9783319764719 - Applications of Big Data Analytics: Trends, Issues, and Challenges (11 risultati)

XII, 214 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Condizione: New.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.Topics and features:Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicingExplores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plantsDescribes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenariosProposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disordersReviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree verticesPresents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessmentThis practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects.Dr. Mohammed M. Alaniis an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE.Dr. Hissam Tawfikis a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK.Dr. Mohammed Saeedis a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE.Dr. Obinna Anyais a Research Staff Member at IBM Research - Almaden, San Jose, CA, USA.

Hardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: new. Questo è un articolo print on demand.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.Topics and features:Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicingExplores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plantsDescribes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenariosProposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disordersReviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree verticesPresents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessmentThis practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects.Dr. Mohammed M. Alaniis an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE.Dr. Hissam Tawfikis a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK.Dr. Mohammed Saeedis a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE.Dr. Obinna Anyais a Research Staff Member at IBM Research - Almaden, San Jose, CA, USA. 228 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers a diverse selection of applications of big data Addresses the sensitive topic of big data collection and privacy Explores the future potential of big data, and how the world can benefit from the large amounts of data being collecte.

Condizione: New. Print on Demand.

Buch. Condizione: Neu. Applications of Big Data Analytics | Trends, Issues, and Challenges | Mohammed M. Alani (u. a.) | Buch | xii | Englisch | 2018 | Springer | EAN 9783319764719 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Condizione: New. PRINT ON DEMAND.

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.Topics and features:Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicingExplores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plantsDescribes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenariosProposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disordersReviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree verticesPresents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessmentThis practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch.