Artificial intelligence (AI) Books

Book SynopsisThis book introduces the new paradigm of lifelong and continual learning dialogue systems to endow dialogue systems with the ability to learn continually by themselves through their own self-initiated interactions with their users and the working environments. The authors present the latest developments and techniques for building such continual learning dialogue systems. The book explains how these developments allow systems to continuously learn new language expressions, lexical and factual knowledge, and conversational skills through interactions and dialogues. Additionally, the book covers techniques to acquire new training examples for learning new tasks during the conversation. The book also reviews existing work on lifelong learning and discusses areas for future research. Table of Contents1 Introduction.- 2 Open-world Continual Learning: A Framework.- 3 Continuous Factual Knowledge Learning in Dialogues.- 4 Continuous and Interactive Language Learning and Grounding.- 5 Continual Learning in Chit-chat Systems.- 6 Continual Learning for Task-oriented Dialogue Systems.- 7 Continual Learning of Conversational Skills.- 8 Conclusion and Future Directions.

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Book Synopsis- AI Enabled Human Action Recognition..- Enhanced Date Fruit Classification with a Novel One-Dimensional Convolutional Neural Network..- Accuracy Improvement of Fish Counting in Sonar Images using Deep Learning with Double Transfer Learning..- Predicting Agricultural Crop Yield in Indian States Using Machine Learning Models..- Comparative Analysis of Machine Learning Models on Binary Classification Using Tabular Datasets: A Study on Credit Risk, Australian, and German Datasets..- Hybrid Multi-Objective Optimization for Efficient Workflow Scheduling in Cloud Computing Environments: A PSO-GD Integrated Approach..- Exploring Novel Perspective on Collaborative AI: Techniques, Challenges, and Limitation..- Enhanced Malicious URL Detection through Feature Significance Analysis..- A Smart Intelligence Intrusion Detection System Using Optimal Elephant Hardening Feature Selection with Deep Generative Adversarial Neural Network Classifier..- Breast Cancer Diagnostics with Deep Learning Schemes Using Multi-Image Modalities..- Ethical Implications of Using AI to Monitor and Regulate Dark Web Activities..- Analyzing AI Generated Text using various Machine Learning, Deep Learning and LLM Models..- Predictive Modeling and Strategic Planning for Urban Flood Risk Mitigation..- A Review on Deep Learning Techniques for Cervical Cancer Detection..- Enhanced COVID-19 Detection Using CNN and Texture-Based Feature Extraction With Gradient Boosting Ensemble learner..- AI for Intelligent Data Retrieval..- Automated Skin Lesion Detection Using Deep Learning Approach..- A Review on Student Behavior Detection..- Vcare: A Survey on Menstrual Health Awareness and Accessibility..- Sentiment and Comment Analysis Using Various Machine Learning Algorithms and Evaluation of Classifiers on Educational YouTube Videos..- Identifying fake products using Blockchain..- Tourism Trends Through Yelp Review Analysis..- Revolutionizing eLearning with Metaverse Technologies: Virtual Classrooms and Beyond..- Integrating Artificial Intelligence and IoT for Early Detection and Management of Fungal Diseases in Oilseed Crops.

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Book SynopsisResearch on Autonomous Collision Avoidance and Navigation Strategies for Mobile Robots Based on Point Cloud Library (PCL) and Imitation Learning.- Development and Application Research of Motion Video Analysis Platform in Sports Training.- Construction of a Quadruped Robot Imitation Motion Control System based on Deep Reinforcement Learning.- Sports Action Teaching Correction System Combined with Intelligent Pose Recognition Technology.- Intelligent Logistics Path Planning and Real-Time Scheduling Optimization Based on Ant Colony Optimization Algorithm.

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Book SynopsisSocial network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.Table of ContentsA Randomized Approach for Structural and Message based Private Friend Recommendation in Online Social Networks; B. K. Samanthula, W.Jiang.- Context Based Semantic Relations in Tweets; O. Ozdikis et al.- Fast exact and approximate computation of betweenness centrality in social networks; M. Baglioni et al.- Network Simulation; E. Franchi.- Early Stage Conversation Catalysts on Entertainment-Based Web Forums; J. Lanagan et al.- Predicting Users Behaviours in Distributed Social Networks Using Community Analysis ; B. Ngonmang et al.- What should we protect? Defining differential privacy for social network analysis; C. Task, C.Clifton.- Complex Network Analysis of Research Funding: A Case Study of NSF Grants; H. Kardes et al.- Community Evolutionary Events in Online Social Networks; M. Abulaish, S. Yousuf Bhat.-@Rank: Personalized Centrality Measure for Email Communication Networks; P. Lubarski, M. Morzy.-Twitter Sentiment Analysis: How To Hedge Your Bets In The Stock Markets; T.Rao, S. Srivastava.- The Impact of Measurement Time on Subgroup Detection in Online Communities; S. Zeini et al.- Spatial and Temporal Evaluation of Network-Based Analysis of Human Mobility; M. Coscia et al.- An Ant based Particle Swarm Optimization Algorithm for Maximum Clique Problem in Social networks; M. Soleimani-pouri et al.- XEngine: An XML Search Engine for Social Groups; K.Taha.- Size, diversity and components in the network around an entrepreneur: Shaped by culture and shaping embeddedness of firm relations; M. Cheraghi, T.Schott .- Content Mining of Microblogs; M.Ö. Cingiz, B. Diri.

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Book SynopsisThis book presents a discussion of problems encountered in the deployment of Intelligent Transport Systems (ITS). It puts emphasis on the early tasks of designing and proofing the concept of integration of technologies in Intelligent Transport Systems. In its first part the book concentrates on the design problems of urban ITS. The second part of the book features case studies representative for the different modes of transport. These are freight transport, rail transport and aerospace transport encompassing also space stations. The book provides ideas for deployment which may be developed by scientists and engineers engaged in the design of Intelligent Transport Systems. It can also be used in the training of specialists, students and post-graduate students in universities and transport high schools.Table of ContentsPart I Deployment of ITS in Road Transport.- Part II ITS Case Studies.

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Book SynopsisThe book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.Table of ContentsPredicting human behavior based on web search activity: Greek referendum of 2015.- Compact Video Description and Representation for Automated Summarization of Human Activities.- Attribute Learning for Network Intrusion Detection.- A Fast Deep Convolutional Neural Network for face detection in Big Visual Data.- Learning Symbols by Neural Network.- Designing HMMs models in the age of Big Data.- Extended Formulations for Online Action Selection on Big Action Sets.- Multi-Task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports.- An infrastructure and approach for infering knowledge over Big Data in the Vehicle Insurance Industry.- Unified Retrieval Model of Big Data.- Adaptive Elitist Differential Evolution Extreme Learning Machines on Big Data: Intelligent Recognition of Invasive Species.

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Book SynopsisIn diesem Buch lernst du Schritt für Schritt, wie du mit dem kostenlosen MIT App Inventor einen Chatbot entwickelst. Du erfährst zuerst, was Chatbots eigentlich sind und dass diese als Alexa, Siri, Bixby, Cortana und Google schon um uns sind. Du gehst der Frage nach, auf welche Weise Chatbots intelligent sind. Die erste Chatbot-App, die du nach Anleitung entwickelst, beantwortet eine einfache Frage von dir. Am Ende erzählt der Chatbot Witze. Weitere Beispiele zeigen dir, was sonst noch alles möglich ist: Der Chatbot wird immer schlauer und geht immer besser auf seinen Chatpartner ein. Bestens geeignet für Kinder und Jugendliche ab 10 Jahren.Table of ContentsEinleitung 5 Hallo, zukünftige Chatbot-Entwicklerin oder zukünftiger Chatbot-Entwickler! 5 Über den MIT App Inventor 2 5 Über dieses Buch 6 Über dich 7 Über die Symbole, die wir in diesem Buch verwenden 8 Kapitel 1: Was sind Chatbots? 9 Was ist ein Chatbot? 10 Smart Home – alles ist vernetzt 12 Sind Chatbots intelligent? 13 Kapitel 2: Dein erster Chatbot 15 Account anlegen, einloggen, starten 16 Starte dein erstes Chatbot-Projekt! 24 Ein Chatbot muss bedient werden können: Das Design 25 Mit Chatbots reden – die Funktionalität 34 Schritt für Schritt zum ersten Gespräch 44 Option 1: Den Chatbot auf deinem Smartphone oder Tablet testen 44 Option 2: Nur das Design deines Chatbots mittels Emulator testen 50 Übers Ziel hinaus – noch mehr Möglichkeiten 52 Kapitel 3: Chatbots für Einsteiger 53 Der Sprachverzerrer 54 Der Musik-Chatbot 64 Der Sensor-Chatbot 87 Sensor-Chatbot mit Beschleunigungssensor 95 Sensor-Chatbot mit Lichtsensor 102 Kapitel 4: Für Fortgeschrittene 108 Schnick-Schnack-Schnuck-Chatbot 109 Spieldesign 110 Der Chatbot spielt mit 113 Timer-Chatbot 125 Die Zeitanzeige 126 Sensoren für den Timer-Chatbot 130 Kommandos geben 132 Kapitel 5: Chatbots für Profis 146 Der Witze-Chatbot 147 Das Design 147 Die Programmierung 149 Der Quiz-Chatbot 153 Weitere Ideen 157 Kapitel 6: Blick zu den Profis 159 Programmieren mit Tastatur 160 Bis zum nächsten Mal 160 Zum Wiederfinden 161 Über die Autoren 165

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Book SynopsisThis is the second edition of the valuable reference source for numerical simulations of contact mechanics suitable for many fields. These include civil engineering, car design, aeronautics, metal forming, or biomechanics. For this second edition, illustrative simplified examples and new discretisation schemes and adaptive procedures for coupled problems are added. This book is at the cutting edge of an area of significant and growing interest in computational mechanics. Trade ReviewFrom the reviews of the second edition: "The book is not simply a monograph reviewing the author’s distinguished research career, but a true textbook covering the research of the major players in computational contact mechanics over the last 25 years and offers an extensive list of references. … If I were given the opportunity to teach an advanced special topics course on finite element methods, I wouldn’t hesitate to use this book. For a researcher … the text provides an excellent review." (David J. Benson, SIAM Review, Vol. 49 (2), 2007)Table of Contentsto Contact Mechanics.- Continuum Solid Mechanics and Weak Forms.- Contact Kinematics.- Constitutive Equations for Contact Interfaces.- Contact Boundary Value Problem and Weak Form.- Discretization of the Continuum.- Discretization, Small Deformation Contact.- Discretization, Large Deformation Contact.- Solution Algorithms.- Thermo-mechanical Contact.- Beam Contact.- Computation of Critical Points with Contact Constraints.- Adaptive Finite Element Methods for Contact Problems.

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Book SynopsisThis volume contains the proceedings of the European Conference on Machine Learning 1994, which continues the tradition of earlier meetings and which is a major forum for the presentation of the latest and most significant results in machine learning. Machine learning is one of the most important subfields of artificial intelligence and computer science, as it is concerned with the automation of learning processes. This volume contains two invited papers, 19 regular papers, and 25 short papers carefully reviewed and selected from in total 88 submissions. The papers describe techniques, algorithms, implementations, and experiments in the area of machine learning.Table of ContentsIndustrial applications of ML: Illustrations for the KAML dilemma and the CBR dream.- Knowledge representation in machine learning.- Inverting implication with small training sets.- A context similarity measure.- Incremental learning of control knowledge for nonlinear problem solving.- Characterizing the applicability of classification algorithms using meta-level learning.- Inductive learning of characteristic concept descriptions from small sets of classified examples.- FOSSIL: A robust relational learner.- A multistrategy learning system and its integration into an interactive floorplanning tool.- Bottom-up induction of oblivious read-once decision graphs.- Estimating attributes: Analysis and extensions of RELIEF.- BMWk revisited generalization and formalization of an algorithm for detecting recursive relations in term sequences.- An analytic and empirical comparison of two methods for discovering probabilistic causal relationships.- Sample PAC-learnability in model inference.- Averaging over decision stumps.- Controlling constructive induction in CIPF: An MDL approach.- Using constraints to building version spaces.- On the utility of predicate invention in inductive logic programming.- Learning problem-solving concepts by reflecting on problem solving.- Existence and nonexistence of complete refinement operators.- A hybrid nearest-neighbor and nearest-hyperrectangle algorithm.- Automated knowledge acquisition for Prospector-like expert systems.- On the role of machine learning in knowledge-based control.- Discovering dynamics with genetic programming.- A geometric approach to feature selection.- Identifying unrecognizable regular languages by queries.- Intensional learning of logic programs.- Partially isomorphic generalization and analogical reasoning.- Learning from recursive, tree structured examples.- Concept formation in complex domains.- An algorithm for learning hierarchical classifiers.- Learning belief network structure from data under causal insufficiency.- Cost-sensitive pruning of decision trees.- An instance-based learning method for databases: An information theoretic approach.- Early screening for gastric cancer using machine learning techniques.- DP1: Supervised and unsupervised clustering.- Using machine learning techniques to interpret results from discrete event simulation.- Flexible integration of multiple learning methods into a problem solving architecture.- Concept sublattices.- The piecewise linear classifier DIPOL92.- Complexity of computing generalized VC-dimensions.- Learning relations without closing the world.- Properties of Inductive Logic Programming in function-free Horn logic.- Representing biases for Inductive Logic Programming.- Biases and their effects in Inductive Logic Programming.- Inductive learning of normal clauses.

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Book SynopsisThe development and use of models of various objects is becoming a more common practice in recent days. This is due to the ease with which models can be developed and examined through the use of computers and appropriate software. Of those two, the former - high-speed computers - are easily accessible nowadays, and the latter - existing programs - are being updated almost continuously, and at the same time new powerful software is being developed. Usually a model represents correlations between some processes and their interactions, with better or worse quality of representation. It details and characterizes a part of the real world taking into account a structure of phenomena, as well as quantitative and qualitative relations. There are a great variety of models. Modelling is carried out in many diverse fields. All types of natural phenomena in the area of biology, ecology and medicine are possible subjects for modelling. Models stand for and represent technical objects in physics, chemistry, engineering, social events and behaviours in sociology, financial matters, investments and stock markets in economy, strategy and tactics, defence, security and safety in military fields. There is one common point for all models. We expect them to fulfil the validity of prediction. It means that through the analysis of models it is possible to predict phenomena, which may occur in a fragment of the real world represented by a given model. We also expect to be able to predict future reactions to signals from the outside world.Trade ReviewFrom the reviews:“This textbook gives a short introduction to measurements, mathematical modeling, and computer simulation of dynamic systems. The mathematical modeling of dynamic systems is mainly based on systems of linear ordinary differential equations. … This book is divided into 5 chapters. … mainly written for students and researchers in engineering disciplines, who are interested in measurements, mathematical modeling, and computer simulation of dynamic systems.” (Manfred Tasche, Zentralblatt MATH, Vol. 1185, 2010)Table of Contentsto Measuring Systems.- Sensors.- Methods of Noise Reduction.- Model Development.- Mapping Error.

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Book SynopsisThis monograph is the r st in Fuzzy Approximation Theory. It contains mostly the author s research work on fuzziness of the last ten years and relies a lot on [10]-[32] and it is a natural outgrowth of them. It belongs to the broader area of Fuzzy Mathematics. Chapters are self-contained and several advanced courses can be taught out of this book. We provide lots of applications but always within the framework of Fuzzy Mathematics. In each chapter is given background and motivations. A c- plete list of references is provided at the end. The topics covered are very diverse. In Chapter 1 we give an extensive basic background on Fuzziness and Fuzzy Real Analysis, as well a complete description of the book. In the following Chapters 2,3 we cover in deep Fuzzy Di?erentiation and Integ- tion Theory, e.g. we present Fuzzy Taylor Formulae. It follows Chapter 4 on Fuzzy Ostrowski Inequalities. Then in Chapters 5, 6 we present results on classical algebraic and trigonometric polynomial Fuzzy Approximation.Table of ContentsABOUT H-FUZZY DIFFERENTIATION.- ON FUZZY TAYLOR FORMULAE.- FUZZY OSTROWSKI INEQUALITIES.- A FUZZY TRIGONOMETRIC APPROXIMATION THEOREM OF WEIERSTRASS-TYPE.- ON BEST APPROXIMATION AND JACKSON-TYPE ESTIMATES BY GENERALIZED FUZZY POLYNOMIALS.- BASIC FUZZY KOROVKIN THEORY.- FUZZY TRIGONOMETRIC KOROVKIN THEORY.- FUZZY GLOBAL SMOOTHNESS PRESERVATION.- FUZZY KOROVKIN THEORY AND INEQUALITIES.- HIGHER ORDER FUZZY KOROVKIN THEORY USING INEQUALITIES.- FUZZY WAVELET LIKE OPERATORS.- ESTIMATES TO DISTANCES BETWEEN FUZZY WAVELET LIKE OPERATORS.- FUZZY APPROXIMATION BY FUZZY CONVOLUTION OPERATORS.- DEGREE OF APPROXIMATION OF FUZZY NEURAL NETWORK OPERATORS, UNIVARIATE CASE.- HIGHER DEGREE OF FUZZY APPROXIMATION BY FUZZY WAVELET TYPE AND NEURAL NETWORK OPERATORS.- FUZZY RANDOM KOROVKIN THEOREMS AND INEQUALITIES.- FUZZY-RANDOM NEURAL NETWORK APPROXIMATION OPERATORS, UNIVARIATE CASE.- -SUMMABILITY AND FUZZY KOROVKIN APPROXIMATION.- -SUMMABILITY AND FUZZY TRIGONOMETRIC KOROVKIN APPROXIMATION.- UNIFORM REAL AND FUZZY ESTIMATES FOR DISTANCES BETWEEN WAVELET TYPE OPERATORS AT REAL AND FUZZY ENVIRONMENT.

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Book SynopsisThis book constitutes the refereed proceedings of the 6th KES International Conference on Agent and Multi-Agent Systems, KES-AMSTA 2012, held in Dubrovnik, Croatia, in June 2012. The conference attracted a substantial number of researchers and practitioners from all over the world who submitted their papers for ten main tracks covering the methodology and applications of agent and multi-agent systems, one workshop (TRUMAS 2012) and five special sessions on specific topics within the field. The 66 revised papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on virtual organizations, knowledge and learning agents, intelligent workflow, cloud computing and intelligent systems, self-organization, ICT-based alternative and augmentative communication, multi-agent systems, mental and holonic models, assessment methodologies in multi-agent and other paradigms, business processing agents, Trumas 2012 (first international workshop), conversational agents and agent teams, digital economy, and multi-agent systems in distributed environments.

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Book SynopsisThis volume constitutes the refereed proceedings of the international workshops, Confederated International Workshops: OTM Academy, OTM Industry Case Studies Program, ACM, EI2N, ISDE, META4eS, ORM, SeDeS, SINCOM, SMS and SOMOCO 2013, held as part of OTM 2013 in Graz, Austria, in September 2013. The 75 revised full papers presented together with 12 posters and 5 keynotes were carefully reviewed and selected from a total of 131 submissions. The papers are organized in topical sections on: On The Move Academy; Industry Case Studies Program; Adaptive Case Management and other non-workflow approaches to BPM; Enterprise Integration, Interoperability and Networking; Information Systems in Distributed Environment; Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society; Fact-Oriented Modeling; Semantics and Decision Making; Social Media Semantics; Social and Mobile Computing for collaborative environments; cooperative information systems; Ontologies, Data Bases and Applications of Semantics.Table of ContentsOn The Move Academy.- Industry Case Studies Program.- Adaptive Case Management and other non-workflow approaches to BPM.- Enterprise Integration, Interoperability and Networking.- Information Systems in Distributed Environment.- Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society.- Fact-Oriented Modeling.-Semantics and Decision Making.- Social Media Semantics.- Social and Mobile Computing for collaborative environments.- Cooperative information systems.- Ontologies, Data Bases and Applications of Semantics.

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Book SynopsisThis book presents a study of digital computation in contemporary cognitive science. Digital computation is a highly ambiguous concept, as there is no common core definition for it in cognitive science. Since this concept plays a central role in cognitive theory, an adequate cognitive explanation requires an explicit account of digital computation. More specifically, it requires an account of how digital computation is implemented in physical systems. The main challenge is to deliver an account encompassing the multiple types of existing models of computation without ending up in pancomputationalism, that is, the view that every physical system is a digital computing system. This book shows that only two accounts, among the ones examined by the author, are adequate for explaining physical computation. One of them is the instructional information processing account, which is developed here for the first time."This book provides a thorough and timely analysis of differing accounts of computation while advancing the important role that information plays in understanding computation. Fresco’s two-pronged approach will appeal to philosophically inclined computer scientists who want to better understand common theoretical claims in cognitive science.”Marty J. Wolf, Professor of Computer Science, Bemidji State University “An original and admirably clear discussion of central issues in the foundations of contemporary cognitive science.” Frances Egan, Professor of Philosophy, Rutgers, The State University of New JerseyTable of ContentsSetting the Stage: Computation in Cognitive Science.- An Analysis of the Adequacy Criteria for Evaluating Accounts of Computation.- Starting at the Beginning: Turing’s Account Examined.- The Triviality “Account” Examined.- Semantic Accounts of Computation Examined.- Computation as Information Processing.- Causal and Functional Accounts of Computation Examined.- Computation Revisited in the Context of Cognitive Science.

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Book SynopsisClustering is an important unsupervised classification technique where data points are grouped such that points that are similar in some sense belong to the same cluster. Cluster analysis is a complex problem as a variety of similarity and dissimilarity measures exist in the literature.This is the first book focused on clustering with a particular emphasis on symmetry-based measures of similarity and metaheuristic approaches. The aim is to find a suitable grouping of the input data set so that some criteria are optimized, and using this the authors frame the clustering problem as an optimization one where the objectives to be optimized may represent different characteristics such as compactness, symmetrical compactness, separation between clusters, or connectivity within a cluster. They explain the techniques in detail and outline many detailed applications in data mining, remote sensing and brain imaging, gene expression data analysis, and face detection.The book will be useful to graduate students and researchers in computer science, electrical engineering, system science, and information technology, both as a text and as a reference book. It will also be useful to researchers and practitioners in industry working on pattern recognition, data mining, soft computing, metaheuristics, bioinformatics, remote sensing, and brain imaging.Trade ReviewFrom the reviews:“The book focuses on emerging metaheuristic approaches to unsupervised classification, with an emphasis on a symmetry-based definition of similarity. … I found this book very appealing. I also thought of it as very valuable for my preoccupations towards the real-world application of unsupervised classification to medical imaging. I thus believe that, when reading this book, junior as well as experienced researchers will find many new challenging theoretical and practical ideas.” (Catalin Stoean, zbMATH, Vol. 1276, 2014)“The book views clustering as a (multiobjective) optimization problem and tackles it with metaheuristics algorithms. More interestingly, the authors of this book propose the exploitation of the concepts of point and line symmetry to define new distances to be used in clustering techniques. … researchers in the field will surely appreciate it as a good reference on the use of the symmetry notion in clustering.” (Nicola Di Mauro, Computing Reviews, July, 2013)Table of ContentsChap. 1 Introduction.- Chap. 2 Some Single- and Multiobjective Optimization Techniques.- Chap. 3 SimilarityMeasures.- Chap. 4 Clustering Algorithms.- Chap. 5 Point Symmetry Based Distance Measures and their Applications to Clustering.- Chap. 6 A Validity Index Based on Symmetry: Application to Satellite Image Segmentation.- Chap. 7 Symmetry Based Automatic Clustering.- Chap. 8 Some Line Symmetry Distance Based Clustering Techniques.- Chap. 9 Use of Multiobjective Optimization for Data Clustering.- References.- Index.

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Book SynopsisThe book collects the contributions to the NATO Advanced Study Institute on "Speech Recognition and Understanding: Recent Advances, Trends and Applications", held in Cetraro, Italy, during the first two weeks of July 1990. This Institute focused on three topics that are considered of particular interest and rich of i'p.novation by researchers in the fields of speech recognition and understanding: Advances in Hidden Markov modeling, connectionist approaches to speech and language modeling, and linguistic processing including language and dialogue modeling. The purpose of any ASI is that of encouraging scientific communications between researchers of NATO countries through advanced tutorials and presentations: excellent tutorials were offered by invited speakers that present in this book 15 papers which sum­ marize or detail the topics covered in their lectures. The lectures were complemented by discussions, panel sections and by the presentation of related works carried on by some of the attending researchers: these presentations have been collected in 42 short contributions to the Proceedings. This volume, that the reader can find useful for an overview, although incomplete, of the state of the art in speech understanding, is divided into 6 Parts.Table of Contents1 Recent Results on Hidden Markov Models.- Invited papers.- Hidden Markov Models for Speech Recognition — Strengths and Limitations.- Hidden Markov Models and Speaker Adaptation.- A 20,000 word Automatic Speech Recognizer. Adaptation to French of the US TANGORA System.- Automatic Adjustments of the Markov Models Topology for Speech Recognition Applications over the Telephone.- Phonetic Structure Inference of Phonemic HMM.- Phonetic Units and Phonotactical Structure Inference by Ergodic Hidden Markov Models.- Clustering of Gaussian Densities in Hidden Markov Models.- Developments in High-Performance Connected Digit Recognition.- Robust Speaker-Independent Hidden Markov Model Based Word Spotter.- Robust Speech Recognition in Noisy and Reverberant Environments.- An ISDN Speech Server based on Speaker Independent Continuous Hidden Markov Models.- RAMSES: A Spanish Demisyllable Based Continuous Speech Recognition System.- Speaker Independent, 1000 Words Speech Recognition in Spanish.- Continuously Variable Transition Probability HMM for Speech Recognition.- 2 Continuous Speech Recognition Systems.- Invited papers.- Context-Dependent Phonetic Hidden Markov Models for Speaker-Independent Continuous Speech Recognition (Abstract).- Speaker-Independent Continuous Speech Recognition Using Continuous Density Hidden Markov Models.- Contributed papers.- A Fast Lexical Selection Strategy for Large Vocabulary Continuous Speech Recognition.- Performance of a Speaker-Independent Continuous Speech Recognizer.- Automatic Transformation of Speech Databases for Continuous Speech Recognition.- Iterative Optimization of the Data Driven Analysis in Continuous Speech.- Syllable-based Stochastic Models for Continuous Speech Recognition.- Word Hypothesization in Continuous Speech Recognition.- Phone Recognition Using High Order Phonotactic Constraints.- An Efficient Structure for Continuous Speech Recognition.- Search Organization for Large Vocabulary Continuous Speech Recognition.- 3 Connectionist Models of Speech.- Invited papers.- Neural Networks or Hidden Markov Models for Automatic Speech Recognition: Is there a Choice?.- Neural Networks for Continuous Speech Recognition.- Connectionist Large Vocabulary Speech Recognition.- The Cortical Column as a Model for Speech Recognition: Principles and First Experiments.- Contributed papers.- Radial Basis Functions for Speech Recognition.- Phonetic Features Extraction Using Time-Delay Neural Networks.- Improved Broad Phonetic Classification and Segmentation with an Auditory Model.- Automatic Learning of a Production Rule System for Acoustic-Phonetic Decoding.- 4 Stochastic Models for Language and Dialogue.- Invited papers.- Stochastic Grammars and Pattern Recognition.- Basic Methods of Probabilistic Context Free Grammars.- A Probabilistic Approach to Person-Robot Dialogue.- Contributed papers.- Experimenting Text Creation by Natural-Language, Large-Vocabulary Speech Recognition.- DUALGRAM: An Efficient Method for Representing Limited-Domain Language Models.- Strategies for Speech Recognition and Understanding Using Layered Protocols.- 5 Understanding and Dialogue Systems.- Invited papers.- TINA: A Probabilistic Syntactic Parser for Speech Understanding Systems.- The Voyager Speech Understanding System: A Progress Report.- The Interaction of Word Recognition and Linguistic Processing in Speech Understanding.- Linguistic Processing in a Speech Understanding System.- Contributed papers.- Linguistic Tools for Speech Recognition and Understanding.- Evidential Reasoning and the Combination of Knowledge and Statistical Techniques in Syllable Based Speech Recognition.- 6 Speech Analysis, Coding and Segmentation.- Contributed papers.- Data Base Management for Use with Acoustic-Phonetic Speech Data Bases.- BPF Outputs Compared with Formant Frequencies and LPCs for the Recognition of Vowels.- A Codification of Error Signal by Splines Functions.- Specific Distance for Feature Selection in Speech Recognition.- Multiple Template Modeling of Sublexical Units.- Learning Structural Models of Sublexical Units.- On the Use of Negative Samples in the MGGI Methodology and its Application for Difficult Vocabulary Recognition Tasks.- A New Method for Dynamic Time Alignment of Speech Waveforms.- A New Technique for Automatic Segmentation of Continuous Speech.- Segmentation of Speech based upon a Linear Model of the Effects of Coarticulation 549 P.J. D.

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Book SynopsisEinleitung.- Grundlagen der Künstliche Intelligenz.- Die 7 Säulen und 33 Sprichwörter für KI-Werte-Leitlinien.- Mensch-Maschine Interaktionsmodelle ein Schlüsselfaktor für die Transparenz und Akzeptanz von KI-Technologien.- Ein Exkurs zum EU-AI Act und wichtige Punkte für Unternehmen.- Handlungsplan zur Umsetzung der KI-Leitlinien.- Experteninterviews aus Wirtschaft, Beratung und Forschung.- Fazit und Ausblick.

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Book SynopsisThere is a tremendous interest among researchers for the development of virtual, augmented reality and games technologies due to their widespread applications in medicine and healthcare. To date the major applications of these technologies include medical simulation, telemedicine, medical and healthcare training, pain control, visualisation aid for surgery, rehabilitation in cases such as stroke, phobia and trauma therapies. Many recent studies have identified the benefits of using Virtual Reality, Augmented Reality or serious games in a variety of medical applications.This research volume on Virtual, Augmented Reality and Serious Games for Healthcare 1 offers an insightful introduction to the theories, development and applications of virtual, augmented reality and digital games technologies in medical and clinical settings and healthcare in general. It is divided into six sections: section one presents a selection of applications in medical education and healthcare management; Section two relates to the nursing training, health literacy and healthy behaviour; Section three presents the applications of Virtual Reality in neuropsychology; Section four includes a number of applications in motor rehabilitation; Section five aimed at therapeutic games for various diseases; and the final section presents the applications of Virtual Reality in healing and restoration.This book is directed to the healthcare professionals, scientists, researchers, professors and the students who wish to explore the applications of virtual, augmented reality and serious games in healthcare further.Table of ContentsApplications in Healthcare Education.- Nursing Training, Health Literacy, and Healthy Behaviour.- Applications in Neuropsychology.- Applications in Motor Rehabilitation.- Therapeutic Games aimed at Various Diseases.- Virtual Healing and Restoration.

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Book SynopsisThe field of AI is not new to researchers, as its foundations were established in the 1950s. After many decades of inattention, there has been a dramatic resurgence of interest in AI, fueled by a confluence of several factors. The benefits of decades of Dennard scaling and Moore’s law miniaturization, coupled with the rise of highly distributed processing, have led to massively parallel systems well suited for handling big data. The widespread availability of big data, necessary for training AI algorithms, is another important factor. Finally, the greatly increased compute power and memory bandwidths have enabled deeper networks and new algorithms capable of accuracy rivaling that of human perception. Already AI has shown success in many diverse areas, including finance (portfolio management, investment strategies), marketing, health care, transportation, gaming, defense, robotics, computer vision, education, search engines, online assistants, image/facial recognition, anomaly detection, spam filtering, online customer service, biometric sensors, and predictive maintenance, to name a few. Despite these remarkable advances, the human brain is still superior in many ways – including, notably, energy efficiency and one-shot learning – giving researchers new areas to explore. In summary, AI research and applications will continue with vigor in software, algorithms, and hardware accelerators. These exciting developments have also brought new questions of ethics and privacy, areas which must be studied in tandem with technological advances. To continue the success story of AI, the AI Compute symposium was launched with the sponsorship of IBM, IEEE CAS and EDS for the first time. The aim of this publication is to compile all the materials presented by the renowned speakers in the symposium into a book format, serving as a learning tool for the audience. This book contains two broad topics: general AI advances (chapters 1-5) and neuromorphic computing directions (chapters 6-9). Technical topics discussed in the book include: 1. Research Directions in AI algorithms and systems 2. An ARM perspective on hardware requirements and challenges for AI 3. The new Era of AI hardware 4. AI and the Opportunity for Unconventional Computing Platforms 5. Thermodynamic Computing 6. Brain-like cognitive engineering system 7. BRAINWAY and Nano - Abacus architecture: Brain-inspired Cognitive Computing using Energy Efficient Physical Computational Structures, Algorithms and Architecture Co-Design 8. Applying Lessons from Nature for Today’s Computing Challenges 9. Emerging Memories - RRAM Fabric for Neuromorphic Computing ApplicationsTable of ContentsPreface 1. Research Directions in AI algorithms and systems - Lisa Amini 2. An ARM perspective on hardware requirements and challenges for AI – Robert Aitken 3. The new Era of AI hardware - Jeff Burns 4. AI and the Opportunity for Unconventional Computing Platforms – Naveen Verma 5. Thermodynamic Computing – Todd Hylton 6. Brain like cognitive engineering system - Jan Rabaey 7. BRAINWAY and Nano - Abacus architecture: Brain -inspired Cognitive Computing using Energy Efficient Physical Computational Structures, Algorithms and Architecture Co-Design - Andreas Andreou 8. Applying Lessons from Nature for Today’s Computing Challenges – Mike Davies 9. RRAM Fabric for Neuromorphic Computing Applications – Wei Lu

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Book SynopsisThe general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses – querying, data mining, data analysis – is addressed by current technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations.Table of ContentsIntroduction.- Knowledge Representation Using Formal Logic.- Quantifying and Managing Uncertainty.- Representing Temporal Knowledge.- Temporal Reasoning.- Representing and Reasoning On Spatial Knowledge.- Representing and Reasoning on Contextual Knowledge.- Causal Reasoning.- Extracting Logical Knowledge from Raw Data.- Scalable Spatiotemporal Logical Knowledge Storage.- Mining Patterns from Large Spatiotemporal Logical Knowledge Stores.- Probabilistic Logic Networks.- Temporal and Contextual Reasoning in PLN.- Inferring the Causes of Observed Changes.-Adaptive Inference Control.

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Book SynopsisSoftware is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)

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Book SynopsisThis book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.Table of Contents1. Introduction to Artificial Intelligence 2. Fuzzy logic and reasoning 3. Knowledge representation 4. Expert system 5. Information fusion 6. Time series analysis 7. Process mining 8. Simulation and optimization 9. Natural language processing 10. Computer vision 11. Conclusions

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Book SynopsisThis book introduces methods to analyze legal documents such as negotiation records and legal precedents, using computational argumentation theory.First, a method to automatically evaluate argumentation skills from the records of argumentation exercises is proposed. In law school, argumentation exercises are often conducted and many records of them are produced. From each utterance in the record, a pattern of “speech act +factor” is extracted, and argumentation skills are evaluated from the sequences of the patterns, using a scoring prediction model constructed by multiple regression analyses between the appearance pattern and the scoring results. The usefulness of this method is shown by applying it to the example case “the garbage house problem”. Second, a method of extracting factors (elements that characterize precedents and cases) and legal topoi from individual precedents and using them as the expression of precedents to analyze how the pattern of factors and legal topoi appearing in a group of precedents affects the judgment (plaintiff wins/defendant wins) is proposed. This method has been applied to a group of tax cases. Third, the logical structure of 70 labor cases is described in detail by using factors and a bipolar argumentation framework (BAF) and an (extended argumentation framework (EAF) together. BAF describes the logical structure between plaintiff and defendant, and EAF describes the decision of the judge. Incorporating the legal topoi into the EAF of computational argumentation theory, the strength of the analysis of precedents by combined use of factored BAF and EAF, not only which argument the judge adopted could be specified. It was also possible to determine what kind of value judgment was made and to verify the logic. The analysis methods in this book demonstrate the application of logic-based AI methods to the legal domain, and they contribute to the education and training of law school students in logical ways of argumentation.Table of ContentsChapter 1. Introduction .- Chapter 2. Related Research.- Chapter 3.- Factor-Based Argumentation Evaluation.- Chapter 4. Case Analysis Using Factors and Legal Topoi.- Chapter 5. Case Analysis for Case Law Education using Factors and Computational Argumentation Theory.- Chapter 6. Conclusion.

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Book SynopsisThis book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 7th International Conference on ICT for Sustainable Development (ICT4SD 2022), held in Goa, India, on 29–30 July 2022. The book covers the topics such as big data and data mining, data fusion, IoT programming toolkits and frameworks, green communication systems and network, use of ICT in smart cities, sensor networks and embedded system, network and information security, wireless and optical networks, security, trust, and privacy, routing and control protocols, cognitive radio and networks, and natural language processing. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.Table of Contents1. Survey Paper on Multi-View Object Detection: Challenges and Techniques.- 2. Exploring the Scheduling techniques for the RTOS.- 3. Grid Power Smoothing Management for Direct Drive PMSG Variable Speed Wind Energy Conversion System with Multilevel Converter.- 4. Fall Detection using Transformer Model.- 5. Survey on various IOT based irrigation techniques in India.- 6. Empirical analysis of crop-yield analysis and disease detection systems: A statistical perspective.- 7.Analysis of Public Perception of Autonomous Vehicles Based on Unlabelled Data from Twitter.- 8. DFCNNet: A Convolutional Neural Network to Detect Deepfakes.- 9. White Blood Cells Classification Using Deep Learning Technique.- 10. Comparative Analysis of Convolutional Neural Network in Object Detection.- 11. A Review of the Applications and Future Scope of Artificial Intelligence in Smart Transport.- 12.Besuited EEG Signal Analysis for Stress Monitoring Using BIONIC Sensor.- 13. Publish –Subscribe With Iot For A Smart Soil Moisture Irrigation System.- 14. An Optimized Taxonomy And Identification Of Retinal Eye Diseases For Diabetes Patients Using CNN.- 15. Axiomatically Designed Research Support Systems.- 16. Detection Of Hepatitis-B Virus Using NFC-Enabled Smartphone Based Portable Amperometric Immunosensor.- 17. Encrypto – Decrypto.- 18. Enhancing the employability of engineering graduates: An assertion on fundamental educational aspect of engineering education with proposing a hypothesis of ‘Wishing Theory’ based on prospective machine learning model.- 19. UpMove DownMove Strategy using NeuralNetwork Techniques For The Prediction Of Stock Prices.- 20. Breast Cancer Detection Using Bag Of visual Words.- etc.

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Book SynopsisThis book includes selected papers presented at World Conference on Information Systems for Business Management (ISBM 2022), held in Bangkok, Thailand, during September 2–3, 2022. It covers up-to-date cutting-edge research on data science, information systems, infrastructure and computational systems, engineering systems, business information systems, and smart secure systems.Table of Contents Social Media as Communication-Transformation Tools.- Bi directional DC-DC converter-based Energy Storage Method for Electric Vehicles.- Design of Smart Irrigation System in Sone Command Area Bihar for Paddy Crop.- A Footstep to Image Deconvolution Technique for the both Known and Unknown Blur Parameter.- Secured Monitoring of Unauthorized UAV by Surveillance Drone Using NS2.

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Book SynopsisThis book gathers the proceedings of the Multidisciplinary International Conference of Research Applied to Defense and Security (MICRADS 2022), held at Escuela Naval de Suboficiales ARC "Barranquilla," in Barranquilla, Colombia, during July 11–13, 2022. It covers a broad range of topics in systems, communication, and defense; strategy and political–administrative vision in defense; and engineering and technologies applied to defense. Given its scope, it offers a valuable resource for practitioners, researchers, and students alike.Table of ContentsDetection of Highly Energetic Materials using Infrared Spectroscopy Coupled with Chemometrics.- Platform for Interactive Audiovisual Productions and Generative Art using Processing.- Feasibility Study of the Use of Petri Nets in the Verification of UML Diagrams.- Maturity Model for Boards of Directors in Cyber Risk Governance. A Conceptual and Practical Proposal.- A Visual Graph Approach for Evaluating the Vulnerability of ENC Standards.- Bibliometric Analysis on Cibersegurity: Spoofing Attack Technique and Evolution.- Centralized Management IoT Platform.- Application of the Criterion of Total Movement Minimization in the Ammunition Area of an Armament Factory.- Sweat as a Testing Analytical Fluid for Emotions and Stress Biomarkers Detection.- Statistical Processing of Relationship Between Biomarkers and Disease Severity Caused by Covid-19 Infection-Delta Variant.- Sustainable Development in Higher Education Curricula for Software Engineering Chairs.- Evaluation of Digital Skills. Educating Middle School and High School Students on Cyber Risks.

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Book Synopsis

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Book SynopsisOptimizing The Selection Of Circular Economy Indicators Through A Large-Scale Comprehensive Minimum Cost Consensus Model.- Decision Making For Uncertainty In Spatial Data Using Intuitionistic Fuzzy Sets.- Q-Rung Orthopair Fuzzy Electre Based Multicriteria Decision Model For Green Supplier Selection.- An Integrated Intuitionistic Fuzzy Critic-Aras Method And Its Application in Health-Care Waste Treatment Method Selection.- Threat Evaluation For Dynamic Targets Using Q-Rung Orthopair Soft Rough Fuzzy Multi-Criteria Decision-Making.- Renewable Energy Policy Selection Based On Fermatean Fuzzy Promethee Method.- Multiple Criteria Decision-Making Method Based On Spherical Fuzzy Aggregation Operators With Application In Covid-19 Testing Facility.- Archimedean Norms-Based Choquet Integral Operators For Single-Valued Neutrosophic Linguistic Sets And Their Application To Decision Making.- Sustainable Oil And Gas Supplier Selection Based On Pythagorean Fuzzy Topsis and Vikor Method: A Comparative Analysis.- Failure Mode and Effect Analysis (Fmea) Of Different Types Of Cancer Treatments.- A Reliability Allocation Strategy For Gear Transmission System Of High-Speed Train Based On Prospect Theory.- Cubic Analytic Hierarchy Process With Application In Decision Making.- Determination Of Best Renewable Energy Sources In India Using Swara[1]Aras In Confidence Level Based Interval-Valued Intuitionistic Fuzzy Environment.- Modeling And Analyzing Innovation Diffusion Process Through Multi Stage Approach.- Decision Support System For The Assessment Of Emergency Logistics Supplier By Using An Integrated Q-Rung Orthopair Fuzzy Marcos Method.- Uncertainty In Mathematics Educations: How To Make A Decision With Sustainable And Gamified Mcda/F-Dematel Method.- Feature-Based Inventory Management With Demand Substitution: A Grg-Based Approach Incorporating Fuzzy Constraints.- An Eoq Model Of A Fresh Product Having Variable Demand Under Trade Credit Policy Considering Default Risk.- Decision Making Process Under Uncertain Domain Of Pythagorean Fuzzy Sets Based On An Enhanced Similarity Operators Heuristic Solutions For Interval Valued Games.- On The Study Of Multi-Objective Adjacent Only Quadratic Minimum Spanning Tree Problem Under The Paradigm Of Fuzzy Environment.- Root Hair Algorithm: A Swarm Intelligence Algorithm.

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