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• Part I - AI Concepts
• As the introductory section, this section will discuss the history and basic concepts of AI.
• Chap 1
• AI and Human Civilization - From Greek Mythology to AI Robotics
• Chap 2
• AI Fundamentals
• 2.1
• Definition of AI
• 2.2
• A Brief History of AI
• 2.3
• Turing Test and AI
• 2.4
• Strong AI vs Weak AI
• 2.5
• Main components of AI
• 2.6
• Case Study: Does Turing Test Really Work to Test for AI?
• Part II - AI Technologies
• This section discusses FIVE core AI Technologies which provide the building blocks of various different kind of AI applications, they are: Machine Learning (ML), Data Mining (DM), Computer Vision (CV), Natural Languages Processing (NLP), Ontology-based Search Engine (OSE).
• Chap 3
• Machine Learning (ML)
• 3.1
• What is Machine Learning (ML)?
• 3.2
• Supervised Learning (SL)
• 3.3
• Unsupervised Learning (UL)
• 3.4
• Reinforcement Learning (RL)
• 3.5
• Case Study - How can we improve our memory by using Reinforcement Learning?
• Chap 4
• Data Mining (DM) & Big Data (BD)
• 4.1
• What is Knowledge?
• 4.2
• Data Mining, Big Data and Knowledge Discovery
• 4.3
• Traditional Data Mining Technology
• 4.4
• AI-based Data Mining Technology
• 4.5
• Case Study - How to "mine" our purchase habit using Data Mining Technology?
• Chap 5
• Computer Vision (CV)
• 5.1
• Computer Vision vs Human Vision
• 5.2
• 3 Levels of Computer Vision - Figure-ground Segmentation, Pattern Recognition, Active Vision
• 5.3
• Active Vision and Robotics
• 5.4
• Computer Vision Technology
• 5.5
• Case Study - How AI-based Facial Recognition System works?
• Chap 6
• Natural Language Processing (NLP)
• 6.1
• Human Language and Intelligence
• 6.2
• Natural Language Processing in AI
• 6.3
• Speech Recognition and Voice Synthesis
• 6.4
• Machine Translation
• 6.5
• Case Study - English Language Tutoring Robots
• Chap 7 Ontological-based Search Engine (OSE)
• 7.1
• Human Knowledge and Ontology
• 7.2
• How Search Engine Works?
• 7.3
• Traditional Search Engine vs. Ontological-based Search Engine
• 7.4
• Ontological-based Search Engine and Semantic Web
• 7.5
• Case Study - Turing Test and Ontology Search Engine
• Part III - AI Applications
• This section will discuss major contemporary AI applications which affect ways of living, working style and environment ranging from Intelligent Agents and Robotics to smart campus and smart city projects.
• Chap 8 Intelligent Agents and Robotics
• 8.1
• Hardware Robots vs Software Agents
• 8.2
• Intelligent Agent Technology
• 8.3
• Agent Applications
• 8.4
• Case Study - A Real Case of Shopping and Bargaining Agents
• Chap 9 Intelligent Transportation
• 9.1
• From 1G to 5G
• 9.2
• Location-based System and Positing Technology
• 9.3
• AI-based Auto-driving System
• 9.4
• Intelligent Transportation Systems
• 9.5
• Case Study - How Intelligent Transportation Reshape our Daily Life?
• Chap 10 Smart Health
• 10.1 IoT and Intelligent Sensor Technology
• 10.2 Smart Health Monitoring Devices
• 10.3 Smart Doctor and Expert Systems
• 10.4 Smart Surgeon and Remote Surgery
• 10.5 Case Study - How AI and Big Data work to improve your health?
• Chap 11 Smart Education
• 11.1 Reinforcement Learning vs Traditional Learning
• 11.2 Reinforcement iLearning System
• 11.3 Ontological-based iLearning System
• 11.4 Case Study -AR-based Intelligent Holographical Classroom
• Chap 12 Smart City
• 12.1 Major Components of Smart City
• 12.2 Smart Pole
• 12.3 Smart House
• 12.4 Smart Campus
• 12.5 Case Study - How Smart City Reshape Our Daily Life?
• Part V - Beyond AI
• The section will discuss the topics beyond but critically important for the future development of AI. In particular, it will also discuss some critical issues such as ethics, the development of conscious mind, autonomous robotic in our daily life and related topics.
• Chap 13 AI and Self-consciousness
• 13.1 What is Intelligence?
• 13.2 Self-consciousness in AI
• 13.3 Self-awareness Agents
• 13.4 Case Study: Self-awareness AI, are we still in control?
• Chap 14 AI Ethics, Security and Privacy
• 14.1 AI THREE Golden Rule of Ethics
• 14.2 Internet Security and Authentication Technology
• 14.3 AI Security and Privacy Issues
• 14.4 Case Study: Do we need a new set of AI Ethic Rules?
• Chap 15 What's Next?
• 15.1 Beyond 5G + AI, What next?
• 15.2 AI and Quantum Computing
• 15.3 New Challenges in Future AI
• 15.4 Conclusion
• .
• (source: Nielsen Book Data)

Given the exponential growth of Artificial Intelligence (AI) over the past few decades, AI and its related applications have become part of daily life in ways that we could never have dreamt of only a century ago. Our routines have been changed beyond measure by robotics and AI, which are now used in a vast array of services. Though AI is still in its infancy, we have already benefited immensely. This book introduces readers to basic Artificial Intelligence concepts, and helps them understand the relationship between AI and daily life. In the interest of clarity, the content is divided into four major parts. Part I (AI Concepts) presents fundamental concepts of and information on AI; while Part II (AI Technology) introduces readers to the five core AI Technologies that provide the building blocks for various AI applications, namely: Machine Learning (ML), Data Mining (DM), Computer Vision (CV), Natural Languages Processing (NLP), and Ontology-based Search Engine (OSE). In turn, Part III (AI Applications) reviews major contemporary applications that are impacting our ways of life, working styles and environment, ranging from intelligent agents and robotics to smart campus and smart city projects. Lastly, Part IV (Beyond AI) addresses related topics that are vital to the future development of AI. It also discusses a number of critical issues, such as AI ethics and privacy, the development of a conscious mind, and autonomous robotics in our daily lives. .
(source: Nielsen Book Data)

• Full Papers.- Short Papers.- Industry & Innovation Papers.- Doctoral Consortium Papers.- Workshops.
• (source: Nielsen Book Data)

This two-volume set LNAI 12163 and 12164 constitutes the refereed proceedings of the 21th International Conference on Artificial Intelligence in Education, AIED 2020, held in Ifrane, Morocco, in July 2020.*The 49 full papers presented together with 66 short, 4 industry & innovation, 4 doctoral consortium, and 4 workshop papers were carefully reviewed and selected from 214 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas. *The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Introduction.- Definition, motivation and impact of digitalization in energy transition.- Definition of a general scheme (layers) of a digitalized system in energy transition.- Challenges of digitalization in energy transition.- Artificial Intelligence for energy transition.- General principals and classification of Artificial Intelligence techniques for energy transition.- Artificial Intelligence for Smart Energy Management.- Smart energy management (intrusive and non-intrusive load monitoring).- Artificial Intelligence for Cyber Security and Privacy.- Artificial Intelligence for Mobility and Electrical Vehicles.- Mobility and electrical vehicles.- Artificial Intelligence for Micro Grid Operations and Dynamic Pricing Revenue Management.- Micro Grid operations and Dynamic Pricing Revenue Management.- Artificial Intelligence for Renewable Energy Penetration and Demand Side Management.- Renewable Energy Penetration and Demand Side Management.- Emerging Trends, Open problems, and Future Challenges.- Conclusion.
• (source: Nielsen Book Data)

This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).
(source: Nielsen Book Data)

• Towards an Assistive Social Robot Interacting with Human Patient to Establish a Mutual and Effective Support.- Selecting for Positive Responses to Knock outs in Boolean Networks.- Avalanches of Perturbations in Modular Gene Regulatory Networks.- The Effects of a Simplified Model of Chromatin Dynamics on Attractors Robustness in Random Boolean Networks with Self-loops: an Experimental Study.- A Memetic Approach for the Orienteering Problem.- The Detection of Dynamical Organization in Cancer Evolution Models.- The Simulation of Noise Impact on the Dynamics of a Discrete Chaotic Map.- Exploiting Distributed Discrete-Event Simulation Techniques for Parallel Execution of Cellular Automata.- A Relevance Index-based Method for Improved Detection of Malicious Users in Social Networks.- An Analysis of Cooperative Coevolutionary Differential Evolution as Neural Networks Optimizer.- Design and Evaluation of a Heuristic Optimization Tool Based on Evolutionary Grammars Using PSoCs.- How Word Choice Affects Cognitive Impairment Detection by Handwriting Analysis: a Preliminary Study.- Modeling the Coordination of a Multiple Robots Using Nature Inspired Approaches.- Nestedness Temperature in the Agent-Artifact Space: Emergence of Hierarchical Order in the 2000-2014 Photonics Techno-Economic Complex System.- Towards Programmable Chemistries.- Studying and Simulating the Three-dimensional Arrangement of Droplets.- Investigating Three-dimensional Arrangements of Droplets.
• (source: Nielsen Book Data)

This book constitutes the revised selected papers of the 14th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2019, held in Rende, Italy, in September 2019. The 13 full papers and 4 short paper presented were thoroughly reviewed and selected from 31 submissions. They are focused on the topics of information systems, design and analysis of algorithms, artificial intelligence, machine learning, cognitive science, modeling and simulation, collaborative and social computing, parallel computing, distributed computing. The chapter "Nestedness Temperature in the Agent-Artifact Space: Emergence of Hierarchical Order in the 2000-2014 Photonics Techno-Economic Complex System" is available open access under a CC BY 4.0 license.
(source: Nielsen Book Data)

• Deep Learning Methods for Image Guidance in Radiation Therapy Intentional Image Similarity Search.- Sttructured (De)composable Representations Trained with Neural Networks.- Long Distance Relationships without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling.- Improving Accuracy and Efficiency of Object Detection Algorithms using Multiscale Feature Aggregation Plugins.- Abstract Echo State Networks.- Minimal Complexity Support Vector Machines.- Named Entity Disambiguation at Scale.- Geometric Attention for Prediction of Differential Properties in 3D Point Clouds.- How (Not) to Measure Bias in Face Recognition Networks.-Feature Extraction: A Time Window Analysis based on the X-ITE Pain Database.- Pain Intensity Recognition - An Analysis of Short-Time Sequences in a Real-World Scenario.- A deep learning approach for efficient registration of dual view mammography.- Deep Transfer Learning for Texture Classification in Colorectal Cancer Histology.- Applications of Generative Adversarial Networks to Dermatologic Imaging.- Typing Plasmids with Distributed Sequence Representation.- KP-YOLO: a modification of YOLO algorithm for the keypoint-based detection of QR Codes.- Using Mask R-CNN for Image-Based Wear Classification of Solid Carbide Milling and Drilling Tools.- A Hybrid Deep Learning Approach For Forecasting Air Temperature.- Using CNNs to optimize numerical simulations in geotechnical engineering.- Going for 2D or 3D? Investigating various Machine Learning Approaches for Peach Variety Identification.- A Transfer Learning End-to-End Arabic Text-To-Speech (TTS) Deep Architecture.- ML-Based Trading Models: An investigation during COVID-19 pandemic crisis.- iNNvestigate-GUI - Explaining Neural Networks Through an Interactive Visualization Tool.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
(source: Nielsen Book Data)

• Augmented Cognition in Learning
• Assessing Intravenous Catheterization Simulation Training of Nursing Students Using Functional Near-Infrared Spectroscopy (fNIRs)
• Using fMRI to Predict Training Effectiveness in Visual Scene Analysis
• Synthetic Expertise
• The Expertise Level
• The Dark Sides of Technology
• Barriers to Work-Integrated Learning
• Exploring the Effects of Immersive Virtual Reality on Learning Outcomes: A Two-Path Model
• Flip-Flop Quizzes: A Case Study Analysis to Inform the Design of Augmented Cognition Applications
• Metastimuli: an Introduction to PIMS Filtering
• How Gamification Increases Learning Performance? Investigating the Role of Task Modularity
• Increasing Engagement in a Cyber-Awareness Training Game
• Augmented Cognition for Well-being, Health and Rehabilitation
• Acceptability and Normative Considerations in Research on Autism Spectrum Disorders and Virtual Reality
• Feedback Control for Optimizing Human Wellness
• The Case for Cognitive-Affective Architectures as Affective User Models in Behavioral Health Technologies
• Gathering Peoples Happy Moments from Collective Human Eyes and Ears for a Wellbeing and Mindful Society
• Examination of Stammering Symptomatic Improvement Training using Heartbeat-linked Vibration Stimulation
• Guided Mindfulness: Using Expert Schemas to Evaluate Complex Skill Acquisition
• An Overview of Virtual Reality Interventions for two Neurodevelopmental Disorders: Intellectual Disabilities and Autism
• Human Cognition and Behavior in Complex Tasks and Environments
• Effect of Robotic Surgery Simulators in Training Assessed by Functional Near-Infrared Spectroscopy (fNIRs)
• Preparing for Cyber Crisis Management Exercises
• Tracking Technostress: A Task-Interruption of Data Entry Study
• Enhancing Reality: Adaptation Strategies for AR in the Field
• Confronting Information Security's Elephant, the Unintentional Insider Threat
• Adapting Interaction to Address Critical User States of High Workload and Incorrect Attentional Focus
• an Evaluation of Five Adaptation Strategies
• Information-Theoretic Methods Applied to Dispatch of Emergency Services Data
• Experimental Evaluation of an Adaptive Planning Assistance System in Manned Unmanned Teaming Missions
• Cognitive Variability Factors and Passphrase Selection"
• Variable Self-efficacy as a Measurement for Behaviours in Cyber Security Operations
• Probing for Psycho-Physiological Correlates of Cognitive Interaction with Cybersecurity Events
• Tracking and Improving Strategy Adaptivity in a Complex Task
• Computing with Words in Maritime Piracy and Attack Detection Systems
• Modeling User Information Needs to Enable Successful Human-Machine Teams: Designing Transparency for Autonomous Systems
• The Role of Gaze as a Deictic Cue in Human Robot Interaction.

This book constitutes the refereed proceedings of 14th International Conference on Augmented Cognition, AC 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020, in July 2020. The conference was planned to be held in Copenhagen, Denmark, but had to change to a virtual conference mode due to the COVID-19 pandemic. From a total of 6326 submissions, a total of 1439 papers and 238 posters has been accepted for publication in the HCII 2020 proceedings. The 21 papers presented in this volume were organized in topical sections as follows: cognitive modeling, perception, emotion and interaction; electroencephalography and BCI; and AI and augmented cognition.

• Cognitive Modeling, Perception, Emotion and Interaction.- User Evaluation of Affective Dynamic Difficulty Adjustment based on Physiological Deep Learning.- Understanding Challenges Presented using Emojis as a Form of Augmented Communication.- Investigation of Biological Signals under the Stimulation of Basic Tastes.- Multimodal Analysis using Neuroimaging and Eye Movements to Assess Cognitive Workload.- Challenges and Prospects of Emotional State Diagnosis in Command and Control Environments.- The Platonic-Freudian Model of Mind: Defining "Self" and "Other" as Psychoinformatic Primitives.- A Preliminary Experiment on the Evaluation of Aroma Effects using biological signals.- Electroencephalography and BCI.- A Neuroimaging Approach to Evaluate Choices and Compare Performance of Tower Air Traffic Controllers during Missed Approaches.- A Multi-Stage Theory of Neurofeedback Learning.- Analyses of Impression Changes and Frontal Lobe Activity While Viewing Videos.- Visualizing Emotion and Absorption through a Low Resolution LED Array: From Electroencephalography to Internet of Things.- Methodology for Detection of ERD/ERS EEG Patterns Produced by Cut Events in Film Fragments.- A Study of Colour using Mindwave EEG Sensor.- Ensemble Usage for Classification of EEG Signals: A Review with Comparison.- A Reliable Neurophysiological Assessment of Stress
• Basic Foundations for a Portable BCI Solution.- AI and Augmented Cognition.- No Free Lunch: Free at Last.- Biomimetic Design in Augmented Cognition.- A Field Theory for Multi-Dimensional Scaling.- Non-Monotonic Bias-Based Reasoning Under Uncertainty.- Explainable Artificial Intelligence: What Do You Need to Know?.- The Way We Think about Ourselves.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of 14th International Conference on Augmented Cognition, AC 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020, in July 2020. The conference was planned to be held in Copenhagen, Denmark, but had to change to a virtual conference mode due to the COVID-19 pandemic.From a total of 6326 submissions, a total of 1439 papers and 238 posters has been accepted for publication in the HCII 2020 proceedings. The 21 papers presented in this volume were organized in topical sections as follows: cognitive modeling, perception, emotion and interaction; electroencephalography and BCI; and AI and augmented cognition.
(source: Nielsen Book Data)

• Virtual Reality.- Augmented Reality.- Mixed Reality.- 3D Reconstruction and Visualization.
• (source: Nielsen Book Data)

The 2-volume set LNCS 12242 and 12243 constitutes the refereed proceedings of the 7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2020, held in Lecce, Italy, in September 2020.* The 45 full papers and 14 short papers presented were carefully reviewed and selected from 99 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, 3D reconstruction visualization, and applications in the areas of cultural heritage, medicine, education, and industry. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Applications in Cultural Heritage.- Applications in Medicine.- Applications in Education.- Applications in Industry.
• (source: Nielsen Book Data)

The 2-volume set LNCS 12242 and 12243 constitutes the refereed proceedings of the 7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2020, held in Lecce, Italy, in September 2020.*The 45 full papers and 14 short papers presented were carefully reviewed and selected from 99 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, 3D reconstruction visualization, and applications in the areas of cultural heritage, medicine, education, and industry. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Invited Paper.- Efficient Automated Reasoning about Sets and Multisets with Cardinality Constraints.- SAT
• SMT and QBF.- An SMT Theory of Fixed-Point Arithmetic.- Covered Clauses Are Not Propagation Redundant.- The Resolution of Keller's Conjecture.- How QBF Expansion Makes Strategy Extraction Hard.- Removing Algebraic Data Types from Constrained Horn Clauses Using Difference Predicates.- Solving bit-vectors with MCSAT: explanations from bits and pieces.- Monadic Decomposition in Integer Linear Arithmetic.- Scalable Algorithms for Abduction via Enumerative Syntax-Guided Synthesis.- Decision Procedures and Combination of Theories.- Deciding the Word Problem for Ground Identities with Commutative and Extensional Symbols.- Combined Covers and Beth Definability.- Deciding Simple Infinity Axiom Sets with one Binary Relation by Means of Superpostulates.- A Decision Procedure for String to Code Point Conversion.- Politeness for The Theory of Algebraic Datatypes.- Superposition.- A Knuth-Bendix-Like Ordering for Orienting Combinator Equations.- A Combinator-Based Superposition Calculus for Higher-Order Logic.- Subsumption Demodulation in First-Order Theorem Proving.- A Comprehensive Framework for Saturation Theorem Proving.- Proof Procedures.- Possible Models Computation and Revision - A Practical Approach.- SGGS Decision Procedures.- Integrating Induction and Coinduction via Closure Operators and Proof Cycles.- Logic-Independent Proof Search in Logical Frameworks (short paper).- Layered Clause Selection for Theory Reasoning (short paper).- Non Classical Logics.- Description Logics with Concrete Domains and General Concept Inclusions Revisited.- A Formally Verified, Optimized Monitor for Metric First-Order Dynamic Logic.- Constructive Hybrid Games.- Formalizing a Seligman-Style Tableau System for Hybrid Logic (short paper).- NP Reasoning in the Monotone -Calculus.- Soft subexponentials and multiplexing.- Mechanised Modal Model Theory.
• (source: Nielsen Book Data)

This two-volume set LNAI 12166 and 12167 constitutes the refereed proceedings of the 10th International Joint Conference on Automated Reasoning, IJCAR 2020, held in Paris, France, in July 2020.* In 2020, IJCAR was a merger of the following leading events, namely CADE (International Conference on Automated Deduction), FroCoS (International Symposium on Frontiers of Combining Systems), ITP (International Conference on Interactive Theorem Proving), and TABLEAUX (International Conference on Analytic Tableaux and Related Methods). The 46 full research papers, 5 short papers, and 11 system descriptions presented together with two invited talks were carefully reviewed and selected from 150 submissions. The papers focus on the following topics: Part I: SAT; SMT and QBF; decision procedures and combination of theories; superposition; proof procedures; non classical logics Part II: interactive theorem proving/ HOL; formalizations; verification; reasoning systems and tools *The conference was held virtually due to the COVID-19 pandemic. Chapter 'Constructive Hybrid Games' is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
(source: Nielsen Book Data)

• Interactive Theorem Proving/ HOL.- Competing inheritance paths in dependent type theory: a case study in functional analysis.- A Lean tactic for normalising ring expressions with exponents (short paper).- Practical proof search for Coq by type inhabitation.- Quotients of Bounded Natural Functors.- Trakhtenbrot's Theorem in Coq.- Deep Generation of Coq Lemma Names Using Elaborated Terms.- Extensible Extraction of Efficient Imperative Programs with Foreign Functions, Manually Managed Memory, and Proofs.- Validating Mathematical Structures.- Teaching Automated Theorem Proving by Example: PyRes 1.2 (system description).- Beyond Notations: Hygienic Macro Expansion for Theorem Proving Languages.- Formalizations.- Formalizing the Face Lattice of Polyhedra.- Algebraically Closed Fields in Isabelle/HOL.- Formalization of Forcing in Isabelle/ZF.- Reasoning about Algebraic Structures with Implicit Carriers in Isabelle/HOL.- Formal Proof of the Group Law for Edwards Elliptic Curves.- Verifying Farad_zev-Read type Isomorph-Free Exhaustive Generation.- Verification.- Verified Approximation Algorithms.- Efficient Verified Implementation of Introsort and Pdqsort.- A Fast Verified Liveness Analysis in SSA form.- Verification of Closest Pair of Points Algorithms.- Reasoning Systems and Tools.- A Polymorphic Vampire (short paper).- N-PAT: A Nested Model-Checker (system description).- HYPNO: Theorem Proving with Hypersequent Calculi for Non-Normal Modal Logics (system description).- Implementing superposition in iProver (system description).- Moin: A Nested Sequent Theorem Prover for Intuitionistic Modal Logics (system description).- Make E Smart Again.- Automatically Proving and Disproving Feasibility Conditions.- -term: Verify Termination Properties Automatically (system description).- ENIGMA Anonymous: Symbol-Independent Inference Guiding Machine (system description).- The Imandra Automated Reasoning System (system description).- A Programmer's Text Editor for a Logical Theory: The SUMOjEdit Editor (system description).- Sequoia: a playground for logicians (system description).- Prolog Technology Reinforcement Learning Prover (system description).
• (source: Nielsen Book Data)

This two-volume set LNAI 12166 and 12167 constitutes the refereed proceedings of the 10th International Joint Conference on Automated Reasoning, IJCAR 2020, held in Paris, France, in July 2020.* In 2020, IJCAR was a merger of the following leading events, namely CADE (International Conference on Automated Deduction), FroCoS (International Symposium on Frontiers of Combining Systems), ITP (International Conference on Interactive Theorem Proving), and TABLEAUX (International Conference on Analytic Tableaux and Related Methods). The 46 full research papers, 5 short papers, and 11 system descriptions presented together with two invited talks were carefully reviewed and selected from 150 submissions. The papers focus on the following topics: Part I: SAT; SMT and QBF; decision procedures and combination of theories; superposition; proof procedures; non classical logics Part II: interactive theorem proving/ HOL; formalizations; verification; reasoning systems and tools *The conference was held virtually due to the COVID-19 pandemic. Chapter 'A Fast Verified Liveness Analysis in SSA Form' is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
(source: Nielsen Book Data)

• Part 1: Preparing for the Future of Work
• Chapter 1: Will Robots Replace You?
• Chapter 2: Technology Definitions
• Part 2: Robots are Working
• Chapter 3: Robotic Process Automation
• Chapter 4: Robots in Teams
• Chapter 5: Robots Without Arms
• Part 3: Making Sense for Robots and Society
• Chapter 6: Robots in a World of Data
• Chapter 7: Robots in Society
• Chapter 8: Work in the Future.

Understand the current and future research into technologies that underpin the increasing capabilities of automation technologies and their impact on the working world of the future. Rapid advances in automation and robotics technologies are often reported in the trade and general media, often relying on scary headlines such as "Jobs Lost to Robots." It is certainly true that work will change with the advent of smarter and faster automated workers; however, the scope and scale of the changes is still unknown. Automation may seem to be here already, but we are only at the early stages. Automation and Collaborative Robotics explores the output of current research projects that are improving the building blocks of an automated world. Research into collaborative robotics (cobotics) is merging digital, audio, and visual data to generate a commonly held view between cobots and their human collaborators. Low-power machine learning at the edge of the network can deliver decision making on cobots or to their manipulations. Topics covered in this book include: Robotic process automation, chatbots, and their impact in the near future The hype of automation and headlines leading to concerns over the future of work Component technologies that are still in the research labs Foundational technologies and collaboration that will enable many tasks to be automated with human workers being re-skilled and displaced rather than replaced What You Will Learn Be aware of the technologies currently being researched to improve or deliver automation Understand the impact of robotics, other automation technologies, and the impact of AI on automation Get an idea of how far we are from implementation of an automated future Know what work will look like in the future with the deployment of these technologies Who This Book Is For Technical and business managers interested in the future of automation and robotics, and the impact it will have on their organizations, customers, and the business world in general.
(source: Nielsen Book Data)

• Best Paper Session.- AI Challenges on Cambircon using AIBenc.- AI Challenges on RISC-V using AIBench.- AI Challenges on X86 using AIBench.- AI Challenges on 3D Face Recognition using AIBench.- Benchmark.- AI and Edge.- Big Data.- Datacenter.- Performance Analysis.- Scientific Computing.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the Second International Symposium on Benchmarking, Measuring, and Optimization, Bench 2019, held in Denver, CO, USA, in November 2019. The 20 full papers and 11 short papers presented were carefully reviewed and selected from 79 submissions. The papers are organized in topical sections named: Best Paper Session; AI Challenges on Cambircon using AIBenc; AI Challenges on RISC-V using AIBench; AI Challenges on X86 using AIBench; AI Challenges on 3D Face Recognition using AIBench; Benchmark; AI and Edge; Big Data; Datacenter; Performance Analysis; Scientific Computing.
(source: Nielsen Book Data)

• Facets of Fairness in Search and Recommendation.- Mitigating Gender Bias in Machine Learning Data Sets.- Why Do We Need To Be Bots? What Prevents Society From Detecting Biases in Recommendation Systems.- Effect of Debiasing on Information Retrieval.- Matchmaking Under Fairness Constraints: a Speed Dating Case Study.- Recommendation Filtering a la Carte for Intelligent Tutoring Systems.- Bias Goggles - Exploring the bias of Web Domains through the Eyes of the Users.- Data Pipelines for Personalized Exploration of Rated Datasets.- Beyond Accuracy in Link Prediction.- A Novel Similarity Measure for Group Recommender Systems with Optimal Time Complexity.- What Kind of Content are you Prone to Tweet? Multi-topic Preference Model for Tweeters.- Venue Suggestion Using Social-Centric Scores.- The Impact of Foursquare Checkins on Users' Emotions on Twitter.- Improving News Personalization through Search Logs.- Analyzing the Interaction of Users with News Articles to Create Personalization Services.- Using String-Comparison measures to Improve and Evaluate Collaborative Filtering Recommender Systems.- Enriching Product Catalogs with User Opinions.
• (source: Nielsen Book Data)

This book constitutes refereed proceedings of the First International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2020, held in April, 2020. Due to the COVID-19 pandemic BIAS 2020 was held virtually. The 10 full papers and 7 short papers were carefully reviewed and seleced from 44 submissions. The papers cover topics that go from search and recommendation in online dating, education, and social media, over the impact ofgender bias in word embeddings, to tools that allow to explore bias and fairnesson the Web. .
(source: Nielsen Book Data)

• Cybersecurity & Privacy.- Big Data.- Blockchain & Internet of Things.- Security in Cloud and Fog Computing.- Artificial Intelligence/ Machine Learning Security.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the First International Conference on Big Data and Security, ICBDS 2019, held in Nanjing, China, in December 2019. The 37 revised full papers and 12 short papers were carefully reviewed and selected out of 251 submissions. The papers included in this book cover topics in cybersecurity & privacy, big data, blockchain & internet of things, security in cloud and fog computing, and artificial intelligence/ machine learning security.
(source: Nielsen Book Data)

• 1. Introduction to Emergency Management.-
• 2. Big Data.-
• 3. Learning Algorithms for Emergency Management.-
• 4. Knowledge Graphs and Natural-Language Processing.-
• 5. Social Media Mining for Disaster Management and Community Resilience.-
• 6. Big Data-Driven Citywide Human Mobility Modeling for Emergency Management.-
• 7. Smartphone based Emergency Communication.-
• 8. Emergency Information Visualisation. .
• (source: Nielsen Book Data)

This contributed volume discusses essential topics and the fundamentals for Big Data Emergency Management and primarily focusses on the application of Big Data for Emergency Management. It walks the reader through the state of the art, in different facets of the big disaster data field. This includes many elements that are important for these technologies to have real-world impact. This book brings together different computational techniques from: machine learning, communication network analysis, natural language processing, knowledge graphs, data mining, and information visualization, aiming at methods that are typically used for processing big emergency data. This book also provides authoritative insights and highlights valuable lessons by distinguished authors, who are leaders in this field. Emergencies are severe, large-scale, non-routine events that disrupt the normal functioning of a community or a society, causing widespread and overwhelming losses and impacts. Emergency Management is the process of planning and taking actions to minimize the social and physical impact of emergencies and reduces the community's vulnerability to the consequences of emergencies. Information exchange before, during and after the disaster periods can greatly reduce the losses caused by the emergency. This allows people to make better use of the available resources, such as relief materials and medical supplies. It also provides a channel through which reports on casualties and losses in each affected area, can be delivered expeditiously. Big Data-Driven Emergency Management refers to applying advanced data collection and analysis technologies to achieve more effective and responsive decision-making during emergencies. Researchers, engineers and computer scientists working in Big Data Emergency Management, who need to deal with large and complex sets of data will want to purchase this book. Advanced-level students interested in data-driven emergency/crisis/disaster management will also want to purchase this book as a study guide.
(source: Nielsen Book Data)

• Mitochondrial Haplogroup Assignment for High-Throughput Sequencing Data from Single Individual and Mixed DNA Samples.- Signet Ring Cell Detection with Classi cation Reinforcement Detection Network.- SPOC: Identification of Drug Targets in Biological Networks via Set Preference Output Control.- Identification of a novel compound heterozygous variant in NBAS causing bone fragility by the type of osteogenesis imperfecta.- Isoform-disease association prediction by data fusion.- EpIntMC: Detecting Epistatic Interactions using Multiple Clusterings.- Improving Metagenomic Classi cation using discriminative k-mers from sequencing data.- Dilated-DenseNet For Macromolecule Classifi cation In Cryo-electron Tomography.- Ess-NEXG: Predict Essential Proteins by Constructing a Weighted.- Protein Interaction Network based on Node Embedding and XGBoost.- mapAlign: an efficient approach for mapping and aligning long reads to reference genomes.- Functional Evolutionary Modeling Exposes Overlooked Protein-Coding Genes Involved in Cancer.- Testing the Agreement of Trees with Internal Labels.- SVLR: Genome Structure Variant Detection Using Long Read Sequencing Data.- De novo prediction of drug-target interaction via Laplacian regularized Schatten-p norm minimization.- Diagnosis of ASD from rs-fMRIs based on brain dynamic networks.- miRNA-Disease Associations Prediction Based on Negative Sample Selection and Multi-layer Perceptron.- Checking Phylogenetic Decisiveness in Theory and in Practice.- TNet: Phylogeny-Based Inference of Disease Transmission Networks Using Within-Host Strain Diversity.- Cancer breakpoint hotspots versus individual breakpoints prediction by machine learning models.- Integer Linear Programming Formulation for the Uni ed DuplicationLoss-Coalescence Model.- In silico-guided discovery of potential HIV-1 entry inhibitors mimicking bNAb
• N6: virtual screening, docking, molecular dynamics, and post-molecular modeling analysis.- Learning Structural Genetic Information via Graph Neural Embedding.- A New Network-based Tool to Analyse Competing Endogenous RNAs.- Deep Ensemble models for 16S Ribosomal Gene Classification.- Search for tandem repeats in the rst chromosome from the rice genome.- Deep Learning approach with rotate-shift invariant input to predict protein homodimer structure.- Development of a Neural Network-Based Approach for Prediction of Potential HIV-1 Entry Inhibitors Using Deep Learning and Molecular Modeling Methods.- In Silico Design and Evaluation of Novel Triazole-Based Compounds as Promising Drug Candidates Against Breast Cancer.- Identification of essential genes with NemoPro le and various machine learning models.- NemoLib: Network Motif Libraries for network motif detection and analysis.- Estimating enzyme participation in metabolic pathways for microbial communities from RNA-seq data.- Identication of Virus-Receptor Interactions based on Network Enhancement and Similarity.- Enhanced functional pathway annotations for differentially expressed gene clusters.- Automated Detection of Sleep Apnea from Abdominal Respiratory Signal using Hilbert-Huang Transform.- Na/K-ATPase glutathionylation: in silico modeling of reaction mechanisms.- HiChew: a tool for TAD clustering in embryogenesis.- Generation of Hi-C maps from DNA sequence data using Deep Learning.- S
• C1: A Tool for Interactive Web-Based Single Cell RNA-Seq Data Analysis.- Quantitative analysis of the dynamics of maternal gradients in the early Drosophila embryo.- Atom Tracking Using Cayley Graphs.- SPOC: Identification of Drug Targets in Biological Networks via Set Preference Output Control.- Identification of a novel compound heterozygous variant in NBAS causing bone fragility by the type of osteogenesis imperfecta. .
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 16th International Symposium on Bioinformatics Research and Applications, ISBRA 2020, held in Moscow, Russia, in December 2020. The 23 full papers and 18 short papers presented in this book were carefully reviewed and selected from 131 submissions. They were organized in topical sections named: genome analysis; systems biology; computational proteomics; machine and deep learning; and data analysis and methodology.
(source: Nielsen Book Data)

• Clock Synchronization for Mobile Molecular Communication in Nanonetworks.- A Cooperative Molecular Communication for targeted drug Delivery.- Performance of Diffusion-based MIMO Molecular Communications and Dual Threshold Algorithm.- Binary Concentration Shift Keying with Multiple Measurements of Molecule Concentration in Mobile Molecular Communication.- Real-Time Seven Segment Display Detection and Recognition Online System using CNN.- A novel method for extracting high-quality RR intervals from noisy single-lead ECG signals.- Leak-resistant design of DNA strand displacement systems.- Chessboard EEG Images Classification for BCI Systems Using Deep Neural Network.- Causal Network Analysis and Fault Root Point Detection Based on Symbolic Transfer Entropy.- Personalized EEG feature extraction method based on filter bank and elastic network.- Release rate optimization based on M/M/c/c queue in local nanomachine-based targeted drug delivery.- Research on Course Control of Unmanned Surface Vehicle.- Design and Experiment of a Double-layer Vertical Axis Wind Turbine.- Real-Time Obstacle Detection Based on Monocular Vision for Unmanned Surface Vehicles.- A Method of Data Integrity Check and Repair in Big Data Storage Platform.- A Study of Image Recognition for Standard Convolution and Depthwise Separable Convolution.- A Novel Genetic Algorithm-based DES Key Generation Scheme.- Developing an Intelligent Agricultural System based on Long Short-Term Memory.- Detection of atherosclerotic lesions based on molecular Communication.- Design for Detecting Red Blood Cell Deformation at Different Flow Velocities in Blood Vessel.- Intelligent Power Controller of Wireless Body Area Networks based on Deep Reinforcement Learning.- Target Tracking Based on DDPG in Wireless Sensor Network.- A fuzzy tree system based on cuckoo search algorithm for target tracking in Wireless Sensor Network.- Sensor scheme for target tracking in Mobile Sensor Networks.- Molecular MIMO Communications Platform with BTSK for In-Vessel Network Systems.- Preliminary Studies on Flow Assisted Propagation of Fluorescent Microbeads in Microfluidic Channels for Molecular Communication Systems.- Comparative Evaluation of a New Sensor for Superparamagnetic Iron-Oxide Nanoparticles in a Molecular Communication Setting.- Localization of a Passive Molecular Transmitter with a Sensor Network.
• .
• (source: Nielsen Book Data)

This book constitutes the refereed conference proceedings of the 12th International Conference on Bio-inspired Information and Communications Technologies, held in Shanghai, China, in July 2020. Due to the safety concerns and travel restrictions caused by COVID-19, BICT 2020 took place online in a live stream. BICT 2020 aims to provide a world-leading and multidisciplinary venue for researchers and practitioners in diverse disciplines that seek the understanding of key principles, processes and mechanisms in biological systems and leverage those understandings to develop novel information and communications technologies (ICT). The 20 full and 8 short papers were carefully revied and selected from 56 submissions. In addition to the main track targeting broad and mainstream research topics, BICT 2020 includes four special tracks with focused research topics on internet of everything, intelligent internet of things and network applications, intelligent sensor network, and data-driven intelligent modeling, application and optimization.
(source: Nielsen Book Data)

• Chapter 1: Classification of Arrhythmia Using Artificial Neural Network with Grey Wolf Optimization
• Chapter 2: Multi-objective Biogeography-Based Optimization for Influence Maximization-Cost Minimization in Social Networks
• Chapter 3: Classification of Credit Dataset Using Improved Particle Swarm Optimization Tuned Radial Basis Function Neural Networks
• Chapter 4: Multi-verse Optimization of Multilayer Perceptrons (MV-MLPs) for Efficient Modeling and Forecasting of Crude Oil Prices Data
• Chapter 5: Application of machine learning to predict diseases based on symptoms in rural India
• Chapter 6: Classıfıcatıon of Real Tıme Noısy Fıngerprınt Images Usıng FLANN
• Chapter 7: Software Reliability Prediction with Ensemble Method and Virtual Data Point Incorporation
• Chapter 8: Hyperspectral Image Classification using Stochastic Gradient Descent based Support Vector Machine
• Chapter 9: A Survey on Ant Colony Optimization for Solving Some of the Selected NP-Hard Problem
• Chapter 10: Machine Learning Models for Stock Prediction using Real-Time Streaming Data
• Chapter 11: Epidemiology of Breast Cancer (BC) and its Early Identification via Evolving Machine Learning Classification Tools (MLCT)-A Study
• Chapter 12: Ensemble Classification Approach for Cancer Prognosis and Prediction
• Chapter 13: Extractive Odia Text Summarization System: An OCR based Approach
• Chapter 14: Predicting sensitivity of local news articles from Odia dailies
• Chapter 15: A systematic frame work using machine learning approaches in supply chain forecasting
• Chapter 16: An Intelligent system on computer-aided diagnosis for Parkinsons disease with MRI using Machine Learning
• Chapter 17: Operations on Picture Fuzzy Numbers and their Application in Multi-Criteria Group Decision Making Problems
• Chapter 18: Some Generalized Results on Multi-Criteria Decision Making Model using Fuzzy TOPSIS Technique
• Chapter 19: A Survey on FP-Tree Based Incremental Frequent Pa ttern Mining
• Chapter 20: Improving Co-expressed Gene Pattern Finding Using Gene Ontology
• Chapter 21: Survey of Methods Used for Differential Expression Analysis on RNA Seq Data
• Chapter 22: Adaptive Antenna Tilt for Cellular Coverage Optimization in Suburban Scenario
• Chapter 23: A survey of the different itemset representation for candidate.

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems. This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing.

• Registration Initialization and Acceleration.- Nonlinear Alignment of Whole Tractograms with the Linear Assignment Problem.- Learning-based Affine Registration of Histological Images.- Enabling Manual Intervention for Otherwise Automated Registration of Large Image Series.- Towards Segmentation and Spatial Alignment of the Human Embryonic Brain using Deep Learning for Atlas-based Registration.- Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy.- Interventional Registration.- Multilevel 2D-3D Intensity-based Image Registration.- Towards Automated Spine Mobility Quantification: a Locally Rigid CT to X-ray Registration Framework.- Landmark based Registration.- Reinforced Redetection of Landmark in Pre- and Post-Operative Brain Scan using Anatomical Guidance for Image Alignment.- Deep Volumetric Feature Encoding for Biomedical Images.- Multi-Channel Registration.- Multi-Channel Image Registration of Cardiac MR Using Supervised Feature Learning with Convolutional Encoder-Decoder Network.- Multi-Channel Registration for Diffusion MRI: Longitudinal Analysis for the Neonatal Brain.- An Image Registration-based Method for EPI Distortion Correction based on Opposite Phase Encoding (COPE).- Diffusion Tensor driven Image registration: a Deep Learning Approach.- Multimodal MRI Template Creation in the Ring-Tailed Lemur and Rhesus Macaque.- Sliding Motion.- An Unsupervised Learning Approach to Discontinuity-preserving Image Registration.- An Image Registration Framework for Discontinuous Mappings along Cracks.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 9th International Workshop on Biomedical Image Registration, WBIR 2020, which was supposed to be held in Portoroz, Slovenia, in June 2020. The conference was postponed until December 2020 due to the COVID-19 pandemic. The 16 full and poster papers included in this volume were carefully reviewed and selected from 22 submitted papers. The papers are organized in the following topical sections: Registration initialization and acceleration, interventional registration, landmark based registration, multi-channel registration, and sliding motion.
(source: Nielsen Book Data)