{"title":"Finding Community Infection Spreading Factor’s presence in a Community","authors":"S. Naskar, A. K. Goswami, S. S. Sarma","doi":"10.51456/ijeit.2021.v10i12.002","DOIUrl":null,"url":null,"abstract":"In all the countries, all the communities consist of people having certain attitudes and interests in common. The whole community can be mapped into a graph network. Every distinct individual can be assumed as a node of the constructed graph for the community. To declare a pandemic situation for any country, we first need to check whether the infection is spread throughout the Community or not. For this purpose we need to calculate the existence of cliques and the nodes of the maximal clique will be the infection spreading factors. In this work, we try to find out the presence of these spreading factors in the community graph network.","PeriodicalId":347608,"journal":{"name":"International Journal of Engineering and Innovative Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering and Innovative Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51456/ijeit.2021.v10i12.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In all the countries, all the communities consist of people having certain attitudes and interests in common. The whole community can be mapped into a graph network. Every distinct individual can be assumed as a node of the constructed graph for the community. To declare a pandemic situation for any country, we first need to check whether the infection is spread throughout the Community or not. For this purpose we need to calculate the existence of cliques and the nodes of the maximal clique will be the infection spreading factors. In this work, we try to find out the presence of these spreading factors in the community graph network.