This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    

    In this guide for students, each equation is the subject of an entire chapter, with detailed, plain-language explanations of the physical meaning of each symbol in the equation, for both the integral and differential forms. The final chapter shows how Maxwell's equations may be combined to produce the wave equation, the basis for the electromagnetic theory of light. This book is a wonderful resource for undergraduate and graduate courses in electromagnetism and electromagnetics. A website hosted by the author at www.cambridge.org/9780521701471 contains interactive solutions to every problem in the text as well as audio podcasts to walk students through each chapter.

    … The book the National Security Agency wanted never to be published." –Wired Magazine "…monumental… fascinating… comprehensive… the definitive work on cryptography for computer programmers…" –Dr. Dobb's Journal"…easily ranks as one of the most authoritative in its field." —PC Magazine"…the bible of code hackers." –The Millennium Whole Earth CatalogThis new edition of the cryptography classic provides you with a comprehensive survey of modern cryptography. The book details how programmers and electronic communications professionals can use cryptography—the technique of enciphering and deciphering messages-to maintain the privacy of computer data. It describes dozens of cryptography algorithms, gives practical advice on how to implement them into cryptographic software, and shows how they can be used to solve security problems. Covering the latest developments in practical cryptographic techniques, this new edition shows programmers who design computer applications, networks, and storage systems how they can build security into their software and systems. What's new in the Second Edition? * New information on the Clipper Chip, including ways to defeat the key escrow mechanism * New encryption algorithms, including algorithms from the former Soviet Union and South Africa, and the RC4 stream cipher * The latest protocols for digital signatures, authentication, secure elections, digital cash, and more * More detailed information on key management and cryptographic implementations

    This course is usually the first course taught at the undergraduate level. Marketers understand that even the best products and services will go unsold if they cannot communicate the value to the customer. Understanding this value-based approach is critical for marketing students today, and is at the forefront of this text, setting it apart. This approach is emphasized throughout the text, and demonstrated through the use of the Adding Value boxes found in each chapter. Presents a concise, impactful, and easy to read approach to Principles of Marketing. The text delivers value to both instructor and student through the engaging style and online assignment and assessment options. With monthly updates provided in a newsletter and the dynamic video program, the instructor support provided will bring marketing to life in any class setting.

    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.

    College Writing Skills With Reading features John Langan's clear writing style and his wide range of writing assignments and activities that effectively reinforce the four essentials of good writing: unity, support, coherence, and sentence skills. This alternate version provides 25 entertaining and informative essays by professional writers.

    Students will receive a grounding in areas that vary from treatment to organizational and community settings. This edition also includes of new case studies, practice examples and guiding principles.

    The 5th edition has been completely updated and includes a Companion CD-ROM that contains animations, NCLEX(R) examination-style review questions, printable IV therapy and medication safety checklists, drug calculation problems, and convenient electronic calculators.A separate drug calculations section - Medications and Calculations - features 65 pages of math review and step-by-step instructions for dosage calculations using the four primary methods - basic formula, ratio and proportion, dimensional analysis, and fractional equation. Nursing Process sections relate nursing care to drug therapy. Each step of the nursing process includes concise actions for the plan of care in relation to treatment for selected drug prototypes.A chapter on Principles of Drug Administration features comprehensive coverage of the procedures for administering drugs. It addresses all routes of administration and various settings.Unit openers for drug therapy chapters include an illustrated overview of normal anatomy and physiology, giving readers the foundation for understanding how the drug works in that body system.Herbal Alert boxes highlight various herbal products and their interactions with drugs.More than 100 detailed Prototype Drug Charts list the following information: dosage, indication, contraindication, drug-lab-food interactions, pharmacokinetics, pharmacodynamics, therapeutic effects, side effects, and adverse reactions.Highlighted Client Teaching, Cultural Considerations, and Herbal Alerts are included in the Nursing Process sections to emphasize key implications for nurses.Client Teaching in the nursing process sections guide readers through instructions for teaching patients about medication, self-administration, dietary concerns, and side effects.Includes a separate Transcultural and Genetic Considerations chapter.Critical Thinking Case Studies and Study Questions at the end of each chapter present readers with a clinical scenario and several questions that reinforce key concepts and encourage critical thinking.A new chapter on substance abuse addresses this important aspect of the nurse's role in pharmacology. Preventing Medication Errors boxes draw attention to important safety considerations and present guidelines from the Institute for Safe Medication Practice (ISMP).Critical Thinking Case Study boxes provide clinical scenarios and questions to sharpen analytical and critical thinking skills.Now includes step-by-step instructions for dosage calculations using dimensional analysis.Web sites, organizations, and research database information are available at the end of clinical chapters for further review and research.The newest JCAHO guidelines for medication safety are applied throughout the text and the abbreviations appendix has been revised to reflect these updates.Includes a new Herb/Drug Interaction chart, as well as new sugar-free and alcohol-free drug lists.Features updated coverage of pain as the fifth vital sign.Look-alike/sound-alike drugs are highlighted throughout to promote safe drug administration.Includes a list of the 200 most frequently prescribed drugs.Electronic Resources boxes at the beginning of each chapter direct readers to additional learning activities available on the Companion CD and the Evolve website.

    With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas

    The book s two-part coverage organizes topics under basic theory, and assembles an arsenal of approximation schemes with illustrative applications. For physicists and engineers. "

    He proposes his solution.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    These sections together make an appropriate one-term advanced/graduate level course (mathematical prerequisites: vector analysis and simple partial-differential equations). The book is printed to make it easy for readers to identify these sections.• The remaining Track 2 material provides a wealth of advanced topics instructors can draw from to flesh out a two-term course, with Track 1 sections serving as prerequisites.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates