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  • Sách/Book

  • Statistical methods for survival data analysis

    • Authors: Elisa T. Lee (2013)

  • New content includes an introduction to left and interval censored data; the log-logistic distribution; estimation procedures for left and interval censored data; parametric methods iwth covariates; Cox's proportional hazards model (including stratification and time-dependent covariates); and multiple responses to the logistic regression model. Coverage of graphical methods has been deleted. Large data sets are provided on an FTP site for readers' convenience. Bibliographic remarks conclude each chapter.
  • Sách/Book

  • The ComSoc guide to managing telecommunications projects

    • Authors: Celia Desmond (2010)

  • This book provides an overview of the telecommunications environment as it has evolved over the past few years, illustrating the need for project management, the significance of project success to the companies, and the application of key project management processes within the telecom environment. Topics covered include: scope management, time management, cost management, procurement management, risk management, communications, quality, human resources, and Integration. It offers professionals a brief and accessible guide to managing telecommunication projects in the 21st century
  • Sách/Book

  • Generalized network design problems : modeling and optimization

    • Authors: Petrică C. Pop (2012)

  • Generalized network design is a very hot topic of research. The monograph describes in a unified manner a series of mathematical models, methods, propositions, and algorithms developed in the last years on generalized network design problems. The book consists of seven chapters, where in addition to an introductory chapter, a number of six generalized network design problems are formulated and examined. The book will be useful for researchers and graduate students interested in operations research, optimization, applied mathematics, and computer science. Due to the substantial practical importance of some presented problems, researchers in other areas will also find it useful.
  • Sách/Book

  • Parallel programming : techniques and applications using networked workstations and parallel computers

    • 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

  • Tài liệu công tác xã hội trong bệnh viện

    • Authors: Phạm Tiến Nam (2019)

  • Trình bày khái quát về công tác xã hội trong bệnh viện; một số phương pháp can thiệp của công tác xã hội trong bệnh viện; một số kỹ năng của người làm công tác xã hội trong bệnh viện; quy trình thực hành của công tác xã hội trong bệnh viện
  • Sách/Book

  • Network routing : algorithms, protocols, and architectures

    • 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.
  • Book

  • The Data Science Design Manual

    • Authors: Steven S. Skiena (2017)

  • The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an "Introduction to Data Science" course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well.