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A Course of Mathematics for Engineers and Scientists, Volume 1 studies the various concepts in pure and applied mathematics, specifically the technique and applications of differentiation and integration of one variable, geometry of two dimensions, and complex numbers. The book is divided into seven chapters, wherein the first of which presents the introductory concepts, such as the functional notation and fundamental definitions; the roots of equations; and limits and continuity. The text then tackles the techniques and applications of differentiation and integration. Geometry of two dimensions and complex numbers are also encompassed in the book. The text will be very invaluable to students of pure and applied mathematics and engineering, as well as those mathematicians and engineers who need a refresher on the topic.

Mathematics for the General Course in Engineering, Volume I covers the syllabus in mathematics for the G.1 year of the general course in engineering. Provided in this text are 31 unworked examples, which form a comprehensive revision course that students are recommended to work through toward the end of the G.l year. Answers to the text examples are provided at the end. The subjects covered in this book are arithmetic; indices, logarithms, and the use of tables; length, area, and volume; algebra; geometry; and trigonometry. This volume provides students taking mathematics for the G.1 year in engineering a sound basis for the work of the G.2 year.

A Course of Mathematics for Engineers and Scientists, Volume 2 continues the course of pure and applied mathematics for undergraduate science and engineering students. It contains further examples and exercises from examination papers from Oxford University, Cambridge University, and the University of London. The topics covered in this book include differential equations, linear equations, matrices and determinants, vector algebra and coordinate geometry, and differentiation and integration of functions of two or more variables. This book is intended as a reference for students taking science and engineering courses at British and Commonwealth Universities.

A Course of Mathematics for Engineers and Scientists offers a mathematics course for undergraduate students reading science and engineering at British and Commonwealth Universities and colleges. The aim of this volume is to generalize and develop the ideas and methods of earlier volumes so that the student can appreciate and use the mathematical methods required in the more advanced parts of physics and engineering. This book begins with elementary ideas of vector algebra which are generalized and developed in two ways. The first is an account of vector analysis and the differential and integral operations and theorems concerning vectors. These ideas find their first generalization in tensor analysis and the transformation of coordinates, including orthogonal curvilinear coordinates. The second development is to matrices, where the properties of arrays of elements, linear equations, and quadratic forms are shown to be the generalizations of elementary algebra and, using'vector space', of familiar geometrical ideas to n dimensions. The solution of differential equations by series provides a general method for the solution of ordinary and some partial differential equations. A discussion of the properties of the solutions in the light of the Sturm-Liouville theory introduces the conceptions of eigenvalues and orthogonal functions, forming a link with matrices. A chapter on the special functions gives some of the better known properties of Bessel, Legendre, Laguerre, and Hermite functions, which commonly occur in the solution of boundary and initial value problems.

New Tertiary Mathematics, Volume 2, Part 2: Further Applied Mathematics deals with various topics of theoretical mechanics and probability, from statics and the dynamics of a rigid body to the dynamics of a particle with one and two degrees of freedom. Many examples of varying difficulty are worked in the text and exercises are added after each major topic is covered. This book is comprised of five chapters and opens with a discussion on statics, with particular reference to the analysis of systems of forces in three dimensions, along with virtual work, stability, and the catenary. Complicated equilibrium problems are considered. The reader is then introduced to the dynamics of a particle in one and two dimensions, as well as the implications of the Galilean transformation and the general theorems of motion for a system of particles. These theorems are applied to simple cases of the motion of a rigid body. The final chapter on probability examines normal and Poisson distributions, Markov chains, and miscellaneous problems. This monograph will be a useful resource for mathematical pupils and students engaged in private study.

I. The topics of this book The concept of a matroid has been known for more than five decades. Whitney (1935) introduced it as a common generalization of graphs and matrices. In the last two decades, it has become clear how important the concept is, for the following reasons: (1) Combinatorics (or discrete mathematics) was considered by many to be a collection of interesting, sometimes deep, but mostly unrelated ideas. However, like other branches of mathematics, combinatorics also encompasses some gen­ eral tools that can be learned and then applied, to various problems. Matroid theory is one of these tools. (2) Within combinatorics, the relative importance of algorithms has in­ creased with the spread of computers. Classical analysis did not even consider problems where'only'a finite number of cases were to be studied. Now such problems are not only considered, but their complexity is often analyzed in con­ siderable detail. Some questions of this type (for example, the determination of when the so called'greedy'algorithm is optimal) cannot even be answered without matroidal tools.

'Whatever regrets may be, we have done our best.'(Sir Ernest Shack­ 0 leton, turning back on 9 January 1909 at 88 23'South.) Brahms struggled for 20 years to write his first symphony. Compared to this, the 10 years we have been working on these two volumes may even appear short. This second volume treats stiff differential equations and differential algebraic equations. It contains three chapters: Chapter IV on one-step (Runge-Kutta) meth­ ods for stiff problems, Chapter V on multistep methods for stiff problems, and Chapter VI on singular perturbation and differential-algebraic equations. Each chapter is divided into sections. Usually the first sections of a chapter are of an introductory nature, explain numerical phenomena and exhibit numerical results. Investigations of a more theoretical nature are presented in the later sections of each chapter. As in Volume I, the formulas, theorems, tables and figures are numbered con­ secutively in each section and indicate, in addition, the section number. In cross references to other chapters the (latin) chapter number is put first. References to the bibliography are again by'author'plus'year'in parentheses. The bibliography again contains only those papers which are discussed in the text and is in no way meant to be complete.

Computational geometry emerged from the field of algorithms design and anal­ ysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The suc­ cess of the field as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains--computer graphics, geographic in­ formation systems (GIS), robotics, and others-in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or difficult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simplified many of the previous approaches. In this textbook we have tried to make these modem algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can also be used for self-study.

Includes index.

A clear, practical and self-contained presentation of the methods of asymptotics and perturbation theory for obtaining approximate analytical solutions to differential and difference equations. Aimed at teaching the most useful insights in approaching new problems, the text avoids special methods and tricks that only work for particular problems. Intended for graduates and advanced undergraduates, it assumes only a limited familiarity with differential equations and complex variables. The presentation begins with a review of differential and difference equations, then develops local asymptotic methods for such equations, and explains perturbation and summation theory before concluding with an exposition of global asymptotic methods. Emphasizing applications, the discussion stresses care rather than rigor and relies on many well-chosen examples to teach readers how an applied mathematician tackles problems. There are 190 computer-generated plots and tables comparing approximate and exact solutions, over 600 problems of varying levels of difficulty, and an appendix summarizing the properties of special functions.

The scope ofthis book is to discuss recent numerical and algorithmic tools for the solution of certain flow problems arising in Computational Fluid Dynam­ ics (CFD). Here, we mainly restrict ourselves to the case ofthe incompressible Navier-Stokes equations, Ut - v~u + U. V'u+ V'p = f, V'·u = o. (1) These basic equations already play an important role in CFD, both for math­ ematicians as well as for more practical scientists: Physically important facts with'real life'character can be described by them, including also economical aspects in industrial applications. On the other hand, the equations in (1) provide the complete spectrum of numerical problems nowadays concerning the mathematical treatment of partial differential equations. Although this field of research may appear to be a small part only inside of CFD, it was and still is of great interest for mathematicians as well as engineers, physicists, computer scientists and many more: a fact which can be easily checked by counting the numerous publications. Nevertheless, our contribution has some unique characteristics since it contains a few ofthe lat­ est results for the numerical solution of (complex) flow problems on modern computer platforms. In this book, our particular emphasis lies on the solu­ tion process ofthe resulting high dimensional discrete systems ofequations which is often neglected in other works. Together with the included CDROM, which contains the'FEATFLOW 1.

This is the first volume of a set of two devoted to the operator approach to linear problems in hydrodynamics. It presents functional analytical methods applied to the study of small movements and normal oscillations of hydromechanical systems having cavities filled with either ideal or viscous fluids. The work is a sequel to and at the same time substantially extends the volume'Operator Methods in Linear Hydrodynamics: Evolution and Spectral Problems'by N.D. Kopachevsky, S.G. Krein and Ngo Zuy Kan, published in 1989 by Nauka in Moscow. It includes several new problems on the oscillations of partially dissipative hydrosystems and the oscillations of visco-elastic or relaxing fluids. The work relies on the authors'and their students'works of the last 30-40 years. The readers are not supposed to be familiar with the methods of functional analysis. In the first part of the present volume, the main facts of linear operator theory relevant to linearized problems of hydrodynamics are summarized, including elements of the theories of distributions, self-adjoint operators in Hilbert spaces and in spaces with an indefinite metric, evolution equations and asymptotic methods for their solutions, the spectral theory of operator pencils. The book is particularly useful for researchers, engineers and students in fluid mechanics and mathematics interested in operator theoretical methods for the analysis of hydrodynamical problems.

This book is derived from notes used in teaching a first-year graduate-level course in elasticity in the Department of Mechanical Engineering at the University of Pittsburgh. This is a modern treatment of the linearized theory of elasticity, which is presented as a specialization of the general theory of continuum mechanics. It includes a comprehensive introduction to tensor analysis, a rigorous development of the governing field equations with an emphasis on recognizing the assumptions and approximations in­ herent in the linearized theory, specification of boundary conditions, and a survey of solution methods for important classes of problems. Two- and three-dimensional problems, torsion of noncircular cylinders, variational methods, and complex variable methods are covered. This book is intended as the text for a first-year graduate course in me­ chanical or civil engineering. Sufficient depth is provided such that the text can be used without a prerequisite course in continuum mechanics, and the material is presented in such a way as to prepare students for subsequent courses in nonlinear elasticity, inelasticity, and fracture mechanics. Alter­ natively, for a course that is preceded by a course in continuum mechanics, there is enough additional content for a full semester of linearized elasticity.

This book is carefully designed to be used on a wide range of introductory courses at first degree and HND level in the U.K., with content matched to a variety of first year degree modules from IEng and other BSc Engineering and Technology courses. Lecturers will find the breadth of material covered gears the book towards a flexible style of use, which can be tailored to their syllabus, and used along side the other IIE Core Textbooks to bring first year students up to speed on the mathematics they require for their engineering degree.•Features real-world examples, case studies, assignments and knowledge-check questions throughout•Introduces key mathematical methods in practical engineering contexts •Bridges the gap between theory and practice

Mathematics is playing an ever more important role in the physical and biological sciences, provoking a blurring of boundaries between scientific disciplines and a resurgence of interest in the modern as well as the classical techniques of applied mathematics. This renewal of interest, both in - search and teaching, has led to the establishment of the series Texts in Applied Mathematics (TAM). The development of new courses is a natural consequence of a high level of excitement on the research frontier as newer techniques, such as numerical and symbolic computer systems, dynamical systems, and chaos, mix with and reinforce the traditional methods of applied mathematics. Thus, the purpose of this textbook series is to meet the current and future needs of these advances and to encourage the teaching of new courses. TAM will publish textbooks suitable for use in advanced undergraduate and beginning graduate courses, and will complement the Applied Mathematical Sciences (AMS) series, whichwill focus on advanced textbooks and research-level monographs.

The book is a collection of contributions concerning the theories, applications and perspectives of Variable Structure Systems (VSS). Variable Structure Systems have been a major control design methodology for many decades. The term Variable Structure Systems was introduced in the late 1950's, and the fundamental concepts were developed for its main branch Sliding Mode Control by Russian researchers Emelyanov and Utkin. The 20th Century has seen the formation and consolidation of VSS theory and its applications. It has also seen an emerging trend of cross-fertilization and integration of VSS with other control and non-control techniques such as feedback linearization,?atness, passivity based control, adaptive and learning? control, system identi?cation, pulse width modulation, H geometric and algebraic methods, arti?cial intelligence, modeling and optimization, neural networks, fuzzy logic, to name just a few. This trend will continue and?ourish in the new millennium. To re?ect these major developments in the 20th Century, this book - cludes 16 specially invited contributions from well-known experts in VSS theory and applications, covering a wide range of topics. The?rst chapter, “First Stage of VSS: People and Events” written by Vadim Utkin, the founder of VSS, oversees and documents the historical developments of VSS in the 20th Century, including many interesting events not known to the West until now. The second chapter, “An Integrated Learning Variable Structure Control Method” written by Jian-Xin Xu, addresses an important issue regarding control integration between variable structure control and learning control.

Partial differential equations are fundamental to the modeling of natural phenomena, arising in every field of science. Consequently, the desire to understand the solutions of these equations has always had a prominent place in the efforts of mathematicians; it has inspired such diverse fields as complex function theory, functional analysis and algebraic topology. Like algebra, topology, and rational mechanics, partial differential equations are a core area of mathematics. This book aims to provide the background necessary to initiate work on a Ph.D. thesis in PDEs for beginning graduate students. Prerequisites include a truly advanced calculus course and basic complex variables. Lebesgue integration is needed only in Chapter 10, and the necessary tools from functional analysis are developed within the course. The book can be used to teach a variety of different courses. This new edition features new problems throughout and the problems have been rearranged in each section from simplest to most difficult. New examples have also been added. The material on Sobolev spaces has been rearranged and expanded. A new section on nonlinear variational problems with'Young-measure'solutions appears. The reference section has also been expanded.

The origins of the finite element method can be traced back to the 1950s when engineers started to solve numerically structural mechanics problems in aeronautics. Since then, the field of applications has widened steadily and nowadays encompasses nonlinear solid mechanics, fluid/structure interactions, flows in industrial or geophysical settings, multicomponent reactive turbulent flows, mass transfer in porous media, viscoelastic flows in medical sciences, electromagnetism, wave scattering problems, and option pricing (to cite a few examples). Numerous commercial and academic codes based on the finite element method have been developed over the years. The method has been so successful to solve Partial Differential Equations (PDEs) that the term'Finite Element Method'nowadays refers not only to the mere interpolation technique it is, but also to a fuzzy set of PDEs and approximation techniques. The efficiency of the finite element method relies on two distinct ingredi­ ents: the interpolation capability of finite elements (referred to as the approx­ imability property in this book) and the ability of the user to approximate his model (mostly a set of PDEs) in a proper mathematical setting (thus guar­ anteeing continuity, stability, and consistency properties). Experience shows that failure to produce an approximate solution with an acceptable accuracy is almost invariably linked to departure from the mathematical foundations. Typical examples include non-physical oscillations, spurious modes, and lock­ ing effects. In most cases, a remedy can be designed if the mathematical framework is properly set up.

We could start writing this book by saying, with several other authors, that the brain is the most powerful and complex information processing device known, whether naturally developed or created artificially. Although we fully agree with this statement, in doing so we would be misleading the reader, in the sense that the present book basically aims to formalize the knowledge concerning brain physiology accumulated over the past few decades. Instead of merely describing the complexity of the cerebral str- ture or presenting a collection of commentaries and reviews of interesting experimental results, we take into account novel achievements in quantum information and quantum computation, and avail ourselves of recently - veloped mathematical tools. Neuroscience was bom in the 19'~ century with the works of Paul Brocca. However, this fledgling field experienced a boom only in recent times, following the development of powerful non-invasive techniques for probing the neural circuitry supporting the complex cognitive functions of the human brain. Although sophisticated mathematical models and phy- cal theories are the basic tools behind the conceptual foundations and a- lytical implementation of these modem techniques, to the best of our knowledge no effort was made to formalize the actual knowledge about brain function into a coherent theoretical framework incorporating the - cent developments in mathematical and physical science. Addressing this lack was our first motivation in writing this book.

Petri nets do not designate a single modeling formalism. In fact, newcomers to the field confess sometimes to be a little puzzled by the diversity of formalisms that are recognized under this'umbrella'. Disregarding some extensions to the theoretical modeling capabilities, and looking at the level of abstraction of the formalisms, Condition/Event, Elementary, Place/Transition, Predicate/Transition, Colored, Object Oriented... net systems are frequently encountered in the literature. On the other side, provided with appropriate interpretative extensions, Controled Net Systems, Marking Diagrams (the Petri net generalization of State Diagrams), or the many-many variants in which time can be explicitly incorporated -Time(d), Deterministic, (Generalized) Stochastic, Fuzzy...- are defined. This represents another way to define practical formalisms that can be obtained by the'cro- product'of the two mentioned dimensions. Thus Petri nets constitute a modeling paradigm, understandable in a broad sense as'the total pattern of perceiving, conceptualising, acting, validating and valuing associated with a particular image of reality that prevails in a science or a branch of science'(Thomas S. Kuhn).

Leading-edge research groups in the field of scientific computing present their outstanding projects using the High Performance Computer in Bavaria (HLRB), Hitachi SR8000-F1, one of the top-level supercomputers for academic research in Germany. The projects address modelling and simulation in the disciplines Biosciences, Chemistry, Chemical Physics, Solid-State Physics, High-Energy Physics, Astrophysics, Geophysics, Computational Fluid Dynamics, and Computer Science. The authors describe their scientific background, their resource requirements with respect to top-level supercomputers, and their methods for efficient utilization of the costly high-performance computing power. Contributions of interdisciplinary research projects that have been supported by the Competence Network for Scientific High Performance Computing in Bavaria (KONWIHR) complete the broad range of supercomputer research and applications covered by this volume.

The finite difference method (FDM) hasbeen used tosolve differential equation systems for centuries. The FDM works well for problems of simple geometry and was widely used before the invention of the much more efficient, robust finite element method (FEM). FEM is now widely used in handling problems with complex geometry. Currently, we are using and developing even more powerful numerical techniques aiming to obtain more accurate approximate solutions in a more convenient manner for even more complex systems. The meshfree or meshless method is one such phenomenal development in the past decade, and is the subject of this book. There are many MFree methods proposed so far for different applications. Currently, three monographs on MFree methods have been published. Mesh Free Methods, Moving Beyond the Finite Element Method d by GR Liu (2002) provides a systematic discussion on basic theories, fundamentals for MFree methods, especially on MFree weak-form methods. It provides a comprehensive record of well-known MFree methods and the wide coverage of applications of MFree methods to problems of solids mechanics (solids, beams, plates, shells, etc.) as well as fluid mechanics. The Meshless Local Petrov-Galerkin (MLPG) Method d by Atluri and Shen (2002) provides detailed discussions of the meshfree local Petrov-Galerkin (MLPG) method and itsvariations. Formulations and applications of MLPG are well addressed in their book.

Since its original publication in 1969, Mathematics for Engineers and Scientists has built a solid foundation in mathematics for legions of undergraduate science and engineering students. It continues to do so, but as the influence of computers has grown and syllabi have evolved, once again the time has come for a new edition.Thoroughly rev

Inverse scattering theory has been a particularly active and successful field in applied mathematics and engineering for the past twenty years. The increasing demands of imaging and target identification require new powerful and flexible techniques besides the existing weak scattering approximation or nonlinear optimization methods. One class of such methods comes under the general description of qualitative methods in inverse scattering theory. This textbook is an easily-accessible'class-tested'introduction to the field. It is accessible also to readers who are not professional mathematicians, thus making these new mathematical ideas in inverse scattering theory available to the wider scientific and engineering community.

The series of Online World Conferences on Soft Computing (WSC) is organized by the World Federation of Soft Computing (WFSC) and has become an established annual event in the academic calendar and was already held for the 8th time in 2003. Starting as a small workshop held at Nagoya University, Japan in 1994 it has - tured to the premier online event on soft computing in industrial applications. It has been hosted by the universities of Granada, Spain, Fraunhofer Gesellschaft, Berlin, Cran?eld University, Helsinki University of Technology and Nagoya University. The goal of WFSC is to promote soft computing across the world, by using the internet as a forum for virtual technical discussion and publishing at no cost to authors and participants. The of?cial journal of the World Federation on Soft Computing is the journal Applied Soft Computing. The 8th WSC Conference (WSC8) took place from September 29th to October 10th, 2003. Registered participants had the opportunity to follow and discuss the online presentations of authors from all over the world. Out of more than 60 subm- sions the program committee had accepted 27 papers for?nal presentation at WSC8.

Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization. Stochastic Linear Programming: Models, Theory, and Computation is a definitive presentation and discussion of the theoretical properties of the models, the conceptual algorithmic approaches, and the computational issues relating to the implementation of these methods to solve problems that are stochastic in nature. The application area of stochastic programming includes portfolio analysis, financial optimization, energy problems, random yields in manufacturing, risk analysis, etc. In this book, models in financial optimization and risk analysis are discussed as examples, including solution methods and their implementation. Stochastic programming is a fast developing area of optimization and mathematical programming. Numerous papers and conference volumes, and several monographs have been published in the area; however, the Kall and Mayer book will be particularly useful in presenting solution methods including their solid theoretical basis and their computational issues, based in many cases on implementations by the authors. The book is also suitable for advanced courses in stochastic optimization.

Stochastic differential equations (SDEs) are a powerful tool in science, mathematics, economics and finance. This book will help the reader to master the basic theory and learn some applications of SDEs. In particular, the reader will be provided with the backward SDE technique for use in research when considering financial problems in the market, and with the reflecting SDE technique to enable study of optimal stochastic population control problems. These two techniques are powerful and efficient, and can also be applied to research in many other problems in nature, science and elsewhere.

Professor Noubari's recommendation:'Professor Starks book provides an effective entry into the field for engineering students who have little or no prior knowledge of this important subject. Avaibility of collection of computer codes and mfiles in combination with topics of the book, makes the book highly valuable to enhance student learning of the subject matter.'

I think the next century will be the century of complexity. We have already discovered the basic laws that govern matter and understand all the normal situations. We don't know how the laws?t together, and what happens under extreme conditions. But I expect we will?nd a complete uni?ed theory sometime this century. There is no limit to the complexity that we can build using those basic laws. Stephen Hawking, January 2000. We don't know what we are talking about. Many of us believed that string theory was a very dramatic break with our previous notions of quantum theory. But now we learn that string theory, well, is not that much of a break. The state of physics today is like it was when we were mysti?ed by radioactivity. They were missing something absolutely fundamental. We are missing perhaps something as profound as they were back then. Nobel Laureate David Gross, December 2005. This volume is essentially a compilation of papers presented at the Int- national Workshop on Mathematics and Physics of Complex and Nonlinear Systems that was held at Indian Institute of Technology Kanpur, March 14 – 26, 2004 on the theme ChaNoXity: The Nonlinear Dynamics of Nature.

This book constitutes the refereed proceedings of the 9th Dortmund Fuzzy Days, held in Dortmund, Germany, 2006. The Fuzzy Days conference has established itself as an international forum for the discussion of new results in the field of Computational Intelligence. All the papers had to undergo a thorough review guaranteeing a solid quality of the programme. The papers are devoted to foundational and practical issues in fuzzy systems, neural networks, evolutionary algorithms, and machine learning and thus cover the whole range of computational intelligence.

Over two hundred novel and innovative computer algebra worksheets or'recipes'will enable readers in engineering, physics, and mathematics to easily and rapidly solve and explore most problems they encounter in their mathematical physics studies. While the aim of this text is to illustrate applications, a brief synopsis of the fundamentals for each topic is presented, the topics being organized to correlate with those found in traditional mathematical physics texts. The recipes are presented in the form of stories and anecdotes, a pedagogical approach that makes a mathematically challenging subject easier and more fun to learn. This is a self-contained and standalone text using MAPLE that may be used in the classroom, for self-study, as a reference, or as a text for an online course.

Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today's database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e.

Clustering has been around for many decades and located itself in a uniquepositionasafundamentalconceptualandalgorithmiclandmark of data analysis. Almost since the very inception of fuzzy sets, the role and potential of these information granules in revealing and describing structureindatawasfullyacknowledgedandappreciated.Asamatter of fact, with the rapid growth of volumes of digital information, the role of clustering becomes even more visible and critical. Furthermore given the anticipated human centricity of the majority of artifacts of digitaleraandacontinuousbuildupofmountainsofdata,onebecomes fully cognizant of the growing role and an enormous potential of fuzzy sets and granular computing in the design of intelligent systems. In therecentyearsclusteringhasundergoneasubstantialmetamorphosis. Frombeinganexclusivelydata drivenpursuit,ithastransformeditself into a vehicle whose data centricity has been substantially augmented by the incorporation of domain knowledge thus giving rise to the next generation of knowledge-oriented and collaborative clustering. Interestingly enough, fuzzy clustering exhibits a dominant role in many developments of the technology of fuzzy sets including fuzzy modeling, fuzzy control, data mining, pattern recognition, and image processing. When browsing through numerous papers on fuzzy m- eling we can witness an important trend of a substantial reliance on fuzzy clustering being regarded as the general development tool. The same central position of fuzzy clustering becomes visible in pattern classi?ers and neurofuzzy systems. All in all, it becomes evident that further progress in fuzzy clustering is of vital relevance and bene?t to the overall progress of the area of fuzzy sets and their applications.

This textbook on models and modeling in mechanics introduces a new unifying approach to applied mechanics: through the concept of the open scheme, a step-by-step approach to modeling evolves. The unifying approach enables a very large scope on relatively few pages: the book treats theories of mass points and rigid bodies, continuum models of solids and fluids, as well as traditional engineering mechanics of beams, cables, pipe flow and wave propagation.

This volume presents results of the International Meshing Roundtable conference organized by Sandia National Laboratories held in September 2005. The conference is held annually and since its inception eleven years ago has become widely recognized as a major forum for the exchange of ideas in this field. The papers of this proceedings are devoted to mesh generation and adaptation which has applications to finite element simulation as well as to computational geometry and computer graphics. This book introduces theoretical and novel ideas with practical potential as well as technical applications from industrial researchers, bringing together renowned specialists from engineering, computer science and mathematics.

Approximation methods are vital in many challenging applications of computational science and engineering. This is a collection of papers from world experts in a broad variety of relevant applications, including pattern recognition, machine learning, multiscale modelling of fluid flow, metrology, geometric modelling, tomography, signal and image processing. It documents recent theoretical developments which have lead to new trends in approximation, it gives important computational aspects and multidisciplinary applications, thus making it a perfect fit for graduate students and researchers in science and engineering who wish to understand and develop numerical algorithms for the solution of their specific problems. An important feature of the book is that it brings together modern methods from statistics, mathematical modelling and numerical simulation for the solution of relevant problems, with a wide range of inherent scales. Contributions of industrial mathematicians, including representatives from Microsoft and Schlumberger, foster the transfer of the latest approximation methods to real-world applications.

If people do not believe that mathematics is simple, it is only because they do not realize how complicated life is. —John von Neumann While this is a course in analysis, our approach departs from the beaten path in some ways. Firstly, we emphasize a variety of connections to themes from neighboring fields, such as wavelets, fractals and signals; topics typically not included in a gradu­ ate analysis course. This in turn entails excursions into domains with a probabilistic flavor. Yet the diverse parts of the book follow a common underlying thread, and to­ gether they constitute a good blend; each part in the mix naturally complements the other. In fact, there are now good reasons for taking a wider view of analysis, for ex­ ample the fact that several applied trends have come to interact in new and exciting ways with traditional mathematical analysis—as it was taught in graduate classes for generations. One consequence of these impulses from'outside'is that conventional boundaries between core disciplines in mathematics have become more blurred. Fortunately this branching out does not mean that students will need to start out with any different or additional prerequisites. In fact, the ideas involved in this book are intuitive, natural, many of them visual, and geometric. The required background is quite minimal and it does not go beyond what is typically required in most graduate programs.

Prior to the computer era, analytical methods in elasticity had already been developed and - proved up to impressive levels. Relevant mathematical techniques were extensively exploited, contributing signi?cantly to the understanding of physical phenomena. In recent decades, - merical computerized techniques have been re?ned and modernized, and have reached high levels of capabilities, standardization and automation. This trend, accompanied by convenient and high resolution graphical visualization capability, has made analytical methods less attr- tive, and the amount of effort devoted to them has become substantially smaller. Yet, with some tenacity, the tremendous advances in computerized tools have yielded various mature programs for symbolic manipulation. Such tools have revived many abandoned analytical methodologies by easing the tedious effort that was previously required, and by providing additional capab- ities to perform complex derivation processes that were once considered impractical. Generally speaking, it is well recognized that analytical solutions should be applied to re- tively simple problems, while numerical techniques may handle more complex cases. However, it is also agreed that analytical solutions provide better insight and improved understanding of the involved physical phenomena, and enable a clear representation of the role taken by each of the problem parameters. Nowadays, analytical and numerical methods are considered as c- plementary: that is, while analytical methods provide the required understanding,numerical solutions provide accuracy and the capability to deal with cases where the geometry and other characteristics impose relatively complex solutions.

This book presents topics of science and engineering which occur in nature or are part of daily life. It describes phenomena which are modelled by partial differential equations, relating to physical variables like mass, velocity and energy, etc. to their spatial and temporal variations. The author has chosen topics representing his career-long interests, including the flow of fluids and gases, granular flows, biological processes like pattern formation on animal skins, kinetics of rarified gases and semiconductor devices. Each topic is presented in its scientific or engineering context, followed by an introduction of applicable mathematical models in the form of partial differential equations.

Modern aerospace vehicles, such as the space shuttle, other launch vehicles, and long-range ballistic missiles, do not discriminate between atmospheric and space flight. Most texts on flight dynamics, however, make this artificial distinction and therefore do not simultaneously cover aircraft and spacecraft. Bridging this gap in the literature, Atmospheric and Space Flight Dynamics is a unified presentation, demonstrating that the two disciplines have actually evolved from the same set of physical principles. Key features inclue an introduction to a broad range of modern topics in an accessible, yet mathematically rigorous presentation; many numerical examples and simulations utilizing MATLAB® and Simulink®; software used as an instructional, hands-on tool, moving away from the'cookbook'approach found in other works; and numerous illustrations and end-of-chapter exercises. Primarily useful as a textbook for advanced undergraduate and beginning graduate-level students, the work is also an excellent reference or self-study guide for researchers and practitioners in aerospace engineering, aviation, mechanical engineering, dynamics, astrodynamics, aeronautics, and astronautics.

Complex numbers can be viewed in several ways: as an element in a field, as a point in the plane, and as a two-dimensional vector. Examined properly, each perspective provides crucial insight into the interrelations between the complex number system and its parent, the real number system. The authors explore these relationships by adopting both generalization and specialization methods to move from real variables to complex variables, and vice versa, while simultaneously examining their analytic and geometric characteristics. The engaging exposition is replete with discussions, remarks, questions, and exercises, motivating not only understanding on the part of the reader, but also developing the tools needed to think critically about mathematical problems. The material includes numerous examples and applications relevant to engineering students, along with some techniques to evaluate various types of integrals. The book may serve as a text for an undergraduate coursein complex variables. The only prerequisite is a basic knowledge of advanced calculus. The presentation is also ideally suited for self-study.

Computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book presents actual comprehensive study of this field. It contains a collection of over one hundred carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning and classifiers, Image processing and computer vision, Speech and word recognition, Medical applications, Various applications. This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

The monograph is devoted to the systematic presentation of the so called'dressing method'for solving differential equations (both linear and nonlinear) of mathematical physics. The essence of the dressing method consists in a generation of new non-trivial solutions of a given equation from (maybe trivial) solution of the same or related equation. The Moutard and Darboux transformations discovered in XIX century as applied to linear equations, the Bäcklund transformation in differential geometry of surfaces, the factorization method, the Riemann-Hilbert problem in the form proposed by Shabat and Zakharov for soliton equations and its extension in terms of the d-bar formalism comprise the main objects of the book. Throughout the text, a generally sufficient'linear experience'of readers is exploited, with a special attention to the algebraic aspects of the main mathematical constructions and to practical rules of obtaining new solutions. Various linear equations of classical and quantum mechanics are solved by the Darboux and factorization methods. An extension of the classical Darboux transformations to nonlinear equations in 1+1 and 2+1 dimensions, as well as its factorization are discussed in detail. The applicability of the local and non-local Riemann-Hilbert problem-based approach and its generalization in terms of the d-bar method are illustrated on various nonlinear equations.

This book provides an introduction to the theory of dynamical systems with the ® aid of the Mathematica computer algebra system. It is written for both senior undergraduates and graduate students. The?rst part of the book deals with c- tinuous systems using ordinary differential equations (Chapters 1–10), the second part is devoted to the study of discrete dynamical systems (Chapters 11–15), and Chapters 16 and 17 deal with both continuous and discrete systems. It should be pointedoutthatdynamicalsystemstheoryisnotlimitedtothesetopicsbutalso- compassespartialdifferentialequations,integralandintegrodifferentialequations, stochastic systems, and time-delay systems, for instance. References [1]–[4] given at the end of the Preface provide more information for the interested reader. The author has gone for breadth of coverage rather than?ne detail and theorems with proofs are kept at a minimum. The material is not clouded by functional analytic and group theoretical de?nitions, and so is intelligible to readers with a general mathematical background. Some of the topics covered are scarcely covered el- where. Most of the material in Chapters 9, 10, 14, 16, and 17 is at a postgraduate levelandhasbeenin?uencedbytheauthor'sownresearchinterests. Thereismore theory in these chapters than in the rest of the book since it is not easily accessed anywhere else. It has been found that these chapters are especially useful as ref- ence material for senior undergraduate project work. The theory in other chapters of the book is dealt with more comprehensively in other texts, some of which may be found in the references section of the corresponding chapter.

“Fuzzy Control - the revolutionary computer technology that is changing our world” - these and other headlines could be read when in the early 90's news from Japan came over telling us about the success of fuzzy controllers. The idea which was put into practice had been suggested by Lot? A. Zadeh in Berkeley in 1965. It had been developed and tested in some practical - plications, especially in Europe. In Japan fuzzy control was celebrated as a technology re?ecting the Japanese way of thinking by its unsharpness and - plicitoverlappingofseveralstatements. Anewtechnologyboomwaspredicted for Japan which would make Europe lose ground. Consequently, this news created unrest. Research projects were initiated and development departments were engaged to translate fuzzy control into products. Adversaries and supporters hurried up to inform themselves and intensely discussed whether the “conventional” or the fuzzy control were the better alternative. Finally, the excitement cooled down since in recent years fuzzy control was analyzed fromthe classical pointofview. Thus,amoreobjective evaluation of its strong and weak points was possible. Furthermore, it was shown how fuzzy systems could be put to use in the steering level which is the level above the control loop, especially in interaction with other methods of soft computing and arti?cial intelligence. Based on these fundamentals, the aim of this book is to support the convenient use of fuzzy controllers and fuzzy systems in the branch of control engineering and automation systems.

This book examines various mathematical tools—based on generalized collocation methods—to solve nonlinear problems related to partial differential and integro-differential equations. Covered are specific problems and models related to vehicular traffic flow, population dynamics, wave phenomena, heat convection and diffusion, transport phenomena, and pollution. Based on a unified approach combining modeling, mathematical methods, and scientific computation, each chapter begins with several examples and problems solved by computational methods; full details of the solution techniques used are given. The last section of each chapter provides problems and exercises giving readers the opportunity to practice using the mathematical tools already presented. Rounding out the work is an appendix consisting of scientific programs in which readers may find practical guidelines for the efficient application of the collocation methods used in the book. Although the authors make use of Mathematica®, readers may use other packages such as MATLAB® or MapleTM depending on their specific needs and software preferences. Generalized Collocation Methods is written for an interdisciplinary audience of graduate students, engineers, scientists, and applied mathematicians with an interest in modeling real-world systems by differential or operator equations. The work may be used as a supplementary textbook in graduate courses on modeling and nonlinear differential equations, or as a self-study handbook for researchers and practitioners wishing to expand their knowledge of practical solution techniques for nonlinear problems.

Geometric Fundamentals of Robotics provides an elegant introduction to the geometric concepts that are important to applications in robotics. This second edition is still unique in providing a deep understanding of the subject: rather than focusing on computational results in kinematics and robotics, it includes significant state-of-the-art material that reflects important advances in the field, connecting robotics back to mathematical fundamentals in group theory and geometry. Geometric Fundamentals of Robotics serves a wide audience of graduate students as well as researchers in a variety of areas, notably mechanical engineering, computer science, and applied mathematics. It is also an invaluable reference text.

The Handbook of Mathematics for Engineers and Scientists covers the main fields of mathematics and focuses on the methods used for obtaining solutions of various classes of mathematical equations that underlie the mathematical modeling of numerous phenomena and processes in science and technology. To accommodate different mathematical backgr

Hybrid Artificial Intelligence Systems (HAIS) combines symbolic and sub-symbolic techniques to construct more robust and reliable problem solving models. This volume focused on'Hybrid Artificial Intelligence Systems'contains a collection of papers that were presented at the 2nd International Workshop on Hybrid Artificial Intelligence Systems, held in 12 - 13 November, 2007, Salamanca, Spain. This carefully edited book provides a comprehensive overview of the recent advances in the hybrid intelligent systems and covers a wide range of application areas, including data analysis and data mining, intelligent control, pattern recognition, robotics, optimization, etc. The book is aimed at researchers, practitioners and postgraduate students who are engaged in developing and applying advanced intelligent systems principles to solving real-world problems.