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Understanding materials, their properties and behavior is fundamental to engineering design, and a key application of materials science. Written for all students of engineering, materials science and design, Materials Selection in Mechanical Design describes the procedures for material selection in mechanical design in order to ensure that the most suitable materials for a given application are identified from the full range of materials and section shapes available.

Extensively revised for this fourth edition, Materials Selection in Mechanical Design is recognized as one of the leading materials selection texts, and provides a unique and genuinely innovative resource.

Features new to this edition:

  • Material property charts now in full color throughout
  • Significant revisions of chapters on engineering materials, processes and process selection, and selection of material and shape while retaining the book's hallmark structure and subject content
  • Fully revised chapters on hybrid materials and materials and the environment
  • Appendix on data and information for engineering materials fully updated
  • Revised and expanded end-of-chapter exercises and additional worked examples

Materials are introduced through their properties; materials selection charts (also available on line) capture the important features of all materials, allowing rapid retrieval of information and application of selection techniques. Merit indices, combined with charts, allow optimization of the materials selection process. Sources of material property data are reviewed and approaches to their use are given. Material processing and its influence on the design are discussed. New chapters on environmental issues, industrial engineering and materials design are included, as are new worked examples, exercise materials and a separate, online Instructor's Manual. New case studies have been developed to further illustrate procedures and to add to the practical implementation of the text.

  • The new edition of the leading materials selection text, now with full color material property charts
  • Includes significant revisions of chapters on engineering materials, processes and process selection, and selection of material and shape while retaining the book's hallmark structure and subject content
  • Fully revised chapters on hybrid materials and materials and the environment
  • Appendix on data and information for engineering materials fully updated
  • Revised and expanded end-of-chapter exercises and additional worked examples
Computer Organization and Design, Fourth Edition, has been updated with new exercises and improvements throughout suggested by instructors teaching from the book.

It covers the revolutionary change from sequential to parallel computing, with a chapter on parallelism and sections in every chapter highlighting parallel hardware and software topics. It includes an appendix by the Chief Scientist and the Director of Architecture of NVIDIA covering the emergence and importance of the modern GPU, describing in detail for the first time the highly parallel, highly multithreaded multiprocessor optimized for visual computing. A companion CD provides a toolkit of simulators and compilers along with tutorials for using them, as well as advanced content for further study and a search utility for finding content on the CD and in the printed text. For the convenience of readers who have purchased an ebook edition or who may have misplaced the CD-ROM, all CD content is available as a download at bit.ly/nFXcLq.

This book is recommended for professional digital system designers, programmers, application developers, and system software developers; and undergraduate students in Computer Science, Computer Engineering and Electrical Engineering courses in Computer Organization, Computer Design, ranging from Sophomore required courses to Senior Electives.

  • This Revised Fourth Edition of Computer Organization and Design has been updated with new exercises and improvements throughout suggested by instructors teaching from the book
  • Covers the revolutionary change from sequential to parallel computing, with a chapter on parallelism and sections in every chapter highlighting parallel hardware and software topics
  • Includes an appendix by the Chief Scientist and the Director of Architecture of NVIDIA covering the emergence and importance of the modern GPU, describing in detail for the first time the highly parallel, highly multithreaded multiprocessor optimized for visual computing
Computer Architecture: A Quantitative Approach, Fifth Edition, explores the ways that software and technology in the cloud are accessed by digital media, such as cell phones, computers, tablets, and other mobile devices. The book, which became a part of Intel's 2012 recommended reading list for developers, covers the revolution of mobile computing. It also highlights the two most important factors in architecture today: parallelism and memory hierarchy.

This fully updated edition is comprised of six chapters that follow a consistent framework: explanation of the ideas in each chapter; a crosscutting issues section, which presents how the concepts covered in one chapter connect with those given in other chapters; a putting it all together section that links these concepts by discussing how they are applied in real machine; and detailed examples of misunderstandings and architectural traps commonly encountered by developers and architects. Formulas for energy, static and dynamic power, integrated circuit costs, reliability, and availability are included. The book also covers virtual machines, SRAM and DRAM technologies, and new material on Flash memory. Other topics include the exploitation of instruction-level parallelism in high-performance processors, superscalar execution, dynamic scheduling and multithreading, vector architectures, multicore processors, and warehouse-scale computers (WSCs). There are updated case studies and completely new exercises. Additional reference appendices are available online.

This book will be a valuable reference for computer architects, programmers, application developers, compiler and system software developers, computer system designers and application developers.

  • Part of Intel's 2012 Recommended Reading List for Developers
  • Updated to cover the mobile computing revolution
  • Emphasizes the two most important topics in architecture today: memory hierarchy and parallelism in all its forms.
  • Develops common themes throughout each chapter: power, performance, cost, dependability, protection, programming models, and emerging trends ("What's Next")
  • Includes three review appendices in the printed text. Additional reference appendices are available online.
  • Includes updated Case Studies and completely new exercises.
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and ‘rusty’ calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs.The textbook bridges the students from their undergraduate training into modern Bayesian methods.
  • Accessible, including the basics of essential concepts of probability and random sampling
  • Examples with R programming language and BUGS software
  • Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis).
  • Coverage of experiment planning
  • R and BUGS computer programming code on website
  • Exercises have explicit purposes and guidelines for accomplishment
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