The Illiac IV was the first large scale array computer. As the fore runner of today's advanced computers, it brought whole classes of scientific computations into the realm of practicality. Conceived initially as a grand experiment in computer science, the revolutionary architecture incorporated both a high level of parallelism and pipe lining. After a difficult gestation, the Illiac IV became operational in November 1975. It has for a decade been a substantial driving force behind the develooment of computer technology. Today the Illiac IV continues to service large-scale scientific aoolication areas includ ing computational fluid dynamics, seismic stress wave propagation model ing, climate simulation, digital image processing, astrophysics, numerical analysis, spectroscopy and other diverse areas. This volume brings together previously published material, adapted in an effort to provide the reader with a perspective on the strengths and weaknesses of the Illiac IV and the impact this unique computa tional resource has had on the development of technology. The history and current status of the Illiac system, the design and architecture of the hardware, the programming languages, and a considerable sampling of applications are all covered at some length. A final section is devoted to commentary."

With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.

Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you. Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems. In this book, you will: Use heuristics and design fitness functions. Build genetic algorithms. Make nature-inspired swarms with ants, bees and particles. Create Monte Carlo simulations. Investigate cellular automata. Find minima and maxima, using hill climbing and simulated annealing. Try selection methods, including tournament and roulette wheels. Learn about heuristics, fitness functions, metrics, and clusters. Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon. What You Need: Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.

Dokumentenmanagementprojekte sind ganzheitliche Projekte. Organisatorische, technische und menschliche Faktoren entscheiden uber Erfolg oder Mierfolg. Das DMS-Handbuch hilft fruhzeitig Fehler zu erkennen und zu vermeiden. Es ist eine Pflichtlekture fur jeden, der sich mit dem Gedanken tragt, ein Dokumentenmanagementsystem einzufuhren. Schritt fur Schritt wird der Leser durch die einzelnen Projektstufen gefuhrt. Mit Hilfe von Tabellen, Charts und Diagrammen wird eine komplexe Materie ubersichtlich dargestellt. Ein ausfuhrliches Glossar mit Begriffserklarungen der Fachtermini und eine Fulle von Checklisten machen das Buch zum unentbehrlichen Begleiter.

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.

Embedded systems take over complex control and data processing tasks in diverse application ?elds such as automotive, avionics, consumer products, and telec- munications. They are the primary driver for improving overall system safety, ef?ciency, and comfort. The demand for further improvement in these aspects can only be satis?ed by designing embedded systems of increasing complexity, which in turn necessitates the development of new system design methodologies based on speci?cation, design, and veri?cation languages. The objective of the book at hand is to provide researchers and designers with an overview of current research trends, results, and application experiences in c- puter languages for embedded systems. The book builds upon the most relevant contributions to the 2008 conference Forum on Design Languages (FDL), the p- mier international conference specializing in this ?eld. These contributions have been selected based on the results of reviews provided by leading experts from - search and industry. In many cases, the authors have improved their original work by adding breadth, depth, or explanation.

This book constitutes the refereed proceedings of the 12th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2022, held in Helsinki, Finland, in June 2022. The 13 full papers presented were carefully reviewed and selected from 21 submissions. The papers address various topics such as information and knowledge systems, including submissions that apply ideas, theories or methods from specific disciplines to information and knowledge systems. Examples of such disciplines are discrete mathematics, logic and algebra, model theory, databases, information theory, complexity theory, algorithmics and computation, statistics and optimization.

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 constitutes the refereed proceedings of the 22nd International Conference on Innovations for Community Services, I4CS 2022, held in Delft, The Netherlands, in June 2022. The 15 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 43 submissions. Three invited papers were also included in the volume. The papers focus on topics such as services for critical infrastructure; network architecture for communities; applications and services supporting work and life; community data and visualization; technology empowers industry processes; and future community support.

Dieses Lehrbuch bietet eine umfassende EinfA1/4hrung in Grundlagen und Methoden der Computerlinguistik und stellt die wichtigsten Anwendungsgebiete in der Sprachtechnologie vor. Es richtet sich gleichermaAen an Studierende der Computerlinguistik und verwandter FAcher mit Bezug zur Verarbeitung natA1/4rlicher Sprache wie an Entwickler sprachverarbeitender Systeme.

FA1/4r die dritte Auflage wurden sAmtliche Kapitel A1/4berarbeitet und aktualisiert sowie zum Teil zu eigenstAndigen, neuen Kapiteln zusammengefA1/4hrt. Insbesondere trAgt die dritte Auflage der rasanten Entwicklung in der Computerlinguistik und Sprachtechnologie durch eine stArkere Fokussierung auf statistische Grundlagen und Methoden Rechnung.

This book constitutes the proceedings of the 16th International Conference on Theoretical Aspects of Software Engineering, TASE 2022, held in Cluj-Napoca, Romania, July 2022. The 21 full regular papers presented together with 5 short papers in this book were carefully reviewed and selected from 71 submissions. The topics of the papers covering various fields in software engineering and the latest developments in in formal and theoretical software engineering methods and techniques.

This two-volume set LNCS 11581 and 11582 constitutes the thoroughly refereed proceedings of the 10th International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, DHM 2019, which was held as part of the 21st HCI International Conference, HCII 2019, in Orlando, FL, USA, in July 2019. The total of 1275 papers and 209 posters included in the 35 HCII 2019 proceedings volumes were carefully reviewed and selected from 5029 submissions. DHM 2019 includes a total of 77 papers; they were organized in topical sections named: Part I, Human Body and Motion: Anthropometry and computer aided ergonomics; motion prediction and motion capture; work modelling and industrial applications; risk assessment and safety. Part II, Healthcare Applications: Models in healthcare; quality of life technologies; health dialogues; health games and social communities.

This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.

Der Einsatz von Software-Agenten zur Koordination wirtschaftlicher Prozesse und auf elektronischen Marktpl tzen ist Kernthema dieses Buches. Dabei werden Potenziale und Chancen, Anwendungen und Prototypen, aber auch Herausforderungen, Grenzen und Risiken der Agententechnologie f r den Einsatz aufgezeigt. Theoretische Grundlagen und Beispiele aus Projekten und deren Konzepte dienen als Basis f r die Realisierung eines eigenen agentenbasierten Markplatzes in Java. Im Vordergrund stehen daher praktische Ans tze zur Realisierung wirtschaftlicher Mechanismen und deren Implementierungen in eigenen Software-Agenten.
Die beigef gte CD enth lt eine eingeschr nkte Lizenzversion des kommerziellen Agentensystems "Living Agents Runtime System" sowie die im Buch beschriebenen Java-Klassen.

Offering an introduction to the field of expert/knowledge based systems, this text covers current and emerging trends as well as future research areas. It considers both the system shell and programming environment approaches to expert system development.;College or university bookshops may order five or more copies at a special student price. Price is available on request.

This book constitutes the refereed post-conference proceedings of the 5th EAI International Conference on Innovations and Interdisciplinary Solutions for Underserved Areas, InterSol 2022, held in Nile University of Nigeria Abuja, Nigeria, in March 2022. The 26 papers presented were selected from 66 submissions and issue different problems in underserved and unserved areas. They face problems in almost all sectors such as energy, water, communication, climate change, food, education, transportation, social development, and economic growth.

This book constitutes the refereed proceedings of the 22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022, which was held in October 2022. Due to COVID-19 pandemic the conference was held virtually. The 33 full papers and 10 short papers, presented were carefully reviewed and selected from 91 submissions. The papers cover many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems

This book focuses on one of the major challenges of the newly created scientific domain known as data science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity. Actionable knowledge has been qualitatively and intensively studied in management, business, and the social sciences but in computer science and engineering, its connection has only recently been established to data mining and its evolution, 'Knowledge Discovery and Data Mining' (KDD). Data mining seeks to extract interesting patterns from data, but, until now, the patterns discovered from data have not always been 'actionable' for decision-makers in Socio-Technical Organizations (STO). With the evolution of the Internet and connectivity, STOs have evolved into Cyber-Physical and Social Systems (CPSS) that are known to describe our world today. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are required to transform complex data into actionable knowledge. Readers are presented with advanced knowledge concepts and the analytics and information fusion (AIF) processes aimed at delivering actionable knowledge. The authors provide an understanding of the concept of 'relation' and its exploitation, relational calculus, as well as the formalization of specific dimensions of knowledge that achieve a semantic growth along the AIF processes. This book serves as an important technical presentation of relational calculus and its application to processing chains in order to generate actionable knowledge. It is ideal for graduate students, researchers, or industry professionals interested in decision science and knowledge engineering.

This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from scratch. It provides a treatment of the general recurrent neural networks with principled methods for training that render the (generalized) backpropagation through time (BPTT). This author focuses on the basics and nuances of recurrent neural networks, providing technical and principled treatment of the subject, with a view toward using coding and deep learning computational frameworks, e.g., Python and Tensorflow-Keras. Recurrent neural networks are treated holistically from simple to gated architectures, adopting the technical machinery of adaptive non-convex optimization with dynamic constraints to leverage its systematic power in organizing the learning and training processes. This permits the flow of concepts and techniques that provide grounded support for design and training choices. The author's approach enables strategic co-training of output layers, using supervised learning, and hidden layers, using unsupervised learning, to generate more efficient internal representations and accuracy performance. As a result, readers will be enabled to create designs tailoring proficient procedures for recurrent neural networks in their targeted applications.

Leverage Apache Spark within a modern data engineering ecosystem. This hands-on guide will teach you how to write fully functional applications, follow industry best practices, and learn the rationale behind these decisions. With Apache Spark as the foundation, you will follow a step-by-step journey beginning with the basics of data ingestion, processing, and transformation, and ending up with an entire local data platform running Apache Spark, Apache Zeppelin, Apache Kafka, Redis, MySQL, Minio (S3), and Apache Airflow. Apache Spark applications solve a wide range of data problems from traditional data loading and processing to rich SQL-based analysis as well as complex machine learning workloads and even near real-time processing of streaming data. Spark fits well as a central foundation for any data engineering workload. This book will teach you to write interactive Spark applications using Apache Zeppelin notebooks, write and compile reusable applications and modules, and fully test both batch and streaming. You will also learn to containerize your applications using Docker and run and deploy your Spark applications using a variety of tools such as Apache Airflow, Docker and Kubernetes. Reading this book will empower you to take advantage of Apache Spark to optimize your data pipelines and teach you to craft modular and testable Spark applications. You will create and deploy mission-critical streaming spark applications in a low-stress environment that paves the way for your own path to production. What You Will Learn Simplify data transformation with Spark Pipelines and Spark SQL Bridge data engineering with machine learning Architect modular data pipeline applications Build reusable application components and libraries Containerize your Spark applications for consistency and reliability Use Docker and Kubernetes to deploy your Spark applications Speed up application experimentation using Apache Zeppelin and Docker Understand serializable structured data and data contracts Harness effective strategies for optimizing data in your data lakes Build end-to-end Spark structured streaming applications using Redis and Apache Kafka Embrace testing for your batch and streaming applications Deploy and monitor your Spark applications Who This Book Is For Professional software engineers who want to take their current skills and apply them to new and exciting opportunities within the data ecosystem, practicing data engineers who are looking for a guiding light while traversing the many challenges of moving from batch to streaming modes, data architects who wish to provide clear and concise direction for how best to harness and use Apache Spark within their organization, and those interested in the ins and outs of becoming a modern data engineer in today's fast-paced and data-hungry world

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/).

This book constitutes the refereed proceedings of the 14th International Conference on ICT Innovations 2022. Reshaping the Future Towards a New Normal, ICT Innovations 2022, held in Skopje, Macedonia, during September 29-October 1, 2022. The 14 full papers and 1 short papers included in this book were carefully reviewed and selected from 42 submissions. They were organized in topical sections as follows: theoretical foundations and distributed computing; artificial intelligence and deep learning; applied artificial intelligence; education; and medical informatics.

This two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.