Marco Brambilla – författare

Interaction Flow Modeling Language describes how to apply model-driven techniques to the problem of designing the front end of software applications, i.e., the user interaction. The book introduces the reader to the novel OMG standard Interaction Flow Modeling Language (IFML). Authors Marco Brambilla and Piero Fraternali are authors of the IFML standard and wrote this book to explain the main concepts of the language. They effectively illustrate how IFML can be applied in practice to the specification and implementation of complex web and mobile applications, featuring rich interactive interfaces, both browser based and native, client side components and widgets, and connections to data sources, business logic components and services.

Interaction Flow Modeling Language provides you with unique insight into the benefits of engineering web and mobile applications with an agile model driven approach. Concepts are explained through intuitive examples, drawn from real-world applications. The authors accompany you in the voyage from visual specifications of requirements to design and code production. The book distills more than twenty years of practice and provides a mix of methodological principles and concrete and immediately applicable techniques.

Learn OMG's new IFML standard from the authors of the standard with this approachable reference Introduces IFML concepts step-by-step, with many practical examples and an end-to-end case example Shows how to integrate IFML with other OMG standards including UML, BPMN, CWM, SoaML and SysML Discusses how to map models into code for a variety of web and mobile platforms and includes many useful interface modeling patterns and best practices

The book deals with the propagation and absorption of high frequency waves in plasmas (hot, fully ionized gases). Research in this field is very active in controlled fusion research, i.e. the quest for energy from nuclear reactions similar to those going on within the sun, and in astrophysics, i.e. the study of space plasmas in the earth ionosphere, stars, and galaxies. The text collects in a structured and self-contained way the basic knowledge on the broad and varied behaviour of plasma waves, adopting the microscopic kinetic description of the plasma as unifying principle. The internal coherence of the theory is explicity stressed, and very interesting physical phenomena peculiar to plasmas, such as collisionless damping of waves, the development of stochasticity in the interactions of charged particles with electromagnetic waves, and nonlinear interactions between waves, are discussed in detail. The most common and useful approximations used in solving practical problems are derived as special cases from the more general kinetic approach, thereby clarifying their meaning and domain of applicability. This exposition should be useful to plasma physicists both as an introduction and a reference to this field of research. Because of its multi-disciplinary aspects it might also be of interest to people specializing in kinetic theory, classical electromagnetism, or classical mechanics, as a nontrivial example of application of the methods of these fields to the unconventional plasma medium.

Bi-directionality in Human-AI Collaborative Systems investigates the foundations, metrics, and applications of human-machine systems, along with the legal ramifications of autonomy, including standards, trust by the public, and bidirectional trust by users and AI systems. The book addresses the challenges in creating synergistic human and AI-based autonomous system-of-systems by focusing on the underlying challenges associated with bi-directionality. Chapters cover advances in LLMs, logic, machine learning choices, the development of standards, as well as human-centered approaches to autonomous human-machine teams. This is a valuable resource for world-class researchers and engineers who are theorizing on, designing, and developing autonomous systems.It will also be useful for government scientists, business leaders, social scientists, philosophers, regulators and legal experts interested in the impact of autonomous human-machine teams and systems.Investigates the challenges in creating synergistic human and AI-based autonomous system-of-systemsIntegrates concepts from a wide range of disciplines, including applied and theoretical AI, quantum mechanics, social sciences, and systems engineeringPresents debates, models, and concepts of mutual dependency for autonomous human-machine teams, challenging assumptions across AI, systems engineering, data science, and quantum mechanics

Generative AI Risks and Benefits within Human-Machine Teams delves into the foundational principles, metrics, and applications of human-machine systems, addressing the legal ramifications of autonomy, public trust, and bidirectional AI systems. This book brings together world-class researchers, engineers, philosophers, social scientists, and other experts to discuss the critical aspects of generative AI, its risks, and benefits. The authors aim to establish a shared context between humans and machines, regulators, the public, and other stakeholders, exploring how these systems impact targeted audiences and society at large. The book combines human-centered computing and autonomous human-machine teams to provide a comprehensive understanding of generative AI's potential and challenges. The book is structured to guide readers through a detailed exploration of these topics. It begins with an introduction to the core concepts of human-machine collaboration and the next generation of large language models. The discussion then moves to practical applications, such as Human-AI collaboration for energy communities, autonomous human-machine team advances, and human-AI collaboration in the design process. The book also delves into adaptive collaboration patterns for logic modeling, assessing multimodal large language models in resolving visual ambiguities, and developing team context-aware collaborative AI assistants. Additionally, it explores the taxonomy of teamwork support for collaborative AI efforts, trust management in human-AI collaboration, and provides a distributed teaming testbed for human-machine collaboration in space missions. Finally, it addresses the limits of classical team science in interdependent human-machine teams. Generative AI Risks and Benefits within Human-Machine Teams is an essential resource for computer scientists and systems engineers focused on designing and theorizing about the development of autonomous systems. By providing in-depth insights into the integration of generative AI within human-machine teams, this book equips professionals with the knowledge to navigate the complexities of AI autonomy, enhance collaboration, and address the ethical and technical challenges associated with these advanced technologies.Explores core concepts and practical applications of human-machine collaborationAddresses ethical, legal, and trust issues in generative AI developmentOffers insights into adaptive collaboration patterns and teamwork supportProvides frameworks for integrating generative AI within autonomous systems

The most prominent Web applications in use today are data-intensive. Scores of database management systems across the Internet access and maintain large amounts of structured data for e-commerce, on-line trading, banking, digital libraries, and other high-volume sites.Developing and maintaining these data-intensive applications is an especially complex, multi-disciplinary activity, requiring all the tools and techniques that software engineering can provide. This book represents a breakthrough for Web application developers. Using hundreds of illustrations and an elegant intuitive modeling language, the authors—all internationally-known database researchers—present a methodology that fully exploits the conceptual modeling approach of software engineering, from idea to application. Readers will learn not only how to harness the design technologies of relational databases for use on the Web, but also how to transform their conceptual designs of data-intensive Web applications into effective software components.

The workshop committee accepted three workshops for publication in this volume: 5th International Workshop on Knowledge Discovery on the Web (KDWEB 2019), Second International Workshop on Maturity of Web Engineering Practices (MATWEP 2019), International Workshop on Data Science and Knowledge Graph (DSKG 2019).

This book constitutes the proceedings of the 21st International Conference on Web Engineering, ICWE 2021, which was supposed to be held in Biarritz, France, in May 2021. The papers were organized in topical sections named: Semantic Web; Web modeling and engineering; Web big data and data analytics; Web user interfaces;

This book discusses how model-based approaches can improve the daily practice of software professionals. This is known as Model-Driven Software Engineering (MDSE) or, simply, Model-Driven Engineering (MDE).MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g., due to the convergence of software development and business analysis.The aim of this book is to provide you with an agile and flexible tool to introduce you to the MDSE world, thus allowing you to quickly understand its basic principles and techniques and to choose the right set of MDSE instruments for your needs so that you can start to benefit from MDSE right away.The book is organized into two main parts.The first part discusses the foundations of MDSE in terms of basic concepts (i.e., models and transformations), driving principles, application scenarios, and current standards, like the well-known MDA initiative proposed by OMG (Object Management Group) as well as the practices on how to integrate MDSE in existing development processes.The second part deals with the technical aspects of MDSE, spanning from the basics on when and how to build a domain-specific modeling language, to the description of Model-to-Text and Model-to-Model transformations, and the tools that support the management of MDSE projects.The second edition of the book features:a set of completely new topics, including: full example of the creation of a new modeling language (IFML), discussion of modeling issues and approaches in specific domains, like business process modeling, user interaction modeling, and enterprise architecturecomplete revision of examples, figures, and text, for improving readability, understandability, and coherencebetter formulation of definitions, dependencies between concepts and ideasaddition of a complete index of book contentIn addition to the contents of the book, more resources are provided on the book's website http://www.mdse-book.com, including the examples presented in the book.

Search computing, which has evolved from service computing, focuses on building the answers to complex search queries by interacting with a constellation of cooperating search services, using ranking and joining of results as the dominant factors for service composition. The field is multi-disciplinary in nature, and takes advantage of contributions from other research areas such as knowledge representation, human-computer interfaces, psychology, sociology, economics and legal sciences.The book is divided into three parts. The first part includes some visionary contributions on the latest trends in search, which is becoming increasingly task-oriented and is starting to use ontological knowledge in order to manage complex queries. The second part explores background and related technologies, which can be considered as parallel fields of research, useful both for setting the theoretical premises for search computing and for providing a technological framework for building search computing systems and applications. The third part delves into the conceptual and technological problems and issues arising when dealing with search computing as a new search paradigm. It provides a unified view of the results of the Search Computing project as achieved exactly one year after its starting date.

Search computing, which has evolved from service computing, focuses on building the answers to complex search queries by interacting with a constellation of cooperating search services, using the ranking and joining of results as the dominant factors for service composition. The field is multi-disciplinary in nature and takes advantage of contributions from other research areas such as knowledge representation, human-computer interfaces, psychology, sociology, economics, and legal sciences. This book, the second in the Search Computing series, describes the evolution of theories, technologies, and methods related to search computing. The book has been divided into eight parts, reflecting the main research directions within the Search Computing project. The parts focus on: search as an information exploration task; interaction design issues when dealing with multi-domain search results; modeling and semantic description of search services; the rank-join problem; query processing techniques and architectures; tools and mashups for application development; the application of search computing to bio-informatics; and the exploitation potentials of project results.

This book constitutes the refereed proceedings of the 12th International Conference on Web Engineering, ICWE 2012, held in Berlin, Germany, in July 2012. The 20 revised full papers and 15 short papers were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on social networks and collaboration, tagging, personalization and personal systems, search, Web modeling, AJAX and user interfaces, Web services, Web crawling, and Web and linked data management. The book also includes 6 poster papers, 12 demos and 5 tutorials.

Search computing, which has evolved from service computing, focuses on building the answers to complex search queries by interacting with a constellation of cooperating search services, using the ranking and joining of results as the dominant factors for service composition.

Web Information Retrieval