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  • Smart Data: State-of-the-Art Perspectives in Computing and Applications

    Smart Data by Li, Kuan-Ching; Di Martino, Beniamino; Yang, Laurence T.;

    State-of-the-Art Perspectives in Computing and Applications

    Sorozatcím: Chapman & Hall/CRC Big Data Series;

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    Rövid leírás:

    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.

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    Hosszú leírás:

    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




    "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

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    Tartalomjegyzék:

    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

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