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Smart Data: State-of-the-Art Perspectives in Computing and Applications: Chapman & Hall/CRC Big Data Series

Editat de Kuan-Ching Li, Beniamino Di Martino, Laurence T. Yang, Qingchen Zhang
en Limba Engleză Paperback – 30 sep 2020
Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more.


Features







  • Presents state-of-the-art research in big data and smart computing







  • Provides a broad coverage of topics in data science and machine learning







  • Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business







  • Covers data security and privacy, including AI techniques







  • Includes contributions from leading researchers


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Specificații

ISBN-13: 9780367656478
ISBN-10: 0367656477
Pagini: 428
Dimensiuni: 178 x 254 mm
Greutate: 0.75 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Big Data Series


Cuprins

Foreword, ix


Acknowledgement, xi


Editors, xiii


List of Contributors, xv


CHAPTER 1 ■ Extreme Heterogeneity in Deep Learning Architectures 1


JEFF ANDERSON, ARMIN MEHRABIAN, JIAXIN PENG, AND TAREK EL-GHAZAWI


CHAPTER 2 ■ GPU PaaS Computation Model in Aneka Cloud


Computing Environments 19


SHASHIKANT ILAGER, RAJEEV WANKAR, RAGHAVENDRA KUNE, AND RAJKUMAR BUYYA


CHAPTER 3 ■ Toward Complex Search for Encrypted Mobile Cloud


Data via Index Blind Storage 41


YUPENG HU, LINJUN WU, WENJIA LI, KEQIN LI, YONGHE LIU, AND ZHENG QIN


CHAPTER 4 ■ Encrypted Big Data Deduplication in Cloud Storage 63


ZHENG YAN, XUEQIN LIANG, WENXIU DING, XIXUN YU, MINGJUN WANG, AND


ROBERT H. DENG


CHAPTER 5 ■ The Role of NonSQL Databases in Big Data 93


ANTONIO SARASA CABEZUELO


CHAPTER 6 ■ Prescriptive and Predictive Analytics Techniques for


Enabling Cybersecurity 113


NITIN SUKHIJA, SONNY SEVIN, ELIZABETH BAUTISTA, AND DAVID DAMPIER


CHAPTER 7 ■ Multivariate Projection Techniques to Reduce


Dimensionality in Large Datasets 133


I. BARRANCO CHAMORRO, S. MUÑOZ-ARMAYONES, A. ROMERO-LOSADA,


AND F. ROMERO-CAMPERO


CHAPTER 8 ■ Geo-Distributed Big Data Analytics Systems: An


Online Learning Approach for Dynamic Deployment 161


YIXIN BAO AND CHUAN WU


CHAPTER 9 ■ The Role of Smart Data in Inference of Human Behavior


and Interaction 191


RUTE C. SOFIA, LILIANA CARVALHO, AND FRANCISCO M. PEREIRA


CHAPTER 10 ■ Compression of Wearable Body Sensor Network Data 215


ROBINSON RAJU, MELODY MOH, AND TENG-SHENG MOH


CHAPTER 11 ■ Population-Specific and Personalized (PSP) Models of


Human Behavior for Leveraging Smart and


Connected Data 243


THEODORA CHASPARI, ADELA C. TIMMONS, AND GAYLA MARGOLIN


CHAPTER 12 ■ Detecting Singular Data for Better Analysis of


Emotional Tweets 259


KIICHI TAGO, KENICHI ITO, AND QUN JIN


CHAPTER 13 ■ Smart Data Infrastructure for Respiratory Health


Protection of Citizens against PM2.5 in Urban Areas 273


DANIEL DUNEA, STEFANIA IORDACHE, ALIN POHOATA, AND EMIL LUNGU


CHAPTER 14 ■ Fog-Assisted Cloud Platforms for Big Data Analytics in


Cyber Physical Systems: A Smart Grid Case Study 289


MD. MUZAKKIR HUSSAIN, MOHAMMAD SAAD ALAM, AND M.M. SUFYAN BEG


CHAPTER 15 ■ When Big Data and Data Science Prefigured Ambient


Intelligence 319


CHRISTOPHE THOVEX


CHAPTER 16 ■ Ethical Issues and Considerations of Big Data 343


EDWARD T. CHEN


CHAPTER 17 ■ Data Protection by Design in Smart Data Environments 359


PAOLO BALBONI


INDEX, 391

Notă biografică

Kuan-Ching Li, Beniamino Di Martino, Laurence T. Yang, Qingchen Zhang

Recenzii

"The book is a great resource for all those interested in learning about the interplay between "smart data" and a number of research themes: algorithms, applications, ethical issues, security and data privacy, among many other topics. The book will be very useful for researchers, practitioners, and graduate students; a welcome addition to the Smart Data literature. The book is a milestone in this fast-moving field."
— Professor Albert Y. Zomaya, Sydney University, Australia
"This book provides a precious set of high-level research contributions for learning how to extract Smart Data from Big Data. Novel intelligent techniques, models, algorithms and applications are presented and discussed. Young researchers and professionals will benefit from the book contents to learn new topics and investigate new research issues. From infrastructure and algorithms to applications and ethics, Smart Data are illustrated and put in practice."
— Professor Domenico Talia, Università della Calabria, Italy

Descriere

This book explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories and data mining and machine learning techniques.