A Detecting System for Abrupt Changes in Temporal Incidence Rate of COVID-19 and Other Pandemics

Autor: Jiecheng Song, Guanchao Tong, Wei Zhu

Publikováno v: Stats, Vol 6, Iss 3, Pp 931-941 (2023)

COVID-19 spread dramatically across the world in the beginning of 2020. This paper presents a novel alert system that will detect abrupt changes in the COVID-19 or other pandemic incidence rate through the estimated time-varying reproduction number (

Externí odkaz: https://doaj.org/article/d4a8fa0a9cc24c62aef306eeb77fcf46

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Predicting COVID-19 Cases in South Korea with All K-Edited Nearest Neighbors Noise Filter and Machine Learning Techniques

Autor: David Opeoluwa Oyewola, Emmanuel Gbenga Dada, Sanjay Misra, Robertas Damaševičius

Publikováno v: Information, Vol 12, Iss 12, p 528 (2021)

The application of machine learning techniques to the epidemiology of COVID-19 is a necessary measure that can be exploited to curtail the further spread of this endemic. Conventional techniques used to determine the epidemiology of COVID-19 are slow

Externí odkaz: https://doaj.org/article/85ef0dbd575740a1905691e3dc2413f7

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Complex Labelling and Similarity Prediction in Legal Texts: Automatic Analysis of France's Court of Cassation Rulings

Autor: Charmet, Thibault, Cherichi, Inès, Allain, Matthieu, Czerwinska, Urszula, Fouret, Amaury, Sagot, Benoît, Bawden, Rachel

Publikováno v: LREC 2022-13th Language Resources and Evaluation Conference
LREC 2022-13th Language Resources and Evaluation Conference, Jun 2022, Marseille, France

International audience; Detecting divergences in the applications of the law (where the same legal text is applied differently by two rulings) is an important task. It is the mission of the French Cour de Cassation. The first step in the detection of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d9f5915d7b39bbc661a0d917a6a695ce
https://hal.inria.fr/hal-03663110