Artificial intelligence (AI) Books

Book SynopsisThis book contains the refereed proceedings of the Cybernetics Perspectives in Systems session of the 11th Computer Science On-line Conference 2022 (CSOC 2022), which was held in April 2022 online. Papers on modern cybernetics and informatics in the context of networks and systems are an important component of current research issues. This volume contains an overview of recent method, algorithms and designs.

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Book SynopsisThis book presents a comprehensive study in the field of advances in medical data science and contains carefully selected articles contributed by experts of information technology. Continuous growth of the amount of medical information and the variety of multimodal content necessitates the demand for a fast and reliable technology able to process data and deliver results in a user-friendly manner at the time and place the information is needed. Computational approaches for understanding human complexity, AI-powered applications in image and signal processing, bioinformatics, sound and motion as activity stimulus, joint activities in biomedical engineering and physiotherapy, disorder in children, selected comparative studies give new meaning to optimization of the functional requirements of the healthcare system for the benefit of the patients. It is an interdisciplinary collection of papers that have both theoretical and applied dimensions. It includes the following research areas: Computational methods for understanding human complexity Image and signal analysis Multidimensional medical data analysis Sound and motion Joint activities in biomedical engineering and physiotherapy This book is a great reference tool for scientists who deal with problems of designing and implementing information processing tools employed in systems that assist the clinicians, radiologists, and physiotherapists in patient diagnosis and treatment. It also serves students in exploring innovations in quantitative medical data analysis, data mining, and artificial intelligence.Table of ContentsClassifying Changes in Motion Behaviour Due to a Hospital Stay Using Floor Sensor Data – a Single Case Study.- Cloud-Based System for Vital Data Recording at Patients’ Home.- Tele-BRAIN Diagnostics Support System for Cognitive Disorders in Parkinson’s Patients.- EEG Signal and Deep Learning Approach in Evaluation of Cognitive Declines in Parkinson’s Disease.- Construction of a Cephalometric Image Based on Magnetic Resonance Imaging Data.- A Revealed Imperfection in Concept Drift Correction in Metabolomics Modeling.- The Influence of Low-Intensity Pulsed Ultrasound (LIPUS) on the Properties of PLGA Biodegradable Polymer Coatings on Ti6Al7Nb Substrate.

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Book SynopsisThis edited book presents scientific results of the 20th IEEE/ACIS International Conference on Software Engineering Research, Management, and Applications (SERA2022) held on May 25, 2022, in Las Vegas, USA. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 12 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.Table of ContentsExamining the Factors that Influence Customers’ Intention to Use Smartwatches in Malaysia Using UTAUT2 Model.- Generating Adversarial Robust Defensive CAPTCHA (GARD-CAPTCHA) in Convolutional Neural Networks.- A Deep Learning Approach for Lantana Camara Weed Detection and Localization in the Natural Environment.- Modeling Concretizations in Software Design.- A Practical Style Guide and Templates Repository for Writing Effective Use Cases.- Label Correction of Sound Data with Label Noise Using Self Organizing Map.- Evaluation Method of Enterprise Cybersecurity.- A Multi-model Multi-task Learning System for Hurricane Genesis Prediction.- Development of Autonomous Driving Adaptive Simulation System Using Deep Learning Process Model.- An OCL Implementation for Model-Driven Engineering of C++.- Improving Students’ Readiness Toward the Labor Market Through Customized Learning.- Assessing Software Fault Risk with Machine Learning.

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Book SynopsisThis book presents recent research in intelligent and fuzzy techniques on digital transformation and the new normal, the state to which economies, societies, etc. settle following a crisis bringing us to a new environment. Digital transformation and the new normal-appearing in many areas such as digital economy, digital finance, digital government, digital health, and digital education are the main scope of this book. The readers can benefit from this book for preparing for a digital “new normal” and maintaining a leadership position among competitors in both manufacturing and service companies. Digitizing an industrial company is a challenging process, which involves rethinking established structures, processes, and steering mechanisms presented in this book. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying digital transformation and new normal. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.

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Book SynopsisThis book constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, held in Halifax, NS, Canada, in June 2022. The 39 full papers presented together with 7 short papers were selected from 113 submissions. The papers are grouped in topical sections on knowledge-based system; machine learning; medical image processing; predictive modeling; natural language processing.Table of ContentsKnowledge-Based Systems Explainable Decision Support Using Task Network Models in Notation.- Computerizing Lipid Management Clinical Guidelines as Interactive Task Networks.- Towards an AI planning-based pipeline for the management of multimorbid patients.- A Knowledge Graph Completion Method Applied to Literature-Based Discovery for Predicting Missing Links Targeting Cancer Drug Repurposing.- Ontological Representation of Causal Relations for a Deep Understanding of Associations between Variables in Epidemiology.- Explainable Clinical Decision Support: Towards Patient-Facing Explanations for Education and Long-term Behavior Change.- Machine Learning Assessing Knee Biomechanical Osteoarthritis Severity and Biomechanical Changes After Total Knee Arthroplasty Using Self-Organizing Maps.- NeuralSympCheck: A Symptom Checking and Disease Diagnostic Neural Model with Extracting Surrogate Decision Trees from Black-box Models to Explain the Temporal Importance of Clinical Features in Predicting Kidney Graft Survival.- Recurrence and Self-Attention vs the Transformer for Time-Series Classification: A Comparative Study.- Integrating Graph Convolutional Neural Networks and Long Short-Term Memory for Efficient Diagnosis of Autism.- Hierarchical Deep Multi-task learning for Classification of Patient Diagnoses.- TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network.- Predicting Next Kidney Offer for Transplant Candidate Declining Current One.- Wrist Ultrasound Segmentation by Deep Learning.- Early Detection and Classification of Patient-Ventilator Asynchrony using Machine Learning.- On graph construction for classification of clinical trials protocols using Graph Neural Networks.- Medical Image Processing Malignant Mesothelioma Subtyping of Tissue Images via Sampling Driven Multiple Instance Prediction.- Calibrating Histopathology Image Classifiers using Label Smoothing.- InvUNET: Involuted UNET for Breast Tumor Segmentation from Ultrasound.- MRI reconstruction with LassoNet and compressed sensing.- Predictive Modeling A 3-window-based framework for the discovery of predictive functional dependencies from clinical data.- When can I expect the mHealth user to return? Prediction meets time series with gaps.- A novel survival analysis approach to predict the need for intubation in intensive care units.- Awareness of being tested and its effect on reading behaviour.- Natural Language Processing Generating extremely short summaries from the scientific literature to support decisions in primary healthcare: a human evaluation study.- A Russian Medical Language Understanding Benchmark.- Biomedical Semantic Textual Similarity: Evaluation of Sentence Representations Enhanced With Principal Component Reduction and Word Frequency Weighting.

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Book SynopsisThe book, “Intelligent Computing - Proceedings of the 2022 Computing Conference”, is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world. Each chapter is a paper presented at the Computing Conference 2022 held on July 14-15, 2022. Computing 2022 attracted a total of 498 submissions which underwent a double-blind peer-review process. Of those 498 submissions, 179 submissions have been selected to be included in this book. The goal of this conference is to give a platform to researchers with fundamental contributions and to be a premier venue for academic and industry practitioners to share new ideas and development experiences. We hope that readers find this book interesting and valuable as it provides the state-of-the-art intelligent methods and techniques for solving real-world problems. We also expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject. Table of ContentsWearable Internet of Things (IoT) Device Model Design based on Low-Cost Healthcare Monitoring System for Current Covid-19 Disease.- A Matching Mechanism for Provision of Housing to the Marginalized.- Speed Harmonisation Strategy for Human-Driven and Autonomous Vehicles Co-existence.- Road Intersection Coordination Scheme for Mixed Traffic (Human Driven and Driver-less Vehicles): A Systematic Review.- Selection of Driving Mode in Autonomous Vehicles based on Road Profile and Vehicle Speed.- Compass Errors in Mobile Augmented Reality Navigation Apps: Consequences and Implications.- Leveraging Zero Trust Security Strategy to Facilitate Compliance to Data Protection Regulations.- Perspectives from 50+ Years’ Practical Zero Trust Experience and Learnings on Buyer Expectations and Industry Promises.- Bit Error Rate Analysis of Pre-formed ReRAM-based PUF.

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Book SynopsisThis book provides an essential compilation of relevant and cutting edge academic and industry work on key Blockchain topics. This book concentrates on a wide range of advances related to Blockchains which include, among others, Blockchain principles, architecture and concepts with emphasis on key and innovative theories, methodologies, schemes and technologies of Blockchain, Blockchain platforms and architecture, Blockchain protocols, sensors and devices for Blockchain, Blockchain foundations, and reliability analysis of Blockchain-based systems. Further, it provides a glimpse of future directions where cybersecurity applications are headed. The book is a rich collection of carefully selected and reviewed manuscripts written by diverse cybersecurity application experts in the listed fields and edited by prominent cybersecurity applications researchers and specialists.Table of ContentsPart I: Blockchain Fundamentals1 Fundamentals of Blockchain Technology2 Identification of Illicit Blockchain Transactions Using Hyperparameters Auto-tuning3 Multidimensional Blockchain: Construction and Security Analysis 4 Blockchain Project Workflow Execution for Trustless Operations Part 2 Blockchains in Internet of Things and Mobile Phones 5 Protecting Location Privacy in Blockchain-based Mobile Internet of Things 6 A Blockchain Based Machine Learning Intrusion Detection System for Internet of Things 7 ECOM: Epoch Randomness-based Consensus Committee Configuration for IoT-Blockchains 8 Customer Outcome Framework for Blockchain-based Mobile Phone Applications Part 3 Blockchains and Healthcare 9 A Secure Decentralized Privacy-Preserving Healthcare System Using Blockchain 10 An Investigation of Blockchain Technology and Smart Contracts Deployment in Smart Medicine 4.0 Part 4 Blockchains and Currency 11 Post-Quantum Digital Signatures for Bitcoin 12 Cyber Laundering: Money Laundering from Fiat Money to Cryptocurrency Part 5 Blockchains in Education, Governance, Supply Chain, and Security 13 A Blockchain-based Fair and Transparent Homework Grading System for Online Education 14 Improving Supply Chain Management Performance with Blockchain Technology 15 Using Blockchain to Improve Corporate Governance 16 Blockchain Security as “People Security”: Applying Sociotechnical Security to Blockchain Technology

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Book SynopsisThis book constitutes the refereed proceedings of the 4th International Conference on Intelligent Technologies and Applications, INTAP 2021, held in Grimstad, Norway, October 11–13, 2021.The 33 full papers included in this book were carefully reviewed and selected from 243 submissions. They were organized in topical sections as follows: Intelligence, Decision support systems, IoT; Robotics; ML and AI for Intelligent Health, Applications of intelligent technologies in Emergency Management; Smart Electrical Energy Systems, AI and ML in Security; ML and AI for sensing technologies, Social Media Analytics; ML in energy sectors and materials; and Miscellaneous.Table of ContentsIntelligence, Decision support systems, IoT.- Dense Nearest Neighborhood Query.- Explainable nonlinear modelling of multiple time series with invertible neural networks.- Iterative Learning for Semi-automatic Annotation Using User Feedback.- Residual Stress Prediction of Welded Joints Using Gradient Boosting Regression.- A Novel Group Teaching Optimization Algorithm based Artificial Neural Network for Classification.- On the Effects of Properties of the Minibatch in Reinforcement Learning.- A novel migration simulation and prediction tool.- Development Environment for Software-defined Smart City Networks.- Robotics.- Branch-Manoeuvring Capable Pipe Cleaning Robot for Aquaponic Systems.- A Multi-Modal Auditory-Visual-Tactile e-Learning Framework.- A Perspective on Intervention Approaches for Children with Autism Spectrum Disorder.- framework for hazard identification of a collaborative Plug&Produce system.- ML and AI for Intelligent Health, Applications of intelligent technologies in Emergency Management.- Future Perspectives on Automated Machine Learning in Biomedical Signal Processing.- DeepFireNet - A Light-Weight Model for Fire-Smoke Classification.- Smart Electrical Energy Systems, AI and ML in Security.- THD Reduction Comparison of Three Phase SPPS via Conventional RC and Novel PRESH Controller.- Artificial Neural Network (ANN) trained by a Novel Arithmetic Optimization Algorithm (AOA) for Short Term Forecasting of Wind Power.- Bode Plot Analysis of PRES and Novel PRESH controller interfaced with three phase GTSPPS.- Energy tracing and blockchain technology: a primary review.- Emulation of IEC 60870-5-104 Communication in Digital Secondary Substations.- ML and AI for sensing technologies, Social Media Analytics.- Point Cloud Instance Segmentation for Automatic Electric Vehicle Battery Disassembly.- Radar-Based Passive Step Counter and its Comparison with a Wrist-Worn Physical Activity Tracker.- Principles for the Arrangement of Social Media Listening Practices in Crisis Management.- AMUSED: An Annotation Framework of Multi-modal Social Media Data.- ML in energy sectors and materials.- An evaluation of predictor variables for photovoltaic power forecasting.- Smart Meter Data Anomaly Detection using Variational Recurrent Autoencoders with Attention.- Detecting the linear and non-linear causal links for disturbances in the power grid.- Machine Learning for PV System Operational Fault Analysis: Literature Review.- Miscellaneous.- An overview of Data Based Predictive Modeling Techniques used in Analysis of Vehicle Crash Severity.- An Evaluation of Autonomous Car Simulators and their applicability for Supervised and Reinforcement Learning.- Classification of Mechanical Fault-Excited Events based on Frequency.- Intelligent Technologies in the Process of Recovering Historical, Cultural, and Heritage Value in Native Communities.- Tensile Experiments on Adhesion between Aluminium Profiles and Glass.- Machine learning for capacity utilization along the routes of an urban freight service.

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Book SynopsisThis book provides practical guidance and awareness for a growing body of knowledge developing across a variety of disciplines. This initiative is a celebration of the Gavriel Salvendy International Symposium (GSIS) and provides a survey of topics and emerging areas of interest in human–automation interaction. This set of articles for the GSIS emphasizes a main thematic areas: mobile computing. Main areas of coverage include Section A: Health, Care and Assistive Technologies; Section B: Usability, User Experience and Design; Section C: Virtual Learning, Training and Collaboration; Section D: Ergonomics in Work, Automation and Production. In total, there are more than 600 pages emphasizing contributions from especially early career researchers that were featured as part of this (virtual) symposium and celebration. Gavriel Salvendy initiated the conferences that run annually as Human–Computer Interaction within LNCS of Springer and Applied Human Factors and Ergonomics International (AHFE). The book is inclusive of human–computer interaction and human factors and ergonomics principles, yet is intended to serve a much wider audience that has interest in automation and human modeling. The emerging need for human–automation interaction expertise has developed from an ever-growing availability and presence of automation in our everyday lives. This initiative is intended to provide practical guidance and awareness for a growing body of knowledge developing across a variety of disciplines and many countries. Table of ContentsDon’t Stand so Close to Me: Acceptance of delegating intimate health care tasks to assistive robots.- Designing a Voice Intelligent Agent: A Review and Appraisal.- Job crafting & re-design in a rapidly changing world of work: A bibliometric analysis & review.- Resilience Engineering and Safe Work Method Statements in Construction Projects.- Agent Transparency for Human-Autonomy Teaming.- Cuteness Engineering and UX Design.- Small screen-large information challenge for older adults: navigating through big pictures and menus of mobile phones.

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Book SynopsisArtificial intelligence (AI) and machine learning (ML) have transformed many standard and conventional methods in undertaking health and well-being issues of humans. AL/ML-based systems and tools play a critical role in this digital and big data era to address a variety of medical and healthcare problems, improving treatments and quality of care for patients. This edition on AI and ML for healthcare consists of two volumes. The first presents selected AI and ML studies on medical imaging and healthcare data analytics, while the second unveils emerging methodologies and trends in AI and ML for delivering better medical treatments and healthcare services in the future.In this first volume, progresses in AI and ML technologies for medical image, video, and signal processing as well as health information and data analytics are presented. These selected studies offer readers theoretical and practical knowledge and ideas pertaining to recent advances in AI and ML for effective and efficient image and data analytics, leading to state-of-the-art AI and ML technologies for advancing the healthcare sector.Table of ContentsAn Introduction to Artificial Intelligence in Healthcare.- Radiomics: Approach to Precision Medicine.- Artificial Intelligence Based Strategies for Data-Driven Radial MRI.

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Book SynopsisThis book constitutes the refereed proceedings of the 12th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2022, held in Helsinki, Finland, in June 2022. The 13 full papers presented were carefully reviewed and selected from 21 submissions. The papers address various topics such as information and knowledge systems, including submissions that apply ideas, theories or methods from specific disciplines to information and knowledge systems. Examples of such disciplines are discrete mathematics, logic and algebra, model theory, databases, information theory, complexity theory, algorithmics and computation, statistics and optimization.Table of ContentsOn Sampling Representatives of Relational Schemas with a Functional Dependency.- On the expressive power of message-passing neural networks as global feature map transformers.- Assumption-Based Argumentation for Extended Disjunctive Logic Programming.- A graph based semantics for Logical Functional Diagrams in power plant controllers.- Database Repair via Event-Condition-Action Rules in Dynamic Logic.- Statistics of RDF store for querying knowledge graphs.- Can you answer while you wait?.- The implication problem for functional dependencies and variants of marginal distribution equivalences.- Approximate Keys and Functional Dependencies in Incomplete Databases With Limited domains.- The Fault-Tolerant Cluster-Sending Problem.- Optimizing multiset relational algebra queries using weak-equivalent rewrite rules.- Properties of System W and its Relationships to Other Inductive Inference Operators.- Towards the Evaluation of Action Reversibility in STRIPS using Domain Generators.

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Book SynopsisThis book tackles the problems of engineering students and teachers while developing language skills through language education, transforming students’ mind-set through cultural studies, developing students’ intellectual abilities and personal qualities, and the use of information technologies in order to enhance the educational process. The International Conference Integration of Engineering Education and the Humanities: Global Intercultural Perspectives will take place 20–22 April 2022. It will be organized by Peter the Great Saint Petersburg Polytechnic University (Saint Petersburg, Russia) in collaboration with Research Centre Kairos (Tomsk, Russia). The event aims to raise discussions around a variety of aspects related to the integration of the humanities into engineering education.As such, the book will be of interest to the teachers, researchers and institutional leaders looking for the latest insights, experiences and research results on the topic.

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Book SynopsisThis book systemically presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.Table of ContentsRDF Data and Management.- Fuzzy Sets and Fuzzy Database Modeling.- Fuzzy RDF Modeling.- Persistence of Fuzzy RDF and Fuzzy RDF Schema.- Fuzzy RDF Queries.

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Book SynopsisThis book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques, along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains, are discussed in this book and help global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. Novel ways are also discovered to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms leads beginners to apply current approaches to optimization problems. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract researchers and practitioners to apply hybrid metaheuristics in real scenarios.Table of ContentsPerformance analysis of Heuristic optimization algorithms for Transportation problem.- Source Code Features Based Branch Coverage Prediction using Ensemble Technique.- Implicit Methods of Multi-Factor Authentication.- Comparative Analysis of different Classifiers Using Machine Learning Algorithm for Diabetes Mellitus.- Survey on Machine Learning Techniques for Software Reliability Accuracy Prediction.- Classification of Pest in Tomato Plants using CNN.- Deep Neural Network Approach For Identifying Good Answers in Community Platforms.- Time Series Analysis of SAR-Cov-2 virus in India using Facebook’s Prophet.- Model-Based Smoke Testing Approach of Service Oriented Architecture (SOA).- Role of Hybrid Evolutionary Approaches for Feature Selection in Classification: A Review.- Evaluation of Deep Learning Models for Detecting Breast Cancer using Mammograms.- Evaluation of Crop Yield Prediction using arsenal and Ensemble Machine learning algorithms.- Notification Based Multichannel MAC (NM-MAC) Protocol for Wireless Body Area Network.- A multi Brain Tumor Classification using a Deep Reinforcement Learning Model.- A Brief Analysis on Security in Healthcare Data using Blockchain.- A Review on Test Case Selection, Prioritization and Minimization in Regression Testing.- Artificial Intelligence Advancement in Pandemic Era.- Predictive technique for Identification of Diabetes using Machine Learning.- Prognosis of Prostate Cancer Using Machine Learning.- Sign language Detection Using Tensorflow Object Detection.- Automated Test Case Prioritization using Machine Learning.- A New Approach To Solve Linear Fuzzy Stochastic Differential Equation.- An Improved Software Reliability Prediction Model by Using Feature Selection and Extreme Learning Machine.- Signal Processing Approaches for Encoded Protein Sequences in Gynaecological Cancer Hotspot Prediction: A Review.- DepNet: Deep Neural Network based model for Estimating the Crowd Count.- Dynamic Stability enhancement of Power system by Sailfish Algorithm tuned fractional SSSC control action.- Application of Machine Learning Model Based Techniques for Prediction of Heart Diseases.- Software Effort and Duration Estimation using SVM and Logistic Regression.- A framework for ranking cloud services based on an integrated BWM-Entropy-TOPSIS Method.- An Efficient and Delay-Aware Path Construction Approach Using Mobile Sink in Wireless Sensor Network.- Application of Different Control Techniques of multi-area Power Systems.- Analysis of An Ensemble Model For Network Intrusion Detection.- D2D Resource Allocation for Joint Power Control in Heterogeneous Cellular Networks.- Prediction of Covid-19 Cases in Kerala based on meteorological parameters using BiLSTM Technique.

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Book SynopsisThis book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.Table of ContentsAn Introduction to Federated and Transfer Learning.- Federated Learning for Resource-Constrained IoT Devices: Panoramas and State of the Art.- Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms.- Cross-silo Federated Neural Architecture Search for Heterogeneous and Cooperative Systems.- A Unifying Framework for Federated Learning.- A Contract Theory based Incentive Mechanism for Federated Learning.- A Study of Blockchain-based Federated Learning.- Swarm Meta Learning.- Rethinking Importance Weighting for Transfer Learning.- Transfer Learning via Representation Learning.- Modeling Individual Humans via a Secondary Task Transfer Learning Method.- From Theoretical to Practical Transfer Learning: The Adapt Library.- Lyapunov Robust Constrained-MDPs for Sim2Real Transfer Learning.- A Study on Efficient Reinforcement Learning Through Knowledge Transfer.- Federated Transfer Reinforcement Learning for Autonomous Driving.

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Book SynopsisBusiness shapes have been changed these days. Change is the main dominant fact that change the way of business operations running. Topics such as innovation, entrepreneurship, leadership, blockchain, mobile business, social media, e-learning, machine learning, and artificial intelligence become essential to be considered by each institution within the technology era. This book tries to give additional views on how technologies influence business and marketing operations for insuring successful institutions survival.The world needs to develop management and intelligent business scenario plans that suite a variety of crisis appears these days. Also, business and marketing intelligence should meet government priorities in individual countries and minimise the risk of business disruptions. Business intelligence - the strategies and technology companies that use it to collect, interpret, and benefit from data - play a key role in informing company strategies, functions, and efficiency. However, being essential to the success, many companies are not taking advantage of tools that can improve their business intelligence efforts. Information technology become a core stone in business. For example, the combination of machine learning and business intelligence can have a far-reaching impact on the insights the company gets from its available data to improve productivity, quality, customer service and more. This book is important because it introduces a large number of chapters that discussed the implications of different Information technology applications in business. This book contains a set of volumes which are: 1- Social Marketing and Social Media Applications, 2- Social Marketing and Social Media Applications, 3- Business and Data Analytics, 4- Corporate governance and performance, 5- Innovation, Entrepreneurship and leadership, 6- Knowledge management, 7- Machine learning, IOT, BIG DATA, Block Chain and AI, 8- Marketing Mix, Services and Branding.Table of ContentsAssessment of the Perception of Usage of Facebook as a Business Tool in SMEs through the Technological Acceptance Model (TAM) and Structural Equation Modeling.- Interdependencies and Integration of Smart Buildings and Smart Cities: A Case of Dubai.- Strategic leadership and its role on implementing public policies in the government departments in Karak Governorate.

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Book SynopsisThis book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations. Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden.

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Book SynopsisThis book constitutes the refereed proceedings of the 19th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2022, held in Sant Cugat, Spain, during August - September 2022.The 16 papers presented in this volume were carefully reviewed and selected from 41 submissions. The papers discuss different facets of decision processes in a broad sense and present research in data science, machine learning, data privacy, aggregation functions, human decision-making, graphs and social networks, and recommendation and search. They were organized in topical sections as follows: Decision making and uncertainty; Data privacy; Machine Learning and data science.Table of Contents​Decision making and uncertainty.- Optimality Analysis for Stochastic LP Problems.- A Multi-Perceptual-Based Approach for Group Decision Aiding.- Probabilistic Judgement Aggregation by Opinion Update.- Semiring-valued fuzzy rough sets and colour segmentation.- Data privacy.- Bistochastic privacy.- Improvement of Estimate Distribution with Local Differential Privacy.- Geolocated Data Generation and Protection Using Generative Adversarial Net-works.- Machine Learning and data science.- A Strategic Approach based on AND-OR Recommendation Trees for Updating Obsolete Information.- Identification of Subjects Wearing a Surgical Mask from their Speech by means of x-vectors and Fisher Vectors.- Measuring Fairness in Machine Learning models via Counterfactual Examples.- Re-Calibrating Machine Learning Models using Confidence Interval Bounds.- An Analysis of Byzantine-Tolerant Aggregation Mechanisms on Model Poisoning in Federated Learning.- Effective Early Stopping of Point Cloud Neural Networks.- Representation and Interpretability of IE Integral Neural Networks.- Deep Attributed Graph Embeddings.- Estimation of Prediction Error with Regression Trees.

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Book SynopsisThis book presents recent advancements in Industry 4.0 and addresses how these can be useful in achieving sustainable solutions in Society 5.0. The book also serves as a reference for developing sustainable engineering solutions to various socio-economic and techno-commercial issues. The book is meticulously structured into two sections: Section I sheds light on fundamentals, nitty-gritties, and principles of technological innovations and advancement in artificial intelligence, cloud computing, industrial Internet of Things (IIOT), and Society 5.0, whereas Section II covers viable engineering solutions developments for revamping Industry 4.0 to Society 5.0. Overall, the authors aim to show how technological advancements can be used to address social issues and improve society.Table of ContentsIntroduction.- Sustainable computing in Healthcare.- IoT for Contemporary Life.- Artificial Intelligence in Multimedia Technology.- Artificial Intelligence in Security and Surveillance.- Artificial Intelligence in Big Data Analytics.- Engineering design for sustainable development using IOT/AI.- Intelligent and Smart Grid Systems.- Sustainable computing in Energy conservation.- Sustainable computing in Society 5.0.- Artificial Intelligence in Geo-Politics.- Cyber Physical System for Social Problems.- Artificial Intelligence and Machine Learning in Healthcare.- Open Challenges in Society 5.0.- Economic empowerment using AI/ML/IoT.- Machine Learning and Computing for Sustainable Development Goals.- Deep Learning for Society 5.0.- Intelligent and Smart Farming for Society 5.0.- Technological Innovation in Industry 4.0.- Artificial Intelligence in E-Governance.- Deep Learning in E-Governance.- Conclusion.

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Book SynopsisThis two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.Table of ContentsEvolutionary Computing and Learning. Neural Networks.- Pattern Recognition.- Image Processing.- Information Security.- Biomedical Informatics Theory and Methods.- Biomedical Data Modeling and Mining.- Intelligent Computing in Computational Biology.- Computational Genomics and Biomarker Discovery.- Intelligent Computing in Drug Design.- Theoretical Computational Intelligence and Applications.- Fuzzy Theory and Algorithms.- Machine Learning and Data Mining.- Intelligent Computing in Computer Vision.- Intelligent Control and Automation.- Intelligent Data Analysis and Prediction.- Intelligent Computing and Optimization.

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Book SynopsisThis two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.Table of ContentsEvolutionary Computing and Learning. Neural Networks.- Pattern Recognition.- Image Processing.- Information Security.- Biomedical Informatics Theory and Methods.- Biomedical Data Modeling and Mining.- Intelligent Computing in Computational Biology.- Computational Genomics and Biomarker Discovery.- Intelligent Computing in Drug Design.- Theoretical Computational Intelligence and Applications.- Fuzzy Theory and Algorithms.- Machine Learning and Data Mining.- Intelligent Computing in Computer Vision.- Intelligent Control and Automation.- Intelligent Data Analysis and Prediction.- Intelligent Computing and Optimization.

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Book SynopsisThe book provides an accessible overview of audio signal processing, and enables readers to design and write algorithms for the analysis, synthesis, and manipulation of musical and acoustic signals for any programming language. It provides an overview of highly interdisciplinary topics developed in a simple but rigorous way, and described in a unified and formal language which focuses on determining discrete-time audio signal models. Readers can find within a self-contained volume basic topics ranging over different disciplines: mechanical acoustics, physical systems and linear and nonlinear models, with lumped and distributed parameters; described and developed with the same level of mathematical formalism, easy to understand and oriented to the development of algorithms. Topics include the fundamental concepts of acoustic mechanics and vibration; the design of filters and equalizers for sound signals, the so-called audio effects, abstract methods of sound synthesis, and finally, methods of synthesis by physical modeling.Table of ContentsFoundations of Acoustics.- Discrete-Time Signals, Circuits and System Fundamentals.- Digital Filters for Audio Applications.- Multi-Rate Audio Processing and Wavelet Transform.- Special Transfer Functions for DASP.- Circuits and Algorithms for Physical Modeling.- Digital Audio Effects.- Sound Synthesis.- Physical Modeling.

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Book SynopsisThis book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022.The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.Table of ContentsExplain to Not Forget: Defending Catastrophic Forgetting with XAI.- Approximation of SHAP values for Randomized Tree Ensembles.- Color shadows (part I): exploratory usability evaluation of activation maps in radiological machine learning.- Effects of Fairness and Explanation on Trust in Ethical AI.- Towards Refined Classifications driven by SHAP explanations.- Global Intepretable Calibration Index, a New Metric to Estimate Machine Learning Models' Calibration.- The ROC Diagonal is not Layperson’s Chance: a New Baseline Shows the Useful Area.- Debiasing MDI Feature Importance and SHAP values in Tree Ensembles.- The Influence of User Diversity on Motives and Barriers when Using Health Apps - A Conjoint Investigation of the Intention-Behavior Gap.- Identifying Fraud Rings Using Domain Aware Weighted Community Detection.- Capabilities, limitations and challenges of style transfer with CycleGANs: a study on automatic ring design generation.- Semantic Causal Abstraction for Event Prediction.- An Evaluation Study of Intrinsic Motivation Techniques applied to Reinforcement Learning over Hard Exploration Environments.- Towards Generating Financial Reports From Tabular Data Using Transformers.- Evaluating the performance of SOBEK text mining keyword extraction algorithm.- Classification of Screenshot Image Captured in Online Meeting System.- A survey on the application of virtual reality in event-related potential research.- Visualizing Large Collections of URLs Using the Hilbert Curve.- How to Reduce the Time Necessary for Evaluation of Tree-based Models.- An Empirical Analysis of and Guidelines for Synthetic-Data-based Anomaly Detection.- SECI Model in Data-Based Procedure for the Assessment of the Frailty State in Diabetic Patients.- Comparing machine learning correlations to domain experts’ causal knowledge: Employee turnover use case.- Machine learning and knowledge extraction to support work safety for smart forest operations.

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Book SynopsisWith the fast development of the Internet, we are experiencing a shift from the traditional sharing of information and applications as the main purpose of the Web to an emergent paradigm, which locates people at the very center of networks and exploits the value of people's connections, relations, and collaboration. Social networks are also playing a major role in the dynamics and structure of intelligent Web-based networking and collaborative systems. Virtual campuses, virtual communities, and organizations strongly leverage intelligent networking and collaborative systems by a great variety of formal and informal electronic relations, such as business-to-business, peer-to-peer, and many types of online collaborative learning interactions, including the emerging e-learning systems. This has resulted in entangled systems that need to be managed efficiently and in an autonomous way. In addition, latest and powerful technologies based on grid and wireless infrastructure as well as cloud computing are currently enhancing collaborative and networking applications a great deal but also facing new issues and challenges. The principal purpose of the research and development community is to stimulate research that will lead to the creation of responsive environments for networking and, at longer-term, the development of adaptive, secure, mobile, and intuitive intelligent systems for collaborative work and learning. The aim of the book “Advances on Intelligent Networking and Collaborative Systems” is to provide latest research findings, innovative research results, methods, and development techniques from both theoretical and practical perspectives related to intelligent social networks and collaborative systems, intelligent networking systems, mobile collaborative systems, secure intelligent cloud systems, and so on as well as to reveal synergies among various paradigms in such a multi-disciplinary field intelligent collaborative systems.

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Book SynopsisThis two-volume set LNCS 13398 and LNCS 13399 constitutes the refereed proceedings of the 17th International Conference on Parallel Problem Solving from Nature, PPSN 2022, held in Dortmund, Germany, in September 2022.The 87 revised full papers were carefully reviewed and selected from numerous submissions. The conference presents a study of computing methods derived from natural models. Amorphous Computing, Artificial Life, Artificial Ant Systems, Artificial Immune Systems, Artificial Neural Networks, Cellular Automata, Evolutionary Computation, Swarm Computing, Self-Organizing Systems, Chemical Computation, Molecular Computation, Quantum Computation, Machine Learning, and Artificial Intelligence approaches using Natural Computing methods are just some of the topics covered in this field.Table of ContentsAutomated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods.- Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration.- Non-Elitist Selection Can Improve the Performance of Irace.- Per-run Algorithm Selection with Warm-starting using Trajectory-based Features.- Efficient Approximation of Expected Hypervolume Improvement using Gauss-Hermite Quadrature.- A Systematic Approach to Analyze the Computational Cost of Robustness in Model-Assisted Robust Optimization.- Adaptive Function Value Warping for Surrogate Model Assisted Evolutionary Optimization.- Finding Knees in Bayesian Multi-Objective Optimization.- High Dimensional Bayesian Optimization with Kernel Principal Component Analysis.- Single Interaction Multi-Objective Bayesian Optimization.- Surrogate-assisted LSHADE algorithm utilizing Recursive Least Squares filter.- Towards Efficient Multiobjective Hyperparameter Optimization: A Multiobjective Multi-Fidelity Bayesian Optimization and Hyperband Algorithm.- A Continuous Optimisation Benchmark Suite from Neural Network Regression.- BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.- Evolutionary Approaches to Improving the Layouts of Instance-Spaces.- A novelty-search approach to filling an instance-space with diverse and discriminatory instances for the knapsack problem.- Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.- Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation.- Cooperative Multi-Agent Search on Endogenously-Changing Fitness Landscapes.- Evolutionary Algorithm for Vehicle Routing with Diversity Oscillation Mechanism.- Evolutionary Algorithms for Limiting the Effect of Uncertainty for the Knapsack Problem with Stochastic Profits.- Self-adaptation via Multi-objectivisation: An Empirical Study.- The Combined Critical Node and Edge Detection Problem. An Evolutionary Approach.- Attention-Based Genetic Algorithm for Adversarial Attack in Natural Language Processing.- Deep Reinforcement Learning with Two-Stage Training Strategy for Practical Electric Vehicle Routing Problem with Time Windows.- Evolving Through the Looking Glass: Learning Improved Search Spaces with Variational Autoencoders.- Generalization and Computation for Policy Classes of Generative Adversarial Imitation Learning.- Generative Models over Neural Controllers for Transfer Learning.- HVC-Net: Deep Learning based Hypervolume Contribution Approximation.- Multi-objective Evolutionary Ensemble Pruning Guided by Margin Distribution.- Revisiting Attention-based Graph Neural Networks for Graph Classification.- Robust Neural Network Pruning by Cooperative Coevolution.- SemiGraphFL: Semi-Supervised Graph Federated Learning.- Evolutionary Design of Reduced Precision Preprocessor for Levodopa-Induced Dyskinesia Classifier.- In-Materio Extreme Learning Machines.- On the impact of the duration of evaluation episodes on the evolution of adaptive robots.- Analysing the Fitness Landscape Rotation for Combinatorial Optimisation.- Analysis of Search Landscape Samplers for Solver Performance Prediction on a University Timetabling Problem.- Fractal Dimension and Perturbation Strength: A Local Optima Networks View.- HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.- Increasing the Diversity of Benchmark Function Sets through Affine Recombination.- Neural Architecture Search: A Visual Analysis. - Digging into Semantics: Where do search-based software repair methods search?.- Gene-pool Optimal Mixing in Cartesian Genetic Programming.- Genetic programming for combining directional changes indicators in international stock markets.- Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling.- Towards Discrete Phenotypic Recombination in Cartesian Genetic Programming.- A general architecture for generating interactive decomposition-based MOEAs.- An Exact Inverted Generational Distance for Continuous Pareto Front.- Direction Vector Selection for R2-based Hypervolume Contribution Approximation.- Do We Really Need to Use Constraint Violation in Constrained Evolutionary Multi-Objective Optimization?.- Dynamic Multi-modal Multi-objective Optimization: A Preliminary Study.- Fair Feature Selection with a Lexicographic Multi-Objective Genetic Algorithm.- Greedy Decremental Quick Hypervolume Subset Selection Algorithms.- Hybridizing Hypervolume-based Evolutionary Algorithms and Gradient Descent by Dynamic Resource Allocation.- Identifying Stochastically Non-dominated Solutions Using Evolutionary Computation.- Large-scale multi-objective influence maximisation with network downscaling.- Multi-Objective Evolutionary Algorithm Based on the Linear Assignment Problem and the Hypervolume Approximation using Polar Coordinates (MOEA-LAPCO).- New Solution Creation Operator in MOEA/D for Faster Convergence.- Obtaining Smoothly Navigable Approximation Sets in Bi-Objective Multi-Modal Optimization.- T-DominO: Exploring Multiple Criteria with Quality-Diversity and the Tournament Dominance Objective.- Recombination Weight based Selection in the DTS-CMA-ES.- The (1+1)-ES Reliably Overcomes Saddle Points.- Collective Learning of Low-Memory Matrix Adaptation for Large-Scale Black-Box Optimization.- Evolutionary Time-Use Optimization for Improving Children's Health Outcomes.- Iterated Local Search for the eBuses Charging Location Problem.- Multi-view clustering of heterogeneous health data: Application to systemic sclerosis.- Specification-Driven Evolution of Floor Plan Design.- Surrogate-assisted Multi-objective Optimization for Compiler Optimization Sequence Selection.- A First Runtime Analysis of the NSGA-II on a Multimodal Problem.- Analysis of Quality Diversity Algorithms for the Knapsack Problem.- Better Running Time of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) by Using Stochastic Tournament Selection.- Escaping Local Optima With Local Search: A Theory-Driven Discussion.- Evolutionary Algorithms for Cardinality-Constrained Ising Models.- General Univariate Estimation-of-Distribution Algorithms.- Population Diversity Leads to Short Running Times of Lexicase Selection.- Progress Rate Analysis of Evolution Strategies on the Rastrigin Function: First Results.- Running Time Analysis of the (1+1)-EA using Surrogate Models on OneMax and LeadingOnes.- Runtime Analysis of Simple Evolutionary Algorithms for the Chance-constrained Makespan Scheduling Problem.- Runtime Analysis of the (1+1) EA on Weighted Sums of Transformed Linear Functions.- Runtime Analysis of Unbalanced Block-Parallel Evolutionary Algorithms.- Self-adjusting Population Sizes for the (1, λ)-EA on Monotone Functions.- Theoretical Study of Optimizing Rugged Landscapes with the cGA.- Towards Fixed-Target Black-Box Complexity Analysis.- Two-Dimensional Drift Analysis: Optimizing Two Functions Simultaneously Can Be Hard.

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Book SynopsisThis book constitutes the refereed conference proceedings of the 9th IFIP WG 13.2 International Conference on Human-Centered Software Engineering, HCSE 2022, which was held in Eindhoven, The Netherlands, during August 2022. The 11 full papers presented together with 2 poster and demo papers were carefully reviewed and selected from 25 submissions. The papers focus on the interdependencies between user interface properties and contribute to the development of theories, methods, tools and approaches for dealing with multiple properties that should be taken into account when developing interactive systems. They are organized in the following topical sections: user-centred design approaches; model-based and model-driven approaches; software development strategies; and posters and demos.

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Book SynopsisThis book discusses artificial intelligence (AI) and cybersecurity from multiple points of view. The diverse chapters reveal modern trends and challenges related to the use of artificial intelligence when considering privacy, cyber-attacks and defense as well as applications from malware detection to radio signal intelligence.The chapters are contributed by an international team of renown researchers and professionals in the field of AI and cybersecurity.During the last few decades the rise of modern AI solutions that surpass humans in specific tasks has occurred. Moreover, these new technologies provide new methods of automating cybersecurity tasks. In addition to the privacy, ethics and cybersecurity concerns, the readers learn several new cutting edge applications of AI technologies.Researchers working in AI and cybersecurity as well as advanced level students studying computer science and electrical engineering with a focus on AI and Cybersecurity will find this book useful as a reference. Professionals working within these related fields will also want to purchase this book as a reference. Table of ContentsPart I Cybersecurity ConcernsUse of Artificial Intelligence in a Cybersecurity EnvironmentPetri Vähäkainu and Martti LehtoA Review of Cyber Threat (Artificial) Intelligence in SecurityManagementMartin Lundgren and Ali PadyabModel Based Resilience Engineering for Design and Assessment ofMission Critical Systems Containing AI ComponentsAutomation of CybersecurityWorkArtificial Intelligence for Cybersecurity Education and TrainingOffensive Machine Learning Methods and the Cyber Kill ChainDefensive Machine Learning Methods and the Cyber Defence Chain . Part II Privacy and EthicsDifferential Privacy: An Umbrella ReviewAI in Cyber Operations: Ethical and Legal Considerations for End-UsersPart III ApplicationsAndroid Malware Detection Using Deep LearningArtificial Intelligence Enabled Radio Signal IntelligenceDeep Learning Quantile Regression for Robustness, Confidence andPlanningModel Fooling Threats Against Medical Imaging

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Book SynopsisThis book constitutes the refereed proceedings of the 13th International Conference on the Theory and Application of Diagrams, Diagrams 2022, held in Rome, Italy, in September 2022. The 11 full papers and 19 short papers presented together with 5 posters were carefully reviewed and selected from 58 submissions. 8 chapters are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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Book Synopsis This book includes recent research on climbing and walking robots. CLAWAR 2022 is the twenty-fifth International Conference Series on Climbing and Walking Robots and Mobile Machine Support Technologies. The conference is organized by CLAWAR Association in collaboration with the University of the Azores, S. Miguel, Portugal, during September 12-14, 2022. CLAWAR 2022 provides an updated state of the art on robotics and its use in a diversity of applications and/or simulation scenarios, within the framework “Robotics in Natural Settings”. The topics covered include Bio-Inspired Robotics, Biped Locomotion, Educational Robotics, Human-Machine/Human-Robot Interaction, Innovative Actuators, Inspection, Legged Locomotion, Modeling and Simulation of CLAWAR, Outdoor and Field Robotics, Planning and Control, Wearable Devices and Assistive Robotics, and the Use of A.I. in Robotics. The intended readership includes participants of CLAWAR 2022 conference, international robotic researchers, scientists, and professors of related topics worldwide, and professors and students of postgraduate courses in Robotics and Automation, Control Engineering, Mechanical Engineering, and Mechatronics.

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Book SynopsisThis book addresses the topic of autonomous flying robots physically interacting with the environment under the influence of wind. It aims to make aerial robots aware of the disturbance, interaction, and faults acting on them. This requires reasoning about the external wrench (force and torque) acting on the robot and distinguishing between wind, interactions, and collisions. The book takes a model-based approach and covers a systematic approach to parameter identification for flying robots. The book aims to provide a wind speed estimate independent of the external wrench, including estimating the wind speed using motor power measurements. Aerodynamics modeling is approached in a data-driven fashion, using ground-truth measurements from a 4D wind tunnel. Finally, the book bridges the gap between trajectory tracking and interaction control, to allow physical interaction under wind influence. Theoretical results are accompanied by extensive simulation and experimental results.Table of Contents Introduction.- Modeling.- Tracking and interaction control.- Wind estimation.- Force discrimination.- Applications and outlook.- Conclusion.

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Book SynopsisNowadays, data analysis is becoming an appealing topic due to the emergence of new data types, dimensions, and sources. This motivates the development of probabilistic/statistical approaches and tools to cope with these data. Different communities of experts, namely statisticians, mathematicians, computer scientists, engineers, econometricians, and psychologists are more and more interested in facing this challenge. As a consequence, there is a clear need to build bridges between all these communities for Data Science.This book contains more than fifty selected recent contributions aiming to establish the above referred bridges. These contributions address very different and relevant aspects such as imprecise probabilities, information theory, random sets and random fuzzy sets, belief functions, possibility theory, dependence modelling and copulas, clustering, depth concepts, dimensionality reduction of complex data and robustness.

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Book SynopsisThe volume LNAI 13546 constitutes the refereed proceedings of the 23rd Annual Conference Towards Autonomous Robotic Systems, TAROS 2022, held in Culham, UK, in September 2022. The 14 full papers and 10 short papers were carefully reviewed and selected from 38 submissions. Organized in the topical sections "Algorithms" and "Systems", they discuss significant findings and advances in the following areas: Robotic Grippers and Manipulation; Soft Robotics, Sensing and Mobile Robots; Robotic Learning, Mapping and Planning; Robotic Systems and Applications.Table of ContentsA distributed approach to haptic simulation.- A Novel Two-Hand-Inspired Hybrid Robotic End-Effector Fabricated Using 3D Printing.- Investigating the relationship between posture and safety in teleoperational tasks: A pilot study in improved operational safety through enhanced human-machine interaction.- Design and Analysis of an End Effector Using the Fin Ray Structure for Integrated Limb Mechanisms.- Trigger-Assisted Ambidextrous Control Framework for Teleoperation of Two Legged Manipulators.- Teleoperating a Legged Manipulator through Whole-Body Control.- In-silico Design and Computational Modelling of Electroactive Polymer based Soft Robotics.- Exploration of Underwater Storage Facilities with Swarm of Micro-Surface Robots.- Characterization of an Inflatable Soft Actuator and Tissue Interaction for In Vitro Mechanical Stimulation of Tissue.- EMap: Real-time terrain estimation.- Design and Preliminary In-Classroom Evaluation\\of a Low-Cost Educational Mobile Robot.- Internal State-based Risk Assessment for Robots in Hazardous Environment.- Investigating Scene Visibility Estimation within ORB-SLAM3.- Tactile and Proprioceptive Online Learning in Robotic Contour Following.- Learning cooperative behaviours in adversarial multi-agent systems.- Task Independent Safety Assessment for Reinforcement Learning.- Sensing Anomalies as Potential Hazards: Datasets and Benchmarks.- Integration and robustness analysis of the Buzz swarm programming language with the Pi-puck robot platform.- Implementing and assessing a remote teleoperation setup with a Digital Twin using cloud networking.- Agent-Based Simulation of Multi-Robot Soil Compaction Mapping.- A-EMS: An Adaptive Emergency Management System for Autonomous Agents in Unforeseen Situations.- Towards Scalable Multi-Robot Systems by Partitioning the Task Domain.- Effectiveness of brush operational parameters for robotic debris removal.- Automatic, Vision-Based Tool Changing Solution for Dexterous Teleoperation Robots in a Nuclear Glovebox

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Book SynopsisThis book constitutes the refereed proceedings of the 14th International Conference on Computational Collective Intelligence, ICCCI 2022, held in Hammamet, Tunisia, in September 2022. The 56 full papers and 10 short papers were carefully reviewed and selected from 420 submissions. The papers are grouped in topical ​sections on collective intelligence and collective decision-making; deep learning techniques; natural language processing; data minning and machine learning; knowledge engineering and semantic web; computer vision techniques; social networks and intelligent systems; cybersecurity and internet of things; cooperative strategies for decision making and optimization; computational intelligence for digital content understanding; applications for industry 4.0.Table of ContentsCollective Intelligence and Collective Decision-Making.- Deep Learning Techniques.- Natural Language Processing.- Data Mining and Machine learning.- Knowledge Engineering and Semantic Web.- Computer Vision Techniques.- Social Networks and Intelligent Systems.- Cybersecurity and Internet of Things.- Cooperative Strategies for Decision Making and Optimization.- Computational Intelligence for Digital Content Understanding.- Applications for Industry 4.0.

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Book SynopsisThis book is about the generalization and modernization of approximation by neural network operators. Functions under approximation and the neural networks are Banach space valued. These are induced by a great variety of activation functions deriving from the arctangent, algebraic, Gudermannian, and generalized symmetric sigmoid functions. Ordinary, fractional, fuzzy, and stochastic approximations are exhibited at the univariate, fractional, and multivariate levels. Iterated-sequential approximations are also covered. The book’s results are expected to find applications in the many areas of applied mathematics, computer science and engineering, especially in artificial intelligence and machine learning. Other possible applications can be in applied sciences like statistics, economics, etc. Therefore, this book is suitable for researchers, graduate students, practitioners, and seminars of the above disciplines, also to be in all science and engineering libraries.Table of ContentsAlgebraic function induced Banach space valued ordinary and fractional neural network approximations.- Gudermannian function induced Banach space valued ordinary and fractional neural network approximations.- Generalized symmetrical sigmoid function induced Banach space valued ordinary and fractional neural network approximations.- Abstract multivariate algebraic function induced neural network approximations.- General multivariate arctangent function induced neural network approximations.- Abstract multivariate Gudermannian function induced neural network approximations.- Generalized symmetrical sigmoid function induced neural network multivariate approximation.- Quantitative Approximation by Kantorovich-Choquet quasi-interpolation neural network operators revisited.- Quantitative Approximation by Kantorovich-Shilkret quasi-interpolation neural network operators revisited.- Voronsovkaya Univariate and Multivariate asymptotic expansions for sigmoid functions induced quasi-interpolation neural network operators revisited.- Univariate Fuzzy Fractional various sigmoid function activated neural network approximations revisited.- Multivariate Fuzzy Approximation by Neural Network Operators induced by several sigmoid functions revisited.- Multivariate Fuzzy-Random and stochastic various activation functions activated Neural Network Approximations.

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Book SynopsisThis book constitutes the refereed proceedings of the first MICCAI Workshop on Resource-Efficient Medical Image Analysis, REMIA 2022, held in conjunction with MICCAI 2022, in September 2022 as a hybrid event. REMIA 2022 accepted 13 papers from the 19 submissions received. The workshop aims at creating a discussion on the issues for practical applications of medical imaging systems with data, label and hardware limitations.Table of ContentsMulti-Task Semi-Supervised Learning for Vascular Network.- Segmentation and Renal Cell Carcinoma Classification.- Self-supervised Antigen Detection Artificial Intelligence (SANDI).- RadTex: Learning Effcient Radiograph Representations from Text Reports.- Single Domain Generalization via Spontaneous Amplitude Spectrum Diversification.- Triple-View Feature Learning for Medical Image Segmentation.- Classification of 4D fMRI Images Using ML, Focusing on Computational and Memory Utilization Effciency.- An Effcient Defending Mechanism Against Image Attacking On Medical Image Segmentation Models.- Leverage Supervised and Self-supervised Pretrain Models for Pathological Survival Analysis via a Simple and Low-cost Joint Representation Tuning.- Pathological Image Contrastive Self-Supervised Learning.- Investigation of Training Multiple Instance Learning Networks with Instance Sampling.- Masked Video Modeling with Correlation-aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound.- A self-attentive meta-learning approach for image-based few-shot disease detection.- Facing Annotation Redundancy: OCT Layer Segmentation with Only 10 Annotated Pixels Per Layer.

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Book SynopsisThis book constitutes the proceedings of the 5th International Workshop on Predictive Intelligence in Medicine, PRIME 2022, held in conjunction with MICCAI 2022 as a hybrid event in Singapore, in September 2022.The 19 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine.Table of ContentsFederated Time-dependent GNN Learning from Brain Connectivity Data with Missing Timepoints.- Bridging the Gap between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing.- Multi-Tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas.- Multiple Instance Neuroimage Transformer.- Intervertebral Disc Labeling With Learning Shape Information, A Look Once Approach.- Mixup augmentation improves age prediction from T1-weighted brain MRI scans.- Diagnosing Knee Injuries from MRI with Transformer Based Deep Learning.- MISS-Net: Multi-view contrastive transformer network for MCI stages prediction using brain 18F-FDG PET imaging.- TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation.- Opportunistic hip fracture risk prediction in Men from X-ray: Findings from the Osteoporosis in Men (MrOS) Study.- Weakly-Supervised TILs Segmentation based on Point Annotations using Transfer Learning with Point Detector and Projected-Boundary Regressor.- Discriminative Deep Neural Network for Predicting Knee OsteoArthritis in Early Stage.- Long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-Task Learning on Imaging and Tabular Data.- Quantifying the Predictive Uncertainty of Regression GNN Models Under Target Domain Shifts.- Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets.- Learning subject-specific functional parcellations from cortical surface measures.- A Triplet Contrast Learning of Global and Local Representations for Unannotated Medical Images.- Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification.- Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores using Graph Neural Networks and Meta-Learning

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Book SynopsisThis book constitutes the refereed proceedings of the 23rd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2022, held in Bolzano, Italy, in September 2022. The 11 full papers presented together with 5 short papers were carefully reviewed and selected from 57 submissions The previous event in the series, EKAW 2020, introduced a special theme related to “Ethical and Trustworthy Knowledge Engineering.” This theme is still very relevant in 2022, and thus has remained one of the core topics of the conference.The conference concerned with all aspects about eliciting, acquiring, modeling and managing knowledge, and the construction of knowledge-intensive systems and services for the semantic web, knowledge management, e-business, natural language processing, intelligent information integration, and much more.Table of ContentsBasic Human Values and Moral Foundations Theory in ValueNet Ontology.- Extending Ontology Engineering Practices to Facilitate Application Development.- MultiAligNet: Cross-Lingual Knowledge Bridges between Words and Senses.- Question Answering with Additive Restrictive Training (QuAART): Question Answering for the Rapid Development of New Knowledge Extraction Pipelines.- New Strategies for Training Knowledge Graph Embeddings: the Recommendation Case.- Documenting the Creation, Manipulation and Evaluation of Links for Reuse and Reproducibility.- Should we afford affordances? Injecting ConceptNet knowledge into BERT-based models to improve commonsense reasoning ability.- Towards a Knowledge Graph of Health Evolution.- Beyond Causality: Representing Event Relations in Knowledge Graphs.- Evaluating the Interpretability of Threshold Operators.- EBOCA: Evidences for BiOmedical Concepts Association Ontology.- Counter Effect Rules Mining in Knowledge Graphs.- A FAIR Core Semantic Metadata Model for FAIR Multidimensional Tabular Datasets.- Human-centric Ontology Evaluation: Process and Tool Support.- Towards Pragmatic Explanations for Domain Ontologies.- Quasi-equivalent concept trade-off in ontology design: initial considerations and analyses.

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Book SynopsisThis book shows latest research on the role Artificial inelegance in enabling IoT to evoke IoI, and how IoI flourish inside technologies like social media platforms, social networks: communities of practice/interest, to assure a globally sustainable unit where humans integrate with machines to collaboratively share ideas and solve complex problems. Such a book holds several benefits. It will reveal theoretical practical, and managerial implications through discussions that will embrace a wide array of technologies focused on the role of AI enabled IoT to evoke IoI. EAMMIS 2022 was organized by the Bridges Foundation in cooperation with Coventry University, UK on the 10th and 11th of June 2022. EAMMIS 2022 theme was From the Internet of Things to the Internet of Ideas: The role of Artificial Intelligence. The papers presented at the conference provide a holistic view of AI and its applications, IOT and the IOI which will help societies to better use and benefit from AI, IOT and IOI to develop future strategies and actions.

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Book SynopsisThis book gives a detailed information of various real-life applications from various fields using nature inspired optimization techniques. These techniques are proven to be efficient and robust in many difficult problems in literature. The authors provide detailed information about real-life problems and how various nature inspired optimizations are applied to solve these problems. The authors discuss techniques such as Biogeography Based Optimization, Glow Swarm Optimization, Elephant herd Optimization Algorithm, Cuckoo Search Algorithm, Ant Colony Optimization, and Grey Wolf Optimization etc. These algorithms are applied to a wide range of problems from the field of engineering, finance, medicinal etc. As an important part of the Women in Science and Engineering book series, the work highlights the contribution of women leaders in nature inspired optimization, inspiring women and men, girls and boys to enter and apply themselves to the field.Table of Contents1) AN OVERVIEW OF SWARM INTELLIGENCE BASED ALGORITHMS2) Particle Swarm Optimization and its Applications in the Manufacturing Industry3) Role of Machine Learning in Bioprocess Engineering: Current Perspectives and Future Directions 4) Advanced Selection Operation for Differential Evolution Algorithm 5) Profit Optimization of Two-Unit Briquetting System using grey wolf Optimization algorithm 6) Solving Portfolio optimization using Sine-cosine Algorithm embedded mutation operations7) Detecting Group Shilling Profiles in Recommender Systems: A Hybrid Clustering and Grey Wolf Optimizer Technique8) SINGLE IMAGE REFLECTION REMOVAL USING DEEP LEARNING 9) Social media analysis: A tool for popularity prediction using machine learning classifiers

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Book SynopsisThis book constitutes the proceedings of the 20th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2022, held in L'Aquila, Italy in July 2022.The 37 full papers in this book were reviewed and selected from 67 submissions. Another 10 demonstrations papers were selected from 11 submissions are presented here as short papers. The papers deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, including: advanced models and learning, agent-based programming, decision-making, education and social interactions, formal and theoretic models, health and safety, mobility and the city, swarms and task allocation.

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Book SynopsisThe 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022.The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.Table of Contents​Image Processing and Low-level Vision.- Video Deraining via Temporal Discrepancy Learning.- Multi-priors Guided Dehazing Network Based on Knowledge Distillation.- DLMP-Net: a dynamic yet lightweight multi-pyramid network for crowd density estimation.- CHENet: Image to Image Chinese Handwriting Eraser.- Identidication method for rice pests with small sample size problem combining deep learning and metric learning.- Boundary-Aware Polyp Segmentation Network.- SUDANet:A Siamese UNet with Dense Attention Mechanism for Remote Sensing Image Change Detection.- A Local-Global Self-attention Interaction Network for RGB-D Cross-modal Person Re-identification.- A RAW Burst Super-Resolution Method with Enhanced Denoising.- Unpaired and Self-supervised Optical Coherence Tomography Angiography Super-resolution.- Multi-Feature Fusion Network for Single Image Dehazing.- LAGAN: Landmark Aided Text to Face Sketch Generation.- DMF-CL: Dense Multi-scale Feature Contrastive Learning for Semantic segmentation of Remote-sensing images.- Image derain method for generative adversarial network based on wavelet high frequency feature fusion.- GPU-Accelerated Infrared Patch-Image Model for Small Target Detection.- Hyperspectral and Multispectral Image Fusion Based on Unsupervised Feature Mixing and Reconstruction Network.- Information Adversarial Disentanglement for Face Swapping.- A Dense Prediction ViT Network for Single Image Bokeh Rendering.- Multi-scale Coarse-to-fine Network for Demoiring.- Learning Contextual Embedding Deep Networks for Accurate and Efficient Image Deraining.- A Stage-Mutual-Ane Network for Single Remote Sensing Image Super-Resolution.- Style-based Attentive Network for Real-World Face Hallucination.- Cascade Scale-aware Distillation Network for Lightweight RemoteSensing Image Super-Resolution.- Few-Shot Segmentation via Rich Prototype Generation and RecurrentPrediction Enhancement.- Object Detection, Segmentation and Tracking.- TAFDet: A Task Awareness Focal Detector for Ship Detection in SAR Images.- MSDNet:Multi-scale Dense Networks for Salient Object Detection.- WaveSNet: Wavelet Integrated Deep Networks for Image Segmentation.- Infrared Object Detection Algorithm Based on Spatial Feature Enhancement.- Object Detection Based on Embedding Internal and External Knowledge.- ComLoss: A Novel Loss towards More Compact Predictions for Pedestrian Detection.- Remote sensing image detection based on attention mechanism and YOLOv5.- Detection of Pin Defects in Transmission Lines Based on Dynamic Receptive Field.- Identification of bird s nest hazard level of transmission line based on improved yolov5 and location constraints.- Image Magnification Network for Vessel Segmentation in OCTA Images.- CFA-Net: Cross-level Feature Fusion and Aggregation Network for Salient Object Detection.- Disentangled Feature Learning for Semi-supervised Person Re-identification.- Detection Beyond What and Where: A Benchmark for Detecting Occlusion State.- Weakly Supervised Object Localization with Noisy-Label Learning.- Enhanced Spatial Awareness For Deep Interactive Image Segmentation.- Anchor-Free Location Refinement Network for Small License Plate Detection.- Multi-View LiDAR Guided Monocular 3D Object Detection.- Dual Attention-guided Network for Anchor-free Apple Instance Segmentation in Complex Environments.- Attention-Aware Feature Distillation for Object Detection in Decompressed Images.- Cross-Stage Class-Specific Attention for Image Semantic Segmentation.- Defect Detection for High Voltage Transmission Lines Based on Deep Learning.- ORION: Orientation-Sensitive Object Detection.- An Infrared Moving Small Object Detection Method Based on Trajectory Growth.- Two-stage Object Tracking Based on Similarity Measurement for FusedFeatures of Positive and Negative Samples.- PolyTracker: Progressive Contour Regression for Multiple ObjectTracking and Segmentation.- Dual-branch Memory Network for Visual Object Tracking.- Instance-wise Contrastive Learning for Multi-Object Tracking.- Information Lossless Multi-Modal Image Generation for RGB-T Tracking.- JFT: A Robust Visual Tracker Based on Jitter Factor and Global Registration.- Caged Monkey Dataset: A New Benchmark for Caged Monkey Pose Estimation.- WTB-LLL: A Watercraft Tracking Benchmark Derived by Low-light-level Camera.- Dualray: Dual-view X-ray Security Inspection Benchmark and FusionDetection Framework.

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Book SynopsisThis book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXIV International Conference on Neuroinformatics, held on October 17–21, 2022, in Moscow, Russia.Table of ContentsPart I: Neuroinformatics and Artificial Intelligence.- Tree Inventory with LiDAR Data.- Towards Reliable Solar Atmospheric Parameters Neural-Based Inference.- Addressing Task Prioritization in Model-based Reinforcement Learning.- Automatic Generation of Conversational Skills from Dialog Datasets.- Part II: Neural Networks and Cognitive Sciences. Adaptive Behavior and Evolutionary Simulation.- Individual Topology Structure of Eye Movement Trajectories.- Neural Network Providing the Involvement of Voluntary Attention into the Processing and Conscious Perception of Sensory Information.- Alpha Rhythm Dynamics During Spoken Word Recognition.- Robotic Devices Control Based on Neuromorphic Classifiers of Imaginary Motor Commands.- A Software System for Training Motor Imagery in Virtual Reality.- On the Importance of Diversity.- “MYO-chat” – A New Computer Control System for People with Disabilities.- Low-bit Quantization of Transformer for Audio Speech Recognition.- A Model of Predicting and Using Regularities by an Autonomous Agent.- A Review of One-Shot Neural Architecture Search Methods.- Does a Recurrent Neural Network Use Reflection During a Reflexive Game?.- A Gender Genetic Algorithm and its Comparison with Conventional Genetic Algorithm.- Associations of Morphometric Changes of the Brain with the Levels of IGF1, a Multifunctional Growth Factor, and with Systemic Immune Parameters Reflect the Disturbances of Neuroimmune Interactions in Patients with Schizophrenia.- Part III: Modern Methods and Technologies in Neurobiology.- Dynamics of Background and Evoked Activity of Neurons in the Auditory Cortex of the Unanaesthetized Cat.- Search for Markers of Moderate Cognitive Disorders through Phase Synchronization between Rhythmic Photostimulus and EEG Pattern.- Astrocytes Enhance Image Representation Encoded in Spiking Neural Network.- Classification of Neuron Type Based on Average Activity.- Comparative Analysis of Statistical and Neural Network Classification Methods on the Example of Synthesized Data in the Stimulus-Independent Brain-Computer Interface Paradigm.- Shunting Effect of Synaptic Channels Located on Presynaptic Terminal.- Analysis of Appearances, Formation and Evolution of Biological Functional Systems.- The Reinforcement Learning Theory, Value Function, and the Nature of Value Function Calculation by the Insular Cortex.- To the Role of Inferior Olives in Cerebellar Neuromechanics.- Individual Differences in Mismatch-Induced c-Fos Expression in the Retrosplenial Cortex in Rats: Shift in Activity is Layer-Specific.- Sleep of Poor and Good Nappers under the Afternoon Exposure to Weak 2-Hz/8-Hz Electromagnetic Fields.- Part IV: Applications of Neural Networks.- Classification of Light Microscopy Image Using Probabilistic Bayesian Neural Network.- SPICE Model of Analog Content-Addressable Memory Based on 2G FeFET Crossbar.- IQ-GAN: Instance Quantized Image Synthesis.- Specifics of Crossbar Resistor Arrays.- Recurrent and Graph Neural Networks for Particle Tracking at the BM@N Experiment.- Modeling of a Neural Network Algorithm for Suppressing Non-Stationary Interference in an Adaptive Antenna Array.- Learning Various Locomotion Skills from Scratch with Deep Reinforcement Learning.- Center3dAugNet: Effect of Rotation Representation on One-Stage Joint Car Detection and 6D-Pose Estimation.- Global memory transformer for processing long documents.- Development of the Convolutional Neural Network for Defining the Renal Pathology Using Computed Tomography Images.- Possibility of Using Various Architectures of Convolutional Neural Networks in the Problem of Determining the Type of Rhythm.- DeepPavlov Topics: Topic Classification Dataset for Conversational Domain in English.- Multi-Input Convolutional Neural Networks in Real-Time Semantic Segmentation Tasks.- Integration of Data and Algorithms in Solving Inverse Problems of Spectroscopy of Solutions by Machine Learning Methods.- Investigation of Pareto Front of Neural Network Approximation of Solution of Laplace Equation in Two Statements: with Discontinuous Initial Conditions or with Measurement Data?.- Multitask learning for extensive object description to improve scene understanding on monocular video.- Use of Classification Algorithms to Predict the Grade of Geomagnetic Disturbance.- Information processing in spiking neuron-astrocyte network in ageing.- Multilingual Case-insensitive Named Entity Recognition.- Multi-level Pipeline for Data Mining with Similar Structure.- Creating a Brief Review of Judicial Practice Using Clustering Methods.- Part V: Neural Network Theory, Concepts and Architectures.- "Gas” instead of “Liquid”: which Liquid State Machine is Better?.- Using a Resistor Array to Tackle Optimization Problems.- Generative Adversarial Networks as an Approach to Unsupervised Link Prediction Problem.- DGAC: Dialog Graph AutoConstruction up on Data with a Regular Structure.- Relay System of Differential Equations with Delay as a Perceptron Model.- Analysis of Predictive Capabilities of Adaptive Multilayer Models with Physics-Based Architecture for Duffing Oscillator?.- An Attempt to Formalize the Formulation of the Network Architecture Search Problem for Convolutional Neural Networks.- Use of Conditional Variational Autoencoders and Partial Least Squares in Solving an Inverse Problem of Spectroscopy.- On the Similarities between Denoising Diffusion Models and Autoencoders.

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Book SynopsisThis book presents select papers from the 2nd EAI International Conference on Computational Intelligence and Communications (CICom 2021). The papers reveal recent advances in the broader domains of Computational Intelligence including (1) automation, control, and intelligent transportation system; (2) big data, Internet of Things, and smart cities; (3) wireless communication systems and cyber security and; (4) human/brain-computer interfaces, and image and pattern recognition. The book demonstrates complex real-world problems in which mathematical or traditional modelling are not the preferred solution and posits alternative solutions. This collection of applications demonstrates the important advances in computational intelligence. The chapters present various ideas that will benefit researchers, graduate students and engineers in this domain.Table of ContentsIntroduction.- Perception Enhancement of a Vehicle in a Bad Weather Environment.- Adaptive Backstepping-RBF Control of Lower Limb Exoskeleton.- Advances in Coyote Optimization Algorithm.- Efficient Big Data Architecture Based on Micro Service.- K Semantics for Security Policy Enforcement on Android Applications with Practical Cases.- On the Performance of MIMO Vehicular Visible Light Communications.- An Evaluation Framework for Blockchain-based Public Key Infrastructures.- Intelligent Target Cell Selection Algorithm for Low Latency 5G Networks.- Conclusion.

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Book SynopsisThis book contains the works connected with the key advances in Intelligent Information Technologies for Industry presented in the main track of IITI 2022, the Sixth International Scientific Conference on Intelligent Information Technologies for Industry held on October 31 - November 6, 2022, in Istanbul, Turkey. The works were written by the experts in the field of artificial intelligence including topics such as machine learning, decision making intelligent systems, fuzzy logic, bioinspired systems and Bayesian networks. The following industrial application domains were touched: railway automation, intelligent medical systems, flexible socio-technical systems, navigation systems and energetic systems. The editors believe that this book will be helpful for all scientists and engineers interested in the modern state of applied artificial intelligence.

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Book SynopsisThis book provides readers with peer-reviewed research papers presented at the 6th International Conference on Green Technology and Sustainable Development (GTSD) held in Nha Trang City, Vietnam, from July 29 to 30, 2022. The book is original work of researchers from academia and industry focusing on the theme “Green technology and sustainable development in Industrial Revolution 4.0” not only to raise awareness of the vital importance of sustainability in education, technology, and economic development, but also to highlight the essential roles of technology innovation for the green future. The book presents a wide range of research aspects including energy engineering, electric power systems, renewable energy systems, automatic control engineering, robotics, vehicle engineering, material engineering, construction engineering, mechanical engineering, vibrations, computational analysis, numerical investigation, system failure, technological solutions in health care, and so on. Through thorough research basing on both experimental and numerical methods, the authors feature either solutions for existing problems or optimization and improvement for performance of existing methods. The collected research results could be useful alternatives and implications for industry experts, research institutions, universities, and all others who share a common interest in the future global sustainable development.

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Book SynopsisThis book offers a comprehensive review of smart technologies and perspectives on their application in urban engineering. It covers a wide range of applications, from transport and energy management to digital manufacturing, smart city, environment, and sustainable development, providing readers with new ideas for future research and collaborations. This book presents select papers from the International Conference on Smart Technologies in Urban Engineering (STUE-2022), held to commemorate the 100th anniversary of the O.M. Beketov National University of Urban Economy in Kharkiv, Ukraine, on June 9–11, 2022. All the contributions offer plenty of valuable information and would be of great benefit to the experience exchange among scientists in urban engineering.

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Book SynopsisThis book is a collection of papers presented during the 8th World Conference on Soft Computing in February 2022. The papers cover multiple areas important for soft computing. Some papers are dedicated to fundamental aspects of soft computing, i.e., fuzzy mathematics, type-2 fuzzy sets, evolutionary-based optimization, aggregation, and neural networks. Others emphasize the application of soft computing methods to data analysis, image processing, decision-making, classification, series prediction, economics, control, and modeling.Table of ContentsPart 1. Soft Computing and Fuzzy Logic.- 1. Lotfi A. Zadeh’s Life and His Scientific Legacy.- 2. From Fuzzy Optimization to Possibilistic-Probabilistic Optimization with our Teacher Professor Lotfi Zadeh.- 3. Ideas of Lotfi Zadeh in Explainable Artificial Intelligence.- 4. Different Concepts, Similar Computational Complexity: Nguyen’s Results about Fuzzy and Interval Computations 35 Years.

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