%{search_type} search results

"Academic, industry, and government experts provide a global survey of the financial services sector's transformation by AI, data science, and blockchain"-- Provided by publisher.

• Table of Contents Introduction to Software Architecture API Design Data Modeling The Data Layer The Twelve-Factor App Methodology Web Server Structures Event-Driven Structures Advanced Event-Driven Structures Microservices vs Monolith Testing and TDD Package Management Logging Metrics Profiling Debugging Ongoing Architecture.
• (source: Nielsen Book Data)

Make the best of your test suites by using cutting-edge software architecture patterns in Python Key Features Learn how to create scalable and maintainable applications Build a web system for micro messaging using concepts in the book Use profiling to find bottlenecks and improve the speed of the system Book DescriptionDeveloping large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity-and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems. What you will learn Think like an architect, analyzing software architecture patterns Explore API design, data storage, and data representation methods Investigate the nuances of common architectural structures Utilize and interoperate elements of patterns such as microservices Implement test-driven development to perform quality code testing Recognize chunks of code that can be restructured as packages Maintain backward compatibility and deploy iterative changes Who this book is forThis book will help software developers and architects understand the structure of large complex systems and adopt architectural patterns that are scalable. Examples in the book are implemented in Python so a fair grasp of basic Python concepts is expected. Proficiency in any programming languages such as Java or JavaScript is sufficient.
(source: Nielsen Book Data)

• Table of Contents An Overview of Amazon EMR Exploring the Architecture and Deployment Options Common Use Cases and Architecture Patterns Big Data Applications and Notebooks Available in Amazon EMR Setting Up and Configuring EMR Clusters Monitoring, Scaling, and High Availability Understanding Security in Amazon EMR Understanding Data Governance in Amazon EMR Implementing Batch ETL Pipeline with Amazon EMR and Apache Spark Implementing Real-Time Streaming with Amazon EMR and Spark Streaming Implementing UPSERT on S3 Data Lake with Apache Spark and Apache Hudi Orchestrating Amazon EMR Jobs with AWS Step Functions and Apache Airflow/MWAA Migrating On-Premises Hadoop Workloads to Amazon EMR Best Practices and Cost Optimization Techniques.
• (source: Nielsen Book Data)

Design scalable big data solutions using Hadoop, Spark, and AWS cloud native services Key Features Build data pipelines that require distributed processing capabilities on a large volume of data Discover the security features of EMR such as data protection and granular permission management Explore best practices and optimization techniques for building data analytics solutions in Amazon EMR Book DescriptionAmazon EMR, formerly Amazon Elastic MapReduce, provides a managed Hadoop cluster in Amazon Web Services (AWS) that you can use to implement batch or streaming data pipelines. By gaining expertise in Amazon EMR, you can design and implement data analytics pipelines with persistent or transient EMR clusters in AWS. This book is a practical guide to Amazon EMR for building data pipelines. You'll start by understanding the Amazon EMR architecture, cluster nodes, features, and deployment options, along with their pricing. Next, the book covers the various big data applications that EMR supports. You'll then focus on the advanced configuration of EMR applications, hardware, networking, security, troubleshooting, logging, and the different SDKs and APIs it provides. Later chapters will show you how to implement common Amazon EMR use cases, including batch ETL with Spark, real-time streaming with Spark Streaming, and handling UPSERT in S3 Data Lake with Apache Hudi. Finally, you'll orchestrate your EMR jobs and strategize on-premises Hadoop cluster migration to EMR. In addition to this, you'll explore best practices and cost optimization techniques while implementing your data analytics pipeline in EMR. By the end of this book, you'll be able to build and deploy Hadoop- or Spark-based apps on Amazon EMR and also migrate your existing on-premises Hadoop workloads to AWS. What you will learn Explore Amazon EMR features, architecture, Hadoop interfaces, and EMR Studio Configure, deploy, and orchestrate Hadoop or Spark jobs in production Implement the security, data governance, and monitoring capabilities of EMR Build applications for batch and real-time streaming data analytics solutions Perform interactive development with a persistent EMR cluster and Notebook Orchestrate an EMR Spark job using AWS Step Functions and Apache Airflow Who this book is forThis book is for data engineers, data analysts, data scientists, and solution architects who are interested in building data analytics solutions with the Hadoop ecosystem services and Amazon EMR. Prior experience in either Python programming, Scala, or the Java programming language and a basic understanding of Hadoop and AWS will help you make the most out of this book.
(source: Nielsen Book Data)

• Table of Contents Getting Started with TinyML Prototyping with Microcontrollers Building a Weather Station with TensorFlow Lite for Microcontrollers Voice Controlling LEDs with Edge Impulse Indoor Scene Classification with TensorFlow Lite for Microcontrollers and the Arduino Nano Building a Gesture-Based Interface for YouTube Playback Running a Tiny CIFAR-10 Model on a Virtual Platform with the Zephyr OS Toward the Next TinyML Generation with microNPU.
• (source: Nielsen Book Data)

Work through over 50 recipes to develop smart applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico using the power of machine learning Key Features Train and deploy ML models on Arduino Nano 33 BLE Sense and Raspberry Pi Pico Work with different ML frameworks such as TensorFlow Lite for Microcontrollers and Edge Impulse Explore cutting-edge technologies such as microTVM and Arm Ethos-U55 microNPU Book DescriptionThis book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers. The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you'll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button, supplying power to microcontrollers with batteries, and more. Next, you'll cover recipes relating to temperature, humidity, and the three "V" sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you'll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you'll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game. By the end of this book, you'll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase. What you will learn Understand the relevant microcontroller programming fundamentals Work with real-world sensors such as the microphone, camera, and accelerometer Run on-device machine learning with TensorFlow Lite for Microcontrollers Implement an app that responds to human voice with Edge Impulse Leverage transfer learning to classify indoor rooms with Arduino Nano 33 BLE Sense Create a gesture-recognition app with Raspberry Pi Pico Design a CIFAR-10 model for memory-constrained microcontrollers Run an image classifier on a virtual Arm Ethos-U55 microNPU with microTVM Who this book is forThis book is for machine learning developers/engineers interested in developing machine learning applications on microcontrollers through practical examples quickly. Basic familiarity with C/C++, the Python programming language, and the command-line interface (CLI) is required. However, no prior knowledge of microcontrollers is necessary.
(source: Nielsen Book Data)

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

"This book examines artistic practices that use machine learning and computational technologies through historical perspectives surrounding adaptive systems from the 1950s onwards"-- Provided by publisher.

• A Study of Energy Reduction Strategies in Renewable Hybrid Grid.- Classification and Watermarking of Brain Tumor using Artificial and Convolutional Neural Networks.- A Proposal for a Deep Learning Model to Enhance Student Guidance and Reduce Dropout.- EduBot: An Unsupervised Domain-Specific Chatbot for Educational Institutions.- SQL Generation from Natural Language using Supervised Learning and Recurrent Neural Networks.- Toward Intelligent Solution to Identify Learner Attitude from Source Code.
• (source: Nielsen Book Data)

This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA'2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
(source: Nielsen Book Data)

• A Fuzzy Ontology Based Approach To Support Product Eco-Design.-
• A Genetic-based SVM Approach for Quality Data Classification.- Towards a platform to implement an intelligent and predictive maintenance in the context of industry.- Towards a Prediction Analysis in an Industrial Context.- Methodology for Implementation of Industry . Technologies in Supply Chain for SMEs.- A Deep Reinforcement Learning DRL Decision Model For Heating Process Parameters Identification In Automotive Glass Manufacturing
• Analytic Hierarchy Process AHP for supply chain . risks management.- SmartDFRelevance: a Holonic Agent based System for Engineering Industrial Projects in Concurrent Engineering Context.- A Cyber-Physical Warehouse Management System Architecture in an.- Industry . context.- PLM and Smart technologies for product and supply chain design.- Production systems simulation considering Non-Productive Times and Human Factors.- Distributed and Embedded System to Control Traffic Collision Based on Artificial Intelligence.- The Emergence and Decision Support in Complex System with Fuzzy Logic Control.- Markov Decision Processes with Discounted Costs over a Finite Horizon: Action Elimination.- Robust adaptive fuzzy path tracking control of Differential Wheeled Mobile Robot.- Deep Learning approach for Automated Guided Vehicle System.- Path Planning Using Particle Swarm Optimization And Fuzzy Logic
• Prediction of Robot localization states using Hidden Markov Models.- A New Approach for Multi-Agent Reinforcement Learning.- Recommender System for Most Relevant k Pick-Up Points.- Feature Detection and Tracking for Visual Effects: Augmented Reality and Video Stabilization.- Spectral image recognition using artificial dynamic neural network in information resonance mode.- U-Net Based Model for Obfuscated Human Faces Reconstruction.- A Machine Learning Assistant for Choosing Operators and Tuning Their Parameters in Image Processing Tasks.- Convergence and parameters setting of continuous Hopfield neural networks applied to image restoration problem.- The Ibn Battouta Air Traffic Control Corpus with Real Life ADS-B and METAR data.- Weed Recognition System For Low-Land Rice Precision Farming Using Deep Learning Approach.- A Comparative Study Between Mixture and Stepwise Regression to Model The Parameters Of The Composting Process.- Deep Learning Based Sponge Gourd Diseases Recognition For Commercial Cultivation in Bangladesh.- Exploitation of vegetation indices and Random Forest for cartography of rosemary cover: application to Gourrama region, Morocco.
• (source: Nielsen Book Data)

This book gathers the refereed proceedings of the Artificial Intelligence and Industrial Applications (A2IA'2020), the first installment of an annual international conference organized by the ENSAM-Meknes at Moulay Ismail University, Morocco. The 30 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as smart manufacturing, smart maintenance, smart supply chain management, supervised learning, unsupervised learning, reinforcement learning, graph-based and semi-supervised learning, neural networks, deep learning, planning and optimization, and other AI applications. The book is intended for AI experts, offering them a valuable overview of the status quo and a global outlook for the future, with many new and innovative ideas and recent important developments in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
(source: Nielsen Book Data)

• Introduction - Ethical and Sustainable Human and Artificial AI Artificial Intelligence and Robotics Applying The Benefits of AI and Identifying Challenges and Risks Starting AI - How to Build A Machine Learning Toolbox Algorithms The Management, Roles and Responsibilities of Humans and Machines AI in Use in Industry - Reimagining Everything in the Fourth Industrial Revolution AI Case Studies .
• (source: Nielsen Book Data)

In alignment with BCS AI Foundation and Essentials certificates, this introductory guide provides the understanding you need to start building artificial intelligence (AI) capability into your organisation. You will learn how AI is being utilised today and how it is likely to be used in the future to balance the talents of humans and machines. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed.
(source: Nielsen Book Data)

• Chapter 1. A Novel Approach for Analysing and Detection of Obfuscated Malware Payloads in Android Platform Using Dexmonitor.- Chapter 2. A Study on the Prevention Mechanisms for Kernel Attacks.- Chapter 3. Enhancing Data Security Using DNA Algorithm in Cloud Storage.- Chapter 4. Stable Multi-Agent Clustering Method to Improve the Security in VANET.- Chapter 5. Anonymous Block Chain, Electronic Voting Using Linkable Ring Signatures.- Chapter 6. A Comprehensive Study on Ransomware Attacks in Online Pharmacy Community.- Chapter 7. A Comprehensive Survey on RF Module at 433 Mhzfor Different Applications.- Chapter 8. A Memory Efficient Tool for Bengali Parts Of Speech Tagging.- Chapter 9. Long-Term Wind Speed Forecasting - A Review.- Chapter 10. Methods for Epileptic Seizure Prediction Using EEG Signals: A Survey.- Chapter 11. Railway Wagon Health Monitoring System Using E-BMA Protocol in Wireless Sensor Networks.- Chapter 12. An Interactive Virtual E-Learning Framework Using Crowdsourced Analytics.- Chapter 13. Security for Data in IOT Using A Newaps Elliptic Curve Light Weight Cryptography Algorithm.- Chapter 14. Feature Selection Strategy for Academic Datasets Using Correlation Analysis.- Chapter 15. Exploration of Magnetic Resonance Imaging for Prognosis of Alzheimer Disease Using Convolutional Neural Network.
• .
• (source: Nielsen Book Data)

This book features a collection of high-quality research papers presented at the International Conference on Advanced Computing Technology (ICACT 2020), held at the SRM Institute of Science and Technology, Chennai, India, on 23-24 January 2020. It covers the areas of computational intelligence, artificial intelligence, machine learning, deep learning, big data, and applications of artificial intelligence in networking, IoT and bioinformatics.
(source: Nielsen Book Data)

• Automatic Standardization of Data based on Machine Learning and Natural Language Processing.- Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network.-APPLICATION OF BAYESIAN AUTOMATED HYPERPARAMETER TUNING ON CLASSIFIERS PREDICTING CUSTOMER RETENTION IN BANKING INDUSTRY.- Quantum Machine Learning: A Review and Current Status.- Survey of Transfer Learning and a Case Study of Emotion Recognition using Inductive Approach.- An Efficient Algorithm for Complete Linkage Clustering with a Merging Threshold.
• (source: Nielsen Book Data)

This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17-19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. .
(source: Nielsen Book Data)

• 1.
• Deep Learning for Innovative Medical Decision Support
• 2.
• Deep Learning and Image Analysis for Medical Decision Support
• 3.
• Deep Learning Oriented Systems for Medical Education
• 4.
• Hybrid Deep Systems for Medical Education and Decision Support
• 5.
• Deep Learning and Optimization for Medical Education and Decision Support 6.
• Deep Learning and Multimedia for Medical Education and Decision Support
• 7.
• Deep Learning and Traditional Methods for Medical Education and Decision Support.
• (source: Nielsen Book Data)

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today's problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation. .
(source: Nielsen Book Data)

• Chapter 1. Double hierarchy linguistic term set and its extensions.-
• Chapter 2. Measure methods for DHHFLTSs.-
• Chapter 3. Consistency theory framework of DHHFLPRs.-
• Chapter 4. Group consensus decision-making methods with DHHFLPRs, LPOs and self-confident DHLPRs.-
• Chapter 5. Large-scale group consensus decision-making methods with DHHFLPRs.
• (source: Nielsen Book Data)

This book presents the concept of the double hierarchy linguistic term set and its extensions, which can deal with dynamic and complex decision-making problems. With the rapid development of science and technology and the acceleration of information updating, the complexity of decision-making problems has become increasingly obvious. This book provides a comprehensive and systematic introduction to the latest research in the field, including measurement methods, consistency methods, group consensus and large-scale group consensus decision-making methods, as well as their practical applications. Intended for engineers, technicians, and researchers in the fields of computer linguistics, operations research, information science, management science and engineering, it also serves as a textbook for postgraduate and senior undergraduate university students.
(source: Nielsen Book Data)

• Part I: Artificial Intelligence and Optimization.- Stochastic Proximal Gradient Algorithm with Minibatches Application to Large Scale Learning Models.- The Human Mental Search Algorithm for Solving Optimisation Problems.- Reducing Redundant Association Rules Using Type-2 Fuzzy Logic.- Identifiability of Discrete Concentration Graphical Models with a Latent Variable.- An Automatic Classification of Genetic Mutations by Exploring Different Classifiers.- Towards Artificial Intelligence: Concepts, Applications, and Innovations.- Part II: Big Data and Artificial Intelligence Applications.- In Depth Analysis, Applications and Future Issues of Artificial Neural Network.- Big Data and Deep Learning in Plant Leaf Diseases Classification for Agriculture.- Machine Learning Cancer Diagnosis Based on Medical Image Size and Modalities.
• (source: Nielsen Book Data)

This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.
(source: Nielsen Book Data)

• Faster Result Retrieval from Health Care Product Sales Data Warehouse using Materialized Queries.- Feature Selection using Ant Colony Optimization and Weighted Visibility Graph.- From Generic to Custom: A Survey on Role of Machine Learning in Pharmacogenomics, Its Applications and Challenges.- Personalized Structure Balance Theory Based Movie Recommendation System.- Machine Learning Techniques for the Investigation of Phishing Websites.
• (source: Nielsen Book Data)

This book presents the proceedings of 8th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2020), which aims to bring together researchers, scientists, engineers and practitioners to share new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. The book is divided into two volumes: Evolution in Computational Intelligence (Volume 1) and Intelligent Data Engineering and Analytics (Volume 2). Covering a broad range of topics in computational intelligence, the book features papers on theoretical as well as practical aspects of areas such as ANN and genetic algorithms, computer interaction, intelligent control optimization, evolutionary computing, intelligent e-learning systems, machine learning, mobile computing, and multi-agent systems. As such, it is a valuable reference resource for postgraduate students in various engineering disciplines.
(source: Nielsen Book Data)

• Table of Contents An Introduction to Generative AI: "Drawing" Data from Models Setting Up a TensorFlow Lab Building Blocks of Deep Neural Networks Teaching Networks to Generate Digits Painting Pictures with Neural Networks Using VAEs Image Generation with GANs Style Transfer with GANs Deepfakes with GANs The Rise of Methods for Text Generation NLP 2
• .0: Using Transformers to Generate Text Composing Music with Generative Models Play Video Games with Generative AI: GAIL Emerging Applications in Generative AI.
• (source: Nielsen Book Data)

Understand the theory behind deep generative models and experiment with practical examples Key Features Build a solid understanding of the inner workings of generative models Experiment with practical TensorFlow 2.x implementations of state-of-the-art models Explore a wide range of current and emerging use cases for deep generative AI Book DescriptionDeep generative models are powerful tools that rival human creative capabilities. In this book, you'll discover how these models emerged, from restricted Boltzmann machines and deep belief networks to VAEs, GANs, and beyond. You'll develop a foundational understanding of generative AI and learn how to implement models yourself in TensorFlow, supported by references to seminal and current research. After getting to grips with the fundamentals of deep neural networks, you'll set up a scalable code lab in the cloud and begin to explore the huge breadth of potential use cases for generative models. You'll look at Open AI's news generator, networks for style transfer and deepfakes, synergy with reinforcement learning, and more. As you progress, you'll recreate the code that makes these possible, piecing together TensorFlow layers, utility functions, and training loops to uncover links between the different modes of generation. By the end of this book, you will have acquired the knowledge to create and implement your own generative AI models. What you will learn Implement paired and unpaired style transfer with networks like StyleGAN Use facial landmarks, autoencoders, and pix2pix GAN to create deepfakes Build several text generation pipelines based on LSTMs, BERT, and GPT-2, learning how attention and transformers changed the NLP landscape Compose music using hands-on LSTM models, simple GANs, and the intricate MuseGAN Train a deep learning agent to move through a simulated physical environment Discover emerging applications of generative AI, such as folding proteins and creating videos from images Who this book is forThis book will appeal to Python programmers, seasoned modelers, and machine learning engineers who are keen to learn about the creation and implementation of generative models. To make the most out of this book, you should have a basic familiarity with probability theory, linear algebra, and deep learning.
(source: Nielsen Book Data)

• Stochastic Investigation of Two-unit Redundant System with Provision of Different Repair Schemes.- A Workflow Allocation Strategy under Precedence Constraints for IaaS Cloud Environment.- Artificial Neural Network Analysis for Predicting Spatial Patterns of Urbanization in India.- Satellite Radar Interferometry for DEM Generation using Sentinel-1A Imagery.
• (source: Nielsen Book Data)

This book presents high-quality, peer-reviewed papers from the International Conference on "Innovations in Computational Intelligence and Computer Vision (ICICV 2020), " hosted by Manipal University Jaipur, Rajasthan, India, on January 17-19, 2020. Offering a collection of innovative ideas from researchers, scientists, academics, industry professionals and students, the book covers a variety of topics, such as artificial intelligence and computer vision, image processing and video analysis, applications and services of artificial intelligence and computer vision, interdisciplinary areas combining artificial intelligence and computer vision, and other innovative practices.
(source: Nielsen Book Data)

• Frontmatter
• Remerciements
• Sommaire
• Préface
• 1. Qu'est-ce au juste que l'intelligence artificielle?
• 2. Avec l'intelligence artificielle générale pour Graal
• 3. Langage, créativité et émotions
• 4. Les réseaux de neurones artificiels
• 5. Les robots et la vie artificielle (A-life)
• 6. Mais, est-ce réellement de l'intelligence?
• 7. La Singularité
• Références
• Lectures complémentaires
• Index

L'intelligence artificielle, qui consiste à faire faire aux ordinateurs ce que peut faire l'esprit humain et ses applications touchent tous les aspects de notre vie et se trouvent tout autour de nous. Ce petit livre nous rappelle que les résultats de l'intelligence artificielle ont été inestimables pour les biologistes, les psychologues et les linguistes en les aidant à comprendre les processus de la mémoire, de l'apprentissage et du langage sous un angle nouveau. L'intelligence artificielle a aussi alimenté et aiguisé les débats philosophiques concernant la nature de l'esprit, l'intelligence et le caractère unique des êtres humains. Ainsi, Margaret Boden, leader dans le domaine de la recherche en intelligence artificielle, passe en revue ici tous les défis philosophiques et technologiques soulevés par l'intelligence artificielle, et tente de répondre à la question si complexe : les programmes pourront-ils être un jour réellement intelligents, créatifs, ou même conscients ?

• Data Jackets as Communicable Metadata for Potential Innovators - Toward Opening to Social Contexts.- A Proposal Based on Instance Typicality for Dealing with Nominal Attribute Values in Instance-Based Learning Environments.- Dataset for Intrusion Detection in Mobile Ad-Hoc Networks.- Visual Password Scheme Using Bag Context Shape Grammars.- Peak detection enhancement in autonomous wearable Fall Detection.- Automated detection of tuberculosis from sputum smear microscopic images using transfer learning techniques.- Comparative Performance Analysis of Neural Network Base Training Algorithm and Neuro-Fuzzy System with SOM for the Purpose of Prediction of the Features of Superconductors.
• (source: Nielsen Book Data)

This book highlights recent research on intelligent systems and nature-inspired computing. It presents 62 selected papers from the 19th International Conference on Intelligent Systems Design and Applications (ISDA 2019), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from 33 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
(source: Nielsen Book Data)

• Introduction.- IoT Overview.- Emerging Trends in IoT.- IoT Use Cases.- Energy and Utilities.- Context Management in IoT.- Context and Context Management.- Context-aware Architecture.- Augmented Reality and IoT.- Augmented Reality and IoT design Issues.- Augmented Reality and IoT enabled Architecture.- Conclusions.
• (source: Nielsen Book Data)

This book discusses the use of converged technology, a rapidly growing area that enhancements smart devices, communication, Internet of things (IoT), and augmented reality (AR). The book also explores the need for convergence of IoT and AR for various purposes, like personalized services, context awareness, and bridging the gap between the physical and digital world. Furthermore, it examines the implementation of IoT and AR in use cases to define pathways that allow application developers to design modern solutions to satisfy requirements like scalability, abstraction and security. Featuring an introduction, and covering sensing techniques, and effective architecture in AR-based IoT real-time use cases, the book also addresses the issues and challenges in designing standard architecture and middleware to support diverse applications. Given its scope, it is a valuable resource for teachers and students in engineering, as well as researchers, developers, and users working in multi-disciplinary areas.
(source: Nielsen Book Data)

• PART I - INTELLIGENT TRANSPORT SYSTEMS AND INFRASTRUCTURE
• CHAPTER 1: An Overview on Intelligent Transportation Systems in the Context of Internet of Vehicles
• CHAPTER 2: Intelligent Transportation Systems and its Necessity in Various Traffic Conditions in Indian Scenarios PART II - CONNECTED VEHICLES
• CHAPTER 3: Autonomous Driving Cars: Decision-Making
• CHAPTER 4: IEEE 802.11ah for Internet of Vehicles: Design Issues and Challenges
• CHAPTER 5: Medium access control in connected vehicles: Advances and Limitations PART III - ADVANCE DRIVER ASSISTED SYSTEM
• CHAPTER 6: An Overview of ADAS in Internet of Vehicles
• CHAPTER 7: iDriveAR: in Vehicle Driver Awareness and Drowsiness Framework based on Facial Tracking and Augmented reality
• CHAPTER 8: The Concept of Fusion for Clear Vision of Hazy Roads in ADAS PART VI - EVALUATION METHODS AND SECURITY ISSUES
• CHAPTER 9: Blockchain-enabled Security and Privacy for Internet of Vehicles
• CHAPTER 10: Approximation Algorithm and Linear Congruence: A state-of-art Approach in Information Security issues towards Internet of Vehicles
• CHAPTER 11: E-powertrain error detection using AI Techniques.
• (source: Nielsen Book Data)

This book provides an insight on the importance that Internet of Vehicles (IoV) solutions can have in taking care of vehicular safety through internetworking and automation. Key features of the book are the inclusion and elaboration of recent and emerging developments in various specializations of intelligent transportation systems and their solutions by incorporating IoT (Internet of Things) and IoV. This book presents to its readers useful IoV applications and architectures that cater to their improved driving requirements and lead towards autonomous driving. The application domains have a large range in which vehicular networking, communication technology, sensor devices, computing materials and devices, IoT communication, vehicular and on-road safety, data security and other topics are included. .
(source: Nielsen Book Data)

• Introduction
• Monitoring of Weld Pool Surface with Active Vision
• Visual Sensing of 3D Weld Pool Geometry with Passive Vision Image
• Penetration prediction with machine learning models
• Penetration Control for Bead-on plate welding
• Penetration Detection of narrow U-groove welding
• Lack of fusion detection inside narrow U-groove
• Conclustions and recommendations.

This book describes the application of vision-sensing technologies in welding processes, one of the key technologies in intelligent welding manufacturing. Gas tungsten arc welding (GTAW) is one of the main welding techniques and has a wide range of applications in the manufacturing industry. As such, the book also explores the application of AI technologies, such as vision sensing and machine learning, in GTAW process sensing and feature extraction and monitoring, and presents the state-of-the-art in computer vision, image processing and machine learning to detect welding defects using non-destructive methods in order to improve welding productivity. Featuring the latest research from ORNL (Oak Ridge National Laboratory) using digital image correlation technology, this book will appeal to researchers, scientists and engineers in the field of advanced manufacturing.
(source: Nielsen Book Data)

"The first book that provides a systematic and rigorous logical theory of causality"-- Provided by publisher.

• Part I: Natural Language Processing.- A Hybrid Feature Selection Approach Based on LSI for Classification of Urdu Text.- Automated Document Categorization Model.- Automated Categorization & Mining Tweets for Disaster Management.- Sentiment Analysis in Airline Data: Customer Rating Based Recommendation Prediction using WEKA.- Part II: Computer Vision.- Image Inpainting for Irregular Holes using Extreme Learning Machine.- OCR using Computer Vision and Machine Learning.- Few Shot Learning for Medical Imaging.- Hyperspectral Remote Sensing Image Classification using Active Learning.- A Smart Document Converter: Conversion of Handwritten Text Document to Computerized Text Document.- GRNN Based An Intelligent Technique for Image Inpainting.- Part III: Data Analysis and Prediction.- Content-Based Airline Recommendation Prediction using Machine Learning Techniques.- Meta-heuristic Based Approach for Slope Stability Analysis to Design an Optimal Soil Slope.- An Application of Operational Analytics: for Predicting Sales Revenue of Restaurant.- Application of Machine Learning Algorithm for Anomaly Detection for Industrial Pumps.- Part IV: Decision Making System.- Fast Accessing Non-volatile, High Performance-High Density, Optimized Array for Machine Learning Processor.- Long Term Evolution for Secured Smart Railway Communications using Internet of Things.- Application of the Flower Pollination Algorithm to Locate Critical Failure Surface for Slope Stability Analysis.
• (source: Nielsen Book Data)

This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners. .
(source: Nielsen Book Data)

• Table of Contents Getting Started with TensorFlow 2.x The TensorFlow Way Keras Linear Regression Boosted Trees Neural Networks Predicting with Tabular Data Convolutional Neural Networks Recurrent Neural Networks Transformers Reinforcement Learning with TensorFlow and TF-Agents Taking TensorFlow to Production.
• (source: Nielsen Book Data)

Master TensorFlow to create powerful machine learning algorithms, with valuable insights on Keras, Boosted Trees, Tabular Data, Transformers, Reinforcement Learning and more Key Features Work with the latest code and examples for TensorFlow 2 Get to grips with the fundamentals including variables, matrices, and data sources Learn advanced deep learning techniques to make your algorithms faster and more accurate Book DescriptionThe independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data. You will work through recipes on training models, model evaluation, sentiment analysis, regression analysis, artificial neural networks, and deep learning - each using Google's machine learning library, TensorFlow. This cookbook begins by introducing you to the fundamentals of the TensorFlow library, including variables, matrices, and various data sources. You'll then take a deep dive into some real-world implementations of Keras and TensorFlow and learn how to use estimators to train linear models and boosted trees, both for classification and for regression to provide a baseline for tabular data problems. As you progress, you'll explore the practical applications of a variety of deep learning architectures, such as recurrent neural networks and Transformers, and see how they can be applied to computer vision and natural language processing (NLP) problems. Once you are familiar with the TensorFlow ecosystem, the final chapter will teach you how to take a project to production. By the end of this machine learning book, you will be proficient in using TensorFlow 2. You'll also understand deep learning from the fundamentals and be able to implement machine learning algorithms in real-world scenarios. What you will learn Grasp linear regression techniques with TensorFlow Use Estimators to train linear models and boosted trees for classification or regression Execute neural networks and improve predictions on tabular data Master convolutional neural networks and recurrent neural networks through practical recipes Apply reinforcement learning algorithms using the TF-Agents framework Implement and fine-tune Transformer models for various NLP tasks Take TensorFlow into production Who this book is forIf you are a data scientist or a machine learning engineer, and you want to skip detailed theoretical explanations in favor of building production-ready machine learning models using TensorFlow, this book is for you. Basic familiarity with Python, linear algebra, statistics, and machine learning is necessary to make the most out of this book.
(source: Nielsen Book Data)

"A collection of critical essays dealing with the social and ethical impacts of AI including issues of trust, reliability, and bias"-- Provided by publisher.

This book intends to bring together researchers and developers from industry, the education field, and the academic world to report on the latest scientific research, technical advances, and methodologies. The 10th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning is hosted by the University of L'Aquila and is going to be held in L'Aquila (Italy). Initially planned on the 17th to the 19th of June 2020, it was postponed to the 7th to the 9th of October 2020, due to the COVID-19 outbreak. The 10th edition of this conference and its related workshops expand the topics of the evidence-based TEL workshops series in order to provide an open forum for discussing intelligent systems for TEL, their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone solutions, or web-based ones. This bridge has been realized also thanks to the sponsor of this edition of MIS4TEL: the Armundia Group https://www.armundia.com, the support from national associations (AEPIA, APPIA, CINI, and EurAI), and organizers (UNIVAQ, UNIROMA1, UNIBZ, UCV, UFSC, USAL, AIR institute, UNC, and UNIBA).
(source: Nielsen Book Data)
This book features papers from workshops at the 10th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning, which was hosted by the University of L'Aquila (Italy) from 17th to 19th June 2020. The workshops provided participants with the opportunity to present and discuss novel research ideas on emerging topics complementing the main conference. They particularly focused on multi-disciplinary and transversal aspects such as TEL in nursing education programs, social and personal computing for web-supported learning communities, interactive environments and emerging technologies for eLearning, and TEL for future citizens.
(source: Nielsen Book Data)

• Introduction
• Kinematic Geometry of the PnP Robots
• Differential Kinematics of the Robots
• Kinematic Performance Criteria
• Elastostatics and Stiffness
• Rigid Multibody Dynamics
• Robot Elastodynamics
• Design optimization of parallel PnP Robots.

This book discusses the parametric modeling, performance evaluation, design optimization and comparative study of the high-speed, parallel pick-and-place robots. It collects the modeling methodology, evaluation criteria and design guidelines for parallel PnP robots to provide a systematic analysis method for robotic developers. Furthermore, it gathers the research results previously scattered in many prestigious international journals and conference proceedings and methodically edits them and presents them in a unified form. The book is of interest to researchers, R&D engineers and graduate students in industrial parallel robotics who wish to learn the core principles, methods, algorithms, and applications.
(source: Nielsen Book Data)

• Ability Study of Proximity Measure for Big Data Mining Context on Clustering.- Not Yet Decided.- An Approach to Implement MapReduce and aggregation pipeline utilizing NoSql Technologies.- Energy Hole Alleviation in Wireless sensor.
• (source: Nielsen Book Data)

This book offers a collection of high-quality peer-reviewed research papers presented at the Second International Conference on Communication and Computational Technologies (ICCCT 2019), held at Rajasthan Institute of Engineering and Technology, Jaipur, Rajasthan, India, on 30-31 August 2019. In contributions prepared by researchers from academia and industry alike, the book discusses a wide variety of industrial, engineering and scientific applications of emerging techniques.
(source: Nielsen Book Data)

• Development of an Industry 4.0 demonstrator using Sequence Planner and ROS2.- ROS2 for ROS1 users.- Multi-Robot SLAM framework for ROS with Efficient Information Sharing.- Agile experimentation of robot swarms in large scale.- Lessons learned building a self-driving car on top of ROS.- Landing a UAV on a moving platform using a front facing camera.- Integrating the Functional Mock-up Interface with ROS and Gazebo.- An ARVA sensor simulator.- ROS Implementation for Untethered Microrobot Manipulation.- ClegS: A package to develop C-legged robots.- Video frames selection method for 3D Reconstruction depending on ROS-based monocular SLAM.- ROS Rescue: Fault Tolerance System for ROS.
• (source: Nielsen Book Data)

This book is the fifth volume in the successful book series Robot Operating System: The Complete Reference. The objective of the book is to provide the reader with comprehensive coverage on the Robot Operating System (ROS), which is currently considered to be the primary development framework for robotics applications, and the latest trends and contributing systems. The content is divided into six parts. Pat I presents for the first time the emerging ROS 2.0 framework, while Part II focuses on multi-robot systems, namely on SLAM and Swarm coordination. Part III provides two chapters on autonomous systems, namely self-driving cars and unmanned aerial systems. In turn, Part IV addresses the contributions of simulation frameworks for ROS. In Part V, two chapters explore robotic manipulators and legged robots. Finally, Part VI presents emerging topics in monocular SLAM and a chapter on fault tolerance systems for ROS. Given its scope, the book will offer a valuable companion for ROS users and developers, helping them deepen their knowledge of ROS capabilities and features. .
(source: Nielsen Book Data)

• Intro
• Preface
• Introduction
• Contents
• 1 Safety the Basis for Future Mobility
• 1.1 Safety is Much More Than Safety Engineering
• 1.2 Safety as a Social Right
• 1.3 Legal Basis for "Auto-Mobility"
• 1.3.1 The German Road Traffic Act (StVG)
• 1.3.2 Origin of the German Road Traffic Act
• 1.3.3 Adaptation of the Traffic Right for the Globalisation Trend
• 1.3.4 Activities in Germany for Future Mobility Solutions
• 1.3.5 Genevan and Viennese Convention
• 1.4 European Union (EU) and Legislation
• 1.4.1 EU Directives Related to Road Traffic
• 1.4.2 European Vehicle Class

• 1.4.3 EU Directive for Future Mobility
• 1.5 Licensing Act
• 1.6 US Road Traffic Regulations
• 1.7 UNECE
• 1.8 Legal View on Future Mobility
• 1.8.1 New Licensing Approach for Automated Vehicles
• 1.8.2 ITS Law
• 1.8.3 ETSI-European Telecommunications Standards Institute
• 1.8.4 OECD, Organisation for Economic Co-operation and Development
• 1.8.5 ETSC European Transport Safety Council
• 1.8.6 IT Security Act
• 1.9 Product Liability
• 1.10 Common Law and Civil Law
• 1.11 Legal Regulation in China
• 1.12 Insurance
• 2 Risk Management
• 2.1 Risk Management Cycle

• 2.1.1 Development of the Context
• 2.1.2 Identification of Risk
• 2.1.3 Assessment of the Risk in the Target Context
• 2.1.4 Development of a Strategy and Treatment of Potential Risk
• 2.1.5 Development and Defining of Activities and Their Objectives
• 2.1.6 Development of an Implementation and Realisation Strategy
• 2.1.7 Review and Evaluation of the Plan
• 2.2 Technical Risk
• 2.3 Risk in Road Traffic
• 2.3.1 Causes of Technical Risk
• 2.3.2 Control of Technical Risk
• 2.4 Standardisation of Safety for Road Vehicles
• 2.4.1 Risk and Integrity Definition from the IEC 61508

• 2.4.2 Risk According to ISO 26262
• 2.5 Critical Infrastructure
• 2.5.1 Organisation for Critical Infrastructure
• 2.5.2 Cloud Computing
• 2.5.3 Transport and Traffic and Critical Infrastructure
• 3 Automation in Mobility
• 3.1 Human Driving: a Closed-Loop Control System
• 3.2 Human Driving
• 3.2.1 Driver's HMI
• 3.2.2 Driver in the Loop
• 3.2.3 Human Driving Journey
• 3.3 Human Control Mechanism
• 3.4 Human Behaviour and Context
• 3.4.1 Observer of the Observer
• 3.4.2 Industry Automation
• 3.4.3 Multiple Contexts for Different Layers of Abstraction

• 3.5 Communication and Interfaces
• 3.6 Human Driver as a Control System
• 3.6.1 Human Communication
• 3.6.2 Human Perception
• 3.6.3 Technical Control System Comparison
• 3.6.4 Control System Architecture in Comparison with the Human Control System
• 3.7 Cyclic Data Processing Versus Distributed Event-Driven Data Processing
• 3.7.1 Distributed Control
• 3.7.2 Configuration of Human Control System
• 3.8 Cybernetics and Control
• 3.8.1 Digital Twin
• 3.8.2 Cybernetics About Behaviour and Control
• 3.8.3 Cybernetics and Sufficiently Perceiving the Environment

The book provides background information about technical solutions, processes and methodology to develop future automated mobility solutions. Beginning from the legal requirements as the minimum tolerable risk level of the society, the book provides state-of-the-art risk-management methodologies. The system engineering approach based on todays engineering best practices enhanced by principles derived from cybernetics. The approach derived from the typical behaviour of a human driver in public road traffic to a cybernetical based system engineering approach. Beyond the system engineering approach, a common behaviour model for the operational domain will show aspects how to extend the system engineering model with principles of cybernetics. The role and the human factors of road traffic participants and drivers of motor vehicles are identified and several viewpoints for different observers show how such mixed traffic scenarios could be assessed and optimised. The influence of the changing mobility demands of the society and the resulting changes to the origination of producer, owner, driver and supplier show aspects for future liability and risk share option for new supply chains. Examples from various industries provide some well-proven engineering principles how to adapt those for the future mobility for the benefit of the users. The aim of the book is to raise awareness that the safety provided by a product, a means of transport or a system up to an entire traffic system depends on the capabilities of the various actors. In addition to the driver and passengers, there are also other road users, maintenance personnel and service providers, who must have certain abilities to act safely in traffic. These are also the capabilities of the organisation, not only the organisation that develops or brings the product to market, but also the organisation that is responsible for the operation and the whole lifecycle of the products. The book is for people who want to get invo lved in the mobility of the future. People, that have ideas to become a player who want to help shape the future mobility of society and who want to bring responsible solutions for users into the market.

• Chapter 1. An Integrated Design of Fuzzy C-Means and NCA based Multi-Properties Features Reduction for Brain Tumor Recognition.-
• Chapter 2. Hybrid Image Processing based Examination of 2D Brain MRI Slices to Detect Brain Tumour/Stroke Section - A Study.-
• Chapter 3. Edge Enhancing Coherence Diffusion Filter for Level Set Segmentation and Asymmetry Analysis using Curvelets in Breast Thermograms.-
• Chapter 4. Lung Cancer Diagnosis Based on Image Fusion and prediction using CT and PET image.-
• Chapter 5. Segmentation and Validation of Infrared Breast Images using Weighted Level Set and Phase Congruency Edge Map Framework.-
• Chapter 6. Analysis of Material Profile for Polymer Based Mechanical Microgripper for Thin Plate Holding.-
• Chapter 7. Design and Testing of Elbow Actuated Wearable Robotic Arm for Muscular Disorders.-
• Chapter 8. A Comprehensive Study of Image Fusion Techniques and Their Applications.-
• Chapter 9. Multilevel Mammogram Image Analysis for Identifying Outliers, Misclassification using Machine Learning.-
• Chapter 10. A Review on Automatic Detection of Retinal Lesions in Fundus Images for Diabetic Retinopathy.-
• Chapter 11. Medical Image Watermarking: A Review on Wavelet Based Methods.-
• Chapter 12. EEG Signal Extraction Analysis Techniques.-
• Chapter 13. Classification of sEMG Signal based Arm Action using Convolutional Neural Network.-
• Chapter 14. An Automated Approach for the Identification of TB Images Enhanced by Non-uniform Illumination Correction.
• (source: Nielsen Book Data)

This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
(source: Nielsen Book Data)

• Introduction.- A Brief Review of Socio-Inspired Metaheuristics.- Multi Cohort Intelligence Algorithm.- Optimization of Electric Discharge Machining (EDM).- Optimization of Abrasive Water Jet Machining (AWJM).- Optimization of Micro Milling Process.- Optimization of Micro Drilling Process.- Optimization of Cutting Forces in Micro Drilling of CFRP Composites for Aerospace Applications.- Optimization of Micro Turning Process.- Optimization of Machining Process Parameters of Titanium Alloy Under (MQL) Environment.
• (source: Nielsen Book Data)

This book discusses comprehensively the advanced manufacturing processes, including illustrative examples of the processes, mathematical modeling, and the need to optimize associated parameter problems. In addition, it describes in detail the cohort intelligence methodology and its variants along with illustrations, to help readers gain a better understanding of the framework. The theoretical and statistical rigor is validated by comparing the solutions with evolutionary algorithms, simulation annealing, response surface methodology, the firefly algorithm, and experimental work. Lastly, the book critically reviews several socio-inspired optimization methods. .
(source: Nielsen Book Data)

• Intro
• Preface
• Invited Speakers
• DSS, Classifications, Trends and Enabling Modern Information and Communication Technologies
• Distorted Statistics based on Choquet Calculus
• Overview of QUasi-Affine TRansformation Evolutionary (QUATRE) Algorithm
• Nature-Inspired Optimization of Type-2 Fuzzy Logic Controllers
• Seeing Is Believing
• Contents
• Short CVs of Guest Editors
• I Soft Computing and Conventional Techniques in Power Engineering Methods and Applications in Electrical Engineering I

• Daily Load Curve Forecasting. Comparative Analysis: Conventional vs. Unconventional Methods
• Abstract
• 1 Introduction
• 2 Developed Algorithms
• 2.1 Artificial Neural Networks (ANN)
• 2.2 Multiple Linear Regression (MLR)
• 2.3 Curve Fitting (CF)
• 2.4 Decision Trees (DT)
• 3 Numerical Results. Discussions
• 3.1 Forecast Performed for 2017 Year
• 3.2 Forecast Performed for 2018 Year
• 3.3 Comparative Analysis for Several Forecasts
• 4 Conclusion
• Acknowledgment
• References
• LoRaWAN Based Airport Runway Lights Monitoring System
• Abstract
• 1 Introduction
• 2 LoRa Technology

• 3 Case Study and Results
• 4 Conclusions
• Acknowledgment
• References
• The Enhanced Crow Search Algorithm for Fuel-Cost Function Parameters Assessment of the Cogeneration Units from Thermal Power Plants
• Abstract
• 1 Introduction
• 2 Estimating the Fuel-Cost Function Parameters
• 3 The Crow Search Algorithm (CS)
• 4 The Enhanced CS Algorithm (ECS)
• 5 Case Studies and Results
• 6 Conclusions
• References
• Modelling a Photovoltaic Power Station
• Abstract
• 1 Introduction
• 2 Simulation of the Photovoltaic Panels Using MatLAB Software

• 2.1 Simulink: Modelling of a PV Solar Cell
• 2.2 The Intensity of the Induced Electrical Current by the Sun
• 2.3 Dependence on the Temperature
• 3 The Simulation of a PV Power Station
• 4 Conclusions
• References
• Identification of Fault Locations on Tree Structure Systems
• 1 Introduction
• 2 Description of the Troubleshooting System Currently Used by the Power Suppliers
• 3 Mathematical Background of the Proposed Method
• 4 Fault Probability Data Bank
• 5 SGFI Algorithm
• 5.1 Localization of the Fault Zone (Procedure 1)

• 5.2 Fault Position Localization in the Fault Zone (Procedure 2)
• 5.3 Result of the Proposed Algorithm
• 5.4 Simulation Analysis of the SGFI Algorithm
• 6 Conclusions
• References
• Probability Distribution Functions for Short-Term Wind Power Forecasting
• 1 Introduction
• 2 Wind Probability Distribution Functions
• 2.1 Weibull Distribution
• 2.2 Lindley Distribution for Random Variables
• 2.3 Joint Probability Distribution Function for Wind Forecasting
• 3 Short-Term Wind Power Forecasting Using SVR and ANN
• 3.1 Wind Power Forecasting Using Support Vector Regressors
• 3.2 Wind Power Forecasting Using ANN.

This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13-15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics - Arad Section, General Association of Engineers in Romania - Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.
(source: Nielsen Book Data)

• Table of Contents Getting Started with the Model Architecture of the Transformer Fine-Tuning BERT Models Pretraining a RoBERTa Model from Scratch Downstream NLP Tasks with Transformers Machine Translation with the Transformer Text Generation with OpenAI GPT-2 and GPT-3 Models Applying Transformers to Legal and Financial Documents for AI Text Summarization Matching Tokenizers and Datasets Semantic Role Labeling with BERT-Based Transformers Let Your Data Do the Talking: Story, Questions, and Answers Detecting Customer Emotions to Make Predictions Analyzing Fake News with Transformers Appendix: Answers to the Questions.
• (source: Nielsen Book Data)

Become an AI language understanding expert by mastering the quantum leap of Transformer neural network models Key Features Build and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning models Go through hands-on applications in Python using Google Colaboratory Notebooks with nothing to install on a local machine Learn training tips and alternative language understanding methods to illustrate important key concepts Book DescriptionThe transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains with transformers. The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face. The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets. What you will learn Use the latest pretrained transformer models Grasp the workings of the original Transformer, GPT-2, BERT, T5, and other transformer models Create language understanding Python programs using concepts that outperform classical deep learning models Use a variety of NLP platforms, including Hugging Face, Trax, and AllenNLP Apply Python, TensorFlow, and Keras programs to sentiment analysis, text summarization, speech recognition, machine translations, and more Measure the productivity of key transformers to define their scope, potential, and limits in production Who this book is forSince the book does not teach basic programming, you must be familiar with neural networks, Python, PyTorch, and TensorFlow in order to learn their implementation with Transformers. Readers who can benefit the most from this book include deep learning & NLP practitioners, data analysts and data scientists who want an introduction to AI language understanding to process the increasing amounts of language-driven functions.
(source: Nielsen Book Data)

• CHAPTER 1 Introduction
• CHAPTER 2 Accelerated Algorithms for Unconstrained Convex Optimization
• 1. Preliminaries
• 2. Accelerated Gradient Method for smooth optimization
• 3. Extension to the Composite Optimization
• 3.1. Nesterov's First Scheme
• 3.2. Nesterov's Second Scheme
• 3.2.1. A Primal Dual Perspective
• 3.3. Nesterov's Third Scheme
• 4. Inexact Proximal and Gradient Computing
• 4.1. Inexact Accelerated Gradient Descent
• 4.2. Inexact Accelerated Proximal Point Method
• 5. Restart
• 6. Smoothing for Nonsmooth Optimization
• 7. Higher Order Accelerated Method
• 8. Explanation: An Variational Perspective
• 8.1. Discretization
• CHAPTER 3 Accelerated Algorithms for Constrained Convex Optimization
• 1. Preliminaries
• 1.1. Case Study: Linear Equality Constraint
• 2. Accelerated Penalty Method
• 2.1. Non-strongly Convex Objectives
• 2.2. Strong Convex Objectives
• 3. Accelerated Lagrange Multiplier Method
• 3.1. Recovering the Primal Solution
• 3.2. Accelerated Augmented Lagrange Multiplier Method
• 4. Accelerated Alternating Direction Method of Multipliers
• 4.1. Non-strongly Convex and Non-smooth
• 4.2. Strongly Convex and Non-smooth
• 4.3. Non-strongly Convex and Smooth
• 4.4. Strongly Convex and Smooth
• 4.5. Non-ergodic Convergence Rate
• 4.5.1. Original ADMM
• 4.5.2. ADMM with Extrapolation and Increasing Penalty Parameter
• 5. Accelerated Primal Dual Method
• 5.1. Case 1
• 5.2. Case 2
• 5.3. Case 3
• 5.4. Case 4
• CHAPTER 4 Accelerated Algorithms for Nonconvex Optimization
• 1. Proximal Gradient with Momentum
• 1.1. Basic Assumptions
• 1.2. Convergence Theorem
• 1.3. Another Method: Monotone APG
• 2. AGD Achieves the Critical Points Quickly
• 2.1. AGD as a Convexity Monitor
• 2.2. Negative Curvature
• 2.3. Accelerating Nonconvex Optimization
• 3. AGD Escapes the Saddle Points Quickly
• 3.1. Almost Convex
• 3.2. Negative Curvature Descent
• 3.3. AGD for Non-Convex Problem
• 3.3.1. Locally Almost Convex! Globally Almost Convex
• 3.3.2. Outer Iterations
• 3.3.3. Inner Iterations
• CHAPTER 5 Accelerated Stochastic Algorithms
• 1. The Individual Convexity Case
• 1.1. Accelerated Stochastic Coordinate Descent
• 1.2. Background for Variance Reduction Methods
• 1.3. Accelerated Stochastic Variance Reduction Method
• 1.4. Black-Box Acceleration
• 2. The Individual Non-convexity Case
• 2.1. Individual Non-convex but Integrally Convex
• 3. The Non-Convexity Case
• 3.1. SPIDER
• 3.2. Momentum Acceleration
• 4. Constrained Problem
• 5. Infinity Case
• CHAPTER 6 Paralleling Algorithms
• 1. Accelerated Asynchronous Algorithms
• 1.1. Asynchronous Accelerated Gradient Descent
• 1.2. Asynchronous Accelerated Stochastic Coordinate Descent
• 2. Accelerated Distributed Algorithms
• 2.1. Centralized Topology
• 2.1.1. Large Mini-batch Algorithms
• 2.1.2. Dual Communication-Efficient Methods
• 2.2. Decentralized Topology
• CHAPTER 7 Conclusions
• APPENDIX Mathematical Preliminaries.
• (source: Nielsen Book Data)

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where the algorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time.
(source: Nielsen Book Data)

• Part I: Basics and Theory
• Photometry
• Geometry
• Sensors
• Light Sources
• Part II: Algorithms Photometric stereo
• Structured light
• Other shape reconstruction techniques
• Photometric estimation Part III: Applications
• Visualization, Augmented Reality, Virtual Reality, and Mixed Reality Systems
• Biomedical Applications
• E-Heritage
• Robot Vision, Autonomous Vehicles, and Humans.
• (source: Nielsen Book Data)

This book describes active illumination techniques in computer vision. We can classify computer vision techniques into two classes: passive and active techniques. Passive techniques observe the scene statically and analyse it as is. Active techniques give the scene some actions and try to facilitate the analysis. In particular, active illumination techniques project specific light, for which the characteristics are known beforehand, to a target scene to enable stable and accurate analysis of the scene. Traditional passive techniques have a fundamental limitation. The external world surrounding us is three-dimensional; the image projected on a retina or an imaging device is two-dimensional. That is, reduction of one dimension has occurred. Active illumination techniques compensate for the dimensional reduction by actively controlling the illumination. The demand for reliable vision sensors is rapidly increasing in many application areas, such as robotics and medical image analysis. This book explains this new endeavour to explore the augmentation of reduced dimensions in computer vision. This book consists of three parts: basic concepts, techniques, and applications. The first part explains the basic concepts for understanding active illumination techniques. In particular, the basic concepts of optics are explained so that researchers and engineers outside the field can understand the later chapters. The second part explains currently available active illumination techniques, covering many techniques developed by the authors. The final part shows how such active illumination techniques can be applied to various domains, describing the issue to be overcome by active illumination techniques and the advantages of using these techniques. This book is primarily aimed at 4th year undergraduate and 1st year graduate students, and will also help engineers from fields beyond computer vision to use active illumination techniques. Additionally, the book is suitable as course material for technical seminars.
(source: Nielsen Book Data)

• Designing and Developing Adaptive Instructional Systems.- Sensor-based Adaptive Instructional Systems in Live Simulation Training.- An Ambient & Pervasive Personalized Learning Ecosystem: "Smart Learning" in the Age of the Internet of Things.- Bridging Conceptual Models and Architectural Interchange for Adaptive Instructional Systems.- Dewey's Ethics of Moral Principles and Deliberation: Extending IEEE's Ethics Initiative for Adaptive Instructional Systems.- Realistic and Relevant Role-Players for Experiential Learning.- Learning Traces, Measurement and Assessment Templates for AIS Interoperability.- Supporting different Roles and Responsibilities in Developing and Using Context-based Adaptive Personalized Collaboration Environments Compliant to the Law.- Experiential Instruction of Metacognitive Strategies.- Falling Forward: Lessons Learned from Real-Life Implementation of Adaptive Learning Solutions.- Usability Dimensions of Simulated Trainers for Buried Explosives.- Toward Zero Authoring: Considering How to Maximize Courseware Quality and Affordability Simultaneously.- Agent-Based Methods in Support of Adaptive Instructional Decisions.- Representing Functional Relationships of Adaptive Instructional Systems in a Conceptual Model.- Knowledge-to-Information Translation Training (KITT): An Adaptive Approach to Explainable Artificial Intelligence.- User Rights and Adaptive A/IS - From Passive Interaction to Real Empowerment.- Supporting Metacognitive Learning Strategies through an Adaptive Application.- Towards Iteration by Design: An Interaction Design Concept for Safety Critical Systems.- Learner Modelling and Methods of Adaptation.- Bayesian Student Modelling in the AC&NL Tutor.- Nature at Your Service - Nature Inspired Representations Combined with Eye-gaze Features to Infer User Attention and Provide Contextualized Support.- Adapting Instruction by Measuring Engagement with Machine Learning in Virtual Reality Training.- Realizing the Promise of AI-Powered, Adaptive, Automated, Instant Feedback on Writing for Students in Grade 3-8 with an IEP.- Declarative Knowledge Extraction in the AC&NL Tutor.- On the Importance of Adaptive Operator Training in Human-Swarm Interaction.- The Mental Machine: Classifying Mental Workload State from Unobtrusive Heart Rate- measures Using Machine Learning.- Production Implementation of Recurrent Neural Networks in Adaptive Instructional Systems.- Pilot State Monitoring for Cursus Recommendation.- Experimental Evaluation of Heart-based Workload Measures as Related to Their Suitability for Real-time Applications.- EEG Covariance-based Estimation of Cooperative States in Teammates.- Adapting the Zone of Proximal Development to the Wicked Environments of Professional Practice.- An Adaptive Instructional System for the Retention of Complex Skills.- Learner Modeling in the Context of Caring Assessments.- Evaluating the Effectiveness of Adaptive Instructional Systems.- The Evolving Assessment Landscape and Adaptive Instructional Systems: Moving Beyond Good Intentions.- Contextual Barriers to Validity in Adaptive Instruction and Assessment.- Does Time Matter in Learning? A Computer Simulation of Carroll's Model of Learning.- Competency Development through Experiential Training: Mapping Scenarios with Assessments.- Does Gamification Work? Analyzing Effects of Game Features on Learning in an Adaptive Scenario-Based Trainer.- From "Knowing What" to "Knowing When": Exploring a Concept of Situation Awareness Synchrony for Evaluating SA Dynamics in Teams.- Exploring Video Engagement in an Intelligent Tutoring System.- Using a Non-Player Character to Improve Training Outcomes for Submarine Electronic Warfare Operators.- The Impact of Adaptive Activities in Acrobatiq Courseware: Investigating the Efficacy of Formative Adaptive Activities on Learning Estimates and Summative Assessment Scores.- A Mastery Approach to Flashcard-based Adaptive Training. .
• (source: Nielsen Book Data)

This volume constitutes the refereed proceedings of the Second International Conference on Adaptive Instructional Systems, AIS 2020, which was due to be held in July 2020 as part of HCI International 2020 in Copenhagen, Denmark. The conference was held virtually due to the COVID-19 pandemic. A total of 1439 papers and 238 posters have been accepted for publication in the HCII 2020 proceedings from a total of 6326 submissions. The 41 papers presented in this volume were organized in topical sections as follows: designing and developing adaptive instructional systems; learner modelling and methods of adaptation; evaluating the effectiveness of adaptive instructional systems. Chapter "Exploring Video Engagement in an Intelligent Tutoring System" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
(source: Nielsen Book Data)

• 1st Workshop on Intelligent Data - From Data to Knowledge (DOING 2020).- 2nd Workshop on Modern Approaches in Data Engineering and Information System Design (MADEISD 2020).- 1st Workshop on Scientic Knowledge Graphs (SKG 2020).- 2nd Workshop of BI & Big Data Applications (BBIGAP 2020).- International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2020).- The 1st International Workshop on Assessing Impact and Merit in Science (AIMinScience 2020).- Doctoral Consortium.
• (source: Nielsen Book Data)

This book constitutes thoroughly reviewed and selected papers presented at Workshops and Doctoral Consortium of the 24th East-European Conference on Advances in Databases and Information Systems, ADBIS 2020, the 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, and the 16th Workshop on Business Intelligence and Big Data, EDA 2020, held in August 2020. Due to the COVID-19 the joint conference and satellite events were held online. The 26 full papers and 5 short papers were carefully reviewed and selected from 56 submissions. This volume presents the papers that have been accepted for the following satellite events: Workshop on Intelligent Data - From Data to Knowledge, DOING 2020; Workshop on Modern Approaches in Data Engineering and Information System Design, MADEISD 2020; Workshop on Scientic Knowledge Graphs, SKG 2020; Workshop of BI & Big Data Applications, BBIGAP 2020; International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2020; International Workshop on Assessing Impact and Merit in Science, AIMinScience 2020; Doctoral Consortium.
(source: Nielsen Book Data)

• Exploring Artificial Jabbering For Automatic Text Comprehension Question Generation.- Digital Value-Adding Chains in Vocational Education: Automatic Keyword Extraction from Learning Videos to Provide Learning Resource Recommendations.- Human-centered design of a dashboard on students' revisions during writing.- An operational Framework for Evaluating the Performance of Learning Record Stores.- Does an e-mail reminder intervention with learning analytics reduce procrastination in a blended university course.- Designing an Online Self-Assessment for Informed Study Decisions: The User Perspective.- What Teachers Need for Orchestrating Robotic Classrooms.- Assessing Teacher's Discourse Effect on Students' Learning: A Keyword Centrality Approach.- For learners, with learners: Identifying indicators for an academic advising dashboard for students.- Living with learning difficulties: Two case studies exploring the relationship between emotion and performance in students with learning difficulties.- Learnersourcing Quality Assessment of Explanations for Peer Instruction.- Using Diffusion Network Analytics to Examine and Support Knowledge Construction in CSCL Settings.- Supporting Second Language Learners' Development of Affective Self-Regulated Learning Skills through the Use and Design of Mobile Technology.- We Know What You Did Last Semester: Learners' Perspectives on Screen Recordings as a Long-Term Data Source for Learning Analytics.- Teaching Simulation Literacy with Evacuations: Concept, Technology, and Material for a Novel Approach.- Design of conversational agents for CSCL: comparing two types of agent intervention strategies in a university classroom.- Exploring Human-AI Control over Dynamic Transitions between Individual and Collaborative Learning.- Exploring Student-Controlled Social Comparison.- New Measures for Offline Evaluation of Learning Path Recommenders.- Assessing the Impact of the combination of Self-directed learning, Immediate feedback and Visualizations on Student Engagement in Online Learning.- CGVis: A Visualization-Based Learning Platform for Computational Geometry Algorithms.- How to Design Effective Learning Analytics Indicators? A Human-Centered Design Approach.- Emergency Remote Teaching: Capturing Teacher Experiences in Spain with SELFIE.- Utilising Learnersourcing to Inform Design Loop Adaptivity.- Fooling it - Student Attacks on Automatic Short Answer Grading.- Beyond indicators: A scoping review of the academic literature related to SDG4 and educational technology.- Pedagogical underpinnings of open science, citizen science and open innovation activities: a state-of-the-art analysis.- Knowledge-Driven Wikipedia Article Recommendation for Electronic Textbooks.- InfoBiTS: A mobile application to foster digital competencies of senior citizens.- Student Awareness and Privacy Perception of Learning Analytics in Higher Education.- User Assistance for Serious Games Using Hidden Markov Model.- Guiding Socio-technical Reflection of Ethical Principles in TEL Software Development: The SREP Framework.- Git4School: a Dashboard for Supporting Teacher Interventions in Software Engineering Courses.- Exploring the design and impact of online exercises for teacher training about dynamic models in mathematics.- Interactive Concept Cartoons: Exploring an Instrument for Developing Scientific Literacy.- Quality Evaluation of Open Educational Resources.- Designing Digital Activities to Screen Locomotor Skills in Developing Children.- Towards Adaptive Social Comparison for Education.- Simulation Based Assessment of Epistemological Beliefs about Science.- An Approach to Support Interactive Activities in Live Stream Lectures.- Educational Escape Games for Mixed Reality.- Measuring Learning Progress for serving Immediate Feedback needs: Learning Process Quantification Framework (LPQF).- Data-driven Game Design: The Case of Difficulty in Educational Games.- Extracting Topics from Open Educational Resources.- Supporting Gamification with an Interactive Gamification Analytics Tool (IGAT).- OpenLAIR an Open Learning Analytics Indicator Repository Dashboard.- CasualLearn: A smart application to learn History of Art.- Applying Instructional Design Principles on Augmented Reality Cards for Computer Science Education.- Extending Patient Education with CLAIRE: An Interactive Virtual Reality and Voice User Interface Application.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, held in Heidelberg, Germany, in September 2020. The 24 research papers and 20 demo and 5 poster papers presented in this volume were carefully reviewed and selected from 91 submissions. The European Conference on Technology-Enhance Learning, which celebrates its 15th anniversary this year, is committed to address global challenges and quality education. The papers deal with the Sustainable Development Goals, particularly SDG 4 and SDG 10, to help to reduce the existing gaps and inequalities between countries and regions from around the world in terms of inclusiveness, equity, access, and quality of education. The chapters: "Designing an Online Self-Assessment for Informed Study Decisions: The User Perspective"; "Living with Learning Difficulties: Two Case Studies Exploring the Relationship Between Emotion and Performance in Students With Learning Difficulties"; "Applying Instructional Design Principles on Augmented Reality Cards for Computer Science Education"; and "Teaching Simulation Literacy With Evacuations - Concept, Technology, and Material for a Novel Approach" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. Due to the Corona pandemic EC-TEL 2020 was held as an virtual event.
(source: Nielsen Book Data)

• Robust Functional Regression for Outlier Detection
• Transform Learning Based Function Approximation for Regression and Forecasting
• Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data
• A fully automated periodicity detection in time series
• Conditional Forecasting of Water Level Time Series with RNNs
• Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories
• Localized Random Shapelets
• Feature-Based Gait Pattern Classification for a Robotic Walking Frame
• How to detect novelty in textual data streams? A comparative study of existing methods
• Seq2VAR: multivariate time series representation with relational neural networks and linear autoregressive model
• Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets
• Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems
• Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets using Deep Learning
• Learning Stochastic Dynamical Systems via Bridge Sampling
• Quantifying Quality of Actions Using Wearable Sensor
• An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis.

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data.

• Part I. Artificial Intelligence and Machine Learning
• Part II. Artificial Intelligence User Research
• Part III. Artificial Intelligence Applications
• Part IV. Applications in Software and Systems Engineering
• Part V. Applications in Supply Chain Management and Business
• Part VI. Cognitive Computing and Internet of Things
• Part VII. Human Factors in Energy: Oil, Gas, Nuclear and Electric Power Industries.

This book addresses emerging issues concerning the integration of artificial intelligence systems in our daily lives. It focuses on the cognitive, visual, social and analytical aspects of computing and intelligent technologies, and highlights ways to improve the acceptance, effectiveness, and efficiency of said technologies. Topics such as responsibility, integration and training are discussed throughout. The book also reports on the latest advances in systems engineering, with a focus on societal challenges and next-generation systems and applications for meeting them. Based on the AHFE 2020 Virtual Conference on Software and Systems Engineering, and the AHFE 2020 Virtual Conference on Artificial Intelligence and Social Computing, held on July 16-20, 2020, it provides readers with extensive information on current research and future challenges in these fields, together with practical insights into the development of innovative services for various purposes.
(source: Nielsen Book Data)

This book discusses the latest advances in the development of artificial intelligence systems and their applications in various fields, from medicine and technology to education. It comprises papers presented at the Third International Conference of Artificial Intelligence, Medical Engineering, Education (AIMEE2019), held at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, on 1-3 October 2019. Covering topics such as mathematics and biomathematics; medical approaches; and technological and educational approaches, it is intended for the growing number of specialists and students in this field, as well as other readers interested in discovering where artificial intelligence systems can be applied in the future.

• Natural Language Processing.- Image Processing and Pattern Recognition.- Intelligent Applications and Robotics.
• (source: Nielsen Book Data)

The two-volume set LNAI 12468 and 12469 constitutes the proceedings of the 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, held in Mexico City, Mexico, in October 2020. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 186 submissions. The contributions are organized in topical as follows: Part I: machine and deep learning, evolutionary and metaheuristic algorithms, and soft computing. Part II: natural language processing, image processing and pattern recognition, and intelligent applications and robotics.
(source: Nielsen Book Data)

• Extraction of Tumor Chunk Using Image Segmentation - Thresholding and HSV Color Space.- Predictive & Interactive IOT Diagnosis System with AI and ML Tools: Review.- Multi Agent Data Mining using Asymmetric AES Algorithm in Cloud Computing.- A Novel Architecture for a Two-Pass Opinion Mining Classifier.- QoS based Routing Algorithm for Software Defined Network using Ant Colony optimization.- An Integrated AdaBoost Algorithm for Down Syndrome Disease Recognition.- A Comprehensive Healthcare Model for a Smart Left Ventricle Assisting Device.- Moving Hand Segmentation from H.264 Compressed Sign Language Videos.- CNN-Based Real-time Indian Sign Language Recognition System.- Sarcasm Detection using Multiple Occurrences of Emojis and Hashtagged Words.- Multiclass Multiple Object Tracking.- Dimensionality Reduction in Hyperspectral Images using Auto-encoders.- Improved Registration of Infrared Images using EOH Descriptor.- Fine Grained Analysis of Bridging Social Capital with Triadic Analysis in a Co-Author Network.- Accumulation of Methodologies for Intensifying the Lifetime of the Wireless Sensor Networks.- A Multifactor Biometric Based User Authentication Protocol for IOT Networks.- Leveraging Topic Models with Novel Word Embeddings for Effective Document Clustering.- Survey on Access Control Mechanisms in Cloud Environments.- Sales Analysis and Performance of Super Store using Qlik Geo Analytics.- Assessment of Crop Rotation Using Multi Polarized Sentinel-1 Temporal SAR Data Over Parts of Kumaun Region of Uttarakhand.- Spatiotemporal and Delay Dynamics on a Prey Predator Fishery Model.- An Efficient Intrusion Detection System with Convolutional Neural Network.- Supervised Machine Learning Approach for Identification of Malicious URLs.- A Unified Framework for Stress Forecasting Using Machine Learning Algorithms.- Investigation and Analysis of Crop Maintenance Using IoT & KNN Techniques.- Enhancement of Anisotropic Diffusion Filtered Cardiac MR Images using Contrast based Fuzzy Approach.- Social Media Ecosystem: Review on Social Media Profile's Security and Introduce a New Approach.- An Investigation on Managing Patient Flow at Hospital Emergency Care Unit using Tree-Based Data Mining Techniques.- A Path Based Model for Link Prediction in Location Based Social Networks.- Predicting the Cost of Pre-owned Cars using Linear Regression Mechanisms in Machine Learning.- Bio-Inspired High Utility Item Framework based Particle Swarm Optimization Tree Algorithms for Mining High Utility Itemset.- On Atom-Bond Connectivity Invariant of Graphs.- Theoretical Design and Experimental Study for Urban Data Management using Energy-Saved IoT Big Data.- An Effective Approach for Security Attacks Based on Machine Learning Algorithms.- Class Based Associative Classification using Super Subset to Predict the By-Diseases in Thyroid Disorders.- Recommendation of Diet using Hybrid Collaborative Filtering Learning Methods.- Classification of Natural Images Using Machine Learning Classifiers on Graph Based Approaches.- Convolutional Neural Network Based Diagnosis of Alzheimer's Disease using Time Frequency features.- Humanly Evolving Robotics with Angular Sensor Control (HERASC).- Post-occupancy Evaluation of Building Facilities in a University Community using an Electronic Platform.- Internet of Things: Demystifying Smart Cities & Communities.- Comparative Analysis of Optimizations of Antecedents and Consequents of Fuzzy Inference System Rules Lists using Genetic Algorithm Operations.- Uses and Impact of Social Media on Work Performance of Low Literate People.- A Comparative Analysis on Rumor Microblogs Detection from Social Network Sites.- Smart Sprint Methodology for Financial Management System Development.- A Novel Infrared Image Segmentation Method for Identifying the Faults in the Systems.
• (source: Nielsen Book Data)

This book is a collection of outstanding papers presented at the 1st International Conference on Advances in Computational Intelligence and Informatics (ICACII 2019), organized by the Department of Computer Science & Engineering, Anurag Group of Institutions (AGI), Hyderabad, on 20-21 December 2019. It includes innovative ideas and new research findings in the field of Computational Intelligence and Informatics that will benefit researchers, scientists, technocrats, academics and engineers alike. The areas covered include high-performance systems, data science and analytics, computational intelligence and expert systems, cloud computing, computer networks and emerging technologies.
(source: Nielsen Book Data)

• [I]. Advanced computing: A computer vision based approach for the analysis of acuteness of garbage
• The moderating effect of demographic factors acceptance virtual reality learning in developing countries in the Middle East
• Table tennis forehand and backhand stroke recognition based on neural network
• An effective vision based framework for the identification of tuberculosis in chest X-ray images
• User assisted clustering based key frame extraction
• A threat towards the neonatal mortality
• Digital marketing effectiveness using incrementality
• Explainable artificial intelligence for falls prediction
• Enhanced UML use case meta-model semantics from cognitive and utility perspectives
• The impact of mobile augmented reality design implementation on user engagement
• Intelligent mobile edge computing : a deep learning based approach
• Analysis of clustering algorithms in machine learning for healthcare data
• Securing mobile agents migration using tree parity machine with new tiny encryption algorithm
• An approach to waste segregation and management using convolutional neural networks
• Open source intelligence initiating efficient investigation and reliable web searching
• A neural network based hybrid model for depression detection in Twitter
• Unleashing the VEP tirplet count of virtually created 3D Bangla alphabet to integrate with augmented reality application
• A hybrid machine learning framework for prediction of software effect at the initial phase of software development
• Chronic disease prediction using deep learning
• A deep learning based method to discriminate between photorealistic computer generated images and photographic images
• Load balancing algorithm in cloud computing using mutatino based PSO algorithm
• Statistical model for qualitative grading of milled rice
• Measuring the effectiveness of software code review comments

• Proposed model for feature extraction for vehicle detection
• Analysis of feature selection methods for P2P botnet detection
• ELM-MVD : an extreme learning machine trained model for malware variants detection
• Real-time biometric system for security and surveillance using face recognition
• An effective block-chain based authentication technique for cloud based IoT
• Early detection of autism spectrum disorder in children using supervised machine learning
• Auto segmentation of lung in non-small cell lung cancer using deep convolution neural network
• Multiwavelet based unmanned aerial vehicle thermal image fusion for surveillance and target location
• Investigating movement detection in unedited camera footage
• Time series forecasting using machine learning
• Improving packet queues using selective epidemic routing protocol in opportunistic networks (SERPO)
• Heart disease prediction system using classification algorithms.

• [II]. Data sciences: Graph database and relational database performance comparison on a transportation network
• Optimizing creative allocations in digital marketing
• Big data analytics for customer relationship management : a systematic review and research agenda
• Agricultural field analysis using satellite surface reflectance data and machine learning technique
• Sponsored data connectivity at the network edge
• Dynamic bidding with contextual bid decision trees in digital advertisement
• MOOC performance prediction by deep learning from raw clickstream data
• UDHR : unified decentralized health repository
• Mining massive time series data : with dimensionality reduction techniques
• Comparative analysis of data mining techniques to predict heart disease for diabetic patients.

This book constitutes the post-conference proceedings of the 4th International Conference on Advances in Computing and Data Sciences, ICACDS 2020, held in Valletta, Malta, in April 2020.* The 46 full papers were carefully reviewed and selected from 354 submissions. The papers are centered around topics like advanced computing, data sciences, distributed systems organizing principles, development frameworks and environments, software verification and validation, computational complexity and cryptography, machine learning theory, database theory, probabilistic representations. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Internet of Things, Industry and Blockchain, and Cryptology
• Digital Forensics and Surveillance, Botnet and Malware, and DDoS and Intrusion Detection/Prevention
• Ambient Cloud and Edge Computing, Wireless and Cellular Communication.

This book presents refereed proceedings of the First International Conference on Advances in Cyber Security, ACeS 2019, held in Penang, Malaysia, in July-August 2019. The 25 full papers and 1 short paper were carefully reviewed and selected from 87 submissions. The papers are organized in topical sections on internet of things, industry and blockchain, and cryptology; digital forensics and surveillance, botnet and malware, and DDoS and intrusion detection/prevention; ambient cloud and edge computing, wireless and cellular communication.

• Keynote Extended Abstracts.- Blockchains and Databases: Opportunities and Challenges for the Permissioned and the Permissionless.- Processing Temporal and Time Series Data: Present State and Future Challenges.- Integrating (Very) Heterogeneous Data Sources: a Structured and an Unstructured Perspective.- Data Access and Database Performance.- Upper Bound on the Size of FP-tree.- An Efficient Index for Reachability Queries in Public Transport Networks.- Context-Free Path Querying by Kronecker Product.- Pattern Sampling in Distributed Databases.-Can We Probabilistically Generate Uniformly Distributed Relation Instances Efficiently?.- Machine Learning.- Towards Proximity Graph Auto-Configuration: an Approach Based on Meta-Learning.- Fake News Detection Based on Subjective Opinions.- Improving on Coalitional Prediction Explanation.- Data Processing.- JSON Functionally.- Semantic Web.- Template-Based Multi-Solution for Data-to-Text Generation (on RDF).- Distributed Tree-Pattern Matching in Big Data Analytics Systems.- Data Analytics.- Iterations and Propensity Score Matching in MonetDB.- The Tell-Tale Cube.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 24th European Conference on Advances in Databases and Information Systems, ADBIS 2020, held in Lyon, France, in August 2020.* The 13 full papers presented were carefully reviewed and selected from 82 submissions. The papers cover a wide range of topics from different areas of research in database and information systems technologies and their advanced applications from theoretical foundations to optimizing index structures. They are organized in the following topical sections: keynote extended abstracts; data access and database performance; machine learning; semantic web; data processing; and data analytics. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Symmetric-Key Cryptography 1.- Malicious Activity Detection 1.- Multiparty Computation.- Malicious Activity Detection 2.- Post Quantum Cryptography.- Symmetric-Key Cryptography 2.- Privacy.- Pairing-Based Cryptography.- Machine Learning.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 15th International Workshop on Security, IWSEC 2020, held in Fukui, Japan, in September 2020.* The 15 regular papers and 1 short paper presented in this volume were carefully reviewed and selected from 47 submissions. They were organized in topical sections named: symmetric-key cryptography, malicious activity detection, multiparty computation, post quantum cryptography, privacy, pairing-based cryptography, and machine learning. * The conference was held virtually due to the COVID-19 pandemic.
(source: Nielsen Book Data)

• Childrens Age and Gender Recognition from Raw Speech Waveform using DNN
• Inter-Vehicular Communication in Urban Traffic Scenario
• Distributed Estimation of IIR Systems Parameter in Sensor Network using Multihop Diffusion LMS Algorithm
• Implementation of Raspberry Pi for fault detection in optic fibre line
• Distributed Optical Fiber Sensing System Performance Improvement using Signal Processing Techniques.

This book features high-quality research papers presented at the 2nd International Conference on Intelligent Computing and Advances in Communication (ICAC 2019), held at Siksha 'O Anusandhan Deemed to be University, Bhubaneswar, Odisha, India, in November 2019. Covering a wide variety of topics, including management of clean and smart energy systems and environmental challenges, it is a valuable resource for researchers and practicing engineers working in various fields of renewable energy generation, and clean and smart energy management.

• Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder
• Dual Sequential Variational Autoencoders for Fraud Detection
• A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks
• Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams
• GraphMDL: Graph Pattern Selection Based on Minimum Description Length
• Towards Content Sensitivity Analysis
• Gibbs Sampling Subjectively Interesting Tiles
• Even Faster Exact k-Means Clustering
• Ising-Based Consensus Clustering on Special Purpose Hardware
• Transfer Learning by Learning Projections from Target to Source
• Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs
• Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces
• Vouw: Geometric Pattern Mining Using the MDL Principle
• A Consensus Approach to Improve NMF Document Clustering
• Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams
• Widening for MDL-Based Retail Signature Discovery
• Addressing the Resolution Limit and the Field of View Limit in Community Mining
• Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics
• Adversarial Attacks Hidden in Plain Sight
• Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code
• Overlapping Hierarchical Clustering (OHC)
• Digital Footprints of International Migration on Twitter
• Percolation-Based Detection of Anomalous Subgraphs in Complex Networks
• A Late-Fusion Approach to Community Detection in Attributed Networks
• Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction
• A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization
• Actionable Subgroup Discovery and Urban Farm Optimization
• AVATAR
• Machine Learning Pipeline Evaluation Using Surroga te Model
• Detection of Derivative Discontinuities in Observational Data
• Improving Prediction with Causal Probabilistic Variables
• DO-U-Net for Segmentation and Counting
• Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media
• Event Recognition Based on Classification of Generated Image Captions
• Human-to-AI Coach: Improving Human Inputs to AI Systems
• Aleatoric and Epistemic Uncertainty with Random Forests
• Master your Metrics with Calibration
• Supervised Phrase-Boundary Embeddings
• Predicting Remaining Useful Life with Similarity-Based Priors
• Orometric Methods in Bounded Metric Data
• Interpretable Neuron Structuring with Graph Spectral Regularization
• Comparing the Preservation of Network Properties by Graph Embeddings
• Making Learners (More) Monotone
• Combining Machine Learning and Simulation to a Hybrid Modelling Approach
• LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification
• Angle-Based Crowding Degree Estimation for Many-Objective Optimization.

This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDAs mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

• Six Sigma Methodology and Implementation in Indian Context: A Review Based Study.- Evaluation of work posture using ergonomics in Indian small scale industry.- Manufacturing Intelligence in the Context of Indian SME's.- Multi-objective optimization of process parameter during dry Turning of Grade5 Titanium alloy with carbide inserts: Hybrid Fuzzy-TOPSIS approach.- Analysis of Factors for Green Supply Chain in Indian Timber Market: An ISM Approach.- The Value Engineering Way: A Case of Industrial Fans.- Obstacles of Flexible Manufacturing System: An AHP Approach for Quantifying the Rank Given by the ISM Model.- To Find the Effectiveness of Barriers in Reverse Logistics by using ISM.- Optimization of MQL Machining Parameters Using Combined Taguchi and TOPSIS Method.- Life Cycle Assessment Framework for Sustainable Development in Manufacturing Environment.- Artificial Neural Network Models for the Prediction of Metal Removal Rate in Rotary Ultrasonic Machining.- Finding the Percentage Effectiveness of Agile Manufacturing Barriers: An AHP Approach.- Modeling the Knowledge Sharing Barriers in Indian Small and Medium Industries using ISM.- Simulation and Optimization of Flexible Flow Shop Scheduling Problem in an Indian Manufacturing Industry.- Computational Investigation on the Thermal Characteristics of Heat Pipe Using Nanofluids.- Analysis of Barriers to Lean-Green Manufacturing System (Lgms): A Multi-Criteria Decision Making Approach.- Machine Learning Application for Pulsating Flow Through.- Ranking of Factors for Integrated Lean, Green and Agile Manufacturing for Indian Manufacturing Sme's.
• (source: Nielsen Book Data)

This book consists of select proceedings of the International Conference on Functional Material, Manufacturing and Performances (ICFMMP) 2019, and presents latest research on using the combined intelligence of people, processes, and machines to impact the overall economics of manufacturing. The book focuses on optimizing manufacturing resources, improving business value and safety, and reducing waste - both on the floor and in back-office operations. It highlights the applications of the latest manufacturing execution system (MES), intelligent devices, machine-to-machine communication, and data analysis for the production lines and facilities. This book will be useful to manufacturers of finished goods and of sub-assemblies in the automotive, agriculture, and construction equipment sector. It will also provide solutions to make production strategies exceptional and can be a useful reference for beginners, researchers, and professionals interested in intelligent manufacturing technologies.
(source: Nielsen Book Data)

• Gerlach Shaping based Air Intake Duct Optimisation.- Multidisciplinary Analysis of a Re-entry Vehicle.- Optimization of multiple gravity assist trajectory with deep space maneuver using evolutionary algorithm.- Conceptual Design Optimization of High Altitude Airships having a Tri-lobed Envelope.- Multiobjective Aerodynamic Optimization of a Hypersonic Scramjet Inlet.- Study of Wing Flutter at Preliminary Stages of Design.- Coupled Aero-structural Simulation Techniques using High-fidelity Analysis and Design Tools.- Optimization Of B-Spline Launch Vehicle Payload Fairing.- Design of Vortex Flaps for Reducing Approach Speed of a Supersonic Naval Fighter Aircraft.-Performance comparison of discrete Kalman filter and dynamic programming methods for pavement roughness identification.- Multi-Disciplinary Optimization of Sensor Bracket.
• (source: Nielsen Book Data)

This volume contains select papers presented during the 2nd National Conference on Multidisciplinary Analysis and Optimization. It discusses new developments at the core of optimization methods and its application in multiple applications. The papers showcase fundamental problems and applications which include domains such as aerospace, automotive and industrial sectors. The variety of topics and diversity of insights presented in the general field of optimization and its use in design for different applications will be of interest to researchers in academia or industry.
(source: Nielsen Book Data)

• 1. A Comprehensive Introduction to Photometric 3D-Reconstruction.-
• 2. Perspective Shape from Shading an Exposition on Recent Works with New Experiments.-
• 3. RGBD-Fusion: Depth Refinement for Diffuse and Specular Objects.-
• 4. Non-Rigid Structure from Motion and Shading.-
• 5. On the Well-Posedness of Uncalibrated Photometric Stereo Under General Lighting.-
• 6. Recent Progress in Shape from Polarization.-
• 7. Estimating Facial Aging using Light Scattering Photometry.
• (source: Nielsen Book Data)

This book presents the latest advances in photometric 3D reconstruction. It provides the reader with an overview of the state of the art in the field, and of the latest research into both the theoretical foundations of photometric 3D reconstruction and its practical application in several fields (including security, medicine, cultural heritage and archiving, and engineering). These techniques play a crucial role within such emerging technologies as 3D printing, since they permit the direct conversion of an image into a solid object. The book covers both theoretical analysis and real-world applications, highlighting the importance of deepening interdisciplinary skills, and as such will be of interest to both academic researchers and practitioners from the computer vision and mathematical 3D modeling communities, as well as engineers involved in 3D printing. No prior background is required beyond a general knowledge of classical computer vision models, numerical methods for optimization, and partial differential equations. .
(source: Nielsen Book Data)

• Regular Papers.- An Interruptible Task Allocation Model : Application to a Honey Bee Colony Simulation.- RT-BDI: A Real-Time BDI Model.- Routing Model Evaluator.- The DigForSim Agent Based Simulator of People Movements in Crime Scenes.- Personal Data Privacy Semantics in Multi-Agent Systems Interactions.- Towards Real-time Crowd Simulation Under Uncertainty Using an Agent-Based Model and an Unscented Kalman Filter.- The JaCa-Android Framework for Programming BDI-based Personal Agents on Mobile Devices.- Assisted Parameter and Behavior Calibration in Agent-based Models with Distributed Optimization.- Fast and Efficient Partner Selection in Large Agents' Communities: When Categories Overcome Direct Experience.- Multi-Agent Modelling and Simulation of Hospital Acquired Infection Propagation Dynamics by Contact Transmission in Hospital Wards.- Unsupervised Sleep Stages Classification Based On Physiological Signals.- Recommending Learning Videos for MOOCs and Flipped Classrooms.- Improving Sustainable Mobility with a Variable Incentive Model for Bike-Sharing Systems Based on Agent-based Social Simulation.- Decentralized Constraint Optimization in Composite Observation Task Allocation to Mobile Sensor Agents.- Comparing the Performance of Message Delivery Methods for Mobile Agents.- Application of Agent-based Modelling to Simulate Ribosome Translation.- Intent Recognition from Speech and Plan Recognition.- Planner-Guided Robot Swarms.- A MAS-based Approach for POI Group Recommendation in LBSN.- Agent Programmability Enhancement for Rambling over a Scientific Dataset.- Scalable Heterogeneous Multiagent Learning from Demonstration.- Multimodal Joke Generation and Paralinguistic Personalization for a Socially-Aware Robot.- A Framework for Verifying Autonomous Robotic Agents Against Environment Assumptions.- Impact of Trust and Reputation Based Brokerage on the CloudAnchor Platform.- Formal Verification of Autonomous UAV Behavior for Inspection Tasks Using the Knowledge Base System IDP.- Pattern-Based Goal-Oriented Development of Fault-Tolerant MAS in Event-B.- A Study on Automated Receptionists in a Real-world Scenario.- Navigation of Autonomous Swarm of Drones using Translational Coordinates.- Multi-agent Service Area Adaptation for Ride-Sharing Using Deep Reinforcement Learning.- Demo Papers.- MAXIM-GPRT: A Simulator of Local Schedulers, Negotiations, and Communication for Multi-Agent Systems in General-Purpose and Real-Time Scenarios.- Assisting Users on the Privacy Decision-Making Process in an OSN for Educational Purposes.- A Demonstration of the Routing Model Evaluator.- JADE/JaCaMo+2COMM: Programming Agent Interactions.- Agent-based Mixed Reality Environments in Healthcare: the Smart Shock Room Project.- Demo Paper: Monitoring and Evaluation of Ethical Behavior in Dialog Systems.- A Multi-Agent Simulator for Infection Spread in a Healthcare Environment.- SafeCity: A Platform for Safer and Smarter Cities.- AGADE Traffic 2.0 - A Knowledge-based Approach for Multi-agent Traffic Simulations.- PoVaBiA: a Multi-agent Decision-making Support Tool for Organic Waste Management.- Dedale : Demonstrating a Realistic Testbed for Decentralized Multi-agents Problems.- Agent-based Crowd Discussion Support System and its Societal Experiments.- Disaster Response Simulation.- Understandable Teams of Pepper Robots.- A Practical Demonstration of a Variable Incentive Model for Bike-sharing Systems Based on Agent-based Social Simulation.- Implementation of a Holonic Multi-agent System in Mixed or Augmented Reality for Large Scale Interactions.- A Multi-agent Evaluation of Traffic Light Models.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020, held in L'Aquila, Italy, in October 2020. The 29 regular and 17 demo papers presented in this volume were carefully reviewed and selected from 64 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, educa-tion and social interactions, formal and theoretic models, health and safety, mobility and the city, swarms and task allocation.
(source: Nielsen Book Data)

• Advanced Modelling, Simulation and Data Analytics in Production and Supply Networks.- A Robust Multi-Commodity Rebalancing Process in Humanitarian Logistics.- Towards a unified reliability-centered information logistics model for production assets.- Characterization of energy consumers in production systems with renewable on-site power generation.- A simulation model supporting the production optimization for high-precision machines assembly.- Agent-Based Modeling and Analysis of Dynamic Slab Yard Management in a Steel Factory.- A Simulation Analysis of Part Feeding to Assembly Stations with Vertical Robotic Storage and Retrieval.- Process Mining in Manufacturing: Goals, Techniques and Applications.- Bayesian Modelling for Product Testing and Release.- Advanced, Digital and Smart Manufacturing.- The Use of Organizational Innovation Concepts in Manufacturing Companies.- Systems Engineering Approach to Identify Requirements for Digital Twins Development.- Manufacturing Operations Management for Smart Manufacturing - A Case Study.- Industry 4.0 on demand: a value driven methodology to implement Industry 4.0.- Gamification of Operational Tasks in Manufacturing - A Literature Review.- Technology Adoption in the Industry 4.0 Era: Empirical Evidence from Manufacturing Companies.- Towards the definition of an Impact Level factor of SME features over Digital Transformation.- Industry 4
• .0: maturity of automotive companies in Brazil for the digitization of processes.- General readiness assessment of Industry 4
• .0: Evidence from Serbian manufacturing industry.- Digital and Virtual Quality Management Systems.- Assembly issue resolution system using machine learning in aero engine manufacturing.- Introduction to Material Feeding 4
• .0: strategic, tactical, and operational impact.- Cloud-Manufacturing.- Cycle Time Estimation Model for Hybrid Assembly Stations based on Digital Twin Concept.- Cyber-Physical Production Systems and Digital Twins.- Digital Shadows as an enabler for the internet of production.- The transformation towards smart(er) factories: integration requirements of the digital twin.- IIOT Interoperability.- Towards inter-operable enterprise systems - graph-based validation of a context-driven approach for message profiling.- Supply Chain Planning and Optimization.- Software-based Assistance System for Decision Support on Supply Chain Level.- Integration of triple sustainable management by considering multi-period supply chain for next-generation fuel.- Potential benefits of Reverse Blending in the fertilizer industry.- Effectiveness of Vendor Managed Inventory [VMI] in Explosive Inventory Management.- Value chain integration - a framework for assessment.- A dynamic hybrid Berth Allocation Problem with routing constraints in bulk ports.- Blockchain-based secured collaborative model for supply chain resource sharing and visibility.- Gripper types and components in robotic bin picking.- A stochastic model for a two-level disassembly lot-sizing problem under random lead time.- Digital and Smart Supply Chain Management.- ERP in Industry 4.0 Context.- Identifying the opportunities for enhancing the digital readiness level of the supply chain.- Intelligent Logistics Networks Management.- The Role of Last-Mile Delivery in the Future of E-commerce.- Production-storage and transport integratedplanning for a multi-site mining industry.- Artificial Intelligence and Blockchain Technologies in Logistics and DSN.- Evaluating a Blockchain-based supply chain purchasing process through simulation.- Questionnaire model for paraconsistent quality assessment of software developed in Sales Force.- Novel Production Planning & Control Approaches.- Supporting the Decision of the Order Processing Strategy by using Logistic Models: A Case Study.- Order acceptance and scheduling with a throughput diagram.- Machine Learning and Artificial Intelligence.- Machine Learning-Supported Planning of Lead Times in Job Shop Manufacturing.- Connected, Smart Factories of the Future.- Identifying Key Business Processes that Can Benefit from Industry 4.0 in the Gas Sector, The Public Gas Distribution Networks Case in Greece.- The impact of Industry 4.0 connectivity on the collaboration along Brazilian automotive supply chain.- Manufacturing Systems Engineering: Agile, Flexible, Reconfigurable.- Towards a reference model for configuration of reconfigurable manufacturing system (RMS).- Automatic Design of Dispatching Rules with Genetic Programming for Dynamic Job Shop Scheduling.- A Literature review on the Level of Automation and new approach proposal.- De-risking investments in industrial systems using Real Options Analysis: Case of chemical industry.- Data-driven Replenishment Method Choice in a Picking System.- Business Process Management for Manufacturing Execution System deployment: some lessons from a bearings manufacturer experience.- An Application of a DSML in Industry 4.0 Production Processes.- Towards an Industry-Applicable Design Methodology for Developing Reconfigurable Manufacturing.- Reconfigurable Manufacturing: Lesson Learnt from the COVID-19 Outbreak.- Digital Assistance Systems: Augmented Reality and Virtual Reality.- Virtual and Augmented reality as a digital support to HR systems in production management.- Application of Virtual Reality Technologies for Achieving Energy Efficient Manufacturing: Literature Analysis and Findings.- Smart Products in Smart Manufacturing Systems: An Opportunity to Utilize AR?.- Evaluation of Augmented Reality in Industry.- Circular Products Design and Engineering.- Finding and Capturing Value in e-Waste for Refrigerators Manufacturers and Recyclers.- Circular, Green, Sustainable Manufacturing.- Sustainable Business Model Innovation in Furniture Supply Chain: A Case Study.- A basic study on scheduling method for electric power saving of production machine.- Sustainability in fabric chains and garments for a circular economy.- Planning environments of hospital laboratories: An exploratory study.- Knowledge and practices towards sustainability and circular economy transitions: A Norwegian manufacturing perspective.- A methodology to integrate sustainability evaluations into vendor rating.- Environmental and Social Lifecycle Assessments.- Travel-Times Analysis and Passenger Transport Disutilities in Congested American Cities: Los Angeles, New York, Atlanta, Austin, and Chicago.- Socio-Cultural Aspects in Production Systems.- The interdependencies of Quality Management, Knowledge Management and Innovation Performance. A literature review.- Insights from a top-down lean subprogram deployment in a corporate group: The use of deployment tactics.- Tools for Evaluating Human Factor Aspects in Production and Logistics System.- Economy and its symbiosis with Circularity.- Data-driven Manufacturing and Services Operations Management.- First Steps to the Digital Shadow of Maintenance Services' Value Contribution.- Reshoring of service operations: evidence from a Delphi study.- Digital and physical testbed for production logistics operations.- Principles and Research Agenda for Sustainable, Data-Driven Food Production Planning and Control.- Product-Service Systems in DSN.- Agile guideline for development of smart services in manufacturing enterprises with support of artificial intelligence.- Collaborative Design and Engineering.- Framework for identifying gripper requirements for collaborative applications in manufacturing.- A novel value driven co-creation framework.- Autonomous mobile robots in hospital logistics.- Interorganizational learning in manufacturing industry.
• (source: Nielsen Book Data)

The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020.The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product.
(source: Nielsen Book Data)

• The Operator 4
• .0: New Physical and Cognitive Evolutionary Paths.- Facilitating Operator Participation in Continuous Improvement: An Investigation of Organizational Factors.- Improving the Safety of Using Didactic Setups by Augmented Reality.- Production Management as-a-Service: A Softbot Approach.- Knowledge Strategies for Organisation 4.0.- Challenges for the Operator 3.0 Addressed Through the Enabling Technologies of the Operator 4.0.- Agent- and Skill-based Process Interoperability for Socio-Technical Production Systems-of-Systems.- Digital Transformation Approaches in Production Management.- Challenges in Data Life Cycle Management for Sustainable Cyber-Physical Production Systems.- Explainable AI in Manufacturing: A Predictive Maintenance Case Study.- Retrofit Concept for Textile Production.- Organizational enablers for digitalization in manufacturing industry.- Concept of PLM application integration with VR and AR techniques.- The big potential of Big Data in manufacturing: evidence from emerging economies.- A conceptual model for deploying digitalization in SMEs through capability building.- The Potential of Game Development Platforms for Digital Twins and Virtual Labs: Case Study of an Energy.- The Application of ICT Software Solutions in Manufacturing Sector in Serbia.- Achieving Business Model Innovation with the Personalized Product Business Model Radar Template.- Integrating electronic components into 3D printed parts to develop a digital manufacturing approach.- Digital transformation and its potential effects on future management: Insights from an ETO context.- Applying contextualization for data-driven transformation in manufacturing.- Digital Transformation for more Sustainable Supply Chains.- Smart contract-based blockchain solution to reduce supply chain risks.- Towards sustainability: The manufacturers' perspective.- Data-Driven Applications in Smart Manufacturing and Logistics Systems.- Smart Factory Competitiveness based on real time Monitoring and Quality predictive model applied to multi-stages Production lines.- A New Application of Coordination Contracts for Supplier Selection in a Cloud Environment.- Workforce Assignment with a Different Skill Level for Automotive Parts Assembly Lines.- A framework of data-driven dynamic optimisation for smart production logistics.- Decentralized Industrial IoT Data Management Based on Blockchain and IPFS.- Integrated Platform and Digital Twin Application for Global Automotive Part Suppliers.- Analyzing the Characteristics of Digital Twin and Discrete Event Simulation in Cyber Physical Systems.- Streaming Analytics in Edge-Cloud Environment for Logistics Processes.- An Improvement in Master Surgical Scheduling using Artificial Neural Network and Fuzzy Programming.- SKOS Tool: A Tool for Creating Knowledge Graphs to Support Semantic Text Classification.- Data-Driven Services: Characteristics, Trends and Applications.- The successful commercialization of a digital twin in an industrial product service system.- Using Service Dominant logic to assess the value co-creation of Smart Services.- Engineering of data-driven Service Systems for Smart Living: Application and Challenges.- The role of service business models in the manufacturing of transition economies.- System architecture analysis with network index in MBSE approach -Application to smart interactive service with digital health modeling.- The Data-Driven Product-Service Systems Design and Delivery (4DPSS) methodology.- Data-driven maintenance delivery framework: test in an Italian company.- Towards a Comparative Data Value Assessment Framework for Smart Product Service Systems.- Impact of platform openness on ecosystems and value streams in Platform-based PSS exemplified using RAMI 4.0.- Industry 4.0 data-related technologies and servitization: a systematic literature review.- A framework to support value co-creation in PSS development.- The Future of Lean Thinking and Practice.- Utilizing Lean Thinking as a Means to Digital Transformation in Service Organizations.- On the Need of Functional Priority and Failure Risk Assessment to Optimize Human Resource Allocation in Public Service Organizations.- Assessing the Value of Process Improvement Suggestions.- On the Necessity for Identifying Waste in Knowledge Work Dominated Projects: A Case Study from Oil and Gas-Related Product Development Projects.- Lean Thinking: from the shop floor to an organizational culture.- Digital Lean Manufacturing and its Emerging Practices.- A Learning Roadmap for Digital Lean Manufacturing.- Investigating the Challenges and Opportunities for Production Planning and Control in Digital Lean Manufacturing.- New Forms of Gemba Walks and their Digital Tools in the Digital Lean Manufacturing World.- New Reconfigurable, Flexible or Agile Production Systems in the Era of Industry 4.0.- A computational method for identifying the optimum buffer size in the era of Zero Defect Manufacturing.- A Bi-objective Scheduling Model for Additive Manufacturing with Multiple Materials and Sequence-dependent Setup Time.- Dynamic Distributed Job-Shop Scheduling Problem Consisting of Reconfigurable Machine Tools.- Towards a Non-Disruptive System for Dynamic Orchestration of the Shop Floor.- Assembly process design: performance evaluation under ergonomics consideration using several robot collaboration modes.- A Method of Distributed Production Management for Highly-Distributed Flexible Job Shops.- A Digital Twin modular framework for Reconfigurable Manufacturing Systems.- Reconfigurable Digitalized and Servitized Production Systems: Requirements and Challenges.- The impact of dynamic tasks assignment in paced mixed-model assembly line with moving workers.- Balancing and configuration planning of RMS to minimize energy cost.- Operations Management in Engineer-to-Order Manufacturing.- Factors affecting shipyard operations and logistics: A framework and comparison of shipbuilding approaches.- Using the Smartphone as an Augmented Reality Device in ETO Industry.- Exploring the Path Towards Construction 4
• .0: Collaborative Networks & Enterprise Architecture Views.- The Potential for Purchasing function to Enhance Circular Economy Business Models for ETO production.- Planning procurement activities in ETO projects.- Maturity model for successful cost transformation in ETO companies.- Backlog Oriented Bottleneck Management - Practical Guide for Production Managers.- Cross-functional coordination before and after the CODP: an empirical study in the machinery industry.- Production Management in Food Supply Chains.- Food Bank: A Proposal for Short Agri-Food Chains.- The New Frontiers in World Soybean Production: An Analysis of Savanna in Piaui, Brazil.- Prediction of cold chain transport conditions using data mining.- Environmental impact classification of perishable on-road transport using data mining.- Economic and Environmental Perfomance in Coffee Supply Chains: A Brazilian Case Study.- Managing Perishable Multi-Product Inventory with Supplier Fill-Rate, Price Reduction and Substitution.- Digital Technology Enablers for Resilient and Customer Driven Food Value Chains.- Gastronomic Service System Design.- Human-Robot Hybrid Service System Introduction for Enhancing Labor and Robot Productivity.- Forecasting Customers Visiting using Machine Learning and Characteristics Analysis with Low Forecasting Accuracy Days.- A study on menu planning method for managed meal -Consideration of the cost of ordering ingredients.- Service system design considering employee satisfaction.- Product and Asset Life Cycle Management in the Circular Economy.- Exploring synergies between Circular Economy and Asset Management.- Information flows supporting Circular Economy adoption in the manufacturing sector.- A conceptual model of the IT ecosystem for Asset Management in the global manufacturing context.- Production Ramp-up Strategies for Product.- Part Selection for Freeform Injection Molding: framework for development of a unique methodology.- A Model for Cost-Benefit Analysis of Production Ramp-up Strategies.- Key factors on utilizing the production system design phase for increasing operational performance.- Business Model Development for a Dynamic Production Network Platform.- Changeable Closed-Loop Manufacturing Systems: A Case Study of Challenges in Product Take-Back.
• (source: Nielsen Book Data)

The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020. The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product.
(source: Nielsen Book Data)

• Image Processing for Practical Applications.- New Methods of Forming and Measurement of Sub-pixel Shift of Digital Images.- The Characteristics of the Phase-energy Image Spectrum.- Detectors Fields.- Comparative Evaluation of Algorithms for Trajectory Filtering.
• (source: Nielsen Book Data)

This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. The book is directed to the Ph.D. students, professors, researchers, and software developers working in the areas of digital video processing and computer vision technologies.
(source: Nielsen Book Data)

• Introduction.- Related Work.- Intelligent, Adaptive and social e-learning in POLYGLOT. .
• (source: Nielsen Book Data)

This book discusses three important, hot research issues: social networking-based learning, machine learning-based user modeling and sentiment analysis. Although these three technologies have been widely used by researchers around the globe by academic disciplines and by R&D departments in the IT industry, they have not yet been used extensively for the purposes of education. The authors present a novel approach that uses adaptive hypermedia in e-learning models to personalize educational content and learning resources based on the needs and preferences of individual learners. According to reports, in 2018 the vast majority of internet users worldwide are active on social networks, and the global average social network penetration rate as of 2018 is close to half the population. Employing social networking technologies in the field of education allows the latest technological advances to be used to create interactive educational environments where students can learn, collaborate with peers and communicate with tutors while benefiting from a social and pedagogical structure similar to a real class. The book first discusses in detail the current trend of social networking-based learning. It then provides a novel framework that moves further away from digital learning technologies while incorporating a wide range of recent advances to provide solutions to future challenges. This approach incorporates machine learning to the student-modeling component, which also uses conceptual frameworks and pedagogical theories in order to further promote individualization and adaptivity in e-learning environments. Moreover, it examines error diagnosis, misconceptions, tailored testing and collaboration between students are examined and proposes new approaches for these modules. Sentiment analysis is also incorporated into the general framework, supporting personalized learning by considering the user's emotional state, and creating a user-friendly learning environment tailored to students' needs. Support for students, in the form of motivation, completes the framework. This book helps researchers in the field of knowledge-based software engineering to build more sophisticated personalized educational software, while retaining a high level of adaptivity and user-friendliness within human-computer interactions. Furthermore, it is a valuable resource for educators and software developers designing and implementing intelligent tutoring systems and adaptive educational hypermedia systems. .
(source: Nielsen Book Data)

• Machine and Deep Learning.- Evolutionary and Metaheuristic Algorithms.- Soft Computing. .
• (source: Nielsen Book Data)

The two-volume set LNAI 12468 and 12469 constitutes the proceedings of the 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, held in Mexico City, Mexico, in October 2020. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 186 submissions. The contributions are organized in topical as follows: Part I: machine and deep learning, evolutionary and metaheuristic algorithms, and soft computing. Part II: natural language processing, image processing and pattern recognition, and intelligent applications and robotics.
(source: Nielsen Book Data)

• 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.
• (source: Nielsen Book Data)

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. .
• (source: Nielsen Book Data)

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. .
(source: Nielsen Book Data)

• Design and Development.- Second Screen and Crossmedia.- Interaction Techniques and Technologies.- Accessibility.- User Experience.
• (source: Nielsen Book Data)

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.
• (source: Nielsen Book Data)

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. .
(source: Nielsen Book Data)

• 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.
• (source: Nielsen Book Data)

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.
• (source: Nielsen Book Data)

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.
(source: Nielsen Book Data)

• 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.
• (source: Nielsen Book Data)

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.
(source: Nielsen Book Data)

• 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. .
(source: Nielsen Book Data)

• 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.
• (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)

• 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)

• 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)