The 15th International Conference "Intelligent Systems - 2022" (INTELS'22) was held on 14-16 December 2023 at the Russian Academy of Sciences, Moscow, Russia. It is a biennial event with a thirty-year history. INTELS'22 focused on the areas of intelligent systems and artificial intelligence, their theoretical aspects, and their application to sustainable development. Most of the papers are devoted to research and development of control systems in robotics. Both classical methods and modern methods based on machine learning are used to solve complex control problems.

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This Reprint represents the proceedings of the 7th International Conference on Knowledge Innovation and Invention 2024 (ICKII 2024). This conference was organized by the Science Education Center, National Taiwan Normal University, the Photovoltaic Research and Education Center for Smart Green Energy, National Formosa University, the International Institute of Knowledge Innovation and Invention (IIKII), and the IEEE Tainan Section Sensors Council (IEEE TSSC) in the area of sciences and engineering technologies. It provides a unified communication platform for researchers in the topics of Information Technology, Innovation Design, Bioengineering, Communication Science and Engineering, Industrial Design, Creative Design, Applied Mathematics, Computer Science, Electrical and Electronic Engineering, Mechanical and Automation Engineering, Green Technology and Architecture Engineering, Material Science, and other related fields. This conference enables the interdisciplinary collaboration of science and engineering technologists in the academic and industrial fields, as well as networking internationally. ICKII 2024 provided 15 Regular Sessions and 4 Invited Sessions including 223 papers, and 46 excellent papers about relevant engineering fields to the conference were selected through peer review for publication in Engineering Proceedings (ISSN: 2673-4591, indexed by Scopus). The proceedings of ICKII 2024 are expected to accelerate the interdisciplinary collaboration of science and engineering technologists in the academic and industrial fields as well as international networking.

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This open access book presents a collection of papers focusing on current 3D research challenges in the domain of digital cultural heritage. 3D technologies find considerable use within the field of cultural heritage at the beginning of the 21st century, for example in the areas of data acquisition, modeling, archiving in local repositories, harvesting in digital libraries and their long-term preservation. This volume put emphasis on a number of challenges facing 3D research in the 2D/3D digitization of tangible objects and their transformation to digital/virtual/memory twins; the interplay of geometry, semantics and the recovery and management of knowledge in digital cultural heritage; the handling of 3D data via the Cloud on the Internet and mobile devices; the presentation of cultural heritage content in 3D to the general public; and the 3D reproduction of cultural heritage objects from virtual to real.

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This open access conference proceedings contains all the papers presented at the ICTIMT 2023, the 3rd International Conference on Thermal Issues in Machine Tools. The event takes place in Dresden, the capital of Saxony, from March 21-23 2023. The conference is organized by the Chair of Machine Tools Development and Adaptive Controls of the Technische Universität Dresden.

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How to teach a computer? You can either write a fixed program – or you can enable the computer to learn on its own. Living beings do not have any programmer writing a program for developing their skills, which then only has to be executed. They learn by themselves – without the previous knowledge from external impressions – and thus can solve problems better than any computer today. What qualities are needed to achieve such a behavior for devices like computers? Can such cognition be adapted from biology? History, development, decline and resurgence of a wide approach to solve problems.

Originally, this work has been prepared in the framework of a seminar of the University of Bonn in Germany, but it has been and will be extended. First and foremost, to provide a comprehensive overview of the subject of neural networks.

Zeta2 edition. Also available in German.

 

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Computer science

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Many modern computer systems, including homogeneous and heterogeneous architectures, support shared memory in hardware. In a shared memory system, each of the processor cores may read and write to a single shared address space. For a shared memory machine, the memory consistency model defines the architecturally visible behavior of its memory system. Consistency definitions provide rules about loads and stores (or memory reads and writes) and how they act upon memory. As part of supporting a memory consistency model, many machines also provide cache coherence protocols that ensure that multiple cached copies of data are kept up-to-date. The goal of this primer is to provide readers with a basic understanding of consistency and coherence. This understanding includes both the issues that must be solved as well as a variety of solutions. We present both high-level concepts as well as specific, concrete examples from real-world systems. This second edition reflects a decade of advancements since the first edition and includes, among other more modest changes, two new chapters: one on consistency and coherence for non-CPU accelerators (with a focus on GPUs) and one that points to formal work and tools on consistency and coherence. This is an open access book. This is an open access book.

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The purpose of this Special Issue is to pay tribute to the significant contributions made by Professor Feng Qi in these fields and to provide some important recent advances in theory, methods, and applications.

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Ellipsometry is a measuring method for surface characterization and thin-film measurement of flat surfaces using polarized light. However, a new measuring principle based on return-path ellipsometry and retroreflection enables the detection of free-form surfaces. This new measurement principle and related questions regarding the measurement function, evaluation algorithms and ambiguities as well as degrees of freedom of the solution set are examined in this work.

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Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene.

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A new approach for defining causality and such related notions as degree of responsibility, degrees of blame, and causal explanation. Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C “actually caused” event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established in order to determine responsibility. The philosophy literature has been struggling with the problem of defining causality since Hume. In this book, Joseph Halpern explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression. Halpern applies and expands an approach to causality that he and Judea Pearl developed, based on structural equations. He carefully formulates a definition of causality, and building on this, defines degree of responsibility, degree of blame, and causal explanation. He concludes by discussing how these ideas can be applied to such practical problems as accountability and program verification. Technical details are generally confined to the final section of each chapter and can be skipped by non-mathematical readers.

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Adaptive filtering is useful in any application where the signals or the modeled system vary over time. The configuration of the system and, in particular, the position where the adaptive processor is placed generate different areas or application fields such as prediction, system identification and modeling, equalization, cancellation of interference, etc., which are very important in many disciplines such as control systems, communications, signal processing, acoustics, voice, sound and image, etc. The book consists of noise and echo cancellation, medical applications, communications systems and others hardly joined by their heterogeneity. Each application is a case study with rigor that shows weakness/strength of the method used, assesses its suitability and suggests new forms and areas of use. The problems are becoming increasingly complex and applications must be adapted to solve them. The adaptive filters have proven to be useful in these environments of multiple input/output, variant-time behaviors, and long and complex transfer functions effectively, but fundamentally they still have to evolve. This book is a demonstration of this and a small illustration of everything that is to come.

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Active filters are key technologies in applications such as telecommunications, advanced control, smart grids, and green transport. This book provides an update of the latest technological progress in signal processing and adaptive filters, with a focus on Kalman filters and applications. It illustrates fundamentals and guides filter design for specific applications, primarily for graduate students, academics, and industrial engineers who are interested in the theoretical, experimental, and design aspects of active filter technologies.

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Adaptive filtering can be used to characterize unknown systems in time-variant environments. The main objective of this approach is to meet a difficult comprise: maximum convergence speed with maximum accuracy. Each application requires a certain approach which determines the filter structure, the cost function to minimize the estimation error, the adaptive algorithm, and other parameters; and each selection involves certain cost in computational terms, that in any case should consume less time than the time required by the application working in real-time. Theory and application are not, therefore, isolated entities but an imbricated whole that requires a holistic vision. This book collects some theoretical approaches and practical applications in different areas that support expanding of adaptive systems.

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In this work, an approach for adaptive world modeling is proposed. World models for cognitive systems often employ predefined domain models, which may become insufficient when encountering unforeseen entities. The presented approach addresses an adaptive extension of such domain models, considering the relevance of proposed model adaptations. As a basis, a quantitative model evaluation is devised, rating the ability of a domain model to represent the currently observed environment state.

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In der vorliegenden Arbeit wird eine biologisch motivierte Verhaltenssteuerung für ein kognitives Automobil vorgestellt, die ein hohes Maß an Rückmeldung liefert und damit die Grundlage für zukünftige Lernverfahren bildet. Weiterhin wird eine universell einsetzbare Bahnplanungskomponente entwickelt. Wesentliches Element des vorgestellten Ansatzes ist die Repräsentation von Fahrintention und Fahrzeugumfeld mit Hilfe von dynamischen Gefahrenkarten.

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This reprint discussed Coding and compression; Content storing and management; Electronic media; Internet technology; Image and video signals; Multimedia processing; Quality of experience (QoE); Quality of service (QoS); Signal processing; Streaming services; Subjective and objective metrics; User experience (UX).

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Computers and machines were developed to reduce time consumption and manual human efforts to complete projects efficiently. With fast-growing technologies in the field, we have finally reached a stage where almost everyone in the world has access to these high technologies. However, this is just a starting phase because future development is taking a more advanced route in the shape of artificial intelligence (AI). Although AI is under the computer science umbrella, nowadays there is no field unaffected by this high technology. The overall aim of using intelligence learning methods is to train machines to think intelligently and make decisions in different situations the same as humans. Previously, machines were doing what they were programmed to do, but now with AI, devices can think and behave like a human being. This book aims to present the application of advanced analytics and AI in different industries as practical tools to develop prediction, optimization, and make decision models.

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The methods for human identity authentication based on biometrics - the physiological and behavioural characteristics of a person have been evolving continuously and seen significant improvement in performance and robustness over the last few years. However, most of the systems reported perform well in controlled operating scenarios, and their performance deteriorates significantly under real world operating conditions, and far from satisfactory in terms of robustness and accuracy, vulnerability to fraud and forgery, and use of acceptable and appropriate authentication protocols. To address some challenges, and the requirements of new and emerging applications, and for seamless diffusion of biometrics in society, there is a need for development of novel paradigms and protocols, and improved algorithms and authentication techniques. This book volume on "Advanced Biometric Technologies" is dedicated to the work being pursued by researchers around the world in this area, and includes some of the recent findings and their applications to address the challenges and emerging requirements for biometric based identity authentication systems. The book consists of 18 Chapters and is divided into four sections namely novel approaches, advanced algorithms, emerging applications and the multimodal fusion. The book was reviewed by editors Dr. Girija Chetty and Dr. Jucheng Yang We deeply appreciate the efforts of our guest editors: Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers.

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This Special Issue includes 14 contributions, with 2 review contributions and 12 research contributions. The review contributions provide a survey with an overview of the state of the art in detecting and projecting cyber-attack scenarios, and the review of a specific application area, the safety of autonomous haulage systems in the mining environment related to both cybersecurity and communication. 10 research contributions are addressing the area of advanced services for intrusion detection systems: (a) the use of different machine learning models depending on the specific scenarios and datasets; (b) the use of deep learning techniques for the detection of zero-day attacks; (c) a proposal of an integrated scalable framework aimed at efficiently detecting anomalous events on large amounts of unlabeled data logs; (d) a spatiotemporal characterization of cyber-attacks for detecting such attacks; (e) a two-stage intrusion detection system for industrial control networks; (f) a chatbot for detecting online sex offenders, based on an artificial conversational entity (ACE); and (g) an open-source platform for manipulating both streaming and archived network flow data in real time. This Special Issue also contains two protection-related research contributions, including: (a) a countermeasure for on–off web defacement attacks and (b) the evaluation of multi-path routing as a protection feature against network attacks and failures.

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"Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution.

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Advanced intelligent control is a rapidly developing, complex and challenging field with significant practical importance and potential applications. The authors aim to stimulate advancements in science and technology by addressing this field and presenting new trends in the design, control and applications of real-time intelligent sensor system control using advanced intelligent control methods and techniques. The purpose of the Special Issue is to promote in-depth research and communication regarding these topics. The authors focus on innovative multi-sensor fusion techniques integrated into robots, which are combined with computer vision, virtual and augmented reality (VR&AR) and intelligent communication including remote control, adaptive sensor networks and human–robot (H2R) interaction systems. Special attention is given to advancements in sensors, actuators, computation technology and communication networks that provide the necessary tools for implementing intelligent control hardware. These advancements are targeted toward various scientific research fields, including machine learning (such as deep learning), bio-inspired algorithms, recurrent neural networks, neuro-fuzzy control and artificial intelligence in general. The Special Issue includes original research papers that report on the recent advancements in intelligent control using intelligent sensors. It serves as a further extension of the previously successful Special Issue, “Advanced Intelligent Control through Versatile Intelligent Portable Platforms”.

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The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research.

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This Special Issue aims to attract the latest research and findings in the design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificially intelligent devices and algorithms to assist/monitor the elderly, patients, and the disabled population.

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Measurement is a multidisciplinary experimental science. Measurement systems synergistically blend science, engineering and statistical methods to provide fundamental data for research, design and development, control of processes and operations, and facilitate safe and economic performance of systems. In recent years, measuring techniques have expanded rapidly and gained maturity, through extensive research activities and hardware advancements. With individual chapters authored by eminent professionals in their respective topics, Advanced Topics in Measurements attempts to provide a comprehensive presentation and in-depth guidance on some of the key applied and advanced topics in measurements for scientists, engineers and educators.

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This book aims to bring together recent advances and applications of video coding. All chapters can be useful for researchers, engineers, graduate and postgraduate students, experts in this area, and hopefully also for people who are generally interested in video coding. The book includes nine carefully selected chapters. The chapters deal with advanced compression techniques for multimedia applications, concerning recent video coding standards, high efficiency video coding (HEVC), multiple description coding, region of interest (ROI) coding, shape compensation, error resilient algorithms for H.264/AVC, wavelet-based coding, facial video coding, and hardware implementations. This book provides several useful ideas for your own research and helps to bridge the gap between the basic video coding techniques and practical multimedia applications. We hope this book is enjoyable to read and will further contribute to video coding.

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The present reprint contains 33 articles accepted and published in the Special Issue entitled “Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics, 2022” in the MDPI journal, Mathematics, which covers a wide range of topics connected to the theory and applications of feature representation learning for image processing, artificial intelligence, data mining and robotics. These topics include, among others, elements from image blurring, image aesthetic quality assessment, pedestrian detection, visual tracking, vehicle re-identification, face recognition, 3D reconstruction, the stability of switched systems, domain adaption, deep reinforcement, sentiment analysis, graph convolutional networks, knowledge graphs, geometric metric learning, etc. It is hoped that this reprint will be interesting and useful for those working in the area of image processing, computer vision, machine learning, natural language processing and robotics, as well as for those with backgrounds in machine learning who are willing to become familiar with recent advancements in artificial intelligence, which, today, is present in almost all aspects of human life and activities.

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This open access book contains contributions from the Global Fluid Power Society (GFPS) PhD Symposium 2024. It reflects the collaborative efforts of researchers who are dedicated to pushing the boundaries of fluid power research. The GFPS PhD symposium, established in 2016 as a biannual event, is a platform for exchanging ideas and insights related to fluid power technology, among young researchers. It serves as a focal point for the exploration of various technical topics related to fluid power, including components, systems, and applications. Fluid power technology undergoes a rapid transformation towards electrification and digitalization, requiring innovation and new technical solutions across the industry, in response to societal requirements on different aspects of sustainability. The book covers a range of topics that align with the symposium's theme: Advancements in Fluid Power Technology: Sustainability, Electrification, and Digitalization. The content encompasses a wide spectrum of subjects, including fluid power applications, control and automation, energy efficiency, electrification, and environmental sustainability. The book can be a valuable reference for researchers and professionals interested in fluid power research and allied fields.

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The relationship between individuality and aggregation is an important topic in Complex Systems Science, as both aspects are facets of emergence. This problem has generally been addressed by adopting a classical individual- versus population-level approach, in which boundaries emerge in segregated communities. More specifically, boundaries delimiting and interconnecting aggregates are at play. It is, therefore, crucial to define the properties of complex systems correctly, such as generic agent-based models, with which to simulate communities situated in grid- and scale-free network environments. To do this, complexities may be resolved through simulation, modeling and analysis techniques, which help provide confidence regarding the behavior of such systems, especially of those operating in dynamic environments or under unexpected constraints. Moreover, modeling and simulation help reduce the risks and costs involved in the design and development of validation tests.

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Artificial Intelligence (AI) has attracted the attention of researchers and users alike and is taking an increasingly crucial role in our modern society. From cars, smartphones, and airplanes to medical equipment, consumer applications, and industrial machines, the impact of AI is notoriously changing the world we live in. In this context, Deep Learning (DL) is one of the techniques that has taken the lead for cognitive processes, pattern recognition, object detection, and machine learning, all of which have played a crucial role in the growth of AI. As such, this book examines DL applications and future trends in the field. It is a useful resource for researchers and students alike.

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Modern geometric computing increasingly plays a role in modeling environments and processing sensing information, providing a variety of tools for the efficient design, analysis, and manufacturing of complex shapes. The research area of architectural geometry (AG) has emerged at the common border of architecture, applied geometry, computational design, mathematics, and manufacturing. This book presents the state of the art of research in AG.

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This reprint covers new aspects of the recent developments in the theory and applications of fractional differential equations, including inclusions, inequalities, and systems of fractional differential equations with Riemann-Liouville derivatives, Caputo derivatives, or other generalized fractional derivatives, subject to various boundary conditions. The authors study the existence, uniqueness, multiplicity, and nonexistence of classical or mild solutions, the approximation of solutions, and the approximate controllability of mild solutions for diverse mathematical models.

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This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject.

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The book presents some very interesting and excellent articles for this divergent title. The 22 chapters presented here cover core topics of computer science such as visualization of large databases, security, ontology, user interface, graphs, object oriented software developments, and on the engineering side filtering, motion dynamics, adaptive fuzzy logic, and hyper static mechanical systems. It also covers topics which are combination of computer science and engineering such as meta computing, future mobiles, colour image analysis, relative representation and recognition, and neural networks. The book will serve a unique purpose through these multi-disciplined topics to share different but interesting views on each of these topics.

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This volume brings about the contemporary results in the field of discrete-time systems. It covers papers written on the topics of robust control, nonlinear systems and recent applications. Although the technical views are different, they all geared towards focusing on the up-to-date knowledge gain by the researchers and providing effective developments along the systems and control arena. Each topic has a detailed discussions and suggestions for future perusal by interested investigators.

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Intelligent systems, known as expert systems, serve to this purpose in the extent that they have signed as facilitators in this process. These are systems that are based on expert knowledge, on any subject, in order to emulate human expertise in the specific field. To obtain this knowledge, the knowledge engineers, also called software engineers, need to develop methodologies for intelligent systems. In this area there is still no unified methodology that provides effective methods, notations and tools to aid in development.

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In these 34 chapters, we survey the broad disciplines that loosely inhabit the study and practice of human-computer interaction. Our authors are passionate advocates of innovative applications, novel approaches, and modern advances in this exciting and developing field. It is our wish that the reader consider not only what our authors have written and the experimentation they have described, but also the examples they have set.

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Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers.

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In the era of the Internet of Things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development of camera hardware quality, i.e., the resolution and exposure time of cameras, which may require high computational costs. As an alternative, image enhancement techniques can exact salient features to improve the quality of captured images according to the differences in diverse features, although they suffer from some challenges, i.e., a low contrast, artifacts, and overexposure, thus making it decidedly necessary to determine how to use advanced image enhancement techniques. The topic of advances in the image enhancement of electronics is presented in this reprint, which brings together the research accomplishments of researchers from academia and industry. The secondary goal of this reprint is to display the latest research results of advances in image enhancement.

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For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches.

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The field of digital image segmentation is continually evolving. Most recently, the advanced segmentation methods such as Template Matching, Spatial and Temporal ARMA Processes, Mean Shift Iterative Algorithm, Constrained Compound Markov Random Field (CCMRF) model and Statistical Pattern Recognition (SPR) methods form the core of a modernization effort that resulted in the current text. This new edition of "Advanced Image Segmentation" is but a reflection of the significant progress that has been made in the field of image segmentation in just the past few years. The book presented chapters that highlight frontier works in image information processing.

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This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

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Advances in Knowledge Representation offers a compilation of state of the art research works on topics such as concept theory, positive relational algebra and k-relations, structured, visual and ontological models of knowledge representation, as well as detailed descriptions of applications to various domains, such as semantic representation and extraction, intelligent information retrieval, program proof checking, complex planning, and data preparation for knowledge modelling, and a extensive bibliography. It is a valuable contribution to the advancement of the field. The expected readers are advanced students and researchers on the knowledge representation field and related areas; it may also help to computer oriented practitioners of diverse fields looking for ideas on how to develop a knowledge-based application.

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This book contains twelve chapters detailing significant advances and applications in fluid dynamics modeling with focus on biomedical, bioengineering, chemical, civil and environmental engineering, aeronautics, astronautics, and automotive. We hope this book can be a useful resource to scientists and engineers who are interested in fundamentals and applications of fluid dynamics.

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Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain–machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications.

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An invariant object recognition system needs to be able to recognise the object under any usual a priori defined distortions such as translation, scaling and in-plane and out-of-plane rotation. Ideally, the system should be able to recognise (detect and classify) any complex scene of objects even within background clutter noise. In this book, we present recent advances towards achieving fully-robust object recognition. The relation and importance of object recognition in the cognitive processes of humans and animals is described as well as how human- and animal-like cognitive processes can be used for the design of biologically-inspired object recognition systems. Colour processing is discussed in the development of fully-robust object recognition systems. Examples of two main categories of object recognition systems, the optical correlators and pure artificial neural network architectures, are given. Finally, two examples of object recognition's applications are described in details. With the recent technological advancements object recognition becomes widely popular with existing applications in medicine for the study of human learning and memory, space science and remote sensing for image analysis, mobile computing and augmented reality, semiconductors industry, robotics and autonomous mobile navigation, public safety and urban management solutions and many more others. This book is a "must-read" for everyone with a core or wider interest in this "hot" area of cutting-edge research.

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This book describes and discusses the use of principal component analysis (PCA) for different types of problems in a variety of disciplines, including engineering, technology, economics, and more. It presents real-world case studies showing how PCA can be applied with other algorithms and methods to solve both large and small and static and dynamic problems. It also examines improvements made to PCA over the years.

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Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic.

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Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics.

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This cutting-edge book brings together experts in the field to provide a multidimensional perspective on sentiment analysis, covering both foundational and advanced methodologies. Readers will gain insights into the latest natural language processing and machine learning techniques that power sentiment analysis, enabling the extraction of nuanced emotions from text. Key Features: •State-of-the-Art Techniques: Explore the most recent advancements in sentiment analysis, from deep learning approaches to sentiment lexicons and beyond. •Real-World Applications: Dive into a wide range of applications, including social media monitoring, customer feedback analysis, and sentiment-driven decision-making. •Cross-Disciplinary Insights: Understand how sentiment analysis influences and is influenced by fields such as marketing, psychology, and finance. •Ethical and Privacy Considerations: Delve into the ethical challenges and privacy concerns inherent to sentiment analysis, with discussions on responsible AI usage. •Future Directions: Get a glimpse into the future of sentiment analysis, with discussions on emerging trends and unresolved challenges. This book is an essential resource for researchers, practitioners, and students in fields like natural language processing, machine learning, and data science. Whether you’re interested in understanding customer sentiment, monitoring social media trends, or advancing the state of the art, this book will equip you with the knowledge and tools you need to navigate the complex landscape of sentiment analysis.

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In the last decade, further applications of speech processing were developed, such as speaker recognition, human-machine interaction, non-English speech recognition, and non-native English speech recognition. This book addresses a few of these applications. Furthermore, major challenges that were typically ignored in previous speech recognition research, such as noise and reverberation, appear repeatedly in recent papers. I would like to sincerely thank the contributing authors, for their effort to bring their insights and perspectives on current open questions in speech recognition research.

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Stereopsis is a vision process whose geometrical foundation has been known for a long time, ever since the experiments by Wheatstone, in the 19th century. Nevertheless, its inner workings in biological organisms, as well as its emulation by computer systems, have proven elusive, and stereo vision remains a very active and challenging area of research nowadays. In this volume we have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints.

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The book presents a wide range of innovative research ideas and current trends in stereo vision. The topics covered in this book encapsulate research trends from fundamental theoretical aspects of robust stereo correspondence estimation to the establishment of novel and robust algorithms as well as applications in a wide range of disciplines. Particularly interesting theoretical trends presented in this book involve the exploitation of the evolutionary approach, wavelets and multiwavelet theories, Markov random fields and fuzzy sets in addressing the correspondence estimation problem. Novel algorithms utilizing inspiration from biological systems (such as the silicon retina imager and fish eye) and nature (through the exploitation of the refractive index of liquids) make this book an interesting compilation of current research ideas.

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The intersection of AI, the Internet of Things (IoT) and edge computing has kindled the edge AI revolution that promises to redefine how we perceive and interact with the physical world through intelligent devices. Edge AI moves intelligence from the network centre to the devices at its edge, entrusting these endpoints to analyse data locally, make decisions, and provide real-time responses. Recent advances in power-efficient high-performance embedded silicon make edge AI a viable proposition, albeit one requiring new distributed architectures and novel design concepts. Moving decision-making closer to the edge makes responses faster and systems more reliable, while the constant pressure to reduce network bandwidth demand and the need to contain spiralling data storage and operations costs help justify the engineering investment necessary to embrace this new paradigm. Moving to decentralised operation opens the door to a multitude of novel applications, covering immersive technologies and autonomous systems across fields as diverse as healthcare and industrial automation, personal assistance and prognostics, surgery, and process control. In the best tradition of systems engineering, the first stage of this transition process is understanding the application domain for edge AI deployment, the "system context". This book presents some key topics and early thinking from the EdgeAI* project, covering data backhaul technologies, lifecycle management, mechanisms for developing AIs at the edge and techniques for interacting with those AIs. It provides examples of application domains before concluding with a review of how edge AI systems can be understood by their users. It also examines and presents new results based on current investigations and activities in edge AI technologies, considering the future trends in autonomic systems, hyperautomation, AI engineering, generative AI, connectivity, and cybersecurity mesh. This book aims to empower the reader with the knowledge and insights needed to understand and embrace the transformative power of edge AI technology. The extensively referenced chapters, contributed by experts and thought leaders in the field, are recommended to anyone interested in developing edge AI systems. *Edge AI Technologies for Optimised Performance Embedded Processing"" (EdgeAI) Key Digital Technologies (KDT) Joint Undertaking (JU) European research project. https://https://edge-ai-tech.eu/

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