These proceedings address a broad range of topic areas, including telecommunication, power systems, digital signal processing, robotics, control systems, renewable energy, power electronics, soft computing and more.
This book presents mathematical models of demand-side management programs, together with operational and control problems for power and renewable energy systems.
This book constitutes the proceedings of the 40th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2021, which took place in York, UK, in September 2021.
With a specific focus on energy efficiency, Optimizing IoT Networks examines the application of machine learning to enhance resource allocations in IoT networks.
Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML).
Health Technologies and Informatics: Research and Developments provides a comprehensive overview of mobile health applications, biodata management and analytics, medical imaging, personalized and public health systems, and biosignal processing.
Presenting innovative research methods, this second edition of a bestseller describes a simple and practical methodology for conducting cutting-edge design science research (DSR).
Focusing on a very active area of mathematical research in the last decade, Combinatorics of Set Partitions presents methods used in the combinatorics of pattern avoidance and pattern enumeration in set partitions.
Compensating for Quasi-periodic Motion in Robotic Radiosurgery outlines the techniques needed to accurately track and compensate for respiratory and pulsatory motion during robotic radiosurgery.
AI for Digital Warfare explores how the weaponising of artificial intelligence can and will change how warfare is being conducted, and what impact it will have on the corporate world.
Cognitive systems engineering has been widely and successfully applied in the design of safety critical systems such as nuclear power, aviation, and military command-and-control.
Since the invention of computers and other similar machines, scientists and researchers have been trying very hard to enhance their capabilities to perform various tasks.
Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model.
A new edition of the bestselling industrial and systems engineering text, this book provides students, researchers, and practitioners with easy access to a wide range of industrial engineering tools and techniques in a concise format.
Tree-based Methods for Statistical Learning in R provides a thorough introduction to both individual decision tree algorithms (Part I) and ensembles thereof (Part II).
Machine Learning for Radio Resource Management and Optimization in 5G and Beyond highlights a new line of research that uses innovative technologies and methods based on artificial intelligence/machine learning techniques to address issues and challenges related to radio resource management in 5G and 6G communication systems.
The 2-volume set LNCS 11613 and 11614 constitutes the refereed proceedings of the 6th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2019, held in Santa Maria al Bagno, Italy, in June 2019.
A complete reference to adaptive control of systems with nonsmooth industrial nonlinearities such as: backlash; dead-zones; component failure; friction; hysteresis; saturation; and time delays.
This book gathers the proceedings of the 2nd Latin American Congress on Automation and Robotics, held at Pontificia Universidad Javeriana de Cali, Colombia, on October 30th-November 1st, 2019.
Foundations of Reinforcement Learning with Applications in Finance aims to demystify Reinforcement Learning, and to make it a practically useful tool for those studying and working in applied areas - especially finance.
This book covers three main types of agricultural systems: the use of robotics, drones (unmanned aerial vehicles), and satellite-guided precision farming methods.
This volume encompasses many new types of constraints and clustering methods as well as delivers thorough coverage of the capabilities and limitations of constrained clustering.
Achieving state-of-the-art excellence and attaining the cost reductions associated with outstanding logistics efforts is an obvious gain in terms of competitive edge and profitability.
In the ever-evolving landscape of cancer treatment, the fusion of artificial intelligence (AI) with medical science marks a groundbreaking shift toward more precise, efficient, and personalized healthcare.
This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it.
This volume gathers the latest advances, innovations, and applications in the field of robotics engineering, as presented by leading international researchers and engineers at the Latin American Symposium on Industrial and Robotic Systems (LASIRS), held in Tampico, Mexico on October-November 30-01 2019.
Quantum computing is a field in which advanced technologies like quantum communication, artificial intelligence and machine learning can be used to secure and speed up connectivity using quantum computers, quantum drones or quantum satellites.
The book, the first in a two-volume set, covers fundamental concepts of machine design and its applications for undergraduate students of mechanical engineering.
This book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts.
With the rapidly advancing fields of Data Analytics and Computational Statistics, it's important to keep up with current trends, methodologies, and applications.
This book presents advanced control techniques that use neural networks to deal with grid disturbances in the context renewable energy sources, and to enhance low-voltage ride-through capacity, which is a vital in terms of ensuring that the integration of distributed energy resources into the electrical power network.