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Multi-Criteria Decision-Making Sorting Methods : Applications to Real-World Problems / ELSEVIER SCIENCE (2023)
Titre : Multi-Criteria Decision-Making Sorting Methods : Applications to Real-World Problems Type de document : e-book Editeur : ELSEVIER SCIENCE Année de publication : 2023 Importance : 280 p. ISBN/ISSN/EAN : 978-0-323-85232-6 Langues : Anglais (eng) Mots-clés : Management
PRISE DE DECISION ; CONFLITRésumé : Multi Criteria Decision Making (MCDM) is a generic term for all methods that help people making decisions according to their preferences, in situations where there is more than one conflicting criterion. It is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. The approach of MCDM involves decision making concerning quantitative and qualitative factors. Nombre d'accès : Illimité En ligne : https://neoma-bs.idm.oclc.org/login?url=https://ebookcentral.proquest.com/lib/ne [...] Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=574546
Titre : 5G IoT and Edge Computing for Smart Healthcare Type de document : e-book Auteurs : Akash Kumar BHOI Editeur : ELSEVIER SCIENCE Année de publication : 2022 ISBN/ISSN/EAN : 9780323905480 Note générale : copyrighted Langues : Anglais (eng) Résumé : 5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realization of a smart-healthcare system. The book provides insights on 5G technologies, along with intelligent processing algorithms/processors that have been adopted for processing the medical data that would assist in addressing the challenges in computer-aided diagnosis and clinical risk analysis on a real-time basis. Each chapter is self-sufficient, solving real-time problems through novel approaches that help the audience acquire the right knowledge. With the progressive development of medical and communication - computer technologies, the healthcare system has seen a tremendous opportunity to support the demand of today's new requirements. Focuses on the advancement of 5G in terms of its security and privacy aspects, which is very important in health care systems Address advancements in signal processing and, more specifically, the cognitive computing algorithm to make the system more real-time Gives insights into various information-processing models and the architecture of layers to realize a 5G based smart health care system Nombre d'accès : Illimité En ligne : https://neoma-bs.idm.oclc.org/login?url=https://www.scholarvox.com/book/88955608 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=585054
Titre : Advanced Data Mining Tools and Methods for Social Computing Type de document : e-book Auteurs : Sourav DE Editeur : ELSEVIER SCIENCE Année de publication : 2022 ISBN/ISSN/EAN : 9780323857086 Note générale : copyrighted Langues : Anglais (eng) Résumé : Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. Provides insights into the latest research trends in social network analysis Covers a broad range of data mining tools and methods for social computing and analysis Includes practical examples and case studies across a range of tools and methods Features coding examples and supplementary data sets in every chapter Nombre d'accès : Illimité En ligne : https://neoma-bs.idm.oclc.org/login?url=https://www.scholarvox.com/book/88930382 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=549369
Titre : Adversarial Robustness for Machine Learning Type de document : e-book Auteurs : Pin-Yu CHEN Editeur : ELSEVIER SCIENCE Année de publication : 2022 ISBN/ISSN/EAN : 9780128240205 Note générale : copyrighted Langues : Anglais (eng) Résumé : Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on adversarial attack, defense and veri?cation. Sections cover adversarial attack, veri?cation and defense, mainly focusing on image classi?cation applications which are the standard benchmark considered in the adversarial robustness community. Other sections discuss adversarial examples beyond image classification, other threat models beyond testing time attack, and applications on adversarial robustness. For researchers, this book provides a thorough literature review that summarizes latest progress in the area, which can be a good reference for conducting future research. In addition, the book can also be used as a textbook for graduate courses on adversarial robustness or trustworthy machine learning. While machine learning (ML) algorithms have achieved remarkable performance in many applications, recent studies have demonstrated their lack of robustness against adversarial disturbance. The lack of robustness brings security concerns in ML models for real applications such as self-driving cars, robotics controls and healthcare systems. Summarizes the whole field of adversarial robustness for Machine learning models Provides a clearly explained, self-contained reference Introduces formulations, algorithms and intuitions Includes applications based on adversarial robustness Nombre d'accès : Illimité En ligne : https://neoma-bs.idm.oclc.org/login?url=https://www.scholarvox.com/book/88955559 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=586155
Titre : Applied Numerical Methods for Chemical Engineers Type de document : e-book Auteurs : Navid MOSTOUFI Editeur : ELSEVIER SCIENCE Année de publication : 2022 ISBN/ISSN/EAN : 9780128229613 Note générale : copyrighted Langues : Anglais (eng) Résumé : Applied Numerical Methods for Chemical Engineers emphasizes the derivation of a variety of numerical methods and their application to the solution of engineering problems, with special attention to problems in the chemical engineering field. These algorithms encompass linear and nonlinear algebraic equations, eigenvalue problems, finite difference methods, interpolation, differentiation and integration, ordinary differential equations, boundary value problems, partial differential equations, and linear and nonlinear regression analysis. MATLAB is adopted as the calculation environment throughout the book because of its ability to perform all the calculations in matrix form, its large library of built-in functions, its strong structural language, and its rich graphical visualization tools. Through this book, students and other users will learn about the basic features, advantages and disadvantages of various numerical methods, learn and practice many useful m-files developed for different numerical methods in addition to the MATLAB built-in solvers, develop and set up mathematical models for problems commonly encountered in chemical engineering, and solve chemical engineering related problems through examples and after-chapter problems with MATLAB by creating application m-files. Clearly and concisely develops a variety of numerical methods and applies them to the solution of chemical engineering problems. These algorithms encompass linear and nonlinear algebraic equations, eigenvalue problems, finite difference methods, interpolation, linear and nonlinear regression analysis, differentiation and integration, ordinary differential equations, boundary value problems, and partial differential equations Includes systematic development of the calculus of finite differences and its application to the integration of differential equations, and a detailed discussion of nonlinear regression analysis, with powerful programs for implementing multivariable nonlinear regression and statistical analysis of the results Makes extensive use of MATLAB and Excel, with most of the methods discussed implemented into general MATLAB functions. All the MATLAB-language scripts developed are listed in the text and included in the book’s companion website Includes numerous real-world examples and homework problems drawn from the field of chemical and biochemical engineering Nombre d'accès : Illimité En ligne : https://neoma-bs.idm.oclc.org/login?url=https://www.scholarvox.com/book/88955521 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=585042 PermalinkArtificial Intelligence for Healthcare Applications and Management / Boris GALITSKY / ELSEVIER SCIENCE (2022)PermalinkPermalinkClassification Made Relevant : How Scientists Build and Use Classifications and Ontologies / Jules J. BERMAN / ELSEVIER SCIENCE (2022)PermalinkCustomized Production Through 3D Printing in Cloud Manufacturing / Lin ZHANG / ELSEVIER SCIENCE (2022)PermalinkDeep Network Design for Medical Image Computing : Principles and Applications / Haofu LIAO / ELSEVIER SCIENCE (2022)PermalinkDesigning Secure IoT Devices with the Arm Platform Security Architecture and Cortex-M33 / Trevor MARTIN / ELSEVIER SCIENCE (2022)PermalinkPermalinkDigital Innovation for Healthcare in COVID-19 Pandemic: Strategies and Solutions / Patricia Ordóñez De PABLOS / ELSEVIER SCIENCE (2022)PermalinkPermalink
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