This book focuses on the electromagnetic and thermal modeling and analysis of electrical machines, especially canned electrical machines for hydraulic pump applications. It addresses both the principles and engineering practice, with more weight placed on mathematical modeling and theoretical analysis. This is achieved by providing in-depth studies on a number of major topics such as: can shield effect analysis, machine geometry optimization, control analysis, thermal and electromagnetic network models, magneto motive force modeling, and spatial magnetic field modeling. For the can shield effect analysis, several cases are studied in detail, including classical canned induction machines, as well as state-of-the-art canned permanent magnet machines and switched reluctance machines. The comprehensive and systematic treatment of the can effect for canned electrical machines is one of the major features of this book, which is particularly suited for readers who are interested in learning about electrical machines, especially for hydraulic pumping, deep-sea exploration, mining and the nuclear power industry. The book offers a valuable resource for researchers, engineers, and graduate students in the fields of electrical machines, magnetic and thermal engineering, etc.

Data Management is the process of planning, coordinating and controlling data resources. More often, applications need to store and search a large amount of data. Managing Data has been continuously challenged by demands from various areas and applications and has evolved in parallel with advances in hardware and computing techniques.

This volume focuses on its recent advances and it is composed of five parts and a total of eighteen chapters. The first part of the book contains five contributions in the area of information retrieval and Web intelligence: a novel approach to solving index selection problem, integrated retrieval from Web of documents and data, bipolarity in database querying, deriving data summarization through ontologies, and granular computing for Web intelligence. The second part of the book contains four contributions in knowledge discovery area. Its third part contains three contributions in information integration and data security area. The remaining two parts of the book contain six contributions in the area of intelligent agents and applications of data management in medical domain.

This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology. Hidden Markov Models: Methods and Protocols guides readers through chapters on biological systems; ranging from single biomolecule, cellular level, and to organism level and the use of HMMs in unravelling the complex mechanisms that govern these complex systems. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Hidden Markov Models: Methods and Protocols aims to demonstrate the impact of HMM in biology and inspire new research.

The effective planning of residential location choices is one of the great challenges of contemporary societies and requires forecasting capabilities and the consideration of complex interdependencies which can only be handled by complex computer models. This book presents a range of approaches used to model residential locations within the context of developing land-use and transport models. These approaches illustrate the range of choices that modellers have to make in order to represent residential choice behaviour. The models presented in this book represent the state-of-the-art and are valuable both as key building blocks for general urban models, and as representative examples of complexity science.

This Festschrift is dedicated to Professor Dr.-Ing. habil. Peter Wriggers on the occasion of his 60th birthday. It contains contributions from friends and collaborators as well as current and
former PhD students from almost all continents. As a very diverse group of people, the authors cover a wide range of topics from fundamental research to industrial applications: contact mechanics, finite element technology, micromechanics, multiscale approaches,
particle methods, isogeometric analysis, stochastic methods and further research interests. In summary, the volume presents an overview of the international state of the art in computational mechanics, both in academia and industry.

Stochastic global optimization is a very important subject, that has applications in virtually all areas of science and technology. Therefore there is nothing more opportune than writing a book about a successful and mature algorithm that turned out to be a good tool in solving difficult problems. Here we present some techniques for solving several problems by means of Fuzzy Adaptive Simulated Annealing (Fuzzy ASA), a fuzzy-controlled version of ASA, and by ASA itself. ASA is a sophisticated global optimization algorithm that is based upon ideas of the simulated annealing paradigm, coded in the C programming language and developed to statistically find the best global fit of a nonlinear constrained, non-convex cost function over a multi-dimensional space. By presenting detailed examples of its application we want to stimulate the reader's intuition and make the use of Fuzzy ASA (or regular ASA) easier for everyone wishing to use these tools to solve problems. We kept formal mathematical requirements to a minimum and focused on continuous problems, although ASA is able to handle discrete optimization tasks as well. This book can be used by researchers and practitioners in engineering and industry, in courses on optimization for advanced undergraduate and graduate levels, and also for self-study.

This book deals with various computational procedures for multiple repeated analyses (reanalysis) of structures, and presents them in a unified approach. It meets the need for a general text covering the basic concepts and methods as well as recent developments in this area. Reanalysis is common to numerous analysis and design tasks such as nonlinear analysis, structural optimization, damage analysis, and probabilistic analysis. The book discusses various analysis models, including linear and nonlinear analysis, static and dynamic analysis, and design sensitivity analysis. It demonstrates how various concepts and methods are integrated to achieve effective solution procedures. The approach presented has several advantages in terms of generality, efficiency of the calculations, accuracy of the results and ease of implementation. Efficiency and accuracy considerations are discussed and illustrated. To clarify the presentation, many illustrative examples and numerical results are demonstrated. The text is related to a wide range of applications in such fields as Mechanical Engineering, Aerospace Engineering, Civil Engineering, and Naval Architecture. This should prove useful to students, researchers, analysts and consultants involved in analysis and design of structures. Previous books on structural analysis do not cover most of the material presented in the book.

"We live in the age of data. In the last few years, the methodology of extracting insights from data or "data science" has emerged as a discipline in its own right. The R programming language has become one-stop solution for all types of data analysis. The growing popularity of R is due its statistical roots and a vast open source package library. The goal of "Beginning Data Science with R" is to introduce the readers to some of the useful data science techniques and their implementation with the R programming language. The book attempts to strike a balance between the how: specific processes and methodologies, and understanding the why: going over the intuition behind how a particular technique works, so that the reader can apply it to the problem at hand. This book will be useful for readers who are not familiar with statistics and the R programming language.

Compared with data from general application domains, modern biological data has many unique characteristics. Biological data are often characterized as having large volumes, complex structures, high dimensionality, evolving biological concepts, and insufficient data modelling practices. Over the past several years, bioinformatics has become an all-encompassing term for everything relating to both computer science and biology. The goal of this book is to cover data and applications identifying new issues and directions for future research in biomedical domain. The book will become a useful guide learning state-of-the-art development in biomedical data management, data-intensive bioinformatics systems, and other miscellaneous biological database applications. The book addresses various topics in bioinformatics with varying degrees of balance between biomedical data models and their real-world applications.

Let's try to play the music and not the background. Ornette Coleman, liner notes of the LP "Free Jazz" 20] WhenIbegantocreateacourseonfreejazz, theriskofsuchanenterprise was immediately apparent: I knew that Cecil Taylor had failed to teach such a matter, and that for other, more academic instructors, the topic was still a sort of outlandish adventure. To be clear, we are not talking about tea- ing improvisation here-a di?erent, and also problematic, matter-rather, we wish to create a scholarly discourse about free jazz as a cultural achievement, and follow its genealogy from the American jazz tradition through its various outbranchings, suchastheEuropeanandJapanesejazzconceptionsandint- pretations. We also wish to discuss some of the underlying mechanisms that are extant in free improvisation, things that could be called technical aspects. Such a discourse bears the ?avor of a contradicto in adjecto: Teachingthe unteachable, the very negation of rules, above all those posited by white jazz theorists, and talking about the making of sounds without aiming at so-called factual results and all those intellectual sedimentations: is this not a suicidal topic? My own endeavors as a free jazz pianist have informed and advanced my conviction that this art has never been theorized in a satisfactory way, not even by Ekkehard Jost in his unequaled, phenomenologically precise p- neering book "Free Jazz" 57].

This book and companion DVD provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with a broad range of real-world applications. The companion DVD contains tutorials, sample code, and software packages with demonstrations, enabling readers to test and use tools presented in the book.

The book will be useful as a textbook for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.

Because of its ability to treat both regions with irregular boundaries and with different material types, the finite element method is increasingly being applied to surface water and soil transport problems and this is the focus of the present volume. The method is ideally suited to simulation of complex real applications for resolving environmental issues and for conducting environmental impact studies. The present volume focuses on the two main areas of environmental modeling with finite elements and the supporting finite element methodology. Five chapters are devoted to ocean and coastal engineering, one to other surface water problems, several to ground water modeling and contaminant transport, including radioactive waste, and the remainder to mathematical models, particularly for mixed finite elements and nonlinear problems. Environmental problems are of increasing topicality and importance today. Special care has been taken in organizing and editing the material to form the right combination of modeling, methodology, and applications studies to form a cohesive treatment appropriate for a graduate course or seminar on the subject. It is aimed in particular at engineers working in computational environmental fluid mechanics and transport processes.

This volume is a collection of chapters covering recent advances in stochastic optimal control theory and algebraic systems theory. The book will be a useful reference for researchers and graduate students in systems and control, algebraic systems theory, and applied mathematics. Requiring only knowledge of undergraduate-level control and systems theory, the work may be used as a supplementary textbook in a graduate course on optimal control or algebraic systems theory.

The main focus of this thesis is the mathematical structure of Group Field Theories (GFTs) from the point of view of renormalization theory. Such quantum field theories are found in approaches to quantum gravity related, on the one hand, to Loop Quantum Gravity (LQG) and on the other, to matrix- and tensor models. Background material on these topics, including conceptual and technical aspects, are introduced in the first chapters. The work then goes on to explain how the standard tools of Quantum Field Theory can be generalized to GFTs and exploited to study the large cut-off behaviour and renormalization group transformations of the latter. Among the new results derived in this context are a proof of renormalizability of a three-dimensional GFT with gauge group SU(2), which opens the way to applications of the formalism to quantum gravity.

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different approaches and help students grasp general concepts and theoretical results. The text is suitable for majors in mathematics and statistics as well as majors in computer science, economics, finance, and physics. The author offers two explicit options to teaching the material, which is reflected in "routes" designated by special "roadside" markers. The first route contains basic, self-contained material for a one-semester course. The second provides a more complete exposition for a two-semester course or self-study.

With an emphasis on models and techniques, this textbook introduces many of the fundamental concepts of stochastic modeling that are now a vital component of almost every scientific investigation. In particular, emphasis is placed onlaying the foundationfor solvingproblemsin reliability, insurance, finance, and credit risk.

The material has been carefully selected to cover the basic concepts and techniques on each topic, making this an ideal introductory gateway to more advanced learning. With exercises and solutions to selected problems accompanying each chapter, this textbook is for a wide audience including advanced undergraduate and beginning-level graduate students, researchers, and practitioners in mathematics, statistics, engineering, and economics."

"Combat Modeling" is a systematic learning resource and reference text for the quantitative analysis of combat. After a brief overview, authors Washburn and Kress present individual chapters on shooting without feedback; shooting with feedback; target defense; attrition models; game theory and wargames; search; unmanned aerial vehicles; and terror and insurgency. Three appendices provide a review of basic probability concepts, probability distributions, and Markov models; an introduction to optimization models; and a discussion of Monte-Carlo simulations. Drawing on their many years of experience at the Naval Postgraduate School in Monterey, California, Washburn and Kress have created a reference that will provide the tools and techniques for analysts involved in the underpinnings of combat decisions. This is a book that can be used as a military manual, reference book, and textbook for military courses on this vital subject.

A lot of economic problems can be formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories. The series is designed to bring together those mathematicians who are seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking effective mathematical tools for their research.

This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. The conference provided a major point of collaboration between researchers, engineers and practitioners in the areas of Pattern Recognition, both from theoretical and applied perspectives, with a focus on mathematical methodologies. Contributions describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, and experimental and theoretical studies which yield new insights that provide key advances in the field. This book will be suitable for scientists and researchers in optimization, numerical methods, computer science, statistics and for differential geometers and mathematical physicists.

In this issue of Notes on Numerical Fluid Mechanics and Multidisciplinary Design (NNFM) the results of the collaborative research center SFB 401 Flow Modulation and Fluid-Structure Interaction at Airplane Wings at the Rheinisch-Westf. alische Technische Hochschule (RWTH) Aachen University are reported. The funding was provided by the Deutsche Forschungsgeme- schaft (DFG). The research was performed from 1997 through 2008 and on the average consisted of more than 14 subprojects per year. Approximately 110 scientists from universities of the Austria, Belgium, France, Great Britain, Italy, Japan, Netherlands, Russia, South Korea, S- den, Switzerland, United States, and international research organizations such as DLR, NASA, NLR, ONERA were invited. The distinct scientists from all over the world gave seminars on topics related to the research ?elds tackled in the collaborative research center SFB 401. Some of them stayed for just a few days, others were hosted for a longer time to intensify the joint research. Besidesthescienti?cvaluetheFlow Modulation and Fluid-StructureInt- action at Airplane Wings programpossessesapronouncededucationalmerit. This becomes evident by the fact that 35 doctoral theses, 80 diploma theses, and 117 study theses were stimulated by the research program of the SFB 401 and ?nished before 2010. The authors of this issue of NNFM acknowledge the valuable support fromall guestscientists and everybodyscienti?callyinvolvedin the SFB 401.

A unique interdisciplinary foundation for real-world problem solving

Stochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and finance, to name but a few. Whether the goal is refining the design of a missile or aircraft, determining the effectiveness of a new drug, developing the most efficient timing strategies for traffic signals, or making investment decisions in order to increase profits, stochastic algorithms can help researchers and practitioners devise optimal solutions to countless real-world problems.

Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control is a graduate-level introduction to the principles, algorithms, and practical aspects of stochastic optimization, including applications drawn from engineering, statistics, and computer science. The treatment is both rigorous and broadly accessible, distinguishing this text from much of the current literature and providing students, researchers, and practitioners with a strong foundation for the often-daunting task of solving real-world problems.

The text covers a broad range of today’s most widely used stochastic algorithms, including:

• Random search
• Recursive linear estimation
• Stochastic approximation
• Simulated annealing
• Genetic and evolutionary methods
• Machine (reinforcement) learning
• Model selection
• Simulation-based optimization
• Markov chain Monte Carlo
• Optimal experimental design

The book includes over 130 examples, Web links to software and data sets, more than 250 exercises for the reader, and an extensive list of references. These features help make the text an invaluable resource for those interested in the theory or practice of stochastic search and optimization.

The book offers a new approach to information theory that is more general then the classical approach by Shannon. The classical definition of information is given for an alphabet of symbols or for a set of mutually exclusive propositions (a partition of the probability space ) with corresponding probabilities adding up to 1. The new definition is given for an arbitrary cover of , i.e. for a set of possibly overlapping propositions. The generalized information concept is called novelty and it is accompanied by two new concepts derived from it, designated as information and surprise, which describe "opposite" versions of novelty, information being related more to classical information theory and surprise being related more to the classical concept of statistical significance. In the discussion of these three concepts and their interrelations several properties or classes of covers are defined, which turn out to be lattices. The book also presents applications of these new concepts, mostly in statistics and in neuroscience.

Kinematics is an exciting area of computational mechanics which plays a central role in a great variety of fields and industrial applications. Apart from research in pure kinematics, the field offers challenging problems of practical relevance that need to be solved in an interdisciplinary manner in order for new technologies to develop. The present book collects a number of important contributions presented during the First Conference on Interdisciplinary Applications of Kinematics (IAK 2008) held in Lima, Peru. To share inspiration and non-standard solutions among the different applications, the conference brought together scientists from several research fields related to kinematics, such as for example, computational kinematics, multibody systems, industrial machines, robotics, biomechanics, mechatronics and chemistry. The conference focused on all aspects of kinematics, namely modeling, optimization, experimental validation, industrial applications, theoretical kinematical methods, and design. The results should be of interest for practicing and research engineers as well as Ph.D. students from the fields of mechanical and electrical engineering, computer science, and computer graphics.

Mathematical models are often used to describe complex phenomena such as climate change dynamics, stock market fluctuations, and the Internet. These models typically depend on estimated values of key parameters that determine system behavior. Hence it is important to know what happens when these values are changed. The study of single-parameter deviations provides a natural starting point for this analysis in many special settings in the sciences, engineering, and economics. The difference between the actual and nominal values of the perturbation parameter is small but unknown, and it is important to understand the asymptotic behavior of the system as the perturbation tends to zero. This is particularly true in applications with an apparent discontinuity in the limiting behavior - the so-called singularly perturbed problems. Analytic Perturbation Theory and Its Applications includes a comprehensive treatment of analytic perturbations of matrices, linear operators, and polynomial systems, particularly the singular perturbation of inverses and generalized inverses. It also offers original applications in Markov chains, Markov decision processes, optimization, and applications to Google PageRank(TM) and the Hamiltonian cycle problem as well as input retrieval in linear control systems and a problem section in every chapter to aid in course preparation.

Logic networks and automata are facets of digital systems. The change of the design of logic networks from skills and art into a scientific discipline was possible by the development of the underlying mathematical theory called the Switching Theory. The fundamentals of this theory come from the attempts towards an algebraic description of laws of thoughts presented in the works by George J. Boole and the works on logic by Augustus De Morgan. As often the case in engineering, when the importance of a problem and the need for solving it reach certain limits, the solutions are searched by many scholars in different parts of the word, simultaneously or at about the same time, however, quite independently and often unaware of the work by other scholars. The formulation and rise of Switching Theory is such an example. This book presents a brief account of the developments of Switching Theory and highlights some less known facts in the history of it. The readers will find the book a fresh look into the development of the field revealing how difficult it has been to arrive at many of the concepts that we now consider obvious . Researchers in the history or philosophy of computing will find this book a valuable source of information that complements the standard presentations of the topic.