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dc.contributor.authorNieto-Chaupis, Huber
dc.date.accessioned2025-02-04T15:33:28Z
dc.date.available2025-02-04T15:33:28Z
dc.date.issued2024
dc.identifier.urihttps://hdl.handle.net/20.500.13067/3605
dc.description.abstractThe apparition of a global pandemic commonly seen as a random, is unpredictable in both geographic location as well as time. For example, Monkeypox disease 2022 could have emerged rather before than Corona virus disease 2019 (Covid-19), so that not any sequence leading to a rule might be established. Similar reasoning can be applied to the morphological characteristics of Covid-19 statistics.Along the period 2020–2023, Covid-19 pandemic exhibited various waves and up to two large peaks. This paper explores the relation between the apparition of these peaks and a kind of algebra by which pandemic might be mathematically correlated to it. When model is applied to data, it is found that exists there a kind of correspondence at the sense that apparition of peaks are dictated by noncommutative operators that act onto dataes_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherIEEEes_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/es_PE
dc.subjectCOVID-19es_PE
dc.subjectPandemicses_PE
dc.subjectAlgebraes_PE
dc.subjectData modelses_PE
dc.subjectPolynomialses_PE
dc.subjectMathematical modelses_PE
dc.subjectCognitiones_PE
dc.subjectNumerical modelses_PE
dc.subjectCommutatorses_PE
dc.subjectDiseaseses_PE
dc.titleGlobal Pandemics Dictated by Noncommutative Algebraes_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.journalIEEEes_PE
dc.identifier.doihttps://doi.org/10.1007/978-3-031-70518-2_56
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.04es_PE
dc.publisher.countryPEes_PE
dc.source.beginpage1es_PE
dc.source.endpage5es_PE


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