الصفحة 2
الصفحة 2
MICAI 2006 : Advances in Artificial Intelligence ; 5th Mexican International Conference on Artificial Intelligence, Apizaco, Mexico, November 13-17, 2006, Proceedings
This volume contains the papers presented during the oral session of the 5 Mexican International Conference on Artificial Intelligence, held on November 13–17, 2006, at the Technologic Institute of Apizaco, Mexico. The conference received for evaluation 448 submissions by 1207 authors from 42 different countries
MICAI 2005 : Advances in Artificial Intelligence ; 4th Mexican International Conference on Artificial Intelligence, Monterrey, Mexico, November 14-18, 2005, Proceedings
Constitutes the refereed proceedings of the 4th Mexican International Conference on Artificial Intelligence, MICAI 2005, held Mexico, in November 2005. This book is organized in topical sections on knowledge representation and management, logic and constraint programming, uncertainty reasoning, multiagent systems and distributed AI, and others.
Measurement Uncertainty : An Approach via the Mathematical Theory of Evidence
This text is the first to make full use of the mathematical theory of evidence to express the uncertainty in measurements. It gives an overview of the current standard, then pinpoints and constructively resolves its limitations through its unique approach. The text presents various tools for evaluating uncertainty, beginning with the probabilistic approach and concluding with the expression of uncertainty using random-fuzzy variables. The exposition is driven by numerous examples. The book is designed for immediate use and application in research and laboratory work.
Measurement Uncertainties in Science and Technology
At the turn of the 19th century, Carl Friedrich Gauß founded error calculus by predicting the then unknown position of the planet Ceres. Ever since, error calculus has occupied a place at the heart of science. In this book, Grabe illustrates the breakdown of traditional error calculus in the face of modern measurement techniques. Revising Gauß’ error calculus ab initio, he treats random and unknown systematic errors on an equal footing from the outset. Furthermore, Grabe also proposes what may be called well defined measuring conditions, a prerequisite for defining confidence intervals that are consistent with basic statistical concepts. The resulting measurement uncertainties are as robust and reliable as required by modern-day science, engineering and technology.
Measurement Errors and Uncertainties : Theory and Practice
Measurement Errors and Uncertainties addresses the most important problems that physicists and engineers encounter when estimating errors and uncertainty. Building from the fundamentals of measurement theory, the author develops the theory of accuracy of measurements and offers a wealth of practical recommendations and examples of applications.
Mathematics of Uncertainty : Ideas, Methods, Application Problems
Mathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics in which uncertainty, variability, imprecision and fuzziness of data are of importance. This introductory book describes the basic ideas of the mathematical fields of uncertainty from simple interpolation to wavelets, from error propagation to fuzzy sets and neural networks. The book presents the treatment of problems of interpolation and approximation, as well as observation fuzziness which can essentially influence the preciseness and reliability of statements on functional relationships.
Mathematics and Culture II : Visual Perfection: Mathematics and Creativity
This book presents the mathematical foundations of systems theory in a self-contained, comprehensive, detailed and mathematically rigorous way. This volume is devoted to the analysis of dynamical systems with emphasis on problems of uncertainty, whereas the second volume will be devoted to control. It combines features of a detailed introductory textbook with that of a reference source. The book contains many examples and figures illustrating the text which help to bring out the intuitive ideas behind the mathematical constructions.
Mathematical Systems Theory I : Modelling, State Space Analysis, Stability and Robustness
This book presents the mathematical foundations of systems theory in a self-contained, comprehensive, detailed and mathematically rigorous way. This volume is devoted to the analysis of dynamical systems with emphasis on problems of uncertainty, whereas the second volume will be devoted to control. It combines features of a detailed introductory textbook with that of a reference source. The book contains many examples and figures illustrating the text which help to bring out the intuitive ideas behind the mathematical constructions.
Irreversible Decisions under Uncertainty : Optimal Stopping Made Easy
In real life, as well as in economic models, individuals often make decisions in an uncertain environment. In many cases, a problem which an optimizing agent faces can be formulated or reformulated as a problem of optimal timing of a certain irreversible or partially reversible action or optimal stopping problem. In this book, the authors present an alternative approach to optimal stopping problems. The basic ideas and techniques of the approach can be explained much simpler than the standard methods in the literature on optimal stopping problems. The monograph will teach the reader to apply the technique to many problems in economics and finance, including new ones. From the technical point of view, the method can be characterized as option pricing via the Wiener-Hopf factorization.
Introduction to Bayesian Scientific Computing : Ten Lectures on Subjective Computing
Inverse problems are closely related to statistical inference problems, where the observations are used to infer on an underlying probability distribution. This connection between statistical inference and inverse problems is a central topic of the book. Inverse problems are typically ill-posed: small uncertainties in data may propagate in huge uncertainties in the estimates of the unknowns. To cope with such problems, efficient regularization techniques are developed in the framework of numerical analysis. The counterpart of regularization in the framework of statistical inference is the use prior information.
Interventions for Persisting Ductus Arteriosus in the Preterm Infant
Over the past few years a remarkably rapid evolution in the professional level of neonatology and in the survival of immature infants has been witnessed. Persisting ductus arteriosus is common in this population and is associated with impaired longterm outcome. Many uncertainties exist concerning indication, approach, best time, and side effects of necessary measurements and interventions to avoid later neurodevelopmental handicaps of the survivors. Experts in neonatology and pediatric cardiology give their opinion in this book. We are sure it will help to define the level of evidence and to develop standards of intervention for persisting ductus arteriosus in Europe. Adequate dealing with the ductus will become a challenge for every perinatal center.
Interval / Probabilistic Uncertainty and Non-Classical Logics
Contains proceedings of the first international workshop that brought together researchers working on interval and probabilistic uncertainty and on non-classical logics. We hope that this workshop will lead to a boost in the much-needed collaboration between the uncertainty analysis and non-classical logic communities, and thus, to better processing of uncertainty.
Interdisciplinary Perspectives on Mortality and its Timings : When is Death?
This volume provides a series of illuminating perspectives on the timings of death, through in-depth studies of Shakespearean tragedy, criminal execution, embalming practices, fears of premature burial, rumours of Adolf Hitler’s survival, and the legal concept of brain death. In doing so, it explores a number of questions, including: how do we know if someone is dead or not? What do people experience at the moment when they die? Is death simply a biological event that comes about in temporal stages of decomposition, or is it a social event defined through cultures, practices, and commemorations? In other words, when exactly is death? Taken together, these contributions explore how death emerges in a series of stages that are uncertain, paradoxical, and socially contested.
Intelligent information processingg II ; IFIP TC12/WG12.3 International Conference on Intelligent Information Processing (IIP2004) October 21-23, 2004, Beijing, China
This book is based on IIP2004, which provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in any aspect of intelligent information processing. Papers on intelligence science, intelligent agents, machine learning, and autonomic computing, as well as papers that highlight bioinformatics, e-commerce, and business intelligence were presented. IIP2004 meets the needs of a large and diverse community.
Intelligent Decision Making : An AI-Based Approach
This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends.
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems ; Vol.3990 ; 3rd International Conference, CPAIOR 2006, Cork, Ireland, May 31 - June 2, 2006, Proceedings
Constitutes the refereed proceedings of the Third International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2006. The 20 revised full papers presented together with 3 invited talks address methodological and foundational issues from AI, OR, and algorithmics and present applications to the solution of combinatorial optimization problems in various fields via constraint programming.
Hybrid Evolutionary Algorithms
Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in ’Hybrid Evolutionary Algorithms’. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
How to Future : Leading and Sense-making in an Age of Hyperchange
Provides clear, practical and easy to understand tools that will help you spot trends and patterns, strategically evaluate different futures and guide your strategy Depicts a strategic framework to understand the uncertain nature of the current business world that crucially allows you to embrace hyperchange and adapt and plan for it Delivers a common language to engage stakeholders and teams with innovation practices and strategy foresight
Hazardous Chemicals in Products and Processes : Substitution as an Innovative Process
ubstitution of hazardous substances is a prioritised objective in chemical regulation and risk management. However, it is experienced as a tough task with often inconsistent results. Based on thirteen case studies, this book analyzes substitution as an innovation process and attempts to give answers to the following questions: Why and under which circumstances are companies able and willing to substitute hazardous substances? What are the main drivers and the main barriers? In which way can communication along the supply chain support environmental innovation? How can risk management appropriately deal with the lack of knowledge, with uncertainties and incomplete knowledge about the possible effects of different substances?
Handbook of Geometric Computing : Applications in Pattern Recognition, Computer Vision, Neuralcomputing, and Robotics
Many computer scientists, engineers, applied mathematicians, and physicists use geometry theory and geometric computing methods in the design of perception-action systems, intelligent autonomous systems, and man-machine interfaces. This handbook brings together the most recent advances in the application of geometric computing for building such systems, with contributions from leading experts in the important fields of neuroscience, neural networks, image processing, pattern recognition, computer vision, uncertainty in geometric computations, conformal computational geometry, computer graphics and visualization, medical imagery, geometry and robotics, and reaching and motion planning. For the first time, the various methods are presented in a comprehensive, unified manner.
