"This book explores the complex world of computational intelligence, which utilizes computational methodologies such as fuzzy logic systems, neural networks, and evolutionary computation for the purpose of managing and using data effectively to address complicated real-world problems"--
There are many different approaches to understanding human consciousness. By conducting research to better understand various biological mechanisms, these can be redefined and utilized for technological purposes. Advanced Research on Biologically Inspired Cognitive Architectures is an essential reference source for the latest scholarly research on the biological elements of human cognition and examines the applications of consciousness within computing environments. Featuring exhaustive coverage on a broad range of innovative topics and perspectives, such as artificial intelligence, bio-robotics, and human-computer interaction, this publication is ideally designed for academics, researchers, professionals, graduate students, and practitioners seeking current research on the exploration of the intricacies of consciousness and different approaches of perception.
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.
Many techniques have been developed to control the variety of dynamic systems. To develop those control techniques, it is fundamental to know the mathematical relations between the system inputs and outputs. Incorporating Nature-Inspired Paradigms in Computational Applications is a critical scholarly resource that examines the application of nature-inspired paradigms on system identification. Featuring coverage on a broad range of topics such as biogeographic computation, evolutionary control systems, and natural computing, this book is geared towards IT professionals, engineers, computer scientists, academicians, researchers, and graduate-level students seeking current research on the application of nature-inspired paradigms.
The development of new information and communication technologies has a considerable impact on the way humans interact with each other and their environment. The proper use of these technologies is an important consideration in the success of modern human endeavors. Multidisciplinary Perspectives on Telecommunications, Wireless Systems, and Mobile Computing explores some of the latest advances in wireless communication technologies, making use of empirical research and analytical case studies to evaluate best practices in the discipline. This book will provide insight into the next generation of information and communication technologies for developers, engineers, students, researchers, and managers in the telecommunications field.
Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.
Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.
The process of patient education allows for patients to think about their health in new ways and for educators and professionals to propose new ways to heal, with the ultimate goal of patients having a positive outlook on life and consistently maintained health. Innovative Collaborative Practice and Reflection in Patient Education presents multigenre writing, incorporating authors' personal and professional stories along with academic theories. It combines the fields of education and medicine, presenting innovative approaches to health education and designing new approaches to healing. This research publication will impact the field of health education and be of use to educators, researchers, practitioners, professionals, and patients.
As is true of most technological fields, the software industry is constantly advancing and becoming more accessible to a wider range of people. The advancement and accessibility of these systems creates a need for understanding and research into their development. Optimizing Contemporary Application and Processes in Open Source Software is a critical scholarly resource that examines the prevalence of open source software systems as well as the advancement and development of these systems. Featuring coverage on a wide range of topics such as machine learning, empirical software engineering and management, and open source, this book is geared toward academicians, practitioners, and researchers seeking current and relevant research on the advancement and prevalence of open source software systems.
Road accidents caused by impaired and distracted driving as well as traffic congestion are on the rise, with the numbers increasing dramatically every day. Intelligent transportation systems (ITS) aim to improve the efficiency and safety of traveling by consolidating vehicle operations, managing vehicle traffic, and notifying drivers with alerts and safety messages in real time. Vehicular Cloud Computing for Traffic Management and Systems provides innovative research on the rapidly advancing applications of vehicle-to-vehicle and vehicle-to-infrastructure communication. It also covers the need to fully utilize vehicular ad-hoc network (VANET) resources to provide updated and dynamic information about the conditions of road traffic so that the number of road accidents can be minimized. Featuring research on topics such as identity management, computational architecture, and resource management, this book is ideally designed for urban planners, researchers, policy makers, graduate-level students, transportation engineers, and technology developers seeking current research on vehicle computational design, architecture, security, and privacy.
