dc.creatorNieto-Chaupis, Huber
dc.date.accessioned2022-04-29T17:58:08Z
dc.date.available2022-04-29T17:58:08Z
dc.date.created2022-04-29T17:58:08Z
dc.date.issued2021-12
dc.identifierNieto-Chaupis, H. (2021). Pandemic of Covid-19 as Global Entropy: When Shannon Theory fits To-Date Data of New Infections. In 2021 International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB) (pp. 298-301). IEEE.
dc.identifier978-1-6654-3755-4
dc.identifierhttps://hdl.handle.net/20.500.13067/1814
dc.identifier2021 International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB)
dc.identifierhttps://doi.org/10.1109/ICEIB53692.2021.9686434
dc.description.abstractIt is well-known that Coronavirus has been propagated due to human activities mainly based at intercontinental flights. Thus, in the first months of 2020, most new countries have already presented peaks in the number of infections, so that airports and borders were closed. With the social restrictions imposed along the beginning of second semester of 2020, the curve of cases of infections has exhibited to be flat in comparison to the beginning of 2020. Therefore, the human activities of end-of-year 2020 have caused againg peaks as the second wave of the pandemic in most countries. So far, by the end of 2021, most countries particularly located at Europe, are exhibiting the fourth wave. In this paper, the entropy of Shannon is considered as inherent mechanism and responsible of waves and large peaks of the number of infections. Modelling of data, the results of this paper suggest the inherent presence of a global entropy due to the transfer of randomness between neighboring countries.
dc.languageeng
dc.publisherUniversidad Autónoma del Perú
dc.publisherPE
dc.relationhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85125839956&doi=10.1109%2fICEIB53692.2021.9686434&partnerID=40
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceAUTONOMA
dc.source298
dc.source301
dc.subjectCOVID-19
dc.subjectPandemics
dc.subjectFitting
dc.subjectEurope
dc.subjectBig Data
dc.subjectAirports
dc.subjectEntropy
dc.titlePandemic of Covid-19 as Global Entropy: When Shannon Theory fits To-Date Data of New Infections
dc.typeinfo:eu-repo/semantics/article


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