This book is a specialized monograph on interpolation and definability, a notion central in pure logic and with significant meaning and applicability in all areas where logic is applied, especially computer science, artificial intelligence, logic programming, philosophy of science and natural language. Suitable for researchers and graduate students in mathematics, computer science and philosophy, this is the latest in the prestigous world-renowned Oxford Logic Guides, which contains Michael Dummet's Elements of intuitionism (second edition), J. M. Dunn and G. Hardegree's Algebraic Methods in Philosophical Logic, H. Rott's Change, Choice and Inference: A Study of Belief Revision and Nonmonotonic Reasoning, P. T. Johnstone's Sketches of an Elephant: A Topos Theory Compendium: Volumes 1 and 2, and David J. Pym and Eike Ritter's Reductive Logic and Proof Search: Proof theory, semantics and control.

This book explores the latest and most relevant topics in the field of computational bioengineering and bioinformatics, with a particular focus on patient-specific, disease-progression modeling. It covers computational methods for cardiovascular disease prediction, with an emphasis on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for disease characterization, and recent advances in areas such as biomechanics, cardiovascular engineering, patient-specific modeling, population-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and dental biomechanics, tissue and cell engineering, computational chemistry and high-performance computing. As such, it is a valuable resource for researchers, medical and bioengineering students, and medical device and software experts

This book presents the proceedings of the KES International Conferences on Innovation in Medicine and Healthcare (KES-InMed-19), held in Split, Croatia, on June 17-19, 2020. Covering a number of key areas, including digital IT architecture in healthcare; advanced ICT for medicine and healthcare; biomedical engineering, trends, research and technologies; and healthcare support systems, this book is a valuable resource for researchers, managers, industrialists and anyone wishing to gain an overview of the latest research in these fields.

This book enriches our views on representation and deepens our understanding of its different aspects. It arises out of several years of dialog between the editors and the authors, an interdisciplinary team of highly experienced researchers, and it reflects the best contemporary view of representation and reality in humans, other living beings, and intelligent machines. Structured into parts on the cognitive, computational, natural sciences, philosophical, logical, and machine perspectives, a theme of the field and the book is building and presenting networks, and the editors hope that the contributed chapters will spur understanding and collaboration between researchers in domains such as computer science, philosophy, logic, systems theory, engineering, psychology, sociology, anthropology, neuroscience, linguistics, and synthetic biology.

This volume presents the second part of the proceedings of the Mediterranean Conference on Information & Communication Technologies (MedICT 2015), which was held at Saidia, Morocco during 7-9 May, 2015. MedICT provides an excellent international forum to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development. The conference has also a special focus on enabling technologies for societal challenges, and seeks to address multidisciplinary challenges in Information & Communication Technologies such as health, demographic change, wellbeing, security and sustainability issues. The proceedings publish high quality papers which are closely related to the various theories, as well as emerging and practical applications of particular interest to the ICT community. This second volume provides a compact yet broad view of recent developments in Data, Systems, Services and Education, and covers recent research areas in the field including Control Systems, Software Engineering, Data Mining and Big Data, ICT for Education and Support Activities, Networking, Cloud Computing and Security, ICT Based Services and Applications, Mobile Agent Systems, Software Engineering, Data Mining and Big Data, Online Experimentation & Artificial Intelligence in Education, Networking, Cloud Computing and Security, ICT Based Education and Services ICT Challenges and Applications, Advances in ICT Modeling and Design ICT Developments.

This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.

In an evaluation of the strengths and limitations of artificial intelligence in a number of intellectual domains, Wagman draws comparisons with human cognitive ability in those domains, and assesses its role as a theoretical model, as a collaborator, or as a competitor of the human mind. This book distinguishes itself in its structured and detailed account of advancing intellectual developments in the science of artificial intelligence as opposed to a highly technical or vague philosophical treatment of the topic.

This book provides an overview of the problems involved in engineering scalable, elastic, and cost-efficient cloud computing services and describes the CloudScale method - a description of rescuing tools and the required steps to exploit these tools. It allows readers to analyze the scalability problem in detail and identify scalability anti-patterns and bottlenecks within an application. With the CloudScale method, software architects can analyze both existing and planned IT services. The method allows readers to answer questions like: * With an increasing number of users, can my service still deliver acceptable quality of service? * What if each user uses the service more intensively? Can my service still handle it with acceptable quality of service? * What if the number of users suddenly increases? Will my service still be able to handle it? * Will my service be cost-efficient? First the book addresses the importance of scalability, elasticity, and cost-efficiency as vital quality-related attributes of modern cloud computing applications. Following a brief overview of CloudScale, cloud computing applications are then introduced in detail and the aspects that need to be captured in models of such applications are discussed. In CloudScale, these aspects are captured in instances of the ScaleDL modeling language. Subsequently, the book describes the forward engineering part of CloudScale, which is applicable when developing a new service. It also outlines the reverse and reengineering parts of CloudScale, which come into play when an existing (legacy) service is modified. Lastly, the book directly focuses on the needs of both business-oriented and technical managers by providing guidance on all steps of implementing CloudScale as well as making decisions during that implementation. The demonstrators and reference projects described serve as a valuable starting point for learning from experience. This book is meant for all stakeholders interested in delivering scalable, elastic, and cost-efficient cloud computing applications: managers, product owners, software architects and developers alike. With this book, they can both see the overall picture as well as dive into issues of particular interest.

This book offers a comprehensive reference guide to intelligence systems in environmental management. It provides readers with all the necessary tools for solving complex environmental problems, where classical techniques cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including ant colony, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making tools, particle swarm optimization, agent-based modelling, artificial neural networks, simulated annealing, Tabu search, fuzzy multi-objective optimization, fuzzy rules, support vector machines, fuzzy cognitive maps, cumulative belief degrees, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on complex environmental problems. Moreover, by extending all the main aspects of classical environmental solution techniques to its intelligent counterpart, the book presents a dynamic snapshot on the field that is expected to stimulate new directions and stimulate new ideas and developments.

Our society continues to depend upon systems that are built in a way that they end up being inflexible and intolerant to change. Therefore there is an urgent need to investigate innovations and approaches to the management of adaptive and dependable systems. These studies are usually implemented through design, development, and the evaluation of techniques and models to structure computer systems as adaptive systems. Innovations and Approaches for Resilient and Adaptive Systems is a comprehensive collection of knowledge on increasing the notions and models in adaptive and dependable systems. This book aims to enhance the awareness of the role of adaptability and resilience in system environments for researchers, practitioners, educators, and professionals alike.

This volumes consists of 59 peer-reviewed papers, presented at the International Conference on Sustainable Design and Manufacturing (SDM-16) held in Chania, Crete Greece in April 2016. Leading-edge research into sustainable design and manufacturing aims to enable the manufacturing industry to grow by adopting more advanced technologies, and at the same time improve its sustainability by reducing its environmental impact. SDM-16 covers a wide range of topics from sustainable product design and service innovation, sustainable process and technology for the manufacturing of sustainable products, sustainable manufacturing systems and enterprises, decision support for sustainability, and the study of societal impact of sustainability including research for circular economy. Application areas are wide and varied. The book will provide an excellent overview of the latest research and development in the area of Sustainable Design and Manufacturing.

This book presents a comprehensive discussion on the characterization of vagueness in pictures. It reports on how the problem of representation of images has been approached in scientific practice, highlighting the role of mathematical methods and the philosophical background relevant for issues such as representation, categorization and reasoning. Without delving too much into the technical details, the book examines and defends different kinds of values of fuzziness based on a complex approach to categorization as a practice, adopting conceptual and empirical suggestions from different fields including the arts. It subsequently advances criticisms and provides suggestions for interpretation and application. By describing a cognitive framework based on fuzzy, rough and near sets, and discussing all of the relevant mathematical and philosophical theories for the representation and processing of vagueness in images, the book offers a practice-oriented guide to fuzzy visual reasoning, along with novel insights into the field of interpreting and thinking with fuzzy pictures and fuzzy data.

Semantic-based visual information retrieval is one of the most challenging research directions of content-based visual information retrieval. It provides efficient tools for access, interaction, searching, and retrieving from collected databases of visual media. Building on research from over 30 leading experts from around the world, ""Semantic-Based Visual Information Retrieval"" presents state-of-the-art advancements and developments in the field, and also brings a selection of techniques and algorithms about semantic-based visual information retrieval. It covers many critical issues, such as: multi-level representation and description, scene understanding, semantic modeling, image and video annotation, humancomputer interaction, and more. ""Semantic-Based Visual Information Retrieval"" also explains detailed solutions to a wide range of practical applications. Researchers, students, and practitioners will find this comprehensive and detailed volume to be a roadmap for applying suitable methods in semantic-based visual information retrieval.

This book explores several branches of the social sciences and their perspectives regarding their relations with decision-making processes: computer science, education, linguistics, sociology, and management. The decision-making process in social contexts is based on the analysis of sound alternatives using evaluative criteria. Therefore, this process is one that can be rational or irrational, and can be based on knowledge and/or beliefs. A decision-making process always produces a final decision, which may or may not imply prompt action, and increases the chances of choosing the best possible alternative. The book is divided into four main parts. The concepts covered in the first part, on computer science, explore how the rise of algorithms and the growth in computing power over the years can influence decision-making processes. In the second part, some traditional and innovative ideas and methods used in education are presented: compulsory schooling, inclusive schools, higher education, etc. In turn, the third part focuses on linguistics aspects, and examines how progress is manifested in language. The fourth part, on sociology, explores how society can be influenced by social norms, human interactions, culture, and religion. Management, regarded as a science of the decision-making process, is explored in the last part of this book. Selected organizations' strategies, objectives and resources are presented, e.g., human resources, financial resources, and technological resources. The book gathers and presents, in a concise format, a broad range of aspects regarding the decision-making process in social contexts, making it a valuable and unique resource for the scientific community.

This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership - while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively.

The discovery in 2012 of the Higgs boson at the Large Hadron Collider (LHC) represents a milestone for the Standard Model (SM) of particle physics. Most of the SM Higgs production and decay rates have been measured at the LHC with increased precision. However, despite its experimental success, the SM is known to be only an effective manifestation of a more fundamental description of nature. The scientific research at the LHC is strongly focused on extending the SM by searching, directly or indirectly, for indications of New Physics. The extensive physics program requires increasingly advanced computational and algorithmic techniques. In the last decades, Machine Learning (ML) methods have made a prominent appearance in the field of particle physics, and promise to address many challenges faced by the LHC. This thesis presents the analysis that led to the observation of the SM Higgs boson decay into pairs of bottom quarks. The analysis exploits the production of a Higgs boson associated with a vector boson whose signatures enable efficient triggering and powerful background reduction. The main strategy to maximise the signal sensitivity is based on a multivariate approach. The analysis is performed on a dataset corresponding to a luminosity of 79.8/fb collected by the ATLAS experiment during Run-2 at a centre-of-mass energy of 13 TeV. An excess of events over the expected background is found with an observed (expected) significance of 4.9 (4.3) standard deviation. A combination with results from other \Hbb searches provides an observed (expected) significance of 5.4 (5.5). The corresponding ratio between the signal yield and the SM expectation is 1.01 +- 0.12 (stat.)+ 0.16-0.15(syst.). The 'observation' analysis was further extended to provide a finer interpretation of the V H(H bb) signal measurement. The cross sections for the VH production times the H bb branching ratio have been measured in exclusive regions of phase space. These measurements are used to search for possible deviations from the SM with an effective field theory approach, based on anomalous couplings of the Higgs boson. The results of the cross-section measurements, as well as the constraining of the operators that affect the couplings of the Higgs boson to the vector boson and the bottom quarks, have been documented and discussed in this thesis. This thesis also describes a novel technique for the fast simulation of the forward calorimeter response, based on similarity search methods. Such techniques constitute a branch of ML and include clustering and indexing methods that enable quick and efficient searches for vectors similar to each other. The new simulation approach provides optimal results in terms of detector resolution response and reduces the computational requirements of a standard particles simulation.

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.

This book is inspired by the contemporary fascination with virtual reality and growing presence of this type of technology in everyday life. It explores the ways in which virtual reality evokes illusory transformation responses. The power of virtual reality is in making the mediation by technology in these experiences appear irrelevant to cognitive processes, so much so that it is often assumed that skills acquired in virtual environments are generally transferable to the physical world. However, cognition is affected by virtual reality technology, which is reflected in issues related to virtual embodiment, choice of spatial strategies, differences in neural and electrophysiological patterns associated with movement processing when navigating virtual vs. physical environments, and, at least to some extent, in virtual proxemics. In addition to spatial cognition, the book explores the sense of self in virtual reality, social interaction and virtual togetherness, action and motor cognition, calling to mind debates from philosophy, psychology, and cognitive neuroscience.

This book is intended to help management and other interested parties such as engineers, to understand the state of the art when it comes to the intersection between AI and Industry 4.0 and get them to realise the huge possibilities which can be unleashed by the intersection of these two fields. We have heard a lot about Industry 4.0, but most of the time, it focuses mainly on automation. In this book, the authors are going a step further by exploring advanced applications of Artificial Intelligence (AI) techniques, ranging from the use of deep learning algorithms in order to make predictions, up to an implementation of a full-blown Digital Triplet system. The scope of the book is to showcase what is currently brewing in the labs with the hope of migrating these technologies towards the factory floors. Chairpersons and CEOs must read these papers if they want to stay at the forefront of the game, ahead of their competition, while also saving huge sums of money in the process.

This book proposes several commonly used interval-valued solution concepts of interval-valued cooperative games with transferable utility. It thoroughly investigates these solutions, thereby establishing the properties, models, methods, and applications. The first chapter proposes the interval-valued least square solutions and quadratic programming models, methods, and properties. Next, the satisfactory-degree-based non-linear programming models for computing interval-valued cores and corresponding bisection algorithm are explained. Finally, the book explores several simplification methods of interval-valued solutions: the interval-valued equal division and equal surplus division values; the interval-valued Shapley, egalitarian Shapley, and discounted Shapley values; the interval-valued solidarity and generalized solidarity values; and the interval-valued Banzhaf value. This book is designed for individuals from different fields and disciplines, such as decision science, game theory, management science, operations research, fuzzy sets or fuzzy mathematics, applied mathematics, industrial engineering, finance, applied economics, expert system, and social economy as well as artificial intelligence. Moreover, it is suitable for teachers, postgraduates, and researchers from different disciplines: decision analysis, management, operations research, fuzzy mathematics, fuzzy system analysis, applied mathematics, systems engineering, project management, supply chain management, industrial engineering, applied economics, and hydrology and water resources.

This PALO volume constitutes the Proceedings of the 19th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015), held in Bangkok, Thailand, November 22-25, 2015. The IES series of conference is an annual event that was initiated back in 1997 in Canberra, Australia. IES aims to bring together researchers from countries of the Asian Pacific Rim, in the fields of intelligent systems and evolutionary computation, to exchange ideas, present recent results and discuss possible collaborations. Researchers beyond Asian Pacific Rim countries are also welcome and encouraged to participate. The theme for IES 2015 is "Transforming Big Data into Knowledge and Technological Breakthroughs". The host organization for IES 2015 is the School of Information Technology (SIT), King Mongkut's University of Technology Thonburi (KMUTT), and it is technically sponsored by the International Neural Network Society (INNS). IES 2015 is collocated with three other conferences; namely, The 6th International Conference on Computational Systems-Biology and Bioinformatics 2015 (CSBio 2015), The 7th International Conference on Advances in Information Technology 2015 (IAIT 2015) and The 10th International Conference on e-Business 2015 (iNCEB 2015), as a major part of series of events to celebrate the SIT 20th anniversary and the KMUTT 55th anniversary.

This book is an up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches. This book is a great source to researcher, graduate students, and bachelor students who gain project about structural optimization. Differently from the academic use, the chapter that emphasizes different scopes and methods can take the interest and help engineer working in design and production of structural engineering projects.

The book covers computational statistics, its methodologies and applications for IoT device. It includes the details in the areas of computational arithmetic and its influence on computational statistics, numerical algorithms in statistical application software, basics of computer systems, statistical techniques, linear algebra and its role in optimization techniques, evolution of optimization techniques, optimal utilization of computer resources, and statistical graphics role in data analysis. It also explores computational inferencing and computer model's role in design of experiments, Bayesian analysis, survival analysis and data mining in computational statistics.

This book introduces readers to numerous multiplicative inverse functional equations and their stability results in various spaces. This type of functional equation can be of use in solving many physical problems and also has significant relevance in various scientific fields of research and study. In particular, multiplicative inverse functional equations have applications in electric circuit theory, physics, and relations connecting the harmonic mean and arithmetic mean of several values. Providing a wealth of essential insights and new concepts in the field of functional equations, the book is chiefly intended for researchers, graduate schools, graduate students, and educators, and can also used for seminars in analysis covering topics of functional equations.