Condition Monitoring Using Computational Intelligence Methods

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

Contrary to popular mythology, the designs of favorable products and successful systems do not appear suddenly, or magically. This second edition of Engineering Design demonstrates that symbolic representation and related problem-solving methods, offer significant opportunities to clarify and articulate concepts of design to lay a better framework for design research and design education. Artificial Intelligence (AI) provides a substantial body of material concerned with understanding and modeling cognitive processes. This book adopts the vocabulary and a paradigm of AI to enhance the presentation and explanation of design. It includes concepts from AI because of their explanatory power and their utility as possible ingredients of practical design activity. This second edition has been enriched by the inclusion of recent work on design reasoning, computational design, AI in design, and design cognition, with pointers to a wide cross section of the current literature.

Measuring the performance of public agencies and programmes is essential to ensure that citizens enjoy quality services and that governments can be sure that taxpayers receive value for money. As such, good performance measurement is a crucial component of improvement and planning, monitoring and control, comparison and benchmarking and also ensures democratic accountability. This book shows how the principles, uses and practice of performance measurement for public services differ from those in for-profit organisations, being based on the need to add public value rather than profit. It describes methods and approaches for measuring performance through time, for constructing and using scorecards, composite indicators, the use of league tables and rankings and argues that data-envelopment analysis is a useful tool when thinking about performance. This demonstrates the importance of allowing for the multidimensional nature of performance, as well as the need to base measurement on a soun

Action selection is the task of doing the right thing at the right time. It requires the assessment of available alternatives, executing those most appropriate, and resolving conflicts among competing goals and possibilities. Using advanced computational modelling, this book explores cutting-edge research into action selection in nature from a wide range of disciplines, from neuroscience to behavioural ecology, and even political science. It delivers new insights into both detailed and systems-level attributes of natural intelligence and demonstrates advances in methodological practice. Contributions from leading researchers cover issues including whether biological action selection is optimal, neural substrates for action selection in the vertebrate brain, perceptual selection in decision making, and interactions between group and individual action selection. This first integrated review of action selection in nature contains a balance of review and original research material, consoli

Scientists need statistics. Increasingly this is accomplished using computational approaches. Freeing readers from the constraints, mysterious formulas and sophisticated mathematics of classical statistics, this book is ideal for researchers who want to take control of their own statistical arguments. It demonstrates how to use spreadsheet macros to calculate the probability distribution predicted for any statistic by any hypothesis. This enables readers to use anything that can be calculated (or observed) from their data as a test statistic and hypothesize any probabilistic mechanism that can generate data sets similar in structure to the one observed. A wide range of natural examples drawn from ecology, evolution, anthropology, palaeontology and related fields give valuable insights into the application of the described techniques, while complete example macros and useful procedures demonstrate the methods in action and provide starting points for readers to use or modify in their ow

Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods must b

Ferdjallah (modeling, analysis, and simulation; Old Dominion U., Virginia) introduces students and users to analytical and computational methods for modeling, synthesizing, and simulating digital prin

Migraine is a condition that Western medicine finds notoriously difficult to treat, and acupuncture, moxibustion and Tuina massage can all be effective methods of bringing about relief. This clear and

It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on ch

It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on ch

"The book is focused on the developments and prospective challenging problems in the area of mind game playing (i.e. playing games that require mental skills) using Computational Intelligence (CI) met

Constraints are everywhere: most computational problems can be described in terms of restrictions imposed on the set of possible solutions, and constraint programming is a problem-solving technique that works by incorporating those restrictions in a programming environment. It draws on methods from combinatorial optimisation and artificial intelligence, and has been successfully applied in a number of fields from scheduling, computational biology, finance, electrical engineering and operations research through to numerical analysis. This textbook for upper-division students provides a thorough and structured account of the main aspects of constraint programming. The author provides many worked examples that illustrate the usefulness and versatility of this approach to programming, as well as many exercises throughout the book that illustrate techniques, test skills and extend the text. Pointers to current research, extensive historical and bibliographic notes, and a comprehensive list

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental sciences. Due to their powerful nonlinear modelling capability, machine learning methods today are used in satellite data processing, general circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and hydrological forecasting, ecological modelling, and monitoring of snow, ice and forests. The book includes end-of-chapter review questions and an appendix listing websites for downloading computer code and data sources. A resources website contains datasets for exercises, and password-protected solutions are available. The book is suitable for first-year graduate students and advanced undergraduates. It is also valuable for resear

Written by two leading experts in the field, this book explores the 'many-body' methods that have become the dominant approach in determining molecular structure, properties and interactions. With a tight focus on the highly popular Many-Body Perturbation Theory (MBPT) and Coupled-Cluster theories (CC), the authors present a simple, clear, unified approach to describe the mathematical tools and diagrammatic techniques employed. Using this book the reader will be able to understand, derive and confidently implement relevant algebraic equations for current and even new multi-reference CC methods. Hundreds of diagrams throughout the book enhance reader understanding through visualization of computational procedures and extensive referencing allows further exploration of this evolving area. With an extensive bibliography and detailed index, this book will be suitable for graduates and researchers within quantum chemistry, chemical physics and atomic, molecular and solid-state physics.

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental sciences. Due to their powerful nonlinear modelling capability, machine learning methods today are used in satellite data processing, general circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and hydrological forecasting, ecological modelling, and monitoring of snow, ice and forests. The book includes end-of-chapter review questions and an appendix listing websites for downloading computer code and data sources. A resources website contains datasets for exercises, and password-protected solutions are available. The book is suitable for first-year graduate students and advanced undergraduates. It is also valuable for resear

The analysis of protein-protein interactions is fundamental to the understanding of cellular organization, processes, and functions. Proteins seldom act as single isolated species; rather, proteins involved in the same cellular processes often interact with each other. Functions of uncharacterized proteins can be predicted through comparison with the interactions of similar known proteins. Recent large-scale investigations of protein-protein interactions using such techniques as two-hybrid systems, mass spectrometry, and protein microarrays have enriched the available protein interaction data and facilitated the construction of integrated protein-protein interaction networks. The resulting large volume of protein-protein interaction data has posed a challenge to experimental investigation. This book provides a comprehensive understanding of the computational methods available for the analysis of protein-protein interaction networks. It offers an in-depth survey of a range of approaches

The Overcoming Series offers step-by-step guides to self-improvement based on the methods of cognitive behavioral therapy. The series aims to help readers conquer a broad range of disabling condition

The Overcoming Series offers step-by-step guides to self-improvement based on the methods of cognitive behavioral therapy. The series aims to help readers conquer a broad range of disabling condition

The Overcoming Series offers step-by-step guides to self-improvement based on the methods of cognitive behavioral therapy. The series aims to help readers conquer a broad range of disabling condition

The Overcoming Series offers step-by-step guides to self-improvement based on the methods of cognitive behavioral therapy. The series aims to help readers conquer a broad range of disabling condition

Presents a drug-free plan for curing psoriasis using natural methods that rely on diet, detoxification, and mental attitude to alleviate and control the condition.

This publication takes a critical, evidence-based look at the efficacy of diagnostic tests which are increasingly being used to evaluate organ damage and dysfunction. The use of biomarkers is growing, with a steady stream of products being brought out by the pharmaceutical industry. Some of these assist in diagnosis, others provide a means of monitoring the state of progression of disease and the effectiveness of therapeutic options. However, in many cases the evidence which supports the use of these methods as opposed to traditional biochemical tests has not yet been demonstrated, and it is intended that this volume will help clarify the strengths and weaknesses of using these biomarkers across a wide range of applications and in the various organs of the body. This approach will provide pathologists, clinical biochemists and medical laboratory scientists with an invaluable overview of the diverse applications of biomarkers in medicine.

Creativity is a topic that has traditionally interested psychologists, historians and biographers. Developments in cognitive science and artificial intelligence have provided a powerful computational framework in which creativity can be studied and the creative process can be described and explained. In this book, creativity in technology is discussed using such a computational approach. Using an important historical episode in computer technology as a case study, namely the invention of microprogramming by Maurice Wilkes in 1951, the author presents a plausible explanation of the process by which Wilkes may have arrived at his invention. Based on this case study, the author has also proposed some very general hypotheses concerning creativity that appear to corroborate the findings of some psychologists and historians and then suggests that creative thinking is not significantly different in nature from everyday thinking and reasoning.

The effective management of diabetes can delay or even prevent the development of complications. Patients will often need to take a variety of medications, in addition to embracing lifestyle changes, to achieve this. Prescribing in Diabetes gives clear information about the options for treating the various aspects of diabetes, such as abnormal blood glucose, high blood pressure and abnormal cholesterol. It also gives practical advice on how to support people in managing their problems independently and improve their lifestyle, by making better choices armed with a thorough understanding of the condition and options for treatment. Chapters cover the range of methods available for the delivery of medicines to patients, the differences between type 1 and type 2 diabetes and an overview on how the drugs work. The book also discusses normal blood glucose regulation, self-monitoring, weight management, smoking cessation and the management of the most common complications.

Media argumentation is a powerful force in our lives. From political speeches to television commercials to war propaganda, it can effectively mobilize political action, influence the public, and market products. This book presents a new and systematic way of thinking about the influence of mass media in our lives, showing the intersection of media sources with argumentation theory, informal logic, computational theory, and theories of persuasion. Using a variety of case studies that represent arguments that typically occur in the mass media, Douglas Walton demonstrates how tools recently developed in argumentation theory can be usefully applied to the identification, analysis, and evaluation of media arguments. He draws upon the most recent developments in artificial intelligence, including dialogical theories of argument, which he developed, as well as speech act theory. Each chapter presents solutions to problems central to understanding, analyzing, and criticizing media argumentatio

Media argumentation is a powerful force in our lives. From political speeches to television commercials to war propaganda, it can effectively mobilize political action, influence the public, and market products. This book presents a new and systematic way of thinking about the influence of mass media in our lives, showing the intersection of media sources with argumentation theory, informal logic, computational theory, and theories of persuasion. Using a variety of case studies that represent arguments that typically occur in the mass media, Douglas Walton demonstrates how tools recently developed in argumentation theory can be usefully applied to the identification, analysis, and evaluation of media arguments. He draws upon the most recent developments in artificial intelligence, including dialogical theories of argument, which he developed, as well as speech act theory. Each chapter presents solutions to problems central to understanding, analyzing, and criticizing media argumentatio

From ants to whales, the lives of animals are filled with challenges that demand minute-by-minute decisions: to fight or flee, dominate or obey, take-off, share, eat, spit out or court. Learning develops adaptive tuning to a changeable environment, while intelligence helps animals use their learned experiences in new situations. Using examples from field to laboratory, Animal Intelligence pools resources from ethology, behavioural ecology and comparative psychology to help the reader enter the world of wild intelligence through the analysis of adventures, of ideas and methods, rather than through theoretic modelling. It reminds us that there is a world of intellectual biodiversity out there, providing a multi-faceted panorama of animal intelligence. Written in an accessible and charming style, and with undergraduate and graduate students in mind, this book should be read by anyone with an interest in the world of animal behaviour.

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

This book deploys the mathematical axioms of modern rational mechanics to understand minds as mechanical systems that exhibit actual, not metaphorical, forces, inertia, and motion. Using precise mental models developed in artificial intelligence the author analyzes motivation, attention, reasoning, learning, and communication in mechanical terms. These analyses provide psychology and economics with new characterizations of bounded rationality; provide mechanics with new types of materials exhibiting the constitutive kinematic and dynamic properties characteristic of different kinds of minds; and provide philosophy with a rigorous theory of hybrid systems combining discrete and continuous mechanical quantities. The resulting mechanical reintegration of the physical sciences that characterize human bodies and the mental sciences that characterize human minds opens traditional philosophical and modern computational questions to new paths of technical analysis.

This book explains how to build Natural Language Generation (NLG) systems - computer software systems which use techniques from artificial intelligence and computational linguistics to automatically generate understandable texts in English or other human languages, either in isolation or as part of multimedia documents, Web pages, and speech output systems. Typically starting from some non-linguistic representation of information as input, NLG systems use knowledge about language and the application domain to automatically produce documents, reports, explanations, help messages, and other kinds of texts. The book covers the algorithms and representations needed to perform the core tasks of document planning, microplanning, and surface realization, using a case study to show how these components fit together. It also discusses engineering issues such as system architecture, requirements analysis, and the integration of text generation into multimedia and speech output systems.

This volume includes contributions by leading workers in the field given at the workshop on Numerical Relativity held in Southampton in December 1991. Numerical Relativity, or the numerical solution of astrophysical problems using powerful computers to solve Einstein's equations, has grown rapidly over the last 15 years. It is now an important route to understanding the structure of the Universe, and is the only route currently available for approaching certain important astrophysical scenarios. The Southampton meeting was notable for the first full report of the new 2+2 approach and the related null or characteristic approaches, as well as for updates on the established 3+1 approach, including both Newtonian and fully relativistic codes. The contributions range from theoretical (formalisms, existence theorems) to the computational (moving grids, multiquadrics and spectral methods).

Evolution of language has evolved at multiple levels—from changes in the cognitive processes by which language is acquired in the individual, to language change by diffusion of acquired linguistic features across populations of individuals, to the emergence of linguistic features over phylogenetic time scales. Evolution of language at each of these levels interacts with that at each other level. This volume is a collection of essays by noted researchers from diverse fields that deals with a broad spectrum of issues in the study of language evolution. The principle topics addressed here include: the genetic and cognitive bases for the phylogenetic emergence of language; several distinct accounts of the underlying cognitive processes by which children learn to acquire language; a critique of the methods employed by historical linguists in the last century; the modeling of language evolution using mathematical and computational techniques; discussions on the complexity of language.

Constraints are everywhere: most computational problems can be described in terms of restrictions imposed on the set of possible solutions, and constraint programming is a problem-solving technique that works by incorporating those restrictions in a programming environment. It draws on methods from combinatorial optimisation and artificial intelligence, and has been successfully applied in a number of fields from scheduling, computational biology, finance, electrical engineering and operations research through to numerical analysis. This textbook for upper-division students provides a thorough and structured account of the main aspects of constraint programming. The author provides many worked examples that illustrate the usefulness and versatility of this approach to programming, as well as many exercises throughout the book that illustrate techniques, test skills and extend the text. Pointers to current research, extensive historical and bibliographic notes, and a comprehensive list

A collection of papers from a conference held at Kings College, London. Computer-based Design focuses on all areas of design using computational methods and examines how all these individual tools can

This publication takes a critical, evidence-based look at the efficacy of diagnostic tests which are increasingly being used to evaluate organ damage and dysfunction. The use of biomarkers is growing, with a steady stream of products being brought out by the pharmaceutical industry. Some of these assist in diagnosis, others provide a means of monitoring the state of progression of disease and the effectiveness of therapeutic options. However, in many cases the evidence which supports the use of these methods as opposed to traditional biochemical tests has not yet been demonstrated, and it is intended that this volume will help clarify the strengths and weaknesses of using these biomarkers across a wide range of applications and in the various organs of the body. This approach will provide pathologists, clinical biochemists and medical laboratory scientists with an invaluable overview of the diverse applications of biomarkers in medicine.

Describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using

Partial differential equations arise in almost all areas of science, engineering, modeling, and forecasting. During the last two decades pseudospectral methods have emerged as successful alternatives to better known computational procedures, (e.g. finite difference and finite element methods of numerical solution), in several key application areas. These areas include computational fluid dynamics, wave motion, and weather forecasting. This book explains how, when and why this pseudospectral approach works. In order to make the subject accessible to students as well as researchers and engineers, the subject is presented using illustrations, examples, heuristic explanations, and algorithms rather than rigorous theoretical arguments. This book will be of interest to graduate students, scientists and engineers interested in applying pseudospectral methods to real problems.

This book offers a critical reconstruction of the fundamental ideas and methods of artificial intelligence research. Through close attention to the metaphors of artificial intelligence and their consequences for the field's patterns of success and failure, it argues for a reorientation of the field away from thought in the head and towards activity in the world. By considering computational ideas in a large, philosophical framework, the author eases critical dialogue between technology and the social sciences. AI can benefit from an understanding of the field in relation to human nature, and in return, it offers a powerful mode of investigation into the practicalities of physical realization. This is one of a series of publications associated with the Earth System Governance Project. For more publications, see www.cambridge.org/earth-system-governance.