Julien Biaudet^1,*, Lisa Laroussi-Libeault², Mauricette Michallet³, Laurie Panse², Raymond Merle⁴

Psycho-Oncologie, Vol.18, No.1, pp. 17-22, 2024, DOI:10.32604/po.2023.043536

Abstract Cet article vise à partager une expérience innovante d’organisation et de financement de la recherche ayant impliqué les premiers concernés : les patients. Le groupe de travail « ECLAIR » du Cancéropôle Lyon Auvergne-Rhône-Alpes (CLARA) a été créé en fin d’année 2020 dans le but de contribuer à l’élaboration d’un appel à projets portant sur l’expérience patient en cancérologie, ouvert en janvier 2021. Constitué au départ de 8 membres dont 7 patients, coordonné par un chef de projets du CLARA, le groupe de travail ECLAIR a activement contribué à l’écriture du cahier des charges de l’appel à projets, à l’élaboration… More >

Jiahao Zhang, Honglin Wang^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2427-2441, 2023, DOI:10.32604/cmc.2023.038462

Abstract With the rapid development of technology, processing the explosive growth of meteorological data on traditional standalone computing has become increasingly time-consuming, which cannot meet the demands of scientific research and business. Therefore, this paper proposes the implementation of the parallel Clustering Large Application based upon RANdomized Search (CLARANS) clustering algorithm on the Spark cloud computing platform to cluster China’s climate regions using meteorological data from 1988 to 2018. The aim is to address the challenge of applying clustering algorithms to large datasets. In this paper, the morphological similarity distance is adopted as the similarity measurement standard instead of Euclidean distance,… More >

Neetika Bhandari^1,*, Payal Pahwa²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2043-2055, 2023, DOI:10.32604/iasc.2023.028368

Abstract Data is humongous today because of the extensive use of World Wide Web, Social Media and Intelligent Systems. This data can be very important and useful if it is harnessed carefully and correctly. Useful information can be extracted from this massive data using the Data Mining process. The information extracted can be used to make vital decisions in various industries. Clustering is a very popular Data Mining method which divides the data points into different groups such that all similar data points form a part of the same group. Clustering methods are of various types. Many parameters and indexes exist… More >

Carolina Saint Pierre, Carlos Alberto Busso

Phyton-International Journal of Experimental Botany, Vol.75, pp. 21-30, 2006, DOI:10.32604/phyton.2006.75.021

Abstract This article has no abstract. More >