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Inductive reasoning is everyday, intuitive reasoning; it contrasts with deductive or logical reasoning. Inductive reasoning is much more prevalent than deductive reasoning, yet there has been much less research on inductive reasoning. Using contributions from the leading researchers in the field, the interdisciplinary approach of this book is relevant to those interested in psychology (including cognitive and developmental psychology), decision-making, philosophy, computer science, and education.

Process Modelling and simulation have proved to be extremely successful engineering tools for the design and optimisation of physical, chemical and biochemical processes. The use of simulation has expanded rapidly over the last two decades because of the availability of large high-speed computers and indeed has become even more widespread with the rise of the desk-top PC resources now available to nearly every engineer and student. In the chemical industry large, realistic non-linear problems are routinely solved with the aid of computer simulation. This has a number of benefits, including easy assessment of the economic desirability of a project, convenient investigation of the effects of changes to system variables, and finally the introduction of mathematical rigour into the design process and inherent assumptions that may not have been there before. Computational Methods for Process Simulation develops the methods needed for the simulation of real processes to be found in the process industries. It also stresses the engineering fundamentals used in developing process models. Steady state and dynamic systems are considered, for both spatially lumped and spatially distributed problems. It develops analytical and numerical computational techniques for algebraic, ordinary and partial differential equations, and makes use of computer software routines that are widely available. Dedicated software examples are available via the internet.Written for a compulsory course element in the USIncludes examples using software used in academia and industrySoftware available via the Internet

This textbook presents basic numerical methods and applies them to a large variety of physical models in multiple computer experiments. Classical algorithms and more recent methods are explained. Partial differential equations are treated generally comparing important methods, and equations of motion are solved by a large number of simple as well as more sophisticated methods. Several modern algorithms for quantum wavepacket motion are compared. The first part of the book discusses the basic numerical methods, while the second part simulates classical and quantum systems. Simple but non-trivial examples from a broad range of physical topics offer readers insights into the numerical treatment but also the simulated problems. Rotational motion is studied in detail, as are simple quantum systems. A two-level system in an external field demonstrates elementary principles from quantum optics and simulation of a quantum bit. Principles of molecular dynamics are shown. Modern boundary element methods are presented in addition to standard methods, and waves and diffusion processes are simulated comparing the stability and efficiency of different methods. A large number of computer experiments is provided, which can be tried out even by readers with no programming skills. Exercises in the applets complete the pedagogical treatment in the book. In the third edition Monte Carlo methods and random number generation have been updated taking recent developments into account. Krylov-space methods for eigenvalue problems are discussed in much more detail. Short time Fourier transformation and wavelet transformation have been included as tools for time-frequency analysis. Lastly, elementary quantum many-body problems demonstrate the application of variational and Monte-Carlo methods.

Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations, Third Edition, continues the legacy of this authoritative and complete theoretical work. It is ideal for graduate and PhD students and working engineers interested in posing and solving problems using the tools of logico-mathematical modeling and computer simulation. Continuing its emphasis on the integration of discrete event and continuous modeling approaches, the work focuses light on DEVS and its potential to support the co-existence and interoperation of multiple formalisms in model components. New sections in this updated edition include discussions on important new extensions to theory, including chapter-length coverage of iterative system specification and DEVS and their fundamental importance, closure under coupling for iteratively specified systems, existence, uniqueness, non-deterministic conditions, and temporal progressiveness (legitimacy).Presents a 40% revised and expanded new edition of this classic book with many important post-2000 extensions to core theoryProvides a streamlined introduction to Discrete Event System Specification (DEVS) formalism for modeling and simulationPackages all the "need-to-know" information on DEVS formalism in one place Expanded to include an online ancillary package, including numerous examples of theory and implementation in DEVS-based software, student solutions and instructors manual

The Art of Computer Systems Performance Analysis "At last, a welcome and needed text for computer professionals who require practical, ready-to-apply techniques for performance analysis. Highly recommended!" -Dr. Leonard Kleinrock University of California, Los Angeles "An entirely refreshing text which has just the right mixture of theory and real world practice. The book is ideal for both classroom instruction and self-study." -Dr. Raymond L. Pickholtz President, IEEE Communications Society "An extraordinarily comprehensive treatment of both theoretical and practical issues." -Dr. Jeffrey P. Buzen Internationally recognized performance analysis expert ". it is the most thorough book available to date" -Dr. Erol Gelenbe Université René Descartes, Paris ". an extraordinary book.. A worthy addition to the bookshelf of any practicing computer or communications engineer" -Dr. Vinton G. Cer??? Chairman, ACM SIGCOMM "This is an unusual object, a textbook that one wants to sit down and peruse. The prose is clear and fluent, but more important, it is witty." -Allison Mankin The Mitre Washington Networking Center Newsletter

COMPUTATIONAL METHODS IN CIRCUIT SIMULATION INCUDES THEORY, NUMERICAL TECHNIQUES, AND RECIPES ON HOW TO BUILD A SIMULATOR FOR THE ANALYSIS OF VERY LARGE CIRCUITS WITH COMPLEX DEVICE AND COMPONENT MODELS This book provides theoretical basis of circuit simulation with special emphasis on the simulation of very large circuits and systems. The results are presented in algorithmic form and recipes that can be easily translated into computer code. The book: · Explains the theoretical basis of circuit formulation and describes the Extended Nodal Analysis, which is a generalization of the traditional nodal and modified nodal analysis that allows the inclusion of complex device models. · Describes how to build the circuit equations from the input netlist using the stamp approach. · Presents the solution of large linear equations using sparse matrix techniques, partitioning, iterative and projection methods. · Covers DC solution or the solution of nonlinear algebraic equations, including variations of Newton method and piecewise-linear techniques. · Covers transient analysis or solution of algebraic-differential equations, including integration formulas, stability, error estimation and step-size control. · Explains reduced-order modeling for the simulation of very large dynamic circuits and systems. · Includes sensitivity analysis.

Understanding Molecular Simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique for a given application. A wide variety of tools exist, so the choice of technique requires a good understanding of the basic principles. More importantly, such understanding may greatly improve the efficiency of a simulation program. The implementation of simulation methods is illustrated in pseudocodes and their practical use in the case studies used in the text. Since the first edition only five years ago, the simulation world has changed significantly -- current techniques have matured and new ones have appeared. This new edition deals with these new developments; in particular, there are sections on: Transition path sampling and diffusive barrier crossing to simulaterare eventsDissipative particle dynamic as a course-grained simulation techniqueNovel schemes to compute the long-ranged forcesHamiltonian and non-Hamiltonian dynamics in the context constant-temperature and constant-pressure molecular dynamics simulationsMultiple-time step algorithms as an alternative for constraintsDefects in solidsThe pruned-enriched Rosenbluth sampling, recoil-growth, and concerted rotations for complex moleculesParallel tempering for glassy Hamiltonians Examples are included that highlight current applications and the codes of case studies are available on the World Wide Web. Several new examples have been added since the first edition to illustrate recent applications. Questions are included in this new edition. No prior knowledge of computer simulation is assumed.

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Arguably the strongest addition to numerical finance of the past decade, Algorithmic Adjoint Differentiation (AAD) is the technology implemented in modern financial software to produce thousands of accurate risk sensitivities, within seconds, on light hardware.     AAD recently became a centerpiece of modern financial systems and a key skill for all quantitative analysts, developers, risk professionals or anyone involved with derivatives. It is increasingly taught in Masters and PhD programs in finance.    Danske Bank's wide scale implementation of AAD in its production and regulatory systems won the In-House System of the Year 2015 Risk award. The Modern Computational Finance books, written by three of the very people who designed Danske Bank's systems, offer a unique insight into the modern implementation of financial models. The volumes combine financial modeling, mathematics and programming to resolve real life financial problems and produce effective derivatives software.     This volume is a complete, self-contained learning reference for AAD, and its application in finance. AAD is explained in deep detail throughout chapters that gently lead readers from the theoretical foundations to the most delicate areas of an efficient implementation, such as memory management, parallel implementation and acceleration with expression templates.     The book comes with professional source code in C++, including an efficient, up to date implementation of AAD and a generic parallel simulation library. Modern C++, high performance parallel programming and interfacing C++ with Excel are also covered. The book builds the code step-by-step, while the code illustrates the concepts and notions developed in the book.

Modeling and simulation play an ever increasing role in the development and optimization of materials. Computational Materials Science presents the most important approaches in this new interdisciplinary field of materials science and engineering. The reader will learn to assess which numerical method is appropriate for performing simulations at the various microstructural levels and how they can be coupled. This book addresses graduate students and professionals in materials science and engineering as well as materials-oriented physicists and mechanical engineers.

A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems.There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

Arguably the strongest addition to numerical finance of the past decade, Algorithmic Adjoint Differentiation (AAD) is the technology implemented in modern financial software to produce thousands of accurate risk sensitivities, within seconds, on light hardware.     AAD recently became a centerpiece of modern financial systems and a key skill for all quantitative analysts, developers, risk professionals or anyone involved with derivatives. It is increasingly taught in Masters and PhD programs in finance.    Danske Bank's wide scale implementation of AAD in its production and regulatory systems won the In-House System of the Year 2015 Risk award. The Modern Computational Finance books, written by three of the very people who designed Danske Bank's systems, offer a unique insight into the modern implementation of financial models. The volumes combine financial modeling, mathematics and programming to resolve real life financial problems and produce effective derivatives software.     This volume is a complete, self-contained learning reference for AAD, and its application in finance. AAD is explained in deep detail throughout chapters that gently lead readers from the theoretical foundations to the most delicate areas of an efficient implementation, such as memory management, parallel implementation and acceleration with expression templates.     The book comes with professional source code in C++, including an efficient, up to date implementation of AAD and a generic parallel simulation library. Modern C++, high performance parallel programming and interfacing C++ with Excel are also covered. The book builds the code step-by-step, while the code illustrates the concepts and notions developed in the book.

Starting with the simplest semiclassical approaches and ending with the description of complex fully quantum-mechanical methods for quantum transport analysis of state-of-the-art devices, Computational Electronics: Semiclassical and Quantum Device Modeling and Simulation provides a comprehensive overview of the essential techniques and methods for effectively analyzing transport in semiconductor devices. With the transistor reaching its limits and new device designs and paradigms of operation being explored, this timely resource delivers the simulation methods needed to properly model state-of-the-art nanoscale devices. The first part examines semiclassical transport methods, including drift-diffusion, hydrodynamic, and Monte Carlo methods for solving the Boltzmann transport equation. Details regarding numerical implementation and sample codes are provided as templates for sophisticated simulation software. The second part introduces the density gradient method, quantum hydrodynamics, and the concept of effective potentials used to account for quantum-mechanical space quantization effects in particle-based simulators. Highlighting the need for quantum transport approaches, it describes various quantum effects that appear in current and future devices being mass-produced or fabricated as a proof of concept. In this context, it introduces the concept of effective potential used to approximately include quantum-mechanical space-quantization effects within the semiclassical particle-based device simulation scheme. Addressing the practical aspects of computational electronics, this authoritative resource concludes by addressing some of the open questions related to quantum transport not covered in most books. Complete with self-study problems and numerous examples throughout, this book supplies readers with the practical understanding required to create their own simulators.

COMPUTATIONAL METHODS IN CIRCUIT SIMULATION INCUDES THEORY, NUMERICAL TECHNIQUES, AND RECIPES ON HOW TO BUILD A SIMULATOR FOR THE ANALYSIS OF VERY LARGE CIRCUITS WITH COMPLEX DEVICE AND COMPONENT MODELS This book provides theoretical basis of circuit simulation with special emphasis on the simulation of very large circuits and systems. The results are presented in algorithmic form and recipes that can be easily translated into computer code. The book: · Explains the theoretical basis of circuit formulation and describes the Extended Nodal Analysis, which is a generalization of the traditional nodal and modified nodal analysis that allows the inclusion of complex device models. · Describes how to build the circuit equations from the input netlist using the stamp approach. · Presents the solution of large linear equations using sparse matrix techniques, partitioning, iterative and projection methods. · Covers DC solution or the solution of nonlinear algebraic equations, including variations of Newton method and piecewise-linear techniques. · Covers transient analysis or solution of algebraic-differential equations, including integration formulas, stability, error estimation and step-size control. · Explains reduced-order modeling for the simulation of very large dynamic circuits and systems. · Includes sensitivity analysis.

World Scientific, c.2022, 8vo., boards, 196pp., NF $

The essential introduction to computational science―now fully updated and expandedComputational science is an exciting new field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. This textbook provides students with a versatile and accessible introduction to the subject. It assumes only a background in high school algebra, enables instructors to follow tailored pathways through the material, and is the only textbook of its kind designed specifically for an introductory course in the computational science and engineering curriculum. While the text itself is generic, an accompanying website offers tutorials and files in a variety of software packages.This fully updated and expanded edition features two new chapters on agent-based simulations and modeling with matrices, ten new project modules, and an additional module on diffusion. Besides increased treatment of high-performance computing and its applications, the book also includes additional quick review questions with answers, exercises, and individual and team projects.The only introductory textbook of its kind―now fully updated and expandedFeatures two new chapters on agent-based simulations and modeling with matricesIncreased coverage of high-performance computing and its applicationsIncludes additional modules, review questions, exercises, and projectsAn online instructor's manual with exercise answers, selected project solutions, and a test bank and solutions (available only to professors)An online illustration package is available to professors

Starting with the simplest semiclassical approaches and ending with the description of complex fully quantum-mechanical methods for quantum transport analysis of state-of-the-art devices, Computational Electronics: Semiclassical and Quantum Device Modeling and Simulation provides a comprehensive overview of the essential techniques and methods for effectively analyzing transport in semiconductor devices. With the transistor reaching its limits and new device designs and paradigms of operation being explored, this timely resource delivers the simulation methods needed to properly model state-of-the-art nanoscale devices. The first part examines semiclassical transport methods, including drift-diffusion, hydrodynamic, and Monte Carlo methods for solving the Boltzmann transport equation. Details regarding numerical implementation and sample codes are provided as templates for sophisticated simulation software. The second part introduces the density gradient method, quantum hydrodynamics, and the concept of effective potentials used to account for quantum-mechanical space quantization effects in particle-based simulators. Highlighting the need for quantum transport approaches, it describes various quantum effects that appear in current and future devices being mass-produced or fabricated as a proof of concept. In this context, it introduces the concept of effective potential used to approximately include quantum-mechanical space-quantization effects within the semiclassical particle-based device simulation scheme. Addressing the practical aspects of computational electronics, this authoritative resource concludes by addressing some of the open questions related to quantum transport not covered in most books. Complete with self-study problems and numerous examples throughout, this book supplies readers with the practical understanding required to create their own simulators.

Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations, Third Edition, continues the legacy of this authoritative and complete theoretical work. It is ideal for graduate and PhD students and working engineers interested in posing and solving problems using the tools of logico-mathematical modeling and computer simulation. Continuing its emphasis on the integration of discrete event and continuous modeling approaches, the work focuses light on DEVS and its potential to support the co-existence and interoperation of multiple formalisms in model components. New sections in this updated edition include discussions on important new extensions to theory, including chapter-length coverage of iterative system specification and DEVS and their fundamental importance, closure under coupling for iteratively specified systems, existence, uniqueness, non-deterministic conditions, and temporal progressiveness (legitimacy).Presents a 40% revised and expanded new edition of this classic book with many important post-2000 extensions to core theoryProvides a streamlined introduction to Discrete Event System Specification (DEVS) formalism for modeling and simulationPackages all the "need-to-know" information on DEVS formalism in one place Expanded to include an online ancillary package, including numerous examples of theory and implementation in DEVS-based software, student solutions and instructors manual

From a pioneer in experimental economics, an expanded and updated edition of a textbook that brings economic experiments into the classroomEconomics is rapidly becoming a more experimental science, and the best way to convey insights from this research is to engage students in classroom simulations that motivate subsequent discussions and reading. In this expanded and updated second edition of Markets, Games, and Strategic Behavior, Charles Holt, one of the leaders in experimental economics, provides an unparalleled introduction to the study of economic behavior, organized around risky decisions, games of strategy, and economic markets that can be simulated in class. Each chapter is based on a key experiment, presented with accessible examples and just enough theory.Featuring innovative applications from the lab and the field, the book introduces new research on a wide range of topics. Core chapters provide an introduction to the experimental analysis of markets and strategic decisions made in the shadow of risk or conflict. Instructors can then pick and choose among topics focused on bargaining, game theory, social preferences, industrial organization, public choice and voting, asset market bubbles, and auctions.Based on decades of teaching experience, this is the perfect book for any undergraduate course in experimental economics or behavioral game theory.New material on topics such as matching, belief elicitation, repeated games, prospect theory, probabilistic choice, macro experiments, and statistical analysisParticipatory experiments that connect behavioral theory and laboratory researchLargely self-contained chapters that can each be covered in a single classGuidance for instructors on setting up classroom experiments, with either hand-run procedures or free online softwareEnd-of-chapter problems, including some conceptual-design questions, with hints or partial solutions provided

In the past decade, major progress has been made in understanding mec- nisms of arrhythmias. This progress stems from much-improved experim- tal, genetic, and computational techniques that have helped to clarify the roles of speci?c proteins in the cardiac cycle, including ion channels, pumps, - changer, adaptor proteins, cell-surface receptors, and contractile proteins. The interactions of these components, and their individual potential as therap- tic targets, have also been studied in detail, via an array of new imaging and sophisticated experimental modalities. The past 10 years have also led to the realization that genetics plays a predominant role in the development of lethal arrhythmias. Many of the topics discussed in this text re?ect very recently undertaken research directions including the genetics of arrhythmias, cell signaling mo- cules as potential therapeutic targets, and traf?cking to the membrane. These new approaches and implementations of anti-arrhythmic therapy derive from many decades of research as outlined in the ?rst chapter by the distinguished professors Michael Rosen (Columbia University) and Michiel Janse (University of Amsterdam). The text covers changes in approaches to arrhythmia therapy over time, in multiple cardiac regions, and over many scales, from gene to protein to cell to tissue to organ.