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Big Data and Smart Digital Environment / edited by Yousef Farhaoui, Laila Moussaid.

Contributor(s): SpringerLink (Online service) | Farhaoui, Yousef., editor literario | Moussaid, Laila., editor literario
Series: (Studies in Big Data, 2197-6503; 53); (Intelligent Technologies and Robotics (Springer-42732)).Publisher: Cham : Imprint: Springer, 2019Description: 1 recurso en línea (IX, 406 páginas).ISBN: 9783030120481.Subject: Datos masivosOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
A smart parking for invisible disabilities -- Smart water management: Pillars and Technologies -- Integrating ICT in Education: An Adaptive Learning System Based on Users' Context in Mobile Environments -- Modified Strategy of Direct Torque Control Applied to Asynchronous Motor based on PI Regulators -- Managing Temporal and Versioning Aspects of JSON-based Big Data via the τJSchema Framework -- Specific Qualification for Information System Components from Managers and Technical Staff Perspective -- A clustering-based method for detecting text area in videos recorded with the aid of a smartphone -- Chipless RFID Tag Using Multiple G-Shaped Resonators -- Security Analysis of Ye et al. Authentication Protocol for Internet of Things.
Abstract: This book reviews the state of the art of big data analysis and smart city. It includes issues which pertain to signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualisation, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. Papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular. The book appeals to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well as anyone interested in big data analysis and smart city.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA76.9.B45 2019 EB (Browse shelf(Opens below)) Acceso electrónico eBooks26062247
Total holds: 0

A smart parking for invisible disabilities -- Smart water management: Pillars and Technologies -- Integrating ICT in Education: An Adaptive Learning System Based on Users' Context in Mobile Environments -- Modified Strategy of Direct Torque Control Applied to Asynchronous Motor based on PI Regulators -- Managing Temporal and Versioning Aspects of JSON-based Big Data via the τJSchema Framework -- Specific Qualification for Information System Components from Managers and Technical Staff Perspective -- A clustering-based method for detecting text area in videos recorded with the aid of a smartphone -- Chipless RFID Tag Using Multiple G-Shaped Resonators -- Security Analysis of Ye et al. Authentication Protocol for Internet of Things.

This book reviews the state of the art of big data analysis and smart city. It includes issues which pertain to signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualisation, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. Papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular. The book appeals to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well as anyone interested in big data analysis and smart city.

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