Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is a 2-part book set which presents discoveries, innovative ideas, concepts, practical solutions, and novel applications of Human-Computer Interaction (HCI) and related disciplines such as artificial intelligence, machine learning, data mining, computer vision, and natural language processing. The book provides readers with information about HCI trends which are shaping the future of smart, interconnected urban and industrial environments. This is the second of the two volumes of the edited books. The chapters of this volume cover topics like ERP usability in educational settings, the role of AI in enhancing HCI functionality, usability of local mobile healthcare apps, analyzing the usage of social media apps and a review of HCI systems for disaster management and systems for tracking traffic safety violations. Contributions are authored by experts and scientists in the field of HCI and its interrelated disciplines from 9 different countries – Albania, China, India, Indonesia, Nigeria, Pakistan, Spain, the United Kingdom, and the United States. Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments is an informative reference for scientists, researchers, and developers in both academia and industry who wish to learn, design, implement, and apply these emerging technologies in HCI in different sectors, with the goal of realizing futuristic technology-driven living and functional smart cities and environments.

With the explosion of video and image data available on the Internet, desktops and mobile devices, multimedia search has gained immense importance. Moreover, mining semantics and other useful information from large-scale multimedia data to facilitate online and local multimedia content analysis, search, and other related applications has also gained an increasing attention from the academia and industry. The rapid increase of multimedia data has brought new challenges to multimedia content analysis and multimedia retrieval, especially in terms of scalability. While on the other hand, large-scale multimedia data has also provided new opportunities to address these challenges and other conventional problems in multimedia analysis. The massive associated metadata, context and social information available on the Internet, desktops and mobile devices, and the large number of grassroots users, are a valuable resource that could be leveraged to solve the these difficulties. This is the first reference book on the subject of internet multimedia search and mining and it will be extremely useful for graduates, researchers and working professionals in the field of information technology and multimedia content analysis.

Introduction to Computer Data Representation introduces readers to the representation of data within computers. Starting from basic principles of number representation in computers, the book covers the representation of both integer and floating point numbers, and characters or text. It comprehensively explains the main techniques of computer arithmetic and logical manipulation. The book also features chapters covering the less usual topics of basic checksums and ‘universal’ or variable length representations for integers, with additional coverage of Gray Codes, BCD codes and logarithmic representations. The description of character coding includes information on both MIME and Unicode formats. Introduction to Computer Data Representation also includes historical aspects of data representation, explaining some of the steps that developers took (and the mistakes they made) that led to the present, well-defined and accepted standards of data representation techniques. The book serves as a primer for advanced computer science graduates and a handy reference for anyone wanting to learn about numbers and data representation in computers.

Introduction to Sensors in IoT and Cloud Computing Applications provides information about sensors and their applications. Readers are first introduced to the concept of small instruments and their application as sensors. The chapters which follow explain Internet of Things (IoT) architecture while providing notes on the implementation, demonstration and related issues of IoT systems. The book continues to explore the topic by providing information about sensor-cloud infrastructure, mobile cloud, fog computing (an extension of cloud computing that takes cloud computing to the cutting-edge of networking where data is produced) and integration of IoT devices with cloud computing. The book also presents notes on the taxonomy of fog-computing systems. The six chapters in this book provide essential information for general readers, and students of computer science to understand the basics of cloud computing networks, related concepts and applications.

Model Driven development (MDD) is a software and systems development model that involves the application of visual modeling principles and best practices.

The surge of multicore processors coming into the market and on users’ desktops has made parallel computing the focus of attention once again. This time, however, it is led by the industry, which ensures that multicore computing is here to stay. Nevertheless, there is still so much research work to be done in multicore hardware-software designs before consumer applications can leverage the benefits of this new paradigm. This ebook is being put forward as a platform for immediate collection of state-of-the-art technologies in both hardware and software designs for multicore computing. With the burgeoning prevalence of multicore processors in embedded systems, real-time systems, multimedia systems, bioinformatics systems, network systems, to list a few, this ebook attempts to cover the design and verification issues related to different application domains as a singular source of reference to the state-of-the-art techniques in multicore processor design and software programming that covers multiple application domains. This ebook will be of immense help to system and software engineers, including both experts and non-experts in parallel computing.

Multi-Objective Optimization in Theory and Practice is a traditional two-part approach to solving multi-objective optimization (MOO) problems namely the use of classical methods and evolutionary algorithms. This first book is devoted to classical methods including the extended simplex method by Zeleny and preference-based techniques. This part covers three main topics through nine chapters. The first topic focuses on the design of such MOO problems, their complexities including nonlinearities and uncertainties, and optimality theory. The second topic introduces the founding solving methods including the extended simplex method to linear MOO problems and weighting objective methods. The third topic deals with particular structures of MOO problems, such as mixed-integer programming, hierarchical programming, fuzzy logic programming, and bimatrix games. Multi-Objective Optimization in Theory and Practice is a user-friendly book with detailed, illustrated calculations, examples, test functions, and small-size applications in Mathematica® (among other mathematical packages) and from scholarly literature. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science, and mathematics degree programs.

Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of solutions, metaheuristic algorithms, genetic search algorithms and evolution strategies, decomposition algorithms, hybridization of different metaheuristics, and many-objective (more than three objectives) optimization and parallel computation. The final section of the book presents information about the design and types of fifty test problems for which the Pareto-optimal front is approximated. For each of them, the package NSGA-II is used to approximate the Pareto-optimal front. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science and mathematics degree programs.

Agent technology has generated lots of excitement in the past decade. Currently, multi-agent systems (MAS) composed of autonomous agents representing individuals or organizations and capable of reaching mutually beneficial agreements through negotiation and argumentation are becoming increasingly important and pervasive. Research on both automated negotiation and argumentation in MAS has a vigorous, exciting tradition. However, efforts to integrate both areas have received only selective attention in the academia and the practitioner literature. A symbiotic relationship could significantly strengthen each area’s progress and trigger new R&D challenges and prospects toward the advancement of automated negotiators and argumentation tools. Negotiation and Argumentation in Multi-Agent Systems presents the current state-of-the-art on the theory and practice of automated negotiation and argumentation in MAS. The eBook encourages the interaction between these two areas in data modelling and attempts to converge them toward mutual enhancement and synergism. Equally, the monograph brings together researchers and industry practitioners specialized in these areas to share R&D results and discuss existing and emerging theoretical and applied problems. This book is intended as a textbook for graduate courses and a reference book for researchers, advanced-level students in Computers Science, and IT practitioners.

This book dives into the heart of how to design distributed control architectures for heterogeneous teams of humans, robots, and automated systems, enabling them to achieve greater cooperation and autonomy through the use of network technologies. It provides a wide range of practical, proven strategies for pervasive communication and collaborative problem solving abilities of humans, robots, and their environments. Each chapter consists of a presentation of findings from the latest research in networked robots and ambient intelligence. The chapters also detail how to allow robots to achieve universal access to the extended functionality of the environment that brings various cost effective services to those in need. Readers can envision a realistic view of what can be expected from a networked human robot cooperative environment in the next decade.