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[null,"1.","Record Nr.",null,"UNINA9910793013503321"]
[null,null,"Titolo",null,"Atlas of cilia bioengineering and biocomputing / / edited by Richard Mayne"]
[null,null,"Pubbl/distr/stampa",null,"Gistrup, Denmark : , : River Publishers, , [2018]"]
[{"$nulls":4},"©2018"]
[null,null,"ISBN",null,"1-000-79640-X"]
[{"$nulls":4},"1-00-333728-7"]
[{"$nulls":4},"1-003-33728-7"]
[{"$nulls":4},"1-000-79287-0"]
[{"$nulls":4},"1-5231-3901-3"]
[{"$nulls":4},"87-7022-003-4"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (218 pages)"]
[null,null,"Collana",null,"River Publishers Series in Biomedical Engineering Series"]
[null,null,"Disciplina",null,"571.67"]
[null,null,"Soggetti",null,"Cilia and ciliary motion"]
[{"$nulls":4},"Bioengineering"]
[{"$nulls":4},"Biomimicry"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,"2.","Record Nr.",null,"UNINA9910254992003321"]
[null,null,"Titolo",null,"Data Stream Management : Processing High-Speed Data Streams / / edited by Minos Garofalakis, Johannes Gehrke, Rajeev Rastogi"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2016"]
[null,null,"ISBN",null,"3-540-28608-X"]
[null,null,"Edizione",null,"[1st ed. 2016.]"]
[null,null,"Descrizione fisica",null,"1 online resource (VII, 537 p. 103 illus., 16 illus. in color.)"]
[null,null,"Collana",null,"Data-Centric Systems and Applications, , 2197-9723"]
[null,null,"Disciplina",null,"006.7876"]
[null,null,"Soggetti",null,"Database management"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Data structures (Computer science)"]
[{"$nulls":4},"Information storage and retrieval"]
[{"$nulls":4},"Database Management"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Big Data/Analytics"]
[{"$nulls":4},"Data Structures"]
[{"$nulls":4},"Information Storage and Retrieval"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Part I: Introduction -- Part II: Computation of Basic Stream Synopses -- Part III: Mining Data Streams -- Part IV: Advanced Topics -- Part V: Systems and Architectures -- Part VI: Applications. ."]
[null,null,null,"Sommario/riassunto","We live in the era of “Big Data”: Petabytes of digital information are generated daily, and need to be processed and analyzed for interesting patterns and trends. Besides volume, a defining characteristic of Big Data is its velocity; that is, data is instantiated in the form of continuous, high-speed data streams that arrive at rapid rates, and need to be processed and analyzed on a continuous (24x7) basis. Such data streams pose very difficult challenges for conventional data-management architectures, which are built primarily on the concept of persistent, static data collections. This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities "]
[{"$nulls":4},"in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management. ."]