This book constitutes the refereed proceedings of the 9th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2015, held in Puerto Varas, Chile, in December 2015. The 36 full papers presented together with 11 short papers were carefully reviewed and selected from 62 submissions. The papers are grouped in topical sections on adding intelligence for environment adaption; ambient intelligence for transport; human interaction and ambient intelligence; and ambient intelligence for urban areas.

This LNCS double volume LNCS 10069-10070 constitutes the refereed proceedings of the 10th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2016, which includes the International Work Conference on Ambient Assisted Living (IWAAL), and the International Conference on Am-bient Intelligence for Health (AmIHEALTH), held in Las Palmas de Gran Canaria, Spain, in November/December 2016. The 69 full papers presented together with 40 short papers and 5 doctoral consortium papers were carefully reviewed and selected from 145 submissions. UCAmI 2016 is focused on research topics related to ambient assisted living, internet of things, smart cities, ambient intelligence for health, human-computer interaction, ad-hoc and sensor networks, and security.

This book reports a set of novel research initiatives on ambient intelligence and ubiquitous computing that help researchers and practitioners identify recent advances, as well as the frontiers in these study domains. During the last two decades, both study areas have gained great interest in industry and academia due to the benefits of using smart solutions in various application domains, such as health care, ambient-assisted living, personal security and privacy, citizen participation, provision of urban services, and precision agriculture and farming. The articles included in this book report solutions and provide empirical results on their suitability to address problems and opportunities in these application domains. The articles also include discussions on how the proposals and their evaluation results inform the design of the next generation of ubiquitous and smart systems. Researchers, practitioners, and graduate students take advantage of this knowledge to address innovation and engineering aspects of smart and ubiquitous solutions for the next decade.

This book constitutes the second part of refereed proceedings of the 5th Computational Methods in Systems and Software 2021 (CoMeSySo 2021) proceedings. The real-world problems related to data science and algorithm design related to systems and software engineering are presented in this papers. Furthermore, the basic research’ papers that describe novel approaches in the data science, algorithm design and in systems and software engineering are included. The CoMeSySo 2021 conference is breaking the barriers, being held online. CoMeSySo 2021 intends to provide an international forum for the discussion of the latest high-quality research results

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.

The main objective of this book is to provide a multidisciplinary overview of methodological approaches, architectures, platforms, and algorithms for the realization of an Internet of Things (IoT)-based Smart Urban Ecosystem (SUE). Moreover, the book details a set of real-world applications and case studies related to specific smart infrastructures and smart cities, including structural health monitoring, smart urban drainage networks, smart grids, power efficiency, healthcare, city security, and emergency management. A Smart Urban Ecosystem (SUE) is a people-centric system of systems that involves smart city environments, applications, and infrastructures. SUEs require the close integration of cyber and physical components for monitoring, understanding and controlling the urban environment. In this context, the Internet of Things (IoT) offers a valuable enabling technology, as it bridges the gap between physical things and software components, and empowers cooperation between distributed, pervasive, and heterogeneous entities.

This book has a complete set of applications of artificial neural networks that allow the reader to gain experience about the new systems for implementing and developing artificial intelligence (AI) methods, which can run in several digital systems. On the other hand, the book shows the newest algorithms of artificial intelligence that provide a wide spectrum of research areas in which AI can be deployed. There are a lot of books that address AI applications. However, this book shows the newest applications reached according with the technological changes that are presented nowadays. Those changes drastically appear in digital systems or other parallel areas that allow to improve the performance of AI algorithms. Hence, sometimes, the AI algorithms have to be redesigned in order to run in microcontrollers or FPGAs. The topics covered generate a structured book, so it could be used as a textbook, but it is designed to be accessible to a wide audience interested in AI.

This proceeding book contains the contributions presented at the 3rd URV Doctoral workshop in Computer Science and Mathematics, held in November 2016. The main aim of this workshop is to promote the dissemination of the ideas, methods and results that are developed by the students of our PhD program.

This book focuses on the importance of human factors in optimizing the learning and training process. It reports on the latest research and best practices and discusses key principles of behavioral and cognitive science, which are extremely relevant to the design of instructional content and new technologies to support mobile and multimedia learning, virtual training and web-based learning, among others, as well as performance measurements, social and adaptive learning and many other types of educational technologies, with a special emphasis on those important in the corporate, higher education, and military training contexts. Based on the AHFE 2017 Conference on Human Factors in Training, Education, and Learning Sciences, held July 17–21, 2017 in Los Angeles, California, the book offers a timely perspective on the role of human factors in education. It highlights important new ideas and will foster new discussions on how to optimally design learning experiences.

Over the last decades, the interior of cars has been constantly changing. A promising, yet unexplored, modality are large stereoscopic 3D (S3D) dashboards. Replacing the traditional car dashboard with a large display and applying binocular depth cues, such a user interface (UI) could provide novel possibilities for research and industry. In this book, the author introduces a development environment for such a user interface. With it, he performed several driving simulator experiments and shows that S3D can be used across the dashboard to support menu navigation and to highlight elements without impairing driving performance. The author demonstrates that S3D has the potential to promote safe driving when used in combination with virtual agents during conditional automated driving. Further, he present results indicating that S3D navigational cues improve take-over maneuvers in conditional automated vehicles. Finally, investigating the domain of highly automated driving, he studied how users would interact with and manipulate S3D content on such dashboards and present a user-defined gesture set.