Advanced Methodologies And Technologies In Artificial Intelligence Computer Simulation And Human Computer Interaction Vol 1

As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.

The aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of Web Computing, Intelligent Systems and Internet Computing. As the Web has become a major source of information, techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play key roles in many of today’s prominent Web applications such as e-commerce and computer security. Moreover, the outcome of Web services delivers a new platform for enabling service-oriented systems. The emergence of large scale distributed computing paradigms, such as Cloud Computing and Mobile Computing Systems, has opened many opportunities for collaboration services, which are at the core of any Information System. Artificial Intelligence (AI) is an area of computer science that build intelligent systems and algorithms that work and react like humans. The AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning. They have the potential to become enabling technologies for the future intelligent networks. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences are very important for the future development and innovation of Web and Internet applications.

The book aims to integrate the aspects of IoT, Cloud computing and data analytics from diversified perspectives. The book also plans to discuss the recent research trends and advanced topics in the field which will be of interest to academicians and researchers working in this area. Thus, the book intends to help its readers to understand and explore the spectrum of applications of IoT, cloud computing and data analytics. Here, it is also worth mentioning that the book is believed to draw attention on the applications of said technology in various disciplines in order to obtain enhanced understanding of the readers. Also, this book focuses on the researches and challenges in the domain of IoT, Cloud computing and Data analytics from perspectives of various stakeholders.

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing. Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time. Presents cognitive signal processing methodologies that are related to challenging image processing application domains Provides the state-of-the-art in cognitive signal processing approaches in the area of big-data image processing Focuses on other technical aspects and alternatives to traditional tools, algorithms and methodologies Discusses various real-time case studies and implemented works

This book analyzes the impact of technology in emerging markets by considering conditions and the history of how it has changed the way of working and market development in such contexts. The book delves into key areas such as fintech enterprises, artificial intelligence, pension funds, stock markets, and energy markets though applied studies and research. This book is a useful read for practitioners and scholars interested in how technology has and continues to change the way in which development is defined and achieved, particularly in emerging markets.

This book addresses the difficult task of integrating computational techniques with virtual reality and healthcare. It discusses the use of virtual reality in various areas, such as healthcare, cognitive and behavioural training, understanding mathematical graphs, human–computer interaction, fluid dynamics in healthcare industries, accurate real-time simulation, and healthcare diagnostics. Presenting the computational techniques for virtual reality in healthcare, it is a valuable reference resource for professionals at educational institutes as well as researchers, scientists, engineers and practitioners in industry.

Digital, visual media are found in most aspects of everyday life, from workplaces to household devices - computer and digital television screens, appliances such as refrigerators and home assistants, and applications for social media and gaming. Each technologically enabled opportunity brings an increasingly sophisticated language with the act of pursuing the intrasensorial ways of perceiving the world around us - through touch, movement, sound and vision - that is the heart of screen media use and audience engagement with digital artifacts. Drawing on digital media's currently evolving transformation and transforming capacity this book builds a story of the multiple processes in robotics and AI, virtual reality, creative image and sound production, the representation of data and creative practice. Issues around commodification, identity, identification, and political economy are critically examined for the emerging and affecting encounters and perceptions that are brought to bear.

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications is a comprehensive survey of this fast-paced field that is of interest to all HCI practitioners, educators, consultants, and researchers. This includes computer scientists; industrial, electrical, and computer engineers; cognitive scientists; exp

This book consists of a collection of the high-quality research articles in the field of computer vision and robotics which are presented in the International Conference on Computer Vision and Robotics (CVR 2021), organized by BBD University Lucknow, India, during 7–8 August 2021. The book discusses applications of computer vision and robotics in the fields like medical science, defence, and smart city planning. The book presents recent works from researchers, academicians, industry, and policy makers.

This volume includes contributions based on selected full papers presented at the 11th Pan-Hellenic and International Conference “ICT in Education”, held in Greece in 2018. The volume includes papers covering technical, pedagogical, organizational, instructional, as well as policy aspects of ICT in Education and e-Learning. Special emphasis is given to applied research relevant to the educational practice guided by the educational realities in schools, colleges, universities and informal learning organizations. This volume encompasses current trends, perspectives, and approaches determining e-Learning and ICT integration in practice, including learning and teaching, curriculum and instructional design, learning media and environments, teacher education and professional development. It is based on research work originally presented at the conference, but the call for chapters was open and disseminated to the international community attracting also international contributions.

IE-2 > FV 5E-3 > FV IE-3 > FV IE-4 > FV Trun- Total IST and IST Components Total IST FV> IE-2 Type >5E-3 > IE-3 > IE-4 >0 cated IPE Components Not Modeled in PRA Components 11 3 6 5 27 73 100 AOV 2 CV 4 21 24 16 12 77 94 171 4 6 10 HOV 4 34 158 MOV 2 5 35 33 24 25 124 43 43 MV 2 PORV 1 1 2 PUMP 12 5 6 1 3 27 9 36 54 54 SOV SRV 20 3 23 23 Total 39 17 73 61 49 45 284 313 597 ------- --- Table 2. Levell IPEEE Basic Event Importance - Risk Achievement Worth Total IST and (PE IST Components Not Total IST 2>RAW>0 Truncated Type RAW>2 Components Modeled in PRA Components 100 AOV 13 9 5 27 73 CV 52 16 9 77 94 171 4 4 6 10 HOV MOV 60 54 10 124 34 158 43 43 MV PORV 2 2 2 PUMP 24 3 27 9 36 SOV 54 54 SRV 23 23 23 597 Total 155 102 27 284 313 ~~--- -. . j S 702 and 2 includes the following IST component types: pumps, air-operated valves (AOV), check valves (CV), hydraulically-operated valves (HOV), motor-operated valves (MOV), manual valves (MV), pressurizer power-operated relief valves (PORV), solenoid operated valves (SOV), and safety reliefvalves (SRV).

Solidly founded on 25 years of research and teaching, the author integrates the salient features of the subdisciplines of computer science into a comprehensive conceptual framework for the design of human-computer interfaces. He combines definitions, models, taxonomies, structures, and techniques with extensive references and citations to provide professors and students of all levels with a text and practical reference.