Kazumi Nakamatsu – författare

This book constitutes the thoroughly refereed papers of the workshops held at the 8th International Conference on New Trends in Model and Data Engineering, MEDI 2018, in Marrakesh, Morocco, in October 2018.

The 19 full and the one short workshop papers were carefully reviewed and selected from 50 submissions. The papers are organized according to the 4 workshops: International Workshop on Modeling, Verification and Testing of Dependable Critical Systems, DETECT 2018, Model and Data Engineering for Social Good Workshop, MEDI4SG 2018, Second International Workshop on Cybersecurity and Functional Safety in Cyber-Physical Systems, IWCFS 2018, International Workshop on Formal Model for Mastering Multifaceted Systems, REMEDY 2018.

Social, Ethical & Legal Aspects of Generative AI: Tools, Techniques, and Systems highlights the transformative exploration of the AI revolution. This groundbreaking discourse deciphers the nexus between cutting-edge generative AI tools and the societal framework that shapes their impact. Generative AI is more than a technological marvel; it’s a societal force reshaping industries, education, healthcare, and governance. Explore the ethical dilemmas, legal challenges, and innovative solutions driving its global adoption. This volume provides an insight into the latest innovations and state-of-the-art research in the fields of Social, Ethical & Legal Aspects of Generative AI, showcasing their potential to address AI''s profound societal implications. It spans a diverse array of topics, including:

By merging cutting-edge theoretical insights with practical applications, this volume provides researchers, practitioners, and students with the essential knowledge and tools to explore and advance within the dynamic field of Social, Ethical & Legal Aspects of Generative AI. Generative AI technologies bring transformative potential but also raise critical questions about privacy, bias, and accountability, demanding ethical frameworks to guide their development and deployment. The social implications of generative AI include its impact on employment, creativity, and human interactions, necessitating balanced approaches to ensure inclusivity and equity. Legal challenges surrounding generative AI focus on intellectual property, liability for AI-generated content, and adherence to global data protection laws. Addressing the ethical, social, and legal aspects of generative AI is essential to fostering innovation while safeguarding human rights and societal well-being. 

This book is written as an introduction to annotated logics. It provides logical foundations for annotated logics, discusses some interesting applications of these logics and also includes the authors'' contributions to annotated logics. The central idea of the book is to show how annotated logic can be applied as a tool to solve problems of technology and of applied science. The book will be of interest to pure and applied logicians, philosophers and computer scientists as a monograph on a kind of paraconsistent logic. But, the layman will also take profit from its reading.

This volume introduces new approaches in intelligent control area fromboth the viewpoints of theory and application. It consists of eleven contributionsby prominent authors from all over the world and an introductory chapter. Thisvolume is strongly connected to another volume entitled "New Approaches inIntelligent Image Analysis" (Eds. Roumen Kountchev and Kazumi Nakamatsu).

The chapters ofthis volume are self-contained and include summary, conclusion and futureworks. Some of the chapters introduce specific case studies of various intelligentcontrol systems and others focus on intelligent theory based control techniqueswith applications. A remarkable specificity of this volume is that threechapters are dealing with intelligent control based on paraconsistent logics.

Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the analysis of the modeling of the developed algorithms in different application areas.

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.