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  • Sách/Book


  • Authors: Barry Wilkinson (2005)

  • The book covers the timely topic of cluster programming, interesting to many programmers due to the recent availability of low-cost computers. Uses MPI pseudocodes to describe algorithms and allows different programming tools to be implemented, and provides readers with thorough coverage of shared memory programming, including Pthreads and OpenMP. Useful as a professional reference for programmers and system administrators.

  • Sách/Book


  • Authors: Deepankar Medhi (2007)

  • Network routing can be broadly categorized into Internet routing, PSTN routing, and telecommunication transport network routing. This book systematically considers these routing paradigms, as well as their interoperability. The authors discuss how algorithms, protocols, analysis, and operational deployment impact these approaches. A unique feature of the book is consideration of both macro-state and micro-state in routing; that is, how routing is accomplished at the level of networks and how routers or switches are designed to enable efficient routing.

  • Sách/Book


  • Authors: David L. Olson (2008)

  • This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.

  • Sách/Book


  • Authors: Celia L. Desmond (2004)

  • This concise reference covers important aspects of project management. It explains many key concepts in layman's terms, provides tools for planning, organizing, tracking and managing projects and gives examples of various telecommunications projects from wireline and wireless providers, equipment vendors and component manufacturers

  • Sách/Book


  • Authors: Vladimir Cherkassky (2007)

  • An interdisciplinary framework for learning methodologies-covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied-showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.