Computational Intelligence for Medical Internet of Things (MIoT) Applications | Machine Intelligence Applications for IoT in Healthcare
Idioma: inglés
Editorial: Elsevier Science & Technology, 2023
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Computational Intelligence for Medical Internet of Things (MIoT) Applications | Machine Intelligence Applications for IoT in Healthcare | Ahmed A. Abd El-Latif (u. a.) | Taschenbuch | Advances in ubiquitous sensing applications for healthcare | Einband - flex.(Paperback) | Englisch | 2023 | Elsevier Science & Technology | EAN 9780323994217 | Verantwortliche Person für die EU: Elsevier B.V., Radarweg 29, 1043 NX AMSTERDAM, NIEDERLANDE, productsafety[at]elsevier[dot]com | Anbieter: preigu.
N° de ref. del artículo 122072459
- Título
- Computational Intelligence for Medical Internet of Things (MIoT) Applications | Machine Intelligence Applications for IoT in Healthcare
- Autor
- Ahmed A. Abd El-Latif (u. a.)
- Editorial
- Elsevier Science & Technology
- Año de publicación
- 2023
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 0323994210
- ISBN 13
- 9780323994217
- Peso del artículo
- 792 gramos
- Dimensiones
- 235 x 193 x 21 mm
- Catálogos de vendedores
- Bücher
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Acerca del autor
Prof. Ahmed Abd El-Latif: (B.Sc. with honor rank in Mathematics and Computer Science in 2005, (M.Sc in Computer Science in 2010), and Ph. D. in Computer Science & Technology at Harbin Institute of Technology, Harbin, P. R. China in 2013. He is an associate professor of Computer Science at Menoufia University, Egypt and School of Information Technology and Computer Science, Nile University, Egypt. He is author and co-author of more than indexed 140 papers. He is a referee of many referred international repute journals and conferences. He received many awards, State Encouragement Award in Engineering Sciences 2016, Arab Republic of Egypt; the best Ph.D. student award from Harbin Institute of Technology, China 2013; Young scientific award, Menoufia University, Egypt 2014. He is a fellow at Academy of Scientific Research and Technology, Egypt. Dr. Abd El-Latif is an associate editor in several Scopus Journals and leading many Special issues in SCI journals.
Prof. Kevin Curran is a Professor of Cyber Security, Executive Co-Director of the Legal innovation Centre and group leader of the Ambient Intelligence & Web Technologies Research Group at Ulster University. He is also a senior member of the IEEE. Prof Curran is globally recognized as a security Top Influencer "IFSEC Global influencers in security and fire 2020" in category Security thought leadership. He was ranked #2.
Prof Curran is perhaps most well-known for his work on Internet security & location positioning evidenced by over 800 published works. His expertise has been acknowledged by invitations to present his work at international conferences, overseas universities and research laboratories. He is a regular contributor on TV & radio and in trade and consumer IT magazines with 1000+ interviews in recent years. He is currently the recipient of a Royal Academy of Engineering Senior Research Fellowship and is an IEEE Technical Expert for Internet Security. Professor Curran has performed external panel duties for various Higher Education Institutions and public bodies such as OFCOM and the National Institute for Health Research (NIHR).
Patrick Siarry was born in France in 1952. He received the Ph.D. degree in computer science and optimization from University Paris VI, Paris, France, in 1986, and the Doctorate of Sciences (Habilitation) degree in computer science and optimization from University Paris XI, Orsay, France, in 1994.,He was first involved in the development of analog and digital models of nuclear power plants with Electricité de France, Paris. Since 1995, he has been a Professor of Automatics and Informatics with Université Paris-Est Créteil, Créteil, France. His main research interests include computer-aided design of electronic circuits, cognitive intelligence, and the applications of new stochastic global optimization heuristics to various engineering fields, also including the fitting of process models to experimental data, the learning of fuzzy rule bases, and of neural networks.
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