This book compiles a number of contributions originating from the KESE (Knowledge Engineering and Software Engineering) workshop series from 2005 to 2015. The idea behind the series was the realignment of the knowledge engineering discipline and its strong relation to software engineering, as well as to the classical aspects of artificial intelligence research. The book introduces symbiotic work combining these disciplines, such as aspect-oriented and agile engineering, using anti-patterns, and system refinement. Furthermore, it presents successful applications from different areas that were created by combining techniques from both areas.

Knowledge Management (KM) is strongly rooted in the discipline of Knowledge Engineering (KE), which in turn grew partly out of the artificial intelligence field. Despite their close relationship, however, many KM specialists have failed to fully recognize the synergy or acknowledge the power that KE methodologies, techniques, and tools hold for enh

FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to include Computational Intelligence for applied research. The contributions of the FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, with special focuses on data science and knowledge engineering for sensing decision support, both from the foundations and the applications points-of-view.

This book constitutes revised selected papers of the Second International Workshop on Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment, DEVOPS 2019, held at the Château de Villebrumier, France, in May 2019. The 15 papers presented in this volume were carefully reviewed and selected from 19 submissions. They cover a wide range of problems arising from DevOps and related approaches: current tools, rapid development-deployment processes, modeling frameworks, anomaly detection in software releases, DevDataOps, microservices, and related topics.

This book explores the critical role of acquisition, application, enhancement, and management of knowledge and human competence in the context of the largely digital and data/information dominated modern world. Whilst humanity owes much of its achievements to the distinct capability to learn from observation, analyse data, gain insights, and perceive beyond original realities, the systematic treatment of knowledge as a core capability and driver of success has largely remained the forte of pedagogy. In an increasingly intertwined global community faced with existential challenges and risks, the significance of knowledge creation, innovation, and systematic understanding and treatment of human competence is likely to be humanity's greatest weapon against adversity. This book was conceived to inform the decision makers and practitioners about the best practice pertinent to many disciplines and sectors. The chapters fall into three broad categories to guide the readers to gain insight from generic fundamentals to discipline-specific case studies and of the latest practice in knowledge and competence management.

This book constitutes selected, revised and extended papers of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2020, held in virtual format, in May 2020. The 19 revised full papers presented were carefully reviewed and selected from 96 submissions. The papers included in this book contribute to the understanding of relevant trends of current research on novel approaches to software engineering for the development and maintenance of systems and applications, specically with relation to: model-driven software engineering, requirements engineering, empirical software engineering, service-oriented software engineering, business process management and engineering, knowledge management and engineering, reverse software engineering, software process improvement, software change and configuration management, software metrics, software patterns and refactoring, application integration, software architecture, cloud computing, and formal methods.

To plan, build, monitor, maintain, and dispose of products and assets properly, maintenance and safety requirements must be implemented and followed. A lack of maintenance and safety protocols leads to accidents and environmental disasters as well as unexpected downtime that costs businesses money and time. With the arrival of the Fourth Industrial Revolution and evolving technological tools, it is imperative that safety and maintenance practices be reexamined. Applications and Challenges of Maintenance and Safety Engineering in Industry 4.0 is a collection of innovative research that addresses safety and design for maintenance and reducing the factors that influence and degrade human performance and that provides technological advancements and emergent technologies that reduce the dependence on operator capabilities. Highlighting a wide range of topics including management analytics, internet of things (IoT), and maintenance, this book is ideally designed for engineers, software designers, technology developers, managers, safety officials, researchers, academicians, and students.

This book constitutes the refereed proceedings of the 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2009, held in La Laguna, Canary Islands, Spain, in November 2011. The 50 revised full papers presented were carefully selected from 149 submissions. The papers are organized in topical sections on agent-based and multi-agent systems; machine learning; knowledge representation, logic, search and planning; multidisciplinary topics and applications; vision and robotics; soft computing; Web intelligence and information retrieval.

This book constitutes the proceedings of the 31st International Conference on Case-Based Reasoning Research and Development, ICCBR 2023, which took place in Aberdeen, UK, in July 2023. The 26 full papers included in this book were carefully reviewed and selected from 79 submissions. The papers have been organized in topical sections as follows: CBR and deep learning; representation and similarity; CBR and explainable AI; case base maintenance; adaptation: techniques and application; and case-based applications.