Proceedings 11th Ieee International Conference And Workshop On The Engineering Of Computer Based Systems

Proceedings

Handbook of Systems Engineering and Analysis of Electro-Optical and Infrared Systems

There has been a lot of innovation in systems engineering and some fundamental advances in the fields of optics, imaging, lasers, and photonics that warrant attention. This volume focuses on concepts, principles, and methods of systems engineering‐related topics from government, industrial, and academic settings such as development and operations (DevOps), agile methods, and the concept of the “digital twin.” Handbook of Systems Engineering and Analysis of Electro‐Optical and Infrared Systems: Concepts, Principles, and Methods offers more information on decision and risk analysis and statistical methods in systems engineering such as design of experiments (DOX) methods, hypothesis testing, analysis of variance, blocking, 2k factorial analysis, and regression analysis. It includes new material on systems architecture to properly guide the evolving system design and bridge the gap between the requirements generation and design efforts. The integration of recent high‐speed atmospheric turbulence research results in the optical technical examples and case studies to illustrate the new developments is also included. A presentation of new optical technical materials on adaptive optics (AO), atmospheric turbulence compensation (ATC), and laser systems along with more are also key updates that are emphasized in the second edition 2‐volume set. Because this volume blends modern‐day systems engineering methods with detailed optical systems analysis and applies these methodologies to EO/IR systems, this new edition is an excellent text for professionals in STEM disciplines who work with optical or infrared systems. It’s also a great practical reference text for practicing engineers and a solid educational text for graduate‐level systems engineering, engineering, science, and technology students.

Bayesian Network

Bayesian networks are a very general and powerful tool that can be used for a large number of problems involving uncertainty: reasoning, learning, planning and perception. They provide a language that supports efficient algorithms for the automatic construction of expert systems in several different contexts. The range of applications of Bayesian networks currently extends over almost all fields including engineering, biology and medicine, information and communication technologies and finance. This book is a collection of original contributions to the methodology and applications of Bayesian networks. It contains recent developments in the field and illustrates, on a sample of applications, the power of Bayesian networks in dealing the modeling of complex systems. Readers that are not familiar with this tool, but have some technical background, will find in this book all necessary theoretical and practical information on how to use and implement Bayesian networks in their own work. There is no doubt that this book constitutes a valuable resource for engineers, researchers, students and all those who are interested in discovering and experiencing the potential of this major tool of the century.