In this title, the treatment is made easy-to-follow by giving step-by-step derivations, explanations and by avoiding advanced mathematics unfamiliar to students. It covers: math and physics thorough review sections; and worked examples, followed by a practice exercise.

    If you're a reasonably proficient programmer who can think logically, you have all the background you'll need. Stepanov and Rose introduce the relevant abstract algebra and number theory with exceptional clarity. They carefully explain the problems mathematicians first needed to solve, and then show how these mathematical solutions translate to generic programming and the creation of more effective and elegant code. To demonstrate the crucial role these mathematical principles play in many modern applications, the authors show how to use these results and generalized algorithms to implement a real-world public-key cryptosystem. As you read this book, you'll master the thought processes necessary for effective programming and learn how to generalize narrowly conceived algorithms to widen their usefulness without losing efficiency. You'll also gain deep insight into the value of mathematics to programming--insight that will prove invaluable no matter what programming languages and paradigms you use. You will learn aboutHow to generalize a four thousand-year-old algorithm, demonstrating indispensable lessons about clarity and efficiencyAncient paradoxes, beautiful theorems, and the productive tension between continuous and discreteA simple algorithm for finding greatest common divisor (GCD) and modern abstractions that build on itPowerful mathematical approaches to abstractionHow abstract algebra provides the idea at the heart of generic programmingAxioms, proofs, theories, and models: using mathematical techniques to organize knowledge about your algorithms and data structuresSurprising subtleties of simple programming tasks and what you can learn from themHow practical implementations can exploit theoretical knowledge

    It has been developed in response to the need for a text that supports the mastery of this difficult subject. Therefore, in addition to presenting electromagnetics in a concise and logical manner, the text includes end-of-section review questions, worked examples, boxed remarks that alert students to key ideas and tricky points, margin notes, and point-by-point chapter summaries. Examples and applications invite students to solve problems and build their knowledge of electromagnetics. Application topics include: electric motors, transmission lines, waveguides, antenna arrays and radar systems.

    This title can help you understand why financial markets exist, how financial institutions serve those markets, and the various services those institutions offer.

    From students with disabilities, culturally diverse students, and students with limited English proficiency to economically disadvantaged students this text provides teachers with the tools they need in their diverse classrooms. Revised to reflect the most current research, terminology and teaching practices, the strength of this text continues to be its numerous learning activities and sample lessons addressing both elementary and secondary classrooms. This edition continues its very popular multi- chapter unit on curriculum adaptations with specific strategies and activities for teaching reading, writing, and mathematics. With a new chapter on Response to Intervention and Progress Monitoring and full integration of the RTI framework, and the increase emphasis on middle and secondary students, this text continues its reign as an outstanding resource for all general education teachers. 0131381253 / 9780131381254 Teaching Students Who are Exceptional, Diverse, and at Risk in the General Education Classroom (with MyEducationLab) Package consists of 0135140870 / 9780135140871 MyEducationLab -- Access Card 0137151799 / 9780137151790 Teaching Students Who are Exceptional, Diverse, and at Risk in the General Education Classroom

    And oh the black dress, the black heels and the push up bra--just in case!" What would you do if your sleazy boss ran his hands all over you and then blamed you for not doing your job well? Well, I just packed off on a road trip! Just me in my old jeep, Iqbal Mastani, we travelled all the way from Delhi to this little guest house up in the mountains. I met people I had never known (cute boys who taught me to fish), did things I would have never done (sleeping drunk in a cold balcony) and somewhere in the middle of that, fell in love! Lanka in all its diversity.

    Mastering Algorithms with C offers you a unique combination of theoretical background and working code. With robust solutions for everyday programming tasks, this book avoids the abstract style of most classic data structures and algorithms texts, but still provides all of the information you need to understand the purpose and use of common programming techniques.Implementations, as well as interesting, real-world examples of each data structure and algorithm, are included.Using both a programming style and a writing style that are exceptionally clean, Kyle Loudon shows you how to use such essential data structures as lists, stacks, queues, sets, trees, heaps, priority queues, and graphs. He explains how to use algorithms for sorting, searching, numerical analysis, data compression, data encryption, common graph problems, and computational geometry. And he describes the relative efficiency of all implementations. The compression and encryption chapters not only give you working code for reasonably efficient solutions, they offer explanations of concepts in an approachable manner for people who never have had the time or expertise to study them in depth.Anyone with a basic understanding of the C language can use this book. In order to provide maintainable and extendible code, an extra level of abstraction (such as pointers to functions) is used in examples where appropriate. Understanding that these techniques may be unfamiliar to some programmers, Loudon explains them clearly in the introductory chapters.Contents include:PointersRecursionAnalysis of algorithmsData structures (lists, stacks, queues, sets, hash tables, trees, heaps, priority queues, graphs)Sorting and searchingNumerical methodsData compressionData encryptionGraph algorithmsGeometric algorithms

    Kettl and Fesler understand that the push and pull of political forces make the functions of bureaucracy ever more contentious, but no less crucial to governance.Based on reviewer feedback, and given advances in scholarship and in practice, the authors introduce the crucial topics of ethics, accountability, and leadership early on, utilizing these central ideas as touchstones throughout the book. While this text continues to focus on the core components of public administration--such as budgeting, personnel, and implementation--it's been thoroughly updated to cover recent developments, including administrative issues spotlighted during the 2008 presidential campaigns, the use of technology in government management, and the changing face of the federal workforce. Fully updated tables and figures feature a wealth of current data, and photos add visual context to the book's core concepts.What was an appendix showcasing fourteen case studies in the previous edition is now a set of fully-integrated case studies--one in each chapter--that challenges students to apply ideas and analysis as they go. Each case emphasizes the people on the front lines at the local, state, and federal levels with topics ranging from Taser use in law enforcement to the recent economic bailout. Useful discussion questions at the end of each case help shape student responses and in-class conversation.

    Designed for two-semester, beginning graduate courses in Mathematical Statistics, and for senior undergraduate Mathematics, Statistics, and Actuarial Science majors, this text retains its ongoing features and continues to provide students with background material.

    R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http: //www.imperial.ac.uk/bio/research/crawl... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

    It presents the mathematical foundations of computer graphics with a focus on geometric intuition, allowing the programmer to understand and apply those foundations to the development of efficient code. - The fundamental mathematics used in graphics programs - The basics of the graphics pipeline - BSP trees - Ray tracing - Surface shading - Texture mapping Advanced topics include: - Curves and surfaces - Color science - Global illumination - Reflection models - Image-based rendering - Visualization Extensive exercises and references for further reading enhance each chapter. An introduction for novices---a refresher for professionals.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

    However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques that allow programmers to develop their own functional data structures. The author includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs are easily adaptable to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

    In our modern world, we see people struggling with depression, anxiety, anger, etc. Psychologist and counselors have been using Cognitive Behavioral Therapy to solve all these struggles. A Practical Guide to CBT and Modern Psychology will allow anyone to use CBT in their lives. It doesn't matter whether or not you have a background in Psychology. In this comprehensive guide you will learn all the fundamentals used in CBT by therapists. Inside you will be exposed to the following: CBT History Techniques When and How to use CBT Examples Methods to help others with psychological struggles And much more If you're ready to understand and use the powerful techniques of Cognitive Behavioral Therapy, then this is an excellent guide.