Data fusion or information fusion are names which have been primarily assigned to military-oriented problems. In military applications, typical data fusion problems are: multisensor, multitarget detection, object identification, tracking, threat assessment, mission assessment and mission planning, among many others. However, it is clear that the basic underlying concepts underlying such fusion procedures can often be used in nonmilitary applications as well. The purpose of this book is twofold: First, to point out present gaps in the way data fusion problems are conceptually treated. Second, to address this issue by exhibiting mathematical tools which treat combination of evidence in the presence of uncertainty in a more systematic and comprehensive way. These techniques are based essentially on two novel ideas relating to probability theory: the newly developed fields of random set theory and conditional and relational event algebra. This volume is intended to be both an update on research progress on data fusion and an introduction to potentially powerful new techniques: fuzzy logic, random set theory, and conditional and relational event algebra. Audience: This volume can be used as a reference book for researchers and practitioners in data fusion or expert systems theory, or for graduate students as text for a research seminar or graduate level course.

This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.

This book is an introduction to the theory of linear one-dimensional singular integral equations. It is essentually a graduate textbook. Singular integral equations have attracted more and more attention, because, on one hand, this class of equations appears in many applications and, on the other, it is one of a few classes of equations which can be solved in explicit form. In this book material of the monograph [2] of the authors on one-dimensional singular integral operators is widely used. This monograph appeared in 1973 in Russian and later in German translation [3]. In the final text version the authors included many addenda and changes which have in essence changed character, structure and contents of the book and have, in our opinion, made it more suitable for a wider range of readers. Only the case of singular integral operators with continuous coefficients on a closed contour is considered herein. The case of discontinuous coefficients and more general contours will be considered in the second volume. We are grateful to the editor Professor G. Heinig of the volume and to the translators Dr. B. Luderer and Dr. S. Roch, and to G. Lillack, who did the typing of the manuscript, for the work they have done on this volume.

Looking back at the years that have passed since the realization of the very first electronic, multi-purpose computers, one observes a tremendous growth in hardware and software performance. Today, researchers and engi neers have access to computing power and software that can solve numerical problems which are not fully understood in terms of existing mathemati cal theory. Thus, computational sciences must in many respects be viewed as experimental disciplines. As a consequence, there is a demand for high quality, flexible software that allows, and even encourages, experimentation with alternative numerical strategies and mathematical models. Extensibil ity is then a key issue; the software must provide an efficient environment for incorporation of new methods and models that will be required in fu ture problem scenarios. The development of such kind of flexible software is a challenging and expensive task. One way to achieve these goals is to in vest much work in the design and implementation of generic software tools which can be used in a wide range of application fields. In order to provide a forum where researchers could present and discuss their contributions to the described development, an International Work shop on Modern Software Tools for Scientific Computing was arranged in Oslo, Norway, September 16-18, 1996. This workshop, informally referred to as Sci Tools '96, was a collaboration between SINTEF Applied Mathe matics and the Departments of Informatics and Mathematics at the Uni versity of Oslo."

This book is based on the author's experience with calculations involving polynomial splines. It presents those parts of the theory which are especially useful in calculations and stresses the representation of splines as linear combinations of B-splines. After two chapters summarizing polynomial approximation, a rigorous discussion of elementary spline theory is given involving linear, cubic and parabolic splines. The computational handling of piecewise polynomial functions (of one variable) of arbitrary order is the subject of chapters VII and VIII, while chapters IX, X, and XI are devoted to B-splines. The distances from splines with fixed and with variable knots is discussed in chapter XII. The remaining five chapters concern specific approximation methods, interpolation, smoothing and least-squares approximation, the solution of an ordinary differential equation by collocation, curve fitting, and surface fitting. The present text version differs from the original in several respects. The book is now typeset (in plain TeX), the Fortran programs now make use of Fortran 77 features. The figures have been redrawn with the aid of Matlab, various errors have been corrected, and many more formal statements have been provided with proofs. Further, all formal statements and equations have been numbered by the same numbering system, to make it easier to find any particular item. A major change has occured in Chapters IX-XI where the B-spline theory is now developed directly from the recurrence relations without recourse to divided differences. This has brought in knot insertion as a powerful tool for providing simple proofs concerning the shape-preserving properties of the B-spline series.

Recent groundbreaking discoveries in physics, including the discovery of the Higgs Boson and gravitational waves, have relied on chi-squared analysis and model testing, a data analysis method. This is the first book to make chi-squared model testing accessible to students in introductory physics lab courses and others who need to learn this method, such as beginning researchers in astrophysics and particle physics, beginners in data science, and lab students in other experimental sciences. For over a decade, Harvard University's introductory physics lab sequence has made chi-squared model testing its central theme. Written by two faculty members, the book is based on years of experience teaching students learn how to think like scientists by testing their models using chi-squared analysis. By including uncertainties in the curve fitting technique, chi-squared data analysis improves on the centuries old ordinary least squares and linear regression methods and combines best fit parameter estimation and model testing in one method. A toolkit of essential statistical and experimental concepts is developed from the ground up with novel features to interest even those familiar with the material. The presentation of one and two parameter chi-squared model testing, requiring only elementary probability and algebra, is followed by case studies that apply the methods to simple introductory physics lab experiments. More challenging topics requiring calculus are addressed in an advanced topic chapter. This self-contained and student-friendly introduction includes a glossary, end of chapter problems with complete solutions, and software scripts available in several popular programming languages that the reader can use for chi-squared model testing.

Floating-point arithmetic is the most widely used way of implementing real-number arithmetic on modern computers. However, making such an arithmetic reliable and portable, yet fast, is a very difficult task. As a result, floating-point arithmetic is far from being exploited to its full potential. This handbook aims to provide a complete overview of modern floating-point arithmetic. So that the techniques presented can be put directly into practice in actual coding or design, they are illustrated, whenever possible, by a corresponding program. The handbook is designed for programmers of numerical applications, compiler designers, programmers of floating-point algorithms, designers of arithmetic operators, and more generally, students and researchers in numerical analysis who wish to better understand a tool used in their daily work and research.

The point of departure in the present book is that the decision-makers involved in the evaluation of alternatives under conflicting criteria express their preferential judgement by estimating ratios of subjective values or differences of the corresponding logarithms, the so-called grades. Three MCDA methods are studied in detail; the Simple Multi-Attribute Rating Technique SMART, and the Additive and the Multiplicative AHP, both pairwise-comparison methods which do not suffer from the well-known shortcomings of the original Analytic Hierarchy Process. Context-related preference modeling on the basis of psychophysical research in visual perception and motor skills is extensively discussed in the introductory chapters. Thereafter many extensions of the ideas are presented via case studies in university administration, health care, environmental assessment, budget allocation, and energy planning at the national and the European level. The issues under consideration are: group decision-making with inhomogeneous power distributions, the search for a compromise solution, resource allocation and fair distribution, scenario analysis in long-term planning, conflict analysis via the pairwise comparison of concessions and multi-objective optimization. The final chapters are devoted to the fortunes of MCDA in the hands of its designers. Audience: The book presents methods for decision support and their applications in the fields of university administration, health care, environmental assessment, budget allocation, and strategic energy planning and will be of value to practitioners, students and researchers in these and related fields.

This book starts with the basic concepts of fuzzy sets and progresses througha normative view on possibility distributions and OWA operators in multiple criteria decisions.

Five applications (that all build on experience from solving complex real world problems)of possibility distributions to strategic decisions about closing/not closinga production plant using fuzzy real options, portfolio selection with imprecise future data, predictive probabilities and possibilities for risk assessment in grid computing, fuzzy ontologies for process industry, and design (and implementation) of mobile value servicesare presented and carefully discussed. It can be useful for researchers and students workingin soft computing, real options, fuzzy decision making, grid computing, knowledge mobilization andmobile value services."

The book "Soft Computing Based Modeling in Intelligent Systems"contains the - tended works originally presented at the IEEE International Workshop SOFA 2005 and additional papers. SOFA, an acronym for SOFt computing and Applications, is an international wo- shop intended to advance the theory and applications of intelligent systems and soft computing. Lotfi Zadeh, the inventor of fuzzy logic, has suggested the term "Soft Computing." He created the Berkeley Initiative of Soft Computing (BISC) to connect researchers working in these new areas of AI. Professor Zadeh participated actively in our wo- shop. Soft Computing techniques are tolerant to imprecision, uncertainty and partial truth. Due to the large variety and complexity of the domain, the constituting methods of Soft Computing are not competing for a comprehensive ultimate solution. Instead they are complementing each other, for dedicated solutions adapted to each specific pr- lem. Hundreds of concrete applications are already available in many domains. Model based approaches offer a very challenging way to integrate a priori knowledge into procedures. Due to their flexibility, robustness, and easy interpretability, the soft c- puting applications will continue to have an exceptional role in our technologies. The applications of Soft Computing techniques in emerging research areas show its mat- ity and usefulness. The IEEE International Workshop SOFA 2005 held Szeged-Hungary and Arad- Romania in 2005 has led to the publication of these two edited volumes. This volume contains Soft Computing methods and applications in modeling, optimisation and prediction.

Using examples from finance and modern warfare to the flocking of birds and the swarming of bacteria, the collected research in this volume demonstrates the common methodological approaches and tools for modeling and simulating collective behavior.

Thetopics presented point toward new and challenging frontiers of applied mathematics, making the volume a useful referencetext forapplied mathematicians, physicists, biologists, and economists involved in the modeling of socio-economic systems."

Heavy metals always pose serious ecological risks when released into the environment due to their elemental non-degradable nature, regardless of their chemical form. This calls for the development of efficient and low-cost effluent treatment and metal recuperation technologies for contaminated waste water, not only because regulatory limits need to be met but also because the waste itself can be a resource for certain precious metals.

Biosorption is a general property of living and dead biomass to rapidly bind and abiotically concentrate inorganic or organic compounds from even very diluted aqueous solutions. As a specific term, biosorption is a method that utilizes materials of biological origin - biosorbents formulated from non-living biomass - for the removal of target substances from aqueous solutions. Recent research on biosorption provides a solid understanding of the mechanism underlying microbial biosorption of heavy metals and related elements.

This book gathers review articles analyzing current views on the mechanism and (bio)chemistry of biosorption, the performance of bacterial, fungal and algal biomass, and the practical aspects of biosorbent preparation and engineering. It also reviews the physico-chemical evaluations of biosorbents and modelling of the process as well as the importance of biosorption during heavy metal removal using living cells. It is a reference work for scientists, environmental safety engineers and R&D specialists who wish to further promote biosorption research and use the accumulated knowledge to develop and build industrial applications of biosorption in heavy metal separation technologies.

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The fields of image analysis, computer vision, and artificial intelligence all make use of descriptions of shape in grey-level images. Most existing algorithms for the automatic recognition and classification of particular shapes have been devel oped for specific purposes, with the result that these methods are often restricted in their application. The use of advanced and theoretically well-founded math ematical methods should lead to the construction of robust shape descriptors having more general application. Shape description can be regarded as a meeting point of vision research, mathematics, computing science, and the application fields of image analy sis, computer vision, and artificial intelligence. The NATO Advanced Research Workshop "Shape in Picture" was organised with a twofold objective: first, it should provide all participants with an overview of relevant developments in these different disciplines; second, it should stimulate researchers to exchange original results and ideas across the boundaries of these disciplines. This book comprises a widely drawn selection of papers presented at the workshop, and many contributions have been revised to reflect further progress in the field. The focus of this collection is on mathematical approaches to the construction of shape descriptions from grey-level images. The book is divided into five parts, each devoted to a different discipline. Each part contains papers that have tutorial sections; these are intended to assist the reader in becoming acquainted with the variety of approaches to the problem."

In the last two decades semiconductor device simulation has become a research area, which thrives on a cooperation of physicists, electrical engineers and mathe maticians. In this book the static semiconductor device problem is presented and analysed from an applied mathematician's point of view. I shall derive the device equations - as obtained for the first time by Van Roosbroeck in 1950 - from physical principles, present a mathematical analysis, discuss their numerical solu tion by discretisation techniques and report on selected device simulation runs. To me personally the most fascinating aspect of mathematical device analysis is that an interplay of abstract mathematics, perturbation theory, numerical analysis and device physics is prompting the design and development of new technology. I very much hope to convey to the reader the importance of applied mathematics for technological progress. Each chapter of this book is designed to be as selfcontained as possible, however, the mathematical analysis of the device problem requires tools which cannot be presented completely here. Those readers who are not interested in the mathemati cal methodology and rigor can extract the desired information by simply ignoring details and proofs of theorems. Also, at the beginning of each chapter I refer to textbooks which introduce the interested reader to the required mathematical concepts."

This book is about the pattern formation and the evolution of crack propagation in engineering materials and structures, bridging mathematical analyses of cracks based on singular integral equations, to computational simulation of engineering design. The first two parts of this book focus on elasticity and fracture and provide the basis for discussions on fracture morphology and its numerical simulation, which may lead to a simulation-based fracture control in engineering structures. Several design concepts are discussed for the prevention of fatigue and fracture in engineering structures, including safe-life design, fail-safe design, damage tolerant design.

After starting with basic elasticity and fracture theories in parts one and two, this book focuses on the fracture morphology that develops due to the propagation of brittle cracks or fatigue cracks.

In part three, the mathematical analysis of a curved crack is precisely described, based on the perturbation method. The stability theory of interactive cracks propagating in brittle solids may help readers to understand the formation of a fractal-like cracking patterns in brittle solids, while the stability theory of crack paths helps to identify the straight versus sharply curved or sometimes wavy crack paths observed in brittle solids.

In part four, the numerical simulation method of a system of multiple cracks is introduced by means of the finite element method, which may be used for the better implementation of fracture control in engineering structures.

This book is part of a series on Mathematics for Industry and will appeal to structural engineers seeking to understand the basic backgrounds of analyses, but also to mathematicians with an interest in how such mathematical solutions are evaluated in industrial applications."

The tremendous progress in astronomical observations over the past sixty years has revealed a vast structured universe whose fundamental parti cles are galaxies, and clusters thereof. The interpretation of the new astronomical evidence owes much to Einstein's insights and deductions. All our knowledge of the world derives from the light, more generally the energy, which reaches us from near and far. Einstein recognised the vital role of energy as the solE basis of our information about the workings of nature; his Special Theory of Relativity showed how our understanding of space and time Is linked with measurements involving reflecting light signals. He further demonstrated that matter exists in two interchangeable forms - a mass form and an energy form - which interact closely at all levels. His General Theory of Relativity dealt with the nature of this interaction in the context of gravitational fields, and led to a view of the universe which was soon observationally confirmed. Einstein's methods and results form the theoretical basis of modern cosmology which has spawned many 'models' of the universe; how ever, they all deal with an Einstein-type universe and they all employ his geometric approach to describe it."

This book covers algorithms and discretization procedures for the solution of nonlinear progamming, semi-infinite optimization and optimal control problems. Among the important features included are the theory of algorithms represented as point-to-set maps, the treatment of min-max problems with and without constraints, the theory of consistent approximation which provides a framework for the solution of semi-infinite optimization, optimal control, and shape optimization problems with very general constraints, using simple algorithms that call standard nonlinear programming algorithms as subroutines, the completeness with which algorithms are analysed, and chapter 5 containing mathematical results needed in optimization from a large assortment of sources. Readers will find of particular interest the exhaustive modern treatment of optimality conditions and algorithms for min-max problems, as well as the newly developed theory of consistent approximations and the treatment of semi-infinite optimization and optimal control problems in this framework. This book presents the first treatment of optimization algorithms for optimal control problems with state-trajectory and control constraints, and fully accounts for all the approximations that one must make in their solution.It is also the first to make use of the concepts of epi-convergence and optimality functions in the construction of consistent approximations to infinite dimensional problems.

Both modern mathematical music theory and computer science are strongly influenced by the theory of categories and functors. One outcome of this research is the data format of denotators, which is based on set-valued presheaves over the category of modules and diaffine homomorphisms. The functorial approach of denotators deals with generalized points in the form of arrows and allows the construction of a universal concept architecture. This architecture is ideal for handling all aspects of music, especially for the analysis and composition of highly abstract musical works.

This book presents an introduction to the theory of module categories and the theory of denotators, as well as the design of a software system, called Rubato Composer, which is an implementation of the category-theoretic concept framework. The application is written in portable Java and relies on plug-in components, so-called rubettes, which may be combined in data flow networks for the generation and manipulation of denotators.

The Rubato Composer system is open to arbitrary extension and is freely available under the GPL license. It allows the developer to build specialized rubettes for tasks that are of interest to composers, who in turn combine them to create music. It equally serves music theorists, who use them to extract information from and manipulate musical structures. They may even develop new theories by experimenting with the many parameters that are at their disposal thanks to the increased flexibility of the functorial concept architecture.

Two contributed chapters by Guerino Mazzola and Florian Thalmann illustrate the application of the theory as well as the software in the development of compositional tools and the creation of a musical work with the help of the Rubato framework.

Presenting techniques, case-studies and methodologies that combine the use of simulation approaches with optimization techniques for facing problems in manufacturing, logistics, or aeronautical problems, this book provides solutions to common industrial problems in several fields, which range from manufacturing to aviation problems, where the common denominator is the combination of simulation's flexibility with optimization techniques' robustness. Providing readers with a comprehensive guide to tackle similar issues in industrial environments, this text explores novel ways to face industrial problems through hybrid approaches (simulation-optimization) that benefit from the advantages of both paradigms, in order to give solutions to important problems in service industry, production processes, or supply chains, such as scheduling, routing problems and resource allocations, among others.

This volume consists of twenty-four papers selected by the editors from the sixty-one papers presented at the 1st International Conference on Mathemati cal Methods in Reliability held at the Politehnica University of Bucharest from 16 to 19 September 1997. The papers have been divided into three sections: statistical methods, probabilistic methods, and special techniques and appli cations. Of course, as with any classification, some papers could be as well assigned to other sections. Problems in reliability are encountered in items in everyday usage. Relia bility is an important feature of household appliances, cars, telephones, power supplies, and so on, whether viewed from the vantage of the producer or the consumer. Important decisions are based on the reliability of the product. Obtaining systems that perform adequately for a specified period of time in a given environment is an important goal for both government and industry. Hence study and use of reliability theory, which can be applied in the research, development, and production phases of a system to enable the user to evaluate and improve performance, is a worthwhile venture. If reliability theory is to be useful, it must be quantitative in nature, because reliability must be demonstra ble. Subsequently probability and statistics, among others, play an important part in its development."

Presents a discrete in time-space universal map of relative dynamics that is used to unfold an extensive catalogue of dynamic events not previously discussed in mathematical or social science literature. With emphasis on the chaotic dynamics that may ensue, the book describes the evolution on the basis of temporal and locational advantages. It explains nonlinear discrete time dynamic maps primarily through numerical simulations. These very rich qualitative dynamics are linked to evolution processes in socio-spatial systems. Important features include: The analytical properties of the one-stock, two- and three-location map; the numerical results from the one- and two-stock, two- and three-location dynamics; and the demonstration of the map's potential applicability in the social sciences through simulating population dynamics of the U.S. Regions over a two-century period. In addition, this book includes new findings: the Hopf equivalent discrete time dynamics bifurcation; the Feigenbaum slope-sequences; the presence of strange local attractors and containers; switching of extreme states; the presence of different types of turbulence; local and global turbulence. Intended for researchers and advanced graduate students in applied mathematics and an interest in dynamics and chaos. Mathematical social scientists in many other fields will also find this book useful.

One of the most exciting predictions of Einstein's theory of gravitationisthat there may exist 'black holes': putative objects whose gravitational fields are so strong that no physical bodies and signals can break free of their pull and escape. Even though a completely reliable discovery of a black hole has not yet been made, several objects among those scrutinized by astrophysicists will very likely be conformed as black holes. The proof that they do exist, and an analysis of their properties, would have a significance going far beyond astrophysics. Indeed, what is involved is not just the discovery of yet another, even if extremely remarkable, astrophysical object, but a test of the correctness of our understanding the properties of space and time in extremely strong gravitational fields. Theoretical research into the properties of black holes and into the possible corollaries of the hypothesis that they exist, has been carried out with special vigor since the beginning of the 1970s. In addition to those specific features of black holes that are important for the interpretation of their possible astrophysical manifestations, the theory has revealed a nurober of unexpected characteristics of physical interactions involving black holes. By now, a fairly detailed understanding has been achieved of the properties of the black holes, their possible astrophysical manifestations, and the specifics of the various physical processes involved. Furthermore, profound links were found between black-hole theory and such seemingly very distant fields as thermodynamics, information theory, and quantum theory.

This is the first book on the subject since its introduction more than fifty years ago, and it can be used as a graduate text or as a reference work. It features all of the key results, many very useful tables, and a large number of research problems. The book will be of interest to those interested in one of the most fascinating areas of discrete mathematics, connected to statistics and coding theory, with applications to computer science and cryptography. It will be useful for anyone who is running experiments, whether in a chemistry lab or a manufacturing plant (trying to make those alloys stronger), or in agricultural or medical research. Sam Hedayat is Professor of Statistics and Senior Scholar in the Department of Mathematics, Statistics, and Computer Science, University of Illinois, Chicago. Neil J.A. Sloane is with AT&T Bell Labs (now AT&T Labs). John Stufken is Professor Statistics at Iowa State University.

Over the past decade or so, we have seen a multitude of improvement programmes and projects to improve the safety of patient care in healthcare. However, the full potential of these efforts and especially those that seek to address an entire system has not yet been reached. The current pandemic has made this more evident than ever. We have tended to focus on problems in isolation, one harm at a time, and our efforts have been simplistic and myopic. If we are to save more lives and significantly reduce patient harm, we need to adopt a holistic, systematic approach that extends across cultural, technological, and procedural boundaries. Patient Safety Now is about the fact that it is time to care for everyone impacted by patient safety, how we need to take the time to care for everyone in a meaningful way and how hospitals need to enable staff time to care safely. This book builds on the author's two previous books on patient safety. Rethinking Patient Safety talked about ways in which we need to rethink patient safety in healthcare and describes what we've learned over the last two decades. Implementing Patient Safety talked about what we can do differently and how we can use those lessons learned to improve the way we implement patient safety initiatives and encourage a culture of safety across a healthcare system. Patient Safety Now unites the concepts, theories and ideas of the previous two books with updated material and examples, including what has been learned by patient safety specialists during a pandemic. Patient Safety Now provides the reader with a unique view of patient safety that looks beyond the traditional negative and retrospective approach to one that is proactive and recognizes the impact of conditions, behaviours and cultures that exist in healthcare on everyone. It is written not only for healthcare professionals and patient safety personnel, but for patients and their families who all want the same thing. Too often when things go wrong, relationships quickly become adversarial when in fact this can be avoided by recognizing that, rather than being in separate camps, there are shared needs and goals in relations to patient safety.