You are the creator of your own reality! Are you ready to take control of your life? The Master Method will give you the tools you need to accomplish your goals, improve your relationships, enhance your health, and strengthen your mind and spirit. Seven-time World Champion Marco Sies has compiled the teachings and philosophies of ancient and modern masters into an easy-to-understand process that will guide you to the fulfilled life you've dreamed of. Sharing personal experiences of his extraordinary journey from the humblest of beginnings in Chile to world-class athlete, he has proven that no matter where you are in life, if you master your mind, you can shape your own destiny. Using the simple steps, concepts, exercises, and visualizations of The Master Method, you can finally take control of your life. So dream big"The Master Method will show you how to accomplish those dreams.
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.
Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Engineering, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. This book offers theoretical analysis techniques as well as algorithmic design patterns and experimental methods for the engineering of algorithms. Market: Computer Scientists; Programmers.
The classic and deeply influential work on business management, leadership, problem solving, and quality control—based on Denning’s famous 14 Points for Management. Now reissued for the managers and leaders of today! Translated into 12 languages and continuously in print since its original publication in 1982, this highly influential framework presents the foundations for a completely transformational way to lead and manage people, processes, and resources. According to Deming, American company management’s failure to plan for the future brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to: • Stay in business • Protect investment • Ensure future dividends • Provide more jobs through improved product and service In simple, direct language, Deming explains the principles of management transformation and how to apply them. This edition includes a foreword by Deming’s grandson, Kevin Edwards Cahill, and Kelly Allan, business consultant and Deming expert.
Computer science majors taking a non-programming-based course like discrete mathematics might ask 'Why do I need to learn this?' Written with these students in mind, this text introduces the mathematical foundations of computer science by providing a comprehensive treatment of standard technical topics while simultaneously illustrating some of the broad-ranging applications of that material throughout the field. Chapters on core topics from discrete structures – like logic, proofs, number theory, counting, probability, graphs – are augmented with around 60 'computer science connections' pages introducing their applications: for example, game trees (logic), triangulation of scenes in computer graphics (induction), the Enigma machine (counting), algorithmic bias (relations), differential privacy (probability), and paired kidney transplants (graphs). Pedagogical features include 'Why You Might Care' sections, quick-reference chapter guides and key terms and results summaries, problem-solving and writing tips, 'Taking it Further' asides with more technical details, and around 1700 exercises, 435 worked examples, and 480 figures.
Though your application serves its purpose, it might not be a high performer. Learn techniques to accurately predict code efficiency, easily dismiss inefficient solutions, and improve the performance of your application. Key Features Explains in detail different algorithms and data structures with sample problems and Java implementations where appropriate Includes interesting tips and tricks that enable you to efficiently use algorithms and data structures Covers over 20 topics using 15 practical activities and exercises Book Description Learning about data structures and algorithms gives you a better insight on how to solve common programming problems. Most of the problems faced everyday by programmers have been solved, tried, and tested. By knowing how these solutions work, you can ensure that you choose the right tool when you face these problems. This book teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications. What you will learn Understand some of the fundamental concepts behind key algorithms Express space and time complexities using Big O notation. Correctly implement classic sorting algorithms such as merge and quicksort Correctly implement basic and complex data structures Learn about different algorithm design paradigms, such as greedy, divide and conquer, and dynamic programming Apply powerful string matching techniques and optimize your application logic Master graph representations and learn about different graph algorithms Who this book is for If you want to better understand common data structures and algorithms by following code examples in Java and improve your application efficiency, then this is the book for you. It helps to have basic knowledge of Java, mathematics and object-oriented programming techniques.
The validation of analytical methods is based on the characterisation of a measurement procedure (selectivity, sensitivity, repeatability, reproducibility). This volume collects 31 outstanding papers on the topic, mostly published in the period 2000-2003 in the journal "Accreditation and Quality Assurance." They provide the latest understanding, and possibly the rationale why it is important to integrate the concept of validation into the standard procedures of every analytical laboratory. In addition, this anthology considers the benefits to both: the analytical laboratory and the user of the measurement results.
