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• 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.
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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.
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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)

• 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 .
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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.
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• 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.
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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)

• 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.
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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.
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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.
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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.
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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.
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• 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.
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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)

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

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

• 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.
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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)

• 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)

• 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.
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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)

• 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)

• [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.
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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.
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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)

• 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.
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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)