This fascinating, colourful book offers in-depth insights and first-hand working experiences in the production of art works, using simple computational models with rich morphological behaviour, at the edge of mathematics, computer science, physics and biology. It organically combines ground breaking scientific discoveries in the theory of computation and complex systems with artistic representations of the research results. In this appealing book mathematicians, computer scientists, physicists, and engineers brought together marvelous and esoteric patterns generated by cellular automata, which are arrays of simple machines with complex behavior. Configurations produced by cellular automata uncover mechanics of dynamic patterns formation, their propagation and interaction in natural systems: heart pacemaker, bacterial membrane proteins, chemical rectors, water permeation in soil, compressed gas, cell division, population dynamics, reaction-diffusion media and self-organisation. The book inspires artists to take on cellular automata as a tool of creativity and it persuades scientists to convert their research results into the works of art. The book is lavishly illustrated with visually attractive examples, presented in a lively and easily accessible manner.

The success of a BCI system depends as much on the system itself as on the user's ability to produce distinctive EEG activity. BCI systems can be divided into two groups according to the placement of the electrodes used to detect and measure neurons firing in the brain. These groups are: invasive systems, electrodes are inserted directly into the cortex are used for single cell or multi unit recording, and electrocorticography (EcoG), electrodes are placed on the surface of the cortex (or dura); noninvasive systems, they are placed on the scalp and use electroencephalography (EEG) or magnetoencephalography (MEG) to detect neuron activity. The book is basically divided into three parts. The first part of the book covers the basic concepts and overviews of Brain Computer Interface. The second part describes new theoretical developments of BCI systems. The third part covers views on real applications of BCI systems.

This book presents the combined proceedings of the 13th International Conference on Multimedia and Ubiquitous Engineering (MUE 2019) and the 14th International Conference on Future Information Technology (Future Tech 2019), both held in Xi'an, China, April 24 - 26, 2019. The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies. These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science, and other disciplines related to ubiquitous computing.

This book lies at the interface of machine learning - a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail - and photonics - the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs). Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these systems significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.

This book presents comprehensive solutions for readers wanting to develop their own Natural Language Processing projects for the Thai language. Starting from the fundamental principles of Thai, it discusses each step in Natural Language Processing, and the real-world applications. In addition to theory, it also includes practical workshops for readers new to the field who want to start programming in Natural Language Processing. Moreover, it features a number of new techniques to provide readers with ideas for developing their own projects. The book details Thai words using phonetic annotation and also includes English definitions to help readers understand the content.

The amount of data used in the business world has been growing at a rapid and exponential rate. These large volumes of data have led not only to the rise of big data analytics, but to the need for improvements and advancements in the management of it. Recent Advances in Intelligent Technologies and Information Systems brings together current practices and innovations in the management and processing of diverse big data sets through technological integration. Focusing on concepts such as semantic technologies, open source tools, and soft computing, this book is an integral reference source for professionals, researchers, and practitioners interested in the application of technological advancements.

Is meaningful communication possible between two intelligent parties who share no common language or background? In this work, a theoretical framework is proposed in which it is possible to address when and to what extent such semantic communication is possible: such problems can be rigorously addressed by explicitly focusing on the goals of the communication. Under this framework, it is possible to show that for many goals, communication without any common language or background is possible using universal protocols. This work should be accessible to anyone with an undergraduate-level knowledge of the theory of computation. The theoretical framework presented here is of interest to anyone wishing to design systems with flexible interfaces, either among computers or between computers and their users.

This book presents selected papers from the 9th International Workshop of Advanced Manufacturing and Automation (IWAMA 2019), held in Plymouth, UK, on November 21-22, 2019. Discussing topics such as novel techniques for manufacturing and automation in Industry 4.0 and smart factories, which are vital for maintaining and improving economic development and quality of life, it offers researchers and industrial engineers insights into implementing the concepts and theories of Industry 4.0, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factories.

This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily students and researchers in engineering, computer science and applied mathematics. An understanding of the mathematical development of the main results requires only basic knowledge of mathematical analysis, control, and optimization theories. Some exercises with various degrees of difficulty are provided at the end of the main chapters. The material presented here may serve as a portion of an introductory course or seminar on visibility-based optimal path and motion planning problems with the objective of stimulating interest and further studies in this relatively new area.

This book highlights cooperative coverage control approaches of multi-agent systems in uncertain environments and their applications in various fields. A novel theoretical formulation of multi-agent coverage is proposed to fulfill the coverage task via divide-and-conquer scheme. By taking workload partition and sweeping operations simultaneously, a distributed sweep coverage algorithm of multi-agent systems is developed to cooperatively complete the workload on the given region, and its input-to-state stability is guaranteed in theory. Moreover, the coverage performance is evaluated by estimating the error between the actual coverage time and the optimal time. Three application scenarios are presented to demonstrate the advantages of cooperative coverage control approaches in missile interception, intelligent transportation systems and environment monitoring, respectively.

The Semantic Web is characterized by the existence of a very large number of distributed semantic resources, which together define a network of ontologies. These ontologies in turn are interlinked through a variety of different meta-relationships such as versioning, inclusion, and many more. This scenario is radically different from the relatively narrow contexts in which ontologies have been traditionally developed and applied, and thus calls for new methods and tools to effectively support the development of novel network-oriented semantic applications.

This book by Suarez-Figueroa et al. provides the necessary methodological and technological support for the development and use of ontology networks, which ontology developers need in this distributed environment. After an introduction, in its second part the authors describe the NeOn Methodology framework. The book's third part details the key activities relevant to the ontology engineering life cycle. For each activity, a general introduction, methodological guidelines, and practical examples are provided. The fourth part then presents a detailed overview of the NeOn Toolkit and its plug-ins. Lastly, case studies from the pharmaceutical and the fishery domain round out the work.

The book primarily addresses two main audiences: students (and their lecturers) who need a textbook for advanced undergraduate or graduate courses on ontology engineering, and practitioners who need to develop ontologies in particular or Semantic Web-based applications in general. Its educational value is maximized by its structured approach to explaining guidelines and combining them with case studies and numerous examples. The description of the open source NeOn Toolkit provides an additional asset, as it allows readers to easily evaluate and apply the ideas presented."

This book is an authoritative handbook of current topics, technologies and methodological approaches that may be used for the study of scholarly impact. The included methods cover a range of fields such as statistical sciences, scientific visualization, network analysis, text mining, and information retrieval. The techniques and tools enable researchers to investigate metric phenomena and to assess scholarly impact in new ways. Each chapter offers an introduction to the selected topic and outlines how the topic, technology or methodological approach may be applied to metrics-related research. Comprehensive and up-to-date, Measuring Scholarly Impact: Methods and Practice is designed for researchers and scholars interested in informetrics, scientometrics, and text mining. The hands-on perspective is also beneficial to advanced-level students in fields from computer science and statistics to information science.

This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being. This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches. We are proud to offer the readers this book.

This book offers a timely snapshot of soft computing methodologies and their applications to various problems related to sustainability, including electric energy consumption; fault diagnosis; vessel fuel consumption; determining the best sites for new malls; maritime port projects; and ad-hoc vehicular networks. Further, it demonstrates how metaheuristics and machine learning methods, fuzzy linear programming, neural networks, computing with words, linguistic models and other soft computing methods can be efficiently used to solve real-world problems. Intended as a practice-oriented guide for students, researchers, and professionals working at the interface between computer science, industrial engineering, naval engineering, agriculture, and sustainable development / climate change research, it provides readers with a set of intelligent solutions, helping them answer a range of emerging questions related to sustainability.

"Robust Control of Robots" bridges the gap between robust control theory and applications, with a special focus on robotic manipulators. It is divided into three parts: robust control of regular, fully-actuated robotic manipulators;robust post-failure control of robotic manipulators; androbust control of cooperative robotic manipulators.

In each chapter the mathematical concepts are illustrated with experimental results obtained with a two-manipulator system. They are presented in enough detail to allow readers to implement the concepts in their own systems, or in Control Environment for Robots, a MATLAB(r)-based simulation program freely available from the authors.

The target audience for "Robust Control of Robots" includes researchers, practicing engineers, and graduate students interested in implementing robust and fault tolerant control methodologies to robotic manipulators.

This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.

This book introduces basic computing skills designed for industry professionals without a strong computer science background. Written in an easily accessible manner, and accompanied by a user-friendly website, it serves as a self-study guide to survey data science and data engineering for those who aspire to start a computing career, or expand on their current roles, in areas such as applied statistics, big data, machine learning, data mining, and informatics. The authors draw from their combined experience working at software and social network companies, on big data products at several major online retailers, as well as their experience building big data systems for an AI startup. Spanning from the basic inner workings of a computer to advanced data manipulation techniques, this book opens doors for readers to quickly explore and enhance their computing knowledge. Computing with Data comprises a wide range of computational topics essential for data scientists, analysts, and engineers, providing them with the necessary tools to be successful in any role that involves computing with data. The introduction is self-contained, and chapters progress from basic hardware concepts to operating systems, programming languages, graphing and processing data, testing and programming tools, big data frameworks, and cloud computing. The book is fashioned with several audiences in mind. Readers without a strong educational background in CS--or those who need a refresher--will find the chapters on hardware, operating systems, and programming languages particularly useful. Readers with a strong educational background in CS, but without significant industry background, will find the following chapters especially beneficial: learning R, testing, programming, visualizing and processing data in Python and R, system design for big data, data stores, and software craftsmanship.

The book reports on the latest advances and applications of nonlinear control systems. It consists of 30 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought out in the broad areas of nonlinear control systems such as robotics, nonlinear circuits, power systems, memristors, underwater vehicles, chemical processes, observer design, output regulation, backstepping control, sliding mode control, time-delayed control, variables structure control, robust adaptive control, fuzzy logic control, chaos, hyperchaos, jerk systems, hyperjerk systems, chaos control, chaos synchronization, etc. Special importance was given to chapters offering practical solutions, modeling and novel control methods for the recent research problems in nonlinear control systems. This book will serve as a reference book for graduate students and researchers with a basic knowledge of electrical and control systems engineering. The resulting design procedures on the nonlinear control systems are emphasized using MATLAB software.

This book contains research contributions from leading global scholars in nature-inspired computing. It includes comprehensive coverage of each respective topic, while also highlighting recent and future trends. The contributions provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application. This book has focus on the current researches while highlighting the empirical results along with theoretical concepts to provide a comprehensive reference for students, researchers, scholars, professionals and practitioners in the field of Advanced Artificial Intelligence, Nature-Inspired Algorithms and Soft Computing.

Computational modeling and simulation has developed and expanded into a diverse range of fields such as digital signal processing, image processing, robotics, systems biology, and many more; enhancing the need for a diversifying problem solving applications in this area. Efficiency and Scalability Methods for Computational Intellect presents various theories and methods for approaching the problem of modeling and simulating intellect in order to target computation efficiency and scalability of proposed methods. Researchers, instructors, and graduate students will benefit from this current research and will in turn be able to apply the knowledge in an effective manner to gain an understanding of how to improve this field.

This book brings together scientists, researchers, practitioners, and students from academia and industry to present recent and ongoing research activities concerning the latest advances, techniques, and applications of natural language processing systems, and to promote the exchange of new ideas and lessons learned. Taken together, the chapters of this book provide a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of intelligent natural language processing. The book presents the state-of-the-art in research on natural language processing, computational linguistics, applied Arabic linguistics and related areas. New trends in natural language processing systems are rapidly emerging - and finding application in various domains including education, travel and tourism, and healthcare, among others. Many issues encountered during the development of these applications can be resolved by incorporating language technology solutions. The topics covered by the book include: Character and Speech Recognition; Morphological, Syntactic, and Semantic Processing; Information Extraction; Information Retrieval and Question Answering; Text Classification and Text Mining; Text Summarization; Sentiment Analysis; Machine Translation Building and Evaluating Linguistic Resources; and Intelligent Language Tutoring Systems.

A large international conference on Advances in Intelligent Control and Innovative Computing was held in Hong Kong, March March 16-18, 2011, under the auspices of the International MultiConference of Engineers and Computer Scientists (IMECS 2010). The IMECS is organized by the International Association of Engineers (IAENG). Intelligent Control and Computer Engineering contains 25 revised and extended research articles written by prominent researchers participating in the conference. Topics covered include artificial intelligence, control engineering, decision supporting systems, automated planning, automation systems, systems identification, modelling and simulation, communication systems, signal processing, and industrial applications. Intelligent Control and Innovative Computing offers the state of the art of tremendous advances in intelligent control and computer engineering and also serves as an excellent reference text for researchers and graduate students, working on intelligent control and computer engineering.

There isn't a facet of human life that has not been touched and influenced by robots and automation. What makes robots and machines versatile is their computational intelligence. While modern intelligent sensors and powerful hardware capabilities have given a huge fillip to the growth of intelligent machines, the progress in the development of algorithms for smart interaction, collaboration and pro-activeness will result in the next quantum jump.

This book deals with the recent advancements in design methodologies, algorithms and implementation techniques to incorporate intelligence in "robots and automation systems." Several articles deal with navigation, localization and mapping of mobile robots, a problem that engineers and researchers are grappling with all the time. Fuzzy logic, neural networks and neuro-fuzzy based techniques for real world applications have been detailed in a few articles.

This edited volume is targeted to present the latest state-of-the-art computational intelligence techniques in Robotics and Automation. It is a compilation of the extended versions of the very best papers selected from the many that were presented at the 5th International Conference on Automation, Robotics and Applications (ICARA 2011) which was held in Wellington, New Zealand from 6-8 December, 2011. Scientists and engineers who work with robots and automation systems will find this book very useful and stimulating.