This book presents Proceedings of the International Conference on Intelligent Systems and Networks (ICISN 2021), held at Hanoi in Vietnam. It includes peer-reviewed high-quality articles on intelligent system and networks. It brings together professionals and researchers in the area and presents a platform for exchange of ideas and to foster future collaboration. The topics covered in this book include-foundations of computer science; computational intelligence language and speech processing; software engineering software development methods; wireless communications signal processing for communications; electronics track IoT and sensor systems embedded systems; etc.

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning. Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning; Outlines the computation paradigm for solving classification, regression, and clustering; Features essential techniques for building the a new generation of machine learning.

This book discusses the various open issues of blockchain technology, such as the efficiency of blockchain in different domains of digital cryptocurrency, smart contracts, smart education system, smart cities, cloud identity and access, safeguard to cybersecurity and health care. For the first time in human history, people across the world can trust each other and transact over a large peer-to-peer networks without any central authority. This proves that, trust can be built not only by centralized institution but also by protocols and cryptographic mechanisms. The potential and collaboration between organizations and individuals within peer networks make it possible to potentially move to a global collaborative network without centralization. Blockchain is a complex social, economic and technological phenomenon. This questions what the established terminologies of the modern world like currency, trust, economics and exchange would mean. To make any sense, one needs to realize how much insightful and potential it is in the context and the way it is technically developed. Due to rapid changes in accessing the documents through online transactions and transferring the currency online, many previously used methods are proving insufficient and not secure to solve the problem which arises in the safe and hassle-free transaction. Nowadays, the world changes rapidly, and a transition flow is also seen in Business Process Management (BPM). The traditional Business Process Management holds good establishment last one to two decades, but, the internal workflow confined in a single organization. They do not manage the workflow process and information across organizations. If they do so, again fall in the same trap as the control transfers to the third party that is centralized server and it leads to tampering the data, and single point of failure. To address these issues, this book highlights a number of unique problems and effective solutions that reflects the state-of-the art in blockchain Technology. This book explores new experiments and yields promising solutions to the current challenges of blockchain technology. This book is intended for the researchers, academicians, faculties, scientists, blockchain specialists, business management and software industry professionals who will find it beneficial for their research work and set new ideas in the field of blockchain. This book caters research work in many fields of blockchain engineering, and it provides an in-depth knowledge of the fields covered.

This book draws inspiration from natural shepherding, whereby a farmer utilizes sheepdogs to herd sheep, to inspire a scalable and inherently human friendly approach to swarm control. The book discusses advanced artificial intelligence (AI) approaches needed to design smart robotic shepherding agents capable of controlling biological swarms or robotic swarms of unmanned vehicles. These smart shepherding agents are described with the techniques applicable to the control of Unmanned X Vehicles (UxVs) including air (unmanned aerial vehicles or UAVs), ground (unmanned ground vehicles or UGVs), underwater (unmanned underwater vehicles or UUVs), and on the surface of water (unmanned surface vehicles or USVs). This book proposes how smart 'shepherds' could be designed and used to guide a swarm of UxVs to achieve a goal while ameliorating typical communication bandwidth issues that arise in the control of multi agent systems. The book covers a wide range of topics ranging from the design of deep reinforcement learning models for shepherding a swarm, transparency in swarm guidance, and ontology-guided learning, to the design of smart swarm guidance methods for shepherding with UGVs and UAVs. The book extends the discussion to human-swarm teaming by looking into the real-time analysis of human data during human-swarm interaction, the concept of trust for human-swarm teaming, and the design of activity recognition systems for shepherding. Presents a comprehensive look at human-swarm teaming; Tackles artificial intelligence techniques for swarm guidance; Provides artificial intelligence techniques for real-time human performance analysis.

This book extends the work from introduction of ubiquitous computing, to the Internet of things to security and to privacy aspects of ubiquitous computing. The uniqueness of this book is the combination of important fields like the Internet of things and ubiquitous computing. It assumes that the readers' goal is to achieve a complete understanding of IoT, smart computing, security issues, challenges and possible solutions. It is not oriented towards any specific use cases and security issues; privacy threats in ubiquitous computing problems are discussed across various domains. This book is motivating to address privacy threats in new inventions for a wide range of stakeholders like layman to educated users, villages to metros and national to global levels. This book contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms and protocols. The main endeavour of this book is threat analysis and activity modelling of attacks in order to give an actual view of the ubiquitous computing applications. The unique approach will help readers for a better understanding.

Hybrid Artificial Intelligent Systems (HAIS) try to deal with the complexity of real world phenomena using a multidisciplinary approach and a plurality of techniques. Logistics Management and Optimization through Hybrid Artificial Intelligence Systems offers the latest research within the field of HAIS, surveying the broad topics and collecting case studies, future directions, and cutting edge analyses. Using biologically-inspired algorithms such as ant colony optimization and particle swarm optimization, this text includes solutions and heuristics for practitioners and academics alike, offering a vital resource for staying abreast in this ever-burgeoning field.

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits * Presents the latest advances in learning automata-based optimization approaches. * Addresses the memetic models of learning automata for solving NP-hard problems. * Discusses the application of learning automata for behavior control in evolutionary computation in detail. * Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

This book presents the proceedings of the 2nd International Conference on Networks and Advances in Computational Technologies (NetACT19) which took place on July 23-25, 2019 at Mar Baselios College of Engineering and Technology in Thiruvananthapuram, India. The conference was in association with Bowie State University, USA, Gannon University, USA and Malardalen University, Sweden. Papers presented were included in technical programs that were part of five parallel tracks, namely Computer Application, Image Processing, Network Security, Hardware & Network Systems and Machine Learning. The proceedings brings together experts from industry, governments and academia from around the world with vast experiences in design, engineering and research. Presents the proceedings of the 2nd International Conference on Networks and Advances in Computational Technologies (NetACT19); Includes research in Computer Application, Image Processing, Network Security, Hardware & Network Systems and Machine Learning; Provides perspectives from industry, academia and government.

This book presents a collection of recent research on topics related to Pythagorean fuzzy set, dealing with dynamic and complex decision-making problems. It discusses a wide range of theoretical and practical information to the latest research on Pythagorean fuzzy sets, allowing readers to gain an extensive understanding of both fundamentals and applications. It aims at solving various decision-making problems such as medical diagnosis, pattern recognition, construction problems, technology selection, and more, under the Pythagorean fuzzy environment, making it of much value to students, researchers, and professionals associated with the field.

Immersive technology as an umbrella concept consists of multiple emerging technologies including augmented reality (AR), virtual reality (VR), gaming, simulation, and 3D printing. Research has shown immersive technology provides unique learning opportunities for experiential learning, multiple perspectives, and knowledge transfer. Due to its role in influencing learners' cognitive and affective processes, it is shown to have great potential in changing the educational landscape in the decades to come. However, there is a lack of general cognitive and affective theoretical framework to guide the diverse aspects of immersive technology research. In fact, lacking the cognitive and affective theoretical framework has begun to hamper the design and application of immersive technology in schools and related professional training. Cognitive and Affective Perspectives on Immersive Technology in Education is an essential research book that explores methods and implications for the design and implementation of upcoming immersive technologies in pedagogical and professional development settings. The book includes case studies that highlight the cognitive and affective processes in immersive technology as well as the successful applications of immersive technology in education. Featuring a wide range of topics such as curriculum design, K-12 education, and mobile learning, this book is ideal for academicians, educators, policymakers, curriculum developers, instructional designers, administrators, researchers, and students.

This book brings together papers presented at The 2nd International Conference on Artificial Intelligence in China (ChinaAI) 2020, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics covering all topics in artificial intelligence with new development in China, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).

As humans interact more often and more intimately with computers, and as computational systems become an ever more important element of our society, playing roles in education, the production of culture and goods, and management, it is inevitable that we should seek to interact with these systems in ways that take advantage of our powerful emotional capabilities. Creating Synthetic Emotions through Technological and Robotic Advancements compiles progressive research in the emerging and groundbreaking fields of artificial emotions, affective computing, and sociable robotics that allow humans to begin the once impossible-seeming task of interacting with robots, systems, devices, and agents. This landmark volume brings together expert international researchers to expound upon these topics as synthetic emotions move toward becoming a daily reality.

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.

This book explains why the finite topological space known as abstract cell complex is important for successful image processing and presents image processing methods based on abstract cell complex, especially for tracing and encoding of boundaries of homogeneous regions. Many examples are provided in the book, some teach you how to trace and encode boundaries in binary, indexed and colour images. Other examples explain how to encode a boundary as a sequence of straight-line segments which is important for shape recognition. A new method of edge detection in two- and three-dimensional images is suggested. Also, a discussion problem is included in the book: A derivative is defined as the limit of the relation of the increment of the function to the increment of the argument as the latter tends to zero. Is it not better to estimate derivatives as the relation of the increment of the function to the optimal increment of the argument instead of taking exceedingly small increment which leads to errors? This book addresses all above questions and provide the answers.

This book, to reflect the system's diverse, relevant characteristics, uses three different mathematical tools, namely probability theory, fuzzy theory and random fuzzy theory, to model and analyze the reliability of each system. Reliability system engineering is an interdisciplinary area that chiefly focuses on the lifecycle characteristics of products and involves many fields of basic mathematics, technical science and management science. In recent years, there have been many books on reliability theory, but comparatively few on the reliability of mathematical models, or the reliability of mathematical models based on single probability theory or fuzzy theory. The findings presented here will not only enrich and expand traditional reliability theory, but also promote the development of related disciplines, lending the book considerable theoretical significance.

This book discusses biologically inspired robotic actuators designed to offer improved robot performance and approaching human-like efficiency and versatility. It assesses biological actuation and control in the human motor system, presents a range of technical actuation approaches, and discusses potential applications in wearable robots, i.e., powered prostheses and exoskeletons. Gathering the findings of internationally respected researchers from various fields, the book provides a uniquely broad perspective on bioinspired actuator designs for robotics. Its scope includes fundamental aspects of biomechanics and neuromechanics, actuator and control design, and their application in (wearable) robotics. The book offers PhD students and advanced graduate students an essential introduction to the field, while providing researchers a cutting-edge research perspective.

This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors' intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors' attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.

This book focuses on various advanced technologies which integrate with machine learning to assist one of the most leading industries, healthcare. It presents recent research works based on machine learning approaches supported by medical and information communication technologies with the use of data and image analysis. The book presents insight about techniques which broadly deals in delivery of quality, accurate and affordable healthcare solutions by predictive, proactive and preventative methods. The book also explores the possible use of machine learning in enterprises, such as enhanced medical imaging/diagnostics, understanding medical data, drug discovery and development, robotic surgery and automation, radiation treatments, creating electronic smart records and outbreak prediction.

Over the last 20 years, the role of unmanned aircraft systems in modern warfare has grown at an unprecedented rate. No longer simply used for intelligence, data collection or reconnaissance, drones are routinely used for target acquisition and to strike enemy targets with missiles and bombs. Organized by nationality, Military Drones offers a compact guide to the main unmanned aerial vehicles being flown in combat zones today. These include classics, such as the MQ-1 Predator, primarily used for intelligence gathering; the Black Hornet Nano, a micro UAV that is so small it can fit in the palm of your hand and is used by ground troops for local situational awareness; the Chinese tri-copter Scorpion, which is ideal for the stationary observation and strike role in a built-up area; and the French EADS Talarion, a twinjet long-endurance UAV designed for high-altitude surveillance. Illustrated with more than 100 photographs and artworks, Military Drones provides a detailed insight into the specialist military unmanned aerial vehicles that play a key role in the modern battle space.

Recent advances in eye tracking technology will allow for a proliferation of new applications. Improvements in interactive methods using eye movement and gaze control could result in faster and more efficient human computer interfaces, benefitting users with and without disabilities. Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies focuses on interactive communication and control tools based on gaze tracking, including eye typing, computer control, and gaming, with special attention to assistive technologies. For researchers and practitioners interested in the applied use of gaze tracking, the book offers instructions for building a basic eye tracker from off-the-shelf components, gives practical hints on building interactive applications, presents smooth and efficient interaction techniques, and summarizes the results of effective research on cutting edge gaze interaction applications.

Modern devices, from phones and cars to houses and the appliances within them, are being designed with formidable computational power and expanded functionality. To be truly effective, these smart devices must effectively process data from their environment and experiences and make decisions based on that information. Recent Advances in Ambient Intelligence and Context-Aware Computing investigates the functionality of ubiquitous computational systems and how they may adapt to their environment to improve the quality of interaction for the end-user. This reference book will be of value to under- and post-graduate students, professionals, and researchers networking, computer science, communications, and other information technology disciplines.

This book introduces the point cloud; its applications in industry, and the most frequently used datasets. It mainly focuses on three computer vision tasks -- point cloud classification, segmentation, and registration -- which are fundamental to any point cloud-based system. An overview of traditional point cloud processing methods helps readers build background knowledge quickly, while the deep learning on point clouds methods include comprehensive analysis of the breakthroughs from the past few years. Brand-new explainable machine learning methods for point cloud learning, which are lightweight and easy to train, are then thoroughly introduced. Quantitative and qualitative performance evaluations are provided. The comparison and analysis between the three types of methods are given to help readers have a deeper understanding. With the rich deep learning literature in 2D vision, a natural inclination for 3D vision researchers is to develop deep learning methods for point cloud processing. Deep learning on point clouds has gained popularity since 2017, and the number of conference papers in this area continue to increase. Unlike 2D images, point clouds do not have a specific order, which makes point cloud processing by deep learning quite challenging. In addition, due to the geometric nature of point clouds, traditional methods are still widely used in industry. Therefore, this book aims to make readers familiar with this area by providing comprehensive overview of the traditional methods and the state-of-the-art deep learning methods. A major portion of this book focuses on explainable machine learning as a different approach to deep learning. The explainable machine learning methods offer a series of advantages over traditional methods and deep learning methods. This is a main highlight and novelty of the book. By tackling three research tasks -- 3D object recognition, segmentation, and registration using our methodology -- readers will have a sense of how to solve problems in a different way and can apply the frameworks to other 3D computer vision tasks, thus give them inspiration for their own future research. Numerous experiments, analysis and comparisons on three 3D computer vision tasks (object recognition, segmentation, detection and registration) are provided so that readers can learn how to solve difficult Computer Vision problems.

Research on living systems, human level artificial systems, and machines that exhibit intelligent behavioral characteristics is fundamental in order to tackle complex and dynamic issues in nature and create applicable solutions. Investigations into Living Systems, Artificial Life, and Real-World Solutions provides original research on the theoretical and applied aspects of artificial life, as well as addresses scientific, psychological, and social issues of synthetic life-like behavior and abilities. This book is essential for researchers, students, and scientists interested in the emerging discipline of artificial life to further understand and solve real-world problems.

This monograph provides a comprehensive exploration of new tools for modelling, analysis, and control of networked dynamical systems. Expanding on the authors' previous work, this volume highlights how local exchange of information and cooperation among neighboring agents can lead to emergent global behaviors in a given networked dynamical system. Divided into four sections, the first part of the book begins with some preliminaries and the general networked dynamical model that is used throughout the rest of the book. The second part focuses on synchronization of networked dynamical systems, synchronization with non-expansive dynamics, periodic solutions of networked dynamical systems, and modulus consensus of cooperative-antagonistic networks. In the third section, the authors solve control problems with input constraint, large delays, and heterogeneous dynamics. The final section of the book is devoted to applications, studying control problems of spacecraft formation flying, multi-robot rendezvous, and energy resource coordination of power networks. Modelling, Analysis, and Control of Networked Dynamical Systems will appeal to researchers and graduate students interested in control theory and its applications, particularly those working in networked control systems, multi-agent systems, and cyber-physical systems. This volume can also be used in advanced undergraduate and graduate courses on networked control systems and multi-agent systems.

Throughout the past decade, the notion of ontologies has influenced research in many application areas including databases, information retrieval, electronic commerce, natural language processing, knowledge management, enterprise systems, systems analysis and design, the Web, and more.Ontology-Based Applications for Enterprise Systems and Knowledge Management provides an opportunity for readers to clearly understand the notion of ontology engineering and the practical aspects of this approach in the domains of two interest areas: Knowledge Management Systems and Enterprise Systems. A perfect reference for researchers, scholars, postgraduate students, and practitioners, this book aims to gather the recent advances and research findings of various topics in ontology use for these application areas.