Artificial Intelligence : Applications and innovations
It's about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Provides insight into prospective research and application areas related to industry and technology / Discusses industry- based inputs on success stories of technology adoption / Discusses technology applications from a research perspective in the field of AI / Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning
Advances in Computer and Information Sciences and Engineering
Advances in Computer and Information Sciences and Engineering includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Software Engineering, Computer Engineering, and Systems Engineering and Sciences.
25 Years of Model Checking : History, Achievements, Perspectives
Model checking technology is among the foremost applications of logic to computer science and computer engineering. The model checking community has achieved many breakthroughs, bridging the gap between theoretical computer science and hardware and software engineering, and it is reaching out to new challenging areas such as system biology and hybrid systems. Model checking is extensively used in the hardware industry and has also been applied to the verification of many types of software. Model checking has been introduced into computer science and electrical engineering curricula at universities worldwide and has become a universal tool for the analysis of systems.
Managing Distributed Cloud Applications and Infrastructure : A Self-Optimising Approach
The emergence of the Internet of Things (IoT), combined with greater heterogeneity not only online in cloud computing architectures but across the cloud-to-edge continuum, is introducing new challenges for managing applications and infrastructure across this continuum.
Advances in Information Technologies for Electromagnetics
Simple tutorial chapters introduce the reader to cutting edge technologies, such as parallel and distributed computing, object-oriented technologies, grid computing, semantic grids, agent based computing and service-oriented architectures. On such bases, a variety of EM applications is proposed: 1) parallel FDTD codes (both for antenna analysis and for metamaterial applications), 2) grid computing for computational EM (CEM) (with applications to antenna arrays, wireless and remote-sensing systems) 3) mobile agents for parametric CEM modeling 4) complex/hybrid EM software environments (with applications to planar circuits, quasi-optical systems,…) 5) semantic grids for CAE of antennas arrays.




