Development of models with explicit mechanisms for data generation from cluster structures is of major interest in order to provide a theoretical framework for cluster structures found in data. Especially appealing in this regard are the so-called typological structures in which observed entities relate in various degrees to one or several prototypes. Such structures are relevant in many areas such as medicine or marketing, where any entity (patient/consumer) may adhere, with different degrees, to one or several prototypes (clinical scenario/consumer behavior), modelling a typological classification. In fuzzy clustering, the fuzzy c-means (FCM) method has become one of the most popular techniques. As a fuzzy analogue of c-means crisp clustering, FCM models a typological classification, much the same way as c-means. However, FCM does not adhere to the statistical paradigm at which the data are considered generated by a cluster structure, while crisp c-means does. The present work proposes a framework for typological classification based on a fuzzy clustering model of data generation.
Development of models with explicit mechanisms for data generation from cluster structures is of major interest in order to provide a theoretical framework for cluster structures found in data. Especially appealing in this regard are the so-called typological structures in which observed entities relate in various degrees to one or several prototypes. Such structures are relevant in many areas such as medicine or marketing, where any entity (patient/consumer) may adhere, with different degrees, to one or several prototypes (clinical scenario/consumer behavior), modelling a typological classification. In fuzzy clustering, the fuzzy c-means (FCM) method has become one of the most popular techniques. As a fuzzy analogue of c-means crisp clustering, FCM models a typological classification, much the same way as c-means. However, FCM does not adhere to the statistical paradigm at which the data are considered generated by a cluster structure, while crisp c-means does. The present work proposes a framework for typological classification based on a fuzzy clustering model of data generation.
Combining deft musical analysis and intriguing personal insight, Azzi and Collier vividly capture the life of Piazolla, the Argentinean musician--a visionary who won worldwide acclaim but sparked bitter controversy in his native land. 42 halftones.
Foreword This volume includes papers presented at TAKE 2021 Conference The Multidisciplinary Conference on Intangibles, held online between the 7 th and the 9th July 2021 and hosted by Universidade Portucalense, from Porto, Portugal. Detailed information about the Conference is to be found in the Conference Website: https://take-conference2021.com/. A Book of Abstracts was also published. TAKE 2021 included 80 presentations, by almost 100 participants, including 8 keynote speakers, from 20 countries. Done during the Covid-19 crisis, TAKE 2021 was a show of intelligence, work, and solidarity, We thank infinitely all those involved, which contributed to the success of the event. We hope to continue the TAKE saga, next year with TAKE 2022 whose website is already online: https://take-conference2022.com/. Best wishes and kindest regards. Eduardo Tomé, on behalf of the Organizing Committee
Written by two expert oncologists, specializing in female cancers, Dx/Rx: Gynecologic Cancer is a perfect pocket reference for all professionals involved in the care of women with gynecologic cancer. This handy, 136-page book provides comprehensive, up-to-date information on the epidemiology, symptoms, diagnosis, and management of malignancies of the ovaries, cervix, uterus, and fallopian tubes. Topics include a review of gynecologic tumors, detailed analysis on treatment strategies, and a discussion of past and current literature that has shaped the field. Presented in a concise, quick-reference format, Dx/Rx: Gynecologic Cancer is an essential guide for the care of women with malignancies of the reproductive system.
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