Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/4661
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dc.contributor.authorBalamurugan, A.en_US
dc.contributor.authorSureshkumar, S.en_US
dc.contributor.authorSrivani, Puttaen_US
dc.contributor.authorLourens, Melanie Elizabethen_US
dc.contributor.authorAlsekai, Deema Mohammeden_US
dc.date.accessioned2023-03-14T07:03:36Z-
dc.date.available2023-03-14T07:03:36Z-
dc.date.issued2022-11-15-
dc.identifier.citationBalamurugan, A. et al. M. 2022. Optimization of e-learning and performance using IOT and 6G Technology. Journal of Pharmaceutical Negative Results. 13(Special Issue 9): 543-552 (9).en_US
dc.identifier.issn0976-9234-
dc.identifier.urihttps://hdl.handle.net/10321/4661-
dc.description.abstractThe sixth-generation (6G) has stricter criteria for the online learning capability and high interpretability of taught algorithms. It is anticipated that machine learning would be crucial for making network effective and flexible, however the most promising technologies are frequently considered as secret elements because of their profound designs’ major areas of strength for and. To make AI calculations more reasonable to 6G-empowered web of things (IoT) organizations, the motivation behind this paper is to analyse their translations. This article presents two different ways for acquiring translations: the free technique and the Joint strategy. Probes numerous IoT network datasets exhibit that the recommended techniques produce unrivalled execution regarding the two clarifications and forecasts.en_US
dc.format.extent10 pen_US
dc.language.isoenen_US
dc.publisherMedknow Publicationsen_US
dc.relation.ispartofJournal of Pharmaceutical Negative Results; Vol. 13, Issue Special Issue 9en_US
dc.subject1115 Pharmacology and Pharmaceutical Sciencesen_US
dc.subjectIoT (Internet of Things)en_US
dc.subject6G (sixth generation network)en_US
dc.subjectML (Machine Learning), etc.en_US
dc.titleOptimization of E-learning and performance using IOT and 6G Technologyen_US
dc.typeArticleen_US
dc.date.updated2023-01-27T09:37:02Z-
dc.publisher.urihttps://doi.org/10.47750/pnr.2022.13.S09.060en_US
dcterms.dateAccepted2022-10-6-
dc.identifier.doi10.47750/pnr.2022.13.S09.060-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.openairetypeArticle-
Appears in Collections:Research Publications (Management Sciences)
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