This book delivers the state of the art in deep learning (DL) methods hybridized with evolutionary computation (EC). Over the last decade, DL has dramatically reformed many domains: computer vision, speech recognition, healthcare, and automatic game playing, to mention only a few. All DL models, using different architectures and algorithms, utilize multiple processing layers for extracting a hierarchy of abstractions of data. Their remarkable successes notwithstanding, these powerful models are facing many challenges, and this book presents the collaborative efforts by researchers in EC to solve some of the problems in DL. EC comprises optimization techniques that are useful when problems are complex or poorly understood, or insufficient information about the problem domain is available. This family of algorithms has proven effective in solving problems with challenging characteristics such as non-convexity, non-linearity, noise, and irregularity, which dampen the performance of most classic optimization schemes. Furthermore, EC has been extensively and successfully applied in artificial neural network (ANN) research -from parameter estimation to structure optimization. Consequently, EC researchers are enthusiastic about applying their arsenal for the design and optimization of deep neural networks (DNN). This book brings together the recent progress in DL research where the focus is particularly on three sub-domains that integrate EC with DL: (1) EC for hyper-parameter optimization in DNN; (2) EC for DNN architecture design; and (3) Deep neuroevolution. The book also presents interesting applications of DL with EC in real-world problems, e.g., malware classification and object detection. Additionally, it covers recent applications of EC in DL, e.g. generative adversarial networks (GAN) training and adversarial attacks. The book aims to prompt and facilitate the research in DL with EC both in theory and in practice.

The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research.

This book's main goals are to bring together in a concise way all the methodologies, standards and recommendations related to Data, Queries, Links, Semantics, Validation and other issues concerning machine-readable data on the Web, to describe them in detail, to provide examples of their use, and to discuss how they contribute to - and how they have been used thus far on - the "Web of Data". As the content of the Web becomes increasingly machine readable, increasingly complex tasks can be automated, yielding more and more powerful Web applications that are capable of discovering, cross-referencing, filtering, and organizing data from numerous websites in a matter of seconds. The book is divided into nine chapters, the first of which introduces the topic by discussing the shortcomings of the current Web and illustrating the need for a Web of Data. Next, "Web of Data" provides an overview of the fundamental concepts involved, and discusses some current use-cases on the Web where such concepts are already being employed. "Resource Description Framework (RDF)" describes the graph-structured data model proposed by the Semantic Web community as a common data model for the Web. The chapter on "RDF Schema (RDFS) and Semantics" presents a lightweight ontology language used to define an initial semantics for terms used in RDF graphs. In turn, the chapter "Web Ontology Language (OWL)" elaborates on a more expressive ontology language built upon RDFS that offers much more powerful ontological features. In "SPARQL Query Language" a language for querying and updating RDF graphs is described, with examples of the features it supports, supplemented by a detailed definition of its semantics. "Shape Constraints and Expressions (SHACL/ShEx)" introduces two languages for describing the expected structure of - and expressing constraints on - RDF graphs for the purposes of validation. "Linked Data" discusses the principles and best practices proposed by the Linked Data community for publishing interlinked (RDF) data on the Web, and how these techniques have been adopted. The final chapter highlights open problems and rounds out the coverage with a more general discussion on the future of the Web of Data. The book is intended for students, researchers and advanced practitioners interested in learning more about the Web of Data, and about closely related topics such as the Semantic Web, Knowledge Graphs, Linked Data, Graph Databases, Ontologies, etc. Offering a range of accessible examples and exercises, it can be used as a textbook for students and other newcomers to the field. It can also serve as a reference handbook for researchers and developers, as it offers up-to-date details on key standards (RDF, RDFS, OWL, SPARQL, SHACL, ShEx, RDB2RDF, LDP), along with formal definitions and references to further literature. The associated website webofdatabook.org offers a wealth of complementary material, including solutions to the exercises, slides for classes, raw data for examples, and a section for comments and questions.

This new textbook examines the motivations and the different algorithms for automatic document summarization (ADS). We performed a recent state of the art. The book shows the main problems of ADS, difficulties and the solutions provided by the community. It presents recent advances in ADS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several exemples are included in order to clarify the theoretical concepts. The books currently available in the area of Automatic Document Summarization are not recent. Powerful algorithms have been developed in recent years that include several applications of ADS. The development of recent technology has impacted on the development of algorithms and their applications. The massive use of social networks and the new forms of the technology requires the adaptation of the classical methods of text summarizers. This is a new textbook on Automatic Text Summarization, based on teaching materials used in two or one-semester courses. It presents a extensive state-of-art and describes the new systems on the subject. Previous automatic summarization books have been either collections of specialized papers, or else authored books with only a chapter or two devoted to the field as a whole. In other hand, the classic books on the subject are not recent.

DIRECTING, DIALOGUE AND ACTING From Richard Williams' The Animator's Survival Kit comes key chapters in mini form. The Animator's Survival Kit is the essential tool for animators. However, sometimes you don't want to carry the hefty expanded edition around with you to your college or studio if you're working on just one aspect of it that day. The Animation Minis take some of the most essential chapters and make them available in smaller, lightweight, hand-bag/backpack size versions. Easy to carry. Easy to study. This Mini focuses on Directing, Dialogue and Acting. As a director, whatever your idea is, you want to put it over, so the main thing with directing is to be clear - very clear. The Director's job is to hold everything together so that the animator can give the performance. Richard Williams shows how that performance can be achieved with flexibility and contrast. With Acting and Dialogue, the temptation is to try to do everything at once - Williams' advice: do one thing at a time.

Too often the suggestion of using games and virtual environments in an educational setting is met with skepticism and objections. Many traditionally-oriented educators are simply not aware of the benefits that come from implementing digital games into an instructional environment. Serious Games and Virtual Worlds in Education, Professional Development, and Healthcare seeks to counter these doubts by explaining how digital environments can easily become familiar and beneficial for educational and professional development. Highlighting techniques beyond the traditional practice, this reference source is useful for researchers, academics, professionals, and students interested in the benefits to implementing these games into various aspects of our environment.

This book focuses on the key technologies and scientific problems involved in emotional robot systems, such as multimodal emotion recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the design and application examples of emotional HRI systems. Aiming at the development needs of emotional robots and emotional human-robot interaction (HRI) systems, this book introduces basic concepts, system architecture, and system functions of affective computing and emotional robot systems. With the professionalism of this book, it serves as a useful reference for engineers in affective computing, and graduate students interested in emotion recognition and intention understanding. This book offers the latest approaches to this active research area. It provides readers with the state-of-the-art methods of multimodal emotion recognition, intention understanding, and application examples of emotional HRI systems.

The technologies in data mining have been applied to bioinformatics research in the past few years with success, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining plays a essential role in understanding the emerging problems in genomics, proteomics, and systems biology. ""Advanced Data Mining Technologies in Bioinformatics"" covers important research topics of data mining on bioinformatics. Readers of this book will gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. ""Advanced Data Mining Technologies in Bioinformatics"" is extremely useful for data mining researchers, molecular biologists, graduate students, and others interested in this topic.

Artificial intelligence (AI) is influencing the future of almost every sector and human being. AI has been the primary driving force behind emerging technologies such as big data, blockchain, robots, and the internet of things (IoT), and it will continue to be a technological innovator for the foreseeable future. New algorithms in AI are changing business processes and deploying AI-based applications in various sectors. The Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence is a comprehensive reference that presents cases and best practices of AI and knowledge engineering applications on business intelligence. Covering topics such as deep learning methods, face recognition, and sentiment analysis, this major reference work is a dynamic resource for business leaders and executives, IT managers, AI scientists, students and educators of higher education, librarians, researchers, and academicians.

This 2 volume-set of IFIP AICT 583 and 584 constitutes the refereed proceedings of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020, held in Neos Marmaras, Greece, in June 2020.* The 70 full papers and 5 short papers presented were carefully reviewed and selected from 149 submissions. They cover a broad range of topics related to technical, legal, and ethical aspects of artificial intelligence systems and their applications and are organized in the following sections: Part I: classification; clustering - unsupervised learning -analytics; image processing; learning algorithms; neural network modeling; object tracking - object detection systems; ontologies - AI; and sentiment analysis - recommender systems. Part II: AI ethics - law; AI constraints; deep learning - LSTM; fuzzy algebra - fuzzy systems; machine learning; medical - health systems; and natural language. *The conference was held virtually due to the COVID-19 pandemic.

Radio Frequency Identification (RFID) is an automatic identification method, relying on storing and remotely retrieving data using devices called RFID tags (also called transponders).
This book is a guide to CompTIA's new RFID+ Security exam and includes the following study elements: Exam objectives covered in a chapter are clearly explained in the beginning of the chapter, Notes and Alerts highlight the crucial points, Exam s Eye View emphasizes the important points from the exam s perspective, Key Terms present definitions, Review Questions contain questions modeled after the real exam questions. Answers to these questions are presented with complete explanations in an appendix. Also included is a full practice exam modeled after the real exam. The answers to the exam questions are presented with full explanations.
* The only RFID+ study guide that provides 100% coverage of all exam objectives for the CompTIA RFID+ exam
* Includes a full web-based practice exam to run through before you sit your actual exam
* Packed full of special features and material to aid and reinforce learning"

This book features selected papers presented at the 15th International Conference on Electromechanics and Robotics "Zavalishin's Readings" - ER(ZR) 2020, held in Ufa, Russia, on 15-18 April 2020. The contributions, written by professionals, researchers and students, cover topics in the field of automatic control systems, electromechanics, electric power engineering and electrical engineering, mechatronics, robotics, automation and vibration technologies. The Zavalishin's Readings conference was established as a tribute to the memory of Dmitry Aleksandrovich Zavalishin (1900-1968) - a Russian scientist, corresponding member of the USSR Academy of Sciences and founder of the school of valve energy converters based on electric machines and valve converters energy. The first conference was organized by the Institute of Innovative Technologies in Electromechanics and Robotics at the Saint Petersburg State University of Aerospace Instrumentation in 2006.

The genre of the video clip has been established for more than thirty years, mainly served by the sub genres of video art and music video. This book explores processes of hybridization between music video, film, and video art by presenting current theoretical discourses and engaging them through interviews with well-known artists and directors, bringing to the surface the crucial questions of art practice. The collection discusses topics including postcolonialism, posthumanism, gender, race and class and addresses questions regarding the hybrid media structure of video, the diffusion between content and form, art and commerce as well as pop culture and counterculture. Through the diversity of the areas and interviews included, the book builds on and moves beyond earlier aesthetics-driven perspectives on music video.

This book offers a comprehensive reference guide to customer-oriented product design and intelligence. It provides readers with the necessary intelligent tools for designing customer-oriented products in contexts characterized by incomplete information or insufficient data, where classical product design approaches cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including fuzzy QFD, fuzzy FMEA, the fuzzy Kano model, fuzzy axiomatic design, fuzzy heuristics-based design, conjoint analysis-based design, and many others. To foster reader comprehension, all chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers, and postgraduate students pursuing research on customer-oriented product design. Moreover, by extending all the main aspects of classical customer-oriented product design to its intelligent and fuzzy counterparts, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas, and developments.

This book relates research being implemented in three main research areas: secure connectivity and intelligent systems, real-time analytics and manufacturing knowledge and virtual manufacturing. Manufacturing SMEs and MNCs want to see how Industry 4.0 is implemented. On the other hand, groundbreaking research on this topic is constantly growing. For the aforesaid reason, the Singapore Agency for Science, Technology and Research (A*STAR), has created the model factory initiative. In the model factory, manufacturers, technology providers and the broader industry can (i) learn how I4.0 technologies are implemented on real-world manufacturing use-cases, (ii) test process improvements enabled by such technologies at the model factory facility, without disrupting their own operations, (iii) co-develop technology solutions and (iv) support the adoption of solutions at their everyday industrial operation. The book constitutes a clear base ground not only for inspiration of researchers, but also for companies who will want to adopt smart manufacturing approaches coming from Industry 4.0 in their pathway to digitization.

Healthcare Information Systems and Informatics: Research and Practices compiles estimable knowledge on the research of information systems and informatics applications in the healthcare industry. This book addresses organizational issues, including technology adoption, diffusion, and acceptance, as well as cost benefits and cost effectiveness, of advancing health information systems and informatics applications as innovative forms of investment in healthcare. Rapidly changing technology and the complexity of its applications make this book an invaluable resource to researchers and practitioners in the healthcare fields.

This concise book provides a survival toolkit for efficient, large-scale software development. Discussing a multi-contextual research framework that aims to harness human-related factors in order to improve flexibility, it includes a carefully selected blend of models, methods, practices, and case studies. To investigate mission-critical communication aspects in system engineering, it also examines diverse, i.e. cross-cultural and multinational, environments. This book helps students better organize their knowledge bases, and presents conceptual frameworks, handy practices and case-based examples of agile development in diverse environments. Together with the authors' previous books, "Crisis Management for Software Development and Knowledge Transfer" (2016) and "Managing Software Crisis: A Smart Way to Enterprise Agility" (2018), it constitutes a comprehensive reference resource adds value to this book.

This book discusses the impact of advanced information technologies, such as data processing, machine learning, and artificial intelligence, on organizational decision-making processes and practices. One of the book's central themes is the interplay between human reasoning and machine logic in the context of organizational functioning, specifically, the fairly common situations in which subjective beliefs are pitted against objective evidence giving rise to conflict rather than enhancing the quality of organizational sensemaking. Aiming to not only raise the awareness of the potential challenges but also to offer solutions, the book delineates and discusses the core impediments to effective human-information technology interactions, and outlines strategies for overcoming those obstacles on the way to enhancing the efficacy of organizational decision-making.

This book presents the stream-tube method (STM), a method offering computational means of dealing with the two- and three-dimensional properties of numerous incompressible materials in static and dynamic conditions. The authors show that the kinematics and stresses associated with the flow and deformation in such materials can be treated by breaking the system down into simple computational sub-domains in which streamlines are straight and parallel and using one or two mapping functions in steady-state and non-steady-state conditions. The STM is considered for various problems in non-Newtonian fluid mechanics with different geometries. The book makes use of examples and applications to illustrate the use of the STM. It explores the possibilities of computation on simple mapped rectangular domains and three-dimensional parallel-piped domains under different conditions. Complex materials with memory are considered simply without particle tracking problems. Readers, including researchers, engineers and graduate students, with a foundational knowledge of calculus, linear algebra, differential equations and fluid mechanics will benefit most greatly from this book.

The follow-up to Cory Althoff's bestselling The Self-Taught Programmer, which inspired hundreds of thousands of professionals to learn to program outside of school! Fresh out of college and with just a year of self-study behind him, Cory Althoff was offered a dream first job as a software engineer for a well-known tech company, but he quickly found himself overwhelmed by the amount of things he needed to know, but hadn't learned yet. This experience combined with his personal journey learning to program inspired his widely praised guide, The Self-Taught Programmer. Now Cory's back with another guide for the self-taught community of learners focusing on the foundations of computer science. The Self-Taught Computer Scientist introduces beginner and self-taught programmers to computer science fundamentals that are essential for success in programming and software engineering fields. Computer science is a massive subject that could cover an entire lifetime of learning. This book does not aim to cover everything you would learn about if you went to school to get a computer science degree. Instead, Cory's goal is to give you an introduction to some of the most important concepts in computer science that apply to a programming career. With a focus on data structures and algorithms, The Self-Taught Computer Scientist helps you fill gaps in your knowledge, prepare for a technical interview, feel knowledgeable and confident on the job, and ultimately, become a better programmer. Learn different algorithms including linear and binary search and test your knowledge with feedback loops Understand what a data structure is and study arrays, linked lists, stacks, queues, hash tables, binary trees, binary heaps, and graphs Prepare for technical interviews and feel comfortable working with more experienced colleagues Discover additional resources and tools to expand your skillset and continue your learning journey It's as simple as this: You have to study computer science if you want to become a successful programmer, and if you don't understand computer science, you won't get hired. Ready for a career in programming, coding, or software engineering and willing to embrace an "always be learning" mindset? The Self-Taught Computer Scientist is for you.

This volume gathers the latest advances, innovations, and applications in the field of intelligent systems such as robots, cyber-physical and embedded systems, as presented by leading international researchers and engineers at the International Conference on Intelligent Technologies in Robotics (ITR), held in Moscow, Russia on October 21-23, 2019. It covers highly diverse topics, including robotics, design and machining, control and dynamics, bio-inspired systems, Internet of Thing, Big Data, RFID technology, blockchain, trusted software, cyber-physical systems (CFS) security, development of CFS in manufacturing, protection of information in CFS, cybersecurity of CFS. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists, demonstrating that intelligent systems will drive the technological and societal change in the coming decades.

Recent advances in gene sequencing technology are now shedding light on the complex interplay between genes that elicit phenotypic behavior characteristic of any given organism. In order to mediate internal and external signals, the daunting task of classifying an organism's genes into complex signaling pathways needs to be completed. The Handbook of Research on Computational Methodologies in Gene Regulatory Networks focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization. This innovative Handbook of Research presents a complete overview of computational intelligence approaches for learning and optimization and how they can be used in gene regulatory networks.

Drawn to Life is a two-volume collection of the legendary lectures of long-time Disney animator Walt Stanchfield. For over 20 years, Walt mentored a new generation of animators at the Walt Disney Studios and influenced such talented artists such as Tim Burton, Brad Bird, Glen Keane, and Andreas Deja. His writing and drawings have become must-have lessons for fine artists, film professionals, animators, and students looking for inspiration and essential training in drawing and the art of animation. Written by Walt Stanchfield (1919–2000), who began work for the Walt Disney Studios in the 1950s. His work can be seen in films such as Sleeping Beauty, The Jungle Book, 101 Dalmatians, and Peter Pan. Edited by Disney Legend and Oscar®-nominated producer Don Hahn, whose credits include the classic Beauty and the Beast, The Lion King, and Hunchback of Notre Dame.