Electronic Government
Chapters 6, 24, 26 and 36 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Computational Geometry with Independent and Dependent Uncertainties
This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.
Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence
This book constitutes the thoroughly refereed proceedings of the 35th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2022, held in Kitakyushu, Japan, in July 2022. The 67 full papers and 11 short papers presented were carefully reviewed and selected from 127 submissions. The IEA/AIE 2022 conference focuses on focuses on applications of applied intelligent systems to solve real-life problems in all areas including business and finance, science, engineering, industry, cyberspace, bioinformatics, automation, robotics, medicine and biomedicine, and human-machine interactions.
The Nature of Complex Networks
The Nature of Complex Networks provides a systematic introduction to the statistical mechanics of complex networks and the different theoretical achievements in the field that are now finding strands in common. The book presents a wide range of networks and the processes taking place on them, including recently developed directions, methods, and techniques. It assumes a statistical mechanics view of random networks based on the concept of statistical ensembles but also features the approaches and methods of modern random graph theory and their overlaps with statistical physics. This book will appeal to graduate students and researchers in the fields of statistical physics, complex systems, graph theory, applied mathematics, and theoretical epidemiology.
Universal Access in Human-Computer Interaction. Novel Design Approaches and Technologies
This two-volume set constitutes the refereed proceedings of the 16th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2022, held as part of the 24th International Conference, HCI International 2022, held as a virtual event, in June-July 2022. A total of 1271 papers and 275 posters included in the 39 HCII 2022 proceedings volumes. UAHCI 2022 includes a total of 73 papers; they focus on topics related to universal access methods, techniques and practices, studies on accessibility, design for all, usability, UX and technology acceptance, emotion and behavior recognition for universal access, accessible media, access to learning and education, as well universal access to virtual and intelligent assistive environments.
Outstanding User Interfaces with Shiny
Outstanding User Interfaces with Shiny provides the reader with necessary knowledge to develop beautiful and highly interactive user interfaces. It gives the minimum requirements in HTML/JavaScript and CSS to be able to extend already existing Shiny layouts or develop new templates from scratch. Suitable for anyone with some experience of Shiny, package development and software engineering best practices, this book is an ideal guide for graduates and professionals who wish to bring their app design to the next level. Key Features: Provides a survival kit in web development to seamlessly get started with HTML/CSS/JavaScript Leverage CSS and Sass and higher-level tools like {bslib} to substantially enhance the design of your app in no time A comprehensive guide to the {htmltools} package to seamlessly customize existing layouts Describes in detail how Shiny inputs work and how R and JavaScript communicate Details all the necessary steps to create a production-grade custom template from scratch: packaging, shiny tags creation, validating and testing R components and JavaScript Expose common web development debugging technics Provides a list of existing templates, resources to get started and to explore
Computational Social Science
Selected papers from the International Conference on New Computational Social Science, focusing on the following five aspects: Big data acquisition and analysis, Integration of qualitative research and quantitative research, Sociological Internet experiment research, Application of ABM simulation method in Sociology Research, Research and development of new social computing tools. With the rapid development of information technology, especially sweeping progress in the Internet of things, cloud computing, social networks, social media and big data, social computing, as a data-intensive science, is an emerging field that leverages the capacity to collect and analyze data with an unprecedented breadth, depth and scale. It represents a new computing paradigm and an interdisciplinary field of research and application. A broad comprehension of major topics involved in social computing is important for both scholars and practitioners. This proceedings presents and discusses key concepts and analyzes the state-of-the-art of the field. The conference not only gave insights on social computing, but also affords conduit for future research in the field. Social computing has two distinct trends: One is on the social science issues, such as computational social science, computational sociology, social network analysis, etc; The other is on the use of computational techniques. Finally some new challenges ahead are summarized, including interdisciplinary cooperation and training, big data sharing for scientific data mashups, and privacy protect.
Explainable and Transparent AI and Multi-Agent Systems
This book constitutes the refereed proceedings of the 4th International Workshop on Explainable and Transparent AI and Multi-Agent Systems, EXTRAAMAS 2022, held virtually during May 9-10, 2022. The 14 full papers included in this book were carefully reviewed and selected from 25 submissions. They were organized in topical sections as follows: explainable machine learning; explainable neuro-symbolic AI; explainable agents; XAI measures and metrics; and AI & law.
Hybrid Artificial Intelligent Systems
This book constitutes the refereed proceedings of the 17th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2022, held in Salamanca, Spain, in September 2022.The 43 full papers presented in this book were carefully reviewed and selected from 67 submissions. They were organized in topical sections as follows: bioinformatics; data mining and decision support systems; deep learning; evolutionary computation; HAIS applications; image and speech signal processing; and optimization techniques.
SharePoint Architect’s Planning Guide
A practical handbook with proven recommendations and design considerations for creating elegant SharePoint solutions and integrating with other collaboration tools to build value for your organizationKey Features: Learn how to structure sites, pages, and data with effective metadataUnderstand the modernization of SharePoint over time and discover ways to leverage its out-of-the-box featuresFit all the pieces together across cloud tools like Teams, OneDrive, Planner, and FormsBook Description: After opening a toolbox full of tools, it can initially be hard to know which is the right one for the job - which tool works best and when. Showing you how to create an informed and purposeful plan for SharePoint Online in the context of the Microsoft 365 suite of tools is what this book is all about.SharePoint Architect's Planning Guide will help you understand all you can do with SharePoint. Whether the tools are new to you or you've used the older versions in the past, your journey will start by learning about the building blocks. This book is not a step-by-step guide; there are tons of online resources to give you that and to help you better keep up with the pace of change. This book is a planning guide, helping you with the context, capabilities, and considerations for implementing SharePoint Online in the most successful way possible. Whether you need to plan a new intranet, migrate files to a modern platform, or take advantage of tools such as Power Platform, Teams, and Planner, this guide will help you get to grips with the technology, ask the right questions to build your plan, and successfully implement it from the technical and user adoption perspectives.By the end of this Microsoft book, you'll be able to perceive the toolbox as a whole and efficiently prepare a planning and governance document for use in your organization.What You Will Learn: Find out how to build or migrate to an effective modern intranetExplore how SharePoint works with other Microsoft 365 toolsDiscover best practices for extending SharePointUnderstand the ways to implement effective metadataPlan for successful adoption and change managementExplore best practices for site and data architectureWho this book is for: This book is for any IT professional looking for an all-encompassing view of the collaboration tools in Microsoft 365 to plan for successful SharePoint adoption. This book will benefit long-time SharePoint on-premises administrators making a leap to the cloud, as well as IT architects with experience in other areas who've never worked with SharePoint.
Diagrammatic Representation and Inference
This book constitutes the refereed proceedings of the 13th International Conference on the Theory and Application of Diagrams, Diagrams 2022, held in Rome, Italy, in September 2022. The 11 full papers and 19 short papers presented together with 5 posters were carefully reviewed and selected from 58 submissions. 8 chapters are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Adversarial Robustness for Machine Learning
Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on adversarial attack, defense and verification. Sections cover adversarial attack, verification and defense, mainly focusing on image classification applications which are the standard benchmark considered in the adversarial robustness community. Other sections discuss adversarial examples beyond image classification, other threat models beyond testing time attack, and applications on adversarial robustness. For researchers, this book provides a thorough literature review that summarizes latest progress in the area, which can be a good reference for conducting future research. In addition, the book can also be used as a textbook for graduate courses on adversarial robustness or trustworthy machine learning. While machine learning (ML) algorithms have achieved remarkable performance in many applications, recent studies have demonstrated their lack of robustness against adversarial disturbance. The lack of robustness brings security concerns in ML models for real applications such as self-driving cars, robotics controls and healthcare systems.
Machine Learning
1 Introduction.- 2 Model Selection and Evaluation.- 3 Linear Models.- 4 Decision Trees.- 5 Neural Networks.- 6 Support Vector Machine.- 7 Bayes Classifiers.- 8 Ensemble Learning.- 9 Clustering.- 10 Dimensionality Reduction and Metric Learning.- 11 Feature Selection and Sparse Learning.- 12 Computational Learning Theory.- 13 Semi-Supervised Learning.- 14 Probabilistic Graphical Models.- 15 Rule Learning.- 16 Reinforcement Learning.
Fundamentals of Artificial Intelligence
This book is for K12 students who want to learn AI, for teachers who want to teach AI and bring AI into the classroom, and for any individual who wants to understand AI in a simple and effective way.Artificial Intelligence is all around us. This book demystifies AI for K12 students and teachers using a unique combination of concept learning, hands-on plugged and unplugged exercises, context of how AI is used in industries from finance to marketing, and project ideas for students to apply their own creativity and build their own AIs. The ten fully illustrated color chapters cover both Machine Learning and Deep Learning, a comprehensive overview of AI Ethics, and popular AI algorithms from Linear Regression to Convolutional Neural Networks. Teacher's corners provide teachers with additional resources for bringing AI into the classroom. The book is paired with extensive online resources in curriculum, datasets, exercises, and code.The two authors (Nisha Talagala and Sindhu Ghanta) have extensive experience building industry AI solutions and have applied their knowledge to teach AI to K12 students. This book comes from their experiences of teaching AI to thousands of students around the world.More information can be found on www.corp.aiclub.world/ai-book-middle-school-high-school
Parallel Problem Solving from Nature - Ppsn XVII
This two-volume set LNCS 13398 and LNCS 13399 constitutes the refereed proceedings of the 17th International Conference on Parallel Problem Solving from Nature, PPSN 2022, held in Dortmund, Germany, in September 2022.The 87 revised full papers were carefully reviewed and selected from numerous submissions. The conference presents a study of computing methods derived from natural models. Amorphous Computing, Artificial Life, Artificial Ant Systems, Artificial Immune Systems, Artificial Neural Networks, Cellular Automata, Evolutionary Computation, Swarm Computing, Self-Organizing Systems, Chemical Computation, Molecular Computation, Quantum Computation, Machine Learning, and Artificial Intelligence approaches using Natural Computing methods are just some of the topics covered in this field.
Intelligence Science IV
This book constitutes the refereed proceedings of the 5th International Conference on Intelligence Science, ICIS 2022, held in Xi'an, China, in August 2022. The 41 full and 5 short papers presented in this book were carefully reviewed and selected from 85 submissions. They were organized in topical sections as follows: Brain cognition; machine learning; data intelligence; language cognition; remote sensing images; perceptual intelligence; wireless sensor; and medical artificial intelligence.
Chinese Lexical Semantics
This book constitutes the thoroughly refereed post-workshop proceedings of the 22nd Chinese Lexical Semantics Workshop, CLSW 2021, held in Nanjing, China in May 2021. The 68 full papers and 4 short papers included in this volume were carefully reviewed and selected from 261 submissions. They are organized in the following topical sections: Lexical Semantics and General Linguistics; Natural Language Processing and Language Computing; Cognitive Science and Experimental Studies; Lexical Resources and Corpus Linguistics.
Haptic and Audio Interaction Design
This book constitutes the refereed proceedings of the 11th International Conference on Haptic and Audio Interaction Design, HAID 2022, held in London, UK, in August 2022. The 13 full papers presented were carefully reviewed and selected from 19 submissions that were sent for peer review. The papers are organized in topical sections on accessibility, perception, design and applications, and musical applications.
Accelerate DevOps with GitHub
Take your DevOps and DevSecOps game to the next level by leveraging the power of the GitHub toolset in practiceKey Features: Release software faster and with confidenceIncrease your productivity by spending more time on software delivery and less on fixing bugs and administrative tasksDeliver high-quality software that is more stable, scalable, and secureBook Description: This practical guide to DevOps uses GitHub as the DevOps platform and shows how you can leverage the power of GitHub for collaboration, lean management, and secure and fast software delivery.The chapters provide simple solutions to common problems, thereby helping teams that are already on their DevOps journey to further advance into DevOps and speed up their software delivery performance. From finding the right metrics to measure your success to learning from other teams' success stories without merely copying what they've done, this book has it all in one place. As you advance, you'll find out how you can leverage the power of GitHub to accelerate your value delivery - by making work visible with GitHub Projects, measuring the right metrics with GitHub Insights, using solid and proven engineering practices with GitHub Actions and Advanced Security, and moving to event-based and loosely coupled software architecture.By the end of this GitHub book, you'll have understood what factors influence software delivery performance and how you can measure your capabilities, thus realizing where you stand in your journey and how you can move forward.What You Will Learn: Effectively measure software delivery performanceAdopt DevOps and lean management techniques in your teamsPlan, track, and visualize your work using GitHub Issues and ProjectsUse continuous delivery with GitHub Actions and PackagesScale quality through testing in production and chaos engineering"Shift left" security and secure your entire software supply chainUse DevSecOps practices with GitHub Advanced SecuritySecure your code with code scanning, secret scanning, and DependabotWho this book is for: This book is for developers, solutions architects, DevOps engineers, and SREs, as well as for engineering or product managers who want to enhance their software delivery performance. Whether you're new to DevOps, already have experience with GitHub Enterprise, or come from a platform such as Azure DevOps, Team Foundation Server, GitLab, Bitbucket, Puppet, Chef, or Jenkins but struggle to achieve maximum performance, you'll find this book beneficial.
Designing Human-Centric AI Experiences
User experience (UX) design practices have seen a fundamental shift as more and more software products incorporate machine learning (ML) components and artificial intelligence (AI) algorithms at their core. This book will probe into UX design's role in making technologies inclusive and enabling user collaboration with AI. AI/ML-based systems have changed the way of traditional UX design. Instead of programming a method to do a specific action, creators of these systems provide data and nurture them to curate outcomes based on inputs. These systems are dynamic and while AI systems change over time, their user experience, in many cases, does not adapt to this dynamic nature. Applied UX Design for Artificial Intelligence will explore this problem, addressing the challenges and opportunities in UX design for AI/ML systems, look at best practices for designers, managers, and product creators and showcase how individuals from a non-technical background can collaborate effectively with AI and Machine learning teams. You Will Learn: Best practices in UX design when building human-centric AI products or featuresAbility to spot opportunities for applying AI in their organizationsAdvantages and limitations of AI when building software productsAbility to collaborate and communicate effectively with AI/ML tech teams - UX design for different modalities (voice, speech, text, etc.)Designing ethical AI system
Microsoft Power BI Data Analyst Certification Guide
Gain the knowledge and skills needed to become a certified Microsoft Power BI data analyst and get the most out of Power BIKey Features: Get the skills you need to pass the PL-300 certification exam with confidenceCreate and maintain robust reports and dashboards to enable a data-driven enterpriseTest your new BI skills with the help of practice questionsBook Description: Microsoft Power BI enables organizations to create a data-driven culture with business intelligence for all. This guide to achieving the Microsoft Power BI Data Analyst Associate certification will help you take control of your organization's data and pass the exam with confidence.From getting started with Power BI to connecting to data sources, including files, databases, cloud services, and SaaS providers, to using Power BI's built-in tools to build data models and produce visualizations, this book will walk you through everything from setup to preparing for the certification exam. Throughout the chapters, you'll get detailed explanations and learn how to analyze your data, prepare it for consumption by business users, and maintain an enterprise environment in a secure and efficient way.By the end of this book, you'll be able to create and maintain robust reports and dashboards, enabling you to manage a data-driven enterprise, and be ready to take the PL-300 exam with confidence.What You Will Learn: Connect to and prepare data from a variety of sourcesClean, transform, and shape your data for analysisCreate data models that enable insight creationAnalyze data using Microsoft Power BI's capabilitiesCreate visualizations to make analysis easierDiscover how to deploy and manage Microsoft Power BI assetsWho this book is for: This book is for data analysts and BI professionals who want to become more competent in Microsoft Power BI. Although the content in this book will help you pass the PL-300 exam, there are plenty of other practical applications beyond exam preparation in the chapters. No prior experience with Power BI is needed.
Low-Code Application Development with Appian
Go from no-code to low-code and translate your business requirements into full-fledged enterprise-ready applicationsKey Features: Digitize and automate your business processes quickly using Appian's powerful low-code functionalitiesUnderstand enterprise data models and turn them into actionable Appian RecordsUse declarative code-style UI building to design intuitive UIs and reusable components in AppianBook Description: This book is an exhaustive overview of how the Appian Low-Code BPM Suite enables tech-savvy professionals to rapidly automate business processes across their organization, integrating people, software bots, and data. This is crucial as 80% of all software development is expected to be carried out in low code by 2024.This practical guide helps you master business application development with Appian as a beginner low-code developer. You'll learn to automate business processes using Appian low-code, records, processes, and expressions quickly and on an enterprise scale. In a fictional development project, guided by step-by-step explanations of the concepts and practical examples, this book will empower you to transform complex business processes into software.At first, you'll learn the power of no-code with Appian Quick Apps to solve some of your most crucial business challenges. You'll then get to grips with the building blocks of an Appian, starting with no-code and advancing to low-code, eventually transforming complex business requirements into a working enterprise-ready application.By the end of this book, you'll be able to deploy Appian Quick Apps in minutes and successfully transform a complex business process into low-code process models, data, and UIs to deploy full-featured, enterprise-ready, process-driven, mobile-enabled apps.What You Will Learn: Use Appian Quick Apps to solve the most urgent business challengesLeverage Appian's low-code functionalities to enable faster digital innovation in your organizationModel business data, Appian records, and processesPerform UX discovery and UI building in AppianConnect to other systems with Appian Integrations and Web APIsWork with Appian expressions, data querying, and constantsWho this book is for: This book empowers software developers and tech-savvy business users with a new tool that'll help them increase efficiency by a huge margin and speed up the delivery of new features to meet the demands of business departments. Business users with a maker's attitude finally have the chance to develop their own business applications, as low-code drastically reduces the complexity of traditional software development. Prior experience with automation solutions and low-code programming is needed to help you get the most out of this book.
Random Matrix Methods for Machine Learning
This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality phenomena. This enables a precise understanding, and possible improvements, of the core mechanisms at play in real-world machine learning algorithms. The book opens with a thorough introduction to the theoretical basics of random matrices, which serves as a support to a wide scope of applications ranging from SVMs, through semi-supervised learning, unsupervised spectral clustering, and graph methods, to neural networks and deep learning. For each application, the authors discuss small- versus large-dimensional intuitions of the problem, followed by a systematic random matrix analysis of the resulting performance and possible improvements. All concepts, applications, and variations are illustrated numerically on synthetic as well as real-world data, with MATLAB and Python code provided on the accompanying website.
Well-Being in the Information Society
This book constitutes the refereed proceedings of the 9th International Conference on Well-Being in the Information Society, WIS 2022, held in Turku, Finland, in August 2022. The 14 revised full papers presented were carefully reviewed and selected from 17 submissions. The proceedings are structured in four sections as follows: ​mental well-being and e-health; social media and well-being; innovative solution for well-being in the information society; driving well-being in the information society.
Bayesian Methods for Interaction and Design
Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesian optimisation; and Bayesian approaches to modelling the cognitive processes of users.
Artificial Intelligence Applications and Innovations
This book constitutes the refereed proceedings of five International Workshops held as parallel events of the 18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022, virtually and in Hersonissos, Crete, Greece, in June 2022: the 11th Mining Humanistic Data Workshop (MHDW 2022); the 7th 5G-Putting Intelligence to the Network Edge Workshop (5G-PINE 2022); the 1st workshop on AI in Energy, Building and Micro-Grids (AIBMG 2022); the 1st Workshop/Special Session on Machine Learning and Big Data in Health Care (ML@HC 2022); and the 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics (AIBEI 2022). The 35 full papers presented at these workshops were carefully reviewed and selected from 74 submissions.
Bayesian Methods for Interaction and Design
Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesian optimisation; and Bayesian approaches to modelling the cognitive processes of users.
Serious Games
This book constitutes the refereed proceedings of the 8th Joint International Conference on Serious Games, JCSG 2022, held in Weimar, Germany, in September 2022. The 14 full papers presented together with 5 short papers were carefully reviewed and selected from 31 submissions. JSCG 2022 is dedicated to serious games and its interdisciplinary characteristics combining game concepts and technologies required in the different application domains. This year's proceedings are categorized into the following topical sub-headings: Learning Psychology, Design Aspects, Game Design, Health Games, Games Application, and Mixed Reality.
Case-Based Reasoning Research and Development
This book constitutes the proceedings of the 30th International Conference on Case-Based Reasoning, ICCBR 2022, which took place in Nancy, France, during September 12-15, 2022.The theme of ICCBR 2022 was Global Challenges for CBR aiming to consider how CBR can and might contribute to challenges in sustainability, climate change, and global health. The 26 papers presented in this volume were carefully reviewed and selected from 68 submissions. They deal with AI and related research focusing on comparison and integration of CBR with other AI methods such as deep learning architectures, reinforcement learning, lifelong learning, and eXplainable AI (XAI).
Machine Learning and Knowledge Extraction
This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022.The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.
Hands-On Healthcare Data
Healthcare is the next frontier for data science. Using the latest in machine learning, deep learning, and natural language processing, you'll be able to solve healthcare's most pressing problems: reducing cost of care, ensuring patients get the best treatment, and increasing accessibility for the underserved. But first, you have to learn how to access and make sense of all that data. This book provides pragmatic and hands-on solutions for working with healthcare data, from data extraction to cleaning and harmonization to feature engineering. Author Andrew Nguyen covers specific ML and deep learning examples with a focus on producing high-quality data. You'll discover how graph technologies help you connect disparate data sources so you can solve healthcare's most challenging problems using advanced analytics. You'll learn: Different types of healthcare data: electronic health records, clinical registries and trials, digital health tools, and claims data The challenges of working with healthcare data, especially when trying to aggregate data from multiple sources Current options for extracting structured data from clinical text How to make trade-offs when using tools and frameworks for normalizing structured healthcare data How to harmonize healthcare data using terminologies, ontologies, and mappings and crosswalks
Applications of Machine Learning and Deep Learning on Biological Data
The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, comprehensive programming of bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and efficacy of programming such algorithms. Applications of Machine Learning and Deep Learning on Biological Data is an examination of applying ML and DL to such areas as proteomics, genomics, microarrays, text mining, and systems biology. The key objective is to cover ML applications to biological science problems, focusing on problems related to bioinformatics. The book looks at cutting-edge research topics and methodologies in ML applied to the rapidly advancing discipline of bioinformatics. ML and DL applied to biological and neuroimaging data can open new frontiers for biomedical engineering, such as refining the understanding of complex diseases, including cancer and neurodegenerative and psychiatric disorders. Advances in this field could eventually lead to the development of precision medicine and automated diagnostic tools capable of tailoring medical treatments to individual lifestyles, variability, and the environment. Highlights include: Artificial Intelligence in treating and diagnosing schizophrenia An analysis of ML's and DL's financial effect on healthcare An XGBoost-based classification method for breast cancer classification Using ML to predict squamous diseases ML and DL applications in genomics and proteomics Applying ML and DL to biological data
The Doctor and the Algorithm
For years, technologists and computer scientists have promised an AI revolution that would transform the very basis of how we imagine and administer modern medicine. AI-driven advancements in medical error rates, diagnostic accuracy, or disease outbreak detection could potentially save thousands of lives. But health AI also carries the potential for exacerbating deep systemic biases if left unchecked. The Doctor and the Algorithm combines insights from science and technology studies, critical algorithm studies, and public interest informatics to better understand the promise and peril of health AI. The book draws on case studies in automated diagnostics, algorithmic pain measurement, AI-driven drug discovery, and death prediction to investigate how health AI is made, promoted, and justified. It explores the enthusiastic promises of health AI marketing communication and medical futurism while also analyzing the inequitable outcomes new AI technology often creates for already marginalized communities. Finally, the book closes with specific recommendations for regulatory frameworks that might support more ethical and equitable approaches to health AI in the future. Interweaving textual analysis and original informatics, The Doctor and the Algorithm offers a sobering analysis of the promise of medical AI against the real and unintended consequences that deep medicine can bring for patients, providers, and public health alike.
Image Analysis and Processing. Iciap 2022 Workshops
The two-volume set LNCS 13373 and 13374 constitutes the papers of several workshops which were held in conjunction with the 21st International Conference on Image Analysis and Processing, ICIAP 2022, held in Lecce, Italy, in May 2022.The 96 revised full papers presented in the proceedings set were carefully reviewed and selected from 157 submissions.ICIAP 2022 presents the following Sixteen workshops: Volume I: GoodBrother workshop on visual intelligence for active and assisted livingParts can worth like the Whole - PART 2022Workshop on Fine Art Pattern Extraction and Recognition - FAPERWorkshop on Intelligent Systems in Human and Artificial Perception - ISHAPE 2022Artificial Intelligence and Radiomics in Computer-Aided Diagnosis - AIRCADDeep-Learning and High Performance Computing to Boost Biomedical Applications - DeepHealthVolume II: Human Behaviour Analysis for Smart City Environment Safety - HBAxSCESBinary is the new Black (and White): Recent Advances on Binary Image ProcessingArtificial Intelligence for preterm infants' healthCare - AI-careTowards a Complete Analysis of People: From Face and Body to Clothes - T-CAPArtificial Intelligence for Digital Humanities - AI4DHMedical Transformers - MEDXFLearning in Precision Livestock Farming - LPLFWorkshop on Small-Drone Surveillance, Detection and Counteraction Techniques - WOSDETCMedical Imaging Analysis For Covid-19 - MIACOVID 2022Novel Benchmarks and Approaches for Real-World Continual Learning - CL4REAL
Image Analysis and Processing. Iciap 2022 Workshops
The two-volume set LNCS 13373 and 13374 constitutes the papers of several workshops which were held in conjunction with the 21st International Conference on Image Analysis and Processing, ICIAP 2022, held in Lecce, Italy, in May 2022.The 96 revised full papers presented in the proceedings set were carefully reviewed and selected from 157 submissions.ICIAP 2022 presents the following Sixteen workshops: Volume I: GoodBrother workshop on visual intelligence for active and assisted livingParts can worth like the Whole - PART 2022Workshop on Fine Art Pattern Extraction and Recognition - FAPERWorkshop on Intelligent Systems in Human and Artificial Perception - ISHAPE 2022Artificial Intelligence and Radiomics in Computer-Aided Diagnosis - AIRCADDeep-Learning and High Performance Computing to Boost Biomedical Applications - DeepHealthVolume II: Human Behaviour Analysis for Smart City Environment Safety - HBAxSCESBinary is the new Black (and White): Recent Advances on Binary Image ProcessingArtificial Intelligence for preterm infants' healthCare - AI-careTowards a Complete Analysis of People: From Face and Body to Clothes - T-CAPArtificial Intelligence for Digital Humanities - AI4DHMedical Transformers - MEDXFLearning in Precision Livestock Farming - LPLFWorkshop on Small-Drone Surveillance, Detection and Counteraction Techniques - WOSDETCMedical Imaging Analysis For Covid-19 - MIACOVID 2022Novel Benchmarks and Approaches for Real-World Continual Learning - CL4REAL
Database and Expert Systems Applications
This two-volume set, LNCS 13426 and 13427, constitutes the thoroughly refereed proceedings of the 33rd International Conference on Database and Expert Systems Applications, DEXA 2022, held in Vienna in August 2022.The 43 full papers presented together with 20 short papers in these volumes were carefully reviewed and selected from a total of 120 submissions. The papers are organized around the following topics: Big Data Management and Analytics, Consistency, Integrity, Quality of Data, Constraint Modelling and Processing, Database Federation and Integration, Interoperability, Multi-Databases, Data and Information Semantics, Data Integration, Metadata Management, and Interoperability, Data Structures and much more.
Impact of Class Assignment on Multinomial Classification Using Multi-Valued Neurons
Multilayer neural networks based on multi-valued neurons (MLMVNs) have been proposed to combine the advantages of complex-valued neural networks with a plain derivative-free learning algorithm. In addition, multi-valued neurons (MVNs) offer a multi-valued threshold logic resulting in the ability to replace multiple conventional output neurons in classification tasks. Therefore, several classes can be assigned to one output neuron. This book introduces a novel approach to assign multiple classes to numerous MVNs in the output layer. It was found that classes that possess similarities should be allocated to the same neuron and arranged adjacent to each other on the unit circle. Since MLMVNs require input data located on the unit circle, two employed transformations are reevaluated. The min-max scaler utilizing the exponential function, and the 2D discrete Fourier transform restricting to the phase information for image recognition. The evaluation was performed on the Sensorless Drive Diagnosis dataset and the Fashion MNIST dataset.
Artificial Intelligence for Knowledge Management
This book features a selection of extended papers presented at the 7th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2019, held in Macao, China, in August 2019, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2019.The 8 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.
Artificial Intelligence in Education
This two-volume set LNAI 13355 and 13356 constitutes the refereed proceedings of the 23rd International Conference on Artificial Intelligence in Education, AIED 2022, held in Durham, UK, in July 2022.The 40 full papers and 40 short papers presented together with 2 keynotes, 6 industry papers, 12 DC papers, 6 Workshop papers, 10 Practitioner papers, 97 Posters and Late-Breaking Results were carefully reviewed and selected from 243 submissions. The conference presents topics such as intelligent systems and the cognitive sciences for the improvement and advancement of education, the science and engineering of intelligent interactive learning systems. The theme for the AIED 2022 conference was "AI in Education: Bridging the gap between academia, business, and non-pro t in preparing future-proof generations towards ubiquitous AI."
Weaving Fire into Form
This book investigates multiple facets of the emerging discipline of Tangible, Embodied, and Embedded Interaction (TEI). This is a story of atoms and bits. We explore the interweaving of the physical and digital, toward understanding some of their wildly varying hybrid forms and behaviors. Spanning conceptual, philosophical, cognitive, design, and technical aspects of interaction, this book charts both history and aspirations for the future of TEI. We examine and celebrate diverse trailblazing works, and provide wide-ranging conceptual and pragmatic tools toward weaving the animating fires of computation and technology into evocative tangible forms. We also chart a path forward for TEI engagement with broader societal and sustainability challenges that will profoundly (re)shape our children's and grandchildren's futures. We invite you all to join this quest.
Modeling Decisions for Artificial Intelligence
This book constitutes the refereed proceedings of the 19th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2022, held in Sant Cugat, Spain, during August - September 2022.The 16 papers presented in this volume were carefully reviewed and selected from 41 submissions. The papers discuss different facets of decision processes in a broad sense and present research in data science, machine learning, data privacy, aggregation functions, human decision-making, graphs and social networks, and recommendation and search. They were organized in topical sections as follows: Decision making and uncertainty; Data privacy; Machine Learning and data science.
Advancing Research in Information and Communication Technology
For 60 years the International Federation for Information Processing (IFIP) has been advancing research in Information and Communication Technology (ICT). This book looks into both past experiences and future perspectives using the core of IFIP's competence, its Technical Committees (TCs) and Working Groups (WGs). Soon after IFIP was founded, it established TCs and related WGs to foster the exchange and development of the scientific and technical aspects of information processing. IFIP TCs are as diverse as the different aspects of information processing, but they share the following aims: To establish and maintain liaison with national and international organizations with allied interests and to foster cooperative action, collaborative research, and information exchange.To identify subjects and priorities for research, to stimulate theoretical work on fundamental issues, and to foster fundamental research which will underpin future development.To provide a forum for professionals with a view to promoting the study, collection, exchange, and dissemination of ideas, information, and research findings and thereby to promote the state of the art.To seek and use the most effective ways of disseminating information about IFIP's work including the organization of conferences, workshops and symposia and the timely production of relevant publications.To have special regard for the needs of developing countries and to seek practicable ways of working with them.To encourage communication and to promote interaction between users, practitioners, and researchers.To foster interdisciplinary work and - in particular - to collaborate with other Technical Committees and Working Groups. The 17 contributions in this book describe the scientific, technical, and further work in TCs and WGs and in many cases also assess the future consequences of the work's results. These contributions explore the developments of IFIP and the ICT profession now and over the next 60 years. The contributions are arranged per TC and conclude with the chapter on the IFIP code of ethics and conduct.
Cross-Cultural Design. Interaction Design Across Cultures
The four-volume set LNCS 13311 - 13314 constitutes the refereed proceedings of the 14th International Conference on Cross-Cultural Design, CCD 2022, which was held as part of HCI International 2022 and took place virtually during June 26 - July 1, 2022. The papers included in the HCII-CCD volume set were organized in topical sections as follows: Part I: Cross-Cultural Interaction Design; Collaborative and Participatory Cross-Cultural Design; Cross-Cultural Differences and HCI; Aspects of Intercultural Design Part II: Cross-Cultural Learning, Training, and Education; Cross-Cultural Design in Arts and Music; Creative Industries and Cultural Heritage under a Cross-Cultural Perspective; Cross-Cultural Virtual Reality and Games Part III: Intercultural Business Communication; Intercultural Business Communication; HCI and the Global Social Change Imposed by COVID-19; Intercultural Design for Well-being and Inclusiveness Part IV: Cross-Cultural Product and Service Design; Cross-Cultural Mobility and Automotive UX Design; Design and Culture in Social Development and Digital Transformation of Cities and Urban Areas; Cross-Cultural Design in Intelligent Environments.
Computational Intelligence in Healthcare
Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. Artificial intelligent systems offer great improvement in healthcare systems by providing more intelligent and convenient solutions and services assisted by machine learning, wireless communications, data analytics, cognitive computing, and mobile computing. Modern health treatments are faced with the challenge of acquiring, analysing, and applying the large amount of knowledge necessary to solve complex problems. AI techniques are being effectively used in the field of healthcare systems by extracting the useful information from the vast amounts of data by applying human expertise and CI methods, such as fuzzy models, artificial neural networks, evolutionary algorithms, and probabilistic methods which have recently emerged as promising tools for the development and application of intelligent systems in healthcare practice. This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with them. Contained in the book are state-of-the-art CI methods and other allied techniques used in healthcare systems as well as advances in different CI methods that confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide the latest research related to the healthcare sector to researchers and engineers with a platform encompassing state-of-the-art innovations, research and design, and the implementation of methodologies.
Chinese Lexical Semantics
The two-volume proceedings, LNCS 13249 and 13250, constitutes the thoroughly refereed post-workshop proceedings of the 22nd Chinese Lexical Semantics Workshop, CLSW 2021, held in Nanjing, China in May 2021. The 68 full papers and 4 short papers were carefully reviewed and selected from 261 submissions. They are organized in the following topical sections: Lexical Semantics and General Linguistics; Natural Language Processing and Language Computing; Cognitive Science and Experimental Studies; Lexical Resources and Corpus Linguistics.
Computational Neuroscience
This book constitutes the refereed proceedings of the Third Latin American Workshop, LAWCN 2021, held in Sao Luis do Maranhao, Brazil, during December 8-10, 2021.The 13 full papers and 3 short papers included in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections as follows: Interdisciplinary applications of Artificial Intelligence (AI) and Machine Learning (ML); AI and ML applied to robotics; AI and ML applied to biomedical sciences; Health issues and computational neuroscience; Software and hardware implementations in neuroscience; and Neuroengineering - science and technology.
Dominant Algorithms to Evaluate Artificial Intelligence
This book describes the Throughput Model methodology that can enable individuals and organizations to better identify, understand, and use algorithms to solve daily problems. The Throughput Model is a progressive model intended to advance the artificial intelligence (AI) field since it represents symbol manipulation in six algorithmic pathways that are theorized to mimic the essential pillars of human cognition, namely, perception, information, judgment, and decision choice. The six AI algorithmic pathways are (1) Expedient Algorithmic Pathway, (2) Ruling Algorithmic Guide Pathway, (3) Analytical Algorithmic Pathway, (4) Revisionist Algorithmic Pathway, (5) Value Driven Algorithmic Pathway, and (6) Global Perspective Algorithmic Pathway. As AI is increasingly employed for applications where decisions require explanations, the Throughput Model offers business professionals the means to look under the hood of AI and comprehend how those decisions are attained by organizations. Key Features: - Covers general concepts of Artificial intelligence and machine learning - Explains the importance of dominant AI algorithms for business and AI research - Provides information about 6 unique algorithmic pathways in the Throughput Model - Provides information to create a roadmap towards building architectures that combine the strengths of the symbolic approaches for analyzing big data - Explains how to understand the functions of an AI algorithm to solve problems and make good decisions - informs managers who are interested in employing ethical and trustworthiness features in systems. Dominant Algorithms to Evaluate Artificial Intelligence: From the view of Throughput Model is an informative reference for all professionals and scholars who are working on AI projects to solve a range of business and technical problems.
