This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book's chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval.The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

This book provides a pioneering approach to modeling the human diabetic patient using a software agent. It is based on two MASc (Master of Applied Science) theses: one looking at the evolution of the patient agent in time, and another looking the interaction of the patient agent with the healthcare system. It shows that the software agent evolves in a manner analogous to the human patient and exhibits typical attributes of the illness such as reacting to food consumption, medications, and activity. This agent model can be used in a number of different ways, including as a prototype for a specific human patient with the purpose of helping to identify when that patient's condition deviates from normal variations. The software agent can also be used to study the interaction between the human patient and the health care system. This book is of interest to anyone involved in the management of diabetic patients or in societal research into the management of diabetes. The diabetic patient agent was developed using the Ackerman model for diabetes, but this model can be easily adapted for any other model subject with the necessary physiological data to support that model.

The Intelligent Techniques for Planning presents a number of modern approaches to the area of automated planning. These approaches combine methods from classical planning such as the construction of graphs and the use of domain-independent heuristics with techniques from other areas of artificial intelligence. This book discuses, in detail, a number of state-of-the-art planning systems that utilize constraint satisfaction techniques in order to deal with time and resources, machine learning in order to utilize experience drawn from past runs, methods from knowledge systems for more expressive representation of knowledge and ideas from other areas such as Intelligent Agents. Apart from the thorough analysis and implementation details, each chapter of the book also provides extensive background information about its subject and presents and comments on similar approaches done in the past.

The volume "Modern Information Processing: From Theory to Applications," edited by Bernadette Bouchon-Meunier, Giulianella Coletti and Ronald Yager, is a collection of carefully selected papers drawn from the program of IPMU'04, which was held in Perugia, Italy.
The book represents the cultural policy of IPMU conference which is not focused on narrow range of methodologies, but on the contrary welcomes all the theories for the management of uncertainty and aggregation of information in intelligent systems, providing a medium for the exchange of ideas between theoreticians and practitioners in these and related areas.
The book is composed by 7 sections:
UNCERTAINTY
PREFERENCES
CLASSIFICATION AND DATA MINING
AGGREGATION AND MULTI-CRITERIA DECISION MAKING
KNOWLEDGE REPRESENTATION
The book contributes to enhancement of our ability to deal effectively with uncertainty in all of its manifestations.
The book can help to build brigs among theories and methods methods for the management of uncertainty.
The book addresses issues which have a position of centrality in our information-centric world.
The book presents interesting results devoted to representing knowledge: the goal is to capture the subtlety of human knowledge (richness) and to allow computer manipulation (formalization).
The book contributes to the goal: an efficient use of the information for a good decision strategy.
APPLIED DOMAINS
. The book contributes to enhancement of our ability to deal effectively with uncertainty in all of its manifestations.
. The book can help to build brigs among theories and methods methods for the management of uncertainty.
. The book addresses issues which have a position of centrality in our information-centric world.
. The book presents interesting results devoted to representing knowledge: the goal is to capture the subtlety of human knowledge (richness) and to allow computer manipulation (formalization).
. The book contributes to the goal: an efficient use of the information for a good decision strategy."

This book features selected papers presented at the 14th International Conference on Electromechanics and Robotics 'Zavalishin's Readings' - ER(ZR) 2019, held in Kursk, Russia, on April 17-20, 2019. The contributions, written by professionals, researchers and students, cover topics in the field of automatic control systems, electromechanics, electric power engineering and electrical engineering, mechatronics, robotics, automation and vibration technologies. The Zavalishin's Readings conference was established as a tribute to the memory of Dmitry Aleksandrovich Zavalishin (1900-1968) - a Russian scientist, corresponding member of the USSR Academy of Sciences, and founder of the school of valve energy converters based on electric machines and valve converters energy. The first conference was organized by the Institute of Innovative Technologies in Electromechanics and Robotics at the Saint Petersburg State University of Aerospace Instrumentation in 2006. The 2019 conference was held with the XIII International Scientific and Technical Conference "Vibration 2019", and was organized by Saint Petersburg State University of Aerospace Instrumentation (SUAI), Saint Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) and the Southwest State University (SWSU) in with cooperation Russian Foundation for Basic Research (project No. 19-08-20021).

This book discusses vehicular communication systems, IoT, intelligent transportation systems and the Internet of Vehicles, and also introduces destination marketing in a structured manner. It is primarily intended for research students interested in emerging technologies for connected Internet of Vehicles and intelligent transportation system networks; academics in higher education institutions, including universities and vocational colleges; IT professionals; policy makers; and legislators. The book can also be used as a reference resource for both undergraduate and graduate studies. Written in plain and simple language, it describes new concepts so that they are accessible to readers without prior knowledge of the field.

This book discusses the principle of automotive intelligent technology from the point of view of modern sensing and intelligent control. Based on the latest research in the field, it explores safe driving with intelligent vision; intelligent monitoring of dangerous driving; intelligent detection of automobile power and transmission systems; intelligent vehicle navigation and transportation systems; and vehicle-assisted intelligent technology. It draws on the author's research in the field of automotive intelligent technology to explain the fundamentals of vehicle intelligent technology, from the information sensing principle to mathematical models and the algorithm basis, enabling readers to grasp the concepts of automotive intelligent technology. Opening up new scientific horizons and fostering innovative thinking, the book is a valuable resource for researchers as well as undergraduate and graduate students.

The book offers an integrated vision on Cloud and HPC, Big Data, Analytics and virtualization in computing-oriented manufacturing, combining information and communication technologies, service-oriented control of holonic architectures as well as enterprise integration solutions based on SOA principles. It is structured in eight parts, each one grouping research and trends in digital manufacturing and service oriented manufacturing control: Cloud and Cyber-Physical Systems for Smart Manufacturing, Reconfigurable and Self-organized Multi-Agent Systems for Industry and Service, Sustainability Issues in Intelligent Manufacturing Systems, Holonic and Multi-agent System Design for Industry and Service, Should Intelligent Manufacturing Systems be Dependable and Safe?, Service-oriented Management and Control of Manufacturing Systems, Engineering and Human Integration in Flexible and Reconfigurable Industrial Systems,Virtualization and Simulation in Computing-oriented Industry and Service.p>

This book presents a comprehensive definition of smart grids and their benefits, and compares smart and traditional grids. It also introduces a design methodology for stand-alone hybrid renewable energy system with and without applying the smart grid concepts for comparison purposes. It discusses using renewable energy power plants to feed loads in remote areas as well as in central power plants connected to electric utilities. Smart grid concepts used in the design of the hybrid renewable power systems can reduce the size of components, which can be translated to a reduction in the cost of generated energy. The proposed hybrid renewable energy system includes wind, photovoltaic, battery, and diesel, and is used initially to feed certain loads, covering the load required completely. The book introduces a novel methodology taking the smart grid concept into account by dividing the loads into high and low priority parts. The high priority part should be supplied at any generated conditions. However, the low priority loads can be shifted to the time when the generated energy from renewable energy sources is greater than the high priority loads requirements. The results show that the use of this smart grid concept reduces the component size and the cost of generated energy compared to that without dividing the loads. The book also describes the use of smart optimization techniques like particle swarm optimization (PSO) and genetic algorithm (GA) to optimally design the hybrid renewable energy system. This book provides an excellent background to renewable energy sources, optimal sizing and locating of hybrid renewable energy sources, the best optimization methodologies for sizing and designing the components of hybrid renewable energy systems, and offers insights into using smart grid concepts in the system's design and sizing. It also helps readers understand the dispatch methodology and how to connect the system's different components, their modeling, and the cost analysis of the system.

This book presents revised and extended versions of the best papers presented at the 9th International Joint Conference on Computational Intelligence (IJCCI 2017), held in Funchal, Madeira, from 1 to 3 November 2017. It focuses on four of the main fields of computational intelligence: evolutionary computation, fuzzy computation, neural computation, and cognitive and hybrid systems. As well as presenting the recent advances of these areas, it provides new and innovative solutions for established researchers and a source of information and/or inspiration those new to the field. Discussing innovative techniques in various application areas, it is a useful resource for individual researchers and a valuable addition to academic libraries (of universities and engineering schools).

Based on the idea of a universal rule for problem solving, the book suggests that the "System-Fuzzy Approach (SFA)" Model can be applied to various complex real-world problems. It is the first book for problem solving in complicated problems with a universal project management tool. Systematic searching is an essential step in identifying the right direction in problem solving; and the fuzzy steps in concrete problem solving reflect the flexibility and compromises involved in the process. Nevertheless, the fuzzy steps also demonstrate human beings' impressively flexible problem-solving skills. Simulating human decision-making processes based on fuzzy information processing is essential in our digital era, in which many problems need to be solved by means of artificial intelligence; hence the Fuzzy-AI Model emerged. As a universal rule and tool, it can be applied to a broad range of real-world problems. Offering a valuable guide to fuzzy decision-making, this book is intended for researchers, scientists and graduate students in the fields of Engineering, Economics, Sociology, Managerial Science, Project Management etc.

This book addresses the topic of fractional-order modeling of nuclear reactors. Approaching neutron transport in the reactor core as anomalous diffusion, specifically subdiffusion, it starts with the development of fractional-order neutron telegraph equations. Using a systematic approach, the book then examines the development and analysis of various fractional-order models representing nuclear reactor dynamics, ultimately leading to the fractional-order linear and nonlinear control-oriented models. The book utilizes the mathematical tool of fractional calculus, the calculus of derivatives and integrals with arbitrary non-integer orders (real or complex), which has recently been found to provide a more compact and realistic representation to the dynamics of diverse physical systems. Including extensive simulation results and discussing important issues related to the fractional-order modeling of nuclear reactors, the book offers a valuable resource for students and researchers working in the areas of fractional-order modeling and control and nuclear reactor modeling.

This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the above challenges by bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in intelligent systems. The book not only serves as a valuable reference source for researchers and professionals in the fields of computer vision and robotics, but will also benefit practitioners and graduates/postgraduates seeking advanced information on fuzzy techniques and their applications in motion analysis.

This book presents the outcomes of the 16th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2018), which was held in Kunming, China on June 13-15, 2018. The aim of the conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. The book includes findings on all aspects (theory, applications and tools) of computer and information science, and discusses related practical challenges and the solutions adopted to solve them. The conference organizers selected the best papers from those accepted for presentation. The papers were chosen based on review scores submitted by members of the program committee and underwent a further rigorous round of review. From this second round, 13 of the conference's most promising papers were then published in this Springer (SCI) book and not the conference proceedings. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.

This book focuses on innovative strategies to manage and build software systems for generating new knowledge from large archaeological data sets The book also reports on two case studies carried out in real-world scenarios within the Cultural Heritage setting. The book presents an original conceptual framework for developing software solutions to assist the knowledge generation process in connection with large archaeological data sets and related cultural heritage information- a context in which the inputs are mainly textual sources written in freestyle, i.e. without a predetermined, standard structure. Following an in-depth exploration of recent works on the knowledge generation process in the above-mentioned context and IT-based options for facilitating it, the book proposes specific new techniques capable of capturing the structure and semantics implicit in such textual sources, and argues for using this information in the knowledge generation process. The main result is the development of a conceptual framework that can accommodate textual sources and integrate the information included in them into a software engineering framework. The said framework is meant to assist cultural heritage professionals in general, and archaeologists in particular, in both knowledge extraction and the subsequent decision-making process.

In this revolutionary work, the author sets the stage for the science of
the 21st Century, pursuing an unprecedented synthesis of fields previously
considered unrelated. Beginning with simple classical concepts, he ends
with a complex multidisciplinary theory requiring a high level of
abstraction. The work progresses across the sciences in several
multidisciplinary directions: Mathematical logic, fundamental physics,
computer science and the theory of intelligence. Extraordinarily enough,
the author breaks new ground in all these fields.

In the field of
fundamental physics the author reaches the revolutionary conclusion that
physics can be viewed and studied as logic in a fundamental sense, as
compared with Einstein's view of physics as space-time geometry. This opens
new, exciting prospects for the study of fundamental interactions. A
formulation of logic in terms of matrix operators and logic vector spaces
allows the author to tackle for the first time the intractable problem of
cognition in a scientific manner. In the same way as the findings of
Heisenberg and Dirac in the 1930s provided a conceptual and mathematical
foundation for quantum physics, matrix operator logic supports an important
breakthrough in the study of the physics of the mind, which is interpreted
as a fractal of quantum mechanics. Introducing a concept of logic quantum
numbers, the author concludes that the problem of logic and the
intelligence code in general can be effectively formulated as eigenvalue
problems similar to those of theoretical physics. With this important leap
forward in the study of the mechanism of mind, the author concludes that
the latter cannot be fully understood either within classical or quantum
notions. A higher-order covariant theory is required to accommodate the
fundamental effect of high-level intelligence. The landmark results
obtained by the author will have implications and repercussions for the
very foundations of science as a whole. Moreover, Stern's Matrix Logic is
suitable for a broad spectrum of practical applications in contemporary
technologies.

This book presents an authoritative collection of contributions reporting on fuzzy logic and decision theory, together with applications and case studies in economics and management science. Dedicated to Professor Jaume Gil Aluja in recognition of his pioneering work, the book reports on theories, methods and new challenges, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike.

This book is a collection of several contributions which show the state of the art in specific areas of Computational Intelligence. This carefully edited book honors the 65th birthday of Rudolf Kruse. The main focus of these contributions lies on treating vague data as well as uncertain and imprecise information with automated procedures, which use techniques from statistics, control theory, clustering, neural networks etc. to extract useful and employable knowledge.

This unique work introduces the basic principles of artificial intelligence with applications in geographical teaching and research, GIS, and planning. Written in an accessible, non-technical and witty style, this book marks the beginning of the Al revolution in geography with major implications for teaching and research. The authors provide an easy to understand basic introduction to Al relevant to geography. There are no special mathematical and statistical skills needed, indeed these might well be a hindrance. Al is a different way of looking at the world and it requires a willingness to experiment, and readers who are unhindered by the baggage of obsolete technologies and outmoded philosophies of science will probably do best. The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry.

• A major methodological milestone in geography
• The first geographical book on artificial intelligence (Al)
• No need for previous mathematical or statistical skills/knowledge
• Accessible style makes a difficult subject available to a wide audience
• Stan Openshaw is one of the world s leading researchers into geographical computing, spatial analysis and GIS.

This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.

This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.

This book gathers 12 of the most promising papers presented at the 15th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2017) held on June 7-9, 2017 at the University of Greenwich, London, UK. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science, to share their experiences and to exchange new ideas and information in a meaningful way. The book also presents research findings regarding all aspects (theory, applications and tools) of computer and information science, and discusses the practical challenges encountered along the way and the solutions adopted to solve them.