Wineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and consumers. This book systematically investigates how to process human language format reviews and mine useful knowledge from a large volume of processed data. This book presents a human language processing tool named Computational Wine Wheel to process professional wine reviews and three novel Wineinformatics studies to analyze wine quality, price and reviewers. Through the lens of data science, the author demonstrates how the wine receives 90+ scores out of 100 points from Wine Spectator, how to predict a wine's specific grade and price through wine reviews and how to rank a group of wine reviewers. The book also shows the advanced application of the Computational Wine Wheel to capture more information hidden in wine reviews and the possibility of extending the wheel to coffee, tea beer, sake and liquors. This book targets computer scientists, data scientists and wine industrial researchers, who are interested in Wineinformatics. Senior data science undergraduate and graduate students may also benefit from this book.

This book constitutes the refereed proceedings of the 25th Brazilian Symposium on Formal Methods, SBMF 2022, which was held virtually in December 2022. The 8 regular papers presented in this book were carefully reviewed and selected from 15 submissions. The symposium focuses on the development, dissemination, and use of formal methods for the construction of high-quality computational systems, aiming to promote opportunities for researchers and practitioners with an interest in formal methods to discuss the recent advances in this area.

Eingebettete Systeme ubernehmen komplexe Steuerungs- und Regelungsaufgaben fur technische Systeme. Ihre Funktionalitat wird durch das Zusammenspiel von Spezialhardware, Standardprozessoren, Peripherie und Software realisiert. Oft liegt der Schwerpunkt auf Hardware-Aspekten. Tatsachlich spielt der Softwareentwurf eine mindestens genauso wichtige Rolle beim Entwurf dieser Systeme. Hier setzt das Buch an und liefert einen guten Uberblick uber das Thema. Klassifikationen und Themen wie Nebenlaufigkeit, Echtzeit und Echtzeitbetriebssysteme bilden die Grundlagen. Die Programmierung eingebetteter Systeme wird mit C++, Java sowie an den Beispielen von Esterel und Giotto erlautert. Ausgewahlte Softwareentwurfstechniken wie Statecharts, hybride Systeme, UML und Hardware-Software Co-Design werden ausfuhrlich vorgestellt. Eingebettete Systeme finden oft in sicherheitskritischen Bereichen Einsatz. Die Sicherung der Softwarequalitat ist daher von zentraler Bedeutung und bildet einen weiteren wichtigen Teil des Buches."

Artificial Intelligence for Improved Patient Outcomes provides new, relevant, and practical information on what AI can do in healthcare and how to assess whether AI is improving health outcomes. With clear insights and a balanced approach, this innovative book offers a one-stop guide on how to design and lead pragmatic real-world AI studies that yield rigorous scientific evidence-all in a manner that is safe and ethical. Daniel Byrne, Director of Artificial Intelligence Research at AVAIL (the Advanced Vanderbilt Artificial Intelligence Laboratory) and author of landmark pragmatic studies published in leading medical journals, shares four decades of experience as a biostatistician and AI researcher. Building on his first book, Publishing Your Medical Research, the author gives the reader the competitive advantage in creating reproducible AI research that will be accepted in prestigious high-impact medical journals. Provides easy-to-understand explanations of the key concepts in using and evaluating AI in medicine. Offers practical, actionable guidance on the mechanics and implementation of AI applications in medicine. Shares career guidance on a successful future in AI in medicine. Teaches the skills to evaluate AI tools and avoid being misled by the hype. For a wide audience of healthcare professionals impacted by Artificial Intelligence in medicine, including physician-scientists, AI developers, entrepreneurs, and healthcare leaders who need to evaluate AI applications designed to improve safety, quality, and value for their institutions. Enrich Your eBook Reading Experience Read directly on your preferred device(s), such as computer, tablet, or smartphone. Easily convert to audiobook, powering your content with natural language text-to-speech.

This book introduces the Internet access for vehicles as well as novel communication and computing paradigms based on the Internet of vehicles. To enable efficient and reliable Internet connection for mobile vehicle users, this book first introduces analytical modelling methods for the practical vehicle-to-roadside (V2R) Internet access procedure, and employ the interworking of V2R and vehicle-to-vehicle (V2V) to improve the network performance for a variety of automotive applications. In addition, the wireless link performance between a vehicle and an Internet access station is investigated, and a machine learning based algorithm is proposed to improve the link throughout by selecting an efficient modulation and coding scheme. This book also investigates the distributed machine learning algorithms over the Internet access of vehicles. A novel broadcasting scheme is designed to intelligently adjust the training users that are involved in the iteration rounds for an asynchronous federated learning scheme, which is shown to greatly improve the training efficiency. This book conducts the fully asynchronous machine learning evaluations among vehicle users that can utilize the opportunistic V2R communication to train machine learning models. Researchers and advanced-level students who focus on vehicular networks, industrial entities for internet of vehicles providers, government agencies target on transportation system and road management will find this book useful as reference. Network device manufacturers and network operators will also want to purchase this book.

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP's performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future. Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.

The book presents the proceedings of two conferences: the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020), which took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Papers cover all aspects of Data Science, Data Mining, Machine Learning, Artificial and Computational Intelligence (ICDATA) and Information Retrieval Systems, Information & Knowledge Engineering, Management and Cyber-Learning (IKE). Authors include academics, researchers, professionals, and students. Presents the proceedings of the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020); Includes papers on topics from data mining to machine learning to informational retrieval systems; Authors include academics, researchers, professionals and students.

This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams-where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.

This open access book provides an in-depth description of the EU project European Language Grid (ELG). Its motivation lies in the fact that Europe is a multilingual society with 24 official European Union Member State languages and dozens of additional languages including regional and minority languages. The only meaningful way to enable multilingualism and to benefit from this rich linguistic heritage is through Language Technologies (LT) including Natural Language Processing (NLP), Natural Language Understanding (NLU), Speech Technologies and language-centric Artificial Intelligence (AI) applications. The European Language Grid provides a single umbrella platform for the European LT community, including research and industry, effectively functioning as a virtual home, marketplace, showroom, and deployment centre for all services, tools, resources, products and organisations active in the field. Today the ELG cloud platform already offers access to more than 13,000 language processing tools and language resources. It enables all stakeholders to deposit, upload and deploy their technologies and datasets. The platform also supports the long-term objective of establishing digital language equality in Europe by 2030 - to create a situation in which all European languages enjoy equal technological support. This is the very first book dedicated to Language Technology and NLP platforms. Cloud technology has only recently matured enough to make the development of a platform like ELG feasible on a larger scale. The book comprehensively describes the results of the ELG project. Following an introduction, the content is divided into four main parts: (I) ELG Cloud Platform; (II) ELG Inventory of Technologies and Resources; (III) ELG Community and Initiative; and (IV) ELG Open Calls and Pilot Projects.

This book constitutes revised selected papers from the refereed proceedings of the 11th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2021, held as a virtual event during December 16-18, 2021. The 13 full papers included in this book were carefully reviewed and selected from 17 submissions. They were organized in topical sections as follows: Computational advances in bio and medical sciences; and computational advances in molecular epidemiology.

This proceedings LNCS 13521 constitutes the refereed proceedings of the 24th International Conference on Human-Computer Interaction, HCII 2022, which was held virtually as part of the 24th International Conference, HCII 2022, in June 26 to July 1, 2022. HCII 2022 received a total of 5583 submissions from academia, research institutes, industry, and governmental agencies from 88 countries submitted contributions, and 1276 papers and 275 posters were included in the proceedings that were published just before the start of the conference. Additionally, 296 papers and 181 posters are included in the volumes of the proceedings published after the conference, as "Late Breaking Work" (papers and posters). The contributions thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas.

This book constitutes the proceedings of the 5th International Conference, ICC3 2021, held in Coimbatore, India, during December 16-18, 2021. The 14 full papers included in this book were carefully reviewed and selected from 84 submissions. They were organized in topical sections as follows: computational intelligence; cyber security; and computational models.

This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge. The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are needed for real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.

This book includes extended and revised selected papers from the 10th International Conference on Smart Cities and Green ICT Systems, SMARTGREENS 2021, and 7th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2021, held as virtual event, in April 28-30, 2021. The conference was held virtually due to the COVID-19 crisis. The 22 full papers included in this book were carefully reviewed and selected from 140 submissions. The papers present research on advances and applications in the fields of smart cities, electric vehicles, sustainable computing and communications, energy aware systems and technologies, intelligent vehicle technologies, intelligent transport systems and infrastructure, connected vehicles.

The three volume set LNCS 13554, 13555, 13556 constitutes the proceedings of the 27th European Symposium on Research in Computer Security, ESORICS 2022, which took place in September 2022. The conference took place in Copenhagen, Denmark, in a hybrid mode.The 104 full papers and 6 poster papers presented in these proceedings were carefully reviewed and selected from 562 submissions. They were organized in topical sections as follows: Part I: Blockchain security; privacy; crypto; attacks; sidechannels; Part II: Anonymity; cloud security; access control; authentication; digital signatures; IoT security; applications; Part III: Formal analysis; Web security; hardware security; multiparty computation; ML techniques; cyber-physical systems security; network and software security; posters.

This book constitutes the thoroughly refereed post conference papers of the 4th International Conference on Blockchain and Trustworthy Systems, Blocksys 2022, held in Chengdu, China, in August 2022. The 26 full papers were carefully reviewed and selected from 56 submissions. The papers are organized in topical sections: Trustworthy Systems; Blockchain; Private Computing.

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.

The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23-27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23-27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

This book constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Coordination, Organizations, Institutions, and Norms for Governance of Multi-Agent Systems, COINE 2022, which was held in Auckland, New Zealand, on May 9, 2022. The 14 papers included in these proceedings were carefully reviewed and selected from 15 submissions. They deal with autonomous agents and multi-agent systems, focusing on the scientific and technological aspects of social coordination, organizational theory, artificial (electronic) institutions, and normative and ethical MAS.

This book constitutes the proceedings of the 8th International Symposium on Model-Based Safety and Assessment, IMBSA 2022, held in Munich, Germany, in September 2022. The 15 revised full papers and 3 short papers presented were carefully reviewed and selected from 27 initial submissions. The papers focus on model-based and automated ways of assessing safety and other attributes of dependability of complex systems. They are organized in topical sections on safety analysis automation, MBSA practices, causal models and failure modeling strategies, designing mitigations of faults and attacks, data based safety analysis, dynamic risk assessment.

This book offers an introduction and hands-on examples that demonstrate how Learning Analytics (LA) can be used to enhance digital learning, teaching and training at various levels. While the majority of existing literature on the subject focuses on its application at large corporations, this book develops and showcases approaches that bring LA closer to smaller organizations, and to educational institutions that lack sufficient resources to implement a full-fledged LA infrastructure. In closing, the book introduces a set of software tools for data analytics and visualization, and explains how they can be employed in several LA scenarios.

This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. The emergence of Industry 4.0 has witnessed the deployment of reconfigurable hardware or field programmable gate arrays (FPGAs) in diverse embedded applications. These are associated with the execution of several real-time tasks arranged in schedules. However, they are associated with several issues. Development of fully and partially reconfigurable task schedules are discussed that eradicates the existing problems. However, such real-time task schedules may be jeopardized due to hardware threats. Analysis of such threats is discussed and self-aware security techniques are proposed that can detect and mitigate such threats at runtime.

This open access book constitutes the refereed proceedings of 1st International Workshop on Psychology, Learning, Technology, PLT 2022, Foggia, Italy, during January 2022. The 8 full papers presented here were carefully reviewed and selected from 23 submissions. In addition, one invited paper is also included. Psychology, Learning, ad Technology Conference (PLT2022) aims to explore learning paths that incorporate digital technologies in innovative and transformative ways and the improvement of the psychological and relational life. The conference includes topics about the methodology of application of the ICT tools in psychology and education: from blended learning to the application of artificial intelligence in education; from the teaching, learning, and assessment strategies and practices to the new frontiers on Human-Computer Interaction.

This book constitutes the proceedings of the 18th International Workshop on OpenMP, IWOMP 2022, held in Chattanooga, TN, USA, in September 2022.The 11 full papers presented in this volume were carefully reviewed and selected for inclusion in this book from the 13 submissions. The papers are organized in topical sections named: OpenMP and multiple nodes; exploring new and recent OpenMP extensions; effectie use of advanced heterogeneous node architectures; OpenMP tool support; OpenMP and multiple translation units. Chapter "Improving Tool Support for Nested Parallel Regions with Introspection Consistency" is publshed Open Access and licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).