Condition Monitoring Using Computational Intelligence Methods

This book is written for engineers and other practitioners using numerical methods in their work and serves as a textbook for courses in applied mathematics and numerical analysis.

Artificial intelligence has recently turned to formal logic in the search for powerful yet well-behaved knowledge representation languages. This book covers the background of classical logic, including the major meta-theorems, and the state of the art in theorem proving including Bibel's connection method. Also covered are the advanced adaptations of classical logic now being used in artificial intelligence - temporal and modal logics, reason maintenance and intensional logic. First published in 1988, the book covers a wider range of topics than the currently available books in this area, and is more directly aimed at workers in artificial intelligence.

Presents methods for determining the secondary and tertiary structure of proteins. The issues covered here involve theoretical/empirical approaches for predicting protein structure; a review using pro

Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neu

Numerical Computation of Internal and External Flows Volume 2: Computational Methods for Inviscid and Viscous Flows C. Hirsch, Vrije Universiteit Brussel, Brussels, Belgium This second volume deals wi

Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The

Integral equations form an important class of problems, arising frequently in engineering, and in mathematical and scientific analysis. This textbook provides a readable account of techniques for their numerical solution. The authors devote their attention primarily to efficient techniques using high order approximations, taking particular account of situations where singularities are present. The classes of problems which arise frequently in practice, Fredholm of the first and second kind and eigenvalue problems, are dealt with in depth. Volterra equations, although attractive to treat theoretically, arise less often in practical problems and so have been given less emphasis. Some knowledge of numerical methods and linear algebra is assumed, but the book includes introductory sections on numerical quadrature and function space concepts. This book should serve as a valuable text for final year undergraduate or postgraduate courses, and as an introduction or reference work for practisin

This book presents advances in computational methods, experimental synthesis, and advanced characterizations for novel catalytic materials. The authors show how catalytical materials can be used for v

The human condition affects us all. As we journey through life, we face birth, aging, sickness, and death, each bringing significant challenges. How can we better understand our human condition? What can we learn from it?In Buddhist Encounters: Finding a Home in the Human Condition, Dr. Lewis R. Lancaster explores the essence of our existence, addressing the internal conflicts and external pressures exacerbated by the post-pandemic and AI era. Through the lens of Buddhist teachings, he seeks answers to these timeless issues, reflecting on the very dilemma that concerned the Buddha himself.

The human condition affects us all. As we journey through life, we face birth, aging, sickness, and death, each bringing significant challenges. How can we better understand our human condition? What can we learn from it? In Buddhist Encounters: Finding a Home in the Human Condition, Dr. Lewis R. Lancaster explores the essence of our existence, addressing the internal conflicts and external pressures exacerbated by the post-pandemic and AI era. Through the lens of Buddhist teachings, he seeks answers to these timeless issues, reflecting on the very dilemma that concerned the Buddha himself.

AN INSTANT NEW YORK TIMES BESTSELLERFrom Wharton professor and author of the popular One Useful Thing Substack newsletter Ethan Mollick comes the definitive playbook for working, learning, and living in the new age of AISomething new entered our world in November 2022 — the first general purpose AI that could pass for a human and do the kinds of creative, innovative work that only humans could do previously. Wharton professor Ethan Mollick immediately understood what ChatGPT meant: after millions of years on our own, humans had developed a kind of co-intelligence that could augment, or even replace, human thinking. Through his writing, speaking, and teaching, Mollick has become one of the most prominent and provocative explainers of AI, focusing on the practical aspects of how these new tools for thought can transform our world. In Co-Intelligence, Mollick urges us to engage with AI as co-worker, co-teacher, and coach. He assesses its profound impact on business and education, using do

A groundbreaking endeavor that explores human spirituality using the evolving technology of artificial intelligenceWhy are we here? What does it mean to love? How do we overcome suffering? Why do we feel so alone? Is happiness truly possible?For thousands of years, humanity has turned to the same sacred texts to explore these universal questions―from the Bible and the Tao Te Ching, to the poetry of Rumi and Sappho, to modern-day mystics. What if you could take all of the wisdom contained within these collective pages and, using the world’s most advanced artificial intelligence, receive the answers?Thanks to OpenAI, a nonprofit research lab cofounded by Elon Musk and other tech luminaries, this is now possible. OpenAI’s mission is to ensure that artificial intelligence serves the betterment of humanity―and What Makes Us Human? offers an innovative exploration of AI’s potential in this realm.To create this first-of-its-kind book, international bestselling poet Iain S. Thomas and prodigio

An original comprehensive guide on computational nanomechanics discussing basic concepts and implications in areas such as computational physics, materials, mechanics and engineering as well as several other interdisciplinary avenues. This book makes the underlying theory accessible to readers without specialised training or extensive background in quantum physics, statistical mechanics, or theoretical chemistry. It combines a careful treatment of theoretical concepts with a detailed tutorial on computer software and computing implementation, including multiscale simulation and computational statistical theory. Multidisciplinary perspectives are provided, yielding a true insight on the applications of computational nanomechanics across diverse engineering fields. The book can serve as a practical guide with step-by-step discussion of coding, example problems and case studies. This book will be essential reading for students new to the subject, as well as an excellent reference for gra

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

Since the mid-2010s, virtual reality (VR) technology has advanced rapidly. This book explores the many opportunities that VR can offer for humanities and social sciences researchers. It provides a user-friendly, non-technical methods guide to using ready-made VR content and 360° video as well as creating custom materials.

Up-to-date edition of Computational Geomechanics, broadening the focus of the first edition to include more applications This extended second edition of the highly successful book Computational Geomec

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and

This introductory overview explores the methods, models and interdisciplinary links of artificial economics, a new way of doing economics in which the interactions of artificial economic agents are computationally simulated to study their individual and group behavior patterns. Conceptually and intuitively, and with simple examples, Mercado addresses the differences between the basic assumptions and methods of artificial economics and those of mainstream economics. He goes on to explore various disciplines from which the concepts and methods of artificial economics originate; for example cognitive science, neuroscience, artificial intelligence, evolutionary science and complexity science. Introductory discussions on several controversial issues are offered, such as the application of the concepts of evolution and complexity in economics and the relationship between artificial intelligence and the philosophies of mind. This is one of the first books to fully address artificial economics

In the digital world, the significance of emotional intelligence (EI) will gain further importance as technologies such as artificial intelligence (AI) and automation partly or fully replace human int

Adaptive Intelligence is a dramatic reappraisal and reframing of the concept of human intelligence. In a sweeping analysis, Robert J. Sternberg argues that we are using a fatally-flawed, outdated conception of intelligence; one which may promote technological advancement, but which has also accelerated climate change, pollution, the use of weaponry, and inequality. Instead of focusing on the narrow academic skills measured by standardized tests, societies should teach and assess adaptive intelligence, defined as the use of collective talent in service of the common good. This book describes why the outdated notion of intelligence persists, what adaptive intelligence is, and how it could lead humankind on a more positive path.

Adaptive Intelligence is a dramatic reappraisal and reframing of the concept of human intelligence. In a sweeping analysis, Robert J. Sternberg argues that we are using a fatally-flawed, outdated conception of intelligence; one which may promote technological advancement, but which has also accelerated climate change, pollution, the use of weaponry, and inequality. Instead of focusing on the narrow academic skills measured by standardized tests, societies should teach and assess adaptive intelligence, defined as the use of collective talent in service of the common good. This book describes why the outdated notion of intelligence persists, what adaptive intelligence is, and how it could lead humankind on a more positive path.

This introduction to the singularly perturbed methods in the nonlinear elliptic partial differential equations emphasises the existence and local uniqueness of solutions exhibiting concentration property. The authors avoid using sophisticated estimates and explain the main techniques by thoroughly investigating two relatively simple but typical non-compact elliptic problems. Each chapter then progresses to other related problems to help the reader learn more about the general theories developed from singularly perturbed methods. Designed for PhD students and junior mathematicians intending to do their research in the area of elliptic differential equations, the text covers three main topics. The first is the compactness of the minimization sequences, or the Palais-Smale sequences, or a sequence of approximate solutions; the second is the construction of peak or bubbling solutions by using the Lyapunov-Schmidt reduction method; and the third is the local uniqueness of these solutions.

Artificial intelligence (AI) stands out as a transformational technology of the digital age. Its practical applications are growing very rapidly. One of the chief reasons AI applications are attaining prominence, is in its design to learn continuously, from real-world use and experience, and its capability to improve its performance.It is no wonder that the applications of AI span from complex high-technology equipment manufacturing to personalized exclusive recommendations to end-users. Many deployments of AI software, given its continuous learning need, require computation platforms that are resource intense, and have sustained connectivity and perpetual power through central electrical grid. In order to harvest the benefits of AI revolution to all of humanity, traditional AI software development paradigms must be upgraded to function effectively in environments that have resource constraints, small form factor computational devices with limited power, devices with intermittent or no

In this Element, I first introduce intelligence in terms of historical definitions. I show that intelligence, as conceived even by the originators of the first intelligence tests, Alfred Binet and David Wechsler, is a much broader construct than just scores on narrow tests of intelligence and their proxies. I then review the major approaches to understanding intelligence and its development: the psychometric (test-based), cognitive and neurocognitive (intelligence as a set of brain-based cognitive representations and processes), systems, cultural, and developmental. These approaches, taken together, present a much more complex portrait of intelligence and its development than the one that would be ascertained just from scores on intelligence tests. Finally, I draw some take-away conclusions.

Emotional intelligence is an important trait for success at work. IQ tests are biased against minorities. Every child is gifted. Preschool makes children smarter. Western understandings of intelligence are inappropriate for other cultures. These are some of the statements about intelligence that are common in the media and in popular culture. But none of them are true. In the Know is a tour of the most common incorrect beliefs about intelligence and IQ. Written in a fantastically engaging way, each chapter is dedicated to correcting a misconception and explains the real science behind intelligence. Controversies related to IQ will wither away in the face of the facts, leaving readers with a clear understanding about the truth of intelligence.

Emotional intelligence is an important trait for success at work. IQ tests are biased against minorities. Every child is gifted. Preschool makes children smarter. Western understandings of intelligence are inappropriate for other cultures. These are some of the statements about intelligence that are common in the media and in popular culture. But none of them are true. In the Know is a tour of the most common incorrect beliefs about intelligence and IQ. Written in a fantastically engaging way, each chapter is dedicated to correcting a misconception and explains the real science behind intelligence. Controversies related to IQ will wither away in the face of the facts, leaving readers with a clear understanding about the truth of intelligence.

Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and als

Language resources and computational models are becoming increasingly important for the study of language variation. A main challenge of this interdisciplinary field is that linguistics researchers may not be familiar with these helpful computational tools and many NLP researchers are often not familiar with language variation phenomena. This essential reference introduces researchers to the necessary computational models for processing similar languages, varieties, and dialects. In this book, leading experts tackle the inherent challenges of the field by balancing a thorough discussion of the theoretical background with a meaningful overview of state-of-the-art language technology. The book can be used in a graduate course, or as a supplementary text for courses on language variation, dialectology, and sociolinguistics or on computational linguistics and NLP. Part 1 covers the linguistic fundamentals of the field such as the question of status and language variation. Part 2 discusses

Single Molecule Science (SMS) has emerged from developing, using and combining technologies such as super-resolution microscopy, atomic force microscopy, and optical and magnetic tweezers, alongside sophisticated computational and modelling techniques. This comprehensive, edited volume brings together authoritative overviews of these methods from a biological perspective, and highlights how they can be used to observe and track individual molecules and monitor molecular interactions in living cells. Pioneers in this fast-moving field cover topics such as single molecule optical maps, nanomachines, and protein folding and dynamics. A particular emphasis is also given to mapping DNA molecules for diagnostic purposes, and the study of gene expression. With numerous illustrations, this book reveals how SMS has presented us with a new way of understanding life processes. A must-have for researchers and graduate students, as well as those working in industry, primarily in the areas of biophy

Based on interdisciplinary research into 'Directional Change', a new data-driven approach to financial data analysis, this book applies machine learning to financial market monitoring and algorithmic

Examining the potential benefits and risks of using artificial intelligence to advance global sustainability.Drones with night vision are tracking elephant and rhino poachers in African wildlife parks

This book aims to illuminate theoretical and methodological advances in computational cultural neuroscience and the implications of these advances for philosophy.

This book aims to illuminate theoretical and methodological advances in computational cultural neuroscience and the implications of these advances for philosophy.

This book addresses the integration of all the new tools and technologies presented in today’s plethora of artificial intelligence tools and technologies to boost and enhance business intelligence. It

This book addresses the integration of all the new tools and technologies presented in today’s plethora of artificial intelligence tools and technologies to boost and enhance business intelligence. It

The study of electronic structure of materials is at a momentous stage, with new computational methods and advances in basic theory. Many properties of materials can be determined from the fundamental equations, and electronic structure theory is now an integral part of research in physics, chemistry, materials science and other fields. This book provides a unified exposition of the theory and methods, with emphasis on understanding each essential component. New in the second edition are recent advances in density functional theory, an introduction to Berry phases and topological insulators explained in terms of elementary band theory, and many new examples of applications. Graduate students and research scientists will find careful explanations with references to original papers, pertinent reviews, and accessible books. Each chapter includes a short list of the most relevant works and exercises that reveal salient points and challenge the reader.

The book provides a major source of information about the novel approach of chromaticity with examples of how chromaticity may be deployed for various monitoring applications.

The book provides a major source of information about the novel approach of chromaticity with examples of how chromaticity may be deployed for various monitoring applications.

Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in bio