Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction
Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction

Author: Khosrow-Pour, D.B.A., Mehdi

Publisher: IGI Global

Published: 2018-09-28

Total Pages: 1456

ISBN-13: 1522573690

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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.

VLSI and Hardware Implementations using Modern Machine Learning Methods
VLSI and Hardware Implementations using Modern Machine Learning Methods

Author: Sandeep Saini

Publisher: CRC Press

Published: 2021-12-30

Total Pages: 329

ISBN-13: 1000523810

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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.

Bio-inspired Swarm Robotics and Control: Algorithms, Mechanisms, and Strategies
Bio-inspired Swarm Robotics and Control: Algorithms, Mechanisms, and Strategies

Author: Bhowmick, Parijat

Publisher: IGI Global

Published: 2024-04-23

Total Pages: 281

ISBN-13:

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The academic community is currently facing the challenge of navigating the complexities of swarm robotics. This field demands understanding the design, control, and coordination of autonomous robotic swarms. The intricacies of developing algorithms that facilitate communication, cooperation, and adaptation among simple individual agents remain a formidable obstacle. Addressing issues like task allocation, formation control, path planning, and decentralized decision-making are pivotal to unlocking the true potential of swarm robotics. Bio-inspired Swarm Robotics and Control: Algorithms, Mechanisms, and Strategies immerses readers in the cutting-edge realm of swarm robotics, a discipline inspired by the intricate choreography observed in biological systems like insect colonies, bird flocks, and fish schools. Encompassing a rich array of bio-inspired algorithms, mechanisms, and strategies, the text elucidates how robots can communicate, cooperate, and adapt within dynamic environments. The book propels robotics, automation, and artificial intelligence advancements by fostering interdisciplinary connections and charting a course toward more efficient and resilient multi-robot systems. This book is ideal for biologists, engineers, and computer scientists to join forces in unlocking the full potential of swarm robotics.

Trends in Deep Learning Methodologies
Trends in Deep Learning Methodologies

Author: Vincenzo Piuri

Publisher: Academic Press

Published: 2020-11-12

Total Pages: 308

ISBN-13: 0128232684

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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

Explainable Artificial Intelligence for Smart Cities
Explainable Artificial Intelligence for Smart Cities

Author: Mohamed Lahby

Publisher: CRC Press

Published: 2021-11-09

Total Pages: 361

ISBN-13: 1000472361

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Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future. The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become ‘black-box’ to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

Neuroscientific Insights and Therapeutic Approaches to Eating Disorders
Neuroscientific Insights and Therapeutic Approaches to Eating Disorders

Author: Kukreja, Jyoti

Publisher: IGI Global

Published: 2024-07-23

Total Pages: 460

ISBN-13:

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In the complex landscape of binge eating disorders, a pervasive and intricate challenge unfolds. Binge eating, characterized by Binge eating disorders, is a difficult challenge that requires a nuanced understanding of the underlying neuroscientific mechanisms for effective prevention and intervention strategies. There is a pressing need to bridge the gap between cutting-edge neuroscientific research and the evolving therapeutic landscape. To address this, our groundbreaking book is tailored for academic scholars in the neuroscientific community. We offer a transformative journey into the heart of binge eating disorders, unraveling the mysteries that govern neural circuits, genetic factors, hormonal imbalances, and more. Neuroscientific Insights and Therapeutic Approaches to Eating Disorders is a beacon for researchers, clinicians, and mental health professionals seeking to deepen their comprehension of eating disorders. It addresses the present-day challenges posed by binge eating and presents a roadmap for future research and clinical applications. This comprehensive resource synthesizes the latest findings in neuroscience with innovative therapeutic approaches, ultimately paving the way for improved outcomes. Episodes of excessive food consumption and loss of control demand a nuanced understanding of the underlying neuroscientific mechanisms for effective prevention and intervention strategies. Our present reality is marked by a pressing need to bridge the gap between cutting-edge neuroscientific research and the evolving therapeutic landscape. The intricate relationship between the brain and eating disorders calls for a comprehensive resource that not only dissects the neurobiological foundations but also illuminates the path toward innovative therapeutic approaches.

Machine Learning Methods for Pain Investigation Using Physiological Signals
Machine Learning Methods for Pain Investigation Using Physiological Signals

Author: Philip Johannes Gouverneur

Publisher: Logos Verlag Berlin GmbH

Published: 2024-06-14

Total Pages: 228

ISBN-13: 3832582576

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Pain assessment has remained largely unchanged for decades and is currently based on self-reporting. Although there are different versions, these self-reports all have significant drawbacks. For example, they are based solely on the individual’s assessment and are therefore influenced by personal experience and highly subjective, leading to uncertainty in ratings and difficulty in comparability. Thus, medicine could benefit from an automated, continuous and objective measure of pain. One solution is to use automated pain recognition in the form of machine learning. The aim is to train learning algorithms on sensory data so that they can later provide a pain rating. This thesis summarises several approaches to improve the current state of pain recognition systems based on physiological sensor data. First, a novel pain database is introduced that evaluates the use of subjective and objective pain labels in addition to wearable sensor data for the given task. Furthermore, different feature engineering and feature learning approaches are compared using a fair framework to identify the best methods. Finally, different techniques to increase the interpretability of the models are presented. The results show that classical hand-crafted features can compete with and outperform deep neural networks. Furthermore, the underlying features are easily retrieved from electrodermal activity for automated pain recognition, where pain is often associated with an increase in skin conductance.

Cases on Modern Computer Systems in Aviation
Cases on Modern Computer Systems in Aviation

Author: Shmelova, Tetiana

Publisher: IGI Global

Published: 2019-02-19

Total Pages: 506

ISBN-13: 1522575898

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Because trainees need to learn about the underlying technologies to use automation safely and efficiently, the development of automated aviation systems training is a growing challenge. Task analysis has been singled out as the basis of the training, but it can be more time-consuming than traditional development techniques. Cases on Modern Computer Systems in Aviation is an essential reference source that covers new information technology use in aviation systems to streamline the cybersecurity, decision-making, planning, and design processes within the aviation industry. Featuring coverage on a broad range of topics such as computer systems in aviation, artificial intelligence, software-defined networking (SDN), air navigation systems, decision support systems (DSS), and more, this publication is ideally designed for aviation specialists and industry professionals, technicians, practitioners, researchers, and academicians seeking current research on modern modeling approaches to streamline management in aviation.

Data Analytics Applications in Emerging Markets
Data Analytics Applications in Emerging Markets

Author: José Antonio Núñez Mora

Publisher: Springer Nature

Published: 2022-10-26

Total Pages: 209

ISBN-13: 9811946957

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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.