Untitled - PHI Learning

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BIOLOGY .............................................................................................. 3

BUSINESS & MANAGEMENT .................................................................... 6

Accounting/Finance ....................................................................... 6

Advertising/Media Studies .............................................................. 9

Production/Quantitative Methods ...................................................11

Strategic Management ...................................................................12

COMPUTERS AND INFORMATION PROCESSING ..........................................13

ECONOMICS .........................................................................................45

ENGINEERING ......................................................................................61

Electronics and Electrical ..............................................................61

Mechanical ..................................................................................65

Production ...................................................................................70

ENVIRONMENT/ENERGY STUDIES ............................................................72

JOURNALISM/LANGUAGE/LINGUISTICS ...................................................73

MATHEMATICS/STATISTICS ....................................................................78

MEDICINE ...........................................................................................81

PHILOSOPHY .......................................................................................82

PHYSICS .............................................................................................83

PROFESSIONAL TITLE ...........................................................................84

PSYCHOLOGY .......................................................................................85

AUTHORWISE ALPHABETICAL LISTING ....................................................89

CONTENTS

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Computational Molecular Biology is an emerging discipline which is increasingly engaging the attention of computer scientists, mathematicians, and biologists.

This text covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and biotechnology. The book has substantial “computational biology without formulas” component that gives biological motivation and computational ideas in a simple way. This simplified presentation of biology and computing aims to make the book accessible to computer scientists entering this new area and to biologists who do not have sufficient background for more involved computational techniques. Every chapter has an introductory section that describes both computational and biological ideas without any formulas.

The book concentrates on computational ideas rather than details of the algorithms and makes special efforts to present these ideas in an easy-to-understand manner.

KEY FEATURES

• The text covers new ideas—for example, Computational Proteomics, Genome Rearrangements, Sequence Comparison and DNA Arrays—as well as old ideas, for instance, Restriction Mapping, to show that a synthesis of both is necessary for a holistic understanding of the subject.

• The last section in each chapter briefly describes the important recent developments that are outside the body of the chapter.

• Large number of diagrams are provided to illustrate the concepts.

• One chapter is exclusively devoted to Problems.

• The exhaustive Bibliography would fuel further research into the subject.

This up-to-date and well-researched study would prove to be extremely useful to students of molecular biology, bioinformatics, computer science, and mathematics. Besides, professionals in the field should value it for the new insights it provides into the subject.

CONTENTS: Preface. Computational Gene Hunting. Restriction Mapping. Map Assembly. Sequencing. DNA Arrays. Sequence Comparison. Multiple Alignment. Finding Signals in DNA. Gene Prediction. Genome Rearrangements. Computational Proteomics. Problems. All You Need to Know about Molecular Biology. Bibliography. Index.

COMPUTATIONAL MOLECULAR BIOLOGY An Algorithmic Approach

PAVEL A. PEVZNER, Professor, Departments of Mathematics, Computer Science, and Biological Sciences, University of Southern California.

332 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-2550-8 / ` 350.00

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The Genetics of Cognitive Neuroscience aims to give the reader a working understanding of the influence of specific genetics variants on cognition, affective regulation, personality, and central nervous system disorders.

It has been known that the aspects of behavior runs in families; studies shows that characteristics related to cognition, temperament, and all major psychiatric disorders are heritable.

The book offers a primer on understanding the genetics mechanisms of such inherited traits.

The chapters emphasize fundamental issues regarding the design of experiments, the use of bioinformatics tools, the integration of data from different levels of analysis and the validity of finding, arguing that association between genes and cognitive processes must be replicable and placed in a neurobiological context for validation.

CONTENTS: Preface. Introduction. I: Methodologies for Genetic Association Studies of Cognition— Molecular Genetics and Bioinformatics: An Outline for Neuropsychological Genetics—Lucas Kempf and Daniel R. Weinberger. Statistical Methods in Neuropsychiatric Genetics—Kristin K. Nicodemus and Fengyu Zhang. Animal Models of Genetic Effects on Cognition—Francesco Papaleo, Daniel R. Weinberger, and Jingshan Chen. II: Genetic Approaches to Individual Differences in Cognition and Affective Regulation—The Genetics of Intelligence Danielle Posthuma—Eco J.C. de Geus, and Ian J. Deary. Candidate Genes Associated with Attention and Cognitive Control—John Fossella, Jin Fan, and Michael I. Posner. Genetics of Corticolimbic Function and Emotional Reactivity—Ahmad R. Hariri, Erika E. Forbes, and Kristin L. Bigos. Genes Associated with Individual Differences in Cognitive Aging— Terry E. Goldberg and Venkata S. Mattay. III: Genetic Studies of Cognition and Treatment Response in Neuropsychiatric Disease—Genetics of Dyslexia: Cognitive Analysis, Candidate Genes, Comorbidities, and Etiologic Interactions—Bruce F. Pennington, Lauren M. McGrath, and Shelley D. Smith. Cognitive Intermediate Phenotypes in Schizophrenia Genetics—Gary Donohoe, Terry E. Goldberg, and Aiden Corvin. The Genetic Basis for the Cognitive Deterioration of Alzheimer’s Disease—John M. Ringman and Jeffrey L. Cummings. Pharmacogenetic Approaches to Neurocognition in Schizophrenia— Katherine E. Burdick and Anil K. Malhotra. Contributors. Index.

GENETICS OF COGNITIVE NEUROSCIENCE, THE

Edited by:

TERRY E. GOLDBERG is Professor of Psychiatry and Behavioral Sciences at Albert Einstein College of Medicine and Director of Neurocognitive Research at the Zucker Hillside Hospital’s Psychiatry Research Division and the Litwin Zucker Alzheimer’s Research Center at the Long Island Medical Center in Manhasset, New York.DANIEL R. WEINBERGER is Chief of the Clinical Brain Disorders Branch and Director of Genes, Cognition, and Psychosis Program at the National Institute of Mental Health of the National Institutes of Health in Bethesda, Maryland.

312 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4299-6 / ` 295.00

BIOLOGY

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Becoming conversant with the intricacies of molecular biology and its extensive technical vocabulary can be a challenge, though, as introductory materials often seem more like a barrier than an invitation to the study of life. This text offers a concise and accessible introduction to molecular biology, requiring no previous background in science; it covers the basics in all aspects of molecular biology, from biochemistry and evolution to molecular medicine and biotechnology.

A reader who has mastered the information in The Processes of Life is ready to move on to more complex material in almost any area of contemporary biology.

The Processes of Life is an excellent introduction to molecular biology… . By deconstructing an exceedingly complicated body of information into a set of core principles, Hunter provides the reader with a framework for grasping the strengths and challenges of modern biology... this book’s clarity and frankness make it an invaluable resource for any person, from any profession, seeking an introduction to molecular biology.

—Andrea L. Suárez

Larry Hunter has once again taken a complicated field and reduced it to a set of key principles and associated examples. His writing style mirrors his personality—enthusiastic, frank, and to the point. This book is a great way for those with a technical background to get up to speed on modern biology and the wealth of challenges it provides.

—Russ B. Altman

CONTENTS: Preface. In the Beginning... Evolution. A Little Bit of Chemistry. The Structure and Function of Bacteria. Biological Macromolecules. Eukaryotes. Multicellular Organisms and Development. Anatomy, Physiology, and Systems Biology. Disease and Its Treatment. Molecular Biotechnology. Molecular Bioethics. Glossary. Index.

PROCESSES OF LIFE, THE An Introduction to Molecular Biology

LAWRENCE E. HUNTER is a Director of Computational Bioscience Program and of the Center for Computational Pharmacology at the University of Colorado School of Medicine.

316 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4078-7 / ` 350.00

BIOLOGY

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This book presents a variety of computational methods used to solve dynamic problems in economics and finance. It emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses. The examples are drawn from a wide range of subspecialties of economics and finance, with particular emphasis on problems in agricultural and resource economics, macroeconomics, and finance.

The book is divided into two parts. The first part develops basic numerical methods, including linear and nonlinear equation methods, complementarity methods, finite-dimensional optimization, numerical integration and differentiation, and function approximation. The second part presents methods for solving dynamic stochastic models in economics and finance, including dynamic programming, rational expectations, and arbitrage pricing models in discrete and continuous time. The book uses matlab to illustrate the algorithms and includes a utilities toolbox to help readers develop their own computational economics applications.

One of this book’s many strengths is its structure, the way theory-based chapters alternate with analytical ones. This will make it an invaluable resource in the classroom.

—Thomas J. Sargent, Department of Economics, New York University, and Hoover Institution, Stanford University

This book ties together numerical methods with state-of-the-art mathematical tools in a user-friendly way. It should be part of the program in ‘math camps’ for incoming graduate students in economics and finance. The matlab programs are a very useful resource for anyone doing applied research.

—Paul D. McNelis, Professor of Economics, Georgetown University

CONTENTS: Preface. Introduction. Linear Equations and Computer Basics. Nonlinear Equations and Complementarity Problems. Finite-Dimensional Optimization. Numerical Integration and Differentiation. Function Approximation. Discrete Time, Discrete State Dynamic Models. Discrete Time, Continuous State Dynamic Models: Theory and Examples. Discrete Time, Continuous State Dynamic Models: Methods. Continuous Time Models: Theory and Examples. Continuous Time Models: Solution Methods. Appendix A: Mathematical Background. Appendix B: A Matlab Primer. References. Index.

APPLIED COMPUTATIONAL ECONOMICS AND FINANCE

MARIO J. MIRANDA is Professor and Chair of Graduate Studies, Department of Agricultural, Environmental, and Development Economics, Ohio State University.PAUL L. FACKLER is Associate Professor, Department of Agricultural and Resource Economics, North Carolina State University.

528 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3934-7 / ` 495.00

BUSINESS & MANAGEMENT Accounting/Finance

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This text makes available the most important methodological advances in bond evaluation from the past twenty years. With uncommon precision and a strong emphasis on the underlying economic fundamentals, it presents a unified framework for understanding the basic tools of bond evaluation, including duration, convexity, and immunization.

The most valuable feature of the book is a general immunization theorem that can be used by practitioners to protect investors against any change in the structure of spot interest rates. Also of note is the detailed presentation of the Heath-Jarrow-Morton model and a discussion of its relationships with classical immunization schemes.

Each chapter is followed by a series of questions, problem sets, and projects; detailed solutions to all of them appear at the end of the book.

Bonds are mathematical securities, and Olivier de La Grandville gives us the economics, the theory, the math, the intuition, and the numerical examples in this wonderfully thorough book.

—Roger Ibbotson, Yale School of Management

The book can be described as a ‘dream’ toolbox for any bond portfolio analyst.

—Milad Zarin, University of Neuchâtel

CONTENTS: Introduction. A First Visit to Interest Rates and Bonds. An Arbitrage-Enforced Valuation of Bonds. The Various Concepts of Rates of Return on Bonds: Yield to Maturity and Horizon Rate of Return. Duration: Definition, Main Properties, and Uses. Duration at Work: The Relative Bias in the T-Bond Futures Conversion Factor. Immunization: A First Approach. Convexity: Definition, Main Properties, and Uses. The Importance of Convexity in Bond Management. The Yield Curve and the Term Structure of Interest Rates. Immunizing Bond Portfolios Against Parallel Moves of the Spot Rate Structure. Continuous Spot and Forward Rates of Return, with Two Important Applications. Two Important Applications. Estimating the Long-Term Expected Rate of Return, Its Variance, and Its Probability Distribution. Introducing the Concept of Directional Duration. A General Immunization Theorem, and Applications. Arbitrage Pricing in Discrete and Continuous Time. The Heath-Jarrow-Morton Model of Forward Interest Rates, Bond Prices, and Derivatives. The Heath-Jarrow-Morton Model at Work: Applications to Bond Immunization. By Way of Conclusion: Some Further Steps. Answers to Questions. Further Reading. References. Index.

BOND PRICING AND PORTFOLIO ANALYSIS Protecting Investors in the Long Run

OLIVIER de La GRANDVILLE, Professor of Economics, University of Geneva and Visiting Professor, Department of Management Science and Engineering, Stanford University.

476 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-2888-4 / ` 395.00


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Portfolio management is a tough business. Each day, managers face the challenges of an ever-changing and unforgiving market, where strategies and processes that worked yesterday may not work today, or tomorrow. The usual advice for improving portfolio performance—refining your strategy, staying within your style, doing better research, trading more efficiently—is important, but doesn’t seem to affect outcomes sufficiently.

This book, by an experienced advisor to institutional money managers, goes beyond conventional thinking to offer a new analytic framework that enables investors to improve their performance confidently, deliberately, and simply, by applying the principles of behavioral finance. It offers a conceptually straightforward and well-tested framework that measures key inputs in active portfolio management to management success like skills, process, and behavioral tendencies with evidence of how it helps managers enhance self-awareness and become better investors. In a series of short, accessible chapters, the author investigates a range of topics from psychology and neuroscience, describing their relevance to the challenges of portfolio management. Finally, the book offers seven ideas for improving investment performance as given below.

• Embracing the Scientific Method • Maintaining a Diary • Accounting for Skill • Learning about Buying Skill • Measuring Your Sell Effectiveness • Calibrating Sizing• Using Checklists

The Disciplined Trader meets Moneyball. This book is a worthwhile read for any portfolio manager, analyst, or trader focused on continual improvement and even greater success.

—Warren Touwen, Core Product, Bloomberg

For fund managers seeking to improve their investing skills there are many publications offering tantalizing but fragmented paths for progress. In this book Michael Ervolini brings together topics such as fast and slow thinking, checklists, and self-awareness to construct coherent and pragmatic solutions. Using the principles of the scientific method he shows how a successful investment process can evolve through time, improving the consistency of decision making and keeping investing skills relevant in an ever-changing world.

—Simon Savage, Asset Manager, GLG Partners

Michael Ervolini is a clever man in touch with reality. Recognizing that portfolio management is a tough, challenging business full of conflicts, he gets it that rationality is easy to talk about but difficult to implement. It requires recognition of deep uncertainty and the human resource that is emotion. Since passive investing puts you at the mercy of the market, active portfolio management has to be made to work. It can be, Ervolini says, if there is proper feedback. It requires a willingness to be curious about what we do and to create ways to learn from experience. This is what he does in this book. Read it!

—David Tuckett, Director, Centre for the Study of Decision-Making Uncertainty, University College, London

CONTENTS: Foreword by Terrance Odean. Preface. Acknowledgments. Introduction. Part One: Game Change—Industry Challenges. Why Johnny Can’t Improve. New Analytic Framework. Process and Behaviors. Feedback in Action. Phantastic Risks. Part Two: Behavioral Matters—What Drives Selling? Sell the Way You Buy—Strategically. Bearing Up in a Bear Market. Aching Conviction. Unconscious Deliberation. Investing in Self-Awareness. Stressing Performance. Thesis, Narrative, or Just Another Disappointing Story. Dreaming of Alpha. Motivated Reasoning. Regrettable Choices. Endowing Success. Counterfactual Investing. Great Investing is Not Natural. Inside-Out Investing. Beware Phantastic Investments. Thanks for the Memories. Skills, Process, and Behaviors. Processing Success. Primed for Success. Fear, Anger, and Risk. Successful Choices. Changing for the Better. Portfolio Thinking. Promiscuous Thinking. Getting in the Flow. Believing is Seeing. A Storied Portfolio. The Trouble with Improving. Tired Investing. That Winning Feeling. Hold That Thought. Overcoming Overconfidence. The Power of Vulnerability. Part Three: Improving Right Away—Project 1: Embracing the Scientific Method. Project 2: Maintaining a Diary. Project 3: Accounting for Skill. Project 4: Learning about Buying Skill. Project 5: Measuring Your Sell Effectiveness. Project 6: Calibrating Sizing. Project 7: Checklists. Epilogue. Glossary.

MANAGING EQUITY PORTFOLIOS A Behavioral Approach to Improving Skills and Investment Processes

MICHAEL A. ERVOLINI, CEO of Cabot Research, a global software company that provides innovative analytics to money managers to help them improve portfolio performance.

300 pp. (Hard Cover) / 16.0 × 24.1 cm / ISBN-978-81-203-5217-9 / ` 495.00


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Digital media offers an always-accessible, apparently inexhaustible supply of entertainment and information with feature films, television shows, homemade videos, tweets, blogs, and breaking news. Though choices seem endless, public attention is limited.

This book explains how audiences take shape in the digital age and how digital media finds the audiences they need in an era of infinite choice? The author does this by describing the factors that create audiences, including the preferences and habits of media users, the role of social networks, the resources and strategies of media providers, and the growing impact of media measures—from ratings to user recommendations. He incorporates these factors into one comprehensive framework and calls it the marketplace of attention.

The book will be useful for students of management, media studies and professionals alike.

Scholarly discussion of audiences are a fragmented as the readers and viewers they analyze. Theories of selective exposure, bubbles, preference formation, rational ignorance, uses and gratification, scheduling patterns, and counter-programming all vie for attention. This book skillfully draws these theories and evidence together to answer a simple but vexing questions: how much do we know about how audiences are generated, and what does that imply about the marketplace of ideas?

—James T. Hamilton, Hearst Professor of Communication, Stanford University

An engaging, coolheaded look at the changing media landscape There have been many breathless accounts of how new media might be changing the world, predicting we are on the verge of either utopia or disaster. Webster pulls together hard evidence and frontier research to tell us what actually is happening, cutting through the hyperbole and offering a balanced account of where we have been and where we are going.

—Matthew Gentzkow, Richard O. Ryal Professor of Economics, University of Chicago Booth School of Business

CONTENTS: Preface. The Marketplace of Attention—Digital Media. Attention. The Marketplace. Audiences. In the Balance. Media Users—Ways of Seeing. Media Choice. The User’s Dilemma. The Role of Social Networks. Going Viral. The Structures of Everyday Life. The Puzzle of Preferences. The Media—The Attention Economy. Making Media. Making Audiences. Desperately Seeking Attention. Media Measures—The Rise of Media Measures. Making Measures. Bias in Measurement. Seeking the World through “Big Data’. Audience Formations—Audience Fragmentation. Preference-Driven Loyalties. Structure-Driven Loyalties. Local News and Information. Massively Overlapping Culture. Constructing the Marketplace of Attention—Structuration. The Dimensions of Structure. A Map of Media Structures. The Interaction of Structure and Agency. Structuring Preferences. The Swing Vote. Public Attention in the Marketplace of Ideas—The Marketplace of Ideas. Stories of Hope and Despair. Questioning Our Assumptions. The Shape of Things to Come. Notes. Bibliography. Index.

MARKETPLACE OF ATTENTION, THE How Audiences Take Shape in a Digital Age

JAMES G. WEBSTER, Professor, School of Communication, Northwestern University, Illinois, USA.

280 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-5187-5 / ` 695.00

BUSINESS & MANAGEMENT Advertising/Media Studies

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Big Data is made up of lots of little data: numbers entered into cell phones, addresses entered into GPS devices, visits to websites, online purchases, ATM transactions, and any other activity that leaves a digital trail. This book on Big Data cuts through the hype to explore the potential of Big Data. It shows the ways in which the analysis of Big Data can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy.

The authors describe Reality Mining at five different levels: the individual, the neighbourhood and organization, the city, the nation and the world. For each level, they first offer a non-technical explanation of data collection methods and then describe applications and systems that have been or could be built. Thus, making it understandable to everyone. Some examples are a mobile app that helps smokers quit smoking; a workplace “knowledge system”; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and analysis of social media to track the spread of disease. Their argument being how Big Data, used respectfully and responsibly, can help people live better, healthier, and happier lives.

The book will be useful for students of management, computer science, media studies and professionals as well.

We look at digital devices as things that are meant to serve us. In Reality Mining we are taken on a journey from individuals to countries, to illustrate the true transformative power that the collective use of these digital devices brings to humanity. A fascinating trip guided by researchers who have successfully bridged discovery with entrepreneurship!

—Albert-Laszló Barabasi, Robert Gray Doge Professor of Network Science, Northeastern University; author of Linked

A smart look at how Big Data transforms our lives, from the microcosm of the individual to the macrocosm of the planet. Eagle’s pioneering research in data-mining human behavior is inspiring, while Greene’s insights on what it all means make Reality Mining an indispensable book. And importantly, privacy issues are not an after-thought but are interlaced throughout. as it should be.

—Kenneth Cukier, Coauthor of Big Data: A Revolution That Will Transform How We Live, Work, and Think

CONTENTS: Introduction. I: The Individual (One Person)—Mobile Phones, Sensors, and Lifelogging: Collecting Data from Individuals While Considering Privacy. Using Personal Data in a Privacy-Sensitive Way to Make a Person’s Life Easier and Healthier. II: The Neighborhood and the Organization (10 to 1,000 People)— Gathering Data from Small Heterogeneous Groups. Engineering and Policy: Building more Efficient Businesses, Enabling Hyperlocal Politics, Life Queries, and Opportunity Searches. III: The City (1,000 to 1,000,000 People)—Traffic Data, Crime Stats, and Closed-Circuit Cameras: Accumulating Urban Analytics. Engineering and Policy: Optimizing Resource Allocation. IV: The National (1 Million to 100 Million People)—Taking the Pulse of a Nation: Census, Mobile Phones, and Internet Giants. Engineering and Policy Addressing National Sentiment, Economic Deficits, and Disasters. V: Reality Mining the World’s Data (100 Million 7 Billion People)—Gathering the World’s Data: Global Census, International Travel and Commerce, and Planetary-Scale Communication. Engineering a Safer and Healthier Word. Conclusion. Notes. Index.

REALITY MINING Using Big Data to Engineer: A Better WorldNATHAN EAGLE, one of the “50 people who will change the world” on the 2012 Wired Smart List, is the co-founder and CEO of Jana, a company that helps global brands reach customers in emerging markets via mobile airtime. He holds faculty positions at Harvard and Northeastern University.

KATE GREENE is a freelance science and technology journalist based in San Francisco whose work has appeared in The Economist, Discover, and U.S. News & World Report, among other publications.

208 pp. (Hardcover) / 13.9 × 21.6 cm / ISBN-978-81-203-5188-2 / ` 595.00

BUSINESS & MANAGEMENT Advertising/Media Studies

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This book offers a comprehensive introduction to workflow management, the management of business processes with information technology. By defining, analyzing, and redesigning an organization’s resources and operations, workflow management systems ensure that the right information reaches the right person or computer application at the right time. The book provides a basic overview of workflow terminology and organization, as well as detailed coverage of workflow modeling with Petri nets. Because Petri nets make definitions easier for nonexperts to understand, they facilitate communication between designers and users. The book includes a chapter of case studies, review exercises, and a glossary.

This book provides a very good, wide-ranging introduction to the theory of workflow technology. Of particular note is the rigorous derivation of workflow process models using Petrinet formalization.

—David Hollingsworth, Distinguished Engineer, ICL Pathway, UK, and Chairman, Workflow Management Coalition, Technical Committee

CONTENTS: Series Foreword. Acknowledgments. Introduction. Organizing Workflows. Modeling Workflows. Management of Workflows. Analyzing Workflows. Functions and Architecture of Workflow Systems. Roadmap for Workflow System Development. Sagitta 2000 Case Study. Appendix A: Workflow Theory. Appendix B: Workflow Modeling Using UML. Solutions to Exercises. Glossary. Bibliography. Index.

WORKFLOW MANAGEMENT Models, Methods, and Systems

WIL VAN DER AALST and KEES VAN HEE.

348 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-3794-7 / ` 325.00

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BUSINESS & MANAGEMENT Strategic Management

Corporate managers who face both strategic uncertainty and market uncertainty confront a classic trade-off between commitment and flexibility. They can stake a claim by making a large capital investment today, influencing their rivals’ behavior, or they can take a “wait and see” approach to avoid adverse market consequences tomorrow. In this book the authors describe an emerging paradigm that can quantify and balance commitment and flexibility, “option games,” by which the decision-making approaches of real options and game theory can be combined.The authors first discuss prerequisite concepts and tools from basic game theory, industrial organization, and real options analysis, and then present the new approach in discrete time and later in continuous time. Their presentation of continuous-time option games is the first systematic coverage of the topic and fills a significant gap in the existing literature.Competitive Strategy provides a rigorous yet pragmatic and intuitive approach to strategy formulation. It synthesizes research in the areas of strategy, economics, and finance in a way that is accessible to readers not necessarily expert in the various fields involved.

Competitive Strategy provides a masterful treatment of the use of options and game theory in the analysis of fundamental strategy problems such as capacity expansion, pre-emption, first vs. late mover positioning, etc. Flexibility and commitment are essential characteristics of any competitive strategy and Trigeorgis and Chevalier-Roignant give us a most insightful and practical set of models and tools. This is a must read book for any strategy scholar and decision maker.

—Karel Cool, Professor of Strategic Management and BP Chaired Professor of European Competitiveness, INSEAD, France

Competitive Strategy provides a powerful synthesis of modern finance and corporate strategy. Today we can anticipate innovation in strategic advice and its implementation. Who better to prepare us for it than Lenos Trigeorgis, with his experiences as serious academic researcher, skilled consultant and seasoned teacher, and Benoît Chevalier-Roignant with the fresh, innovative mind of a young scholar? Their carefully developed exposition exemplifies the power of real options and games to clarify and quantify the strategic decision-making of the firm. The authors skillfully transform the art of strategy into ‘strategic science’.

—Robert C. Merton, Nobel Laureate in Economic Sciences

This book unifies two major strands of economic theory—real options and games—into a single, coherent framework, and then shows how these ideas can be applied to the formulation of corporate strategy in a rigorous fashion. With deep knowledge, Trigeorgis and Chevalier-Roignant take the art of strategy to new heights of analytic sophistication.

—Carliss Baldwin, William L. White Professor of Business Administration, Harvard University

CONTENTS: Glossary. Symbols. Foreword by Avinash Dixit. Preface. The Strategy Challenge. I: Strategy, Games and Options—Strategic Management and Competitive Advantage. Market Structure Games: Static Approaches. Market Structure Games: Dynamic Approaches. Uncertainty, Flexibility, and Real Options. II: Option Games: Discrete-time Analysis—An Integrative Approach to Strategy: Option Games. Option to Invest. Innovation Investment in Two-Stage Games. III: Option Games: Continuous-time Models—Monopoly: Investment and Expansion Options. Oligopoly: Simultaneous Investment. Leadership and Early-Mover Advantage. Preemption versus Collaboration in a Duopoly. Extensions and Other Applications. Appendix: Basics of Stochastic Processes. References. Index.

COMPETITIVE STRATEGY Options and Games

BENOÎT CHEVALIER-ROIGNANT has been a management consultant for several years.LENOS TRIGEORGIS is the Bank of Cyprus Chair Professor of Finance in the School of Economics and Management at the University of Cyprus and Professor of Finance at King’s College of the University of London.

516 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-5101-1 / ` 650.00

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This book introduces the rapidly growing field of ant colony optimization. It gives a broad overview of many aspects of ACO, ranging from a detailed description of the ideas underlying ACO, to the definition of how ACO can generally be applied to a wide range of combinatorial optimization problems, and describes many of the available ACO algorithms and their main applications.

The book first describes the translation of observed ant behaviour into working optimization algorithms. The ant colony metaheuristics is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for network routing problem, is described in detail. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises.

The book is intended primarily for (1) academic and industry researchers in operations research, artificial intelligence, and computational intelligences; (2) practitioners willing to learn how to implement ACO algorithms to solve combinatorial optimization problems; and (3) graduate and postgraduate students in computer science, management studies, operations research, and artificial intelligence.

CONTENTS: Preface. Acknowledgments. From Real to Artificial Ants. The Ant Colony Optimization Metaheuristic. Ant Colony Optimization Algorithms for the Traveling Salesman Problem. Ant Colony Optimization Theory. Ant Colony Optimization for NP-Hard Problems. AntNet: An Algorithm for Data Network Routing. Conclusions and Prospects for the Future. Appendix. References. Index.

ANT COLONY OPTIMIZATION

MARCO DORIGO is Research Director of IRIDA lab at the Universite Libre de Bruxelles and the inventor of the ant colony optimization metaheuristic for combinatorial optimization problems. THOMAS STÜTZLE is Assistant Professor in the Computer Science Department at Darmstadt University of Technology.

320 pp. (Hard Cover) / 17.8 × 23.5 cm / ISBN-978-81-203-2684-9 / ` 450.00

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This book is aimed at training aspiring computational biologists to handle new and unanticipated problems. It teaches the students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. The text covers models of optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

In twenty-first-century biology, modeling has a similar role as the microscope had in earlier centuries; it is arguably the most important research tool for studying complex phenomena and processes in all areas of the life sciences, from molecular biology to ecosystems analysis. Every biologist therefore needs to be familiar with the basic approaches, methods, and assumptions of modeling. Biological Modeling and Simulation is an essential guide that helps biologists explore the fundamental principles of modeling. It should be on the bookshelf of every student and active researcher.

—Manfred D. Laubichler, School of Life Sciences, Arizona State University

CONTENTS: Preface. Introduction. I: Models for Optimization—Classic Discrete Optimization Problems. Hard Discrete Optimization Problems. Case Study: Sequence Assembly. General Continuous Optimization. Constrained Optimization. II: Simulation and Sampling—Sampling from Probability Distributions. Markov Models. Markov Chain Monte Carlo Sampling. Mixing Times of Markov Models. Continuous-Time Markov Models. Case Study: Molecular Evolution. Discrete Event Simulation. Numerical Integration. Ordinary Differential Equations. Numerical Integration. Partial Differential Equations. Numerical Integration. Stochastic Differential Equations. Case Study: Simulating Cellular Biochemistry. III: Parameter-Tuning—Parameter-Tuning as Optimization. Expectation Maximization. Hidden Markov Models. Linear System-Solving. Interpolation and Extrapolation. Case Study: Inferring Gene Regulatory Networks. Model Validation. References. Index.

BIOLOGICAL MODELING AND SIMULATION A Survey of Practical Models, Algorithms, and Numerical Methods

RUSSELL SCHWARTZ.

404 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3889-0 / ` 395.00


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The book is a compact and easy to navigate text on the subject. It offers a quick and accessible reference for anyone who wants to know C# in detail. It is particularly useful for C# learners who are familiar with Java.

This second edition has been updated and expanded, reflecting the evolution and extension of the C# programming language. It covers C# versions 3.0 and 4.0 (as covered in Microsoft Visual Studio 2010), and provides a look ahead at some of the innovations of version 5.0. In particular, it describes asynchronous programming as found in version 5.0.

The book describes C# in detail but informally and concisely, presenting lambda expressions, extension methods, anonymous object expressions, object initializers, collection initializers, local variable type inference, type dynamic, type parameter covariance and contravariance, and Linq (language integrated query), among other topics. It also provides more than 250 examples to illustrate both common use and subtle points. Two-page spreads show general rules on the left and relevant examples on the right, maximizing the amount of information accessible at a glance.

The complete, ready-to-run example programs are available at the book’s Web site, http://www.itu.dk/people/sestoft/csharpprecisely/

CONTENTS: Preface. Notational Conventions. Compiling, Loading, and Executing C# Programs. Names and Reserved Names. C# Naming Conventions. Comments and Program Layout. Data and Types. Variables, Parameters, Fields, and Scope. Strings. String Builders. Arrays. Classes. The Machine Model: Stack, Heap, and Garbage Collection. Expressions. Statements. Struct Types. Interfaces. Enum Types. Delegate Types. Type dynamic (C# 4.0). Nullable Types over Value Types. Exceptions. Threads, Concurrent Execution, and Synchronization. Task Parallel Library (C#4.0). Asynchronous Methods: async and await (C#5.0). Mathematical Functions. Input and Output. Generic Types and Methods. Generic Collections: Sets, Lists, and Dictionaries. Linq, Language Integrated Query (C# 3.0). Namespaces. Partial Type Declarations. Assertions and the Debug.Asert Method. Attributes. Main Differences between C# and Java. Resources. Index.

C# PRECISELY, 2nd ed.

PETER SESTOFT is Professor of Software Development at the IT University of Copenhagen, Denmark.HENRIK I. HANSEN holds master’s degrees in information technology and chemistry.

260 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4597-3 / ` 250.00


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A guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples.

The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples.

The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security.

The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors.

Review for the Book

“This book helps make the cloud computing ecosystem comprehensible for scientist and student alike. Foster and Gannon provide an introduction to concepts, an explanation of systems, clean code examples in Python, and even downloadable Jupyter notebooks.”

Simson L. Garfinkel Cloud Computing Instructor

author of Architects of the Information Society

CLOUD COMPUTING FOR SCIENCE AND ENGINEERING

IAN FOSTER is the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago and Distinguished Fellow at Argonne National Laboratory.

DENNIS B. GANNON is Emeritus Professor of Computer Science at Indiana University Bloomington.

392 pp. / 17.8 × 23.5 cm / ISBN-978-93-88028-79-0 / Forthcoming


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This innovative text presents programming as a unified discipline in a way that is both practical and scientifically sound. The book focuses on techniques of lasting value and explains them precisely in terms of a simple abstract machines.

After an introduction to programming concepts, the book presents both well-known and lesser-known computation models (“programming paradigm”). Each model has its own set of techniques and each is included on the basis of its usefulness in practice. The general models include declarative programming, declarative concurrency, explicit state, object-oriented programming, shared-state concurrency, and relational programming. Specialized models include graphical user interface programming, distributed programming, and constraint programming. Each model is based on its kernel language—a simple core language that consists of a small number of programmer-significant elements. The kernel languages are introduced progressively, adding concepts one by one, thus showing the deep relationships between different models. The kernel languages are defined precisely in terms of a simple abstract machine. The book has many program fragments and exercises, all of which can be run on the Mozart Programming system, an Open Source Software package that features an interactive incremental development environment.

The book intends to be used in undergraduate courses on programming concepts and techniques, applied programming models, concurrent and distributed programming, computational models and on constraint programming.

CONTENTS: Preface. Running the Example Programs. Introduction to Programming Concepts. I: General Computation Models—Declarative Computation Model. Declarative Programming Techniques. Declarative Concurrency. Message-Passing Concurrency. Explicit State. Object-Oriented Programming. Shared-State Concurrency. Relational Programming. II: Specialized Computation Models—Graphical User Interface Programming. Distributed Programming. Constraint Programming. III: Semantics—Language Semantics. IV: Appendixes—References. Index.

CONCEPTS, TECHNIQUES, AND MODELS OF COMPUTER PROGRAMMINGPETER VAN ROY is Professor in the Department of Computing Science and Engineering at Universite Catholique de Louvain, at Louvain-la-Neuve, Belgium.SEIF HARIDI is Professor of Computer Systems in the Department of Microelectronics and Information Technology at the Royal Institute of Technology, Sweden, and Chief Scientific Advisor of the Swedish Institute of Computer Science.

932 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-2685-9 / ` 450.00


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Data Mining, or Knowledge Discovery, has become an indispensable technology for business and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recognition, databases, and high performance computing, data mining extracts useful information from the large data set now available to industry and science. This collection surveys the most recent advances in the field and charts directions for future research.

The first part discusses topics that include distributed data mining algorithms for new application areas, several aspects of next-generation data mining systems and applications, and detection of recurrent patterns in digital media. The second examines such topics as bio-surveillance, marshalling evidence through data mining, and link discovery. The third focuses at scientific data mining; and the topics include mining temporally-varying phenomena, data sets using graphs, and spatial data mining. The last part considers web, semantics and data mining, examining advances in text mining algorithms and software, semantic webs, and other subjects.

The book serves as a supplementary text for the students of Information Technology. It should also be of interest to the professionals of knowledge management.

CONTENTS: Foreword. Preface. Pervasive, Distributed, and Stream Data Mining—Existential Pleasures of Distributed Data Mining. Research Issues in Mining and Monitoring of Intelligence Data. A Consensus Framework for Integrating Distributed Clusterings Under Limited Knowledge Sharing. Design of Distributed Data Mining Applications on the Knowledge Grid. Photonic Data Services: Integrating Data, Network and Path Services to Support Next Generation Data Mining Applications. Mining Frequent Patterns in Data Streams at Multiple Time Granularities. Efficient Data-Reduction Methods for On-Line Association Rule Discovery. Discovering Recurrent Events in Multichannel Data Streams Using Unsupervised Methods. Counterterrorism, Privacy, and Data Mining—Data Mining for Counterterrorism. Biosurveillance and Outbreak Detection. MINDS—Minnesota Intrusion Detection System. Marshalling Evidence Through Data Mining in Support of Counter Terrorism. Relational Data Mining with Inductive Logic Programming for Link Discovery. Defining Privacy for Data Mining. Scientific Data Mining—Mining Temporally-Varying Phenomena in Scientific Datasets. Methods for Mining Protein Contact Maps. Mining Scientific Data Sets using Graphs. Challenges in Environmental Data Warehousing and Mining. Trends in Spatial Data Mining. Challenges in Scientific Data Mining: Heterogeneous, Biased, and Large Samples. Web, Semantics, and Data Mining—Web Mining—Concepts, Applications, and Research Directions. Advancements in Text Mining Algorithms and Software. On Data Mining, Semantics, and Intrusion Detection: What to Dig for and Where to Find It. Usage Mining for and on the Semantic Web. Bibliography. Index.

DATA MINING Next Generation Challenges and Future DirectionsEdited by:HILLOL KARGUPTA, ANUPAM JOSHI and YELENA YESHA are teaching in the Department of Computer Science and Electrical Engineering at the University of Maryland Baltimore County. The first author is also affiliated with AGNIKLLC in Columbia. KRISHNAMOORTHY SIVAKUMAR, Assistant Professor at the School of Electrical Engineering and Computer Science, Washington State University.

576 pp. / 13.9 × 21.6 cm / ISBN-978-81-203-2794-8 / ` 450.00


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This comprehensive text uses a simple and concise framework to teach key ideas in programming language design and implementation. The book’s unique approach is based on a family of syntactically simple pedagogical languages that allow students to explore programming language concepts systematically. It takes as its premise and starting point the idea that when language behaviors become incredibly complex, the description of the behaviors must be incredibly simple.

The book presents a set of tools (a mathematical metalanguage, abstract syntax, operational and denotational semantics) and uses it to explore a comprehensive set of programming language design dimensions, including dynamic semantics (naming, state, control, data), static semantics (types, type reconstruction, polymorphism, effects), and pragmatics (compilation, garbage collection).

This new textbook by Franklyn Turbak, David Gifford, and Mark Sheldon—comprehensive, thorough, pedagogically innovative, impeccably written and organized—greatly enriches the area of programming languages and will be an important reference for years to come.

—Assaf Kfoury, Department of Computer Science, Boston University

CONTENTS: Preface. Acknowledgments. I: Foundations—Introduction. Syntax. Operational Semantics. Denotational Semantics. Fixed Points. II: Dynamic Semantics—FL: A Functional Language. Naming. State. Control. Data. III: Static Semantics—Simple Types. Polymorphism and Higher-order Types. Type Reconstruction. Abstract Types. Modules. Effects Describe Program Behavior. IV: Pragmatics—Compilation. Garbage Collection. A: A Metalanguage. B: Our Pedagogical Languages. References. Index.

DESIGN CONCEPTS IN PROGRAMMING LANGUAGES

FRANKLYN TURBAK, Associate Professor, Computer Science Department at Wellesley College.DAVID GIFFORD, Professor of Computer Science and Engineering at MIT. MARK A. SHELDON, Visiting Assistant Professor, Computer Science Department at Wellesley College.

1348 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3996-5 / ` 695.00


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This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises. The examples and exercises allow readers to understand algorithms intuitively and from different perspectives. Proof sketches, arguing the correctness of an algorithm or explaining the idea behind fundamental results, are also included. The algorithms presented in the book are for the most part “classics,” selected because they shed light on the algorithmic design of distributed systems or on key issues in distributed computing and concurrent programming.

This second edition has been substantially revised. A new chapter on distributed transaction offers up-to-date treatment of database transactions and the important evolving area of transactional memory. A new chapter on security discusses two exciting new topics: blockchains and quantum cryptography. Sections have been added that cover such subjects as rollback recovery, fault-tolerant termination detection, and consensus for shared memory. An appendix offers pseudocode descriptions of many algorithms.

Distributed Algorithms can be used in courses for advanced undergraduates or beginning postgraduate students in computer science, or as a reference for researchers in the field.

CONTENTS: Preface. Introduction. Preliminaries. Snapshots. Waves. Deadlock Detection. Termination Detection. Garbage Collection. Routing. Election. Anonymous Networks. Synchronous Networks. Consensus with Crash Failures. Consensus with Byzantine Failures. Mutual Exclusion. Barriers. Distributed Transactions. Self-Stabilization. Security. Online Scheduling. A. Appendix: Pseudocode Descriptions. References. Index.

DISTRIBUTED ALGORITHMS An Intuitive Approach, 2nd ed. WAN FOKKINK is Professor of Theoretical Computer Science at the VU University, Amsterdam.

268 pp. / 17.8 x 23.5 cm / ISBN-978-93-88028-39-4 / ` 395.00


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This book provides students with a deep, working understanding of the essential concepts of programming languages. Most of these essentials relate to the semantics, or meaning, of program elements, and the text uses interpreters (short programs that directly analyze an abstract representation of the program text) to express the semantics of many essential language elements in a way that is both clear and executable. The approach is both analytical and hands-on. The book provides views of programming languages using widely varying levels of abstraction, maintaining a clear connection between the high-level and low-level views. Exercises are a vital part of the text and are scattered throughout; the text explains the key concepts, and the exercises explore alternative designs and other issues. The complete Scheme code for all the interpreters and analyzers in the book can be found online through The MIT Press Web site.

For this new edition, each chapter has been revised and many new exercises have been added. Significant additions have been made to the text, including completely new chapters on modules and continuation-passing style. Essentials of Programming Languages can be used for both graduate and undergraduate courses, and for continuing education courses for programmers.

With lucid prose and elegant code, this book provides the most concrete introduction to the few building blocks that give rise to a wide variety of programming languages. I recommend it to my students and look forward to using it in my courses.

—Chung-chieh Shan, Department of Computer Science, Rutgers University

I’ve found the interpreters-based approach for teaching programming languages to be both compelling and rewarding for my students. Exposing students to the revelation that an interpreter for a programming language is itself just another program opens up a world of possibilities for problem solving. The third edition of Essentials of Programming Languages makes this approach of writing interpreters more accessible than ever.

—Marc L. Smith, Department of Computer Science, Vassar College

CONTENTS: Foreword by Hal Abelson. Preface. Acknowledgements. Inductive Sets of Data. Data Abstraction. Expressions. State. Continuation-Passing Interpreters. Continuation-Passing Style. Types. Modules. Objects and Classes. A: For Further Reading. B: The SLLGEN Parsing System. Bibliography. Index.

ESSENTIALS OF PROGRAMMING LANGUAGES, 3rd ed.

DANIEL P. FRIEDMAN, Professor of Computer Science, Indiana University.MITCHELL WAND, Professor of Computer Science, Northeastern University.

432 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3806-7 / ` 325.00


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Evolutionary Computation is the general term used for several computational techniques which are based to some degree on the evolution of biological life in the natural world. The computer scientist and engineers use this tool for solving complex problems and to build new models; the biologists use them to develop and test better models of natural evolutionary system; and the artificial-life scientists use them for designing and implementing artificial worlds. The most widely used form of evolutionary computation are genetic algorithms, others being genetic programming, evolution strategies and evolutionary programming.

De Jong presents a comprehensive and integrated overview of this fragmented field in this book. This makes it suitable for classroom use as well as a reliable reference for computer scientists and engineers especially working in optimization problems.

CONTENTS: Introduction. A Historical Perspective. Canonical Evolutionary Algorithms. A Unified View of Simple EAs. Evolutionary Algorithms as Problem Solvers. Evolutionary Computation Theory. Advanced EC Topics. The Road Ahead. Appendix A: Source Code Overview. Bibliography. Index.

EVOLUTIONARY COMPUTATION A Unified Approach

KENNETH A. DE JONG, Professor of Computer Science, Head of Evolutionary Computation Laboratory, and Associate Director of the Krasnow Institute at George Mason University.

268 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3002-3 / ` 250.00

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Object-oriented programming has emerged as the dominant computer programming style, and object-oriented languages such as C++ and Java are immensely popular with academics and industry professionals.

This book provides a comprehensive description of the foundations of statically typed class-based object-oriented programming languages. It begins by analyzing existing object-oriented languages, paying special attention to their type systems and impediments to expressiveness. The text then examines two key features: subtypes and subclasses. After a brief introduction to the lambda calculus, it presents a prototypical object-oriented language, SOOL, a simple type system which is similar to systems of class-based object-oriented languages in common use. The text concludes with a discussion of features, such as parametric polymorphism and MyType construct, which are not yet included in most statically typed object-oriented languages.

This book, which treats a subject of current interest, should prove highly useful to students of computer science and IT as well as to professionals in the field.

KEY FEATURES

• Introduces readers to key issues in the type systems of object-oriented programming languages.

• Provides core material on class-based object-oriented languages.

• Highlights the formalism for writing the syntax and type-checking rules for programming languages.

CONTENTS: List of Figures. Preface. Part One: Type Problems in Object-Oriented Languages—Introduction. Fundamental Concepts of Object-Oriented Languages. Type Problems in Object-Oriented Languages. Adding Expressiveness to Object-Oriented Languages. Understanding Subtypes. Type Restrictions on Subclasses. Varieties of Object-Oriented Programming Languages. Part Two: Foundations: The Lambda Calculus—Formal Language Descriptions and the Lambda Calculus. The Polymorphic Lambda Calculus. Part Three: Formal Descriptions of Object-Oriented Languages—SOOL, a Simple Object-Oriented Language. A Simple Translational Semantics of Objects and Classes. Improved Semantics for Classes. SOOL’s Type System is Safe (and Sound). Completing SOOL: super, nil, Information Hiding, and Multiple Inheritance. Part Four: Extending Simple Object-Oriented Languages—Adding Bounded Polymorphism to SOOL. Adding MyType to Object-Oriented Programming Languages. Match-Bounded Polymorphism. Simplifying: Dropping Subtyping for Matching. Bibliography. Index.

FOUNDATIONS OF OBJECT-ORIENTED LANGUAGESTypes and Semantics

KIM B. BRUCE, Professor of Computer Science, Williams College, Williams Town, Massachusetts.

404 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-2456-0 / ` 425.00

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As book review editor of the IEEE Transactions on Neural Networks, Mohamad Hassoun has had the opportunity to assess the multitude of books on artificial neural networks that have appeared in recent years. Now, in Fundamental of Artificial Neural Networks, he provides the first systematic account of the artificial neural network paradigms by identifying clearly the fundamental concepts and major methodologies that underlie most of the current theory and practice employed by neural network researchers. This text emphasizes the fundamental theoretical aspects of the computational capabilities and the learning abilities of artificial neural networks.

The text assumes that the reader is conversant with the concept of a system and the notion of a “state”, as well as with the basic elements of Boolean algebra and switching theory.

CONTENTS: Preface. Acknowledgment. Abbreviations. Symbols. Threshold Gates. Computational Capabilities of Artificial Neural Networks. Learning Rules. Mathematical Theory of Neural Learning. Adaptive Multilayer Neural Networks I. Adaptive Multilayer Neural Networks II. Associative Neural Memories. Global Search Methods for Neural Networks. References. Index.

FUNDAMENTALS OF ARTIFICIAL NEURAL NETWORKS

MOHAMAD H. HASSOUN, Associate Professor, Department of Electrical and Computer Engineering, Wayne State University.

540 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-1356-9 / ` 595.00

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This internationally acclaimed textbook provides a comprehensive introduction to the modern study of computer algorithms. It 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 presents an algorithm, a design technique, an application area, or a related topic. The algorithms are described and designed in a manner 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 third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, and substantial additions to the chapter on recurrences (now called “Divide-and-Conquer”). 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 new exercises and problems have been added in this edition.

The text is intended primarily for students studying algorithms or data structures. As it discusses engineering issues in algorithm design, as well as mathematical aspects, it is equally well suited for self-study by technical professionals.

Introduction to Algorithms, the ‘bible’ of the field, is a comprehensive textbook covering the full spectrum of modern algorithms: from the fastest algorithms and data structures to polynomial-time algorithms for seemingly intractable problems, from classical algorithms in graph theory to special algorithms for string matching, computational geometry, and number theory. The revised third edition notably adds a chapter on van Emde Boas trees, one of the most useful data structures, and on multithreaded algorithms, a topic of increasing importance.

—Daniel Spielman, Department of Computer Science, Yale University

CONTENTS: Preface. I: Foundations—Introduction. The Role of Algorithms in Computing. Getting Started. Growth of Functions. Divide-and-Conquer. Probabilistic Analysis and Randomized Algorithms. II: Sorting and Order Statistics—Introduction. Heapsort. Quicksort. Sorting in Linear Time. Medians and Order Statistics. III: Data Structures—Introduction. Elementary Data Structures. Hash Tables. Binary Search Trees. Red-Black Trees. Augmenting Data Structures. IV: Advanced Design and Analysis Techniques—Introduction. Dynamic Programming. Greedy Algorithms. Amortized Analysis. V: Advanced Data Structures—Introduction. B-Trees. Fibonacci Heaps. Van Emde Boas Trees. Data Structures for Disjoint Sets. VI: Graph Algorithms—Introduction. Elementary Graph Algorithms. Minimum Spanning Trees. Single-Source Shortest Paths. All-Pairs Shortest Paths. Maximum Flow. VII: Selected Topics—Introduction. Multithreaded Algorithms. Matrix Operations. Linear Programming. Polynomials and the FFT. Number-Theoretic Algorithms. String Matching. Computational Geometry. NP-Completeness. Approximation Algorithms. VIII: Appendix—Mathematical Background—Introduction. A: Summations. B: Sets, etc. C: Counting and Probability. D: Matrices. Bibliography. Index.

INTRODUCTION TO ALGORITHMS, 3rd ed.THOMAS H. CORMEN, Professor of Computer Science and former Director, Institute for Writing and Rhetoric at Dartmouth College.CHARLES E. LEISERSON, Professor of Computer Science and Engineering at Massachusetts Institute of Technology.RONALD L. RIVEST, Andrew and Erna Viterbi Professor, Electrical Engineering and Computer Science at Massachusetts Institute of Technology.CLIFFORD STEIN, Professor, Industrial Engineering and Operations Research at Columbia University.

1312 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4007-7 / ` 1695.00


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This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material, including five new chapters.

Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.

This is the ‘computational thinking’ book we have all been waiting for! With humor and historical anecdotes, John Guttag conveys the breadth and joy of computer science without compromising technical detail. The second edition includes brand new material that focuses on computational approaches to understanding data, complementing traditional computational problem solving.

—Jeannette M. Wing, Corporate Vice President, Microsoft Research, and Consulting Professor of Computer Science and former Department Head, Carnegie Mellon University

John Guttag is an extraordinary teacher and an extraordinary writer. This is not ‘a Python book,’ although you will learn Python. Nor is it a ‘programming book,’ although you will learn to program. It is a rigorous but eminently readable introduction to computational problem solving, and now also to data science—this second edition has been expanded and reorganized to reflect Python’s role as the language of data science.

—Ed Lazowska, Bill & Melinda Gates Chair in Computer Science and Engineering, and Director of the eScience Institute, University of Washington

CONTENTS: Preface. Acknowledgments. Getting Started. Introduction to Python. Some Simple Numerical Programs. Functions, Scoping, and Abstraction. Structured Types, Mutability, and Higher-Order Functions. Testing and Debugging. Exceptions and Assertions. Classes and Object-Oriented Programming. A Simplistic Introduction to Algorithmic Complexity. Some Simple Algorithms and Data Structures. Plotting and More about Classes. Knapsack and Graph Optimization Problems. Dynamic Programming. Random Walks and More About Data Visualization. Stochastic Programs, Probability, and Distributions. Monte Carlo Simulation. Sampling and Confidence Intervals. Understanding Experimental Data. Randomized Trials and Hypothesis Checking. Conditional Probability and Bayesian Statistics. Lies, Damned Lies, and Statistics. A Quick Look at Machine Learning. Clustering. Classification Methods. Python 3.5 Quick Reference. Index.

INTRODUCTION TO COMPUTATION AND PROGRAMMING USING PYTHON, 2nd ed.

JOHN V. GUTTAG, Dugald C. Jackson Professor of Computer Science and Electrical Engineering, MIT.

468 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-5292-6 / ` 695.00

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This book takes a cyber-physical approach to embedded systems, introducing the engineering concepts underlying embedded systems as a technology and as a subject of study. The focus is on modeling, design, and analysis of cyber-physical systems, which integrate computation, networking, and physical processes. The second edition offers two new chapters, several new exercises, and other improvements. The book can be used as a textbook at the advanced under-graduate or introductory post-graduate level and as a professional reference for practicing engineers and computer scientists. Readers should have some familiarity with machine structures, computer programming, basic discrete mathematics and algorithms, and signals and systems.

ENDORSEMENTS

Books titled Introduction to Embedded Systems traditionally focus on computer hardware and software. By taking A Cyber-Physical Systems Approach, Lee and Seshia give students the integrated perspective they need to understand and design the computing systems that make our world function. No other book provides such a comprehensive introduction to embedded systems for real-time applications.

Bruce H. Krogh Professor of Electrical and Computer Engineering

Carnegie Mellon University

Introduction to Embedded Systems by Lee and Seshia is an introductory yet rigorous textbook for the future Internet of Things engineer. It provides a unified systems view of computing and the physical world that will be the foundation of the 21st-century Internet of Things revolution.

George J. Pappas Joseph Moore Professor, University of Pennsylvania

Designers of embedded systems are only too often overwhelmed by the many skills and disciplines that have to be mastered: from writing device drivers, to worst case execution time analysis, to formal verification and modeling of continuous time systems. This book by Lee and Seshia is an excellent guide to bringing order into these complexities of design by discerning the fundamental from the detail, the essential property from the accidental aspect. It presents all the indispensable knowledge areas for an embedded systems designer and leaves out what can be delegated to other specialized disciplines.

Axel Jantsch Professor of Systems on Chips, Institute of Computer Technology,

TU Wien, Vienna; author of Modeling Embedded Systems and SoC's

CONTENTS: Preface. Introduction. I Modeling Dynamic Behaviors—Continuous Dynamics. Discrete Dynamics. Hybrid Systems. Composition of State Machines. Concurrent Models of Computation. II Design of Embedded Systems—Sensors and Actuators. Embedded Processors. Memory Architectures. Input and Output. Multitasking. Scheduling. III Analysis and Verification—Invariants and Temporal Logic. Equivalence and Refinement. Reachability Analysis and Model Checking. Quantitative Analysis. Security and Privacy. IV Appendices—Sets and Functions. Complexity and Computability. Bibliography. Notation Index. Index.

INTRODUCTION TO EMBEDDED SYSTEMS A Cyber-Physical Systems Approach, 2nd ed.

EDWARD ASHFORD LEE is Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley.

SANJIT ARUNKUMAR SESHIA is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley.

560 pages / 17.8 x 23.5 cm / ISBN-978-93-88028-40-0 / ` 695.00


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This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues.

The text is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader’s understanding of the text.

This is the best general book on genetic algorithms written to date.

—John H. Holland, University of Michigan

Professor Mitchell’s book is an excellent introduction to this lively and important field.

—Robert Axelrod, Arthur W. Bromage Distinguished University Professor of Political Science and Public Policy, University of Michigan

Mitchell’s book is comprehensive, covering both traditional GA methods and the recent wealth of GA variants and also providing details of GA implementation, theoretical foundations, and scientific applications.

—David L. Waltz, NEC Research Institute and Brandeis University

Melanie Mitchell has written an outstanding—and needed—new text for the burgeoning field of genetic algorithms…her work is sure to become the field’s new standard source and text.

—Stewart W. Wilson, Rowland Institute for Science

. . . fills an important role of students interested in GAs for either reason. Its coverage of recent theoretical GA work also helps to build a common foundation for the biologists and computer scientists intrigued by what GAs have to offer.

—Richard K. Belew, University of California, San Diego

Melanie Mitchell has successfully assembled a collection of recent applications that convey the excitement and potential of genetic algorithms in solving an array of otherwise difficult or intractable problems.

—John R. Koza, Consulting Professor, Computer Science Department, Stanford University

CONTENTS: Preface. Acknowledgements. Genetic Algorithms: An Overview. Genetic Algorithms in Problem Solving. Genetic Algorithms in Scientific Models. Theoretical Foundations of Genetic Algorithms. Implementing a Genetic Algorithms. Conclusions and Future Directions. Appendix A: Selected General References. Appendix B: Other Resources. Bibliography. Index.

INTRODUCTION TO GENETIC ALGORITHMS, AN

MELANIE MITCHELL.

224 pp. / 16.0 × 24.0 cm / ISBN-978-81-203-1358-5 / ` 150.00

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This text evolved from a new curriculum in scientific computing developed to teach undergraduate science and engineering majors how to use high-performance computing systems (supercomputers) in scientific and engineering applications.

The book assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers.

The authors begin with a survey of scientific computing and then provide a review of background (numerical analysis, IEEE arithmetic, UNIX, Fortran) and tools (elements of MATLAB, IDL, AVS). Full coverage is given to scientific visualization and to the architectures (scientific workstations and vector and parallel supercomputers) and performance evaluation needed to solve large-scale problems. The concluding section on applications includes three problems (molecular dynamics, advection, and computerized tomography) that illustrate the challenge of solving problems on a variety of computer architectures as well as the suitability of a particular architecture to solving a particular problem.

Since this is taught as a hands-on course with extensive programming and experimentation with a variety of architectures and programming paradigms, the authors have provided a laboratory manual and supporting software available via anonymous ftp from the directory/pub/HPSC on cs.colorado.edu.

CONTENTS: Series Foreword. Preface. An Overview of Scientific Computing. Part I: Background—A Review of Selected Topics from Numerical Analysis. IEEE Arithmetic Short Reference. UNIX, vi, and ftp: A Quick Review. Elements of UNIX Make. Elements of Fortran. Part II: Tools—Elements of Matlab. Elements of IDL. Elements of AVS. Part III: Scientific Visualization—Scientific Visualization. Part IV: Architectures—Computer Performance. Vector Computing. Distributed-memory MIMD Computing. SIMD Computing. Part V: Applications—Molecular Dynamics. Advection. Computerized Tomography. Bibliography. Index.

INTRODUCTION TO HIGH-PERFORMANCE SCIENTIFIC COMPUTING, ANLLOYD D. FOSDICK is Professor Emeritus.ELIZABETH R. JESSUP is Assistant Professor. CAROLYN J.C. SCHAUBLE is Research Associate, Department of Computer Science, University of Colorado. GITTA DOMIK is Professor, Department of Mathematics and Computer Science, University of Paderborn, Germany.

788 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-1354-5 / ` 395.00

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Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semiparametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.

Machine learning is rapidly becoming a skill that computer science students must master before graduation. This new edition of the book reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptors and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program.

The book can be used by both advanced undergraduate and postgraduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.

Ethem Alpaydin’s Introduction to Machine Learning provides a nice blending of the topical coverage of machine learning (à la Tom Mitchell) with formal probabilistic foundations (à la Christopher Bishop). This newly updated version now introduces some of the most recent and important topics in machine learning (e.g., spectral methods, deep learning, and learning to rank) to students and researchers of this critically important and expanding field.

—John W. Sheppard, Professor of Computer Science, Montana State University

This volume is both a complete and accessible introduction to the machine learning world. This is a ‘Swiss Army knife’ book for this rapidly evolving subject. Although intended as an introduction, it will be useful not only for students but for any professional looking for a comprehensive book in this field. Newcomers will find clearly explained concepts and experts will find a source for new references and ideas.

—Hilario Gómez-Moreno, IEEE Senior Member, University of Alcalá, Spain

CONTENTS: Preface. Notations. Introduction. Supervised Learning. Bayesian Decision Theory. Parametric Methods. Multivariate Methods. Dimensionality Reduction. Clustering. Nonparametric Methods. Decision Trees. Linear Discrimination. Multilayer Perceptrons. Local Models. Kernel Machines. Graphical Models. Hidden Markov Models. Bayesian Estimation. Combining Multiple Learners. Reinforcement Learning. Design and Analysis of Machine Learning Experiments. A. Probability. Index.

INTRODUCTION TO MACHINE LEARNING 3rd ed.

ETHEM ALPAYDIN, Professor in the Department of Computer Engineering at Bogazici University, Istanbul.

640 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-5078-6 / ` 695.00


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An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks both from a broad neuroscience and cognitive science perspective, with an increased emphasis on the biology and psychology governing the assumptions of the models as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author’s own ideas.

KEY FEATURES

• Emphasizes not so much the formal analysis of network algorithms as the use of algorithms.

• Devotes some effort to describe the biological representation of data by giving several examples of biological and cognitive computation using neural networks.

• The beginning of the book contains programs for some computer modeling experiments to enable students to play with algorithms and theories.

• Provides fragments of code, useful Pascal procedures and functions, and describes results from network modeling programs, throughout the text.

• The afterword tells how to obtain the complete programs, datasets and further details about the operation and design of the programs.

CONTENTS: Introduction. Acknowledgments. Properties of Single Neurons. Synaptic Integration and Neuron Models. Essential Vector Operations. Lateral Inhibition and Sensory Processing. Simple Matrix Operations. The Linear Associator: Background and Foundations. The Linear Associator: Simulations. Early Network Models: The Perceptron. Gradient Descent Algorithms. Representation of Information. Applications of Simple Associators: Concepts Formation and Object Motion. Energy and Neural Networks: Hopfield Networks and Boltzmann Machines. Nearest Neighbor Models. Adaptive maps. The BSB Model: A Simple Nonlinear Autoassociative Neural Network. Associative Computation. Teaching Arithmetic to a Neural Network. Afterword. Index.

INTRODUCTION TO NEURAL NETWORKS, AN

JAMES A. ANDERSON.

668 pp. / 20.0 × 25.0 cm / ISBN-978-81-203-1351-4 / ` 525.00

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The Internet gives us access to a wealth of information in languages we don’t understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how machine learning techniques can improve statistical machine translation, currently at the forefront of research in the field.

The book looks first at enabling technologies—technologies that solve problems that are not machine translation proper but are linked closely to the development of a machine translation system. The book then presents new or improved statistical machine translation techniques.

CONTENTS: Series Foreword. Preface. A Statistical Machine Translation Primer. I: Enabling Technologies—Mining Patents for Parallel Corpora. Automatic Construction of Multilingual Name Dictionaries. Named Entity Transliteration and Discovery in Multilingual Corpora. Combination of Statistical Word Alignments Based on Multiple Preprocessing Schemes. Linguistically Enriched Word-Sequence Kernels for Discriminative Language Modeling. II: Machine Translation—Toward Purely Discriminative Training for Tree-Structured Translation Models. Reranking for Large-Scale Statistical Machine Translation. Kernel-Based Machine Translation. Statistical Machine Translation through Global Lexical Selection. Discriminative Phrase Selection for SMT. Semisupervised Learning for Machine Translation. Learning to Combine Machine Translation Systems. References. Contributors. Index.

LEARNING MACHINE TRANSLATIONEdited by:CYRIL GOUTTE is a researcher in the Interactive Language Technologies Group at the Canadian National Research Council’s Institute for Information Technology.NICOLA CANCEDDA is a researcher in the Cross-Language Technologies Research Group at the Xerox Research Centre Europe.MARC DYMETMAN is a researcher in the Cross-Language Technologies Research Group at the Xerox Research Centre Europe.GEORGE FOSTER is a researcher in the Interactive Language Technologies Group at the Canadian National Research Council’s Institute for Information Technology.

328 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4055-8 / ` 325.00

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Complex communicating computer systems—computers connected by data networks and in constant communication with their environments—do not always behave as expected. This book introduces behavioral modeling, a rigorous approach to behavioral specification and verification of concurrent and distributed systems. It is among the very few techniques capable of modeling systems interaction at a level of abstraction sufficient for the interaction to be understood and analyzed. Offering both a mathematically grounded theory and real-world applications, the book is suitable for classroom use by postgraduate students of Computer Science and as a reference for system architects.

The book covers the foundation of behavioral modeling using process algebra, transition systems, abstract data types, and modal logics. Exercises and examples augment the theoretical discussion. It introduces a modeling language, mCRL2, that enables concise descriptions of even the most intricate distributed algorithms and protocols. Using behavioral axioms and such proof methods as confluence, cones, and foci, readers will learn how to prove such algorithms equal to their specifications. Specifications in mCRL2 can be simulated, visualized, or verified against their requirements. An extensive mCRL2 toolset for mechanically verifying the requirements is freely available online; this toolset has been successfully used to design and analyze industrial software that ranges from healthcare applications to particle accelerators at CERN. Appendixes offer material on equations and notation as well as exercise solutions.

Solution Manual is available for adopting faculty.

This book offers an excellent coverage of the foundations behind data-enriched process algebra and modal mu-calculus aimed at the rigorous modeling and verification of distributed systems. This clearly written textbook contains targeted examples and exercises and is highly recommended for readers who want to get acquainted with modern concurrency theory.

—Joost-Pieter Katoen, RWTH Aachen University and University of Twente

mCRL2 is one of the most expressive and analytically powerful process-algebra-based tool sets currently available. With the publication of the wonderfully written Modeling and Analysis of Communicating Systems, the tool set now has the comprehensive companion manuscript it deserves.

—Scott A. Smolka, Professor of Computer Science, Stony Brook University

Finally, the book that contains the full story of mCRL2, an extremely powerful specification formalism for concurrent, complex systems empowered by an extensive tool set. This book provides detailed and instructive information on the wide range of modeling and analysis possibilities of mCRL2 and is a must-read for anyone who cares about the correctness of computer systems.

—Kim Guldstrand Larsen, Professor of Computer Science, Aalborg University; coauthor of Reactive Systems: Modelling, Specification and Verification

CONTENTS: Preface. Acknowledgments. I: Modeling—Introduction. Actions, Behavior, Equivalence, and Abstraction. Data Types. Sequential Processes. Parallel Processes. The Modal µ-calculus. Modeling System Behavior. Timed Process Behavior. II: Analysis—Basic Manipulation of Processes. Linear Process Equations and Linearization. Confluence and -prioritization. Cones and Foci. * Verification of Distributed Systems. Verification of Modal Formulas Using Parameterized Boolean Equation Systems. III: Semantics—Semantics. IV: Appendixes—A: Brief Tool Primer. B: Equational Definition of Built-In Data Types. C: Plain-Text Notation. D: Syntax of the Formalisms. E: Axioms for Processes. F: Answers to Exercises. Bibliography.

MODELING AND ANALYSIS OF COMMUNICATING SYSTEMS

JAN FRISO GROOTE, Professor of Computer Science at the Eindhoven University of Technology, the Netherlands.

MOHAMMAD REZA MOUSAVI, Professor of Computer Systems Engineering at the Center for Research on Embedded Systems at Halmstad University, Sweden.

392 pp. / 20.0 × 25.0 cm / ISBN-978-81-203-5183-7 / ` 795.00

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The interplay between optimization and machine learning is one of the most important developments in modern computational science.

Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today’s machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

CONTENTS: Series Foreword. Preface. Introduction: Optimization and Machine Learning. Convex Optimization with Sparsity-Inducing Norms. Interior-Point Methods for Large-Scale Cone Programming. Incremental Gradient, Subgradient, and Proximal Methods for Convex Optimization: A Survey. First-Order Methods for Nonsmooth Convex Large-Scale Optimization. I: General Purpose Methods. First-Order Methods for Nonsmooth Convex Large-Scale Optimization. II: Utilizing Problem’s Structure. Cutting-Plane Methods in Machine Learning. Introduction to Dual Decomposition for Inference. Augmented Lagrangian Methods for Learning, Selecting, and Combining Features. The Convex Optimization Approach to Regret Minimization. Projected Newton-type Methods in Machine Learning. Interior-Point Methods in Machine Learning. The Tradeoffs of Large-Scale Learning. Robust Optimization in Machine Learning. Improving First and Second-Order Methods by Modeling Uncertainty. Bandit View on Noisy Optimization. Optimization Methods for Sparse Inverse Covariance Selection. A Pathwise Algorithms for Covariance Selection.

OPTIMIZATION FOR MACHINE LEARNINGEdited bySUVRIT SRA is a Research Scientist at the Max Planck Institute for Biological Cybernetics, Tübingen, Germany.SEBASTIAN NOWOZIN is a Postdoctoral Researcher at Microsoft Research, Cambridge, UK. STEPHEN J. WRIGHT is Professor in the Computer Sciences Department at the University of Wisconsin, Madison.

508 pp. / 20.0 × 25.0 cm / ISBN-978-81-203-4754-0 / ` 795.00


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The rapid growth and integration of databases provides scientists, engineers, and business people with a vast new resource that can be analyzed to make scientific discoveries, optimize industrial systems, and uncover financially valuable patterns. To undertake these large data mining projects, researchers and practitioners have adopted established algorithms from statistics, machine learning, neural networks, and databases and have also developed new methods targeted at large data mining problems.

Principles of Data Mining with its unique blend of inputs from information science, computer science, and statistics provides practitioners and students with an introduction to the wide range of algorithms and methodologies in this exciting area.

KEY FEATURES

• Gives an overview based on intuition, stressing on the principles underlying data mining algorithms and their application.

• Shows how algorithms are constructed to solve specific problems systematically.

• Emphasizes on how analysis fits together when applied to real-world data mining problems.

This book is a must read for one who wants to know how to store, access, model and finally describe and understand large data sets.

CONTENTS: List of Tables. List of Figures. Series Foreword. Preface. Introduction. Measurement and Data. Visualizing and Exploring Data. Data Analysis and Uncertainty. A Systematic Overview of Data Mining Algorithms. Models and Patterns. Score Functions for Data Mining Algorithms. Search and Optimization Methods. Descriptive Modeling. Predictive Modeling for Classification. Predictive Modeling for Regression. Data Organization and Databases. Finding Patterns and Rules. Retrieval by Content. Appendix: Random Variables. References. Index.

PRINCIPLES OF DATA MINING

DAVID HAND, Imperial College, London.

HEIKKI MANNILA, Helsinki University of Technology.

PADHRAIC SMYTH, University of California at Irvine.

580 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-2457-2 / ` 550.00


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An introduction to algorithms for readers with no background in advanced mathematics or computer science, emphasizing examples and real-world problems.

Algorithms are what we do in order not to have to do something. Algorithms consist of instructions to carry out tasks—usually dull, repetitive ones. Starting from simple building blocks, computer algorithms enable machines to recognize and produce speech, translate texts, categorize and summarize documents, describe images, and predict the weather. A task that would take hours can be completed in virtually no time by using a few lines of code in a modern scripting program. This book offers an introduction to algorithms through the real-world problems they solve. The algorithms are presented in pseudocode and can readily be implemented in a computer language.

The book presents algorithms simply and accessibly, without overwhelming readers or testing their intelligence. Readers should be comfortable with mathematical fundamentals and have a basic understanding of how computers work; all other necessary concepts are explained in the text. After presenting background in pseudocode conventions, basic terminology, and data structures, chapters cover compression, cryptography, graphs, searching and sorting, hashing, classification, strings, and chance. Each chapter describes real problems and then presents algorithms to solve them. Examples illustrate the wide range of applications, including shortest paths as a solution to paragraph line breaks, strongest paths in elections systems, hashes for song recognition, voting power Monte Carlo methods, and entropy for machine learning. It is meant for undergraduate computer science students. Students in other such as applied sciences can also benefit from it.

Praise for the Book

A broad survey of algorithmic ideas that avoids the standard ‘greatest hits’ approach. It includes advanced topics like voting systems and text compression that are not covered in most introductory algorithm books. Beginners will be running before they can walk!

—Steven Skiena Distinguished Teaching Professor Department of Computer Science

Stony Brook University

REAL-WORLD ALGORITHMS A Beginner's Guide

PANOS LOURIDAS is Associate Professor in the Department of Management Science and Technology at the Athens University of Economics and Business.



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Big Data is made up of lots of little data: numbers entered into cell phones, addresses entered into GPS devices, visits to websites, online purchases, ATM transactions, and any other activity that leaves a digital trail. This book on Big Data cuts through the hype to explore the potential of Big Data. It shows the ways in which the analysis of Big Data can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy.

The authors describe Reality Mining at five different levels: the individual, the neighbourhood and organization, the city, the nation and the world. For each level, they first offer a non-technical explanation of data collection methods and then describe applications and systems that have been or could be built. Thus, making it understandable to everyone. Some examples are a mobile app that helps smokers quit smoking; a workplace “knowledge system”; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and analysis of social media to track the spread of disease. Their argument being how Big Data, used respectfully and responsibly, can help people live better, healthier, and happier lives.

The book will be useful for students of management, computer science, media studies and professionals as well.

We look at digital devices as things that are meant to serve us. In Reality Mining we are taken on a journey from individuals to countries, to illustrate the true transformative power that the collective use of these digital devices brings to humanity. A fascinating trip guided by researchers who have successfully bridged discovery with entrepreneurship!

—Albert-Laszló Barabasi, Robert Gray Doge Professor of Network Science, Northeastern University; author of Linked

A smart look at how Big Data transforms our lives, from the microcosm of the individual to the macrocosm of the planet. Eagle’s pioneering research in data-mining human behavior is inspiring, while Greene’s insights on what it all means make Reality Mining an indispensable book. And importantly, privacy issues are not an after-thought but are interlaced throughout. as it should be.

—Kenneth Cukier, coauthor of Big Data: A Revolution That Will Transform How We Live, Work, and Think

CONTENTS: Introduction. I: The Individual (One Person)—Mobile Phones, Sensors, and Lifelogging: Collecting Data from Individuals While Considering Privacy. Using Personal Data in a Privacy-Sensitive Way to Make a Person’s Life Easier and Healthier. II: The Neighborhood and the Organization (10 to 1,000 People)— Gathering Data from Small Heterogeneous Groups. Engineering and Policy: Building more Efficient Businesses, Enabling Hyperlocal Politics, Life Queries, and Opportunity Searches. III: The City (1,000 to 1,000,000 People)—Traffic Data, Crime Stats, and Closed-Circuit Cameras: Accumulating Urban Analytics. Engineering and Policy: Optimizing Resource Allocation. IV: The National (1 Million to 100 Million People)—Taking the Pulse of a Nation: Census, Mobile Phones, and Internet Giants. Engineering and Policy Addressing National Sentiment, Economic Deficits, and Disasters. V: Reality Mining the World’s Data (100 Million 7 Billion People)—Gathering the World’s Data: Global Census, International Travel and Commerce, and Planetary-Scale Communication. Engineering a Safer and Healthier Word. Conclusion. Notes. Index.

REALITY MINING Using Big Data to Engineer A Better WorldNATHAN EAGLE, one of the “50 people who will change the world” on the 2012 Wired Smart List, is the co-founder and CEO of Jana, a company that helps global brands reach customers in emerging markets via mobile airtime. He holds faculty positions at Harvard and Northeastern University.

KATE GREENE is a freelance science and technology journalist based in San Francisco whose work has appeared in The Economist, Discover, and U.S. News & World Report, among other publications.

208 pp. (Hardcover) / 13.9 × 21.6 cm / ISBN-978-81-203-5188-2 / ` 595.00

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Real-time systems and networks are of increasing importance in many applications, including automated factories, telecommunication systems, defence systems, and space systems. The book introduces the concepts, and state-of-the-art research developments of resource management in real time systems and networks. Unlike other texts in the field, it covers the entire spectrum of issues in resource management, including task scheduling in uniprocessor real-time systems; task scheduling, fault-tolerant task scheduling, and resource reclaiming in multiprocessor real-time systems, conventional task scheduling and object-based task scheduling in distributed real-time systems; and message scheduling, QoS routing, dependable communication, multicast communication, and medium access protocols in real-time networks. It provides algorithmic treatment for all of the issues addressed, highlighting the intuition behind each algorithm and giving examples. It also includes two chapters on case studies.

The book intends to have interests of students of computer science and engineering and of professionals and researchers in the field.

CONTENTS: Preface. Introduction. Task Scheduling in Multiprocessor Real-Time Systems. Resource Reclaiming in Multiprocessor Real-Time Systems. Fault-Tolerant Task Scheduling in Multiprocessor Real-Time Systems. Resource Management in Distributed Real-Time Systems. Scheduling of Object-Based Tasks in Distributed Real-Time Systems. Real-Time Communication in Wide Area Networks. Route Selection in Real-Time Wide Area Networks. Multicasting in Real-Time Networks. Real-Time Communication in Multiple Access Networks. Case Study—Distributed Air Defense System. Case Study—Air Traffic Control System. References. Acronyms. Index.

RESOURCE MANAGEMENT IN REAL-TIME SYSTEMS AND NETWORKS

C. SIVA RAM MURTHY is Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Madras, India.G. MANIMARAN is Assistant Professor in the Department of Electrical and Computer Engineering at IOWA State University.

464 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-2682-8 / ` 425.00

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This book is intended to provide an introduction to the Scheme Programming Language in a clear and concise manner. Scheme is a general purpose, high level programming language, supporting operations on structural data such as strings, lists and vectors, as well as operations on more traditional data such as numbers and characters. It is fairly a simple language to learn and a truly versatile language that has been employed to write text editors, optimizing compilers, operating systems, graphics packages, expert systems, numerical applications, financial analysis packages, virtual reality systems and practically every other type of application imaginable.

Written for professionals and students with some prior programming experience, it begins by leading the programmer gently through the basics of Scheme and continues with an introduction to some of the more advanced features of the language.

The fourth edition stands substantially revised to bring the content up-to-date with the current Scheme standard (http://www.rbrs.org/). This book is not intended to supplant the current standard but rather to provide more comprehensive introduction and reference manual for the language with additional explanatory text and a large number of examples spread throughout the text. One entire chapter is dedicated to the presentation of a set of longer examples.

Answers to many of the exercises, a complete formal syntax of the Scheme, and a summary of forms and procedures are provided in appendices.

This fourth edition builds on the strengths of the previous editions and provides a comprehensive, no-nonsense introduction to the Scheme programming language in its latest form. The combination of solidity and finesse displayed in this book makes it a reference text for educated computer scientists. The accompanying software, Petite Chez Scheme, makes it the ideal starting point for any programmer who wants to extend his or her repertoire with Scheme.

— Olivier Danvy, Aarhus University, Denmark Coeditor-in-Chief of Higher-Order and Symbolic Computation

Kent Dybvig’s The Scheme Programming Language is to Scheme what Kernighan and Ritchie’s The C Programming Language is to C. Dybvig’s book is the book for either the novice or serious Scheme programmer. Its style, wit, and organization has reached a new high with the publication of the fourth edition.

— Daniel P. Friedman, Department of Computer Science, Indiana University

Students in my Programming Language Concepts class need to learn the basics of Scheme in a few days, and to pick up harder concepts throughout the course. For nineteen years, The Scheme Programming Language has been an excellent guide for them. Dybvig’s rapid-fire prose and examples serve both the Scheme beginner and the experienced programmer in need of a reference. Seldom do my students make a point of praising a computer science textbook; that happens over and over with this one.

— Claude W. Anderson, Rose-Hulman Institute of Technology

CONTENTS: Preface. Introduction. Getting Started. Going Further. Procedures and Variables Bindings. Control Operations. Operations on Objects. Input and Output. Syntactic Extension. Records. Libraries and Top-Level Programs. Exceptions and Conditions. Extended Examples. References. Answers to Selected Exercises. Formal Syntax. Summary of Forms. Index.

SCHEME PROGRAMMING LANGUAGE, THE 4th ed.

R. KENT DYBVIG is Professor of Computer Science at Indiana University and principal developer of Chez Scheme.

504 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4300-9 / ` 395.00

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This text is the first comprehensive presentation of reduction semantics in one volume; it also introduces the first reliable and easy-to-use tool set for such forms of semantics. The book comes with a prototyping tool suite to develop, explore, test, debug, and publish semantic models of programming languages. With PLT Redex, semanticists can formulate models as grammars and reduction models on their computer with the ease of paper and pencil.

The text first presents a framework for the formulation of language models, focusing on equational calculi and abstract machines, and then introduces PLT Redex, a suite of software tools for expressing these models as PLT Redex models.

PLT Redex comes with the PLT Scheme implementation, available free at http://www.plt-scheme.org/. Readers can download the software and experiment with Redex as they work their way through the book.

This book is useful for the working semantics engineer (graduate student or professional language designer).

Courses on semantics can easily become as dry as dust; in contrast, this book is nothing short of revolutionary. The first part is a very clear explanation of the basic concepts in programming language semantics, starting with abstract models and moving to progressively more concrete ones. However, the book really comes alive in the second part, where the authors use the PLT Redex language that they have developed to interactively explore language semantics in the same way that DrScheme allows the interactive exploration of programs. I believe that this approach will become the standards way of doing semantics research in the future, and there is no better way to take advantage of it than to read this book.

— Michael Vanier, Department of Computer Science, Caltech

CONTENTS: Preface. I: Reduction Semantics—Semantics via Syntax. Analyzing Syntactic Semantics. The l-Calculus. ISWIM. An Abstract Syntax Machine. Abstract Register Machines. Tail Calls and More Space Savings. Control: Errors, Exceptions, and Continuations. State: Imperative Assignment. Simply Typed ISWIM. II: PLT Redex—The Basics. Variables and Meta-functions. Layered Development. Testing. Debugging. Case Study. 1: Order of Evaluation. Case Study 2: Continuations as Values. Typesetting. A: Appendix: A Tour of DrScheme. III: Applications— Modular ACL2—Carl Eastlund, Northeastern University. Modeling Scheme Macros—Martin Gasbichler, Zühlke Engineering AG. A Model of Java/Scheme Interoperability—Kathryn E. Gray, University of Utah. Implementing Hidden Type Variables in Fortress—Joe Hallett, Boston University Eric Allen, Sun Microsystems, Inc. Sukyoung Ryu, Sun Microsystems, Inc.. Type Checking and Inference via Reductions—George Kuan, University of Chicago. Topsl: DSEL as Multi-language System—Jacob Matthews, University of Chicago. Prototyping Nested Schedulers—Mike Rainey, University of Chicago. Bibliography. Index.

SEMANTICS ENGINEERING WITH PLT REDEX

MATTHIAS FELLEISEN is Trustee Professor of Computer Science at Northeastern University.ROBERT BRUCE FINDLER is Assistant Professor of Computer Science at Northwestern University.MATTHEW FLATT is Associate Professor of Computer Science at the University of Utah.

516 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4320-7 / ` 475.00

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The development of the Semantic Web, with machine-readable content, has the potential to revolutionize the World Wide Web and its uses. A Semantic Web Primer is an introduction and guide to this still emerging field, describing its key ideas, languages, and technologies. The book provides a systematic treatment of the different languages (XML, RDF, OWL, and rules) and technologies (explicit metadata, ontologies, and logic and inference) that are central to Semantic Web development as well as such crucial related topics as ontology engineering and application scenarios.

This substantially revised and updated second edition reflects recent developments in the field, covering new application areas and tools. The new material includes a discussion of such topics as SPARQL as the RDF query language; OWL DLP and its interesting practical and theoretical properties; the SWRL language (in the chapter on rules); OWL-S (on which the discussion of Web services is now based). The new final chapter considers the state-of-the-art of the field today, captures ongoing discussions, and outlines the most challenging issues facing the Semantic Web in the future. Suitable for use as a textbook or for self-study by professionals, it concentrates on undergraduate-level fundamental concepts and techniques that will enable readers to proceed with building applications on their own and includes exercises, project descriptions, and annotated references to relevant online materials.

This book is essential reading for anyone who wishes to learn about the Semantic Web. By gathering the fundamental topics into a single volume, it spares the novice from having to read a dozen dense technical specifications. I have used the first edition in my Semantic Web course with much success.

—Jeff Heflin, Associate Professor Department of Computer Science and Engineering, Lehigh University

This book provides a solid overview of the various core subjects that constitute the rapidly evolving Semantic Web discipline. While keeping most of the core concepts as presented in the first edition, the second edition contains valuable language updates, such as coverage of SPARQL, OWL DLP, SWRL, and OWL-S. The book truly provides a comprehensive view of the Semantic Web discipline and has all the ingredients that will help an instructor in planning, designing, and delivering the lectures for a graduate course on the subject.

—Isabel Cruz, Department of Computer Science, University of Illinois, Chicago

CONTENTS: List of Figures. Series Foreword. The Semantic Web Vision. Describing Web Resources: RDF. Querying the Semantic Web. Web Ontology Language: OWL2. Logic and Inference: Rules. Applications. Ontology Engineering. Conclusion. A. XML Basics. Index.

SEMANTIC WEB PRIMER, A, 3rd ed.

GRIGORIS ANTONIOU, Professor, Institute for Computer Science, FORTH (Foundation for Research and Technology-Hellas), Heraklion, Greece.PAUL GROTH, Assistant Professor, Knowledge Representation and Reasoning Group, Department of Computer Science, VU University, Amsterdam.FRANK VAN HARMELEN, Professor, Knowledge Representation and Reasoning Group, Department of Computer Science, VU University, Amsterdam.RINKE HOEKSTRA, Postdoctoral Researcher, Knowledge Representation and Reasoning Group, Department of Computer Science, VU University, Amsterdam.

288 pp. / 16.0 × 24.1 cm / ISBN-978-81-203-5103-5 / ` 450.00

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Any system build on flawed concepts makes it clumsy and hard to make even simplest of changes to repair the damage done. The author begins the book with the statement “Software is built on abstractions. Pick the right ones and programming will flow from design; modules will have small and simple interfaces; and new functionality will more likely fit in without extensive organization.”

Basically, an abstraction is an idea reduced to its essential form. The author introduces the key elements of the approach: a logic, which provides the building blocks of the language; a language, which adds a small amount of syntax to the logic for structuring descriptions; and an analysis, which is a form of constraint solving, and it offers both simulation (generating sample states and executions) and checking (finding counterexamples to claimed properties). The author uses the language Alloy as a vehicle because of its simplicity and tool support; but the book’s lessons are mostly language-independent, and could also be applied in the context of other modeling languages.

Abstraction is the essence of simple and effective software design, and logic is the essential tool for exploring and validating abstractions. These basic insights, which have been laboriously rediscovered by many practicing programmers, are now accessible to students and professionals at all levels of experience. Daniel Jackson supports his clear and elegant text with a powerful logical analysis tool that brings his witty examples to life.

—Tony Hoare, Senior Researcher, Microsoft

CONTENTS: Preface. Acknowledgments. Introduction. A Whirlwind Tour. Logic. Language. Analysis. Examples. Appendices—A: Exercises. B: Alloy Language Reference. C: Kernel Semantics. D: Diagrammatic Notation. E: Alternative Approaches. References. Index.

SOFTWARE ABSTRACTIONS Logic, Language, and Analysis

DANIEL JACKSON, Professor, Department of Electrical Engineering and Computer Science and leads the Software Design Group at the Computer Science and Artificial Intelligence Lab at MIT.

368 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-3170-9 / ` 325.00

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Automata have existed for centuries, it is only recently that anything resembling autonomous agents has begun to appear. The agents now being deployed differ in important ways from earlier concepts, for today the momentum has shifted from hardware to software, from the atoms that comprise a mechanical robot to the bits that make up a digital agent. These software agents function continuously and autonomously in a particular environment that is often inhabited by other agents and processes.

The essays in this book, by leading researchers and developers of agent-based systems, address both the state-of-the-art of agent technology and its likely evolution in the near future.

CONTENTS: Preface. Introduction. Section One: Agents and the User Experience—How Might People Interact with Agents. Agents: From Direct Manipulation to Delegation. Interface Agents: Metaphors with Character. Designing Agents as if People Mattered. Direct Manipulation Versus Agents: Paths to Predictable, Controllable, and Comprehensible Interfaces. Section Two: Agents for Learning and Intelligent Assistance—Agents for Information Sharing and Coordination: A History and Some Reflections. Agents that Reduce Work and Information Overload. KidSim: Programming Agents without a Programming Language. Lifelike Computer Characters: The Persona Project at Microsoft Research. Software Agents for Cooperative Learning. M: An Architecture of Integrated Agents. Section Three: Agent Communication, Collaboration, and Mobility—An Overview of Agent-Oriented Programming. KQML as an Agent Communication Language. An Agent-Based Framework for Interoperability. Agents for Information Gathering. KAoS: Toward an Industrial-Strength Open Agent Architecture. Communicative Actions for Artificial Agents. Mobile Agents. Index.

SOFTWARE AGENTS

JEFFREY M. BRADSHAW (Ed.), leads the agent technology efforts for The Boeing Company and the Fred Hutchinson Cancer Research Center in Seattle, Washington.

492 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4135-7 / ` 425.00

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This book which is a self-contained course on server-based Internet applications software, enables students to build Web-based applications on the scale of Amazon.com. Unlike the desktop applications that most students have already learned to build, server-based applications have multiple simultaneous users.

With this book, students will have the skills to take vague and ambitious specifications and turn them into a system design that can be built and launched in a few months. They will be able to test prototypes with end-users and refine the application design. They will understand how to meet the challenge of extreme business requirements with automatic code generation and the use of open-source toolkits where appropriate. Students will understand HTTP, HTML, SQL, mobile browsers, VoiceXML, data modeling, page flow and interaction design, server-side scripting, and usability analysis.

The book is suitable for classroom use and will be a useful reference for software professionals developing multi-user Internet applications. It will also help managers evaluate such commercial software as Microsoft Sharepoint of Microsoft Content Management Server.

CONTENTS: Preface. Acknowledgments. Introduction. Basics. Planning. Software Structure. User Registration and Management. Content Management. Software Modularity. Discussion. Adding Mobile Users to Your Community. Voice (VoiceXML). Scaling Gracefully. Search. Planning Redux. Distributed Computing with HTTP, XML, SOAP, and WSDL. Metadata (and Automatic Code Generation. User Activity Analysis. Writeup. Reference Chapters. A. HTML. B. Engagement Management by Cesar Brea. C. Grading Standards Glossary. To the Instructor. Sample Contract (between Student Team and Client). About the Authors. Index.

SOFTWARE ENGINEERING FOR INTERNET APPLICATIONEVE ANDERSSON, Senior Vice President and Chair of the Bachelor of Science in Computer Science at Neumont University, Salt Lake City.PHILIP GREENSPUN, a software developer, author, teacher, pilot, and photographer, originated the Software Engineering for Internet Applications course at MIT.ANDREW GRUMET, Independent Software Developer.

412 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3041-2 / ` 295.00

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This book presents a variety of computational methods used to solve dynamic problems in economics and finance. It emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses. The examples are drawn from a wide range of subspecialties of economics and finance, with particular emphasis on problems in agricultural and resource economics, macroeconomics, and finance.

The book is divided into two parts. The first part develops basic numerical methods, including linear and nonlinear equation methods, complementarity methods, finite-dimensional optimization, numerical integration and differentiation, and function approximation. The second part presents methods for solving dynamic stochastic models in economics and finance, including dynamic programming, rational expectations, and arbitrage pricing models in discrete and continuous time. The book uses matlab to illustrate the algorithms and includes a utilities toolbox to help readers develop their own computational economics applications.

One of this book’s many strengths is its structure, the way theory-based chapters alternate with analytical ones. This will make it an invaluable resource in the classroom.

—Thomas J. Sargent, Department of Economics, New York University, and Hoover Institution, Stanford University

This book ties together numerical methods with state-of-the-art mathematical tools in a user-friendly way. It should be part of the program in ‘math camps’ for incoming graduate students in economics and finance. The matlab programs are a very useful resource for anyone doing applied research.

—Paul D. McNelis, Professor of Economics, Georgetown University

CONTENTS: Preface. Introduction. Linear Equations and Computer Basics. Nonlinear Equations and Complementarity Problems. Finite-Dimensional Optimization. Numerical Integration and Differentiation. Function Approximation. Discrete Time, Discrete State Dynamic Models. Discrete Time, Continuous State Dynamic Models: Theory and Examples. Discrete Time, Continuous State Dynamic Models: Methods. Continuous Time Models: Theory and Examples. Continuous Time Models: Solution Methods. Appendix A: Mathematical Background. Appendix B: A Matlab Primer. References. Index.

APPLIED COMPUTATIONAL ECONOMICS AND FINANCE

MARIO J. MIRANDA is Professor and Chair of Graduate Studies, Department of Agricultural, Environmental, and Development Economics, Ohio State University.PAUL L. FACKLER is Associate Professor, Department of Agricultural and Resource Economics, North Carolina State University.

528 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3934-7 / ` 495.00

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ECONOMICS

A Course in Game Theory presents the main ideas of game theory at a level suitable for postgraduate and advanced undergraduate students of Economics, emphasizing the theory’s foundations and interpretations of its basic concepts. The authors provide precise definitions and full proofs of results, sacrificing generalities and limiting the scope of the material in order to do so. The text is organized in four parts: strategic games, extensive games with perfect information, extensive games with imperfect information, and coalitional games. It also includes over 100 exercises.

Martin Osborne and Ariel Rubinstein have made most of their theoretical contributions on the strategic side, and yet they devote a nice portion of the book to cooperative game theory. I recommend this book highly. It is beautifully done, and it recognizes the importance of the cooperative theory.

—Robert J. Aumann, Professor of Mathematics, The Hebrew University of Jerusalem

CONTENTS: Preface. Introduction. I: Strategic Games—Nash Equilibrium. Mixed, Correlated, and Evolutionary Equilibrium. Rationalizability and Iterated Elimination of Dominated Actions. Knowledge and Equilibrium. II: Extensive Games with Perfect Information—Extensive Games with Perfect Information. Bargaining Games. Repeated Games. Complexity Considerations in Repeated Games. Implementation Theory. III: Extensive Games with Imperfect Information—Extensive Games with Imperfect Information. Sequential Equilibrium. IV: Coalitional Games—The Core. Stable Sets, the Bargaining Set, and the Shapley Value. The Nash Solution. List of Results. References. Index.

COURSE IN GAME THEORY, A

MARTIN J. OSBORNE, Professor of Economics, University of Toronto, Canada. ARIEL RUBINSTEIN, Professor of Economics, Tel Aviv University, Israel and Princeton University, USA.

368 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-5186-8 / ` 595.00

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is first described in theoretical terms, with explicit definitions and rigorous proofs; numerical methods and computer codes to implement these methods follow. Drawing on the latest research, the book covers such cutting-edge topics as asset price bubbles, recursive utility, robust control, policy analysis in dynamic New Keynesian models with the zero lower bound on interest rates, and Bayesian estimation of dynamic stochastic general equilibrium (DSGE) models. The book first introduces the theory of dynamical systems and numerical methods for solving dynamical systems, and then discusses the theory and applications of dynamic optimization. It goes on to treat equilibrium analysis, covering a variety of core macroeconomic models, and such additional topics as recursive utility (increasingly used in finance and macroeconomics), dynamic games, and recursive contracts. The book also introduces Dynare, a widely used software platform for handling a range of economic models; readers will learn to use Dynare for numerically solving DSGE models and performing Bayesian estimation of DSGE models. Mathematical appendixes present all the necessary mathematical concepts and results. Matlab codes used to solve examples are indexed and downloadable from the book’s website. A downloadable instructor’s manual is available to adopting instructors.

The book is suitable for post-graduate and research students of Economics.

This book describes a remarkable and valuable collection of tools for the study of economic dynamics under uncertainty. Professor Miao explores the tractable formulation of stochastic models combined with methods for solving and analyzing such models. His book will be a valuable reference for researchers and students seeking a comprehensive treatment of important advances.

—Lars Peter Hansen, 2013 Nobel Laureate, Economics

This book is a terrific and much-needed addition to the landscape of graduate textbooks on macroeconomics. It treats the core topic of dynamic stochastic general equilibrium models, spanning real business cycles all the way to New Keynesian models, and carefully detailing solution and estimation concepts and techniques. With its modern exposition of Dynare and the attention to numerical methods, the book is both encyclopedic as well as hands on. It will surely be in the hands of many graduate students as well as established colleagues for years to come.

—Harald Uhlig, Professor of Economics, University of Chicago

Jianjun Miao’s book provides a clear and comprehensive introduction to the analytical and numerical methods that make up the language of modern macroeconomic theory. The mix of theory, applications, and examples renders it an excellent learning tool. It is bound to become a standard reference on the subject.

—Jordi Galí, Director of CREI and Professor of Economics, Universitat Pompeu Fabra

CONTENTS: Preface. Acknowledgments. I: Dynamical Systems—Deterministic Difference Equations.Stochastic Difference Equations. Markov Processes. Ergodic Theory and Stationary Processes. II: Dynamic Optimization—Markov Decision Process Model. Finite-Horizon Dynamic Programming. Infinite-Horizon Dynamic Programming. Applications. Linear-Quadratic Models. Control under Partial Information. Numerical Methods. Structural Estimation. III: Equilibrium Analysis—Complete Markets Exchange Economies. Neoclassical Growth Models. Bayesian Estimation of DSGE Models Using Dynare. Overlapping Generations Models. Incomplete Markets Models. Search and Matching Models of Unemployment. Dynamic New Keynesian Models. IV: Further Topics—Recursive Utility. Dynamic Games. Recursive Contracts. Mathematical Appendixes— A: Linear Algebra. B: Real and Functional Analysis. C: Convex Analysis. D: Measure and Probability Theory. References. Matlab Index. Name Index. Subject Index.

ECONOMIC DYNAMICS IN DISCRETE TIMEJIANJUN MIAO, Professor of Economics, Boston University, USA.

736 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-5184-4 / ` 795.00

This book offers a unified, comprehensive, and up-to-date treatment of analytical and numerical tools for solving dynamic economic problems. The focus is on introducing recursive methods—an important part of every economist’s set of tools—and readers will learn to apply recursive methods to a variety of dynamic economic problems. The book is notable for its combination of theoretical foundations and numerical methods. Each topic

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This modern, uptodate text provides a comprehensive coverage of growth theory and empirics in a clear, easy-to-read style. It superbly synthesizes much of the existing theoretical and empirical research on the mechanisms and determinants of economic growth and convergence.

After an introductory discussion of economic growth, the book examines neoclassical growth theories, from Solow–Swan in the 1950s and Cass–Koopmans in the 1960s to the more recent refinements. This is followed by a discussion of extensions to the model, with detailed description of heterogeneity of households. The authors then turn their searchlight on endogenous growth theory, discussing, among other topics, models of endogenous technological progress, technological diffusion, and an endogenous determination of labour supply and population. They also explain the essentials of growth accounting and apply this framework to endogenous growth models. The final chapters give an empirical analysis of regions and empirical evidence on economic growth for a broad panel of countries from 1960 to 2000.

This accessible yet rigorous text, which is a beautiful blend of theory and empirical work, is intended as a text for postgraduate students of economics. It should prove equally useful to all those seriously interested in the pursuit of growth and development economics.

CONTENTS: Preface. About the Authors. Introduction. Growth Models with Exogenous Saving Rates (the Solow–Swan Model). Growth Models with Consumer Optimization (the Ramsey Model). Extensions of the Ramsey Growth Model. One-Sector Models of Endogenous Growth. Two-Sector Models of Endogenous Growth (with Special Attention to the Role of Human Capital). Technological Change: Models with an Expanding Variety of Products. Technological Change: Schumpeterian Models of Quality Ladders. The Diffusion of Technology. Labor Supply and Population. Growth Accounting. Empirical Analysis of Regional Data Sets. Empirical Analysis of a Cross Section of Countries. Appendix on Mathematical Methods. References. Index.

ECONOMIC GROWTH, 2nd ed.

ROBERT J. BARRO, Professor of Economics, Harvard University and Senior Fellow, Hoover Institution at Stanford University.XAVIER SALA-I-MARTIN, Professor of Economics, Columbia University.

672 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-2551-7 / ` 595.00

ECONOMICS

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This comprehensive introduction to economic growth presents the main facts and puzzles about growth, proposes simple methods and models needed to explain these facts, acquaints the reader with the most recent theoretical and empirical developments, and provides tools with which to analyze policy design.

The book can be used by postgraduate students of Economics and as a reference for professional economists in government or international financial organizations.

“Aghion and Howitt’s work on growth and policy has vastly increased our understanding of endogenous incentives and supportive policies that drive growth in advanced and developing countries. In this important book, they bring their own insights and the insights of other pioneers to bear on the broader context of growth. This book is accessible, fascinating and extremely useful.”

— Michael Spence Professor Emeritus, Stanford University

and Winner of the 2001 Nobel Prize in Economics

“Aghion and Howitt have produced a very important and thoughtful book which presents questions, models, and answers in a clear and constructive manner. They show how good theory can and should influence both understanding and policy. It will shape the way in which economists think about growth for years ahead.”

—Nicholas Stern Lord Stern of Brentford and IG Patel

Professor of Economics and Government, London School of Economics

CONTENTS: Preface. Introduction. Part I: Basic Paradigms of Growth Theory—Neoclassical Growth Theory. The AK Model. Product Variety. The Schumpeterian Model. Capital, Innovation, and Growth Accounting. Part II: Understanding the Growth Process—Finance and Growth. Technology Transfer and Cross-Country Convergence. Market Size and Directed Technical Change. General-Purpose Technologies. Stages of Growth. Institutions and Nonconvergence Traps. Part III: Growth Policy—Fostering Competition and Entry. Investing in Education. Reducing Volatility and Risk. Liberalizing Trade. Preserving the Environment. Promoting Democracy. Conclusion. Looking Ahead: Culture and Development. Appendix: Basic Elements of Econometrics References. Index.

ECONOMICS OF GROWTH, THE

PHILIPPE AGHION, Robert C. Waggoner Professor of Economics at Harvard University.

PETER HOWITT, Lyn Crost Professor of Social Sciences at Brown University.

520 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4064-0 / ` 525.00

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The microfinance revolution has allowed more than 150 million poor around the world to receive small loans without collateral, build up assets, and buy insurance. This book offers an accessible and engaging analysis of the global expansion of financial markets in poor communities. It introduces readers to the key ideas driving microfinance, integrating theory with empirical data and addressing a range of issues, including savings and insurance, the role of women, impact measurement, and management incentives.

This second edition has been updated throughout to reflect the latest data, with new material on commercialization, credit contracts, savings and insurance, gender, impact measurement, and governance. Appendixes and problem sets cover technical material.

The book is primarily meant for the undergraduate and postgraduate students of economics and public policy. Researchers practitioners in the field will also find the book useful.

“Anyone interested in the science behind microfinance must read this impressive book. It is written with experience in microfinance and a deep understanding of economics.”

— Muhammad Yunus, Nobel Peace Prize Laureate (2006)

“An extraordinary book, inasmuch as it explains not only the underlying rationale of microfinance but, more broadly, of finance itself.”

— Thomas Easton, Asia Business Editor, The Economist

“It is necessary to use critical economic reasoning to understand why the [microfinance] movement is such a success… This book is a splendid contribution to that goal, and will be a great help to the students, teachers, and practitioners in economics and social sciences.”

— Amartya Sen, Lamont University Professor, Harvard University, Nobel Laureate in Economics (1998).

CONTENTS: Preface. Acknowledgements. Rethinking Banking. Why Intervene in Credit Markets? Roots of Microfinance: ROSCAs and Credit Cooperatives. Group Lending. Beyond Group Lending. Savings and Insurance. Gender. Commercialization and Regulation. Measuring Impacts. Subsidy and Sustainability. Managing Microfinance. Notes. References. Abbreviations. Name. Index. Subject. Index.

ECONOMICS OF MICROFINANCE, THE, 2nd ed.

BEATRIZ ARMENDÁRIZ, is Lecturer in Economics at Harvard University, on leave from University College London, where she is Senior Lecturer in Economics.

JONATHAN MORDUCH, is Associate Professor of Public Policy and Economics at New York University.

488 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4271-2 / ` 425.00

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Public economics studies how government taxing and spending activities affect the economy—economic efficiency and the distribution of income and wealth. This comprehensive text on public economics covers the core topics of market failure and taxation as well as recent developments in both policy and the academic literature. It is unique not only in its broad scope but in its balance between public finance and public choice and its combination of theory and relevant empirical evidence.

The book covers the theory and methodology of public economics; presents a historical and theoretical overview of the public sector; and discusses such topics as departures from efficiency (including imperfect competition and asymmetric information), issues in political economy, equity, taxation, fiscal federalism, and tax competition among independent jurisdictions. Suggestions for further reading, from classic papers to recent research, appear in each chapter, as do exercises. The mathematics has been kept to a minimum without sacrificing intellectual rigor; the book remains analytical rather than discursive. This second edition has been thoroughly updated throughout. It offers new chapters on behavioral economics, limits to redistribution, international taxation, cost-benefit analysis, and the economics of climate policy. Additional exercises have been added and many sections revised in response to advice from readers of the first edition.

CONTENTS: Preface to Second Edition. Preface to First Edition. List of Figures. I: Public Economics and Economic Efficiency—An Introduction to Public Economics. Equilibrium and Efficiency. Behavioral Economics. II: Government—Public Sector Statistics. Theories of the Public Sector. III: Departures from Efficiency—Public Goods. Club Goods and Local Public Goods. Externalities. Imperfect Competition. Asymmetric Information. IV: Political Economy—Voting. Rent-Seeking. V: Equity and Distribution—Optimality and Comparability. Inequality and Poverty. VI: Taxation—Commodity Taxation. Income Taxation. Tax Evasion. Limits to Redistribution. VII: Multiple Jurisdictions—Fiscal Federalism. Fiscal Competition. Issues in International Taxation. VIII: Issues of Time—Intertemporal Efficiency. Social Security. Economic Growth. IX: Applications—Cost–Benefit Analysis. Economics of Climate Policy. Index.

INTERMEDIATE PUBLIC ECONOMICS, 2nd ed.

JEAN HINDRIKS is Professor in the Economics Department and Codirector of the Center for Operations Research and Econometrics (CORE) at the Université catholique de Louvain. GARETH D. MYLES is Head of Department and Professor of Economics at the University of Exeter and a Research Fellow at the Institute for Fiscal Studies. He is the author of Public Economics.

1012 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4944-5 / ` 995.00

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The study of industrial organization (IO)—the analysis of the way firms compete with one another—has become a key component of economics and of such related disciplines as finance, strategy, and marketing. This book provides an issue-driven introduction to industrial organization. Although formal in its approach, it is written in a way that requires only basic mathematical training. It includes a vast array of examples, from both within and outside the United States. This second edition has been thoroughly updated and revised.

In addition to updated examples, this edition presents a more systematic treatment of public policy implications. It features added advanced sections, with analytical treatment of ideas previously presented verbally; and exercises, which allow for a deeper and more formal understanding of each topic. The new edition also includes an introduction to such empirical methods as demand estimation and equilibrium identification. Supplemental material is available online.

“Luis Cabral has updated his industrial organization textbook. The revision retains the strengths of the original: it is clear and succinct, with an emphasis on how the field addresses important applications. The many new examples ensure the relevance of the material.”

—Robert Porter, William R. Kenan Jr., Professor of Economics, Northwestern University; coeditor of Handbook of Industrial Organization

“Introduction to Industrial Organization is a rare commodity: an intellectually rigorous textbook that is elegant, concise, and a pleasure to read. Cabral manages to communicate difficult ideas precisely while keeping the focus squarely on issues that matter for the real world. It is the ideal introduction for undergraduates, MBA students, or anyone else looking for a non-technical overview of the field.”

—Matthew Gentzkow, Professor of Economics, Stanford University “Cabral’s Introduction to Industrial Organization is clear, precise, relevant, even fun. This delightful volume is your best choice for crisp and accessible coverage of IO theory. The second edition sparkles just like the first.”

—Carl Shapiro, Transamerica Professor of Business Strategy, Haas School of Business, University of California at Berkeley

“This is a wonderful textbook: concise, precise, and full of up-to-date examples. If you are looking for an intuitive treatment of industrial organization that is rigorous and yet doesn’t bog you down in excessive detail, this is a great choice.”

—Ali Hortacsu, Ralph and Mary Otis Isham Professor of Economics, University of Chicago“Luis Cabral’s book covers all the basic topics in Industrial Organization in an easily accessible way. It is a perfect exposition for an undergraduate class or for a professional who wants to become acquainted with the topics IO deals with and why they are important. He has done the field a great service.”

—Ariel Pakes, Thomas Professor of Economics, Harvard University; editor, Microeconomic Insights “Cabral introduces the theoretical ideas and frameworks of contemporary IO expertly, succinctly, and with flair. Motivating examples and stylized facts bring the theories alive. The new edition of Introduction to Industrial Organization updates and improves the organization of the first, while keeping its expository charms.”

—Michael H. Riordan, Laurans A. Arlene Mendelson, Professor of Economics, Columbia University

CONTENTS: Preface. Acknowledgments. What is Industrial Organization? Part 1—Microeconomics Foundations. Consumers. Firms. Competition, Equilibrium, and Efficiency. Market Failure and Public Policy. Price Discrimination. Part 2—Oligopoly. Games and Strategies. Oligopoly. Collusion and Price Wars. Part 3—Entry and Market Structure. Market Structure. Horizontal Mergers. Market Foreclosure. Part 4—Non-Price Strategies. Vertical Relations. Product Differentiation. Innovation. Networks.

INTRODUCTION TO INDUSTRIAL ORGANIZATION, 2nd ed.

LUÍS M.B. CABRAL is Paganelli-Bull Professor of Economics and International Business and Chair of the Department of Economics at the Leonard N. Stern School of Business at New York University.

440 pp. / 20.0 × 25.0 cm / ISBN-978-93-88028-26-4 / ` 595.00

ECONOMICS

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This landmark text combines depth and breadth of coverage with recent, cutting-edge work in all the major areas of modern labor economics. Its command of the literature and its coverage of the latest theoretical, methodological, and empirical developments make it a valuable resource for postgraduate students of Economics as well as practising labour economists. This second edition has been substantially updated and augmented. It incorporates examples drawn from many countries, and presents empirical methods using contributions that have proved to be milestones in labour economics. This edition devotes more space to the analysis of public policy and the levers available to policy makers, with new chapters on such topics as discrimination, globalization, income redistribution, employment protection, and the minimum wage or labor market programs for the unemployed. Theories are explained on the basis of the simplest possible models, which are in turn related to empirical results. Mathematical appendixes provide a toolkit for understanding the models.

This is the book to use for a graduate labor course anywhere in the world. The topics and research covered in the new edition are right up-to-date, and the level of the book is perfect for Ph.D. students. I used the earlier edition in my course and would use this too.

—Daniel S. Hamermesh, Professor in Economics, Royal Holloway University of London, and Sue Killam Professor Emeritus of Economics, University of Texas at Austin

Labor Economics brings facts to motivate theory that is carefully exposed. Empirical methods and results are integrated with the theory and the book covers an exceptional range of topics, models, and empirical research. The depth and the range of topics make Labor Economics a required volume on the shelves of all academic economists.

—Zvi Eckstein, Dean, The School of Economics, The Interdisciplinary Center (IDC) Herzliya

This is an impressive textbook. It will show graduate students that modern labor economics is an exciting area of research.

—Erik Plug, Professor of Economics, University of Amsterdam

This is an excellent textbook that provides a comprehensive introduction to the principles of modern labor economics and clear, rigorous, intuitive expositions of the major models students will need to navigate the field. Each chapter begins with the basic theory underlying modern applications, and then leads into an overview of recent empirical implementations, usually focusing on one or two relevant papers, and discusses the common econometric challenges associated with each topic. This layout is very useful and intuitive for thinking about the problems and for tying theory to empirics. The book was a pleasure to read and helped shape my thinking about the proper way to introduce ideas into a graduate labor course and to demonstrate the power and flexibility of the models.

—Laura Turner, Assistant Professor of Economics, University of Toronto

CONTENTS: Preface. Introduction. Acknowledgements. Part One: Labor Supply and Demand Behaviors—Labor Supply. Labor Demand. Competitive Equilibrium and Compensating Wage Differentials. Education and Human Capital. Part Two: Imperfectly Competitive Labor Markets—Job Search. Contracts, Risk-Sharing, and Incentive. Collective Bargaining and Labor Unions. Discrimination. Part Three: Job Creations, Job Destruction, and Unemployment—Equilibrium Unemployment. Technological Progress, Unemployment, and Inequality. Globalization, Employment, and Inequality. Part Four: Public Policies—Income Redistribution. Insurance Policies. Active Labor Market Policies. Mathematical Appendices. Name Index. Subject Index.

LABOR ECONOMICS, 2nd ed.PIERRE CAHUC is Professor of Economics at École Polytechnique, Director of the Macroeconomic Laboratory at CREST-ENSAE, Program Director at IZA, Research Fellow at CEPR and member of the Council of Economic Analysis of the Prime Minister.STÉPHANE CARCILLO is Associate Professor of Economics at the University of Paris 1, Panthéon-Sorbonne.ANDRÉ ZYLBERBERG is Emeritus Research Director at the Centre National de la Recherche Scientifique (CNRS), and member of the Paris School of Economics (PSE).

1080 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-5102-8 / ` 975.00

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The text provides the first comprehensive description and evaluation of macroeconomic theory in many years.

The main purpose of the book is to characterize and explain fluctuations in output, unemployment, and movement in prices. Topics include consumption and investment, the implications of finite horizons, goals of economic policy, fiscal policy, and dynamic inconsistency.

Written as a text for postgraduate students, the book also presents topics in a self-contained way that makes it a suitable reference for professional economists. A background in macroeconomics, statistics and econometrics is the prerequisite for studying the text.

KEY FEATURES

• Complete discussions on various models appropriate to each topic.

• A special chapter analyses the goals of economic policy, monetary policy, fiscal policy, and dynamic inconsistency.

• Basic models are described and extended to take into account the presence of uncertainty and stochastic fluctuations.

• Two exclusive chapters cover what-may-be called new Keynesian economics.

CONTENTS: Preface. Introduction. Consumption and Investment: Basic Infinite Horizon Models. The Overlapping Generations Model. Money. Multiple Equilibria, Bubbles, and Stability. Optimal Consumption, Investment, and Inventory Behavior. Competitive Equilibrium Business Cycles. Nominal Rigidities and Economic Fluctuations. Goods, Labor, and Credit Markets. Some Useful Models. Monetary and Fiscal Policy Issues. Name Index. Subject Index.

LECTURES ON MACROECONOMICS

OLIVIER JEAN BLANCHARD, Professor of Economics at Massachusetts Institute of Technology.STANLEY FISCHER, Professor of Economics at Massachusetts Institute of Technology and Vice-President of Development Economics at the World Bank.

664 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-1042-1 / ` 450.00

ECONOMICS

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This book offers a rigorous but nontechnical treatment of major topics in urban economics. To make the book accessible to a broad range of readers, the analysis given is diagrammatic rather than mathematical. The book, though nontechnical, relies on rigorous economic reasoning. In contrast to the cursory theoretical development often found in other textbooks, it offers a thorough and exhaustive treatment of models relevant to each topic, with the goal of revealing the logic of economic reasoning while also teaching urban economics.

The book contains footnotes throughout pointing to relevant exercises, which appear at the back of the book. These 22 extended exercises (containing 125 individuals parts) develop numerical examples, based on the models analyzed in the chapters.

This book is a very nice presentation of basic urban material. Brueckner has a great talent for taking complex ideas and models and putting them in readily accessible frameworks that capture the key points. Moreover, he uses simple examples to illustrate the issues. The material should be accessible to advanced undergraduates and will provide insights for graduate students as well.

—J. Vernon Henderson, Eastman Professor of Political Economy and Professor of Economics and Urban Studies, Brown University

Jan Brueckner’s lucid Lectures on Urban Economics is a rigorous, but non-technical, analysis of the major topics in the field. The lectures survey topics of broad appeal to students, and they provide just enough detail—clear diagrams and tightly written prose—to support a definitive analysis. This slim volume has the hallmark of an excellent undergraduate text.

—John M. Quigley, I. Donald Turner Distinguished Professor and Professor of Economics, University of California, Berkeley

CONTENTS: Preface. Why Cities Exist. Analyzing Urban Spatial Structure. Modification of the Urban Model. Urban Sprawl and Land-Use Controls. Freeway Congestion. Housing Demand and Tenure Choice. Housing Policies. Local Public Goods and Services. Pollution. Crime. Urban Quality-of-Life Measurement. Exercises. References. Index.

LECTURES ON URBAN ECONOMICS

JAN K. BRUECKNER, Professor of Economics at the University of California, Irvine, and former editor of the Journal of Urban Economics.

296 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4752-6 / ` 425.00

ECONOMICS

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ECONOMICS

This introductory text offers an alternative to the encyclopedic, technically oriented approach taken by traditional textbooks on macroeconomic principles. Concise and non-technical but at the same time rigorous, its goal is not to teach students to shift curves on diagrams but to help them understand fundamental macroeconomic concepts and their real-world applications. This is accomplished by the clear exposition of introductory macroeconomic theory provided in the book along with more than 700 two/three sentence “news clips” of economics media coverage that serve as illustrations/exercises of the concepts discussed.

This updated edition includes subprime mortgage crisis and other subjects; new “curiosities” (boxed expositions of important topics) have been added, as have “news clips” about recent events; and the most challenging end-of-chapter questions are now separated from the less challenging. Many chapters include a set of numerical exercises (quite different from those found in traditional texts); a sample exam question appears at the end of each section within a chapter; and a test bank of multiple-choice questions (with answers) is available online. Technical material appears in appendices following each chapter. Other appendices offer answers to the sample exam questions and the even-numbered end-of-chapter exercises.

By setting aside much of the formal apparatus of ‘curve-shifting’ economics, Macroeconomic Essentials focuses attention just where it should be—on understanding key concepts and on thinking. At the center of economics is, after all, the study of human behavior, not the art of mathematical manipulation.

—Lloyd J. Dumas, Professor of Economics University of Texas at Dallas and author of The Peacekeeping Economy

In the third edition of Macroeconomics Essentials, Peter Kennedy sets himself a difficult task and succeeds beautifully. Kennedy’s textbook marries impressive breadth, simplicity, and rigor. He provides a concise and non-technical overview of the core analytical concepts in macroeconomics who are tethered to bits of relevant empirical evidence. This is a particularly useful textbook for instructors outside of economics departments that want to bring students quickly up to speed on the principles that underlie recent political economic trends and events (including the subprime crisis).

—Stephen Nelson, Northwestern University

CONTENTS: Preface. Introduction. The Basics of Supply and Demand, and a Big Picture. Measuring GDP and Inflation. Unemployment. The Role of Aggregate Demand. The Supply Side. Growth and Productivity. The Money Supply. The Monetarist Rule. Monetary Policy and Interest Rates. Real versus-Nominal Interest Rates. Stagflation. The Balance of Payments. Policy in an Open Economy. Purchasing Power Parity. Interest-Rate Parity. Appendix A Answers to Sample Exam Questions, Appendix B Answers to Even Numbered Exercises. Glossary. Index.

MACROECONOMIC ESSENTIALS Understanding Economics in the News 3rd ed.

PETER E. KENNEDY, formerly Professor Emeritus of Economics at Simon Fraser University.

480 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4486-0 / ` 495.00

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This text offers a comprehensive presentation of the mathematics required to tackle problems in economic analyses. To give a better understanding of the mathematical concepts, the text follows the logic of the development of mathematics rather than that of an economics course. The only prerequisite is high school algebra, but the book goes on to cover all the mathematics needed for undergraduate economics. It is also a useful reference for graduate students. After a review of the fundamentals of sets, numbers, and functions, the book covers limits and continuity, the calculus of functions of the one variable, linear algebra, multivariate calculus, and dynamics. To develop the student’s problem-solving skills, the book works through a large number of examples and economic applications.

This streamlined third edition offers an array of new and updated examples. Additionally, lengthier proofs and examples are provided on the book’s website http://mitpress.mit.edu/math_econ3. The book and the Web material are cross-referenced in the text. A Student Solutions Manual is available in ebook form, and instructors are able to access online the Instructor’s Manual, which includes PowerPoint slides.

Mathematics is the language of economics, and this book is an excellent introduction to that language.

— George J. Mailath, Walter H. Annenberg Professor in the Social Sciences and Professor of Economics, University of Pennsylvania

While there are many mathematics texts for economics available, this one is by far the best. It covers a comprehensive range of techniques with interesting applications, and the numerous worked examples and problems are a real bonus for the instructor. Teaching a course with this book is enjoyable and easy.

— Kevin Denny, University College Dublin

CONTENTS: Preface. Part I: Introduction and Fundamentals—Introduction. Review of Fundamentals. Sequences, Series, and Limits. Part II: Univariate Calculus and Optimization— Continuity of Functions. The Derivative and Differential for Functions of One Variable. Optimization of Functions of One Variable. Part III: Linear Algebra—Systems of Linear Equations. Matrices. Determinants and the Inverse Matrix. Some Advanced Topics in Linear Algebra. Part IV: Multivariate Calculus—Calculus for Functions of n-Variables. Optimization of Functions of n-Variables. Constrained Optimization. Comparative Statics. Concave Programming and the Kuhn–Tucker Conditions. Part V: Integration and Dynamic Methods—Integration. An Introduction to Mathematics for Economic Dynamics. Linear, First-Order Difference Equations. Nonlinear, First-Order Difference Equations. Linear, Second-Order Difference Equations. Linear, First-Order Differential Equations. Nonlinear, First-Order Differential Equations. Linear, Second-Order Differential Equations. Simultaneous Systems of Differential and Difference Equations. Optimal Control Theory. Answers. Index.

MATHEMATICS FOR ECONOMICS, 3rd ed.

MICHAEL HOY, JOHN LIVERNOIS, CHRIS McKENNA, and THANASIS STENGOS are with the Department of Economics, University of Guelph, Ontario, Canada. RAY REES, Center for Economic Studies (CES), University of Munich.

976 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4648-2 / ` 650.00

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This book by a leading authority on monetary policy offers a unique view of the subject from the perspectives of both scholar and practitioner. The book discusses the changes in the conduct of monetary policy in recent years, in particular the turn to inflation targeting. It sums up “Everything You Wanted to Know about Monetary Policy Strategy, But Were Afraid to Ask,” and reflects on what we have learnt about monetary policy over the last thirty years.

The book blends theory, empirical evidence, and extensive case studies of monetary policy in advanced and emerging market and transition economies. Throughout, its focus is on the following key areas:

• the importance of price stability and a nominal anchor

• fiscal and financial preconditions for achieving price stability

• central bank independence as an additional precondition

• central bank accountability

• the rationale for inflation targeting

• the optimal inflation target

• central bank transparency and communication

• the role of asset prices in monetary policy.

CONTENTS: Preface. I: How Did We Get Here?—Fundamental Issues in the Conduct of Monetary Policy. What Should Central Banks Do? The Transmission Mechanism and the Role of Asset Prices in Monetary Policy. The Role of Output Stabilization in the Conduct of Monetary Policy. Can Central Bank Transparency Go Too Far? Is There a Role for Monetary Aggregates in the Conduct of Monetary Policy? Rethinking the Role of NAIRU in Monetary Policy: Implications of Model Formulation and Uncertainty. II: Monetary Policy Strategy in Advanced Economies—Central Bank Behavior and the Strategy of Monetary Policy: Observations from Six Industrialized Countries. Inflation Targeting: A New Framework for Monetary Policy? International Experience with Different Monetary Policy Regimes. Why the Federal Reserve Should Adopt Inflation Targeting. III: Monetary Policy Strategy in Emerging Market and Transition Economies—Inflation Targeting in Emerging Market Countries. Monetary Policy Strategies for Latin America. Monetary Policy Strategies for Emerging Market Countries: Lessons from Latin America. Inflation Targeting in Transition Economies: Experience and Prospects. A Decade of Inflation Targeting in the World: What Do We Know and What Do We Need to Know? The Dangers of Exchange-Rate Pegging for Emerging Market Countries. The Mirage of Exchange-Rate Regimes for Emerging Market Countries. IV: What Have We Learned?—Everything You Wanted to Know about Monetary Policy Strategy, but Were Afraid to Ask. Sources. Index.

MONETARY POLICY STRATEGY

FREDERIC S. MISHKIN.

560 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3957-6 / ` 495.00

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This text presents a comprehensive treatment of the most important topics in monetary economics, focusing on the primary models monetary economists have employed to address topics in theory and policy. It covers the basic theoretical approaches, shows how to do simulation work with the models, and discusses the full range of frictions that economists have studied to understand the impacts of monetary policy.

This third edition reflects the latest advances in the field, incorporating new or expanded material on such topics as monetary search equilibria, sticky information, adaptive learning, state-contingent pricing models, and channel systems for implementing monetary policy. Much of the material on policy analysis has been reorganized to reflect the dominance of the new Keynesian approach. The book continues to be not only the leading text in the field but also the standard reference for academics and researchers.

Carl Walsh’s Monetary Theory and Policy is an indispensable bridge between theory and practice. The book is a comprehensive overview of the field. Each topic is addressed by a few models exposited with mathematical rigor and policy insight. The depth and breadth of the model presentations make the book an essential reference for students and central bank economists alike.

—Marvin Goodfriend, Tepper School of Business, Carnegie Mellon University

CONTENTS: Preface. Introduction. Empirical Evidence on Money, Prices, and Output. Money-in-the-Utility Function. Money and Transactions. Money and Public Finance. Money in the Short Run: Informational and Portfolio Rigidities. Money in the Short Run: Nominal Price and Wage Rigidities. Discretionary Policy and Time Inconsistency. New Keynesian Monetary Economics. Money and the Open Economy. Financial Markets and Monetary Policy. Monetary Policy Operating Procedures. References. Name Index. Subject Index.

MONETARY THEORY AND POLICY, 3rd ed.

CARL E. WALSH, Professor of Economics, University of California, Santa Cruz.

648 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4252-1 / ` 495.00

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This book by award winning author Jean Tirole (Nobel Memorial Prize in Economic Sciences) gives a straightforward account of developments in the theory of industrial economics and blends them into the tradition of industrial organization. The text primarily presents accomplishments of what the author calls, ‘The Second Wave’, which began in the 1970s and made a sizeable impact in the theoretical aspects of industrial organization, though the earlier contributions that laid the foundation are not forgotten.

The book is divided into two parts. The first part features market behaviour and considers monopolist’s choices of price and quality, the spectrums of goods advertising and the distribution of structure. Part two analyses the choice price, capacity, product positioning, research and development, and other strategic variables in a comparatively monopolistic market.

CONTENTS: Preface. Introduction. The Theory of the Firm. I: The Exercise of Monopoly Power—Monopoly. Product Selection, Quality, and Advertising. Price Discrimination. Vertical Control. II: Strategic Interaction—Short-Run Price Competition. Dynamic Price Competition and Tacit Collusion. Product Differentiation: Price Competition and Non-Price Competition. Entry, Accommodation, and Exit. Information and Strategic Behavior: Reputation, Limit Pricing, and Predation. Research and Development and the Adoption of New Technologies. Noncooperative Game Theory: A User’s Manual. Review Exercises. Index.

THEORY OF INDUSTRIAL ORGANIZATION, THE

JEAN TIROLE.

496 pp. / 21.6 × 27.8 cm / ISBN-978-81-203-1049-0 / ` 595.00

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1

This book offers an overview of a range of proven and new methods, discussing both theoretical and practical aspects of biomedical signal analysis and interpretation.

It describes a broad range of methods, including continuous and discrete Fourier transforms, independent component analysis (ICA), dependent component analysis, neural networks, and fuzzy logic methods. It also discusses the applications of these theoretical tools to practical problems in everyday biosignal processing.

The book can be used as a text by the undergraduate as well as postgraduate students of the subject.

CONTENTS: Preface. I. Methods—Foundations of Medical Imaging and Signal Recording. Spectral Transformations. Information Theory and Principal Component Analysis. Independent Component Analysis and Blind Source Separation. Dependent Component Analysis. Pattern Recognition Techniques. Fuzzy Clustering and Genetic Algorithms. II. Applications—Exploratory Data Analysis Methods for fMRI. Low-frequency Functional Connectivity in fMRI. Classification of Dynamic Breast MR Image Data. Dynamic Cerebral Contrast-enhanced Perfusion MRI. Skin Lesion Classification. Microscopic Slice Image Processing and Automatic Labeling. NMR Water Artifact Removal. References. Index.

BIOMEDICAL SIGNAL ANALYSIS Contemporary Methods and Applications

FABIAN J. THEIS is head of the Computational Modeling in Biology Group at the Institute of Bioinformatics and Systems Biology, German Research Center for Environmental Health, Neuherberg, Germany. ANKE MEYER-BASE is Associate Professor in the Department of Scientific Computing at Florida State University.

432 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4263-7 / ` 450.00

ENGINEERING Electronics and Electrical Engineering

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This book offers a comprehensive treatment of VHDL and its applications to the design and simulation of real, industry-standard electronic circuits. It focuses on the use of VHDL rather than solely on the language itself. In other words, besides explaining VHDL in detail, it shows why, how, and which type of circuits are inferred from the language constructs.

The book also includes a detailed analysis of circuit simulation with VHDL test benches in all of the four categories (nonautomated, fully automated, functional and timing) of simulations. A rigorous discussion is thus made between VHDL for synthesis and VHDL for simulations.

In a nutshell, the book teaches all the indispensable features of VHDL. It also reviews the fundamental concepts of digital electronics and digital design, resulting in a very practical, self contained approach.

In both synthesis and simulation cases the VHDL codes in all design examples are complete, and include circuit diagrams, physical synthesis in FPGAs (Field Programmable Gate Arrays), simulation results, and explanatory comments.

All of the four VHDL editions (1987, 1993, 2002 and 2008) are covered.

The book is mainly intended for the students of Electrical Engineering and Computer Science and Engineering. It will also be useful to the VHDL and digital design engineers and practitioners in the industry.

“Volnei Pedroni explains what designers really need to know to build hardware with VHDL. This book sets the standard for how hardware description languages should be taught.”

— David Money HarrisProfessor of Engineering

Harvey Mudd College.

CONTENTS: Preface. I. Circuit-Level VHDL—Introduction. Code Structure. Data Types. Operators and Attributes. Concurrent Code. Sequential Code. SIGNAL and VARIABLE. II. System-Level VHDL—PACKAGE and COMPONENT. FUNCTION and PROCEDURE. Simulation with VHDL Testbenches III. Extended and Advanced Designs—VHDL Design of State Machines. VHDL Design with Basic Displays. VHDL Design of Memory Circuits. VHDL Design of Serial Communications Circuits. VHDL Design of VGA Video Interfaces. VHDL Design of DVI Video Interfaces. VHDL Design of FPD-Link Video Interfaces. Appendices. Bibliography. Index.

CIRCUIT DESIGN AND SIMULATION WITH VHDL, 2nd ed.VOLNEI A. PEDRONI, Professor of Electronics Engineering at Brazil’s Federal University of Technology.

632 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4301-6 / ` 645.00

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3ENGINEERING Electronics and Electrical Engineering

As book review editor of the IEEE Transactions on Neural Networks, Mohamad Hassoun has had the opportunity to assess the multitude of books on artificial neural networks that have appeared in recent years. Now, in Fundamental of Artificial Neural Networks, he provides the first systematic account of the artificial neural network paradigms by identifying clearly the fundamental concepts and major methodologies that underlie most of the current theory and practice employed by neural network researchers. This text emphasizes the fundamental theoretical aspects of the computational capabilities and the learning abilities of artificial neural networks.

The text assumes that the reader is conversant with the concept of a system and the notion of a “state”, as well as with the basic elements of Boolean algebra and switching theory.

CONTENTS: Preface. Acknowledgment. Abbreviations. Symbols. Threshold Gates. Computational Capabilities of Artificial Neural Networks. Learning Rules. Mathematical Theory of Neural Learning. Adaptive Multilayer Neural Networks I. Adaptive Multilayer Neural Networks II. Associative Neural Memories. Global Search Methods for Neural Networks. References. Index.

FUNDAMENTALS OF ARTIFICIAL NEURAL NETWORKS

MOHAMAD H. HASSOUN, Associate Professor, Department of Electrical and Computer Engineering, Wayne State University.

540 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-1356-9 / ` 595.00

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Signal processing and neural computation have, for long, significantly but separately influenced many disciplines. New researches and the fact that highly sophisticated kinds of signal processing and elaborate computations are performed side by side in the brain, however, show that these two fields have much to teach each other as well.

This book discusses the cross-fertilization of these two streams and compiles work of leading researchers from both the areas that promote interaction between both the disciplines.

This text is primarily meant for the advanced undergraduate and postgraduate students of bioinformatics and biomedical engineering. However, having evolved from two different fields, the text is also useful for the senior students of electronics and communication engineering, computer science and engineering, and electrical engineering.

CONTENTS: Series Foreword. Preface. Modeling the Mind: From Circuits to Systems. Empirical Statistics and Stochastic Models for Visual Signals. The Machine Cocktail Party Problem. Sensor Adaptive Signal Processing of Biological Nanotubes (Ion Channels) at Macroscopic and Nano Scales. Spin Diffusion: A New Perspective in Magnetic Resonance Imaging. What Makes a Dynamical System Computationally Powerful? A Variational Principle for Graphical Models. Modeling Large Dynamical Systems with Dynamical Consistent Neural Networks. Diversity in Communication: From Source Coding to Wireless Networks. Designing Patterns for Easy Recognition: Information Transmission with Low-Density Parity-Check Codes. Turbo Processing. Blind Signal Processing Based on Data Geometric Properties. Game-Theoretic Learning. Learning Observable Operator Models via the Efficient Sharpening Algorithm. References. Contributors. Index.

NEW DIRECTIONS IN STATISTICAL SIGNAL PROCESSING From Systems to Brains

Edited by:SIMON HAYKIN, JOSÉ C. PRÍNCIPE, TERRENCE J. SEJNOWSKI, and JOHN MCWHIRTER.

524 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3240-9 / ` 495.00

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5ENGINEERING Mechanical Engineering

This comprehensive textbook is unique in its design-focused approach to turbomachinery and gas turbines. It offers students of B.Tech/B.E. and M.Tech/M.E. Mechanical Engineering and practicing engineers methods for configuring these machines to perform with the highest possible efficiency. Examples and problems are based on the actual design of turbomachinery and turbines.

After an introductory chapter that outlines the goals of the book and provides definitions of terms and parts, the book offers a brief review of the basic principles of thermodynamics and efficiency definitions. The rest of the book is devoted to the analysis and design of real turbomachinery configurations and gas turbines, based on a consistent application of thermodynamic theory and a more empirical treatment of fIuid dynamics that relies on the extensive use of design charts. Topics include turbine power cycles, diffusion and diffusers, the analysis and design of three-dimensional free-stream flow, and combustion systems and combustion calculations. The second edition updates every chapter, adding material on subjects that include flow correlations, energy transfer in turbomachines, and three-dimensional design. A solutions manual is available for adopting instructors.

A welcome return. Any book can present equations and algorithms; these authors desire to give us insight. They want to enable us to reason why certain choices are better than others and understand the consequences of our decisions. I have appreciated this book for a long time. It is not harder, but makes us smarter.

—Andrew R. Mech, Professor of Mechanical Engineering, Rose-Hulman Institute of Technology

CONTENTS: List of figures. List of illustrations. List of tables. Preface. Note to readers. Nomenclature. A. brief history of turbomachinery. Introduction. Review of thermodynamics. Thermodynamics of gas-turbine cycles. Diffusion and diffusers. Energy transfer in turbomachines. Three-dimensional velocity diagrams for axial turbomachines. The design and performance prediction of axial-fIow turbines. The design and performance prediction of axial-fIow compressors. Design methods for radial-fIow turbomachines. Convective heart transfer in blade cooling and heat-exchanger design. Gas-turbine starting and control-system principles. Combustion systems and combustion calculations. Mechanical-design considerations. A: Properties of air and combustion products. B: Collected formulae. C: Some constants. D: Conversion factors. Index.

DESIGN OF HIGH-EFFICIENCY TURBOMACHINERY AND GAS TURBINES, THE, 2nd ed.

DAVID GORDON WILSON, Professor of Mechanical Engineering Emeritus at MIT. He is the author of Bicycling Science.THEODOSIOS KORAKIANTIS, Dean of the Parks College of Engineering, Aviation, and Technology; Professor of Aerospace and Mechanical Engineering; and Professor of Biomedical Engineering at Saint Louis University.

624 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-5185-1 / ` 795.00

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ENGINEERING Mechanical Engineering

Engineering Systems is an emerging field that is at the intersection of engineering, management, and the social sciences. Designing complex systems requires not only traditional engineering skills but also knowledge of public policy issues and awareness of societal norms and preference. As scale, scope, and complexity increase, engineers consider technical and social issues together in a highly integrated way as they design flexible, adaptable, robust systems that can be easily modified and reconfigured to satisfy changing requirements and new technological opportunities.

This book offers a comprehensive examination of such systems and the associated emerging field of study. Through scholarly discussion, concrete examples, and history, the authors consider the engineer’s changing role, new ways to model and analyze these systems, the impacts on engineering education, and the future challenges of meeting human needs through the technologically enabled systems of today and tomorrow.

I believe that this book is a first. It defines a new and emerging discipline—engineering systems. The authors give us the theories, concepts, and tools that are necessary to situate engineering problems in a broader and fundamentally relevant context, thereby permitting more complete and useful solutions to current challenges.

—John S. Reed, Chairman of the Corporation, MIT

This book is timely. New thinking is urgently needed in order to manage and thrive in our world of complex systems and systems of systems. Our students, the leaders of tomorrow, must learn and apply engineering systems skills in business, communications, transportation, energy, education, healthcare delivery, public health, and global health. This book marvelously demonstrates why the system-thinking skills required must include the domains of strategic planning, public policy, social sciences, management, and engineering.

—Denis A. Cortese, M.D., Foundation Professor and Director of the Healthcare Delivery and Policy Program, Arizona State University; President of the Healthcare Transformation Institute;

Emeritus President and CEO of Mayo Clinic

CONTENTS: Series Foreword. Foreword by Charles M. Vest. Preface. From Inventions to Systems. What Is an Engineering System. (Re)Thinking about Systems. Life-Cycle Properties of Engineering Systems: The Ilities. Modeling and Analyzing Engineering Systems. Partially Designed, Partially Evolved. Engineering Systems Research and Education. What the Future Holds. Appendix: Engineering Systems Terms and Definitions. Notes. Index.

ENGINEERING SYSTEMS Meeting Human Needs in a Complex Technological WorldOLIVIER L. de WECK is Associate Professor of Aeronautics and Astronautics and Engineering Systems at MIT as well as Associate Director of the Engineering Systems Division.DANIEL ROOS, Founding Director of Engineering Systems Division, is Japan Steel Industry Professor of Engineering Systems and Civil and Environmental Engineering at MIT.CHRISTOPHER L. MAGEE is Professor of the Practice of Mechanical Engineering and Engineering Systems at MIT, where he is also Codirector of the International Design Center of Singapore University of Technology and Design and MIT.

232 pp. (Hard Cover) / 15.3 × 22.9 cm / ISBN-978-81-203-4753-3 / ̀ 595.00

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This book provides a high-level overview of why flexibility in design is needed to deliver significantly increased value. It describes in detail methods to identify, select, and implement useful flexibility. The book is unique in that it explicitly recognizes that future outcomes are uncertain. It thus presents forecasting, analysis, and evaluation tools especially suited to this reality. Appendixes provide expanded explanations of concepts and analytic tools.

Forecasts are a necessary part of planning major capital projects. The problem is these forecasts are almost always wrong. It is very important to recognize this truth and even more important to shield projects from the potential downsides of an uncertain future by building in flexibility. Professors de Neufville and Scholtes have provided a clear and practical guide, well supported by specific examples, on the science of identifying, justifying, and implementing flexibility in design.

—Lloyd A. McCoomb, President and Chief Executive Officer Toronto Pearson International Airport

de Neufville and Scholtes convincingly show us that enhancing flexibility in engineering design can help us a lot to improve our performance. Anchored in their research, the book is an easy read because both authors are also excellent pedagogues who take the reader step by step through some difficult materials. This book is a real must-read for anybody involved in large-scale projects.

—Arnoud de Meyer, President and Professor Singapore Management University

CONTENTS: Series Foreword; Acknowledgments; Introduction. Value I: High-Level Overview—Flexible Design: Its Need and Value. Recognition of Uncertainty. Flexibility Can Increase Value II: Method of Analysis—Phase 1: Estimating the Distribution of Future Possibilities. Phase 2: Identifying Candidate Flexibilities. Phase 3: Evaluating and Choosing Flexible Designs. Phase 4: Implementing Flexibility. Epilog: The Way Ahead. Appendices—A: Flaw of Averages. B: Discounted Cash Flow Analysis. C: Economics of Phasing. D: Monte Carlo Simulation. E: Dynamic Forecasting. F: Financial Options Analysis. Notes. Bibliography. Index.

FLEXIBILITY IN ENGINEERING DESIGN

RICHARD de NEUFVILLE is Professor of Engineering Systems, and Civil and Environmental Engineering at MIT. STEFAN SCHOLTES is Dennis Gillings Professor of Health Management and Academic Director of the Centre for Health Leadership and Enterprise at the Judge Business School, University of Cambridge.

312 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4751-9 / ` 595.00

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Mechanical EngineeringENGINEERING

Foundations of Robotics presents the fundamental concepts and methodologies for the analysis, design, and control of robot manipulators. It explains the physical meanings of the concepts and equations used, and it provides, in an intuitively clear way, the necessary background in kinetics, linear algebra, and control theory. Illustrative examples appear throughout.

CONTENTS: Preface. Overview of Robotic Mechanisms and Controller. Kinematics. Dynamics. Manipulability. Position Control. Force Control. Control of Redundant Manipulators. Appendices—1: Function atan2. 2: Pseudo-Inverses. 3: Singular-Value Decomposition. 4: Lyapunov Stability Theory. Solutions to Selected Exercises. Index.

FOUNDATIONS OF ROBOTICS Analysis and Control

TSUNEO YOSHIKAWA, Division of Applied Systems Science, Faculty of Engineering, Kyoto University.

300 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-1361-3 / ` 175.00

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Digital artifacts from iPads to databases pervade our lives, and the design decisions that shape them affect how we think, act, communicate, and understand the world. But the pace of change has been so rapid that technical innovation is outstripping design. Interactors are often mystified and frustrated by their enticing but confusing new devices; meanwhile, product design teams struggle to articulate shared and enduring design goals. With Inventing the Medium, the author provides a unified vocabulary and a common methodology for the design of digital objects and environments. It is be an essential guide for both students and practitioners in the evolving field of interaction design.

The author explains that innovative interaction designers should think of all objects made with bits—whether games or Web pages, robots or the latest killer apps—as belonging to a single new medium: the digital medium. Designers can speed the process of useful and lasting innovation by focusing on the collective cultural task of inventing this new medium. Exploring strategies for maximizing the expressive power of digital artifacts, Murray identifies and examines four representational affordances of digital environments that provide the core palette for designers across applications: computational procedures user participation, navigable space, and encyclopedic capacity.

Each chapter includes a set of Design Explorations—creative exercises for students and thought experiments for practitioners—that allow readers to apply the ideas in the chapter to particular design problems. Inventing the Medium also provides more than 200 illustrations of specific design strategies drawn from multiple genres and platforms and a glossary of design concepts.

Inventing the Medium gathers humanistic insights from Murray’s pioneering scholarship, demonstrates how they apply to a wide range of digital design problems, and invites readers to begin using these conceptual tools themselves in an engaging and broadly accessible manner. I’ve already seen it have a powerful impact on my students.

—Noah Wardrip-Fruin, Computer Science Department, University of California, Santa Cruz author of Expressive Processing

CONTENTS: Acknowledgments. Introduction: A Cultural Approach to Interaction Design. I: Changing Technologies, Lasting Innovations—Design in an Evolving Medium. Affordances of the Digital Medium. Maximizing the Four Affordances. II: Designing Expressive Procedures—Computational Strategies of Representation. Building Procedural Complexity. III: Spatial Design Strategies—Defining and Navigating Spaces and Places. The Library Model for Collocating Information. IV: Designing Encyclopedic Resources—The Database Model: Strategies for Segmentation and Juxtaposition of Information. The Structural Document Model: Using Standardized Metadata to Share Knowledge. V: Scripting Interaction—The Tool Model: Augmenting the Expressive Power of the Hand. The Machine Model: Visibility and Control as Design Goals. The Companion Model: Helpful Accompaniment as a Design Goal. The Game Model: Scripting Interaction as Structured Play. Glossary. Bibliography. Image Credits. Index.

INVENTING THE MEDIUM Principles of Interaction Design as a Cultural Practice

JANET H. MURRAY is Ivan Allen College Dean’s Recognition Professor of Digital Media and Director of the Experimental Television Lab at Georgia Institute of Technology.

500 pp. / 17.8 × 23.5 cm/ ISBN-978-81-203-4599-7 / ` 995.00

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ENGINEERING Production Engineering

Engineering Systems is an emerging field that is at the intersection of engineering, management, and the social sciences. Designing complex systems requires not only traditional engineering skills but also knowledge of public policy issues and awareness of societal norms and preference. As scale, scope, and complexity increase, engineers consider technical and social issues together in a highly integrated way as they design flexible, adaptable, robust systems that can be easily modified and reconfigured to satisfy changing requirements and new technological opportunities.

This book offers a comprehensive examination of such systems and the associated emerging field of study. Through scholarly discussion, concrete examples, and history, the authors consider the engineer’s changing role, new ways to model and analyze these systems, the impacts on engineering education, and the future challenges of meeting human needs through the technologically enabled systems of today and tomorrow.

I believe that this book is a first. It defines a new and emerging discipline—engineering systems. The authors give us the theories, concepts, and tools that are necessary to situate engineering problems in a broader and fundamentally relevant context, thereby permitting more complete and useful solutions to current challenges.

—John S. Reed, Chairman of the Corporation, MIT

This book is timely. New thinking is urgently needed in order to manage and thrive in our world of complex systems and systems of systems. Our students, the leaders of tomorrow, must learn and apply engineering systems skills in business, communications, transportation, energy, education, healthcare delivery, public health, and global health. This book marvelously demonstrates why the system-thinking skills required must include the domains of strategic planning, public policy, social sciences, management, and engineering.

—Denis A. Cortese, M.D., Foundation Professor and Director of the Healthcare Delivery and Policy Program, Arizona State University; President of the Healthcare Transformation Institute;

Emeritus President and CEO of Mayo Clinic

CONTENTS: Series Foreword. Foreword by Charles M. Vest. Preface. From Inventions to Systems. What is an Engineering System. (Re)Thinking about Systems. Life-Cycle Properties of Engineering Systems: The Ilities. Modeling and Analyzing Engineering Systems. Partially Designed, Partially Evolved. Engineering Systems Research and Education. What the Future Holds. Appendix: Engineering Systems Terms and Definitions. Notes. Index.

ENGINEERING SYSTEMS Meeting Human Needs in a Complex Technological WorldOLIVIER L. de WECK is Associate Professor of Aeronautics and Astronautics and Engineering Systems at MIT as well as Associate Director of the Engineering Systems Division.DANIEL ROOS, Founding Director of Engineering Systems Division, is Japan Steel Industry Professor of Engineering Systems and Civil and Environmental Engineering at MIT.

CHRISTOPHER L. MAGEE is Professor of the Practice of Mechanical Engineering and Engineering Systems at MIT, where he is also Codirector of the International Design Center of Singapore University of Technology and Design and MIT.

232 pp. (Hard Cover) / 15.3 × 22.9 cm / ISBN-978-81-203-4753-3 / ̀595.00

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1ENGINEERING Production Engineering

This book provides a high-level overview of why flexibility in design is needed to deliver significantly increased value. It describes in detail methods to identify, select, and implement useful flexibility. The book is unique in that it explicitly recognizes that future outcomes are uncertain. It thus presents forecasting, analysis, and evaluation tools especially suited to this reality. Appendixes provide expanded explanations of concepts and analytic tools.

Forecasts are a necessary part of planning major capital projects. The problem is these forecasts are almost always wrong. It is very important to recognize this truth and even more important to shield projects from the potential downsides of an uncertain future by building in flexibility. Professors de Neufville and Scholtes have provided a clear and practical guide, well supported by specific examples, on the science of identifying, justifying, and implementing flexibility in design.

—Lloyd A. McCoomb, President and Chief Executive Officer Toronto Pearson International Airport

de Neufville and Scholtes convincingly show us that enhancing flexibility in engineering design can help us a lot to improve our performance. Anchored in their research, the book is an easy read because both authors are also excellent pedagogues who take the reader step by step through some difficult materials. This book is a real must-read for anybody involved in large-scale projects.

—Arnoud de Meyer, President and Professor Singapore Management University

CONTENTS: Series Foreword; Acknowledgments; Introduction. Value I: High-Level Overview—Flexible Design: Its Need and Value. Recognition of Uncertainty. Flexibility Can Increase Value II: Method of Analysis—Phase 1: Estimating the Distribution of Future Possibilities. Phase 2: Identifying Candidate Flexibilities. Phase 3: Evaluating and Choosing Flexible Designs. Phase 4: Implementing Flexibility. Epilog: The Way Ahead. Appendices—A: Flaw of Averages. B: Discounted Cash Flow Analysis. C: Economics of Phasing. D: Monte Carlo Simulation. E: Dynamic Forecasting. F: Financial Options Analysis. Notes. Bibliography. Index.

FLEXIBILITY IN ENGINEERING DESIGN

RICHARD de NEUFVILLE is Professor of Engineering Systems, and Civil and Environmental Engineering at MIT. STEFAN SCHOLTES is Dennis Gillings Professor of Health Management and Academic Director of the Centre for Health Leadership and Enterprise at the Judge Business School, University of Cambridge.

312 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4751-9 / ` 595.00

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ENVIRONMENT/ENERGY STUDIES

This widely used textbook is designed for advanced undergraduate and postgraduate students as well as others who have an interest in exploring energy resource options and technologies with a view toward achieving sustainability on local, national, and global scales. It clearly presents the tradeoffs and uncertainties inherent in evaluating and choosing sound energy portfolios and provides a framework for assessing policy solutions.

The second edition examines the broader aspects of energy use, including resource estimation, environmental effects, and economic evaluations; reviews the main energy sources of today and tomorrow, from fossil fuels and nuclear power to biomass, hydropower, and solar energy; treats energy carriers and energy storage transmission, and distribution; addresses end-use patterns in the transportation, industrial, and building sectors, and considers synergistic complex systems. This new edition also offers updated statistical data and references; a new chapter on the complex interactions among energy, water, and land use; expanded coverage of renewable energy; and new color illustrations. Sustainable Energy addresses the challenges of making responsible energy choices for a more sustainable future.

At last, sustainable energy can be taught from a single textbook—one that is balanced, worldly, comprehensive, and challenging. Watch out, teachers! Science and engineering students are going to demand courses that use this book.

—Robert Socolow, Department of Mechanical and Aerospace Engineering, Princeton University

This book with its references and links is an excellent source text for anyone considering a course on energy options for the future and for anyone else interested in understanding the science and argument which underlie the debate on energy options for a sustainable future.

—R. John Sandeman, International Journal of Environmental Studies

CONTENTS: Preface to the First Edition. Acknowledgments from the First Edition. Preface to the Second Edition. Acknowledgments for the Second Edition. Sustainable Energy: The Engine of Sustainable Development. Estimation and Evaluation of Energy Resources. Technical Performance: Allowability, Efficiency, Production Rates. Local, Regional, and Global Environmental Effects of Energy. Project Economic Evaluation. Energy Systems and Sustainability Metrics. Energy, Water, and Land Use. Fossil Fuels and Fossil Energy. Nuclear Power. Biomass Energy. Geothermal Energy. Hydropower. Solar Energy. Ocean Wave, Tide, Current and Thermal Energy Conversion. Wind Energy. Energy Carriers: Electric Power, Hydrogen Fuel, Other? Energy Management: Storage, Transportation, and Distribution. Transportation Services. Industrial Energy Usage. Commercial and Residential Buildings. Synergistic Complex Systems. Choosing among Options. Conversion Factors. List of Acronyms. Index.

SUSTAINABLE ENERGY Choosing Among Options, 2nd ed.JEFFERSON W. TESTER, Croll Professor of Sustainable Energy Systems at Cornell University. ELISABETH M. DRAKE, Emeritus Researcher at the MIT Energy Initiative. MICHAEL J. DRISCOLL, Professor Emeritus of Nuclear Science and Engineering at MIT. MICHAEL W. GOLAY, Professor of Nuclear Science and Engineering at MIT. WILLIAM A. PETERS, Executive Director of the Institute for Soldier Nanotechnologies at MIT.

1052 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4810-3 / ` 995.00

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3JOURNALISM/LANGUAGE/LINGUISTICS

Grammar as Science offers an introduction to syntax as an exercise in scientific theory construction.

It covers such core topics in syntax as phrase structure, constituency, the lexicon, inaudible elements, movement rules, and transformational constraints, while emphasizing scientific reasoning skills. The individual units are organized thematically into sections that highlight important components of this enterprise, including choosing between theories, constructing explicit arguments for hypotheses, and the conflicting demands that push us toward expanding the technical toolkit on the one hand and constraining it on the other.

This book is constructed as a “laboratory science” course in which students actively experiment with linguistic data.

It is intended for students majoring in linguistics as well as nonlinguistics majors who are taking the course to fulfill academic requirements.

Grammar as Science is an excellent textbook for an introductory syntax course, serving both intended linguistics majors and the general education population equally well. There isn’t anything quite like it in the market. If I ever use a textbook, I would use this one.

— Jorge Hankamer, Department of Linguistics, University of California, Santa Cruz

Larson’s book is an engaging and delightfully lucid introduction to the scientific nature of linguistic argumentation. While thoroughly covering the basics of syntax, it also shows students explicitly how to ‘think like a linguist.’ Students who use this book will come away with an extraordinarily strong grasp of the real underpinnings of linguistics.

— Peggy Speas, Department of Linguistics, University of Massachusetts, Amherst

CONTENTS: Preface for Teachers. Acknowledgements. Part I: Setting Out—Unit 1: What Is Linguistics?. Unit 2: What Is Syntax About?. Part II: Grammars as Theories—Unit 3: Introducing Phrase Structure Rules. Unit 4: Grammars. Unit 5: Working with Grammars. Part III: Choosing between Theories— Unit 6: Comparing Rules and Theories. Unit 7: Constituency and Constituency Tests. Unit 8: Trees and Tree Relations. Unit 9: Determining Category. Unit 10: Revising, Refining, and Reconsidering. Part IV: Arguing for a Theory—Unit 11: Constructing Arguments I. Unit 12: Constructing Arguments II. Part V: Searching for Explanation.—Unit 13: Introducing the Lexicon. Unit 14: Features, Heads, and Phrases. Unit 15: Verbal Complements and Adjuncts. Unit 16: Distinguishing Complements and Adjuncts. Unit 17: Attaching Complements. Unit 18: Attaching Adjuncts. Part VI: Following the Consequences—Unit 19: Complements Sentences I. Unit 20: Complements Sentences II. Unit 21: Invisible Lexical Items. Unit 22: NP Structure. Unit 23: X-Bar Theory. Part VII: Expanding and Constraining the Theory—Unit 24: Interrogatives and Movement. Unit 25: More on Wh-Movement. Unit 26: Constraints on Movement I. Unit 27: Constraints on Movement II. Unit 28: Parametric. Variation. Exercises. References. Index.

GRAMMAR AS SCIENCE

RICHARD K. LARSON is Professor of Linguistics at Stony Brook University.

452 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4321-4 / ` 395.00

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JOURNALISM/LANGUAGE/LINGUISTICS

Current textbooks in formal semantics are all versions of or introductions to the same paradigm in semantic theory: Montague Grammar. Knowledge of Meaning is based on different assumptions and a different history. It provides the only introduction to truth-theoretic semantics for natural languages, fully integrating semantic theory into the modern Chomskyan program in linguistic theory and connecting linguistic semantics to research elsewhere in cognitive psychology and philosophy. As such, it better fits into a modern graduate or undergraduate program in linguistics, cognitive science, or philosophy. Furthermore, since the technical tools it employs are much simpler Knowledge of Meaning can be taught by someone who is not primarily a semanticist.

...no one in recent decades has written a book of this magnitude about the semantics of natural language. Certainly nothing available today matches this volume in depth, precision, and coherence.

—Zoltan Szabo, in The Philosophical Review (January 1997)

CONTENTS: Preface. Acknowledgements. The Nature of Semantic Theory. Knowledge of Meaning and Theories of Truth. Meaning and Structure. Verbs and Predication. Proper Nouns and Reference. Pronouns and Demonstratives. Quantification. Quantifiers and Quantifier Properties. Definite Descriptions. Anaphora. Clausal Complements and Attitude Reports. Events. States, and Times. Meaning and Knowledge. Notes. References. Author Index. Subject Index.

KNOWLEDGE OF MEANING An Introduction to Semantic Theory

RICHARD LARSON, King’s College, London.GABRIEL SEGAL, King’s College, London.

660 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-1357-6 / ` 350.00

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The latest edition of a popular introductory linguistics text, now including a section on computational linguistics, new non-English examples, quizzes for each chapter, and additional special topics.

This popular introductory linguistics text is unique for its integration of themes. Rather than treat morphology, phonetics, phonology, syntax, and semantics as completely separate fields, the book shows how they interact. The authors provide a sound introduction to linguistic methodology, focusing on a set of linguistic concepts that are among the most fundamental within the field. By studying the topics in detail, students can get a feeling for how work in different areas of linguistics is done.

As in the last edition, part I covers the structural and interpretive parts of language—morphology, phonetics, phonology, syntax, semantics, variation, and change. Part II covers use and context of language and includes chapters on pragmatics, psychology of language, language acquisition, and language and the brain. This seventh edition has been extensively revised and updated; new material includes a chapter on computational linguistics, more non-English examples, and a wide range of exercises, quizzes, and special topics.

Review for the Book

“There's a good reason why this Introduction has been the standard for decades: it's consistently inviting, informative, and intelligent. This edition, attuned to the twenty-first century, is the best one yet.”

—Steven Pinker Professor of Psychology,

Harvard University

LINGUISTICS An Introduction to Language and Communication, 7th ed.ADRIAN AKMAJIAN was Professor of Linguistics at the University of Arizona. ANN K. FARMER, is an Information Engineer at Google.LEE BICKMORE is Professor in the Department of Anthropology and Director of the Program in Linguistics and Cognitive Science at the University at Albany, State University of New York. RICHARD A. DEMERS is Professor Emeritus of the Department of Linguistics at the University of Arizona. ROBERT M. HARNISH was Professor Emeritus of Philosophy and Linguistics at the University of Arizona


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JOURNALISM/LANGUAGE/LINGUISTICS

A Linguistics Workbook, is a supplement to Linguistics: An Introduction to Language and Communication, Sixth Edition by Akmajian, Demers, Farmer and Harnish. The aim of this workbook is to offer students exposure to a broader range of languages than is provided in the text. Though most of the examples in the textbook are based on English, the workbook provides exercises drawn from a wide variety of languages. Hence, it can also be used with other introductory and intermediate linguistics texts. This new edition has been updated, with many challenging and stimulating exercises added to it.

CONTENTS: Preface. Acknowledgments. Morphology. Phonetics. Phonology. Syntax. Semantics. Language Variation. Language Change. Pragmatics. Psychology of Language. Appendixes. Bibliography.

LINGUISTICS WORKBOOK, A Companion to Linguistics, 6th ed.

ANN K. FARMER is an information Engineer at Google.RICHARD A. DEMERS is professor emeritus in the Department of Linguistics at the University of Arizona.

312 pp. / 21.6 × 27.8 cm / ISBN-978-81-203-4591-1 / ` 325.00

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Acquisition of language is a human biological endowment, and we know children have a natural disposition for mastering it. The biological side of language is the subject of increasing research. Biolinguists are interested in fundamental questions such as, whether speech and language are localized in the brain, how do encoding and decoding of speech and language function, and whether different components of language (syntax, phonology, semantics) are neuroanatomically distinct. Biolinguistics studies, the relationship between brain function and language. In other words, it is primarily concerned with grammars that represent the computational aspects of the mind/brain.

This book elegantly introduces the subject of biolinguistics. The author provides a lucid overview of Chomsky’s contribution in biolinguistics and builds on it to offer a novel account of the nature of the human faculty of language. Hence, apart from topics internal to biolinguistics, this work touches on topics in the history and philosophy of science, epistemology, philosophy of language, philosophy of mind, and psychology of music, among others. In this content, the biolinguistic approach may ultimately lead to identification of a specific structure of mind.

The book is eminently suitable for courses offered in the departments of Linguistics/Computational Linguistics, Philosophy, Neuroscience, Psychology, and Languages at research level.

CONTENTS: List of Figures. Abbreviations. Preface. The Loneliness of Biolinguistics. Linguistic Theory I. Grammar and Logic. Words and Concepts. Linguistic Theory II. Language and Music. A Joint of Nature. Notes. References. Index.

PRIMACY OF GRAMMAR, THE

NIRMALANGSHU MUKHERJI, Professor of Philosophy, University of Delhi.

300 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4257-6 / ` 295.00

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MATHEMATICS/STATISTICS

This text offers a comprehensive presentation of the mathematics required to tackle problems in economic analyses. To give a better understanding of the mathematical concepts, the text follows the logic of the development of mathematics rather than that of an economics course. The only prerequisite is high school algebra, but the book goes on to cover all the mathematics needed for undergraduate economics. It is also a useful reference for graduate students. After a review of the fundamentals of sets, numbers, and functions, the book covers limits and continuity, the calculus of functions of the one variable, linear algebra, multivariate calculus, and dynamics. To develop the student’s problem-solving skills, the book works through a large number of examples and economic applications.

This streamlined third edition offers an array of new and updated examples. Additionally, lengthier proofs and examples are provided on the book’s website http://mitpress.mit.edu/math_econ3. The book and the Web material are cross-referenced in the text. A Student Solutions Manual is available in ebook form, and instructors are able to access online the Instructor’s Manual, which includes PowerPoint slides.

Mathematics is the language of economics, and this book is an excellent introduction to that language.

— George J. Mailath, Walter H. Annenberg Professor in the Social Sciences and Professor of Economics, University of Pennsylvania

While there are many mathematics texts for economics available, this one is by far the best. It covers a comprehensive range of techniques with interesting applications, and the numerous worked examples and problems are a real bonus for the instructor. Teaching a course with this book is enjoyable and easy.

— Kevin Denny, University College Dublin

CONTENTS: Preface. Part I: Introduction and Fundamentals—Introduction. Review of Fundamentals. Sequences, Series, and Limits. Part II: Univariate Calculus and Optimization— Continuity of Functions. The Derivative and Differential for Functions of One Variable. Optimization of Functions of One Variable. Part III: Linear Algebra—Systems of Linear Equations. Matrices. Determinants and the Inverse Matrix. Some Advanced Topics in Linear Algebra. Part IV: Multivariate Calculus—Calculus for Functions of n-Variables. Optimization of Functions of n-Variables. Constrained Optimization. Comparative Statics. Concave Programming and the Kuhn–Tucker Conditions. Part V: Integration and Dynamic Methods—Integration. An Introduction to Mathematics for Economic Dynamics. Linear, First-Order Difference Equations. Nonlinear, First-Order Difference Equations. Linear, Second-Order Difference Equations. Linear, First-Order Differential Equations. Nonlinear, First-Order Differential Equations. Linear, Second-Order Differential Equations. Simultaneous Systems of Differential and Difference Equations. Optimal Control Theory. Answers. Index.

MATHEMATICS FOR ECONOMICS, 3rd ed.

MICHAEL HOY, JOHN LIVERNOIS, CHRIS McKENNA, and THANASIS STENGOS are with the Department of Economics, University of Guelph, Ontario, Canada. RAY REES, Center for Economic Studies (CES), University of Munich.

976 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4648-2 / ` 650.00

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9MATHEMATICS/STATISTICS

This work of translation of the classic Russian textbook emphasizes a fresh modern approach to the geometric qualitative theory of ordinary differential equations. The subject matter of this book is dominated by two central ideas and their ramifications: the theorem on rectifiability of a vector field and the theory of one-parameter groups of linear transformations. While the author has taken the liberty to omit some of the more specialized topics usually included in books on ordinary differential equations, the applications of these equations to mechanics, on the contrary, have been considered in more detail than the customary approach.

KEY FEATURES• Emphasizes the geometrical and intuitive aspects while familiarizing the students with the concepts of

flows on manifolds and tangent bundles.

• Presents a wealth of topics accompanied by many thought-provoking examples, problems and figures.

• Assumes the reader to possess a knowledge not beyond the scope of the standard elementary courses on analysis and linear algebra.

This college-level textbook treats the subject of ordinary differential equations in an entirely new way. A wealth of topics is presented masterfully, accompanied by many thought-provoking examples, problems, and 259 figures. The author emphasizes the geometrical and intuitive aspects and at the same time familiarizes the student with concepts, such as flows and manifolds and tangent bundles, traditionally not found in textbooks of this level. The exposition is guided by applications taken mainly from mechanics. One can expect this book to bring new life into this old subject.

—American Scientist

CONTENTS: Preface. Frequently Used Notation. Basic Concepts. Basic Theorems. Linear Systems. Proofs of the Basic Theorems. Differential Equations on Manifolds. Sample Examination Problems. Bibliography. Index.

ORDINARY DIFFERENTIAL EQUATIONS

V.I. ARNOLD.

292 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-1352-1 / ` 250.00

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MATHEMATICS/STATISTICS

Traditional mathematics teaching is largely about solving exactly stated problems exactly, yet life often hands us partly defined problems needing only moderately accurate solutions. This engaging book is an antidote to the rigor mortis brought on by too much mathematical rigor, teaching us how to guess answers without needing a proof or an exact calculation.

Street-Fighting Mathematics, builds, sharpens, and demonstrates tools for educated guessing and opportunistic problem solving across diverse fields of knowledge—from mathematics to management. The author describes six tools: dimensional analysis, easy cases, lumping, picture proofs, successive approximation, and reasoning by analogy. Illustrating each tool with numerous examples, he carefully separates the tool—the general principle—from the particular application so that the reader can most easily grasp the tool itself to use on problems of particular interest.

Many everyday problems require quick, approximate answers. Street-Fighting Mathematics teaches a crucial skill that the traditional science curriculum fails to develop: how to obtain order-of-magnitude estimates for a broad variety of problems. This book will be invaluable to anyone wishing to become a better informed professional.

—Eric Mazur, Balkanski Professor of Physics and of Applied Physics, Harvard University

CONTENTS: Foreword. Preface. Dimensions. Easy cases. Lumping. Pictorial Proofs. Taking Out the Big Part. Analogy. Bibliography. Index.

STREET-FIGHTING MATHEMATICS The Art of Educated Guessing and Opportunistic Problem Solving

SANJOY MAHAJAN.Foreword by CARVER A. MEAD.

152 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4254-5 / ` 150.00

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1MEDICINE

This book offers an overview of key recent advances in cognitive electrophysiology which concern the study of the brain’s electrical and magnetic responses to both external and internal stimuli. These can be measured using electroencephalograms (EEGs) and magneto encephalograms (MEGs).

The chapters highlight the increasing overlap in EEG and MEG analytical techniques, describing several methods applicable to both. The text discusses recent developments, including reverse correlation methods in visual-evoked potentials and a new approach to topographic mapping in high density electrode montage—relating the latest thinking on design aspects of ECG and MEG studies, in particular how to optimize the signal to noise ratio as well as statistical developments for maximizing power and accuracy in data analysis using repeated measure ANOVAS.

CONTENTS: Contributors. Preface. Reverse Correlation and the VESPA Method—Edmund C. Lalor, Barak A. Pearlmutter, and John J. Foxe. Principles of Topographic Analyses for Electrical Neuroimaging—Micah M. Murray, Marzia De Lucia, Denis Brunet, and Christoph M. Michel. Noninvasive Estimation of Local Field Potentials: Methods and Applications—Rolando Grave de Peralta Menendez, Micah M. Murray, Gregor Thut, Theodor Landis, and Sara L. Gonzalez Andino. A Practical Guide to Beamformer Source Reconstruction for EEG—Jessica J. Green and John J. McDonald. A Practical Guide to MEG and Beamforming—Anthony T. Herdman and Douglas Cheyne. Dynamic Causal Modeling for Evoked Responses—Stefan J. Kiebel, Marta I. Garrido, and Karl J. Friston. Synchronization Analysis in EEG and MEG—Lawrence M. Ward and Sam M. Doesburg. Procedures and Strategies for Optimizing the Signal-to-Noise Ratio in Event-Related Potential Data—Durk Talsma and Anne-Laura van Harmelen. Statistical Strategies for Translational ERP Studies— Todd C. Handy, Lindsay S. Nagamatsu, Marla J.S. Mickleborough, and Teresa Y.L. Liu-Ambrose. Index.

BRAIN SIGNAL ANALYSIS Advances in Neuroelectric and Neuromagnetic Methods

Edited by:TODD C. HANDY is Associate Professor in Psychology Department at the University of British Columbia, where he runs the Neuroimaging Lab.

272 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4297-2 / ` 325.00

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PHILOSOPHY

In this inspiring book the author defines the field of General Ethics and offers the first example of a truly general ethics. He develops a single, integrated approach to ethics that encompasses the realms of interhuman ethics, the ethics of the natural environment, and the ethics of the built environment. Thus, offering the first example of an ethical “Theory of Everything.”

This book is striking in its originality. It aims at a very ambitious goal: the development of an ethical theory that encompasses the domains of human relationships, nonhuman animals, and the rest of nature, including the built environment. Remarkably, it succeeds in achieving this goal.

—Andrew McLaughlin, Professor Emeritus of Philosophy, Lehman College, City University of New York

CONTENTS: Preface. Acknowledgments. I: General Ethics-and Its Problems—Introduction: The Idea of a General Ethics. Problems That Any General Ethics Must Be Able to Address. II: The Foundational Value of Responsive Cohesion—Introducing the Idea of Responsive Cohesion. The Best Approach to Everything Appendix to Chapter 4 A Note on the Concepts of Responsive Cohesion, Reflective Equilibrium, Organic Unity, Complex Systems, and So On. The Best Approach to Conventional, Interhuman Ethics. III: Contexts, Mindsharers, and ISO-Experients—The Theory of Responsive Cohesion’s Theory of Contexts. Exploring the Cognitive Worlds of Mindsharers and ISO-Experients. Time Blindness, Autobiographical Death, and Our Obligations in Respect of All Beings. IV: Summary, Applications, and Concluding Thoughts—Putting It All Together: The Shape of a General Ethics Worthy of the Name. Applying the Theory of Responsive Cohension. Conclusion. Notes. Bibliography. Index.

THEORY OF GENERAL ETHICS, A Human Relationships, Nature, and the Built Environment

WARWICK FOX.

404 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-3807-4 / ` 295.00

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3PHYSICS

This text offers an introduction to quantum computing, with special emphasis on basic quantum physics, experiments, and quantum devices. It explains the requisite quantum physics in some depth, and then explains the devices themselves.

Quantum Computing without Magic covers the essential probability calculus; the qubit, its physics, manipulation and measurement, and how it can be implemented using superconducting electronics; quaternions and density operator formalism; unitary formalism and its application to Berry phase manipulation; the biqubit, the mysteries of entanglement, nonlocality, separability, biqubit classification, and the Schroedinger’s Cat paradox; the controlled-NOT gate, its applications and implementations; and classical analogs of a quantum devices and quantum processes.

Quantum Computing without Magic can be used as a complementary text for physics and electronic engineering students studying quantum computing and basic quantum mechanics, or as an introduction and guide for electronic engineers, mathematicians, computer scientists, or scholars in these fields who are interested in quantum computing.

Quantum Computing without Magic gives a refreshing and down-to-earth approach to quantum information as well as quantum devices, which will have a fundamental impact on the technology of the twenty-first century.

—Raymond Laflamme, Canada Research Chair in Quantum Information and Director Institute for Quantum Computing, University of Waterloo

CONTENTS: Preface. Series Foreword. Preface. Bits and Registers. The Qubit. Quaternions. The Unitary Formalism. The Biqubit. The Controlled not Gate. Yes, It Can Be Done with Cogwheels. A: Quaternions and Pauli Matrices. B: Biqubit Probability Matrices. C: Tensor Products of Pauli Matrices. References. Index.

QUANTUM COMPUTING WITHOUT MAGIC Devices

ZDZISLAW MEGLICKI, who holds doctorate in electronic engineering and physics, is Senior Technical Advisor to the Office of Vice President for Information Technology at Indiana University.

444 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-3995-8 / ` 425.00

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PROFESSIONAL TITLE

Innovation is the ruling buzzword in business today. In this book, innovation experts Peter J. Denning and Robert Dunham inform us how the chances of an innovative idea’s becoming successful can be increased. Defining innovation as not simply an invention, but a policy and process that is to be managed, they explain that it is a personal skill that can be learnt, developed through practice, and extended into organizations. It is also the art of getting people to adopt change.

The authors identify and describe eight personal practices that all successful innovators perform: sensing, envisioning, offering, adopting, sustaining, executing, leading, and embodying. Together, these practices can boost a fledgling innovator to success. Weakness in any of these practices, they show, blocks innovation.

The authors Denning and Dunham describe innovation at scales ranging from the private (a family organization of chores and allowances) to the planetary (the invention and adoption of the World Wide Web). They provide a detailed account of the eight practices and how to accomplish them; and they chart the path to innovation mastery, from individual practices to teams and social networks.

Truly innovative thinking about innovative thinking—but it’s the authenticity of the authors’ experience that makes this book uniquely valuable and valuably unique.

—Michael Schrage, Research Fellow, MIT Sloan School Center for Digital Business

CONTENTS: Preface. Acknowledgments. I: Foundations of Innovation—Invention Is Not Enough. Generative Innovators in Action. Frames of Mind. Observing. II: The Eight—Practices. Practice One: Sensing. Practice Two: Envisioning. Practice Three: Offering. Practice Four: Adopting. Practice Five: Sustaining. Practice Six: Executing. Practice Seven: Leading. Practice Eight: Embodying. III: Journey to Mastery—Building a Culture of Innovation. Mastering the Mess. Social Networking and Innovation. Dispositions of the Masters. Epilogue: Stradivarius Street. Appendix 1: Eight Practices Summary Chart. Appendix 2: Eight Practices Assessment Tool. Appendix 3: Levels of Performance at Innovation. Appendix 4: Somatic Exercises. About the Authors. Index.

INNOVATOR’S WAY, THE Essential Practices for Successful InnovationPETER J. DENNING is Distinguished Professor, Chair of the Computer Science Department, and Director of the Cebrowski Institute for Information Innovation and Superiority at the Naval Postgraduate School in Monterey, California.ROBERT DUNHAM, founder, Institute for Generative Leadership and the consulting company Enterprise Performance.

Foreword by JOHN SEELY BROWN.

460 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4487-7 / ` 595.00

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5PSYCHOLOGY

The Genetics of Cognitive Neuroscience aims to give the reader a working understanding of the influence of specific genetics variants on cognition, affective regulation, personality, and central nervous system disorders.

It has been known that the aspects of behavior runs in families; studies shows that characteristics related to cognition, temperament, and all major psychiatric disorders are heritable.

The book offers a primer on understanding the genetic mechanisms of such inherited traits.

The chapters emphasize fundamental issues regarding the design of experiments, the use of bioinformatics tools, the integration of data from different levels of analysis and the validity of finding, arguing that association between genes and cognitive processes must be replicable and placed in a neurobiological context for validation.

CONTENTS: Preface. Introduction. I: Methodologies for Genetic Association Studies of Cognition—Molecular Genetics and Bioinformatics: An Outline for Neuropsychological Genetics—Lucas Kempf and Daniel R. Weinberger. Statistical Methods in Neuropsychiatric Genetics—Kristin K. Nicodemus and Fengyu Zhang. Animal Models of Genetic Effects on Cognition—Francesco Papaleo, Daniel R. Weinberger, and Jingshan Chen. II: Genetic Approaches to Individual Differences in Cognition and Affective Regulation—The Genetics of Intelligence Danielle Posthuma—Eco J.C. de Geus, and Ian J- Deary. Candidate Genes Associated with Attention and Cognitive Control— John Fossella, Jin Fan, and Michael I. Posner. Genetics of Corticolimbic Function and Emotional Reactivity—Ahmad R. Hariri, Erika E. Forbes, and Kristin L. Bigos. Genes Associated with Individual Differences in Cognitive Aging—Terry E. Goldberg and Venkata S. Mattay. III: Genetic Studies of Cognition and Treatment Response in Neuropsychiatric Disease—Genetics of Dyslexia: Cognitive Analysis, Candidate Genes, Comorbidities, and Etiologic Interactions— Bruce F. Pennington, Lauren M. McGrath, and Shelley D. Smith. Cognitive Intermediate Phenotypes in Schizophrenia Genetics— Gary Donohoe, Terry E. Goldberg, and Aiden Corvin. The Genetic Basis for the Cognitive Deterioration of Alzheimer’s Disease— John M. Ringman and Jeffrey L. Cummings. Pharmacogenetic Approaches to Neurocognition in Schizophrenia— Katherine E. Burdick and Anil K. Malhotra. Contributors. Index.

GENETICS OF COGNITIVE NEUROSCIENCE, THEEdited by:TERRY E. GOLDBERG is Professor of Psychiatry and Behavioral Sciences at Albert Einstein College of Medicine and Director of Neurocognitive Research at the Zucker Hillside Hospital’s Psychiatry Research Division and the Litwin Zucker Alzheimer’s Research Center at the Long Island Medical Center in Manhasset, New York.DANIEL R. WEINBERGER is Chief of the Clinical Brain Disorders Branch and Director of Genes, Cognition, and Psychosis Program at the National Institute of Mental Health of the National Institutes of Health in Bethesda, Maryland.

312 pp. / 17.8 × 23.5 cm / ISBN-978-81-203-4299-6 / ` 295.00

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PSYCHOLOGY

This concise text discusses the history of modern psychology from the late nineteenth century to the end of twentieth century. Among other topics, the book also examines the emergence of a new branch called cognitive psychology.

KEY FEATURES

• The book attempts to place recent history of psychology in the context of the general social and political culture in which it occurs.

• The text presents the material mainly as an organizational account of psychological processes.

• The book traces the evolution of experimental and theoretical psychology.

CONTENTS: Preface. Acknowledgments. Introduction. The Modern Mind: Its History and Current Use. Aristotle to Alexander Bain: Prolegomena of Modern Psychology. The Social Context for the New Psychology in the Nineteenth and Twentieth Centuries. The Birth of Modern Psychology: Wilhelm Wundt and William James. The “Discovery” of the Unconscious: Imageless Thought. The Early Twentieth Century: Consolidation in Europe and Behaviorism in America. The Interwar Years: Psychology Matures and Theories Abound. The Destruction of Psychology in Germany, 1933 to 1945. The Success of Gestalt Theory and Its Translation to the United States. A New Age of Psychology at the End of World War II. Two Case Histories from the New Psychology. Old Problems and New Directions at the End of the Century. The Clouded Crystal Ball: Psychology Today and Tomorrow. References. Name Index. Subject Index.

HISTORY OF MODERN EXPERIMENTAL PSYCHOLOGY, AFrom James and Wundt to Cognitive Science

GEORGE MANDLER is distinguished Professor of psychology at the University of California, San Diego, and visiting Professor at the University College, London.

312 pp. / 13.9 × 21.6 cm / ISBN-978-81-203-3237-9 / ` 275.00

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Certain ideas have thoughtful thinkers since ancient times. In this book, the author examines these ideas in the writings of thinkers from olden times to the present day. He argues for their importance not just as precursors of modern views but as ideas that are frequently better than the current ones.

The text offers breadth and depth, an engaging style and thorough scholarship, demonstrating the relevance of the great psychological thinkers.

John Malone has written a splendid book! A lively, readable and vigorous defense of history. It covers a wide sweep from the early Greeks through Roman and Christian philosophy and the Enlightenment to modern developments such as cognitivism and behaviorism. It is both informative and critical, full of apercus that clobber their targets with force and grace. I hope that Malone’s book may do for psychology what Bertrand Russell’s historical opus did for philosophy. Read it.

— J.E.R. Staddon

This lucid book takes a fresh look at the individuals and ideas that comprise the history of psychology. Referring to the original theoretical and empirical sources, Malone questions many standard interpretations and received ideas, and provides enlightening ones of his own.

— Howard Rachlin

CONTENTS: Preface and Acknowledgments. History, Psychology, and Science. Science and Psychology in Ancidnet Greece. Static’s and Dynamics in Ancient Greece. From Aristotle to the Enlightment: Pagan Psychologies Give Way to Christianity. The Enlightenment. British Empricism and Kant: What Is Reality?. Scottish and English Practical Psychology. Darwin and Evolutionary Thinking. Nineteenth-Century Science and Psychology’s Rise. Biological Psychology: A Brief History. The New Psychology: Wundt, Würzburg, and Müller. Early-Twentieth-Century Psychology: Titchener and Freud. Pragmatism, Functionalism, Peirce, and James. Twentieth-Century Applied Psychology and Early Behaviorism. Gestalt psychology and Kurt Lewin. Science, Application, and Theory: Pavlov, Guthrie, and Hull. Radical Behaviorism and Cognitive Science: Contrasting Psychologies of the Twentieth-Century? References. Notes. Index.

PSYCHOLOGY Pythagoras to Present

JOHN C. MALONE, Professor of Psychology, University of Tennessee, Knoxville.

572 pp. / 15.3 × 22.9 cm / ISBN-978-81-203-4121-0 / ` 450.00

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