures are clear and relevant with adequate captions.

Although I have few minor comments below that the authors should address to improve their study, the work can be considered for publication in Applied Science.

Below some considerations and comments:

#The abstract section is well written but I suggest, at the end of section, to shed light the findings of the paper, in a synthetic way, and the real contribution applying the PCL approach. The sentence “…method behaves best compared with four benchmark methods..”  it's too general.

#The introduction is too brief and it would be interesting to introduce aspects concerning real cases of multiple sources of contagion, with some references. It would be interesting too, underline other factors such as collective awareness and social relationships in epidemic spreading, etc. There is a lot of scientific literature regarding that. Moreover, I suggest highlighting the problems of decision making, health management in the case of simultaneous infections in real cases. This paper should better suggest how people in the health-care field and management in emergency or risky events can benefit from such an approach.

#The author chooses to explore this problem in complex networks under th SIR model.  I suggest extending the SIR assumption discussion. In section 2.2 there is not a clear examination of the impact of assuming a SIR propagation model. The author identifies two node states in contrast with the SIR assumption of the three states.

#I suggest adding some other references more recent.

This paper presents a model and the analysis methods that are based on scientific literature and although it is not strongly innovative,  it introduces some interesting aspects and for this reason, in my opinion, it is suitable for the publication.

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

See attached file.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The paper has been improved related to the former version. It contains original results which are illustrated with examples. The theoretical and formal technical support  developed in the article is also well-worked and adequate.

Back to TopTop