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

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.FeaturesPresents state-of-the-art research in big data and smart computingProvides a broad coverage of topics in data science and machine learningCombines computing methods with domain knowledge and a focus on applications in science, engineering, and businessCovers data security and privacy, including AI techniquesIncludes contributions from leading researchers

Foreword, ixAcknowledgement, xiEditors, xiiiList of Contributors, xvCHAPTER 1 ¦ Extreme Heterogeneity in Deep Learning Architectures 1JEFF ANDERSON, ARMIN MEHRABIAN, JIAXIN PENG, AND TAREK EL-GHAZAWICHAPTER 2 ¦ GPU PaaS Computation Model in Aneka CloudComputing Environments 19SHASHIKANT ILAGER, RAJEEV WANKAR, RAGHAVENDRA KUNE, AND RAJKUMAR BUYYACHAPTER 3 ¦ Toward Complex Search for Encrypted Mobile CloudData via Index Blind Storage 41YUPENG HU, LINJUN WU, WENJIA LI, KEQIN LI, YONGHE LIU, AND ZHENG QINCHAPTER 4 ¦ Encrypted Big Data Deduplication in Cloud Storage 63ZHENG YAN, XUEQIN LIANG, WENXIU DING, XIXUN YU, MINGJUN WANG, ANDROBERT H. DENGCHAPTER 5 ¦ The Role of NonSQL Databases in Big Data 93ANTONIO SARASA CABEZUELOCHAPTER 6 ¦ Prescriptive and Predictive Analytics Techniques forEnabling Cybersecurity 113NITIN SUKHIJA, SONNY SEVIN, ELIZABETH BAUTISTA, AND DAVID DAMPIERCHAPTER 7 ¦ Multivariate Projection Techniques to ReduceDimensionality in Large Datasets 133I. BARRANCO CHAMORRO, S. MUÑOZ-ARMAYONES, A. ROMERO-LOSADA,AND F. ROMERO-CAMPEROCHAPTER 8 ¦ Geo-Distributed Big Data Analytics Systems: AnOnline Learning Approach for Dynamic Deployment 161YIXIN BAO AND CHUAN WUCHAPTER 9 ¦ The Role of Smart Data in Inference of Human Behaviorand Interaction 191RUTE C. SOFIA, LILIANA CARVALHO, AND FRANCISCO M. PEREIRACHAPTER 10 ¦ Compression of Wearable Body Sensor Network Data 215ROBINSON RAJU, MELODY MOH, AND TENG-SHENG MOHCHAPTER 11 ¦ Population-Specific and Personalized (PSP) Models ofHuman Behavior for Leveraging Smart andConnected Data 243THEODORA CHASPARI, ADELA C. TIMMONS, AND GAYLA MARGOLINCHAPTER 12 ¦ Detecting Singular Data for Better Analysis ofEmotional Tweets 259KIICHI TAGO, KENICHI ITO, AND QUN JINCHAPTER 13 ¦ Smart Data Infrastructure for Respiratory HealthProtection of Citizens against PM2.5 in Urban Areas 273DANIEL DUNEA, STEFANIA IORDACHE, ALIN POHOATA, AND EMIL LUNGUCHAPTER 14 ¦ Fog-Assisted Cloud Platforms for Big Data Analytics inCyber Physical Systems: A Smart Grid Case Study 289MD. MUZAKKIR HUSSAIN, MOHAMMAD SAAD ALAM, AND M.M. SUFYAN BEGCHAPTER 15 ¦ When Big Data and Data Science Prefigured AmbientIntelligence 319CHRISTOPHE THOVEXCHAPTER 16 ¦ Ethical Issues and Considerations of Big Data 343EDWARD T. CHENCHAPTER 17 ¦ Data Protection by Design in Smart Data Environments 359PAOLO BALBONIINDEX, 391