Artificial intelligence (AI) Books

Book SynopsisThis textbook presents the main principles of visual analytics and describes techniques and approaches that have proven their utility and can be readily reproduced. Special emphasis is placed on various instructive examples of analyses, in which the need for and the use of visualisations are explained in detail.The book begins by introducing the main ideas and concepts of visual analytics and explaining why it should be considered an essential part of data science methodology and practices. It then describes the general principles underlying the visual analytics approaches, including those on appropriate visual representation, the use of interactive techniques, and classes of computational methods. It continues with discussing how to use visualisations for getting aware of data properties that need to be taken into account and for detecting possible data quality issues that may impair the analysis. The second part of the book describes visual analytics methods and workflows, organised by various data types including multidimensional data, data with spatial and temporal components, data describing binary relationships, texts, images and video. For each data type, the specific properties and issues are explained, the relevant analysis tasks are discussed, and appropriate methods and procedures are introduced. The focus here is not on the micro-level details of how the methods work, but on how the methods can be used and how they can be applied to data. The limitations of the methods are also discussed and possible pitfalls are identified.The textbook is intended for students in data science and, more generally, anyone doing or planning to do practical data analysis. It includes numerous examples demonstrating how visual analytics techniques are used and how they can help analysts to understand the properties of data, gain insights into the subject reflected in the data, and build good models that can be trusted. Based on several years of teaching related courses at the City, University of London, the University of Bonn and TU Munich, as well as industry training at the Fraunhofer Institute IAIS and numerous summer schools, the main content is complemented by sample datasets and detailed, illustrated descriptions of exercises to practice applying visual analytics methods and workflows.Table of ContentsPart I: Introduction to Visual Analytics in Data Science.- 1. Introduction to Visual Analytics by an Example.- 2. General Concepts.- 3. Principles of Interactive Visualisation.- 4. Computational Techniques in Visual Analytics.- Part II: Visual Analytics along the Data Science Workflow.- 5. Visual Analytics for Investigating and Processing Data.- 6. Visual Analytics for Understanding Multiple Attributes.- 7. Visual Analytics for Understanding Relationships between Entities.- 8. Visual Analytics for Understanding Temporal Distributions and Variations.- 9. Visual Analytics for Understanding Spatial Distributions and Spatial Variation.- 10. Visual Analytics for Understanding Phenomena in Space and Time.- 11. Visual Analytics for Understanding Texts.- 12. Visual Analytics for Understanding Images and Video.- 13. Computational Modelling with Visual Analytics.- 14. Conclusion.

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Book SynopsisThis book is the very first book-length study devoted to the advances in technological development and systems research in cooperative economics. The chapters provide, first of all, a coherent framework for understanding and applying the concepts and approaches of complexity and systems science for the advanced study of cooperative networks and particular cooperative enterprises and communities. Second, the book serves as a unique source of reliable information on the frontier information technologies available for the production, consumer, credit, and agricultural cooperative enterprises, discussing predominant strategies, potential drivers of change, and responses to complex problems. Given the diverse range of backgrounds and advanced research results, researchers, decision-makers, and stakeholders from all fields of cooperative economics in any country of the world will undoubtedly benefit from this book.Table of ContentsThe Role of Credit Cooperatives in Financing the Real Sector of the Economy.- Innovative Marketing Technologies in the Development of a New Product: Methodological Solutions in the Context of Economic Integration and Cooperation.- Cooperative Platform in the Modern Economy.- Education at a Cooperative University in the Digital Economy.- The Development of Cooperation in the Digital Economy Based on Scientific Research by A. V. Chayanov.- Involvement of the World’s Largest Cooperatives in Sustainable Development Processes.- Collaborations in the Modern Economy.

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Book SynopsisThis open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility. Table of ContentsHaptic Science.- The EmojiGrid as a Rating Tool for the Affective Appraisal of Touch.- A 2-DoF Skin Stretch Display on Palm: Effect of Stimulation Shape, Speed and Intensity.- User-Defined Mid-Air Haptic Sensations for Interacting with an AR Menu Environment.- Surface Roughness Judgment during Finger Exploration is Changeable by Visual Oscillations.- Identifying tactors locations on the proximal phalanx of the finger for navigation.- Tactile Perception of Objects by the User's Palm for the Development of Multi-contact Wearable Tactile Displays.- From Hate to Love: How Learning Can Change Affective Responses to Touched Materials.- Switching between objects improves precision in haptic perception of softness.- Discriminating between Intensities and Velocities of Mid-Air Haptic Patterns.- Density estimation is influenced more by mass when objects are denser.- Haptic feedback in a teleoperated Box & Blocks task.- Systematic Adaptation of Exploration Force to Exploration Duration in Softness Discrimination.- Perception of vibratory direction on the back.- Comparing Lateral Modulation and Amplitude Modulation in Phantom Sensation.- Context Matters: The Effect of Textual Tone on the Evaluation of Mediated Social Touch.- Influence of roughness on contact force estimation during active touch.- Green Fingers: Plant Thigmo Responses as an Unexplored Area for Haptics Research.- The impact of control-display gain in kinesthetic search.- The arm’s blind line: anisotropic distortion in perceived orientation of stimuli on the arm.- Evaluation of Changes in Perceived Intensity and Threshold of Moisture Sensation of Clothes Associated with Skin Moisture.- The Effects of Simultaneous Multi-Point Vibratory Stimulation on Kinesthetic Illusion.- Isometric force matching asymmetries depend on the position of the left hand regardless of handedness.- Computational Model of a Pacinian Corpuscle for an Electrical Stimulus: Spike-Rate and Threshold Characteristics.- Haptic Technology.- SwitchPaD: Active Lateral Force Feedback over a Large Area Based on Switching Resonant Modes.- Visuo-Haptic Display by Embedding Imperceptible Spatial Haptic Information into Projected Images.- Manipulating the Perceived Directions of Wind by Visuo-audio-haptic Cross-modal Effects.- A 6-DoF Zero-order Dynamic Deformable Tool for Haptic Interactions of Deformable and Dynamic Objects.- Evaluating Ultrasonic Tactile Feedback Stimuli.- WeATaViX: WEarable Actuated TAngibles for VIrtual reality eXperiences.- Noncontact Thermal and Vibrotactile Display Using Focused Airborne Ultrasound.- KATIB: Haptic-visual Guidance for Handwriting.- ThermalTex: A two-modal tactile display for delivering surface texture and thermal information.- Can Stiffness Sensations be Rendered in Virtual Reality Using Mid-air Ultrasound Haptic Technologies?.- Midair Haptic Presentation Using Concave Reflector.- Movement-Free Virtual Reality Interface using Kinesthetic Illusion Induced by Tendon Vibration.- Haptic Display Using Fishing Rod.- Confinement of Vibrotactile Stimuli in Periodically Supported Plates.- 2MoTac: Simulation of button click by superposition of two ultrasonic plate waves.- A Proposal and Investigation of Displaying Method by Passive Touch with Electrostatic Tactile Display.- Sensing Ultrasonic Mid-Air Haptics with a Biomimetic Tactile Fingertip.- Soft-wearable device for the estimation of shoulder orientation and gesture.- Wearable Vibrotactile Interface Using Phantom Tactile Sensation for Human-Robot Interaction.- A Parallel Elastic Haptic Thimble for Wide Bandwidth Cutaneous Feedback.- Instrumenting Hand-held Surgical Drills With a Pneumatic Sensing Cover for Haptic Feedback.- Rendering Ultrasound Pressure Distribution on Hand Surface in Real-Time.- Energy Analysis of Lateral vs. Normal Vibration Modes for Ultrasonic Surface Haptic Devices.- Midair Tactile Reproduction of Real Objects.- LinkRing: A Wearable Haptic Display for Delivering Multi-contact and Multi-modal Stimuli at the Finger Pads.- ElectroAR: Distributed Electro-tactile Stimulation for Tactile Transfer.- Haptic Applications.- Identification Rate of Simple and Complex Tactile Alerts in MUM-T Setup.- Attention-based Robot Learning of Haptic Interaction.- Motion Guidance using Translational Force and Torque Feedback by Induced Pulling Illusion.- Perceptually Compressive Communication of Interactive Telehaptic Signal.- Sound Image Icon with Aerial Haptic Feedback.- Stiffness Discrimination by Two Fingers with Stochastic Resonance.- Interest Arousal by Haptic Feedback During a Storytelling for Kindergarten Children.- Investigating the influence of haptic feedback in rover navigation with communication delay.- Shared haptic perception for human-robot collaboration.- Two-Point Haptic Pattern Recognition with the Inverse Filter Method.- Adaptive Fuzzy Sliding Mode Controller Design for a New Hand Rehabilitation Robot.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of 10 workshops held at the 35th International ISC High Performance 2020 Conference, in Frankfurt, Germany, in June 2020: First Workshop on Compiler-assisted Correctness Checking and Performance Optimization for HPC (C3PO); First International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics Simulations and Analysis (CFDML); HPC I/O in the Data Center Workshop (HPC-IODC); First Workshop \Machine Learning on HPC Systems" (MLHPCS); First International Workshop on Monitoring and Data Analytics (MODA); 15th Workshop on Virtualization in High-Performance Cloud Computing (VHPC). The 25 full papers included in this volume were carefully reviewed and selected. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include high-performance computing (HPC), computer architecture and hardware, programming models, system software, performance analysis and modeling, compiler analysis and optimization techniques, software sustainability, scientific applications, deep learning.Table of ContentsChecking and Performance Optimization for HPC (C3PO'20).- Compiler-assisted type-safe checkpointing.- Static analysis to enhance programmability and performance in OmpSs-2 21 Automatic detection of MPI assertions.- Automatic Code Motion to Extend MPI Nonblocking Overlap Window.- First International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics Simulations and Analysis (CFDML) .-Complete Deep Computer-Vision Methodology for Investigating Hydrodynamic Instabilities.- Prediction of Acoustic Fields using a Lattice-Boltzmann Method and Deep Learning.- Unsupervised Learning of Particle Image Velocimetry.- Reduced order modeling of dynamical systems using arti cial neural networks applied to water circulation.- Parameter Identification of RANS turbulence model using Physics-embedded neural network.- Investigating the Overhead of the REST Protocol when Using Cloud Services for HPC Storage.- Characterizing I/O Optimization E ect Through Holistic Log Data Analysis of Parallel File Systems and Interconnects.- The Importance of Temporal Behavior when Classifying Job IO Patterns Using Machine Learning Techniques.- GOPHER, an HPC framework for large scale graph exploration and inference.- Ensembles of Networks Produced from Neural Architecture Search.- SmartPred: Unsupervised Hard Disk Failure Detection.- Application IO analysis with Lustre Monitoring using LASSi for ARCHER.- Characterizing HPC Performance Variation with Monitoring and Unsupervised Learning.- Service Function Chaining Based on Segment Routing Using P4 and SR-IOV (P4-SFC) .- Seamlessly managing HPC workloads through Kubernetes.- Interference-aware Orchestration in Kubernetes.- RustyHermit: A Scalable, Rust-based Virtual Execution Environment.- Rootless Containers with Podman for HPC.- Bioinformatics application with Kube ow for batch processing in clouds.- Converging HPC, Big Data and Cloud technologies for precision agriculture data analytics on supercomputers.

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Book SynopsisThis book constitutes the refereed proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020, held in Copenhagen, Denmark, in September/October 2020. The conference was held virtually due to the COVID-19 pandemic.The 19 full papers presented together with 12 short and 2 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections named: scalable similarity search; similarity measures, search, and indexing; high-dimensional data and intrinsic dimensionality; clustering; artificial intelligence and similarity; demo and position papers; and doctoral symposium.Table of ContentsScalable Similarity Search.- Accelerating Metric Filtering by Improving Bounds on Estimated Distances.- Differentially Private Sketches for Jaccard Similarity Estimation.- Pivot Selection for Narrow Sketches by Optimization Algorithms.- mmLSH: A Practical and Efficient Technique for Processing Approximate Nearest Neighbor Queries on Multimedia Data.- Parallelizing Filter-Verification based Exact Set Similarity Joins on Multicores.- Similarity Search with Tensor Core Units.- On the Problem of p1 in Locality-Sensitive Hashing.- Similarity Measures, Search, and Indexing.- Confirmation Sampling for Exact Nearest Neighbor Search.- Optimal Metric Search Is Equivalent to the Minimum Dominating Set Problem.- Metrics and Ambits and Sprawls, Oh My: Another Tutorial on Metric Indexing.- Some branches may bear rotten fruits: Diversity browsing VP-Trees.- Continuous Similarity Search for Evolving Database.- Taking advantage of highly-correlated attributes in similarity queries with missing values.- Similarity Between Points in Metric Measure Spaces.- High-dimensional Data and Intrinsic Dimensionality.- GTT: Guiding the Tensor Train Decomposition.- Noise Adaptive Tensor Train Decomposition for Low-Rank Embedding of Noisy Data.- ABID: Angle Based Intrinsic Dimensionality.- Sampled Angles in High-Dimensional Spaces.- Local Intrinsic Dimensionality III: Density and Similarity.- Analysing Indexability of Intrinsically High-dimensional Data using TriGen.- Reverse k-Nearest Neighbors Centrality Measures and Local Intrinsic Dimension.- Clustering.- BETULA: Numerically Stable CF-Trees for BIRCH Clustering.- Using a Set of Triangle Inequalities to Accelerate K-means Clustering.- Angle-Based Clustering.- Artificial Intelligence and Similarity.- Improving Locality Sensitive Hashing by Efficiently Finding Projected Nearest Neighbors.- SIR: Similar Image Retrieval for Product Search in E-Commerce.- Cross-Resolution deep features based Image Search.- Learning Distance Estimators from Pivoted Embeddings of Metric Objects.- Demo and Position Papers.- Visualizer of Dataset Similarity using Knowledge Graph.- vitrivr-explore: Guided Multimedia Collection Exploration for Ad-hoc Video Search.- Running experiments with confidence and sanity.- Doctoral Symposium.- Temporal Similarity of Trajectories in Graphs.- Relational Visual-Textual Information Retrieval.

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Book SynopsisThis fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, causal graphical models, causal discovery and deep learning, as well as an even greater number of exercises; it also incorporates a software library for several graphical models in Python.The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes.Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Examines new material on partially observable Markov decision processes, and graphical models Includes a new chapter introducing deep neural networks and their relation with probabilistic graphical models Covers multidimensional Bayesian classifiers, relational graphical models, and causal models Provides substantial chapter-ending exercises, suggestions for further reading, and ideas for research or programming projects Describes classifiers such as Gaussian Naive Bayes, Circular Chain Classifiers, and Hierarchical Classifiers with Bayesian Networks Outlines the practical application of the different techniques Suggests possible course outlines for instructors This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference.Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico. He received the National Science Prize en 2016.Table of ContentsPart I: FundamentalsIntroductionProbability TheoryGraph TheoryPart II: Probabilistic ModelsBayesian ClassifiersHidden Markov ModelsMarkov Random FieldsBayesian Networks: Representation and InferenceBayesian Networks: LearningDynamic and Temporal Bayesian NetworksPart III: Decision ModelsDecision GraphsMarkov Decision ProcessesPartially Observable Markov Decision Processes Part IV: Relational, Causal and Deep ModelsRelational Probabilistic Graphical ModelsGraphical Causal ModelsCausal DiscoveryDeep Learning and Graphical ModelsA: A Python Library for Inference and LearningGlossaryIndex

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Book SynopsisThis book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.Table of ContentsStream Learning.- Feature Learning.- Unsupervised Machine Learning.- Hardware.- Methods.- Quantization.

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Book SynopsisWe already observe the positive effects of AI in almost every field, and foresee its potential to help address our sustainable development goals and the urgent challenges for the preservation of the environment. We also perceive that the risks related to the safety, security, confidentiality, and fairness of AI systems, the threats to free will of possibly manipulative systems, as well as the impact of AI on the economy, employment, human rights, equality, diversity, inclusion, and social cohesion need to be better assessed. The development and use of AI must be guided by principles of social cohesion, environmental sustainability, resource sharing, and inclusion. It has to integrate human rights, and social, cultural, and ethical values of democracy. It requires continued education and training as well as continual assessment of its effects through social deliberation. The “Reflections on AI for Humanity” proposed in this book develop the following issues and sketch approaches for addressing them: How can we ensure the security requirements of critical applications and the safety and confidentiality of data communication and processing? What techniques and regulations for the validation, certification, and audit of AI tools are needed to develop confidence in AI? How can we identify and overcome biases in algorithms? How do we design systems that respect essential human values, ensuring moral equality and inclusion? What kinds of governance mechanisms are needed for personal data, metadata, and aggregated data at various levels? What are the effects of AI and automation on the transformation and social division of labor? What are the impacts on economic structures? What proactive and accommodation measures will be required? How will people benefit from decision support systems and personal digital assistants without the risk of manipulation? How do we design transparent and intelligible procedures and ensure that their functions reflect our values and criteria? How can we anticipate failure and restore human control over an AI system when it operates outside its intended scope? How can we devote a substantial part of our research and development resources to the major challenges of our time such as climate, environment, health, and education? Table of ContentsReflections on AI for Humanity: Introduction.- Trustworthy AI.- Democratising the digital revolution: the role of data governance.- Artificial Intelligence and the Future of Work.- Reflections on Decision-Making and Artificial Intelligence.- AI and Human values: inequalities, biases, fairness, nudge and feedback loops.- Next big challenges in core AI technology.- AI for Humanity: The Global Challenges.- AI and Constitutionalism: the challenges ahead.- Analyzing the Contributions of ethical charters to building the Future of Artificial Intelligence governance.- What does “Ethical by Design” Mean?.- AI for Digital Humanities and Computational Social Sciences.- Augmented Human and Human-Machine Co-Evolution: efficiency and ethics.- Democratizing AI for Humanity: A Common Goal.- A Framework for Global Cooperation on Artificial Intelligence and its Governance.

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Book SynopsisThis book discusses the various open issues of blockchain technology, such as the efficiency of blockchain in different domains of digital cryptocurrency, smart contracts, smart education system, smart cities, cloud identity and access, safeguard to cybersecurity and health care. For the first time in human history, people across the world can trust each other and transact over a large peer-to-peer networks without any central authority. This proves that, trust can be built not only by centralized institution but also by protocols and cryptographic mechanisms. The potential and collaboration between organizations and individuals within peer networks make it possible to potentially move to a global collaborative network without centralization. Blockchain is a complex social, economic and technological phenomenon. This questions what the established terminologies of the modern world like currency, trust, economics and exchange would mean. To make any sense, one needs to realize how much insightful and potential it is in the context and the way it is technically developed. Due to rapid changes in accessing the documents through online transactions and transferring the currency online, many previously used methods are proving insufficient and not secure to solve the problem which arises in the safe and hassle-free transaction. Nowadays, the world changes rapidly, and a transition flow is also seen in Business Process Management (BPM). The traditional Business Process Management holds good establishment last one to two decades, but, the internal workflow confined in a single organization. They do not manage the workflow process and information across organizations. If they do so, again fall in the same trap as the control transfers to the third party that is centralized server and it leads to tampering the data, and single point of failure. To address these issues, this book highlights a number of unique problems and effective solutions that reflects the state-of-the art in blockchain Technology. This book explores new experiments and yields promising solutions to the current challenges of blockchain technology. This book is intended for the researchers, academicians, faculties, scientists, blockchain specialists, business management and software industry professionals who will find it beneficial for their research work and set new ideas in the field of blockchain. This book caters research work in many fields of blockchain engineering, and it provides an in-depth knowledge of the fields covered.Table of ContentsBlockchain Technology Introduction, Applications, Challenges.- A Blockchain Framework for Healthcare Data Management.- Blockchain Technology in Healthcare Opportunities and Challenges.- Blockchain in Healthcare System Security Issues, Attacks and Challenges.- Application of Blockchain as a solution.- UML Conceptual Analysis of Smart Contract for Health Claim Processing.

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Book SynopsisKnowing our World: An Artificial Intelligence Perspective considers the methodologies of science, computation, and artificial intelligence to explore how we humans come to understand and operate in our world. While humankind’s history of articulating ideas and building machines that can replicate the activity of the human brain is impressive, Professor Luger focuses on understanding the skills that enable these goals. Based on insights afforded by the challenges of AI design and program building, Knowing our World proposes a foundation for the science of epistemology. Taking an interdisciplinary perspective, the book demonstrates that AI technology offers many representational structures and reasoning strategies that support clarification of these epistemic foundations. This monograph is organized in three Parts; the first three chapters introduce the reader to the foundations of computing and the philosophical background that supports the AI tradition. These three chapters describe the origins of AI, programming as iterative refinement, and the representations and very high-level language tools that support AI application building. The book’s second Part introduces three of the four paradigms that represent research and development in AI over the past seventy years: the symbol-based, connectionist, and complex adaptive systems. Luger presents several introductory programs in each area and demonstrates their use. The final three chapters present the primary theme of the book: bringing together the rationalist, empiricist, and pragmatist philosophical traditions in the context of a Bayesian world view. Luger describes Bayes' theorem with a simple proof to demonstrate epistemic insights. He describes research in model building and refinement and several philosophical issues that constrain the future growth of AI. The book concludes with his proposal of the epistemic stance of an active, pragmatic, model-revising realism.Table of ContentsPART I, In the Beginning.-1 Creating Computer Programs: An Epistemic Commitment.- 2 Historical Foundations.- 3 Modern AI and How We Got Here.- PART II, AI: Structures and Strategies for Complex Problem Solving.- 4 Symbol-Based AI and its Rationalist Presuppositions.- 5 Association and Connectionist Approaches to AI.- 6 Evolutionary Computation and Intelligence.- PART III, On Epistemology: Towards an Active, Pragmatic, Model-Revising Realism.- 7 A Constructivist Rapprochement and an Epistemic Stance.- 8 Bayesian-Based Constructivist Computational Models.- 9 Towards an Active, Pragmatic, Model-Revising Realism.-Bibliography.- Index.

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Book SynopsisThis open access book constitutes the thoroughly refereed post-conference proceedings of the 6th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence.The 7 revised full papers presented together with 2 invited contributions were reviewed and selected from 9 submissions. The contributions address various issues for knowledge representation and reasoning and the common graph-theoretic background, which allows to bridge the gap between the different communities.Table of ContentsExtended Workshop Papers.- Active Semantic Relations in Layered Enterprise Architecture Development.- A Belief Update System Using an Event Model for Location of People in a Smart Home.- A Natural Language Generation Technique for Automated Psychotherapy.- Creative Composition Problem: A Knowledge Graph Logical-based AI Construction and Optimization Solution.- Set Visualisations with Euler and Hasse Diagrams.- Usage Patterns Identification Using Graphs and Machine Learning.- Collaborative Design and Manufacture: Information Structures for Team Formation and Coordination.- Invited Additional Contributions.- Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification.- Galois Connections for Patterns: An Algebra of Labelled Graphs.

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Book SynopsisThe 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021.The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.Table of ContentsRepresentation Learning and Embedding.- Episode Adaptive Embedding Networks for Few-shot Learning.- Universal Representation for Code.- Self-supervised Adaptive Aggregator Learning on Graph.- A Fast Algorithm for Simultaneous Sparse Approximation.- STEPs-RL: Speech-Text Entanglement for Phonetically Sound Representation Learning.- RW-GCN: Training Graph Convolution Networks with biased random walk for Semi-Supervised Classification.- Loss-aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models.- SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network.- VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning.- Self-supervised Graph Representation Learning with Variational Inference.- Manifold Approximation and Projection by Maximizing Graph Information.- Learning Attention-based Translational Knowledge Graph Embedding via Nonlinear Dynamic Mapping.- Multi-Grained Dependency Graph Neural Network for Chinese Open Information Extraction.- Human-Understandable Decision Making for Visual Recognition.- LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding.- Transferring Domain Knowledge with an Adviser in Continuous Tasks.- Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach.- Quality Control for Hierarchical Classification with Incomplete Annotations.- Learning from Data.- Learning Discriminative Features using Multi-label Dual Space.- AutoCluster: Meta-learning Based Ensemble Method for Automated Unsupervised Clustering.- BanditRank: Learning to Rank Using Contextual Bandits.- A compressed and accelerated SegNet for plant leaf disease segmentation: A Differential Evolution based approach.- Meta-Context Transformers for Domain-Specific Response Generation.- A Multi-task Kernel Learning Algorithm for Survival Analysis.- Meta-data Augmentation based Search Strategy through Generative Adversarial Network for AutoML Model Selection.- Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction.- Rule Injection-based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning.- Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition.- Reinforced Natural Language Inference for Distantly Supervised Relation Classification.- SaGCN: Structure-aware Graph Convolution Network for Document-level Relation Extraction.- Addressing the class imbalance problem in medical image segmentation via accelerated Tversky loss function.- Incorporating Relational Knowledge in Explainable Fake News Detection.- Incorporating Syntactic Information into Relation Representations for Enhanced Relation Extraction.

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Book SynopsisThis book explains how various forms of artificial intelligence, namely machine learning, natural language processing, and robotic process automation, could provide a source of competitive advantage to firms deploying them compared to those firms that would not have deployed these technologies. The advantages of machine learning, natural language processing, and robotic process automation in strategy formulation and strategy implementation are explored. The book illustrates the potential sources of advantage for the strategy formulation and strategy implementation processes, which can be derived from the deployment of each form of artificial intelligence.Table of Contents1. Introduction to Artificial Intelligence and the Changing Nature of a Firm: Implications to Strategy and Strategy Implementation.- 2. A High-Level Overview of Artificial Intelligence: Historical Overview and Emerging Developments.- 3. A Brief Overview of the Firm’s Strategy.- 4. Strategy Implementation.- 5. Machine Learning in Strategy and Implementation.- 6. Natural Language Processing in Strategy and Implementation.- 7. Robotic Process Automation in Strategy and Strategy Implementation.- 8. Synopsis to Artificial Intelligence and the Nature of a Firm:Implications to Strategy and Strategy Implementation.

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Book SynopsisThis book presents recent developments in nonlinear and complex systems. It provides recent theoretic developments and new techniques based on a nonlinear dynamical systems approach that can be used to model and understand complex behavior in nonlinear dynamical systems. It covers information theory, relativistic chaotic dynamics, data analysis, relativistic chaotic dynamics, solvability issues in integro-differential equations, and inverse problems for parabolic differential equations, synchronization and chaotic transient. Presents new concepts for understanding and modeling complex systems Table of Contents1. Preface by Dr. Dimitri Volchenkov2. Chapter 1 . J. A. Tenreiro Machado, Shannon Information Analysis of the Chromosome Code.3. Chapter 2. Dimitri Volchenkov, Veniamin Smirnov, An Unfair Coin of the Standard & Poor’s 5004. Chapter 3. Relativistic chaotic scattering by Juan D. Bernal, Jesus M. Seoane, Miguel A.F. Sanjuan5. Chapter 4. Artificial Intelligence for Studying Perception of Ambiguous Images and Decision-Marking Processes in the Human Brain by Alexander N. Pisarchik, Anastasija E. Runnova, Nikita S. Frolov, and Alexander E. Hramov6. Chapter 5. Fuhong Min, Chuang Li, Multistability Coexistence of Memristive Chaotic System, and the Application in Image Decryption7. Chapter 6: Veniamin Smirnov, Zhuanzhuan Ma, And Dimitri Volchenkov, Extreme Events and Emergency Scales 8. Chapter 7: M. Edelman, Evolution of Systems with Power-Law Memory: Do We Have to Die?9. Chapter 8: Dimitri Volchenkov, Probability Entanglement and Destructive Interference in Biased Coin Tossing10. Chapter 9: Messoud Efendiev, Vitali Vougalter, On the solvability of some systems of integro-differential equations with drift.11. Chapter 10: Vitali Vougalter, Vitaly Volpert, Solvability in The Sense of Sequences For Some Non Fredholm Operators With The Bi-Laplacian 12. Chapter 11: Vitali Vougalter, The Preservation of Nonnegativity of Solutions of A Parabolic System With The Bi-Laplacian

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Book SynopsisThis open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures. Table of ContentsMachine Learning and Deep learning approaches in human brain mapping.- A high-resolution model of the human entorhinal cortex in the ‘BigBrain’– use case for machine learning and 3D analyses.- Deep learning-supported cytoarchitectonic mapping of the human lateral geniculate body in the BigBrain.- Brain modelling and simulation.- Computational modelling of cerebellar magnetic stimulation: the effect of washout?.- Usage and scaling of an open-source spiking multi-area model of the monkey cortex.- Exascale compute and data infrastructures for neuroscience and applications.- Modular supercomputing for neuroscience.- Fenix: Distributed e-Infrastructure Services for EBRAINS.- Independent component analysis for noise and artifact removal in three-dimensional Polarized Light Imaging.- Exascale artificial and natural neural architectures.- Brain-inspired algorithms for processing of visual data.- An hybrid attention-based system for the prediction of facial attributes.- The statistical physics of learning revisited: Typical learning curves in model scenarios.- Emotion mining: from unimodal to multimodal approaches.-

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Book SynopsisThis book constitutes the proceedings of the 19th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2021, held in Salamanca, Spain, in October 2021. The 27 regular and 13 short papers presented in this volume were carefully reviewed and selected from 56 submissions. They 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 SynopsisThis book constitutes the refereed proceedings of the Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with MICCAI 2021, in September/October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic.DART 2021 accepted 13 papers from the 21 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. For FAIR 2021, 10 papers from 17 submissions were accepted for publication. They focus on Image-to-Image Translation particularly for low-dose or low-resolution settings; Model Compactness and Compression; Domain Adaptation and Transfer Learning; Active, Continual and Meta-Learning. Table of ContentsDomain Adaptation and Representation Transfer.- A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis.- Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning.- FDA: Feature Decomposition and Aggregation for Robust Airway Segmentation.- Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation.- Self-Supervised Multimodal Generalized Zero Shot Learning For Gleason Grading.- Self-Supervised Learning of Inter-Label Geometric Relationships For Gleason Grade Segmentation.- Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training.- Transductive image segmentation: Self-training and effect of uncertainty estimation.- Unsupervised Domain Adaptation with Semantic Consistency across Heterogeneous Modalities for MRI Prostate Lesion Segmentation.- Cohort Bias Adaptation in Federated Datasets for Lesion Segmentation.- Exploring Deep Registration Latent Spaces.- Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift.- Unsupervised Domain Adaption via Similarity-based Prototypes for Cross-Modality Segmentation.- A ordable AI and Healthcare.- Classification and Generation of Microscopy Images with Plasmodium Falciparum via Arti cial Neural Networks using Low Cost Settings.- Contrast and Resolution Improvement of POCUS Using Self-Consistent CycleGAN.- Low-Dose Dynamic CT Perfusion Denoising without Training Data.- Recurrent Brain Graph Mapper for Predicting Time-Dependent Brain Graph Evaluation Trajectory.- COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19Patient Cases from Point-of-care Ultrasound Imaging.- Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning.- Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks.- Continual Domain Incremental Learning for Chest X-ray Classification in Low-Resource Clinical Settings.- Deep learning based Automatic detection of adequately positioned mammograms.- Can non-specialists provide high quality Gold standard labels in challenging modalities.

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Book SynopsisThis book constitutes the refereed proceedings of the 6th International Conference on Belief Functions, BELIEF 2021, held in Shanghai, China, in October 2021. The 30 full papers presented in this book were carefully selected and reviewed from 37 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.Table of ContentsClustering.- Transfer learning.- Classification.- Statistical inference and learning.- Deep learning.- Conflict, inconsistency and specificity.- Information fusion.- Elicitation.- Algorithms and computation.

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Book SynopsisOn what basis can we challenge Artificial Intelligence (AI) - its infusion, investment, and implementation across the globe? This book answers this question by drawing on a range of critical approaches from the social sciences and humanities, including posthumanism, ethics and human values, surveillance studies, Black feminism, and other strategies for social and political resistance. The authors analyse timely topics, including bias and language processing, responsibility and machine learning, COVID-19 and AI in health technologies, bio-AI and nanotechnology, digital ethics, AI and the gig economy, representations of AI in literature and culture, and many more. This book is for those who are currently working in the field of AI critique and disruption as well as in AI development and programming. It is also for those who want to learn more about how to doubt, question, challenge, reject, reform and otherwise reprise AI as it been practiced and promoted. Trade Review“The book offers a number of useful critiques of AI as it interacts with increasing numbers of Internet users. Readers should take the Marxist perspectives with a grain of salt.” (G. R. Mayforth, Computing Reviews, October 19, 2022)“All of the chapters are well written and the editorial process was clearly very good. … I found four essays particularly noteworthy … . If you are limited on time, these core essays are must-reads. I found this book interesting because it disclosed to me what others outside the computational science community see.” (Anthony J. Duben, Computing Reviews, July 20, 2022)Table of ContentsChapter 1: Introduction: Critical Insights: Bringing the social sciences and humanities to AI.- Section I: Posthumanism.- Chapter 2: Virtually Grown Up: Artificial Intelligence in Youth Fiction.- Chapter 3: The Feminized Robot: Labour and Harawayan Afterlives.- Section II: Human values.- Chapter 4: AI’s fast and furtive spread by infusion into technologies that are already in use – a critical assessment.- Chapter 5: Dumbwaiters & Smartphones: The Responsibility of Intelligence.- Section III: Media and Language.- Chapter 6: Artificial Intelligence: a medium that hides its nature.- Chapter 7: Gender Bias in Machine Translation Systems.- Section IV: Governance.- Chapter 8: Not Anytime Soon: The clinical translation of nanorobots.- Chapter 9: Controversial Covid-19 contact-tracing app in India: digital self-defence, governance and surveillance.- Chapter 10: Intelligent Justice’: AI Implementations in China's Legal Systems.- Section V: Resistance.- Chapter 11: Artificial Intelligence between Oppression and Resistance: Black Feminist Perspectives on Emerging Technologies.- Chapter 12: AI Ruined the Internet – and Everything Else: A manifesto.- Index.

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Book SynopsisThis book constitutes the refereed proceedings of the 19th International Symposium on Automated Technology for Verification and Analysis, ATVA 2021, held in Gold Coast, Australia in October 2021. The symposium is dedicated to promoting research in theoretical and practical aspects of automated analysis, verification and synthesis by providing an international venue for the researchers to present new results. The 19 regular papers presented together with 4 tool papers and 1 invited paper were carefully reviewed and selected from 75 submissions. The papers are divided into the following topical sub-headings: Automata Theory; Machine learning for Formal Methods; Theorem Proving and Tools; Model Checking; Probabilistic Analysis; Software and Hardware Verification; System Synthesis and Approximation; and Verification of Machine Learning.Table of ContentsInvited Paper.- Linear Temporal Logic ­ – From Infinite to Finite Horizon.- Automata Theory.- Determinization and Limit-determinization of Emerson-Lei automata.- Automatic discovery of fair paths in infinite-state transition systems.- Certifying DFA Bounds for Recognition and Separation.- Machine Learning for Formal Methods.- AALpy: An Active Automata Learning Library.- Learning Linear Temporal Properties from Noisy Data: A MaxSAT-based Approach.- Mining Interpretable Spatio-temporal Logic Properties for Spatially Distributed Systems.- Theorem Proving and Tools.- A Formal Semantics of the GraalVM Intermediate Representation.- A Verified Decision Procedure for Orders in Isabelle/HOL.- PJBDD: A BDD Library for Java and Multi-Threading.- Model Checking.- Live Synthesis.- Faster Pushdown Reachability Analysis with Applications in Network Verification.- Verifying Verified Code.- Probabilistic Analysis.- Probabilistic causes in Markov Chains.- TEMPEST - Synthesis Tool for Reactive Systems and Shields in Probabilistic Environments.- AQUA: Automated Quantized Inference for Probabilistic Programs.- Software and Hardware Verification.- Proving SIFA Protection of Masked Redundant Circuits.- Verification by Gambling on Program Slices.- Runtime Enforcement of Hyperproperties.- System Synthesis and Approximation.- Compositional Synthesis of Modular Systems.- Event-B Refinement for Continuous Behaviours Approximation.- Incorporating Monitors in Reactive Synthesis without Paying the Price.- Verification of Machine Learning.- pyNever: a Framework for Learning and Verification of Neural Networks.- Property-Directed Verification and Robustness Certification of Recurrent Neural Networks.

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Book SynopsisThis book constitutes the proceedings of the 41st SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2021, which was supposed to be held in Cambridge, UK, in December 2021. The conference was held virtually due to the COVID-19 pandemic.The 22 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 37 submissions. The volume includes technical papers presenting new and innovative developments in the field as well as application papers presenting innovative applications of AI techniques in a number of subject domains. The papers are organized in the following topical sections: technical paper; machine learning; AI techniques; short technical stream papers; application papers; applications of machine learning; AI for medicine; advances in applied AI; and short application stream papers. Table of ContentsTechnical Papers.- On the Generalization Abilities of Fine-Tuned Commonsense Language Representation Models (Best Technical Paper).- Machine Learning.- Generation of Human-aware Navigation Maps using Graph Neural Networks.- Extended Category Learning with Spiking Nets and Spike Timing Dependent Plasticity.- ORACLE: End-to-end Model Based Reinforcement Learning.- Towards Explaining Metaheuristic Solution Quality by Data Mining Surrogate Fitness Models for Importance of Variables.- AI Techniques.- Assessing the Impact of Agents in Weighted Bipolar Argumentation Frameworks.- Towards Explainable Metaheuristics: PCA for Trajectory Mining in Evolutionary Algorithms.- AI Methods of Autonomous Geological Target Selection in the Hunt for Signs of Extraterrestrial Life.- Probabilistic Rule Induction for Transparent CBR under Uncertainty.- Short Technical Stream Papers.- Detection of Brain Tumour using Deep Learning.- GaussianProductAttributes: Density-based Distributed Representations for Products.- Modelling Emotion Dynamics in Chatbots with Neural Hawkes Processes.- Knowledge-Based Composable Inductive Programming.- Named Entity Recognition and Relation Extraction for COVID-19: Explainable Active Learning with word2vec Embeddings and Transformer-based BERT Models.- Application Papers.- Patients Forecasting in Emergency Services by using Machine Learning and Exogenous variables (Best Application Paper).- Applications of Machine Learning.- Automatic Information Extraction from Electronic Documents using Machine Learning.- Modelling Satellite Data for Automobile Insurance Risk.- Ranking Pathology Data in the Absence of a Ground Truth.- Evolving Large Scale Prediction Models for Vehicle Volume Forecasting in Service Stations.- AI for Medicine.- Sequential Association Rule Mining Revisited: A Study Directed at Relational Pattern Mining for Multi-morbidity.- Addressing the Challenge of Data Heterogeneity using a Homogeneous Feature Vector Representation.- Context-aware Support for Cardiac Health Monitoring using Federated Machine Learning.- Using Automated Feature Selection for Building Case-Based Reasoning Systems: An Example from Patient-Reported Outcome Measurements.- Advances in Applied AI.- A Live-User Evaluation of a Visual Module Recommender & Advisory System for Undergraduate Students.- AdverseGen: A Practical Tool for Generating Adversarial Examples to Deep Neural Networks Using Black-box Approaches.- Adaptive Maneuver Planning for Autonomous Vehicles using Behavior Tree on Apollo Platform.- Behavioural User Identification from Clickstream Data for Business Improvement.- Short Application Stream Papers.- AI enabled Bio Waste Contamination-Scanner.- Parkinson's Disease Tremor Severity Classification - A Comparison Between ON and OFF Medication State.- Towards Publishing Ontology-based Data Quality Metadata of Open Data.- Towards a Brain Controller Interface for Generating Simple Berlin School Style Music with Interactive Genetic Algorithms.

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Book SynopsisThis Festschrift, dedicated to Bengt Jonsson on the occasion of his 60th birthday, contains papers written by many of his friends and collaborators.Bengt has made major contributions covering a wide range of topics including verification and learning. His works on verification, in finite state systems, learning, testing, probabilistic systems, timed systems, and distributed systems reflect both the diversity and the depth of his research. Besides being an excellent scientist, Bengt is also a leader who has greatly influenced the careers of both his students and his colleagues. His main focus throughout his career has been in the area of formal methods, and the research papers dedicated to him in this volume address related topics, particularly related to model checking, temporal logic, and automata learning.Table of ContentsModel Checking, Synthesis, and Learning.- From Linear Temporal Logics to Büchi Automata: The Early and Simple Principle.- Cause-Effect Reaction Latency In Real-Time Systems.- Quantitative Analysis of Interval Markov Chains.- Regular Model Checking: Evolution and Perspectives.- Regular Model Checking Revisited.- High-Level Representation of Benchmark Families for Petri Games.- Towards Engineering Digital Twinsby Active Behaviour Mining.- Never-Stop Context-Free Learning.- A Taxonomy and Reductions for Common Register Automata Formalisms.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th International Symposium on Human Mental Workload: Models and Applications, H-WORKLOAD 2021, held virtually in November 2021.The volume presents 9 revised full papers, which were carefully reviewed and selected from 16 submissions. The papers are organized in two topical sections on models and applications.Table of ContentsModels.- In search of the redline: perspectives on mental workload and the ‘underload problem’. - A novel parabolic model of instructional efficiency grounded on ideal mental workload and performance.- Radical Connectionism – Implications for Mental Workload Research.- Fundamental Frequency as an Alternative Method for Assessing Mental Fatigue of Distance Learning Teachers.- A systematic review of older drivers in a level 3 autonomous vehicle: A cognitive load perspective.- Applications.- On EEG Preprocessing Role in Deep Learning Effectiveness for Mental Workload Classification.- Mental Workload Assessment in Military Pilots Using Flight Simulators and Physiological Sensors.- Exploring the Influence of Information Overload, Internet Addiction, and Social Network Addiction, on Students' Well-being and Academic Outcomes.- Examining Cognitive Workload during Covid-19: A Qualitative Study.- The Relationship between Workload, Fatigue and Sleep Quality of Psychiatric Staff.

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Book SynopsisThis book constitutes the thoroughly refereed post-workshop proceedings of the 21th International Conference on Web Engineering, ICWE 2021, held in Biarritz, France, in May 2021.*The first international workshop on Big data-driven Edge Cloud Services (BECS 2021) was held to provide a venue in which scholars and practitioners can share their experiences and present on-going work on providing value-added Web services for users by utilizing big data in edge cloud environments. The 5 revised full papers and 1 revised short contribution selected from 11 submissions are presented with 2 invited papers.*The conference was held virtually due to the COVID-19 pandemic.Table of ContentsBECS 2021.- Putting Data Science Pipelines on the Edge.- DNN Model Deployment on Distributed Edges.- Towards Proactive Context-Aware IoT Environments by means of Federated Learning.- Real-time Deep Learning-based Anomaly Detection Approach for Multivariate Data Streams with Apache Flink.- A Novel Approach to Dynamic Pricing for Cloud Computing Through Price Band Prediction.- Learning-based Activation of Energy Harvesting Sensors for Fresh Data Acquisition.- Invited Papers.- Exploiting Triangle Patterns for Heterogeneous Graph Attention Network.- Towards Seamless IoT Device-Edge-Cloud Continuum: Software Architecture Options of IoT Devices Revisited.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of the 12th International Conference on Broadband Communications, Networks, and Systems, Broadnets 2021, which took place in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 24 full papers presented were carefully reviewed and selected from 49 submissions. The papers are thematically grouped as a session on broadband communications, networks, and systems; 5G-enabled smart building: technology and challenge; and 5G: The advances in industry.Table of ContentsBroadband communications, Networks, and Systems: Theory and Applications.- A Machine Learning-based Elastic Strategy for Operator Parallelism in a Big Data Stream Computing System.- End-to-End Dynamic Pipelining Tuning Strategy for Small Files Transfer.- Containers’ Privacy and Data Protection via Runtime Scanning Methods.- Digital Twin For Cybersecurity: Towards Enhancing Cyber Resilience.- Differential Privacy-based Permissioned Blockchain for Private Data Sharing in Industrial IoT.- Efficient Privacy-Preserving User Matching with Intel SGX.- Developing an Online Examination Timetabling System Using Artificial Bee Colony Algorithm in Higher Education.- A Topology-Aware Scheduling Strategy for Distributed Stream Computing System.- Data Stream Prediction Strategy for Elastic Stream Computing Systems.- Blockchain Enabled Integrity Protection for Bodycam Video.- Road Rage Recognition System Based on Face Detection Emotion.- A Drip Irrigation Remote Control System using 5G-IoT Technology.- Multipath QUIC - Directions of the Improvements.- One New Adaptive Elliptical Weighting Model Combining with the Tikhonov-ffp-norm for image reconstruction.- Calculation and Numerical Simulation of Building Integrated Photovoltaic System Based on Connected Autonomous Vehicle Platoon Control through Multi-Agent Deep Reinforcement Learning.- 5G-enabled Smart Building: Technology and Challenge.- Accurate Estimation on the State-of-Charge of Lithium-ion Battery Packs.- Fire Simulation and Optimial Evaluation Based on BIM Technology.- Discrete Sliding Mode Control of PMSM with Network Transmission.- Smart Medical and Nursing Platform Based on 5G Technology.- Time-domain predictable trajectory planning for autonomous driving based on Internet of Vehicles.- 5G: The Advances in Industry.- Rate-compatible shortened polar codes based on RM code-aided.- Research on wheat impurity image recognition based on convolutional neural network.- Based on Energy Router Energy Management Control Strategy in micro-grid.

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Book SynopsisThis book contains a selection of the best papers of the 33rd Benelux Conference on Artificial Intelligence, BNAIC/ BENELEARN 2021, held in Esch-sur-Alzette, Luxembourg, in November 2021. The 14 papers presented in this volume were carefully reviewed and selected from 46 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.

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Book SynopsisThis book constitutes the refereed proceedings of the Third International Conference on Distributed Artificial Intelligence, DAI 2021, held in Shanghai, China, in December 2021.The 15 full papers presented in this book were carefully reviewed and selected from 31 submissions. DAI aims at bringing together international researchers and practitioners in related areas including general AI, multiagent systems, distributed learning, computational game theory, etc., to provide a single, high-profile, internationally renowned forum for research in the theory and practice of distributed AI.Table of ContentsThe Power of Signaling and its Intrinsic Connection to the Price of Anarchy.- Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning.- SEIHAI: A Sample-effcient Hierarchical AI for the MineRL Competition.- GC: Multi-Agent Group Belief with Graph Clustering.- Incomplete Distributed Constraint Optimization Problems: Model, Algorithms, and Heuristics.- Securities Based Decision Markets.- MARL for Traffc Signal Control in Scenarios with Different Intersection Importance.- Safe Distributional Reinforcement Learning.- The Positive Effect of User Faults over Agent Perception in Collaborative Settings and its Use in Agent Design.- Behavioral Stable Marriage Problems.- FUN-Agent: a HUMAINE Competitor.- Signal Instructed Coordination in Cooperative Multi-Agent Reinforcement Learning.- A Description of the Jadescript Type System.- Combining M-MCTS and Deep Reinforcement Learning for General Game Playing.- A Two-Step Method for Dynamics of Abstract Argumentation.

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Book SynopsisThis book constitutes the refereed proceedings of the Second Southern African Conference on Artificial Intelligence Research, SACAIR 2021, held in Durban, South Africa, in December 2021. Due to the COVID-19 pandemic the SACAIR 2021 was held online. The 22 papers presented were thoroughly reviewed and selected from the 70 submissions. They are organized on the topical sections on ​AI in the humanities and society, AI in and for information systems, computer vision and image processing, deep learning, knowledge representation and reasoning, machine learning, philosophy and ethics of AI.Table of ContentsAI in the Humanities and Society.- AI in and for Information Systems.- Computer Vision and Image Processing.- Deep Learning.- Knowledge Representation and Reasoning.- Machine Learning.- Philosophy and Ethics of AI.

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Book SynopsisThis book constitutes the proceedings of the 17th International Conference on Advanced Data Mining and Applications, ADMA 2021, held in Sydney, Australia in February 2022.*The 26 full papers presented together with 35 short papers were carefully reviewed and selected from 116 submissions. The papers were organized in topical sections in Part I, including: Healthcare, Education, Web Application and On-device application. * The conference was originally planned for December 2021, but was postponed to 2022.

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Book SynopsisThis book constitutes the proceedings of the 17th International Conference on Advanced Data Mining and Applications, ADMA 2021, held in Sydney, Australia in February 2022.*The 26 full papers presented together with 35 short papers were carefully reviewed and selected from 116 submissions. The papers were organized in topical sections in Part II named: Pattern mining; Graph mining; Text mining; Multimedia and time series data mining; and Classification, clustering and recommendation. * The conference was originally planned for December 2021, but was postponed to 2022.

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Book SynopsisThis open access book aims at deepening the understanding of the relation between cyber-physical systems (CPSs) as socio-technical systems and their digital representations with intertwined artificial intelligence (AI). The authors describe why it is crucial for digital selves to be able to develop emotional behavior and why a humanity-inspired AI is necessary so that humans and humanoids can coexist. The introductory chapter describes major milestones in computer science which form the basis for the implementation of digital twins and digital selves. The subsequent Part I then lays the foundation to develop a socio-technical understanding of the nature of digital twins as representations and trans-human development objects. Following the conceptual understanding of digital twins and how they could be engineered according to cognitive and organizational structures, Part II forms the groundwork for understanding social behavior and its modeling. It discusses various perception-based socio-emotional approaches before sketching behavior-relevant models and their simulation capabilities. In particular, it is shown how emotions can substantially influence the collective behavior of artificial actors. Part III eventually presents a symbiosis showing under which preconditions digital selves might construct and produce digital twins as integrated design elements in trans-human ecosystems. The chapters in this part are dedicated to opportunities and modes of co-creating reflective socio-trans-human systems based on digital twin models, exploring mutual control and continuous development. The final epilog is congenitally speculative in its nature by presenting thoughts on future developments of artificial life in computational substrates. The book is written for researchers and professionals in areas like cyber-physical systems, robotics, social simulation or systems engineering, interested to take a speculative look into the future of digital twins and autonomous agents. It also touches upon philosophical aspects of digital twins, digital selves and humanoids.Table of Contents1. Major Historical Landmarks in Computer Science.- Part I: Digital Twins: Advent and Trans-human Development.- 2. Background and Foundations.- 3. Beyond Data: Unifying Behavior Modeling.- Part II: Social Behavior of Artificial Agents.- 4. Background and Motivation.- 5. Simulation Methods and Game Theory.- 6. Social Dilemmas and Problems of Social Order.- 7. Emotional Modeling with Spatial Games.- 8. Agent-Based Stochastic Simulation of Emotions.- Part III: A Symbiosis.- 9. System-of-Systems Thinking.- 10. Provision of Information as Relational Task.- 11. Enabling Contextual Adaptation.- 12. Embodying Social Behavior.- 13. How to Create Digital Selves.

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Book Synopsis.- Machine Intelligence..- Deep Learning based Novel Approach for Mammogram Classification using Densenet-169..- Attribute Based Federated-Reinforcement Learning Approach for Drone Authorization..- Chronic Kidney Disease prediction and interpretation using Explainable AI..- Systematic review and analysis of Artificial intelligence based breast cancer classification and detection..- War of Tweets: Sentiment Analysis on Ukraine Russia Conflict..- Implementing HRRN for evaluating Cloud performance using Reinforcement Learning..- Using Machine Learning for Prediction of Obstructions for Indoor Location Systems..- Privacy Threats and Protection in Artificial Intelligence and Machine Learning..- Combining linguistic information with BERT for Span based End-to-End Aspect Based Sentiment Analysis..- A Dimensionality Reduction Model: A Retrospective Approach on Dementia Triggering Parameters and Feature Ranking..- Effective Identification of Lung Diseases using Few-Shot Learning..- Comparative Study on Classification based- Data Mining Techniques in Early Diabetes Prediction..- Optimize Machine Learning Model for Sentiment Analysis of Online Education during Covid-19 Pandemic..- Review on the Challenges and Future Directions of Deep Learning-based Techniques for Advance Prediction of Cardiac Attack..- Different Techniques For Detecting  Plant Leaf Disease Using Machine  Learning..- Proposed Framework of Extensive Humanoid Design Cycle and Recent Developments in Bipedal Walk..- Natural Language Processing for Waste Management Using Public Opinions in Smart Cities..- Prediction of Diabetes during Pregnancy through Fog Environment..- Empirical Wavelet Transform grounded poignant ground target recognition and classification by Seismic Signal Processing..- A Powered-Up Classification of Disabling Distributed Network Cloud-Based Attacks Using MLPNN-BP and MLPNN-LM..- Stroke Prediction Framework Based on Missing Value Information and Outlier Detection by Using Machine Learning Techniques in E-Healthcare..- An Artificial Bee Colony Improved Deep Neural Network Prototypical for Controlling Unprovoked Stroke Data in Iot Environment..- Magnetic Resonance Imaging Digitization for Brain Abnormality Recognition..- Comparative investigation of ELM and No-Prop processes for Clustering and Classification: An Empirical Study..- Application of Theory of Nonlinear Dynamics to Study Automated Detection of Epileptic EEG Signals..- Writer-autonomous Offline Autograph Detection founded upon Histogram of oriented gradients (HOGs) feature..- Analysis & evaluation for segmentation of cancer in multi-parametric.

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Book SynopsisChapter 1 The Science of Emotion: Decoding and Analysis of Human Emotional Landscape.- Chapter 2 The Synergy of Clinical Psychology and Affective Computing: Advancements in Emotion Recognition and Therapy.- Chapter 3 Affective Computing in Mood Disorders: Beyond Conventional Diagnostic Tools to Modern Technologies.- Chapter 4 The Role of Affective Computing in Social Justice: Harnessing Equity and Inclusion.- Chapter 5 Exploring the Ethical Dimensions and Societal Consequences of Affective Computing.- Chapter 6 Natural Language Processing for Emotion Recognition and Analysis.- Chapter 7 From Data to Emotions: Affective Computing in Voice Emotion Detection.- Chapter 8 Visual Emotion Recognition Through Affective Computing.- Chapter 9 Affective Computing for Health Management via Recommender Systems: Exploring Challenges and Opportunities.- Chapter 10 Personalized Well-being Interventions (PWIs): A New Frontier in Mental Health.- Chapter 11 Enhancing Affective Computing in NLP through Data Augmentation: Strategies for Overcoming Limited Data Availability.- Chapter 12 Advancements in Multimodal Emotion Recognition: Integrating Facial Expressions and Physiological Signals.- Chapter 13 Ethical Considerations in Affective Computing.- Chapter 14 The Horizon of Consciousness for Affective Computing: Future Trends and Possibilities.

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Book SynopsisThe Importance of Context.- Toward a Theory of Context.- Large Language Models as Contextual Machines.- The One-Hundred Psychological Dimensions of Context.- Conceptualizing Context for Computational Content Analysis.- Reading Chekhov with AI.- Conversations Going Awry.- The Context of Social Norms.- Final Thoughts on AI for Understanding Context.

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Book Synopsis1. Linguistic Z number fuzzy probabilistic rough set and their corresponding three-way decisions.- 2. TOPSIS-based MAGDM under linguistic Z number information.- 3. A new approach of MCGDM: MARCOS-based alternatives measurement with ranking under linguistic Z number information and their application in the selection of logistics distribution cold chain centre.- 4. Linguistic Z number environment-based site selection of medical logistic centre with TODIM-VIKOR approach.- 5. MCGDM based on TODIM-PROMETHEE II under linguistic Z number environment and their application in site selection of emergency shelte.

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Book SynopsisThe Origins of Digital Age.- Mathematical notation and Python.- Counting Algorithms in Python.- Arithmetic Operations.- Square Root Algorithms.- Primality, Equations, Congruences .- Symbolic Computation.

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Book SynopsisINTRODUCTION.- INTERNET OF THINGS.- ENABLING COMMUNICATION TECHNOLOGIES FOR INTERNET OF THINGS.- INTERNET OF THINGS ARCHITECTURE LAYERS.- ATTACKS AND COUNTERMEASURES IN IOT LAYERS.- AUTHENTICATION AND AUTHORIZATION.- NETWORK PROTOCOLS FOR INTERNET OF THINGS.- ATTACKS, CHALLENGES, AND COUNTERMEASURES FOR AN INTEGRATING INTERNET OF THINGS FRAMEWORK.- APPLICATION 1 - ASYMMETRIC KEY CRYPTOGRAPHY BLOCKCHAINS FOR SMART GREENHOUSE FARMING.- APPLICATION 2 - SECURING SMART FARMING SYSTEMS.- CONCLUSION AND FUTURE RESEARCH DIRECTIONS.

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Book Synopsis.- Smart systems..- Design and implementation of a High-Performance Solar-Based Wireless Sensor Network..- IoT Security: Challenges, IDS Evolution and AI Defensive schemes: A Review..- An Effective Framework for Gastrointestinal disease detection using Hybrid features..- An Integrated Best-Worst-VIKOR Method for Evaluation and Selection of Luxury Hotels in India..- IPCCH:  Intrusion Prevention in Cloud Computing using Honeypot..- Entropy Based Transparent and Secure Watermarking Approach Using Arnold Transform..- Dual Scrambling Based Non Blind Robust and  Secure Color Watermarking Technique..- Efficient Technique for Image Enhancement Using Generative Adversarial Network..- An overview of Security Intelligence in IoT Applications with Learning Approaches..- Natural language processing: innovations, recent trends  and challenges..- Neural Machine Translation in Low-Resource Context:  Survey..- Recommendation System for Movies Using Improved version of SOM with Hybrid Filtering Methods..- Hierarchical Attention with Time Information based Healthcare System for Drug Recommendation and ADR Detection..- Evaluation of Different Mapping Schemes for Detection of Tandem Repeats in DNA Sequences..- A Survey on Mammogram Datasets to Develop Breast CAD System..- A Hybrid Approach for Preserving Source Location Privacy for Wireless Sensor Networks..- Multi-Criteria Decision Making Based Optimal Clustering Method for WSN..- Phish-EYE: A New Approach to Detect Homograph domain phishing Attack using Domain Binary Visualization and TensorFlow..- Effect of Cosine Decay Restart Learning Rate Scheduler on Movie Recommender System..- How Optimization Will Influence a Software Quality  Characteristics Recommendation Model..- N-Gram approach to preparing Crime-related Legal DataSet: A roadmap to classify Legal Text..- Handling Mouse Events using Finger's Landmarks..- Analysis on Stock Market stream data using Kafka, AWS and Power BI..- An algorithm for estimating corrected-QT interval in the Electrocardiogram..- Enterprise of Fusion Cryptography-Steganographic Method for Cloud Loading Refuge    with Social Spider Optimization Algorithm..- FOG Grounded Observing Scheme for E-Healthcare based Stroke Estimation and Alert message in IoT Environment..- A System for Automatically Classifying Social Network Posts into Smart Cities Dimensions..- Drowsiness detection and prevention models for the elderly people: a promising design..- An Empirical Evaluation of Pre-Trained Convolutional  Neural Network Models for Neural Style Transfer..- Offline Handwritten Signature Identification and Verification Using LBP features..- Structured and Sparse Principle Component Analysis for Multi-Modal Data Fusion Approach..- Squared Fault and Biased Entropy for Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) Image Synthesis using Firefly Algorithm.

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Book SynopsisForeword of two Engineering Scientists.- Foreword of a Medical and Psychoanalytical Scientist.- Prolog.- Acknowledgements.- Preface by Dietmar Dietrich.- Preface by Volker A. Hartmann Cardelle. 1. Motivation.- 2. Philosophy, Consciousness and Axiomatic.- 3. Neurological and Psychoanalytical Models.- 4. Why Do Humans Need Machines with Consciousness?.- 5 Models and Tools of Computer Technology for Bridging Neurology and Psychoanalysis.- 6. Development of the ?-Organ Model (SiMA Model).- 7. Conclusion.- References.- Appendix by Volker Hartmann Cardelle.- Index.

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