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• Introduction
• The challenges of automated item picking: the last mile of logistics for e-commerce
• Robotic Sensing for Item Picking
• Gripper Design and Grasping Strategies
• Machine Learning for Item Identification and Pose Estimation
• Machine Learning for Motion Planning
• Efficient Task Planning Strategies.

This book is a compilation of advanced research and applications on robotic item picking and warehouse automation for e-commerce applications. The works in this book are based on results that came out of the Amazon Robotics Challenge from 2015-2017, which focused on fully automated item picking in warehouse setting, a topic that has been assumed too complicated to solve or has been reduced to a more tractable form of bin picking or single-item table top picking. The books contributions reveal some of the top solutions presented from the 50 participant teams. Each solution works to address the time-constraint, accuracy, complexity, and other difficulties that come with warehouse item picking. The book covers topics such as grasping and gripper design, vision and other forms of sensing, actuation and robot design, motion planning, optimization, machine learning and artificial intelligence, software engineering, and system integration, among others. Through this book, the authors describe how robot systems are built from the ground up to do a specific task, in this case, item picking in a warehouse setting. The compiled works come from the best robotics research institutions and companies globally. Presents an inside look at the various solutions for automated warehouse item picking based on the Amazon Robotics Challenge (ARC) Contains details of the challenges and solutions involved in automating item picking Provides details and insights on the solutions of the winning teams Includes chapters written by scientists and engineers at the forefront of robotics research.

• Auctions and Mechanism Design.- Congestion Games and Flows over Time.- Markets and Matchings.- Scheduling and Games on Graphs.- Social Choice and Cooperative Games.
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This book constitutes the refereed proceedings of the 13th International Symposium on Algorithmic Game Theory, SAGT 2020, held in Augsburg, Germany, in September 2020.* The 21 full papers presented together with 3 abstract papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: auctions and mechanism design, congestion games and flows over time, markets and matchings, scheduling and games on graphs, and social choice and cooperative games. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Introduction.- Related Work: Machine Learning and Electronic Design Automation.- Unlabeled Data and Artificial Neural Networks.- Placement Loss: Placement Constraints Description and Satisfiability Evaluation.- Experimental Results in Industrial Case Studies.- Conclusions. .
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In this book, innovative research using artificial neural networks (ANNs) is conducted to automate the placement task in analog integrated circuit layout design, by creating a generalized model that can generate valid layouts at push-button speed. Further, it exploits ANNs' generalization and push-button speed prediction (once fully trained) capabilities, and details the optimal description of the input/output data relation. The description developed here is chiefly reflected in two of the system's characteristics: the shape of the input data and the minimized loss function. In order to address the latter, abstract and segmented descriptions of both the input data and the objective behavior are developed, which allow the model to identify, in newer scenarios, sub-blocks which can be found in the input data. This approach yields device-level descriptions of the input topology that, for each device, focus on describing its relation to every other device in the topology. By means of these descriptions, an unfamiliar overall topology can be broken down into devices that are subject to the same constraints as a device in one of the training topologies. In the experimental results chapter, the trained ANNs are used to produce a variety of valid placement solutions even beyond the scope of the training/validation sets, demonstrating the model's effectiveness in terms of identifying common components between newer topologies and reutilizing the acquired knowledge. Lastly, the methodology used can readily adapt to the given problem's context (high label production cost), resulting in an efficient, inexpensive and fast model. .
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• Design and Development.- Second Screen and Crossmedia.- Interaction Techniques and Technologies.- Accessibility.- User Experience.
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This book constitutes the refereed proceedings of the 8th Iberoamerican Conference on Applications and Usability of Interactive Television, jAUTI 2019, in Rio de Janeiro, Brazil, in October 2019. The 10 full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on Design and Development; Second Screen and Crossmedia; Interaction Techniques and Technologies; Accessibility; User Experience.
(source: Nielsen Book Data)

• Segmentation Of Thermal Images By Means Of Metaheuristic Algorithms, For Failure Detection And Preventive Maintenance Of Electronic Systems.- A Survey on Image Processing for Hyperspectral and Remote Sensing Images.- Hybrid Grey-Wolf Optimizer Based Fractional Order Optimal Filtering for Texture Aware Quality Enhancement for Remotely Sensed Images.- Robust K- Means Technique For Band Reduction On Hyperspectral Image Segmentation.- Ethnic Characterization In Amalgamated People For Airport Security Using A Repository Of Images And Pigeon-Inspired Optimization (Pio) Algorithm For The Improvement Of Their Results}.- Multi-Level Image Thresholding Segmentation Using Non-Local Means 2d Histogram And Metaheuristics Algorithms.- Comparison Of Metaheuristic Methods For Template Matching.- Novel Feature Extraction Strategies Supporting 2d Shape Description And Retrieval.- Clustering Data Using Techniques Of Image Processing Erode And Dilate To Avoid The Use Of Euclidian Distance.- Estimation Of The Homography Matrix To Image Stitching.- Active Contour Model in Deep Learning Era: A Revise and Review.- Comparison of Evolutionary Techniques for Car Accident Prediction.- Salp Swarm Algorithm: A Comprehensive Review.- Segmentation Of Magnetic Resonance Brain Images Through The Self-Adaptive Differential Evolution Algorithm And The Minimum Cross-Entropy Criterion.- Automatic Detection Of Malignant Masses In Digital Mammograms Based On A Mcet-Hho Approach.- Cancer Cell Prediction using Machine Learning and Evolutionary Algorithms.- Meta Heuristic Approach of RMDL Classification of Parkinson's disease.- Fuzzy- Crow Search Optimization for Medical Image Segmentation.- Intelligent System For The Visual Support Of Caloric Intake Of Food In Inhabitants Of A Smart City Using A Deep Learning Model.- Image Thresholding with Metaheuristic Algorithms for Cerebral Injuries.- Generative Adversarial Network And Retinal Image Segmentation.
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This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.
(source: Nielsen Book Data)

• Theory, Methods and Tools to support Computer Science
• Computer Security and Cryptography
• Computer Network and Communication
• Real World Application in Information Science and Technology.

This book constitutes the refereed proceedings of the First International Conference on Applied Computing to Support Industry: Innovation and Technology, ACRIT 2019, held in Ramadi, Iraq, in September 2019. The 38 revised full papers and 1 short paper were carefully reviewed and selected from 159 submissions. The papers of this volume are organized in topical sections on theory, methods and tools to support computer science; computer security and cryptography; computer network and communication; real world application in information science and technology.

• Introduction.- Modelling Vehicle Systems.- Offset Models of Vehicles.- Design of Controllers.- Implementation of Controllers.- Conclusion.
• (source: Nielsen Book Data)

This book provides methodologies for designing and implementing guidance algorithms for autonomous vehicles. These algorithms make important decision regarding how to steer and drive a ground vehicle in order to safely stay on an intended path, thereby making the vehicle driverless. The design tools provided in this book enable the reader to develop highly practical and real-world implementable guidance algorithms that will deliver high-accuracy driving for field vehicles. (They are equally applicable for on-road vehicles.) The book covers a variety of vehicle types, including wheeled vehicles, tracked vehicles, wheeled and tracked vehicles towing trailers, and four-wheel-steer and four-wheel-drive vehicles. It also covers active trailers that are driven and steered. Vehicles used in agriculture, mining and road construction are subjected to unpredictable and significant disturbances. The robust control methodologies presented can successfully compensate for these disturbances, as confirmed by the experimental results presented. Though the majority of the methodologies presented are based on sliding-mode controllers, other robust control methodologies are also discussed. To help the reader decide which controller is best suited for his/her choice of vehicle, experimental results are presented in a comparative format. .
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• Fruit Fly Optimization Based Reliable Routing Algorithm for Wireless Sensor Networks.- User Authentication of IoT Devices for Decentralized Architecture Using Blockchain.- Detection of Packet Dropping Nodes in Wireless Mesh Networks.- An Enhanced Bat Algorithm for Parallel Localization Based on a Mobile Beacon Sensor in Wireless Sensor Networks.- Desing of a Virtual Channel Router Architecture for Low Power on Mesh-of-Grid Topology for Network on Chip.- Agent-based Traffic Obstacles Information System.- Hybridization of Constriction Coefficient Based Particle Swarm Optimization and Chaotic Gravitational Search Algorithm for Solving Engineering Design Problems.- Parallel Association Rules Pruning Algorithm on Hadoop MapReduce.- A Statistical Analysis on KDD Cup'99 Dataset for Network Intrusion Detection System.- Efficient Certificateless Privacy Preserving Public Auditing for Cloud Based IIoT.- Classification of Virtual Machine Consolidation Techniques: A Survey.- Enhanced Honey Bee Load Balancing in Large Heterogeneous Cloud Environments.- Real Time Communication Alert System for Missing Vessels in Deep Sea.- A Study of CNN Architectures over Two Hands Indian Sign Language Dataset.- Periocular Recognition Under Unconstrained Conditions Using CNN Based Super-Resolution.- Performance Evaluation of RNNs for Short-Term Investment Decision in Stock Market.
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This book constitutes best selected research papers presented at the International Applied Soft Computing and Communication Networks (ACN 2019) held in Trivandrum, Kerala, India during December 18 - 21, 2019. The papers are organized in topical sections on real time and multimedia communications, security and privacy, network management and software-defined networks, Internet of Things (IoT) and cyber-physical systems, intelligent distributed systems, mobile computing and vehicle communications, surveillance networks and visual intelligence, and emerging topics. The book is a reference for researchers and scientists engaged in various fields of intelligent systems.
(source: Nielsen Book Data)

Cut through the noise and get real results with this workshop for beginners. Use a project-based approach to exploring machine learning with TensorFlow and Keras. Key Features Understand the nuances of setting up a deep learning programming environment Gain insights into the common components of a neural network and its essential operations Get to grips with deploying a machine learning model as an interactive web application with Flask Book Description Machine learning gives computers the ability to learn like humans. It is becoming increasingly transformational to businesses in many forms, and a key skill to learn to prepare for the future digital economy. As a beginner, you'll unlock a world of opportunities by learning the techniques you need to contribute to the domains of machine learning, deep learning, and modern data analysis using the latest cutting-edge tools. The Applied TensorFlow and Keras Workshop begins by showing you how neural networks work. After you've understood the basics, you will train a few networks by altering their hyperparameters. To build on your skills, you'll learn how to select the most appropriate model to solve the problem in hand. While tackling advanced concepts, you'll discover how to assemble a deep learning system by bringing together all the essential elements necessary for building a basic deep learning system - data, model, and prediction. Finally, you'll explore ways to evaluate the performance of your model, and improve it using techniques such as model evaluation and hyperparameter optimization. By the end of this book, you'll have learned how to build a Bitcoin app that predicts future prices, and be able to build your own models for other projects. What you will learn Familiarize yourself with the components of a neural network Understand the different types of problems that can be solved using neural networks Explore different ways to select the right architecture for your model Make predictions with a trained model using TensorBoard Discover the components of Keras and ways to leverage its features in your model Explore how you can deal with new data by learning ways to retrain your model Who this book is for If you are a data scientist or a machine learning and deep learning enthusiast, who is looking to design, train, and deploy TensorFlow and Keras models into real-world applications, then this workshop is for you. Knowledge of computer science and machine learning concepts and experience in ...

• Part I, From Business Problems to Data Science.- Data Science Based on Artificial Intelligence.- Business Problems Dependent on Data.- Artificial Intelligence-Based Data Science Solutions.- Integrate and Conquer.- The Lost-in-Translation Trap.- Part II, The AI-Based Data Science Toolbox.- The AI-Based Data Science Workflow.- Problem Knowledge Acquisition.- Data Preparation.- Data Analysis.- Model Development.- The Model Deployment Life Cycle.- Part III, AI-Based Data Science in Action.- Infrastructure.- People.- Applications of AI-Based Data Science in Manufacturing.- Applications of AI-Based Data Science in Business.- How to Operate AI-Based Data Science in a Business.- How to Become an Effective Data Scientist.- Glossary.
• (source: Nielsen Book Data)

This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: machine learning, deep learning, decision trees and random forests, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem knowledge acquisition, data preparation, data analysis, model development, and model deployment lifecycle. Finally, in Part III the author illustrates the power of AI-based data science with successful applications in manufacturing and business. He also shows how to introduce this technology in a business setting and guides the reader on how to build the appropriate infrastructure and develop the required skillsets. The book is ideal for data scientists who will implement the proposed methodology and techniques in their projects. It is also intended to help business leaders and entrepreneurs who want to create competitive advantage by using AI-based data science, as well as academics and students looking for an industrial view of this discipline.
(source: Nielsen Book Data)

• From Feature Selection to Continuous Optimization.- Evolving a Weighted Combination of Text Similarities for Authorship Attribution.- Image Signal Processor Parameter Tuning with Surrogate-assisted Particle Swarm Optimization.- Combinatorial Surrogate-assisted Optimization for Bus Stops Spacing Problem.- Optimization of a Checkers Player Using Neural and Metaheuristic Approaches.- A Novel Outlook on Feature Selection as a Multi-Objective Problem.- Fast Evolutionary Algorithm for Solving Large-scale Multi-objective Problems.- Looking for Energy Efficient Genetic Algorithms.- Evolving Fitness Landscapes with Complementary Fitness Functions.- Bayesian Immigrant Diploid Genetic Algorithm for Dynamic Environments.- Ant Colony Optimization Algorithm for a Transportation Problem in Home Health Care with the Consideration of Carbon Emissions.- Selective Vehicle Routing Problem: A Hybrid Genetic Algorithm Approach.- Fixed Jobs Multi-agent Scheduling Problem with Renewable Resources.- A Study of Recombination Operators for the Cyclic Bandwidth Problem.- Automatic Calibration of a Farm Irrigation Model: a Multi-modal Optimization Approach.- A Hybrid Evolutionary Algorithm for Offl ine UAV Path Planning.
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This book constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Artificial Evolution, EA 2019, held in Mulhouse, France, in October 2019. The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations, application of evolutionary paradigms to the real world (industry, biosciences...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms...), memetic algorithms, multi-objective optimization, constraint handling, parallel algorithms, dynamic optimization, machine learning and hybridization with other soft computing techniques.
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• AGI and the Knight-Darwin Law: why idealized AGI reproduction requires collaboration.- Error-Correction for AI Safety.- Artificial Creativity Augmentation.- The hierarchical memory based on compartmental spiking neuron model.- The Dynamics of Growing Symbols: A Ludics Approach to Language Design by Autonomous Agents.- Approach for development of engineering tools based on knowledge graphs and context separation.- Towards Dynamic Process Composition in the DSO Cognitive Architecture.- SAGE: Task-Environment Platform for Evaluating a Broad Range of AI Learners.- Post-Turing Methodology: Breaking the Wall on the Way to Artificial General Intelligence.- Self-explaining AI as an alternative to interpretable AI.- AGI needs the Humanities.- A report of a recent book: "AI and Human Thought and Emotion".- Cognitive Machinery and Behaviours.- Combinatorial Decision Dags: A Natural Computational Model for General Intelligence.- What Kind of Programming Language Best Suits Integrative AGI?.- Guiding Symbolic Natural Language Grammar Induction via Transformer-Based Sequence Probabilities.- Embedding Vector Differences Can Be Aligned With Uncertain Intensional Logic Differences.- Delta Schema Network in Model-based Reinforcement Learning.- Information Digital Twin{Enabling Agents to Anticipate Changes in their Tasks.- 'OpenNARS for Applications': Architecture and Control.- Towards AGI Agent Safety by Iteratively Improving the Utility Function.- Learning to Model Another Agent's Beliefs: A Preliminary Approach.- An Attentional Control Mechanism for Reasoning and Learning.- Hyperdimensional Representations in Semiotic Approach to AGI.- The Conditions of Artificial General Intelligence: Logic, Autonomy, Resilience, Integrity, Morality, Emotion, Embodiment, and Embeddedness.- Position paper: The use of engineering approach in creation of artificial general intelligence.- How do you test the strength of AI?.- Omega: An Architecture for AI Unification.- Analyzing Elementary School Olympiad Math Tasks as a Benchmark for AGI.- The meaning of things as a concept in a strong AI architecture.- Toward a General Believable Model of Human-Analogous Intelligent Socially Emotional Behavior.- Autonomous Cumulative Transfer Learning.- New Brain Simulator II Open-Source Software.- Experience-specific AGI Paradigms.- Psychological portrait of a virtual agent in the Teleport game paradigm.- Logical probabilistic biologically inspired cognitive architecture.- An Architecture for Real-time Reasoning and Learning.- A Model for Artificial General Intelligence.
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This book constitutes the refereed proceedings of the 13th International Conference on Artificial General Intelligence, AGI 2020, held in St. Petersburg, Russia, in September 2020.The 30 full papers and 8 short papers presented in this book were carefully reviewed and selected from 60 submissions. The papers cover topics such as AGI architectures, artificial creativity and AI safety, transfer learning, AI unification and benchmarks for AGI.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Automated Reasoning and Data Mining
• Axiomatization of Classes of Domain Cases Based on FCA
• 1 Introduction
• 2 Preliminaries
• 2.1 Domain Cases
• 2.2 Formal Contexts of Axiomatizable Classes
• 2.3 Relatively Axiomatizable Classes
• 3 Axiomatization of Classes of Domain Cases
• 3.1 Sentences Permissible for Models
• 3.2 Theories of Classes of Models Having Different Signatures
• 3.3 Axiomatizable Classes and Decidability of Theories
• 4 Conclusion
• References

• The Combined Method of Automated Knowledge Acquisition from Various Sources: The Features of Development and Experimental Research of the Temporal Version
• 1 Introduction
• 2 The Evolution of the Combined Method of Knowledge Acquisition and Means of Its Implementation
• 3 Features of the Organization of Software Experiments Based on the Temporal Version of CMKA
• 3.1 General Organization of the Language Experiment
• 3.2 General Organization of Experiments with Temporal Database
• 3.3 Merging of Knowledge Field's Elements
• 4 Conclusion
• References

• Multi-agent Systems, Intelligent Robots and Behavior Planning
• Multi-agent Path Finding with Kinematic Constraints via Conflict Based Search
• 1 Introduction
• 2 Problem Statement
• 3 Suggested Approach
• 3.1 Conflict Based Search Algorithm
• 3.2 Continuous Conflict Based Search Algorithm
• 3.3 Safe Interval Path Planning with Rotations
• 3.4 Implementation Details
• 4 Experimental Evaluation
• 4.1 CCBS vs CCBS-kc
• 4.2 AA-SIPP(m) vs CCBS-kc
• 4.3 Comparison of Heuristic Functions
• 5 Conclusion
• References

• Map-Merging Algorithms for Visual SLAM: Feasibility Study and Empirical Evaluation
• 1 Introduction
• 2 Related Work
• 2.1 vSLAM Algorithms
• 2.2 Map-Merging Algorithms
• 3 Problem Statement
• 4 Methods and Metrics Overview
• 5 Experimental Evaluation and Results
• 5.1 Setup
• 5.2 Results
• 6 Conclusion
• References
• Can a Robot Be a Moral Agent?
• 1 Introduction
• 2 A Moral Agent
• 3 Phenomena and Mechanisms
• 3.1 Emotions and Needs
• 3.2 Model of the World, "I"
• 3.3 Imitative Behavior
• 3.4 Empathy
• 3.5 Characteristic Properties of Moral Agents
• 4 Conclusion

This book constitutes the proceedings of the 18th Russian Conference on Artificial Intelligence, RCAI 2020, held in Moscow, Russia, in October 2020. The 27 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 140 submissions. The conference deals with a wide range of topics, including data mining and knowledge discovery, text mining, reasoning, decisionmaking, natural language processing, vision, intelligent robotics, multi-agent systems, machine learning, AI in applied systems, and ontology engineering.
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• Decision Support Model for Assessing Projects by a Group of Investors with Regards of Multi-factors
• 7-Dimensional Optimization Task: PBO-Nature-Inspired Optimizer Versus 10-Years-Old Differential Evolution Based Optimizer 3rd Generation EPSDE
• A Hand Contour Classification Using Ensemble of Natural Features: A Large Comparative Study
• Energy Consumption Reduction in Real Time Multiprocessor Embedded Systems with Uncertain Data
• Developing an Efficient Method for Automatic Threshold Detection Based on Hybrid Feature Selection Approach
• Comparison of Hybrid ACO-k-Means Algorithm and Graph Cut for MRI Images Segmentation
• Parallel Deep Neural Network for Motor Imagery EEG Recognition with Spatiotemporal Features.

This book gathers the refereed proceedings of the Artificial Intelligence and Bioinspired Computational Methods Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Artificial intelligence and bioinspired computational methods now represent crucial areas of computer science research. The topics presented here reflect the current discussion on cutting-edge hybrid and bioinspired algorithms and their applications. .
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• Research Track.- Infant Sound Classification on Multi-stage CNNs with Hybrid Features and Prior Knowledge.- Building Vector Representations for Candidates and Projects in a CV Recommender System.- Candidate Classification and Skill Recommendation in a CV Recommender System.- A Novel Method to Estimate Students' Knowledge Assessment.- Answer Selection Based on Mixed Embedding and Composite Features.- A Neural Framework for Chinese Medical Named Entity Recognition.- An Annotated Chinese Corpus for Rumor Veracity Detection.- Attention-based Asymmetric Fusion Network for Saliency Prediction in 3D Images.- Review Spam Detection Based on Multidimensional.- Application Track.- Rehabilitation XAI to Predict Outcome with Optimal Therapies.- A Mobile Application using Deep Learning to Automatically Classify Adult-only Images.- Short Paper Track.- OSAF_e: One-Stage Anchor Free Object Detection Method Considering Effective Area.- Attention-based Interaction Trajectory Prediction.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 9th International Conference on Artificial Intelligence and Mobile Services, AIMS 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 11 full and 2 short papers presented were carefully reviewed and selected from 42 submissions. They cover topics in AI Modeling, AI Analysis, AI and Mobile Applications, AI Architecture, AI Management, AI Engineering, Mobile backend as a service (MBaaS), User experience of AI and mobile services.
(source: Nielsen Book Data)

• Fast Texture Image Retrieval Using Learning Copula Model of Multiple DTCWT.- Joint Generic Learning and Multi-SourceDomain Adaptation on Unsupervised FaceRecognition.- Reset Attack: An Attack Against Homomorphic Encryption-based Privacy-Preserving Deep Learning System.- Intelligent Contract for Power Market Transaction Based on the BlockChain.- Survey on Zero-trust Network Security.- A Novel Consensus Algorithm for Alliance Chain.- A Novel Thematic Network Data Collector Based on Simulated Annealing Hybrid Genetic Algorithm.- The Study of Fog Computing Security Situation Prediction in Industrial Internet.- A novel keypoints-based image registration method with fully convolutional neural network.- Image super-resolution reconstruction with dense residual attention module.- GF-2 image blue roof building extraction method based on object-oriented classification technology.- Optimization and Parallelization of the cosmological N-body Simulation on Many-core Processor.- Parallel optimization of stencil computation base on Sunway TaihuLight.- Chinese News Data Extraction System Based On Readability Algorithm.- Parallel Acceleration Improvement of Physical Quantity Gradient Algorithm Based on CFD.- Using Process Visualization and Early Warning Based on Learning Analytics to Enhance Teaching and Learning.- Research Progress of Knowledge Graph Embedding.- A Robust Framework for High-quality Voice Conversion with Conditional Generative Adversarial Network.- Effective Android Malware Detection based on Deep Learning.- Research on Tampering Detection of Material Gene Data Based on Fragile Watermarking.- Quantitative Evaluation Of Promotion Of Traditional National Sports Events Based On Probity Multiple Regression Analysis.- Research on Leisure Sports Activities Based on Decision Tree Algorithm.- Semantic Integrity Analysis Based on Transformer.- An improvement of Coherent Semantic Attention for Image Inpainting.- Formal Verification of the Correctness of Operating System on Assembly Layer in Isabelle/HoL.- Nonlinear Correction Based on Depth Neural Network.- Spatial-temporal co-attention network for action recognition.- Improved SSD for object detection.- Sentiment Analysis on Weibo Platform for Stock Prediction.- Refinement Measurement and Evaluation of Streets in Shanghai Old City.- A Traceability Architecture for the Fresh Food Supply Chain based on Blockchain Technology in China.- Research Progress in Blind Forensics of Digital Image Smooth Filtering.- Research on video violence detection technology of UAV on cloud platform.- A Generative Steganography Method Based on WGAN-GP.- A deep learning network for coarse-to-fine deformable medical image registration.- Research on Cross-lingual Machine Reading Comprehension Technology Based on Non-parallel Corpus.- Research on the data reference model of NMIS.- A Real-time Recommender System Design Based on Spark Streaming.- A Novel Clone Detection Scheme Based on Generative Adversarial Networks.- Design of Vehicle Remote Monitoring System Based on LoRa Technology and QT Platform.- Unifying Domain Adaptation into Simultaneous Discriminant Analysis: a Method for Low-resolution Face Recognition with Single Sample per Person.- An exploratory study of blending Smart classroom in database course.- Optimization and simulation of pre-warehouse multi-objective stock levels based on the Weibull distribution function.- Research and Analysis of Fine Management of Engineering Cost Based on BIM.- Survey of Software-Defined Network Security Issues.- A Fall Detection Algorithm Based on a Support Vector Machine.- A Multi-AGV Optimal Scheduling Algorithm Based on Particle Swarm Optimization.- An efficient quantum private comparison protocol based on conjugate coding.- Deliberated Vulnerable Environment Generating based on Container and Structured Vulnerability Intelligence.- Deep neural network watermarking based on texture analysis.- A Robust Reversible Image Watermarking Scheme based on Singular Value Decomposition and Quantization Technique.- Boolean Function Decomposition Based on Grover Algorithm and Its Simulation Using Quantum Language Quipper.- Research on Emotional Recognition of EEG Signals in Experimental Paradigm.- Research on Rasterized Population Evaluation Method Based on Multi-class Machine Learning Method.- Salary Satisfaction of University Teachers with Different Professional Positions.- Defining Cost Function for Robust Embedding.- Efficient Identity-Based Signature authentication scheme for smart home system.- A Resource Allocation Mechanism for Edge-blockchain.- Remote sensing image zero-watermarking algorithm based on accurate polar harmonic Fourier moment.- Multi-layer quantum secret sharing based on GHZ states.- Robot scheduling system based on semantic recognition.- Pedestrian Counting without Tracking for the Security Application of IoT Framework.
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The 3-volume set CCIS 1252 until CCIS 1254 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called "International Conference on Cloud Computing and Security" with the acronym ICCCS. The total of 178 full papers and 8 short papers presented in this 3-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows: Part I: artificial intelligence; Part II: artificial intelligence; Internet of things; information security; Part III: information security; big data and cloud computing; information processing.
(source: Nielsen Book Data)

• Artificial intelligence.- Internet of things.
• (source: Nielsen Book Data)

This two-volume set LNCS 12239-12240 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called "International Conference on Cloud Computing and Security" with the acronym ICCCS. The total of 142 full papers presented in this two-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows: Part I: Artificial intelligence and internet of things. Part II: Internet of things, information security, big data and cloud computing, and information processing.
(source: Nielsen Book Data)

• Artificial intelligence.- Internet of things.- information security.
• (source: Nielsen Book Data)

The 3-volume set CCIS 1252 until CCIS 1254 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called "International Conference on Cloud Computing and Security" with the acronym ICCCS. The total of 178 full papers and 8 short papers presented in this 3-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows: Part I: artificial intelligence; Part II: artificial intelligence; Internet of things; information security; Part III: information security; big data and cloud computing; information processing.
(source: Nielsen Book Data)

• Globalization - Understanding the correlations between attitudes towards globalization, time, resources and financial resources.- Integrated System for students' Evaluation Using KM Approach.- ICT Platform Design for SME Collaboration.- Platform for Knowledge Society and Innovation Ecosystems.- Measuring Successful Digital Services by identifying Active Users.- Effective management of information processes with CMS in Smart City. The concept of Crowdsourcing.- A Naming System for "The Internet of Things" adapted to industry - A case study in Electrical Engineering.- Augmented Learning and Data Filtering: Knowledge Management and Discovery.- AI Classification in Collaboration for Innovation of Electric Motors of Household Appliances.- A Note on Knowledge Management Education: Towards Implementing Active Learning Methods.- Intellect Modelling KIT.
• (source: Nielsen Book Data)

This book features a selection of extended papers presented at the 6th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2018, held in Stockholm, Sweden, in July 2018, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2018.The 11 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management such as machine learning, knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.
(source: Nielsen Book Data)

• AI4KM
• 2019: 7th International Workshop on Artificial Intelligence for Knowledge Management and Innovation.- FinNLP
• 2019: First International Workshop on Financial Technology and Natural Language Processing.- OR
• 2019: 32nd International Workshop on Qualitative Reasoning.- SURL
• 2019: Second International Workshop on Scaling-Up Reinforcement Learning.- First International Workshop on Bringing Semantic Knowledge into Vision and Text Understanding.- EASyHAT
• 2019: International Workshop on Evaluation of Adaptive Systems for Human-Autonomy Teaming.- ACAN
• 2019: 12th International Workshop on Agent-based Complex Automated Negotiations.- First International Workshop on Deep Learning for Human Activity Recognition.- HAI
• 2019: Second International Workshop on Humanizing AI.- Third International Workshop on Language Sense on Computer.- AISafety
• 2019: International Workshop on Artificial Intelligence Safety.- DeLBP
• 2019: 4th International Workshop on Declarative Learning Based Programming.
• (source: Nielsen Book Data)

This book presents selected papers of 12 Workshops held in conjunction with the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019, in Macao, China, in August 2019. The workshops included in this volume are: AI4KM 2019: 7th International Workshop on Artificial Intelligence for Knowledge Management and Innovation. FinNLP 2019: First International Workshop on Financial Technology and Natural Language Processing. OR 2019: 32nd International Workshop on Qualitative Reasoning. SURL 2019: Second International Workshop on Scaling-Up Reinforcement Learning. First International Workshop on Bringing Semantic Knowledge into Vision and Text Understanding. EASyHAT 2019: First International Workshop on Evaluation of Adaptive Systems for Human-Autonomy Teaming. ACAN 2019: 12th International Workshop on Agent-based Complex Automated Negotiations. First International Workshop on Deep Learning for Human Activity Recognition. HAI 2019: Second International Workshop on Humanizing AI. International Workshop on Language Sense on Computer. AISafety 2019: International Workshop on Artificial Intelligence Safety. DeLBP 2019: 4th International Workshop on Declarative Learning Based Programming.
(source: Nielsen Book Data)