Condition Monitoring Using Computational Intelligence Methods

The book reports on new theories and applications in the field of intelligent systems and computing. It covers computational and artificial intelligence methods, as well as advances in computer vision

This concise, plain-language guide for senior undergraduates and graduate students aims to develop intuition, practical skills and an understanding of the framework of numerical methods for the physical sciences and engineering. It provides accessible self-contained explanations of mathematical principles, avoiding intimidating formal proofs. Worked examples and targeted exercises enable the student to master the realities of using numerical techniques for common needs such as solution of ordinary and partial differential equations, fitting experimental data, and simulation using particle and Monte Carlo methods. Topics are carefully selected and structured to build understanding, and illustrate key principles such as: accuracy, stability, order of convergence, iterative refinement, and computational effort estimation. Enrichment sections and in-depth footnotes form a springboard to more advanced material and provide additional background. Whether used for self-study, or as the basis o

How can Twitter data be used to study individual-level human behavior and social interaction on a global scale? This book introduces readers to the methods, opportunities, and challenges of using Twitter data to analyze phenomena ranging from the number of people infected by the flu, to national elections, to tomorrow's stock prices. Each chapter, written by leading domain experts in clear and accessible language, takes the reader to the forefront of the newly emerging field of computational social science. An introductory chapter on Twitter data analysis provides an overview of key tools and skills, and gives pointers on how to get started, while the case studies demonstrate shortcomings, limitations, and pitfalls of Twitter data as well as its advantages. The book will be an excellent resource for social science students and researchers wanting to explore the use of online data.

Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by nu

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.

This book classifies the maximal subgroups of the almost simple finite classical groups in dimension up to 12; it also describes the maximal subgroups of the almost simple finite exceptional groups with socle one of Sz(q), G2(q), 2G2(q) or 3D4(q). Theoretical and computational tools are used throughout, with downloadable Magma code provided. The exposition contains a wealth of information on the structure and action of the geometric subgroups of classical groups, but the reader will also encounter methods for analysing the structure and maximality of almost simple subgroups of almost simple groups. Additionally, this book contains detailed information on using Magma to calculate with representations over number fields and finite fields. Featured within are previously unseen results and over 80 tables describing the maximal subgroups, making this volume an essential reference for researchers. It also functions as a graduate-level textbook on finite simple groups, computational group the

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

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

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

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

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 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).

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.

Recent developments in molecular and computational methods have made it possible to identify the genetic basis of any biological trait, and have led to spectacular advances in the study of human disease. This book provides an overview of the concepts and methods needed to understand the genetic basis of biological traits, including disease, in humans. Using examples of qualitative and quantitative phenotypes, Professor Weiss shows how genetic variation may be quantified, and how relationships between genotype and phenotype may be inferred. This book will appeal to many biologists and biological anthropologists interested in the genetic basis of biological traits, as well as to epidemiologists, biomedical scientists, human geneticists and molecular biologists.

This book provides an introduction to recent developments in the theory of blow up algebras - Rees algebras, associated graded rings, Hilbert functions, and birational morphisms. The emphasis is on deriving properties of rings from their specifications in terms of generators and relations. While this limits the generality of many results, it opens the way for the application of computational methods. A highlight of the book is the chapter on advanced computational methods in algebra using Gröbner basis theory and advanced commutative algebra. The author presents the Gröbner basis algorithm and shows how it can be used to resolve computational questions in algebra. This volume is intended for advanced students in commutative algebra, algebraic geometry and computational algebra, and homological algebra. It can be used as a reference for the theory of Rees algebras and related topics.

SAR Oceanography: Monitoring Oceanic Dynamics with Synthetic Aperture Radar is an authoritative reference for scientists and professionals involved in marine remote sensing and oceanography. The book addresses the critical need for advanced techniques to observe and analyze ocean surface phenomena such as wind, waves, currents, internal waves, and oil spills using SAR technology. It emphasizes the importance of SAR in tropical cyclone monitoring, providing insights into high-resolution, all-weather, day-and-night observations essential for climate research, disaster response, and maritime safety. The content is divided into chapters covering SAR algorithms, applications in different oceanic processes, and recent technological developments. It offers practical case studies and validation methods, making it a valuable resource for researchers, meteorologists, environmental policymakers, and remote sensing specialists. This publication enhances understanding of ocean dynamics and supports

Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. It examines both the commonly used traffic analysis methodologies as well the emerging ones that use deep learning methods. The book also shows how to understand statistical models and machine learning algorithms, and how to apply them to traffic modelling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning is for researchers and practitioners who want to improve the performance of intelligent transportation systems.

The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks,

This book highlights the experimental investigations that have been carried out on magnetic resonance imaging and computed tomography (MRI & CT) images using state-of-the-art Computational Image p

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic web, social networks

Protein Immobilization on Nanomaterials explores advanced technologies and methodologies for immobilizing proteins on nanomaterial surfaces, highlighting their innovative applications in biotechnology, medicine, and materials engineering. This comprehensive resource is designed to educate researchers and practitioners on the latest techniques and advances in this rapidly evolving field. The book delves into various methods of protein immobilization, including physical adsorption, covalent binding, and encapsulation, providing detailed explanations and practical examples. It also covers the characterization of protein-nanomaterial conjugates using advanced analytical techniques such as spectroscopy and microscopy. Key topics include the use of protein-nanomaterial conjugates in biosensors, diagnostic devices, drug delivery systems, and environmental monitoring. With contributions from leading experts, the book presents colorful figures and practical examples to facilitate the understand

Elasticity: Theory, Applications, and Numerics, Fourth Edition, continues its market-leading tradition of concisely presenting and developing the linear theory of elasticity, moving from solution methodologies, formulations, and strategies into applications of contemporary interest, such as fracture mechanics, anisotropic and composite materials, micromechanics, nonhomogeneous graded materials, and computational methods. Developed for a one- or two-semester graduate elasticity course, this new edition has been revised with new worked examples and exercises, and new or expanded coverage of areas such as treatment of large deformations, fracture mechanics, strain gradient and surface elasticity theory, and tensor analysis. Using MATLAB software, numerical activities in the text are integrated with analytical problem solutions.Online ancillary support materials for instructors include a solutions manual, image bank, and a set of PowerPoint lecture slides.

Change detection using remotely sensed images has many applications, such as urban monitoring, land-cover change analysis, and disaster management. This work investigates two-dimensional change detect