An Intemational Journal Available online at www.sciencedirect.com computers &

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with applications Computers and Mathematics with Applications 48 (2004) 971-994

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B O O K R E P O R T S The Book Reports section is a regular feature of Computers ~ Mathematics with Applications.

It is an unconventional section. The Editors decided to break with the longstanding custom of

publishing either lengthy and discursive reviews of a few books, or just a brief listing of titles. Instead, we decided to publish every important material detail concerning those books submitted to us by publishers, which we judge to be of potential interest to our readers. Hence, breaking with custom, we also publish a complete table of contents for each such book, but no review of it as such. We welcome our readers' comments concerning this enterprise. Publishers should submit books intended for review to the Editor-in-Chief,

Professor Ervin Y. Rodin Campus Box 1040

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0898-1221/04/$ - see front matter © 2004 Elsevier Ltd. All rights reserved. Typeset by .AAdS-TEX doi:10.1016/j.camwa.2004.09.001

972 BOOK REPORTS

Selected Papers on Computer Science. F~ited By Donald E. Knuth. CSLI Publishing. 2004. $80.00. 276 pages. Contents. 0. Algorithms, Programs, and Computer Science. 1. Computer Science and its Relation to Mathematics. 2. Mathematics and Computer Science: Coping with Finiteness. 3. Algorithms. 4. Algorithms in Modern Mathe- matics and Computer Science. 5. Algorithmic Themes. 6. Theory and Practice, I. 7. Theory and Practice, II. 8. Theory and Practice, III. 9. Theory and Practice, IV. 10. Are Toy Problems Useful? 11. Ancient Babylonian Algorithms. 12. Von Neumann's First Computer program. 13. The IBM 650: An Appreciation from the Field. 14. Artistic Programming. 15. Speech in St. Petersburg. 16. George Forsythe and the Development of computer Science. Index.

Computer Alqebra Handbook. Edited by Johannes Grabmeier, Erich Kaltofen, Volker Weispfenning. Springer. Heidelberg, Germany. 2003. $79.95. 638 pages. Contents. Foreword. Editorial Remarks. Table of Contents. List of Contributing Authors. 1. Development, Characterization, Prospects. 1.1. Historical Remarks. 1.2. General Characterization. 1.3. Impact on Education. 1.4. Impact on Research. 1.5. Computer Algebra--Today and tomorrow. 1.5.1. today. 1.5.2. Outlook. 2. Topics of Computer Algebra. 2.1. Exact Arithmetic. 2.1.1. Long Integer Arithmetic. 2.1.2. Arithmetic with PolynomiMs, Rational Function and Power Series. 2.1.3. Euclid's Algorithm and Continued fractions. 2.1.4. Modular Arithmetic and the Chinese Remainder Theorem. 2.1.5. Computations with Algebraic Numbers. 2.1.6. Real Algebraic Numbers. 2.1.7. p- adic Numbers and Approximations. 2.1.8. Finite Fields. 2.2 Algorithms for Polynomials and Power Series. 2.2.1. The Division Algorithms. 2.2.2. Factorization of Polynomials. 2.2.3. Absolute Factorization of Polynomials. 2.2.4. Polynomials Decomposition. 2.2.5. Grobner Bases. 2.2.6. Standard Bases. 2.2.7. Characteristic Sets. 2.2.8. Algorithmic Invariant Theory. 2.3. Linear Algebra. 2.3.1. Linear systems. 2.3.2. Algorithms for Matrix Canonical Forms, 2.4. Constructive Methods of Number Theory. 2.4.1. Primality Tests. 2.4.2. Integer Factorization. 2.4.3. Algebraic Number Fields and Algebraic Function Fields. 2.4.4. Galois Groups. 2.4.5. Rational Points on Elliptic Curves. 2.4.6. Geometry of Numbers. 2.5. Algorithms of Commutative Algebra and Algebraic Geometry. 2.5.1. Algorithms for Polynomial Ideal and Their Varieties. 2.5.2. Singularities of Varieties. 2.5.3. Real Algebraic Geometry. 2.6. Algorithmic Aspects of the Theory of Algebras. 2.6.1. Structure Constants. 2.6.2. Generators and Relations, Swapping and G-algebras. 2.6.3. Monad Algebras, Path Algebras, and Generalizations. 2.6.4. Finite-Dimensional Lie Algebras. 2.6.5. Non- commutative Grobner Bases. 2.6.6. Structural Issues and classification. 2.6.7. Identities. 2,6.8. Computational Aspects in the Representation Theory of Quivers and path Algebras. 2.7. Computational Group Theory. 2.7.1. A Crash Course in group Theory. 2.7.2. Describing Groups. 2.7.3. A Brief History. 2.7.4. Permutation Groups. 2.7.5. Matrix Groups. 2.7.6. Black Box groups. 2.7,7. Abelian groups. 2.7,8. Polycyclic Groups. 2.7.9. Finitely Presented Groups. 2.7.10. Group-Theoretic Software. 2,7.11. Another Perspective. 2.8. Algorithms of Representation Theory. 2.8.1. Ordinary Representation Theory. 2.8.2. Modular Representation Theory. 2.8.3. Generic Character tables. 2.8.4. Summary of Systems. Algebraic Methods for Constructing Discret6e Structures. 2.10. Summation and Integration. 2.10.1. Definite Summation and Hypergeometric Identities. 2.10.2. Symbolic Integration. 2.11. Symbolic methods for Differential Equations. 2.11.1. Introduction. 2.11.2. Differential Galois Theory. 2.11.3. Lie Symmetries. 2.11.4. Painleve Theory. 2.11.5. Completion. 2.11.6. Differential Ideal Theory. 2.11.7. Dynamical Systems. 2.11.8. Numerical Analysis. 2.12. Symbolic/Numeric Methods. 2.12.1. Computer Analysis. 2.12.2. Algorithms for Computing Validate Results. 2.12.3. Hybrid Methods. 2.13. Algebraic Complexity Theory. 2.14. Coding Theory and Cryptography. 2.14.1. Coding Theory. 2.14.2. Quantum Coding Theorey 2.14.3. Cryptography. 2.15. Algorithmic Methods in Universal Algebra and Logic. 2.15.1. Term Rewriting Systems. 2.15.2. Decision Procedures and Quantifier Elimination Methods for Algebraic Theories. 2.16. Knowledge Representation and Abstract Data Types. 2.16.1. Mathematical Knowledge Representation and Expert Systems. 2.16.2. Abstract Data Types. 2.17. On the Design of Computer Algebra Systems. 2.17.1. Memory Management. 2.17.2. Program Verification and Abstract Data Types. 2.17.3. The Concept of Types. 2.17.4. Genericity. 2.17.5. Modularization. 2.17.6. Parallel Implementation. 2.17.7. Continuing Deveiopment of computer Algebra Systems. 2.18. Parallel Computer Algebra Systems. 2.18.1. Parallel Architectures and Operating Systems Supports. 2.18.2. Parallel Execution: Mapping and Scheduling. 2.18.3. Parallelism Expression and Languages. 2.19. Interfaces and Standardization. 2.19. Interfaces and Standardization. 2.19.1. Interfaces to Word Processors. 2.19.2. Graphics. 2.19.3. Interfaces to Numerical Software. 2.19.4. User Interfaces. 2.19.5. General Problem- Solving Environment. 2.19.6. Standardization, 2.19.7. MathML. 2.20. Hardware Implementation of Computer Algebra Algorithms. 3. Applications of Computer Algebra. 3.1. Physics. 3.1.1. Elementary Particles Physics. 3.1.2. Gravity. 3.1.3. 'Central Configurations' in the Newtonian N-Body Problem of Celestial Mechanics. 3.1.4. CA-Systems for Differ- ential Geometry and Applications. 3.1.5. Differential Equations in Physics. 3.2. Mathematics. 3.2.1. Computer algebra in Group Theory. 3.2.2. The Tangent Cone Algorithm and Applications in the Theory of Singularities. 3.2.3. Automatic Theorem Proving in Geometry. 3.2.4. Homological Algebra. 3.2.5. Study of Differential Struc- tures on Quantum Groups. 3.2.6. Orthogonal Polynomials and Computer Algebra. 3.2.7. Computer Algebra

BOOK REPORTS 973

in Symmetric Bifurcation Theory. 3.2.8. Symbolic-Numeric Treatment of Equivalent Systems of Equations. 3.3. Computer Science. 3.3.1. Computer Algebra in Computer Science. 3.3.2. Decomposable Structures, Generating Functions and Average-Case of Algorithms. 3.3.3. Telecommunication Management Networks. 3.4. Engineering. 3.4.1. Computer Algebra, a Modern Research Tool for Engineering. 3.4.2. Critical Load Computations for Jet Engines. 3.4.3. Audio Signal Processing. 3.4.4. Robotics. 3.4.5 Computer Aided Design and Modelling. 3.5. Chemistry. 3.5.1. Computer Algebra in Chemistry and Crystallography. 3.5.2. Chemical Reaction Systems. 3.6. Computer Algebra in Education. 3.6.1. New Hand-Held Computer Symbolic Algebra Tools in Mathematics Education. 3.6.2. The Dutch Perspective. 3.6.3. Computer Algebra in Teaching and Learning Mathematics: Experiences at the University of Plymouth, England. 3.6.4. The Educational Use of Computer Algebra Sys- tems at the University of Illinois. 3.6.5. Mathematics Education from a MATHEMATICA Perspective. 3.6.6. Visualization: Courseware for Mathematics Education. 4. Computer Algebra Systems. 4.1.1. AXIOM. 4.1.2. Aldor. 4.1.3. DERIVE and the TI-92. 4.1.4. Macsyma. 4.1.5. MAGMA. 4.1.6. Maple. 4.1.7. Mathematica. 4.1.8. MuPAD. 4.1.9. REDUCE. 4.2. Special Purpose Systems. 4.2.1. Algebraic Combinatorics Environment (ACE). 4.2.2. Building Nonassociative Algebras With Albert. 4.2.3. ALGEB. 4.2.4. AMORE. 4.2.5. BERGMAN. 4.2.6. CANNES/PARCAN. 4.2.7. CARAT. 4.2.8. CASA. 4.2.9. Chevie. 4.2.10. C-Meataxe. 4.2.11. CoCoA. 4.2.12. CREP. 4.2.13. The Desir Project and Its Continuation. 4.2.14. DISCRETA: A Tool for Constructing t-Designs. 4.2.15. FELIX. 4.2.16. Format. 4.2.17. FOXBOX and Other Blackout Systems. 4.2.18. GAP. 4.2.19. GiNaC. 4.2.20. Kan/sml. 4.2.21. KANT V4. 4.2.22. LIDIA. 4.2.23. Lie. 4.2.24. A brief Introduction to Macaulay 2. 4.2.26. MAS. 4.2.27. MASYCA. 4.2.28. NTL: A Library for Doing Number Theory. 4.2.29. NTL: A Library for Doing Number Theory. 4.2.30. PARI. 4.2.31. PARSAC. 4.2.32. QUOTPIC. 4.2.33. REDUX. 4.2.34. REPTILES A Program for Interactively Generating periodic Tilings. 4.2.35. SAC-l, Aides/SAC-2, Saclib. 4.2.36. SciNapse: Software that Writes PDE Software. 4.2.37. SENAC. 4.2.38. SIMATH-Algorithms in Number Theory. 4.2.39. SINGULAR- A Computer Algebra System for Polynomial Computations. 4.2.40. SymbMath. 4.2.41. SYMMETRICA. 4.2.42. Theorema: Computation and Deduction in Natural Style. 4.2.43. THEORIST-a User Interface for Symbolic Algebra. 4.3. Packages. 4.3.1. ANU Polycyclic Quotient Programs. 4.3.2. AREP. 4.3.3. CALI. 4.3.4. CLN, 4.3.5. CRACK, LIEPDE, APPLYSYM, and CONLAW. 4.3.6. DIMSYM. 4.3.7. EinS. 4.3.8. FeynArts and FormCalc. 4.3.9. FEYNCALC-Tools and Tables for Elementary Particle Physics. 4.3.10. GRAPE. 4.3.11. Recognizing Matrix Groups over Finite Fields. 4.3.12. MOLGEN. 4.3.13. ORME. 4.3.14. Ratappr. 4.3.15. TTC: Tools of Tensor Calculus. 5. Meetings and Publications. 5.1. Conferences and Proceedings. 5.2 Books on Computer Algebra. Cited references. Subject Index. Index for Author's Contributions.

Newton Methods for Nonlinear Problems. Edited by P. Deuflehard. Springer. Heidelberg. 2004. $99.00. 424 pages. Contents. Outline of Contents. 1. Introduction. 1.1. Newton-Raphson Method for Scalar Equations. 1.2. Newton's Method for General Nonlinear Problems. 1.2.1. Classical convergence theorems revisited. 1.2.2. Affine invariance and Lipschitz conditions. 1.2.3 The algorithmic paradigm. 1.3. A Roadmap of Newton-type Methods. 1.4. Adaptive Inner Solvers for Inexact Newton Methods. 1.4.1. Residual norm minimization: GMRES. 1.4.2. Energy norm minimization: PCG. 1.4.3. Error norm minimization: CGNE. 1.4.4. Error norm reduction: GBIT. 1.4.5. Linear multigrid methods. Exercises. Part I. Algebraic Equations. 2. Systems of Equations: Local Newton Methods. 2.1. Error Oriented Algorithms. 2.1.1. Ordinary Newton method. 2.1.2. Simplified Newton method. 2.1.3. Newton-like methods. 2.1.4. Broyden's "good" rank-1 updates. 2.1.5. Inexact Newton-ERR methods. 2.2. Residual Based Algorithms. 2.2.1. Ordinary Newton method. 2.2.2. Simplified Newton method. 2.2.3. Broyden's "bad" rank-1 updates. 2.2.4. Inexact Newton-RES method. 2.3. Convex Optimization. 2.3.1. Ordinary Newton method. 2.3.2. Simplified Newton method. Exercises. 3. Systems of Equations: Global Newton Methods. 3.1. Globalization Concepts. 3.1.1. Componentwise convex mappings. 3.1.2. Steepest descent methods. 3.1.3. Trust region concepts. 3.1.4. Newton Path. 3.2. Residual Based Descent. 3.2.1. Affine Contravariant Convergence Analysis. 3.2.2. Adaptive trust region strategies. 3.2.3. Inexact Newton-RES method. 3.3. Error Oriented Descent. 3.3.1. General level function. 3.3.2. Natural level function 3.3.3. Adaptive trust region strategies. 3.3.4. Inexact Newton-ERR methods. 3.4. Convex functional descent. Convex Functional Descent. 3.4.1. Affine conjugate convergence analysis. 3.4.2. Adaptive trust region strategies. 3.4.3. Inexact Newton-PCG method. Exercises. 4. Least Squares Problems: Gauss-Newton Methods. 4.1. Linear Least Squares Problem. 4.L1. Unconstrained problems. 4.1.2. Equality constrained problems. 4.2. Residual Based Algorithms. 4.2.1. Local Gauss-Newton methods. 4.2.2. Global Gauss Newton methods. 4.2.3. Adaptive trust region strategy. 4.3. Error Oriented Algorithms. 4.3.1. Local convergence results. 4.3.2. Local Gauss-Newton algorithms. 4.3.3. Global convergence results. 4.3.4. Adaptive trust region strategies. 4.3.5. Adaptive rank strategies. 4.4. Underdetermined Systems of Equations. 4.4.1. Local quasi-Gauss-Newton method. Exercises. 5. Parameter Dependent Systems: Continuation methods. 5.1. Newton Continuation Methods. 5.1.1. Classifica- tion of continuation methods. 5.1.2. Afflne covariant feasible stepsizes. 5.1.3. Adaptive pathfollowing algorithms.

974 Book REPORTS

5.2. Gauss-Newton Continuation Method. 5.2.1. Discrete tangent continuation beyond turning points. 5.2.2. Affine covariant feasible stepsizes. 5.2.3. Adaptive stepsise control. 5.3. Computation of Simple Bifurcations. 5.3.1. Augmented systems for critical points. 5.3.2. Newton-like algorithms for simple bifurcations. 5.3.3. Branching-off algorithms. Exercises. Part II. Differential Equations. 6. Stiff ODE Initial Value Problems. 6.1. Affme Similar Linear Contractivity. 6.2. Nonstiff versus Stiff Initial Value Problems. 6.2.1. Picard iteration versus Newton iteration, 6.2.2. Newton-type uniqueness theorems. 6.3. Uniqueness Theorems for Implicit One-step Methods. 6.4. Pseudo-transient Continuation for Steady State Problems. 6.4.1. Exact pseudo-transient continuation. 6.4.2. Inexact pseudo-transient continuation. Exercises. 7. ODE Boundary Value Problems. 7.1 Multiple Shooting for Timelike BVPs. 7.1.1. Cyclic linear systems. 7.1.2. Realization of Newton methods. 7.1.3. Realization of continuation methods. 7.2. Parameter Identification in ODEs. 7.3. Periodic Orbit Computation. 7.3.1. Single orbit computation. 7.3.2. Orbit continuation methods. 7.3.3. Fourier collocation method. 7.4. Polynomial Collocation for Spacelike BVPs. 7.4.1. Discrete versus continuous solutions. 7.4.2. Quasilinearization. as inexact Newton method. Exercises. 8. PDE Boundary Value Problems. 8.1. Asymptotic Mesh Independence. 8.2. Global Discrete Newton Methods. 8.2.1. General PDEs. 8.2.2 Elliptic PDEs. 8.3. Inexact Newton Multilevel FEM for Elliptic PDEs. 8.3.1. Local Newton-Galerkin methods. 8.3.2. Global Newton-Galerkin methods. Exercises. References. Software. Index.

Synerqetics. Edited by Hermann Haken. Springer. Heidelberg. 2004. $99.00. 758 pages. Contents. Part I. An Introduction. Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry and Biology. Part II. Advance Topics. Instability Hierarchies of Self-Organization Systems and Devices. Part III. Springer Series in Synergetics. List of All Published Books.

The Shaqqy Steed of Physics. Edited David Oliver. Springer. Heidelberg. 2004 $59.95. 300 pages. Contents. Preface to Second Edition. Preface to First Edition. Acknowledgements. 1. The shaggy Steed of Physics. 2. The Heavens and the Elements. 3. The Law of Motion. 4. Classical Mechanics: The Heavens. 5. Quantum Mechanics: The Elements. 6. The hidden Unity of Space and Time. 7. The manifold Universe. People. Notes. Index.

Diqitizinq the News. Edited by Pablo J. Boczkowski. The MIT Press. Cambridge. 2004. $30.00. 255 pages. Contents. Acknowledgements. 1. Emerging Media. 2. Exploring and Settling Alternatives to Print in the 1980s and Early 1990s. 3. Hedging: A Web of Challenges in the Second Half of the 1990s. 4. Mimetic Originality: The New York Times on the Web's Technology Section. 5. Vicarious Experiences: HoustonChronicle.com's Virtual Voyager. 6. Distributed Construction: New Jersey Online's Community Connection. 7. "When We Were Print People. Appendix: Research Design. Notes. Bibliography. Series List. Index.

The Rules of the Global Game. Edited by: Kenneth W. Dam. The University of Chicago Press. Chicago. 2004. $19.00. 342 pages. Contents. Preface. Acknowledgments. List of Abbreviations. Part 1: Angles of Vision. 1. The Tension Between the "Is" and the "Should Be". The Normative Approach. The Positive Approach: A Political Analysis. Interest Group Politics. Who Does What (and to Whom) in Washington. Political Contribu- tions and Interest Groups. Rent Seeking by Government Groups. Rent Extraction. The Role of Political parties. Limits to Political Analysis. 2. The Role of Statecraft in Resolving the Tension. The Presidency, the Executive Branch, and the Congress. Implementing Statecraft Strategies. A Closer Look at the Private Sector. Statecraft in Search of Normative Goals. Interest Groups and Public Discourse. Openness, Productivity, and Per Capita Income. 3. Political Dimensions of Trade Policy. Political Analysis. The Institutional Setting of Interest Group Politics. The Influence of Different Kinds of Interest Groups. 4. Normative Dimensions of Trade Policy. The Case for Eliminating Trade Barriers: Comparative Advantage. Intraindustry Trade. The Benefits of Opening Economies to Trade. Qualifications to the Case for Free Trade? The Current State of Play. Part 2: Trade Strategies and Issues. 5. Opening Foreign Markets. The 301 Process. Sanctions as the Achilles' Heel of 301. The Semiconductor Agreement Example. Market Access in the Uruguay Round: Procurement and Agriculture. 6. Trade in Services. The Nature of Trade in Services. The Search for Service Trade Liberalization. From GATT to CATS. Financial and Telecommunications Services. The Path Ahead. 7. The Regional Strategy for Opening Markets. Regional Trade Agreement Today. The Case for and Against RTAs Trade Creation and Diversion . Rent Seeking in the Trade Creation/Diversion Equation. The Third-Country Effect. Interest Groups and NAFTA. 8. The Janus Faces of Fairness. From Protectionism to Fairness. Antidumping Proceedings in Actual Practice. Antidumping in a Statecraft Perspective. The Semiconductor Agreement. Part II. Larger Implications of the Antidumping Law. Part 3: Investment and Finance in a Globalizing World.

Book REPORTS 975

9. Private Foreign Investment. Perspectives on FDI. Investment as a Driver of Trade. Restrictions on Investment as a Restriction on Trade: TRIMs. The Failed OECD MAI Effort. US Policy toward Inward Investment, US Options in Investment Negotiations. 10. The Diversity of Monetary and Financial Issues. The Moving Theatre of Monetary and Financial Issues. Exchange Rates and Patterns of Trade. Exchange Rates and Trade Compared. Managing Exchange Rates. 11. The International Monetary System. Exchange Rates and Reserve Systems. A Political Analysis of US International Monetary Policy. The Key Currency Role of the Dollar. 12. the International Financial System. Underdeveloped in Developing Countries. The Asian Financial Crisis. The Bailout Issue and Prospective Reforms. Policy Issues after the Asian Crisis. US Decision Making in International Finance. Part 4 Irrepressible New Issues. 13. Labor Standards and the Environment. Trade and Labor Standards. Trade and The Environment. 14. trade Information. The Nature of Information. Information Issues. The Uruguay Round TRIPS Agreement. Subsidies to High Technology. 15. Cross- Border Flows of People. US Immigration Policy in Historical Perspective. Immigration Today. An Economic Approach to Immigration Policy. The Consequences of Present Policy. Short- Term Entrants. Reprise. Notes. Bibliography. Index.

Many-Valued Loqics P. Edited by Leonard Bolc and Piotr Borowik. Springer. Heidelberg. 2003 $59.94. 303 pages. Contents. Introduction: The History of Automated Reasoning. 1. Basic Notions and Results. 1.1. Basic Notions of Algebra. 1.2. Finite Algebras. 1.3. Completeness of Function Sets. 1.4. Some Properties of the Ses Zn. 2. Gentzen systems for n-Valued Logical Calculi. 2.1. General Remarks. 2.2. Some Identities in Post Algebras. 2.3. A Language for the n-Valued Logical Calculus and Its Semantics. 2.4. A Gentzen System for the n- Valued Propositional Calculus. 2.5. An Alternative Gentzen System for Finite-Valued Logics. 2.6. A Gentzen System for the n-Valued First-Order Predicate Calculus, 2.7. Completeness of the Sequential Predicate Calculus. 3. Multisequential Systems of Takahashi and Rousseau for Finite-Valued Logics. 3.1. Notational Remarks. 3.2. Many-Valued Propsitional Calculi. 3.3. Many-Valued Predicate Calculus. 3.4. Gentzen-Takahashi Systems for Finite-Valued Logics. 3.5. A Gentzen System for a Particular Class of Finite-Valued Logics. 4. The Resolution Principle in n-Valued Logics. 4.1. Historical Remarks. 4.2. The Language of Multi-Valued Predicate Calculus. 4.3. A Supplement on the Semantics. 4.4. Unifying Substitutions. 4.5. Resolution Proof Systems for Finite-Valued Propositional Logics. 5, Minimization Problems in Resolution Proof Systems. 5.1. A Supplement on Propositional Calculi. 5.2. Semantic Trees. 5.3. Proof Trees. 5.4. More About Resolution Proof Systems. 5.5. Matrices Induced by Resolution Proof Systems. 5.6. Minimal Resolution Proof Systems. 5.7. Disjunctive Logics. 5.8. Polarization. 6. Resolution in Finite-Valued First-Order Predicate Calculi. 6.1. Introductory Remarks and Supplements to Semantics. 6.2. Some Identities in Finite Post Algebras. 6.3. Satisfiability Theorems. 6.4. Canonical Models for n-valued Logics. 6.5. The Resolution Principle for the n- Valued Predicate Calculus. 7. overview of Applications. 7.1. Software Specification and verification. 7.1.1. Motivation. 7.1.2. Analytic Tableau method. 7.1.3. Conclusions. 7.2. Interval Arithmetic. 7.2.1, Introduction. 7.2,2. GL3 Logic. 7.2.3. Definition of I Systems and Its properties. 7,2.4. Axiomatization A. 7.2.5. Conclusions. 7.3. Verification of Electronic Circuits. 7.3.1. Introduction. 7.3.2. Logic. 7.3.3. Example. 7.3.4. Conclusions. 8. Selected Applications of Fuzzy Set Theory. 8.1. Introduction. 8,2. Basic Definition. 8.3. Operations on Fuzzy Sets and Fuzzy Relations. 8.3.1. Union and Intersection of sets. 8,3.2. Complement of a Set. 8.3.3. Composition of Relations. 8.3,4. Fuzzy Modifiers. 8.3.5. The Extension Principle. 8.3.6. Lattice Fuzzy Sets. 8,3.7. Fuzzy Logics as generalized Many-Valued Logics. 8.3.8. Fuzzy Logics as Linguistic Logics. 8.3.9. A Generalization of the Modus Ponens Rule. 9. Selected Application of Rough Set Theory. 9.1. Introduction. 9.2. Approximate Knowledge and Rough Sets. 9.2.1. Knowledge Base. 9.2.2. Knowledge Approximation. 9.2,3. Degrees of Knowledge Accuracy. 9.3. Knowledge Reduction. 9.3.1. Knowledge Reduct and Kernel. 9.3.2. Category Reduction. 9.3.3. Dependencies in a Knowledge Base. 9.4, Knowledge Representation Systems. 9.5. Inference from Rough Knowledge. 9.5.1. Introduction. 9.6. Decision Logic. 9.6.1. language of decision Logic. 9.6,2. Semantics of Decision Logic. 9.6.3. Inference. 9.6.4. Decision Algorithms. 9.7. Reduction of Decision Algorithms. Bibliography. Index.

Theory of Games and Economic Behavior. Edited By John von Neumann and Oskar Morgenstern. Princeton University Press. Princeton NJ. 2004. $50,00. 734 pages. Contents. Introduction (By Harold W. Kuhn). Theory of Games and Economic Behavior (John von Neumann and Oskar Morgenstern). Afterword (Areil Rubinstein). Reviews. The American Journal of Sociology (Herbert A. Simon), Bulletin of the American economic Review (Leonid Hurwicz). Economica (T. Barna). Psychometrika (Walter A. Rosenblith). Head I Win and tails You Lose (Paul Samuelson). Big D (Paul Crume). Mathematics of Games

976 BOOK REPORTS

and Economics (E. l~owland). Theory of Games (Clause Chevalley). Mathematical Theory of Poker Is Applied to Business Problems (Will Lissner). A Theory of Strategy (John McDonald). The Collaboration between Oskar Morgenstern and John yon Neumann on the Theory of Games (Osl~r Morgenstern). Index. Credits.

Blow-Up Theory For Elliptic PDEs In Riemannian Geometry. Edited by Olivier Druet, Emmanuel Hebey, Fred- eric Robert. Princeton University Press. Princeton, NJ. 2004. $45.00. 224 pages.

Contents. Preface.

Chapter 1. Background material. 1.1. Riemannian Geometry. 1.2. Basics in Nonlinear Analysis. Chapter 2. The Model Equations. 2.1. Palais-Smale Sequences. 2.2. Strong Solutions of Minimal Energy. 2.3. Strong Solutions of High Energies. 2.4. The Case of the Sphere. Chapter 3. Blow-Up Theory on Sobolev Spaces. 3.1. The H12-Decomposition for Palais-Smale Sequences. 3.2. Subtracting a Bubble and Nonnegative Solutions. 3.3. The De Grigori-Nash-Moser Iterative Scheme for Strong Solutions. Chapter 4. Exhaustion and Weak Pointwise Estimates. 4.1. Weak Pointwise Estimates. 4.2. Exhaustion of Blow-up Points. Chapter 5. Asymptotics When the Energy is of Minimal Type. 5.1. Strong Convergence and Blow. 5.2. Sharp Pointwise Estimates. Chapter 6. Asymptotic When Energy is Arbitrary. 6.1. A Fundamental Estimate: 1. 6.2. Asymptotic Estimate: 2. 6.3. Asymptotic Behavior. Appendix A. The green's Function on Compact Manifolds. Appendix B. Coercivity is Necessary Condition. Bibliography.

Scalable Input/Output. Edited By Daniel A. Reed. The MIT Press. Cambridge. 2004. $35.00. 391 pages. Contents. Preface. 1. I /O Characterization and Analysis (Phyllis Crandall, Ruth A. Aydt, Andrew A. Chien, and Daniel A. Reed). 1.1. Background. 1.2. Experimental Methodology. 1.3. Application Code Suite. 1.4. Electron Scattering Behavior. 1.5. Terrain Rendering Behavior. 1.6. Hartree Fock Behavior. 1.7. Parallel File System Implications. 1.8. Related Work. 1.9. Conclusions and Future Directions. 2. Collective I /O and Large-Scale Data Management (Alok Choudhary, Mahmut Kandemir, Sachin More, Jaechun No, and tLujeev Thakur.) 2.1. Metadata Management System. 2.2. PASSION Runtime System. 2.3. Conclusions. 3. Building Parallel Database for Multidimensional Data (Chailin Chang, Tahsin M. Kurc, Alan Sussman and Joel Saltz). 3.1. Active Data Repositories. 3.2. Motivating Examples. 3.3. ADR Overview. 3.4. ADR System Architecture. 3.5. Customization Examples. 3.6. Experimental Results. 3.7. Current State and Future Work. 4. ADIO: A Framework for High- Performance, Portable Parallel I /O (Rajeev Thakur, William Gropp and Ewing Lusk). 4.1. The Role of ADIO in the SIO Project. 4.2. The ADIO Concept. 4.3. ADIO Design. 4.4. Implementation. 4.5. Performance. 4.6. MPI-IO. 4.7. Conclusions. 5. Informed Prefetching of Collective Input /output Requests (Tara M. Madhyasthat, Garth A. Gibson and Christos Faloutsos). 5.1. Problem Specification: Collective Access Patterns. 5.2. Collective I /O Implementations. 5.3. Proposed Method: Informed Prefetching. 5.4. Experimental Evaluation. 5.5. Collective Sets. 5.6. Related Work. 5.7. Conclusions and Future Directions. 6. Compiler Support for Out-of-Core Arrays on Parallel Machines (Bradley Broom, Rob Fowler, Ken Kennedy, Charles Koebel and Michael Paleczny. 6.1. Annotations for Specifying Out-of-Core Data Structures. 6.2. The I /O System. 6.3. Compiling for Out-of Core Execution. 6.4. Experience with a Prototype Compiler. 6.5. Performance of the prototype. 6.6. Related Work. 6.7. Conclusions. 7, CLIP: A Checkpointing Tool for Message Passing Parallel Programs (Yuqun Chen, James S. Plank and Kai Li). 7.1. Intel Paragon. 7.2. CLIP Programming Interface. 7.3. The Design of CLIP. 7.4. Performance. 7.5. Related Work. 7.6. Conclusions. 8. Learning to Classify Parallel I /O Access Patterns (Tara M. Mahysathat and Daniel A. Reed). 8.1. Access pattern Classification. 8.2. Intelligent Policy Selection. 8.3. Local Classification experiments. 8.4. Global Classification. 8.5. Global Classification Experiments. 8.6. Related Work. 8.7. Conclusions. 9. Thread Scheduling for Out-of-Core Applications with a Memory Server (Yuanyuan Zhou, Limin Wang, Douglas W. Clark, and Kai Li). 9.1. the Memory Server model. 9.2. Fine-grained Thread Scheduling. 9.3. Implementation. 9.4. Performance. 9.5. Related Work. 9.6. Conclusions and Limitations. 10. A Scalability Study of Shared Virtual Memory Systems (Yuanyuan Zhou, Liviu Iftode, and Kai Li). 10.1. Protocols. 10.2. Prototype Implementations. 10.3. Performance. 10.4. Related Work. 10.5. Conclusions. Appendix: Proposal for a Common Parallel File System Programming interface (Peter F. Corbett, Jean-Pierre Prost, Chris Demetriou, Garth Gibson, Erik Riedel, Jim Zelenka, Yuqun Chen, Ed Felten, Kai Li, John Hartman, Larry Peterson, Brian Bershad, Alec Wolman, and Ruth Aydt.) A.1. Overview. A.2. Document Conventions. A.3. The sio_fs.h Include File. A.4. Data Types. A.5. Range Constants. A.6. File Attributes. A.7. Error Reporting. A.8. Basic Operations. A.9. Synchronous File I/O. A.10. Asynchronous File I/). A.11. File Access Pattern Hints. A.12. Client Cache control. A.13. Control Operations. A.14. Extension Support. A.15. Extension Collective I /O/ . A.16. Extension: Fast Copy. A.17. Result Codes for sio_return_t. A.18. Sample Derived Interfaces. References.

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Semantic Inteqration of Heteroqeneous Software Specifications. Edited by Martin Groi3e-Rhode. Springer, Hei- delberg. 2004. 327 pages. $89.95. Contents. 1, Introduction. 1.1. The viewpoint Model of Software Systems Development. 1.2. Integration of Specifications. 1.2.1. Admissible Interpretations, Correspondence and Consistency. 1.2.2. Language-and Method-Independent Integration. 1.3. Requirements of Reference Models and Their Usage. 1.4. The Transformation Systems Reference Model. 1.4.1. Transformation Systems Reference Model. 1.4.1. Transformation Systems. 1.4.2. Development Operations and Relations. 1.4.3. Development Operations and Relations. 1.43. Composition. 1.4.4. Granularity. 1.5. Organization of the Book. 2. Transformation Systems. 2.1. Transition Graphs and Data Spaces. 2.2. Examples. 2.3. Data Spaces from Other Specification Frameworks. 2.4. Objects and Object References. 2.5. Discussion. 3. Specification of Properties. 3.1. Data Space Specification, 3,2. Control Flow Specification. 3.3. Examples. 3.4. Rewriting Algebras with Transformation Rules. 3.5. Specification with Other Formulae. 3.6. Discussion. 4. Development of Transformation Systems. 4.1. Development Operations. 4.2. Extension and Reduction. 4.3. Categorical Structure. 4.4. Refinement and Implementation. 4.5. Examples. 4.6. Preservation of Properties. 4.7. The Institution of Transformation Systems. 4.8. Development w.r.t. Other Specification Frameworks. 4.9. Discussion. 5. Composition of Transformation Systems. 5.1. Binary Composition via Connection Relations. 5.2. Categorical Structure. 5.3. Composition-by Limits. 5.4. Compositional Semantics. 5.5. Compositionality of Properties. 5.6. Compositionality of Developments. 5.7. Morphisms of Transformation System with Distributed Data. 5.8. Construction of General Compositions by Global Limits. 5.9. Sequential Composition. 5.10. Composition w.r.t. Other Specification Frameworks. 5.111 Discussion. 6. Applications to UML Software Specifications. 6.1. Class Diagram Semantics. 6.1.1. Architecture: Class Graphs and Object Graphs. 6.1.2. Internal Structure: Class Signatures and Object States. 6.1.3. Signature Diagrams and System States. 6.1.4. A Language for Object Systems. 6.1.5. Evaluation of expressions. 6.1.6. Further Static Features of Class Diagrams. 6.1.7. State Transformations. 6.2. State Machine Semantics. 6.2.1. Control and Data States. 6.2.2. Transitions and Transformations. 6.3. Composition of State machines. 6.3.1. Asynchronous Communication. 6.3.2. Synchronous Communication. 6.4. Integration of Class Diagrams and State Machines. 6.5. Sequence Diagram Semantics. 6.6. Discussion. 7. Conclusion. 7.1. Summary. 7.2. Further Developments and Applications. 7.2.1. UML Integration. 7.2.2. In- tegration Methods. 7.2.3. Architecture Description. 7.3. Related Approaches. 7.3.1. Integration of Static States and Dynamic Changes. 7.3.2. Categorical Composition of Theories and Models. 7.3.3. Consistency and Integra- tion of viewpoints Specifications. 7.3.4. Semantic Unification of Programming Languages. 7.4. Methodological Remarks. A Partial Algebras and their Specifications. References. Index.

Beyond Geometry. Edited By Lynn Zelevansky with contributions by Valerie L. Hillings. Miklos Peternak, Bran- don Labelle, Peter Frank, Ines Katzenstein, Aleca Le Blanc. The MIT Press, Cambridge. 2004. $49.95. 240 pages. Contents. Foreword. Beyond Geometry: Objects, System, Concepts (Lynn Zelevansky). Section I: the 1940s and 1950s. Concrete Territory: Geometric Art, Group Formation, and Self-Definition. Section 2: The Object and the Body. Art Research, Experiment: Scientific methods and Systematic Concepts (Miklos Peternak). Section 3 Light and Movement. Performing Geometry: Music's Affair with Numbers, Systems, and Procedures. Section 4 Repetition and Seriality. Geometric Literature: From Concrete Poetry to Artists ' Books (Peter Frank). Section 5: The Object Redefined. Reality Rush: Shifts of Form 1965-1968 (Ines Katzenstein. Section 6: the Problem of Painting. Checklist. Chronology (Aleca Le Blanc). Acknowledgments. Lenders. Index

Linearization of Chains and Sideward Movement. Edited by Jairo Nunes. The MIT Press. Cambridge, MA. 2004. $26.00. 196 pages. Contents. Series Foreword. Acknowledgments. Introduction. 1. Linearization and Phonetic Realization of Chains. 1.1. Introduction. 1.2. Advantages of the Copy theory of Movement. 1.3. Traces and the Linear Correspondence Axiom, 1.4. Traces and Phonetic Realization. 1.5. Linearization of Chains and Phonetic Realization of Chain Links. 1.6. Remnant Movement. 1.7. Conclusion. 2. Traces, Uninterpretable Features, and Accessibility to the Computational System. 2.1. Introduction. 2.2. Traces and Uninterpretable Features. 2.3. Traces Accessibility to the Computational System. 2.4. Conclusion.

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31 The Copy + Merge Theory and Sideward Movement. 3.1. Introduction: The Copy + Merge Theory of Movement. 3.2. Condition on Chain Formation. 3.3. Sideward Movement. 3.4. Parasitic Gaps. 3.5. Across- the-Board Extraction. 3.6. Differences between Parasitic Gap and Across the Board Extraction Constructions. 3.7. Directionality of Sideward Movement and Cyclic Access to the Numeration. 3.8. Sideward Movement and Cyclicity of Merge. 3.9. Further Extensions. 3.10. Conclusion. Conclusion. Notes. References. Index.

Modularity in Development and Evolution. Edited by Gerhard Schlosser, and Gunter P. Wagner. The University of Chicago Press. 2004. $35.00. Contents. Preface. 1. Introduction: The Modularity Concept in Developmental and Evolutionary Biology (Gerhard Schlosser and Gunter P. Wagner). Part 1. The Molecular and Developmental Basis of Modularity. 2. Selector Genes and the Genetic Control of Developmental Modules (Craig Nelson). 3. the Basic Helix-Loop-Helix-Proteins in Vertebrate and Invertebrate Neurogenesis (Uwe Strahle and Patrick Blader). 4. The Pax/Six/Eya/Dach/ Network in Development and Evolution (Gabrielle Kardon, Tiffany A. Heanue, and Clifford J. Tabin). 5. The Notch Signaling Module (Jose F. De Celis). 6. Sonic Hedgehog and Writ Signaling Pathways during Development and Evolution (Anne- Gaelle Borycki). 7. Modular Pleiotropic Effects of Quantitative Trait Loci on Morphological Traits (James M. Cheverud). 8. Central Nervous System Development: From Embryonic Modules to Functional Modules (Christoph Redies and Luis Puelles). Part 2. Recognition and Modeling of Modules. 9. Synexpression Groups: Genetic Modules and Embryonic De- velopment (Christof Niehrs). 10. Systematic Exploration and Mining of Gene Expression Data Provides Evidence for Higher-Order , Modular Regulation (Roland Somogyi, Stefanie Fuhrman, Gary Anderson, Chris Madill, Larry D. Greller, and Bernard Change). 11. Qualitative Analysis of gene Networks: Toward the Delineation of Cross- Regulatory Modules. (Denis Thieffry and Lucas Sanchez). 12. Exploring Modularity with Dynamical Models of Gene Networks (George Von Daesow and Eli Meir). 13. Basins of Attraction in Network Dynamics: A Conceptual Framework for Bimolecular Networks (Andrew Wuensche). Part 3. The Evolutionary Dynamics and Origin of Modules. 14. Informational Accreation, Gene Duplication, and the Mechanisms of Genetic Module Parcellation (Allan G. Force, William A. Cresko, and F. Bryan Pickett). 15. The Role of Genetic Architecture Constraints in the Origin of Variational Modularity (Gunter P. Wagner and Jason G. Mezey). 16. Generative Entrenchment, Modularity and Evolvability: When Genic Selection Meets the Whole Organism (William C. Wimsatt and Jeffery C. Schank). 17. Starting the Segmentation Gene Cascade in Insects (Urs Schmidt-Ott and Ernst A. Wimmer). 18. The Evolution of Nematode Development: How Cells and Genes Change their Function (Ralf J. Sommer). 19. Modularity in the Evolution of Vertebrae Appendages (Neil H. Shubin and Marcus C. Davis). Part 4. Individuals as Modules in Higher-Level Units. 20. The Individuals as a Module: Silitary-Colonial Transitions in Metazoan Evolution and Development (Brad Davidson, Molly W. Jacobs, and Billie J. Swalla). 21. Evolvability, Modularity and Individuality during the Transition to Mulitcellularity in Volvocalean Green Alga (Aurora M. Nedelcu, and Richard E. Michod). 22. Symbiosis, Evolvability and Modularity (Kim Sterelny). Synthesis. 23. The Role of Modules in Development and Evolution (Gerhard Schlosser) Contributors. Index.

Numerical Methods with Proqrams in BASIC, FORTRAN, Pascal and C-t-+. Edited By S. Balachandra Rao and C.K. Shantha. Sangam Books. 2004. 17.95£. 490 pages. Contents. List of Programs. Preface. Acknowledgements. 1. Numbers, errors, and accuracy. 1.1. Why numerical methods? 1.2. Accuracy and error. 1.3. Decimal and binary number systems. 1.3.1. Exponential (or scientific) notation. 1.3.2. Conversion from binary to decimal form. 1.3.3. Algorithm for decimal to binary conversion. 1.4. Truncation, rounding-off and algorithmic errors. 1.5. Absolute and relative error. 1.6. Propagation of error. 1.7. A general formula for error estimation. Exercises. 2. Iterative process. 2.1. Solution of equation .f(x) -- 0. 2.2. existence and uniqueness of a root 2.3. Convergence of the iterative method. 2.4. Geometrical representation. 2.5. Aitken's ~2-process of acceleration. 2.5.1. Algorithm for Aitken's A2-process. Exercises. 3. Solution of nonlinear equations. 3.1. Introduction. 3.2. Bisection method. 3.2.1. Algorithm for the bisection method. 3.2.2. Program for interval bisection method. 3.3. Newton-Raphson method. 3.3.1. Limitations of the Newton-Raphson method. 3.3.2. Convergence of the Newton-Raphson method. 3.3.3. Algorithm for the Newton- Raphson method. 3.3.4. Program for the Enwton-Raphson method. 3.4. Secant method. 3.4.1. Algorithm for the Secant method. 3.5. Regula Falsi method (or method of false position). 3.5.1. Algorithm for Regula Falsi method. Exercises 3A. 3.6. Newton-Raphson method for polynomial equations. 3.6.1. Descartes' rule of signs. 3.6.2. Nested multiplication. Exercises 3B.

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4. Finite differences and interpolation. 4.1. Introduction. 4.2. Difference operators. 4.2.1 An Alternative notation. 4.3. Factorial notation. 4.3.1. Expressing a polynomial in factorial notation. 4.4. Differences of zero. 4,4.1. Definition of x( - n). 4.4,2. Differences of x( - n). 4.5. Backward differences. 4.6. Shift operator (E). 4.7. Central difference operator ($). 4.8. the Averaging operator (#). 4.9. Divided differences. 4.10. Divided difference for equally space arguments. 4.11. properties of divided differences. 4.12. Finite differences and differentiation. 4.13. Errom in a difference table. 4.14. Some Important relations between the operators. Exercises A. 4.15. Finite difference interpolation. 4.16. Interpolation using forward difference (with equal intervals). 4.17. Newton- Gregory formula for backward interpolation. 4.18. Change of origin and scale. 4.19. Newton's formula for divided differences. 4.20. Lagrange's polynomial interpolation. 4.21. Central difference formulae. 4.22. Gauss forward formula for central difference. 4.23. Gauss backward difference formula. 4.24. Stirling's formula. 4.25. Bessel's interpolation formula. 4,26. Everett's interpolation formula. 4.27. Choice of interpolation formulas. 4.28. Errors in interpolation. Exercises 4B. 5. Numerical differentiation. 5.1. Introduction. 5.2. Numerical differentiation. 5.3. Differentiation based on equal-interval interpolation. 5.4. Second-order derivative. 5.5. Derivatives using Newton's backward difference formula. 5.6. Derivatives using central difference formula. 5.6.1. Based on Bessel's formula. 5.6.2. Based on Stirling's formula. 5.7. Differentiation based on Lagrange's interpolation formula. Exercises. 6. Numerical integration. 6.1. Introduction, 6.2. General quadrature formula. 6.3. Trapezium rule. 6.4. Trapezoidal rule. 6.5. Error in the trapezium rule. 6.6. Simpson's rule. 6.7. Simpsen's three-eighths rule. 6.8. Weddle's rule. 6.9. Errors in quadrature methods. 6.10. Romberg integration. 6.11. Gauss quadrature formula. 6.12. Lobatto's formula. 6.13. Use of the quadrature formula. 6.14. Central difference quadrature formula. Exercises. 7. Systems of linear equations. 7.1. Introduction. 7.2. Cramer's rule. 7.3. Classification of numerical methods. 7.4. Geometrical interpretation. 7.5. Gauss elimination method. 7.5.1. Generalization of the elimination method. 7.6. Choice of pivots. 7.6.1. Algorithm of gaussian elimination. 7.7. Complete pivoting. 7.8. Accuracy of a solution. 7.9. Identifying an ill-conditioned system. 7.10. Improvement of the solution. 7.11. Number of arith- metical operations required for the Gauss elimination method. 7.12. Gauss-Jordan elimination method. 7.12.1. Algorithm for the Gauss-Jordan method. 7.13. Triangularisation method of Factorisation process (Choleski's process). 7.14. Inverse of a matrix by compact schemes. 7.15. Iterative methods. 7.15,1. Jacobi's method. 7.15.1.1. Convergence of Jacobi's method. 7.15.2. Gauss-Seidel method. 7.15.2.1. Algorithm for Gauss-Seidel method. 7.16. Comparison of various methods. Exercises. 8. Eigenvalues and eigenvectors. 8.1. Introduction, 8.2. LeVerrier-Faddeev method. 8.3. Some important properties of eigenvalues and eigenvectors. 8.4. Determination of eigenvalues and eigenvectors. 8.5. Iterative method (power method). 8.6. Finding all eigenvalues of a matrix. 8.7. Smallest eigenvalue by iterative method. 8.8. Transformation methods. 8.9. Jacobi method. 8.10. Disadvantages of Jacobi's method. 8.11. Given's method. 8.12. Eigenvalues of a tridiagonal matrix. 8.13. Householder's method. 8.14. Methods for non- symmetric matrices. 8.14.1. The L-R method. 8.14.2, Q-R transformation method. 8.15. Choice of method. Exercises. 9 Differential equations. 9.1. Introduction. 9.2. preliminaries and classification. 9.2.1. General form of an ordinary differential equation. 9.2.2. Solution of an ordinary differential equation. 9.2.3. Order and degree of an ordinary differential equation. 9.2.4. Linear and nonlinear differential equations. 9.2.5. Initial value problem. 9.2.6. Boundary value problem. 9.3. Taylor series method. 9.3.1. Algorithm for Taylor series method. 9.4. Picard's Method (or method of successive approximation). 9,4.1. Algorithm for Picard's method. 9.5. Euler's method. 9.5.1. Algorithm for Euler's method. 9.5.2. Graphical representation of Euler's method. 9.5.3. Error estimation for Euler's method. 9.6. Improved Euler method. 9.6.1. Error estimation for the improved Euler method. Exercises 9A. 9.7. Euler's predictor-corrector method. 9.8. Modified Euler method. Exercises 9B. 9.9. Runge-Kutta methods. 9.9.1. Algorithm for Runge-Kutta method of second order. 9.9.2. Error estimation in Runge-Kutta method of second order. 9.10. Runge-Kutta method of Fourth Order. 9.10.1. Algorithm for Runge-Kutta fourth-order method. 9.10.2. Error estimation in Runge-Kutta method of the fourth order. 9.10.3. Comparison between the second-order and fourth-order. 9.11. Extensions of Runge-Kutta method. 9.11.1. Runge- Kutta-Gill method. 9.11,2. Runge-Kutta~Merson method. 9.11.3. Runge-Kutta-Nutcher method. 9.11.4. Kutta- Nystrom method. Exercises 9C. 10~ A primer to computer programming. 10.1. Introduction, 10.2. Communication with the computer. 10.3. Identifiers. 10.4. Input and output. 10.5. Control statements. 10.5.1. Relations. 10.5.2. Boolean conditions. 10.5.3. The IF statement. 10.5.4. Unconditional looping. 10.5.5. Conditional looping. 10.5.6. Nested Looping. 10.5.7. The GOTO statement. 10.6. Arrays. 10.6.1 Singly subscribed array. 10.6.2. Multidimensional array. 10.7. Subprograms. 10.7.1. Procedures in Pascal. Appendix: C÷+ programs. Answers to problems. Bibliography. Index.

Shapinq the Network Society. Edited by Douglas Schuler and Peter Day. The MIT Press. Cambridge, MA. 2004. $45.00. 433 pages. Contents. Introduction (Douglas Schuler and Peter Day).

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1. Shaping the Network Society: Opportunities and Challenges (Dougals Shuler and Peter Day). I. Civilizing the Network Society. 2. U.S. Global cyberspace (Oliver Boyd-Barrett). 3. Shaping Technology for the "Good Life": the Technological Imperative versus the Social Imperative. 4 Human Rights in the Global Billboard Society (Cees J. Hamelink). II. Global Tales of the Civil Network Society. 5. A census of Public Computing in Toledo, Ohio (Kate Williams and Abdul Alkalimat). 6. A Polder Model in Cyberspace: Amsterdam Public Digital Culture. (Geert Lovink and Patrice Riemens). 7. Community Networks Go Virtual: Tracing the Evolution of ICT in Buenos Aires and Montevideo (Susana Finquelivich). 8. Civil Networking in A Hostile Environment: Experiences in the Former Yugoslavia (Veran Matic). 9. Rethinking Telecenters: Microbanks and Remittance Flows-Reflections from Mexico (Scott S. Robinson. 10. The Role of Community Networks in Shaping the Network Society: Enabling People to Develop Their Own Projects (Fiorella de Cindio). III. Building a New Public Sphere in Cyberspace. 11. Information technology and the International Public Sphere (Craig Calhoun). 12. What Do We Need to Know about the Future We're Creating? Technobiographical Reflections (Howard Rheingold). 13. Libraries: The Information Commons of Civil Society (Nancy Kranich). 14. The Soil of Cyberspace: historical Archeologies of the Blacksburg Electronic Village and the Seattle Community Network (David Silver) 15. Globalization and Media Democracy: The Case of Indymedia (Douglas Morris) 16 Prospects for a New Public Sphere (Peter Day and Douglas Schuler). References. Contributors. Index.

Comb•inq Pattern Classifiers. Edited by Ludmila I. Kuncheva. Wiley. Hoboken NJ. 2004. $89.95, Contents. Preface. Acknowledgments. Notation and Acronyms. 1. Fundamentals of Pat tern Recognition. 1.1. Basic Concepts: Class, Feature, and Data Set. 1.1.1. Pattern recognition Cycle. 1.1.2. Classes and Class Labels. 1.1.3. Features. 1.1.4. Da ta Set. 1.2. Classifier, Discriminant Functions, and Classification Regions. 1.3. Classification Error and Classification Accuracy. 1.3.1. Calculation of the Error. 1.3.2. Training and Testing Data Sets. 1.3.3. Confusion Matrices and Loss matrices. 1.4. Experimental Comparison of Classifiers. 1.4.1. McNemar and Difference of Proportion Tests. 1.4.2. Cochran's Q Test and F- Test. 1.4.3. Cross-Validation Tests. 1,4.4. Experiment Design. 1.5. Bayes Decision Theory. 1.5.1. Probabilistic Framework. 1.5.2. Normal Distribution. 1.5.3. Generate Your Own Data. 1.5.4. Discriminant Functions and Decision Boudnaries. 1.5.5. Bayes Error. 1.5.6. Multinomial Selection Procedure for Comparing Classifiers. 1.6. Taxonomy of Classifier Design Methods. 1.7. Clusterin. Appendix 1A. K-Hold-Out Paired t-test. Appendix lB. K-Fold Cross-Validation Paired t-Test. Appendix 1C. 5~c2ev paired t-Test. Appendix 1D. 500 Generations of Training/Testing Data and Calculation of the Paired t-Test Statistic. Appendix 1E. Data Generation: Lissajous Figure Data. 2. Base Classifiers. 2.1. Linear and Quadratic Classifiers. 2.1.1. Linear Discriminant Classifier. 2.1.2. Quadratic Discriminant Classifier. 2.1.3. Using Data Weights with A Linear Discriminant Classifier and Quadratic Dis- criminant Classifier. 2.1,4. Regualrized Discriminanat Analysis. 2.2. Nonparametric Classifiers. 2.2.2. Parzen Classifier. 2.3. The k-Nearest Neighbor Rule. 2.3.1. theoretical Background. 2.3.2. Finding k-nn Prototypes. 2.3.3. k-nn Variants. 2.4. Tree classifiers. 2.4.1. Binary Versus Nonbinary Splits. 2.4.2. Selection of the Feature for a Node. 2.4.3. Stopping Criterion. 2.4.4. Pruning Methods. 2.5. Neural Networks. 2.5.1. Neurons. 2.5.2. Rosenblatt 's Perceptron. 2.5.3. MultiLayer Perceptron. 2.5.4, Backpropagation Training of MultiLayer Percptron. Appendix 2A. Matlab Code for tree Classifier. Appendix 2B. Matlab Code for Neural Network Classifiers. 3. Multiple Classifier System. 3.1. Philosophy. 3.1.1. Statistical. 3.1.2. Computational. 3.1.3. Representationl 3.2. Terminologies and Taxonomies. 3.2.1. Fusion and Selection. 3.2.2. Decision Optimization and Coverage Optimization. 3.2.3. Trainable and Nontrainable Ensembles. 3.3. To Train or Not to Train? 3.3.1. Tips for Training the Ensemble. 3.3.2. Idea of Stacked Generalization. 3.4. Remarks. 4. Fusion of Label outputs. 4.1. Types of Classifier Outputs. 4.2. Majority Vote. 4.2.1. Democracy in Classifier Combination. 4~2.2. Limits on the Majority Vote Accuracy: An Example. 4.2.3. Patterns of Success and failure. 4.3. Weighted Majority Vote. 4,4. Na:/ve Bays Combination. 4.5. Multinomial Methods. 4.5.1. Behavior Knowledge Space Method. 4.5.2. Wernecke's Method. 4.6. Probabilistic Approximation. 4.6.1. Calculation of the Probability Estimates. 4.6.2. Construction of the Tree. 4,7. Classifier Combination Using Singular value Decomposition. 4,8. Conclusions. Appendix 4A. Matan's Proof for the Limits on the Majority Vote Accuracy. Appendix 4B. Probabilistic Approximation of the Joint pmf for Class-Label Outputs. 5. Fusion of Continuous-Valued Outputs. 5.1. How do We get Portability Outputs? 5.1.1. Probabilities Based on Discriminant Scores. 5.1.2. Probabilities Based on Counts: Laplace Estimator. 5,2, Class-Conscious Combiners. 5.2.1. Nontrainable Combiners. 5.2.2. Trainable Combiners. 5.3. Class-Indifferent Combiners. 5.3.1. Decision Templates, 5.3.2. Dempster-Shafer Combination. 5.4. Where Do the Simple Combiners Come from? 5.4.1. Conditionally Independent Representations. 5.4.2. A Bayesian Perspective 5,4.3 The Supra Bayesian Approach. 5.4.4. Kullbacl-Leibler Divergence. 5.4.5. Consensus Theory. 5.5. Comments. Appendix 5A. Calculation of A for the Fuzzy Integral Combiner.

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6. Classifier Selection. 6.1. Preliminaries. 6.2. Why Classifier Selection Works. 6.3. Estimating Local Competence Dynamically. 6.3.1. Decision- Independent Estimates. 6.3.2. Decision-Dependent Estimates. 6.3.3. Tie-Break for Classifiers with Equal Competences. 6.4. Preestimation of the Competence Regions. 6.4.1. Clustering. 6.4.2. Selective Clustering. 6.5. Selection or Fusion? 6.6. Base Classifiers and Mixture of Experts. 7. Bagging and Boosting. 7.1. Bagging. 7.1.1. Origins: Bagging Predictors. 7.1.2. Why Does Bagging Work? 7.1.3. Variants of Bagging. 7.2. Boosting. 7.2.1. Origins: Algorithm Hedge (/3). 7.2.2. AdaBoost Algorithm. 7.2.3. arc-x4 Algorithm. 7.2.4. Why Does Adai3oost Work? 7.2.5. Variants of Boosting. 7.3. Bias-Variance Decomposition. 7.3.1. Bias~ Variance and Noise of the Classification Error. 7.3.2. Decomposition of the Error. 7.3.3. How Do Bagging and Boosting Affect Bias and. Variance? 7.4. Which is Better: Bagging or Boosting? Appendix 7A. Proof of the error Bound on the Training Set for AdaBoost (Two Classes). Appendix 7B. Proof of the Error Bound on the Training Set for AdaBoost (c Classes). 8. Miscellanea. 8.1. Feature Selection. 8.1.1. Natural Grouping. 8.1.2. Random Selection. 8.1.3. Nonrandom Selection. 8.1.4. Genetic Algorithms. 8.1.5. Ensemble methods for Feature Selection. 8.2. Error Correcting Output Codes. 8.2.1. Code Designs. 8.2.2. Implementation Issues. 8.2.3. Error Correcting Output Codes, Voting and Decision Templates. 8.2.4. Soft Error Correcting Output Code Labels and Pairwise Classification. 8.2.5. Comments and Further Directions. 8.3 Combining Clustering Results. 8.3.1. Measuring Similarity Between Partitions. 8.3.2. Evaluating Clustering Algorithms. 8.3.3. Cluster Ensembles. Appendix 8A. Exhaustive Generation of Error Correcting Output Codes. Appendix 8B. Random Generation of Error Correcting Output Codes. Appendix 8C. Model Explorer Algorithm for Determining the Number of Clusters c. 9. Theoretical Views and Results. 9.1. Equivalence of Simple Combination Rules. 9.1.1. Equivalence of MINI- MUM and MAXIMUM Combiners for Two Classes. 9.1.2. Equivalence of Majority Vote and Median Combiners for Two Classes and Odd Number of Classifiers. 9.2. Added Error for the Mean Combination Rule. 9.2.1. Added Error of an Individual Classifier. 9.2.2. Added Error of the Ensemble. 9.2.3. Relationships Between the Individ- ual Outputs ' Correlation and the ensemble Error. 9.2.4. Questioning the Assumptions and Identifying Further Problems. 9.3. Added Error for the Weighted Mean Combination. 9.3.1. Error Formula. 9.3.2. Optimal Weights for Independent classifiers. 9.4. Ensemble Error for the Weighted mean Combination. 9,4.1. Individual error. 9.4.2. minimum and Maximum. 9.4.3. mean. 9.4.4. Median and Majority Vote. 9.4.5. Oracle. 9.4.6. Example. 10. Diversity in Classifier Ensembles. 10.1. What is Diversity? 10.1.1. Diversity in Biology. 10.1.2. Diversity in Software engineering. 10.1.3. Statistical measures of Relationship. 10.2. Measuring Diversity in Classifier Ensembles. 10.2.1. Pairwise Measures. 10.2.2. Nonpairwise Measures. 10.3. Relationship Between Diversity and Accuracy. 10.3.1. Example. 10.3.2. Relationship Patterns. 10.4. using Diversity. 10.4.1. Diversity for Finding Bounds and Theoretical Relationships. 10.4.2. Diversity for Visualization. 10.4.3. Overproduce and Select. 10.4.4. Diversity for Building the Ensemble. 10.5. Conclusions: Diversity of Diversity. Appendix 10A. Equivalence Between the Averaged Disagreement Measure Day and Kohavei-Wolpert VarianceKW/323. Appendix 10B. Matlab Code for Some Overproduce and Select Algorithms. References. Index.

Unsolved Problems in Mathematical Systems ~ Control Theory. Edited By Vincent D. Blondel &: Alexandre Megretski. Princeton University Press. 2004. $39.50. 360 pages. Contents. Preface. Associate Editors. Website. Part I. Linear systems. Problem 1.1. Stability and composition of transfer functions (Guilermo Fernandez-Anaya, Juan Carlos Martines- Garcia). Problem 1.2. The realization problem for Herglotz-Nevanlinna functions (Seppo Hassi, Henk deSnoo, Edward Tsekanovskii). Problem 1.3. Does any analytic contractive operator function on the polydisk have a dissipative scattering nD realization? (Dmitry S. Kalyuzhniy-Verbovetzsky). Problem 1.4. Partial disturbance decoupling with stability (Juan Carlos Martinez-Garcia, Michael Malabre, Vladimir Kucera). Problem 1.5. Is Monopoli's model reference adaptive controller correct? (A.S. Morse). Problem 1.6 Model reduction of delay systems (Jonathan R. Partinton). Problem 1.7 Schur extremal problems (Lev Sakhnocich). Problem 1.8. The elusive iff test for time-controllability of behaviors (Amol J. Sasane). Problem 1.9. A Farkas lemma for behavioral inequalities (A.A. (Tonny) ten Dam, J.W. (Hans) Nieuwenhuis). Problem 1.10. Regular feedback implementability of linear differential behaviors (H.L. Trentelman). Problem 1.11. Riccati Stability (Erik I. Verriest). Problem 1.12. State and first order representations (Jan C. Willems). Problem 1.13. Projection of State space realizations (Antoine Vandendorpe, Paul Van Dooren). Part 2. Stochastic Systems. Problem 2.1. On error of estimation and minimum of cost for wide band noise driven systems (Agamirza E. Bashirov). Problem 2.2, On the stability of random matrices (Giuseppe C. Calafiore, Fabrizio Dabbene). Problem 2.3. Aspects of Fisher geometry for stochastic linear systems (Bernard Hanzon, Rag Peters). Problem 2.4. On the convergence of normal forms for analytic control systems (Wei Kang, Arthur J. Krener). Part 3. Nonlinear Systems. Problem 3.1. Minimum time control of the Kepler equation (Jean-Baptiste Caillau, Joseph Gergaud, Joseph Noailes). Problem 3.2. Linearization of linearly controllable system (R. Devanathan) Problem 3.3. Bases for Lie algebras and a continuous CBH formula (Matthias Kawski). Problem 3.4. An extended gradient conjecture (Luis Carlos Martins Jr., Geraldo Nunes Silva). Problem 3.5. Optimal transaction costs from a

982 BOOK REPORTS

Stackelberg perspective (Geert Jan Olsder). Problem 3.6. Does cheap control solve a singular nonlinear quadratic problem? (Yuri V. Orlov). Problem 3.7. Delta-Sigma modulator synthesis (Anders Rantzer). Problem 3.8. Determining of various asymptotic of solutions of nonlinear time-optimal problems via right ideals in the moment algebra (G.M. Skylar, S. Yu. Igatovich). Problem 3.9. Dynamics of principle and minor component flows (U. Helmke, S. Yoshizawa, R. Evans, J.H. Manton, and I.M.Y. Marcels). Part 4. Discrete Event, Hybrid Systems. Problem 4.1. L2-induced gains of switched linear systems (Joao P. Hespanha). Problem 4.2. The state partitioning problem of quantized systems (Jan Lunze) Problem 4.3. Feedback control in flowshops (S.P. Sethi and Q. Zhang). Problem 4.4. Decentralized control with communication between controllers (Jan H. van Schuppen). Part 5. Distributed parameter Systems. Problem 5.1. Infinite dimensional back, stepping for nonlinear parabolic PDEs (Andras Balogh, Miroslav Kristic). Problem 5.2. The dynamical Lame system with boundary control: On the structure of reachable sets (M.I. Belishev). Problem 5.3. Null-controllability of the heat equation in unbounded domains (Sorin Micu, Enrique Zuazua). Problem 5.4. Is the conservative wave equation regular? (George Weiss). Problem 5.5. Exact controllability of the semilinear wave equation (Xu Zhang, Enrique Zuasua). Problem 5.6. Some control problems in electromagnetics and fluid dynamics (Lorella Fatone, Maria Christina Recchioni, Francesco Zirilli). Part 6. Stability, Stabilization. Problem 6.1. Copositive Lyapunov functions (M.K. Camlibel, J.M. Schumacher). Problem 6.2. The strong stabilization problem for linear tiem-varying systems (Avraham Feintuch). Problem 6.3. Robustness of transient behavior (Dierdrich Hinrichsen, Elamr Plischke, Fabian Wirth). Problem 6.4. Lie algebras and stability of switched nonlinear systems (Daniel Liberzon). Problem 6.5. Robust stability test for interval frac- tional order linear systems (Ivo Petras, YangQuan Chean, Blas M. Vinagre). Problem 6.6. Delay-independent and delay-dependent Aizerman problem 9Vladimir Rasvan). Problem 6.7. Open problems in control of linear discrete multidimensional systems (Li Xu, Zhiping Lin, Jiang-Qian Ying, Osami Saito, Yoshihisa Anazawa). Problem 6.8. An open problem in adaptive nonlinear control theory (Leonid S. Zhiteckij). Problem 6.9. Generalized Lyapunov theory and its omega-transformable regions (Sheng- Guo Wang). Problem 6.10. Smooth Lyapunov characterization of measurements to error stability (Brian P. Ingalls, Eduardo D. Sontag). Part 7. ControUability~ Observability. Problem 7.1. Time for local controllability of a 1-D tank containing a fluid modeled by the shallow water equations (Jean-Michel Coron). 7.2. A Hautns test for infinite- dimensional systems (Birgit Jacob, Hans Zwart). Problem 7.3. Three problems in the field of observability (Phillipe Jouan). Problem 7.4. Control of the KdV equation (Lionel Roiser). Part 8. Robustness, Robust, Robust Control. Problem 8.1. Heo-norm approximation (A.C. Antroulas, A. Astolfi). Problem 8.2. Noniterative computation of optimal value in H oo control (Ben M. Chen). Problem 8.3. Determining the least upper bound on the achievable delay margin (Daniel E. Davison, Daniel E. Miller). Problem 8.4. Stable controller coefficient perturbation in floating point implementation (Jun Wu, Sheng Chen). Part 9. Identification, Signal processing. Problem 9.1. A conjecture on Lyapunov equations and principal angles in subspace identification (Katrien De Cock, Bart De Moor). Problem 9.2. Stability of a Nonlinear adaptive system for filtering and parameter estimation (Masoud Karimi-Ghartenmani, Alireza K. Ziarani). Part 10. Algorithms, Computation. Problem 10.1. Root-clustering for multivariatepolynomials and robust stabil- ity analysis (Pierre-Alexandre Bliman). Problem 10.2. When is a pair of matrices stable? Problems 10.3. Freeness of multiplicative matrix semigroups (Vincent D. Blondel, Julien Cassaigne, Juhani Karhumaki). Problem 10.4. Vecotr-valued quadratic fors incontrol theory (Francesco Bullo, Jorge Cortes, Andrew D. Lewis, Sonia Martinez). Problem 10.5. Nilpotent bases of distribution (Henry G. Hermes, Matthias Kawski). Problem 10.6. What is the characteristic polynomial of a signal flow graph? (Andrew D. Lewis). Problem 10.7. Open Problems in Randomized ~ analysis (Onur Toker).

Introduction to Virtual Reality. Edited By John Vince. Springer, Heidelberg. 2004. $59.95. 163 pages. Contents. 1 Virtual Reality. 1.1. Introduction. 1.2. What is VR? 1.3. Who Should Read This Book? 1.4. The Aims

and Objectives of This Book. 1.5. Assumptions Made in This Book. 1.6. How to Use This Book. 1.7. Some VR Concepts and Terms. 1.8. Navigation and Interaction. 1.9. Immersion and Presence. 1.10. What is Not VR? 1.11. The Internet. 1.12. Summary. 2. The Benefits of VR. 2.1. Introduction. 2.2. 3D Visualization. 2.3. Navigation. 2.4. Interaction. 2.5. Physical Simulation. 2.6. VEs. 2.7. Applications. 2.8. Summary. 3. 3d Computer graphics. 3.1. Introduction. 3.2. Form Computer Graphics to VR. 3.3. Modeling Objects. 3.4. Dynamic Objects. 3.5. Constraints. 3.6. Collision Detection. 3.7. Perspective views. 3.8. 3D Clipping. 3.9. Stereoscopic Vision. 3.10. Rendering the Image. 3.11. Rendering Algorithms. 3.12. Texture mapping. 3.13. Bump Mapping. 3.14. environment Mapping. 3.15. Shadows. 3.16. Radiosity. 3.17. Other Computer Graphics techniques. 3.18. Summary. 4. Human Factors. 4.1. Introduction. 4.2. Vision. 4.3. Vision and Display Technology. 4.4. Hearing. 4.5. Tactile. 4.6. Equilibrium. 4.7. Summary. 5. VR Hardware. 5.1. Introduction. 5.2. Computers. 5.3. Tracking. 5.4. Input Devices. 5.5. Output Devices. 5.6. Glasses. 5.7. Display. 5.8. Audio. 5.9. Summary. 6. VR Software. 6.1. Introduction. 6.2. VR Software Features. 6.3. Web-Based VR. 6.4. Divisions; sdVISE. 6.5. Blueberry3D. 6.6. Boston Dynamics. 6.7. MultiGen. 6.8. Summary.

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7. VR Applications. 7.1. Introduction. 7.2. Industrial. 7.3. Training Simulators. 7.4. Entertainment. 7.5. VR Centres. 7.6. Summary. 8. Conclusion. 8.1. The Past. 8.2. Today. 8.3. Conclusion. Glossary. Appendices. Appendix A. VRML Web Sites. Appendix B. HMDs. Appendix C. Trackers. Appendix D. VRML Program. Appendix E. Websites for VR Products. References. Index.

Comprehensive Mathematics for Computer Scientists 1. Edited by Guerino Mazzola, Gerard Milmeister, Jody Weissman. Springer, Heidelberg. 2004. $39.95. 357 pgs. Contents. I. Sets, Numbers, and Graphs. 1. Fundamentals-Concepts and Logic. 1.1. Propositional Logic. 1.2. Architecture of Concepts. 2. Axiomatic Set Theory. 2.1. The Axioms. 2.2. Basic Concepts and Results. 3. Boolean Set Algebra. 3.1 The Boolean Algebra of Subsets. 4. Functions and Relations. 4.1. Graphs and Fucntions. 4.2. Realtions. 5. Ordinal and natural Numbers. 5.1. Ordinal Numbers. 5.2. Natural numbers. 6. Recursion Theorem and Universal Properties. 6.1. Recursion Theorem. 6.2. Universal Properties. 6.3. Universal Properties in Relational Database Theory. 7. Natural Arithmetic. 7.1. Natural Operations. 7.2. Euclid and the Normal Forms. 8. Infinities. 8.1. The Diagonalization Procedure. 9. The Classical Number Domains Z, Q, and C. 9.1 Integers Z. 9.2 Rationals Q. 9.3. Real Numbers R. 9.4. Complex Numbers C. 1-Categories and Graphs. 10.1. Directed and Undirected Graphs. 10.2. Morphisms of Digraphs and Graphs. 10.3. Cycles. 11. Contruction of Graphs. 12. Some Special Graphs. 12.1. n-ary Trees. 12.2. Moore Graphs. 12. Planarity. 13.1. Euler's Formula for Polyhedra. 13.2. Kuratowki's Planarity Theorem. 14. First Advance Topic. II. Algebra, Formal Logic, and Linear Geometry. 15. Monoids, Groups, Rings, and Fields. 15.1. Monoids. 15.2. Groups. 15.3. Rings. 15.4. Fields. 16. Primes. 16.1. Prime Factorization. 16.2. Roots of Polynomials and Interpolation. 17. Formal Propositional Logic. 17.1. Syntactics: The Language of Formal Propsitional Logic. 17.2. semantics: Logical Algebras. 17.3. Signification: Valuations. 17.4. Axiomatics. 18. Formal Predicate Logic. 18.1. Syntacties: First-order Language. 18.2. Semantics: T-Structures. 18.3. Significations: Models. 19. Languages, Grammars, and Automata. 19.1. Languages. 19.2. Grammars. 19.3. Automata and Acceptors. 20. Categories of matrixes. 20.1. What Matirxes Are. 20.2. Standard Operations on Matrixes. 20.3. Square Matrixes and their Determinant. 21. Modules and Vector Spaces. 22. Linear Dependence, Bases, and Dimension. 22.1. Bases in Vector Spaces. 22.2. Equations. 22.3. Affine Homomorphisms. 23. Algorithms in Linear algebras. 23.1. Gauss Elimination. 23.2. The LUP Decomposition. 24. Linear Geometry. 24.1. Euclidean Vector Spaces. 24.2. Trigonometric Functions from Two-Dimensional Rotations. 24.3. Gram's Determinant and the Schwaxz Inequality. 25. Eigenvalues, the Vector Product and Quaternious. 25.1. Eigenvalues and Rotations. 25.2. The Vector Product. 25.3. Quaternions. 26. Second Advanced Topic. 26.1. Galois Fields. 26.2. The Ree- Solomon (RS) Error Correction Code. 26.3. The Rivest-Shamir-Adelman (RSA) Encryption Algorithm. A. Further Reading. B. Bibliography. Index. Volume II. III. Topology and Calculus. IV. Selected Higher Subjects.

Alqebra, Geometry and Software Systems. Edited by Michael Joswig, and Nobuki Takayama. Springer, Heidel- berg. 2003. 331. pages. $89.95. Contents. Preface. Detailed Table of Contents. Beneath-and-Beyond Revisited (Michael Joswig). Some Algorithmic Problems in Polytope Theory (Volker Kaibel, Marc E. Pfetsch). Computing Triangulations Using Oriented Matroids (Julian Pfeifle, Jorg Rambau). Discrete Geometry for Algebraic Elimination (Ioannis Z. Emiris). Sparse Resultant Per- turbations (Carlos D'Andres, Ioannis Z. Emiris). Numerical Irreducible Decomposition using PHCpack (Andrew J. Sommese, Jan Vershelde, Charles W. Wampler). Generating Kuimmer Type Formulas for Hypergeometric Functions (Nobuki Takayam). Computer Algebra System Risa/Asir (Masayuki Noro). Singular in a Framework for Polynomial Computations (Hans Schonenmann). Computing Simplical Homology Based on Efficient Smith Normal Form Algorithms (Jean-Guillaume Dumas, Frank Heckenbach, David Saunders, Volkmar Welker). The Geometry of C n is Important for the Algebra of Elementary Functions (James Davenport). A visual Introduction to Cubic Surfaces Using the Computer Software Spicy (Duco van Straten, Oliver Labs). A Client-Server System for the Visualization of Algebraic Surfaces on the Web (Richard Morris). Visualizing Maple Plots with JavaViewLib (Steven Peter Dugaro, Konrad Polthier). Automated Generation of Diagrams with Maple and Java (Dongming Wang). Interactive Mathematical Documents on the Web (Arejh M. Cohen, Hans Cuypers, Ernesto Reinaldo Bar- reio, Hans Sterk). Distributed Computing for Conglomerate Mathematical systems (Andrew Solomon). Index. Software Systems.

The Visual Neurosciences, Volumes 1 and 2. Edited by Leo M. Chalupa and John Werner. MIT Press, Cam- bridge. 2004. $195.00 1808 pages.

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VOLUME 1. CONTENTS.

I. HISTORICAL FOUNDATIONS. 1. Vision Structure and Function; the Early History (Mitchell Glickstein). 2. The Role of Single-Unit Analysis in the Past and Future of Neurobiology (Horace Barlow). II. DEVELOPMENTAL PROCESSES. 3. Molecular Regulation of Vertebrate Retinal Development (Colin F. Barnstable). 4. Nerotrophins, electrical Activity, and the Development of Visual Function (Nicoletta Berardi and Lamberto Maffei). 5. Developmental and Genetic Control of Cell Number in the Retina (Robert W. Williams and Sally A. Moody). 6. Development of the Vertebrate Retina. 7. Development of the Retinal Decnssationa (Carol Mason and Lynda Erskine). 8. The Development of Eye-Specific Segregation in the Retino-Genicul-Striate Patheway (Barbara Chapman). 9. the Role of Neural Activity in the Development of Orientation Selectivity (Chiayu Chin and Michael Weliky). 10, Mechanisms of Plasticity in the Visual Cortex (Nigel W. Daw). 11. Ontogenesis of Cortical Connectivity (Henry Kennedy and Andres Burkhalter). 12. neural Limitations on Visual Development in Primates (Lynne Kiorpes and j. Anthony Movshon). 13. Development of Spatial Selectivity and Response Timin int Humans (Anthony M. Norcia). 14. The Effects of Selected Forms of Early Visual Deprivation on Perception (Donald E. MitcheU0. 15. Toward a Future for Aging Eyes (R.A. Weale). III. RETINAL MECHANISMS AND PROCESSES. 16. Visual Transduction by Rod and Cone Photoreceptors (Marie E. Burns and Trevor D. Lamb). 17. How Retinal Circuits Optimize the Transfer of Visual Information (Peter Sterling). 18. ON and OFF Pathways in the Vertebrate Retina and Visual System (Ralph nelson and Helga Kolb). 19. Retinal synapses (martin Wilson). 20. Retinal Neirotransmitters (Robert E. Marc). 21. Excitation in the reinaL the Flow, Filtering and Molecules of Visual Signaling in the Glutamatergic Pathways from Photoreceptors to Ganglion Cells (David R, Copenhagen). 22. Peptide and Peptide Receptor Expression and Function in the Vertebrate Retina (Nicholas C. Brecha). 23. Inhibition in the Retina (Malcolm M Slaughter). 24. Anatomy, Circuitry, and Physiology of Vertebrate Horizontal Cells (Ido Perlman, Helga Kolb and Ralph Nelson). 25. Retinal Amacrine Cells (David I. Vaney). 26. Ganglion Cells in Mammalian Retinae (Paul R. Martin and Ulrike Grunert). 27. Retinal Ganglion Cell Excitability (Andrew T. Ishida) 28, Direction in retinal Ganglion Cells (Richard H. masland). 29. Spatial Regularity among Retinal Neurons (Jeremy E Cook). IV. ORGANIZATION OF VISUAL PATHWAYS. 30. The M, P, and K Pathways of the Primate Visual System (Ehud Kaplan). 31. Parallel Visual Pathways: A comparative Perspective (Vivien A. Casagrande and Xiangmin Xu). 32. Organization of Visual Areas in Macaque and Human Cerebral Cortex (David C. Van Essen). 33. Communications Between Cortical Areas of the Visual System (Jean Bullier). 34. Ventral and Dorsal Cortical rocessing Streams (Leslie G. Ungerleider and Tatiana Pasternak). V. SUBCORTICAL PROCESSING. 35. The visual Relays in the Thalamus (S. Murray Sherman and R.W. Guillery). 36. The Visual Functions of the Pulvinar (Christian Casanova). 37. Feedback Systems in visual Processing (Adam M. Sillito and Helen E. Jones). 38. Light Responsiveness and Photic Entrainment of the Mammalian Circadian Clock (Johanna H. Meijer and Joseph S. Talmhashi). 39. Learning from the Pupil: Studies of Basic Mechanisms and Clinical Applications (John L. Barbur). 40. Blindsight (Larry Weiskrantz). VI. PROCESSING IN PRIMARY VISUAL CORTEX. 41. Functional Connectivity in the Pathway from Retina to Striate Cortex (R. Clay Reid and W. Martin Usrey). 42. Cell Types and Local Circuits in Primary Visual Cortex of the Macaque Monkey (Edward M. Callaway). 43. Assembly of Receptive Fields in Primary Visual Cortex (David Ferster). 44. A Modern View of the Classical Receptive Field: Linear and Nonlinear Spatiotemporal Processing by V1 Neurons (Gregory C. DeAngelis and Akiyuki Anzai). 45. Beyond the Classical Receptive field: Contextual modulation of V1 Responses (Victor A.F. Lamme). 46. Contributions of Vertical and Horizontal Circuits to the Response Properties of Neurons in Primary Visual Cortex (Thomas R. Tucker and David Fitzpatrick). 47. Nonlinear Properties of visual Cortex Neurons: Temporal Dynamics, Stimulus Selectivity, Neural Performance (Duane G. Albrecht, Wilson S. Geisler and Alison M. Crane). 48. Binocular Interaction in the Visual Cortex (Ralph D. Freeman). 49. From Binocular Disparity to the Perception of Stereoscopic Depth (Andrew J. Parker). VII. DETECTION AND SAMPLING. 50. Formation and acquisition of the Retinal Image (David R. Williams and Heidi Hofer). 51. Thresholds and Noise ( Theodore E. Cohn). 52. Ideal Observer Analysis (Wilson S. Geisler). 53. Scotopic Vision (Walter Makous). 54. Visual Adaptation (Adam Reeves). 55. Rod-Cone Interactions in Human Vision (Steven L. Buck). VII. BRIGHTNESS AND COLOR. 56. Brightness and Lightness (Adriana Fiorentini). 57. Color Appearance (Kenneth Knoblauch and Steven K. Shevell). 58. Chromatic discrimination (Joel Pokorny and Vivianne C. Smith). 59. The Role of Color in Spatial Vision (Karen K DeValois). 60. Pattern-Selective Adaptation in Color and Form Perception (Michael A.. Webster). 61. Color Constancy (David H. Bralnard). 62. Comparative Color Vision. 63. Molecular Genetics of Human Color Vision Defects (Maureen Neitz and Jay Neitz). 64. Linking Retinal Circuits to Color Opponency (David J. Calkins). 65. Neural Coding of Color (Russell L. DeValois). 66. The Processing of Color in Extrastriate Cortex (Karl R. Gegenfurtner and Daniel C. Kiper). 67. Improbable Areas in Color Vision (Semir Zeki). IX. FORM, SHAPE, AND OBJECT RECOGNITION.

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68. Spatial Scale in Visual Processing (Robert F. Hess). 69. Spatial Channels in Vision and Spatial Pooling (Hugh R. Wilson and Frances Wilkinson). 70. Contour Integration and the Lateral Connections of V1 Neurons (David J. Field and Anthony Hayes). 71. Shape Dimensions and Object Primitives (Charles E. Connor). 72. Shape and Shading (Jan J. Koenderink and Andrea J. van Doom). 73. Visual Perception of Texture (Michael S. Landy and Norma Graham). 74. Visual Segmentation and Illusory Contours (Robert Shapley, Nava Rubin and Dario Ringach). 75. Global Yet Early Processing of Visual Surfaces (Yukiyasu Kamitani and Shinsuke Shimojo). 76. Image Parsing Mechanisms of the Visual Cortex (Riidiger yon der Heydt). 77. Inferotemporal Response Properties (Keiji Tanaka). 78. Invariant Object and Face Recognition (Edmund T. Rolls). 79. The Ventral Visual Object Pathway in Humans: Evidence from fMRI (Nancy Kanwisher). X. MOTION, DEPTH, AND SPATIAL RELATIONS. 80. Motion Cues in Insect Vision and Navigation (Mandyam Srinivason and Shaowu Zhang). 81. The Middle Temporal Area: Motion Processing and the Link to Perception (Kenneth H. Britten). 82. Merging Processing Streams: Color Cues for Motion Detection and Interpretation (Karen R. Dobkins and Thomas D. Albright). 83. Functional Mapping of Motion Regions (Guy A. Orban and Wim Vanduffel). 84. Optic Flow (William H. Warren). 85. The Cortical Analysis of Optic Flow (Charles J. Duffy) 86. The Perceptual Organization of Depth (Roland Fleming and Barton L. Anderson). 87. Stereopsis (Clifton M. Schor). 88. Binocular Rivalry (Randolph Blake). 89. Sensorimotor Transformation in the Posterior Parietal Cortex (Hansj6rg Scherberger and Richard A. Anderson). XI. EYE MOVEMENTS. 90. Gaze Control Under Natural Conditions (Robert M. Steinman). 91. Eye Movements in Daily Life (Michael F. Land). 92. Selection of Targets for Saccadic Eye Movements (Jeffrey D. SchMl). 93. Visual Perception during Saccades (David C. Burr and M. Concetta Morrone). 94. Smooth Pursuit Eye Movements: Recent Advances (Stephen J. Heinen and Edward L. Keller). 95. Neural Control of Vergence Eye Movements (Lawrence E. Mays). 96. The Primate Frontal Eye Field (Charles J. Bruce, Harriet R. Friedman, Michael S. Krans and Gregory B. Stanton). 97. Changing Views of the Role of Superior Colliculus in the Control of Gaze (Neeraj J. Gandhi and David L. Sparks). 98. The Dialogue between Cerebral Cortex and Superior Colliculus: Implications for Saccadic Target Selection and Corollary Discharge (Marc A. Sommer and Robert H. Wurtz). 99. Cerebellar Control of Eye Movements (David S. Zee and Mark F. Walker). XII. ATTENTION AND COGNITION. 100. Visual Perception and Cognition in Honeybees (Shaowu Zhang and Mandyam Srinivasan). 101. A Neural Basis for Human Visual Attention (Sabine Kastner). 102. Neural and Behavioral Measures of change Detection (Daniel J. Simons and Michaeil Silverman). 103. The Role of Attention in Visual Cerebral Cortex (John H.R. Maunsell). 104. Volition and the Perefrontal Cortex (Earl K. Miller and Jonathan D. Wallis). XIII. THEROETICAL AND COMPUTATIONAL PERSPECTIVES. 105. The Evolution of the Visual System in Primates (Jon H. Kaas). 106. Gestalt Factors in the Visual Neu- rosciences (Lothar Spillmann and Walter H. Ehrenstein). 107. Neural Mechanisms of Natural Scene Perception (Jack L. Gallant). 108. Principles of Image Representation in Visual Cortex (Bruno A. Olshansen). 109. Local Analysis of Visual Motion (Eero P. Simonocelli). 110. Visual Boundaries and Surfaces (Stephen Grossberg). 111. How the Visual Cortex Recognizes Objects: The Tale of the Standard Model (Maximilian Riesenhuber and Tomaso Poggio). 112. Plasticity of Orientation Processing in Adult Visual Cortex (Valentin Dragoi and Mriganka Sur). 113. Synchrony, Oscillations, and Relational Codes (Wolf Singer). 114. The neuronal Basis of Visual Consciousness (Christof Koch and Francis Crick). List of Contributors. Index. VOLUME 2, Contents. Preface xiii. I. HISTORICAL FOUNDATIONS. 1. Vision Structure and function: The Early History (Mitchell Glickstein). 2. The Role of single-Unit Analysis in the Past and Future of Neurobiology ( Horace Barlow) II. DEVELOPMENTAL PORCESSES. 3. Molecular regulation of vertebrate Retinal Development of Visual Function (Colin J. Barnstable). 4. Neu- rotrophins, Electrtical Acitvity, and the Development of Visual Function (Nicoletta Berardi and Lamberto Maffei). 5. Developmental and Genetic control of Cell Number in the Retina (Robert W. Williams and Sally A. Moody). 6. Development of the Vertebrate Retina (Rachel O.L. Wong and Leanne Godinho). 7. The Development of Retinal Decussations (Carol Mason and Lynda Erskine). 8, The Development of Eye-Specific Segregation in the Retino-Geniculo-Striate Pathway (Barbara Chapman). 9. The Role of Neural Activity in the Development of Orientation Selectivity (Chiayu Chiu and Michael Weliky). 10. Mechanisms of Plasticity in the Visual Cortex (Nigel W. Daw). 11. Ontogenesis of Cortical Connectivity (Henry Kennedy and Andreas Burkhalter). 12. Neural Limitations on Visual Development Ion Primates (Lynne Kiorpes and F. Anthony Movshon). 13. Development of Spatial Selectivity and Response Timing in Humans (Anthony M. Norcia). 14. The Effects of Selected Forms of Early Visual Deprivation on Perception (Donald E. Mitchell). 15. Toward a Future for Aging Eyes (R.A. Weale). III. RETINAL MECHANISMS AND PROCESSES. 16. Visual Transduction by Rod and Cone Photoreceptors (Marie E. Burns and Trevor D. Lamb). 17. How Retian Circuits Optimize the Transfer of Visual Infornmtion (Peter Sterling). 18. ON and OFF Pathways in the Vertebrate Retina and Visual System (Ralph Nelson and Helga Kolb). 19. Retinal Synapses (Martin Wilson). 20.

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Retinal Neurotransmitters (Robert E. Marc). 21. Excitation in the Retina: The Flow, Filtering, and Molecules of Visual Signaling in the Glutamatergic Pathways from Photoreceptors to Ganglion Cells (David R. Copenhagen). 22. Peptide and Peptide Receptor Expression and Functions in the Vertebrate Retina (Nicholas C. Brecha). 23. Inhibition in the Retina (Malcolm M. Slaughter). 24. Anatomy, Circuitry, and Physiology of Vertebrate Horizontal Cells (Ido Perlman, Helga Kolb and Ralph Nelson). 25. Retinal Marine Cells (David I. Vaney). 26. Ganglion Cells in Mammalian Retinae (Paul R. Martin and Ulricke Grunert). 27. Retinal Ganglion Cell Excitability (Andrew T. Ishida). 28. Direction and Selectivity in Retinal Ganglion Cells (Richard H. Masland). 29. Spatial Regularity among Retinal Neurons (Jeremy E. Cook). IV. ORGANIZATIONS OF VISUAL PATHWAYS. 30. the M, P, and K Pathways of the Primate Visual Systems (Ehud Kaplan). 31. Parallel Visual Pathways: A Comparative Perspective (Vivien A. Casagrande and Xiangmin Xu). 32. Organization of Visual Areas in Macaque and Uman Cerebral Cortex (David C. Van Essen). 33. Communications between Cortical Areas of the Visual System (Jena Bullier). 34. Ventral and Dorsal Cortical Processing Streams (Leslie G. Ungerleider and Tatiana Pasternak). V. SUBCORICAL PROCESSING. 35. The Visual Relays in the Thalamus (S. Murray Sherman and R.W. Guillery). 36. The visual Functions of the Pulvinar (Christan Casanova). 37. Feedback Systems in Visual Processing (Adam M. Sillito and Helen E. Jones). 38. Light Responsiveness and Photic Entrainment of the Mammalian Circadian clock (Johanna H. Meijer and Joseph S. Takahashi). 39. Learning from the Pupil: Studies of Basick Mechanisms and Clinical Applications (John L. Barbur). 40. Blind sight (Larry Weiskrantz). VI. PROCESSING IN PRIMARY VISUAL CORTEX. 41. Functional Connectivity in the Pathway fro Retina to Striate Cortex (R. Clay Reid and W. Martin Usrey). 42. Cell Types and Local Circuits in Primary Visual Cortex of the Macaque Monkey (Edward M. Calloway). 43. Assembly of Receptive Fields in Primary Visual Cortex (David Ferster). 44. A Modern View of the Classical Receptive Field: Linear and Nonlinear spatiotemporal Processin by VI Neurons (Gregory C. DeAngelis and Akiyuki Anzai). 45. Beyond the Classical Receptive Field: Contextual Modulation of VI Responses (Victor A.F. Lamme). 46. Contributions of Vertical and Horizontal Circuits to the Response Properties of Neurons in Primary Visual Cortex (Thomsa R. Tucker and David Fitzpatrick). 47. Nonlinear Properties of Visual Cortex Neurons: Temporal Dynamics, Stimulus Selectivity, Neural Performance (Duane G. Albrecht, Wilson S. Geisler and Alison M. Crane). 48. Binocular Interaction in the Visual Cortex (Ralph D. Freeman). 49. From Binocular Disparity tot he Perception of Stereoscopic Depth (Andrew F. Parker). VII. DETECTION AND SAMPLING. 50. Formation and Acqusition of the Retinal Image (David R. Williams and Heidi Hofer). 51. Threshholds and noise (Theodore E. Cohn). 52. Ideal Observer Analysis (Wilson S. Geisler). 53. Scotopic Vision (Walter Makous). 54. Visual Adaptation (Adam Reeves). 55. Rod-Cone Interactions in Human Vision (Steven L. Buck). VII. BRIGHTNESS AND COLOR. 56. Brightness and Lightness (Adirana Fiorentini). 57. Color Appearance (Kenneth Knoblauch and Steven K. Shevell). 58. Chronomatic Discrimination (Joel Pokorny and Vivianne C. Smith). 59. The Role of Color in Spatial Vision (Karen K. DeValois). 60. Pattern-Selective Adapationa in Color and Form Perception (Michael A. Webster). 61. Color Constancy (David H. Brainard). 62. Conmparative Color Visions (Gerald H. Jaeobs). 63. Molecular Genetics of Human Color Vision and Color Vision Defects (Maureen Neitz and Jay Neitz). 64. Linking Retinal Circuits to Color Opponency (David F. Calkins). 65. Neural Coding of Color ( Russell L. De Valois). 66. The Processing of Color in Extrasitriate Cortex (Karl R. Gegenfurtner and Daniel C. Kiper). 67. Improbable Areas in Color Vision (Semir Zeki). IX. FORM, SHAPR, AND OBJECT RECOGNITION. 68. Spatial Scale in Visual Processing (Robert F. Hess). 69. Spatial channels in Vision and Spatial Pooling (Hugh R. Wilson and Fraces Wilkinson). 70. Contour Integration and the Lateral Connections of VI Neurons (David J. Field and Anthony Hayes). 71. Shape Dimensions and Object Primitives (Charles E. Connor). 72. Shape and Shading (Jan J. Koenderink and Andrea J. vanDoorn). 73. Visual Perception of Texture (Michael S. Landy and Norma Graham). 74. Visual Segmentation and Illusory Contours (Rovert Shapley, Nava Rubin and Dario Ringach). 75. Global Yet Early Processing of Visual Srfaces (Yukiyasu Kamitani and Shinsuke Shimojo). 76. Image Parsing Mechanisms of the Visual Cortex (Rudiger vonderHeydt). 77. Inferotemporal Response Properties (Keiji Tanaka). 78. Invariant Object and Face Recognition (Edmund T. Rolls). 79. The Ventral Visual Object Pathway in Humans: Evidence from fMRI (Nancy Kanwisher). X. MOTION, DEPTH, AND SPATIAL RELATIONS. 80. Motion Cues in Insect Vision and Navigation (Mandyam Srinivasan and Shaowu Zhang). 81. The Middle Temporal Area: Motion Processing and the Link to Perception (Kenneth H. Britten). 82. Merging Processing Streams: Color Cues for Motion Detection and Interpretation (Karen R. Dobkins and Thomas D. Albright). 83. Funtional Mapping of Motion Regions (Guy A. Orban and Wim Vanduffel). 84. Optic Flow (William H. Warren). 85. The Cortical Analysis of Optic Flow (Charles J. Duffy). 86. The Perceptual Organization of Depth (Roland Fleming and Barton L. Anderson). 87. Stereopsis (Clifton M. Schor). 88. Binocular Rivalry (Randolph Blake). 89. Sensorimotor Transformation in the Posterior Paretal Cortex (Hansjorg Scherberger and Richard A. Anderson). XI. EYE MOVEMENTS. 90. Gaze Control under Natural Conditions (Robert M. Steinman). 91. Eye Movements in Daily Life (Michael F. Land). 92. Selection of Targets for Saccadic Eye Movements (Jeffrey D. Schall). 93. Visual Perception during

BOOK REPORTS 987

saccades (David C. Burr and M. Concetta Morrone). 94. Smooth Pursuit Eye Movements: Recent Advances (Stephen J. Heinen and Edward L. Keller). 95. Neural Control of Vergence Eye Movements (Lawrence E. Mays). 96. The Primate Frontal Eye Field (Charles J. Bruce, Harriet R. Friedman, Michael S. Kraus and Gregory B. Stanton). 97. Changing Views of the Role of Superior Colliculns in the Control of Gaze (Neeraj J. Gandhi and David L. Sparks). 98. The dialogue between Cerebral Cortex and Superiro Colliculus: Implications for Saccadic Target Selection and Corollary Discharge (Marc A. Sommer and Robert H. Wurtz). 99. Cerebeller Control of Eye Movements (David S. Zee and Mark F. Walker). XII. ATTENTION AND COGNITION. 100. Visual Perception and Cognition in Honeybees (Shaowu Zhang and Mandyam Srinivasan). 101. A Neural Basis for Human Visual Attention (Sabine Kastner). 102. Neural and Behavioral Measures of Change Detection (Daniel J. Simons and Michael Silverman). 103. The Role of Attention in Visual Cerebral Cortex (John H.R. Maunsell). 104. Volition and the Prefrontal Cortex (Earl K. Miller and Jonathan D. Wallis). XIII. THEORETICAL AND COMPUTATIONAL PERSPECTIVES. 105. The evolution of the Visual System in Primates (Jon H. Kaas). 106 Gestalt Factors in the Visual Neurosciences (Lothar Spillmann and Walter H. Ehrenstein). 107. Neural Mechanisms of Natural Scene Perception (Jack L. Gallant). 108. Priciples of Image Representation in Visual Cortex (Bruno A. Oishausen). 109. Local Analysis of Visual Motion (Eero P. Simonocelli). 110. Visual Boundaries and Surfaces (Stephen Grossberg). I l l . How the Viosual Cortex Recognizes Objects: The Tale of the Standard Model (Maximilian Riesenhuber and Tomaso Poggio). 112. Plasticity of Orientation Processing Adult Visual Cortex (Valentin Dragooi and Mriganka Sur). 113. Sychrony, Oscillations, and Relational Codes (Wolf Singer). 114. The Neuronal Basis of Visual Consciousness (Christof Koch and Francis Crick). List of Contributors. Index.

Block Error-Corrsctinq Codes. Edited By Sebastia Xambo-Descamps. Springer. Heidelberg. 2003. 266 pages. $44.95. Contents. Preface. Introduction. 1. Block Error-correcting Codes. 1.1. Basic concepts. 1.2. Linear codes. 1.3. Hadamard codes. 1.4. Parameter bounds. 2. Finite Fields. 2.1. Zn and Fp. 2.2. Construction of finite fields. 2.3. structure of the multiplicative group of a finite field. 2.4. Minimum polynomial. 3. Cyclic Codes. 3.1. Generalities. 3.2. Effective factorizatiou of X n - 1. 3.3. Roots of a cyclic code. 3.4. The Meggit decoder. 4. Alternant Codes. 4.1. Definitions and examples. 4.2. error location, error evaluation and the key equation. 4.3. The Berlekamp-Massey-Sugiyama algorithm. 4.4. The Peterson-Gorenstein-Zierler algorithm. Appendix: The WIRIS/cc system. Bibliography. Index of Symbols. Alphabetic Index, Glossary and Notes.

Theoretical Computer Science. Edited by Juraj Hromkovic. Springer. Heidelberg. 2004. 313 pages. $59.95. Contents. 1. Introduction. 1.1. What is Computer Science? 1.2. A Fascinating Theory. 1.3. To the student. 1.4. Structure of the Book. 2. Alphabets, Words, Languages, and Algorithmic Problems. 2.1. Objectives. 2.2. Alphabets, Words, and Languages. 2.3. Algorithmic problems. 2.4. Kolmogorov Complexity. 2.5. Summary and outlook. 3. Finite Automata. 3.1. Objectives. 3.2. Different Representations of Finite Automata. 3.3. Simulations. 3.4. Proofs of Nonexistence. 3.5. Nondeterminism. 3.6. Summary. 4. Truing Machines. 4.1. Objectives. 4.2. The Turing Machine Model. 4.3. Multitape Turing Machines and the Church-Turing Thesis. 4.4. Nondeterministic Turing Machines. 4.5. Coding of Turing Machines. 4.6. Summary. 5. Computability. 5.1. Objectives. 5.2. The Diagonalization Method. 5.3. The Reduction Method. 5.4. Rice's Theorem. 5.5. Post Correspondence problem. 5.6. the Kolmogorov-Complexity Method. 5.7. Summary. 6. Complexity Theory. 6.1. Objectives. 6.2. Complexity Measures. 6.3. Complexity Classes and the Class P. 6.4. Noudeterminisitc Complexity measures. 6.5. The Class NP and Proof Verification. 6.6. NP-Completeness. 6.7. Summary. 7. Algorithms for Hard Problems. 7.1. Objectives. 7.2. Pseudopolynomial Algorithms. 7.3. Approximation Algorithms. 7.4. Local Search. 7.5. Simulated Annealing. 7.6. Summary. 8. Randomization. 8.1. Objectives. 8.2. Elementary Probability Theory. 8.3. A Randomized Communication Protocol. 8.4. Abundance of Witnesses and Randomized Primality testing. 8.5. Fingerprinting and Equivalence of Two Polynomials. 8.6. Summary. 9. Communication and Cryptography. 9.1. Objectives. 9.2. Classical Cryptosystems. 9.3. Public-Key Cryptosys- terns and RSA. 9.4. Digital Signatures. 9.5. Interactive Proof Systems and Zero-Knowledge Proofs. 9.6. Design of an Interconnectiou Network. 9.7. Summary.

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References. Index.

Radon Trans[orms and the Riqidity o[ the Grassmanians. Edited by Jacques Gasqui and Hubert Goldschmidt. Princeton University Press, Princeton, NJ. 2004. 363 pages. $45.00. Contents. Introduction. Chapter I. Symmetric Spaces and Einstein Manifolds. 1. Riemannian manifolds. 2. Einstein manifolds. 3. Symmetric spaces. 4. Complex manifolds. Chapter II. Radon transforms on Symmetric Spaces. 1. Outline. 2. Homogeneous vector bundles and harmonic analysis. 3. The Guillemin and zero-energy conditions. 4. Radon transforms. 5. Radon transforms and harmonic analysis. 6. Lie algebras. 7. Irreducible symmetric spaces. 8. Criteria for the rigidity of an irreducible symmetric space. Chapter III. Symmetric Spaces of rank One. 1. Flat tori. 2. The projective spaces. 3. The real projective space. 4. The complex projective space. 5. The rigidity of the complex projective space. 6. the other projective spaces. Chapter IV. The Real Grassmanians. 1. The real Grassmanians. 2. The Guillemin condition on the real Grassmanians. Chapter V. The Complex Quadric. 1. Outline. 2. The complex quadric viewed as a symmetric space. 3. The complex quadric viewed as a complex hypersurface. 4. Local Kahler geometry of the complex quadric. 5. The complex quadric and the real Grassmanians. 6. Totally geodesic surfaces and the infinitesimal orbit of the curvature. 7. Multiplicities. 8. Vanishing results for symmetric forms. 9. The complex quadric of dimension teo. Chapter IV. The rigidity of the Complex Quadric. 1. Outline. 2. Total geodesic flat tori of the complex quadrice. 3. Symmetric forms on the complex quadrice. 4. Computing integrals of symmetric forms. 5. Computing integrals of odd symmetric forms. 6. Bounds for the dimensions of spaces opf symmetric forms. 7. the complex quadric of dimension three. 8. The rigidity of the complex quadric. 9. Other proofs of the infinitesimal rigidity of the quadric. 10. The complex quadric of dimension four. 11: Forms of degree one. Chapter VII. The Rigidity of the Real Grassmanians. 1. The rigidity of the real Grassmanians. 2. The Real Grassmanians G'Rn, n. Chapter VII. The Complex Grassmanians. 1. Outline. 2. The complex Grassmanians. 3. Highest weights of irreducible modules associated with the complex Grassmanians. 4. Functions and form on the complex Grassma- nians. 5. The complex Grassmanians of rank two. 6. The Guillemin condition on the complex Grassmanians. 7. Integrals of forms on the complex Grassmanians. 8. Relations among forms on the complex Grassmanians. 9. The complex Grassmanians (~,2. Chapter IX. The Rigidity of the Complex Graesmanians. 1. The rigidity of the complex Grassmanians. 2. On the rigidity of the complex Grassmanians GCn, n. 3. The rigidity of the quaternionic Grassmanians. Chapter X. Products and Symmetric Spaces. 1. Guillemin rigidity and products of symmetric spaces. 2. Con- formally flat symmetric spaces. 3. Infinitesimal rigidity of products of symmetric spaces. 4. The infinitesimal rigidity of G~,2- References. Index.

Desiqn Research. Methods and Perspectives. Edited by Brenda Laurel. The MIT Press. Cambridge, MA. 2003. 334 pages. $39.95. Contents. Preface. The Design Cluster (Peter Lunenfeld). Introduction Muscular Design (Brenda Laurel). Acknowledg- ments (Brenda Laurel). People. Section Introduction (The Changing Role of Research (Christopher Ireleand). Qualitative Methods: From Boring to Brilliant (Christopher Ireland). Ethnography and Critical Design Practice (Tim Plowman). The Paradox of Design Research (Bonnie Mcdaniel Johnson). Designing for the New Old (Eric Dishman). Demo Design Improvisation (Brenad Laurel). Hispanic Culture in Design Research (Carlos Santos). Overview of Quantitative Methods in Design Research (Stacey Purpura). User Requirements (Abbe Don, and Jeff Petrick). Section Introduction Design (As) Research (Anne Brudick). Specualtion, Serendipity and Studio Anybody (Lisa Crocott). Toward a Definition of the Decorational (Denise Gonzales Crisp). Demo design Writ- ing (Anne Burdick). Sensory Anomalies (Michael Naimark). Spontaneous cinema as Design Practice (Rachel Strickland). Fame Forms for New Outcomes (Emma Westcott). Strategy, Tactics and Heuristics for Research (Rob Tow). Section Introduction Test Pilots (Brenda Laurel). Bringing Clarity to the "Fuzzy Front End" (Dar- rel Rhea). Research Methods for Designing Effective Experiences (Nathan Sherdroff). Enabling Design (Scan Dinahue). Non-Assumptive l:tesearch (Dorothy Deasy). Play as Research (Eric Zimmerman). Demo Creating a Culture of Design Research (Eric Zimmerman). Interdisciplinary Design Research (Patrik Svensson). Conceptual Designs (BJ Fogg). Moving Your Idea Through Your Organization (Christoph Loch). Demo Vibe-Hunting (Somi Kim). Living Proof (Tracy Moon). Research to Fuel the Creative Process (David Canaan). Section Introduction Reports from the Field (Brenda Laurel). "You Can' t Bring that game to School!" (Henry Jenkins, Kurt Squire & Philip Tan). Sim Smarts (Will Wright and Brenda Laurel). Social Impact by Design (Darion Rapoza). Research- ing America's Army (Margaret Davis et 02.). A Virtual Walk on the Moon (Bruce Darner). Demo Mobium (Jin Hyun Park). Research and the Movies (Buffy Shutt). Research and Design for Kids (Jan Craige Singer). Real

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Brand Alignment (Davis Masten). Conclusion Beauty, Brains, and Bravery's (Brenda Laurel). References and Acknowledgments. Index. Biographies.

Why Stock Markets Crash. Edited by Didier Sornette. Princeton University Press. Princeton, NJ. 2004. $19,95. 456 pages. Contents. Preface. Chapter 1. FINANCIAL CRAHSES, WHAT, HOW, WHY, AND WHEN? What are Crashes and Why Do We Care? The Crash of October 1987. Historical Crashed. The Tulip Mania. The South Sea Bubble. The Great crash of October 1929. Extreme Events in Complex Systems. Is Prediction Possible? A Working Hypothesis. Chapter 2. FUNDAMENTALS OF FINANCIAL MARKETS. The Basics. Price Trajectories. Return trajectories. Return Distribution and Return Correlation. The Efficient Market Hypothesis and Random Walk. The Random Walk. A Parable: How Information Is Incorporated in Prices, Thus Destroying Potential "Free Lunches". Prices Are Unpredictable, or Are They? Risk-Return Trade-Off. What Are "Abnormal" Returns? Chapter 3. FINANCIAL CRASHED ARE "OUTLIERS'. Drawdowns (Runs). Definition of Drawdowns. Draw- downs and the Detection of "Outliers". Expected Distribution of "Normal Drawdowns. Drawdown Distribution of Stock Market Indices. The Bow Jones Industrial Average. The Nasdaq Composite Index. Further Tests. The Presence of Outliers Is a General Phenomenon. Main Stock Market Indices, Currencies, and Gold. Largest U.S. Companies. Synthesis. Symmetry-Breaking on Crash and Rally Days. Implications for Safety Regulations of Stock Markets. Chapter 4. POSITIVE FEEDBACKS. Feedbacks and Self-Organization in Economics. Hedging Derivatives, Insurance Portfolios, and Rational Panics. "Herd" Behavior and "Crowd" Effect. Behavioral Economics. Herding. Empirical Evidence of Financial Analysts' Herding. Empirical Evidence of Financial Analysts' Herding. Forces of Imitation. It Is Optimal to Imitate When Lacking Information. Mimetic Contagion and the Urn Models. Imitation from Evolutionary Psychology. Rumors. The Survival of the Fittest Idea Gambling Spirits. "Anti-Imitation" and Self-Organization. Why It May Pay to Be in the Minority. ELFarol's Bar Problem. Minority Games. Imitation versUs Contrarian Behavior. Cooperative Behaviors Resulting from Imitation. The Ising Model of Cooperative Behavior. Complex Evolutionary Adaptive Systems of Boundedly Rational Agents. Chapter 5. MODELLING FINANCIAL BUBBLES AND MARKET CRASHED. What is a Model? Strategy for Model Construction in Finance. Basic Principles. The Principles of Absence of Arbitrage Opportunity. Existence of Rational Agents. "Rational Bubbles" and Goldstone Modes of the Price "Parity Symmetry" Breaking. Price Parity Symmetry. Speculation as spontaneous Symmetry Breaking. Basic Ingredients. Of the Two Models. The Risk-Driven Model. Summary of the Main Properties of the Model. The Crash Hazard Rate Drives the Market Place. Imitation and Herding Drive the Crash Hazard Rate. Risk-Driven versus Price-Driven Models. Chapter 6. HIERARCHIES, COMPLES FRACTAL DIMENSIONS AND LOG-PERIODICITY. Critical Phenom- ena by Imitation on Hierarchical Networks. The underlying Hierarchical Structure of Social Networks. Critical Behavior in Hierarchical Networks. A Hierarchical Model of Financial Bubbles. Origin of Log-Periodicity in Hierarchical Systems. Discrete Scale Invariance. Fractal Dimensions. Organization Scale by Scale: The Renor- realization Group. Complex Fractal Dimensions and Log-Periodicity. Importance and Usefulness of Discrete Scale Invariance. Existence of Relevant Length Scales. Prediction. Scenarios Leading to Discrete Scale Invariance and Log Periodicity. Newcomb-Benford Law of First Digits and the Arithmetic System. The Log-Periodic Law of the Evolution of Life. Nonlinear Trend-Following versus Nonlinear Fundamental Analysis Dynamics. Trend Following: Positive Nonlinear Feedback and Finite Time Singularity. Reversal to the Fundamental Value: Negative Nonlinear Feedback. Some Characteristics. Of the Price Dynamics of the Nonlinear Dynamical Model. Chapter 7. AUTOPSY OF MAJOR CRASHES: UNIVERSAL EXPONENTS AND LOG-PERIODICITY. The Crash of October 1987. Precursory Pattern. Aftershock Patterns. The Crash of October 1929. The Three Hong Kong Crashes of 1987, 1994, and 1997. The Hong Kong Crashes. The Crash of October 1997 and Its Resonance on the US Market. Currency Crashes. The Crash of August 1998. Nonparametric Test of Log-Periodicity. The Slow Crash of 1962 Ending the "Tronics" Boom. The Nasdaq Crash of April 200. "Antibubbles". The Bearish Regime on the Nikkei Starting from January 1, 1990. The Gold Deflation Price Starting in Mid-1980. Synthesis: "Emergent" Behavior of the Stock Market. Chapter 8. BUBBLES, CRISES, AND CRASHES IN EMERGENT MARKETS. Speculative Bubbles in Emerging Markets. Methodology. Latin-American Markets. Asian Markets. The Russian Stock Market. Correlations across Markets: Economic Contagion and Synchronization of Bubble Collapse. Implications for Mitigations of Crises. Chapter 9. PREDICTION OF BUBBLES, CRASHES, AND ANTIBUBBLES. The Nature of Predictions. How to Develop and Interpret Statistical Tests of Log-periodicity. First Guidelines for Prediction. What is the Predictive Power of Equation (15)? How Long Prior to a Crash Can One Identify the Log-Periodic Signatures. A hierarchy of Prediction Schemes. The Simple power Law. The "linear" Long-Periodic Formula. The "Nonlinear" Log-Periodic Formula. The Shank's Transformation on a Hierarchy of Characteristic Times. Application to the October 1929 Crash. Application to the October Crash of 1987. Forward Prediction. Successful Prediction of the Nikkei 199 Antibubble. Successful Prediction of the Nasdaq Crash of April 2000. The U.S. market, December 1997 False Alarm. The U.S. Market, October 1999 False Alarm. Present Status of the Forward Predictions. The finite Probability That No Crash Will Occur during a Bubble. Estimation of the Statistical Significance of the Forward Predictions. Statistical Significance of a Single Successful Prediction via Bayes's Theorem. The Error Diagram and the Decision Process. Practical Implications on a Different Trading Strategies.

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Chapter 10. 2050"THE END OF THE GROWTH ERA7 Stock Markets, Economics, and Population. The Pessimistic Viewpoint of "Natural" Scientists. The Optimistic Viewpoint of "Social Scientists. Analysis of the Faster-Than-Exponentiai Growth of Population, GDP, and Financial Indices. Refinement of the Analysis. Com- plex Power Law Singularities. Prediction for the Coming Decade. The Aging "Baby Boomers". Related Works and Evidence. Scenarios for the "Singularity". Collapse Transition to Sustainability. Resuming Accelerating Growth by Overpassing Fundamental Barriers. The Increasing Propensity to Emulate the stock Market Approach. References. Index.

Games in a World of Infrastructures. Edited by Igor Mayer, and Wijnand Veeneman. The University of Chicago Press. 2004. $32.00. 268 pages.

Contents. Foreword (Igor Mayer-Wijnand Veeman).

Introduction (Igor Mayer-Wijnand). 1. Complex Decision-Making in a World of Infrastructures (Wijnand Veeman, Igor Mayer). 2. Gaming-Simulation For Research, Learning and Intervention (Igor Mayer, Wijnand Veeman). 3. The Urban Network Game: Innova- tions in Development Planning (Linda Carton, Igor Mayer, Martin de Jong, Martijn Leijten, Richard Scalzo, Ed Dammers, Femke Verwest). 4. The Incodelta Game: Alternative Decision Making Model For Transport Corridors (Marin de Jong, Igor Mayer). 5. The W4S Game: Exploring the Future Consequences of Water Management (Linda Carton, Sonja Karstens, et al.). 6. Containers Drift: Visualization - Simulation of an Inland Container Terminal Design (Igor Mater, Wieke Bocksteal, Edwin Valetin). 7 The Dubes Game: Supporting Sustainable Urban Renewal Projects (Ellen vanBueren, Pieter Bots, Robin Seijdel, Igor Mayer). 8. Ventum: Responsive Simulation for the Design and Management of an Offshore Wind Farm (Hanneke Mastik, Richard Scalzo). 9. The Tender Game: evaluating Innovations Into Public Transport Tendering Procedures (Weijnand Veeman). 10. Watercity: A Emtaphore Game for Managing Fiber to the Homer in ICT-Broadband (Nieo Baken, Cees Brouwer). 11. Metagames: Exploring Participatory Stakeholder Analysis for Water Management in Egypt (Leon Hermans, Pieter Bots). 12 Infrastratego: Evaluating Strategic Behavior in a Liberalized Electricity Industry (Martijn Kuit, Igor Mayer). Epilogue (Igor Mayer, Wijnand Veeman). Literature. About the Authors.

An Invi tat ion Co 3-D Vision. Edited By Yi Ma, Stefano Soatto , Jana Kosecka, S. Shanka Sastry. Springer, Heidelberg. $69.95. 2004. 526 pages. Contents. Preface. Acknowledgments. 1. Introduction. 1.1. Visual perception form 2-D images to 3- D models. 1.2. A mathematical approach. 1.3. A historical perspective. I. Introductory Material. 2. Representation of Three-Dimensional Moving Scene. 2.1. Three-Dimensional Eu- clidean Space. 2.2. Rigid-body motion. 2.3. Rotational motion and its representations. 2.3.1. Orthogonai matrix representation of rotations. 2.3.2. Canonical exponential coordinates for rotations. 2.4. Rigid-body motion and its representations. 2.4.1. Homogeneous representation. 2.4.2. Canonical exponential coordinates for rigid-body motions. 2.5. Coordinate and velocity transformations. 2.6. Summary. 2.7. Exercises. 2.A. Quaternions and Euler angles for rotations. 3. Image Formation. 3.1. Representation of images. 3.2 Lenses, light, and basic photometry. 3.2.1. Imaging through lenses. 3.2.2. Imaging through a pinhole. 3.3. A geometric model of image formation. 3.3.1 An ideal perspective camera. 3.3.2. Camera with intrinsic parameters. 3.3.3. Radial distortion. 3.3.4. Image, preimage, and coimage of points and lines. 3.4. Summary. 3.5. Exercises. 3.A. Basic Photometry with light sources and surfaces. 3.B. Image formation in the language of projective geometry. 4. Image Primitives and Correspondence. 4.1. Correspondence of geometric features. 4.1.1. From photometric features to geomet- ric primitives. 4.1.2. Local vs. global features to geometric primitives. 4.2. Local deformation models. 4.2.1. Transformations of the image domain. 4.2.2. Transformation of the intensity value. 4.3. Matching point features. 4.3,1. Small baseline: feature tracking and optical flow. 4.3.2. Large baseline: affine model and normalized cross- correlation. 4.3.3. Point feature selection. 4.4. tracking line features. 4.4.1. Edge features and edge detection. 4.4.2. Composition of edge elements: line fitting. 4.4.3. Tracking and matching line segments. 4.5. Summary. 4.6. Exercises. 4.A. Computing image gradients. II. Geometry of Two Views. 5. Reconstruction from Two Calibrated views. 5.1. Epipolar geometry. 5.1.1. The epipolar constraint and the essential matrix. 5.1.2. Elementary properties of the essential matrix. 5.2. Basic reconstruction algorithms. 5.2.1. The eight-point linear algorithm. 5.2.2. Euclidean constraints and structure reconstruction. 5.2.3. Optimal pose and structure. 5.3. Planar scenes and homography. 5.3.1. Planar homography. 5.3.2. Estimating the planar homography matrix. 5.3.3. decomposing the planar homography matrix. 5.3.4. Relationships between the homography and the essential matrix. 5.4. Continuous motion case. 5.4.1. Continuous epipolar constraint and the continuous essential matrix. 5.4.2. Properties of the continuous essential matrix. 5.4.3. The eight-point linear algorithm. 5.4.4. Euclidean constraints and structure reconstruction. 5.4.5. Continuous. homography for a planar scene. 5.4.6. Estimating the continuous homography matrix. 5.4.7. Decomposing the continuous homography matrix. 5.5. Summary. 5.6. Exercises. 5.A. Optimization subject to the epipolar contraint. 6. Reconstruction from Two Unclaibrate Views. 6.1. Uncalibrated camera or distorted space? 6.2. Uncalibrated epipolar geometry. 6.2.1. The fundamental matrix. 6.2.2. Properties of the fundamental matrix.

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6.3. Ambiguities and constraints in image formation. 6.3.1. Structure f the intrinsic parameter matrix. 6.3.2. Structure of the extrinsic parameters. 6.3.3. Structure of the projection matrix. 6.4. Stratified reconstruction. 6.4.1. Geometric stratification. 6.4.2. projective reconstruction. 6.4.3. Afilne reconstruction. 6.4.4. Euclidean reconstruction. 6.4.5. Direct stratification from multiple views (preview). 6.5. Calibration with scene knowledge. 6.5.1. Partial scene knowledge. 6.5.2. Calibration with a rig. 6.5.3. Calibration with a planar pattern. 6.6. Dinner with Kruppa. 6.7. Summary. 6.8. Exercises. 6.A. From images to fundamental matrices. 6.B, Properties of Kruppa's equations. 6.B.1. Linearly independent Kruppa's equations under special motions. 6.B.2. Cheirality constraints. 7. Estimation of Multiple Motions from Two Views. 7.1. Multibody epipolar constraint and the fundamental matrix. 7.2. A rank condition for the number of motions. 7.3. Geometric properties of the multibody fundamental matrix. 7.4. Multibody motion estimation and segmentation. 7.4.1. Estimation of epipolar lines and epipoles. 7.4.2. Recovery of individual fundamental matrices. 7.4.3. 3-D motion segmentation. 7.5. Multibody structure from motion. 7.6. Summary. 7.7. Exercises. 7.A. Homogeneous polynomial Factorization. III. Geometry of Mulitple Views. 8. Mulitple-View geometry of Points and Lines. 8.1. Basic notation for the (pre)image and Coimage of points and lines. 8.2. Preliminary rank conditions of multiple images. 8.2.1. Point features. 8.2.2. Line Features. 8.3. Geometry of pith features. 8.3.1. The multiple-view matrix of a point and its rank. 8.3.2. Geometric interpretation of the rank condition. 8.3.3 Multiple-view factorization of point features. 8.4. Geometry of line features. 8.4.1. The multiple-view matrix of a line and its rank. 8.4.2. Geometric interpretation of the rank condition. 8.4.3. Trilinear relationship among points and lines. 8.5. Uncalibrated factorization and stratification. 8.5.1. Equivalent multiple-view matrices. 8.5.2. Rank-based uncalibrated factorization. 8.5.3. Direct stratification by the absolute quadric constraint. 8.6. Summary. 8.7. Exercises. 8.A. Proof for the properties of bilinear and trilinear constraints. 9. Extensions to general Incidence Relations. 9.1. Incidence relations among points, lines, and planes. 9.1.1. Incidence relations in 3-D space. 9.1.2. Incidence relations in 2-D images. 9.2. Rank conditions for incidence relations. 9.2.1. Intersection of a family of lines. 9.2.2. Restriction to a plane. 9.3. Universal rank conditions on the multiple-view matrix. 9.4. Summary. 9.5. Exercises. 9.A. Incidence relations and rank conditions. 9.B. Beyond constraints among four views. 9.C. Examples of geometric interpretation of the rank conditions. 9.C.1. Case 2: Oleq rank (M) <: 1. 9.C.2. Case 1 :1 < rank (M) < 2. 10. Geometry and Reconstruction from Symmetry. 10.1. Symmetry and multiple-view geometry. 10.1.1. Equivalent views of symmetric structures. 10.1.2. Symmetric structure and symmetry group. 10.1.3. Symmetric multiple-view matrix and rank condition. 10.1.4. Homography group for a planar systemetric structure. 10.2. Symmetry-based 3-D reconstruction. 10.2.1. Canonical pose recovery for symmetric structure. 10.2.2. Pose ambiguity from three types of symmetry. 10.2.3. Structure reconstruction based on symmetry. 10.3. Camera calibration from symmetry. 10.3.1. Calibration from translational symmetry. 10.3.2. Calibration from reflective symmetry. 10.3.3. Calibration from rotational symmetry. 10.4. Summary. 10.5. exercises. IV. Applications. 11. Step-by-Step Building of a #-D Model from Images. 11.1. Feature selection. 11.2. Feature correspondence. 11.2.1. Feature tracking. 11.2.2. Robust matching across wide baselines. 11.3. Projective reconstruction. 11.3.1. Two-view initialization. 11.3.2. Multiple-view reconstruction. 11.3.3. Gradient descent nonlinear refinements ("bundle adjustment')0. 11.4. Upgrade from projective to Euclidean reconstruction. 11.4.1. Stratification with the absolute quadric constraint. 11.4.2. Gradient descent nonlinear refinement ("Euclidean bundle adjustment") 11.5. Visualization. 11.5.1. Epipolar rectification. 11.5.2. dense matching. 11.5.3. Texture mapping. 11.6. Additional techniques for image-based modeling. 12. Visual Feedback. 12.1. Structure and motion estimation as a filtering problem. 12.1.1. Observability. 12.1.2. Realization. 12.1.3. Implementation issues. 12.1.4. Complete algorithm. 12.2. Application to virtual insertion in live video. 12.3. Visual feedback for autonomous car driving. 12.3.1. System setup and implementation, 12.3.2. Vision system design. 12.4.3. System performance and evaluation. V. Appendices. A. Basic Facts from Linear Algebra. A.1. Basic notions associated with a linear space. A.I.1. Linear independence and change of basis. A. 1.2. Inner product and orthogonality. A.1.3. Kronecker product and stack of matrices, A.2. Linear transformations and matrix groups. A.3. Gram-Schmidt and the QR decomposition. A.4. Range, null space (kernel), rank and eigenvectors of a matrix. A.5. Symmetric matrices and skew-symmetric matrices. A.6. Lyapunov map and Lyapunov equation. A.7. The singular value decomposition (SVD). A.7.1, Algebraic derivation. A.7.2. Geometric interpretation. A.7.3. Some properties of the SVD. B. Least-Variance Estimation and Filtering. B.1. Least- variance estimators of random vectors. B.I.1. Projections onto the range of a random vector. B.1.2. Solution for the linear (scalar) estimator. B.1.3. Affine least-variance estimator. B.1.4. Properties and interpretations of the least-variance estimator. B.2. The Kalman-Bucy filter. B.2.1. Linear Gaussian dynamical models. B.2.2. A little intuition. B.2.3. Observability. B.2.4. Derivation of the Kalman filter. B.3. The extended Kalman filter. C. Basic Facts from Nonlinear Optimization. C.1. unconstrained optimization: gradient-based methods. C.I.1. Optimality conditions. C.1.2. Algorithms. C.2. Constrained optimization: Lagrange multiplier method. C.2.1. Optimality conditions. C.2.2. Algorithms. References. Glossary of Notation. Index.

Science Serialized. Edited by Geoffrey Canto and Sally Shuttleworth. The MIT Press. Cambridge. $40.00. 2004. 366 pages.

1. Introduction (Sally Shuttleworth and Geoffrey Cantor). 2. "Let Us Examine the Flower": Botany in Women's Magazines, 1800-1830 (Ann B. Shteir). 3. Science, Natural Theology, and the Practice of Christian

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Piety in Early-Nineteenth-Century Religious Magazines (Jonathan R. Topham). 4. Reporting Rotal Institution Lectures, 1826-1867 (Frank A.J.L. James). 5. The Physiology of the Will: Mind, Body, and Psychology in the Periodical Literature, 1855-1875 (Roger Smith). 6. Sunspots, Weather, and the Unseen Universe: Balfour Stewart's Anti-Materialist Representations of "Energy" in British Periodicals (Graeme Gooday). 7. "Improvised Europeans": Science and Reform in the North American Review, 1865-1880 (Crosbie Smith and Ian Higginson). 8. The Academy: Europe in England (Gillian Beer). 9. Scientists as Materialists in the Periodical Press: Tyndall's Belfast Address (Bernard Lightman). 10. Science, Liberalism, and the Ethics of Belief: The Contemporary Review in 1877 (Helen Small). 11. Victorian Periodicals and the Making of William Kingdon Clifford's Posthumous Reputation (Gowan Dawson). 12. Grant Allen, Physiological Aesthetics, and the Dissemination of Darwin's Botany (Jonathan Smith). 13. The Butler-Darwin Biographical Controversy in the Victorian Periodical Press (James G. Paradis). 14 Understanding Audiences and Misunderstanding Audiences: Some Publics for Science (Harriet Ritvo). About the Authors. Index.

Case Studies in Biomedical Research Ethics. Edited by Timothy F. Murphy. The MIT Press, Cambridge. 2004. $29.00. 340 pages. Contents. Series Foreword. Acknowledgments. Preface. Cases by Chapter. Introduction. 1. Oversight and Study Design. 2. Informed Consent. 3. Selection of Subjects. 4. Conflicts of Interest. 5. Social Effects of research. 6. Embryos, Fetuses, and Children. 7. Genetic research. 8. Use of Animals. 9. Authorship and Publication. Appendix A: The Nuremberg Code. Appendix B: The Declaration of Helsinki. Glossary. Cases by General Category. Alphabetical List of Cases. Index.

Importance Samplinq. Edited by R. Srinivasan. Springer Heidelberg, Germany. (2002) 242 pages. $79.95. Contents: Preface. 1. Elements of Importance Sampling. 1.1. Rare events and simulation. 1.2. Fast simulation. 1.2.1. Random functions. 1.3. Optimal biasing. 1.3.1. Conditions on f , . 1.4. The simulation gain. 2. Methods of Importance Sampling. 2.1. Conventional biasing methods. 2.1.1. Scaling. 2.1.2. Translation. 2.1.3. Exponential twisting. 2.2. Adaptive IS-optimized biasing. 2.2.1. Variance estimation and minimization. 2.2.2. Estimation by IS. 2.3. Combined scaling and translation. 2.4. Other biasing methods. 2.4.1. Extreme order density functions. Biasing with fn,1. Biasing with Sn,n. Appendix A. Appendix B. 3. Sums of Random Variables. 3.1. Tail probability of an i.i.d, sum. 3.2. The g-method. 3.2.1. Advantage over usual IS. 3.3. The inverse IS problem. 3.3.1. System parameter optimization. 3,4. Approximations for tail probability. 3.4.1. The g-representation. 3.5. Asymptotic IS. 3.5.1. The variance rate. Minimizing the rate. 3.5.2. Asymptotic behaviour of the g-method. 3.5.3. Constant probability estimation. The weighting function. 3.6. Density estimation for sums. 3.6.1. An approximation: The Srinivasan density. Convergence of the Srinivasan density. Density and distribution pairs. 3.6.2. Exponential twisting. Appendix C. 4. Detection Theory. 4.1. The Neyman-Pearson lemma. 4.1.1. Properties of likelihood ratio tests. 4.2. Approxi- mations for the error probabilities. 4.3.1. Detection probability. 4.3.2. False alarm probability. 4.4. Densities for the log-likelihood ratio. Appendix D. 5. CFAR detection. 5.1. Constant false alarm rate detection. 5.2. IS for CFAR algorithms. 5.2.1. Input biasing. 5.3. Multiplier determination-adaptive optimization. 5.4. Exponential twisting for CA-CFAR. 5.4.1. Conventional IS estimator. 5.4.2. g-method estimator. A classic example. 5.5. Approximations for CA-CFAR. 5.5.1. Using Density approximations. The asymptotic form. 5.5.2. Using exponential twisting. 5.6. The GM- CFAR detector. 5.6.1. Approximations for FAP. 5.7. Point of application of biasing. 5.8. FAP decomposition for SO detectors: CA and GM. 5.8.1. Fast estimation. 5.8.2. Variance and IS gain. 5.8.3. So- and GO-GM detectors. Approximations for FAP. 5.9. Examples in CFAR detection. 5.10. STAP detection. 6. Ensemble CFAR detection. 6.1. Ensemble processing. 6.2. The E-CFAR detector. 6.2.1. Normalization. 6.2.2. FAP estimation and bias optimization. 6.2.3. Determining ensemble thresholds. 6.3. Performance in nonhomogeneous clutter. 6.4. Results for some ensembles. Geometric mean detectors. 6.4.1. Comments. 6.5.1. FAP decompositions. 6.5.2. Choice of functions: further decompositions. RE1. Res 2,3,5. RE4. RE6. 6.6. Tuning the multipliers: homogeneous operating points. 7. Blind simulation. 7.1. Blind biasing. 7.1.1. The weighting function. 7.2. Tail probability estimation. 7.2.1. The h-function. 7.2.2. The asymptotic rate. 7.2.3. Blind simulation gain. Partially blind case. Completely blind

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case. 7.3. CFAR detection. 7.3.1. Estimator implementation. Optimum twist. 7.3.2. The blind simulation gain. 7.3.3. An application. Threshold adaptation and c~ control. 7.3.4. Comments. 8. Digital Communications. 8.1. Adaptive simulation. 8.2. DPSK in AWGN. 8.3. Parameter optimization. 8.3.1. Noncoherent OOK in AWGN: threshold optimization. 8.4. Sum density of randomly phased sinusoids. 8.5. M-ary PSK in co-channel interference. 8.5.1. Interference dominated environment. Coherent BPSK. M-ary PSK. 8.5.2. Interference with AWGN. Coherent BPSK. M-ary PSK. 8.6. Crosstatk in WDM networks. 8.6.1. Gaussian approximation. 8.6.2. Chernoff bound. 8.6.3. IS estimation. Threshold optimization. 8.7. Multiuser detection. 8.8. Capacity of Mulit-antenna systems. References. Index.

Lectures on Invariant Theory. Edited by Igor Dolgachev. Cambridge University Press. New Yor, NY. 2003. $45.00. 220 pages. Contents: Preface. Introduction. 1. The symbolic method. 1.1. First examples. 1.2. Polarization and restitution. 1.3. Bracket functions. Bibliographical notes. Exercises. 2. The First Fundamental Theorem. 2.1. The omega-operator. 2.2. The proof. 2.3. Grassmann varieties. 2.4. The straightening algorithm. Bibliographical notes. Exercises. 3. Reductive algebraic groups. 3.1. The Gordan-Hilbert Theorem. 3.2. The unitary trick. 3.3. Affine algebraic groups. 3.4. Nagata's Theorem. Bibliographical notes. Exercises. 4. Hilbert's Fourteenth Problem. 4.1. The problem. 4.2. The Weitzenbock Theorem. 4.3. Nagata's coutnerex- ample. Bibliographical notes. Exercises. 5. Algebra of covariant. 5.1. Examples of covariants. 5.2. Covariants of an action. 5.3. Linear representations of reductive groups. 5.4. Dominant weights. 5.5. The Cayley- Sylvester formula. 5.6. Standard tableaux again. Bibliographical notes. Exercises. 6. Quotients. 6.1. Categorical and geometric quotients. 6.2. Examples. 6.3. Rational quotients. Bibliographical notes. Exercises. 7. Linearization of actions. 7.1. Linearized line bundles. 7.3. Linearization of an action. Bibliographical notes. Exercises. 8. Stability. 8.1. Stable points. 8.2. The existence of a quotient. 8.3. Examples. Bibliographical notes. Exercises. 9. Numerical criterion of stability. 9.1. The function #(x, A). 9.2. The numerical criterion. 9.3. The proof. 9.4. The weight polytope. 9.5. Kempf-stability. Bibliographical notes. Exercises. 10. Projective hypersurfaces. 10.1. Nonsingular hypersurfaces. 10.2. Binary forms. 10.3. Plane cubies. 10.4. Cubic surfaces. Bibliographical notes. Exercises. 11. Configurations of Linear subspaces. 11.1. Stable configurations. 11.2. Points in ~n. 11.3. Lines in p3 Bibliographical notes. Exercises. 12. Toric varieties. 12.1. Actions of a torus on an affine space. 12.2. Fans. 12.3. Examples. Bibliographical notes. Exercises. Bibliography. Index of Notation. Index.

The Universal Book of Mathematics. Edited by David Darling. Wiley, Hoboken, NJ. 2004. $40.00. 383 pages. Contents: Acknowledgments. Introduction. Mathematics Entries A to Z. References. Solutions to Puzzles. Category Index.

Computational Algebraic Geometry. Hal Schenck. Cambridge University Press. Cambridge, UK. 2003. Hardback $70.00. Paperback $28.00. 183 pages. Contents: Preface.

1. Basics of commutative Algebra. 1.1. Ideals and Varieties. 1.2. Noetherian Rings and the Hilbert Basis Theorem. 1.3. Associated Primes and Primary Decomposition. 1.4. The Nullstellensatz and Zariski Topology. 2. Projective Space and Graded Objects. 2.1. Projective Space abnd Projective Varieties. 2.2. Graded Rings and Modules, Hilbert Function and Series. 2.3. Linear Algebra Flashback, Hilbert Polynomial. 3. Free Resoutions and Regular Sequences. 3.1. Free Modules and Projective Modules. 3.2. Free Resolutions. 3.3. Regular Sequences, Mapping Cone.

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4. GrSbner Bases. 4.2. Monomial Ideals and Applications. 4.3. Syzygies and GrUobner Bases for Modules. 4.4. Projection and Elimination. 5. Combinatorics, Topology and the Stanley-Reisner Ring. 5.1. Simplicial Complexes and Simplicial Homology. 5.2. The Stanley-t~isner Ring. 5.3. Associated Primes and Primary Decomposition. 6. Functors: Localization, Horn, and Tensor. 6.1. Localization. 6.2. The Horn Functor. 6.3. Tensor Product. 7. Geometry of Points and the Hilbert Function. 7.1. Hilbert Functions of Points, Regularity. 8. Snake ewmIna, Derived Functors, Tor and Ext. 8.1. Snake Lemma, Long Exact Sequence in Homology. 8.2. Derived Functors, Tor. 8.3. Ext. 8.4. Double Complexes. 9. Curves, Sheaves, and Cohomology. 9.1. Sheaves. 9.2. Cohomology. 9.3. Divisors and Maps to Fn. 9.4. Riemann-Roch and Hilbert Polynomial Redux. 10. Projective Dimension, Cohen-Macaulay Modules, Upper Bound Theorem. 10.1. Codimension, Depth. Auslander-Buchsbaum Theorem. 10.2. Cohen-Macaulay Modules and Geometry. 10.3. The Upper Bound Con- jecture for Spheres. A. Abstract Algebra Primer. A.1. Groups. A.2. Rings and Modules. A.3. Computational Algebra. B. Complex Analysis Primer. B.1. Complex Functions, Cauchy-Riemann Equations. B.2. Green's Theorem. B.3. Cauchy's Theorem. B.4. Taylor and Laurent Series, Residues. Bibliography. Index.