Azad M. Madni

This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners.

This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems.

This book explores the ways that disciplinary convergence and technological advance are transforming systems engineering to address gaps in complex systems engineering: Transdisciplinary Systems Engineering (TSE). TSE reaches beyond traditional disciplines to find connections—and this book examines a range of new methods from across such disparate areas of scholarship as computer science, social science, human studies, and systems design to reveal patterns, efficiencies, affordances, and pathways to intuitive design. Organized to serve multiple constituencies, the book stands as an ideal textbook supplement for graduate courses in systems engineering, a reference text for program managers and practicing engineers in all industries, and a primary source for researchers engaged in multidisciplinary research in systems engineering and design.

This textbook is about three key aspects of system design: decision making under uncertainty, trade-off studies and formal risk analyses. Recognizing that the mathematical treatment of these topics is similar, the authors generalize existing mathematical techniques to cover all three areas. Common to these topics are importance weights, combining functions, scoring functions, quantitative metrics, prioritization and sensitivity analyses. Furthermore, human decision-making activities and problems use these same tools. Therefore, these problems are also treated uniformly and modeled using prospect theory. Aimed at both engineering and business practitioners and students interested in systems engineering, risk analysis, operational management, and business process modeling, Tradeoff Decisions in System Design explains how humans can overcome cognitive biases and avoid mental errors when conducting trade-off studies and risk analyses in a wide range of domains. With generous use ofexamples as a common thread across chapters this book.“This book provides an excellent road map for designing and producing competitive products.”

This book explores the ways that disciplinary convergence and technological advance are transforming systems engineering to address gaps in complex systems engineering: Transdisciplinary Systems Engineering (TSE). TSE reaches beyond traditional disciplines to find connections—and this book examines a range of new methods from across such disparate areas of scholarship as computer science, social science, human studies, and systems design to reveal patterns, efficiencies, affordances, and pathways to intuitive design. Organized to serve multiple constituencies, the book stands as an ideal textbook supplement for graduate courses in systems engineering, a reference text for program managers and practicing engineers in all industries, and a primary source for researchers engaged in multidisciplinary research in systems engineering and design.

This textbook is about three key aspects of system design: decision making under uncertainty, trade-off studies and formal risk analyses. Recognizing that the mathematical treatment of these topics is similar, the authors generalize existing mathematical techniques to cover all three areas. Common to these topics are importance weights, combining functions, scoring functions, quantitative metrics, prioritization and sensitivity analyses. Furthermore, human decision-making activities and problems use these same tools. Therefore, these problems are also treated uniformly and modeled using prospect theory. Aimed at both engineering and business practitioners and students interested in systems engineering, risk analysis, operational management, and business process modeling, Tradeoff Decisions in System Design explains how humans can overcome cognitive biases and avoid mental errors when conducting trade-off studies and risk analyses in a wide range of domains. With generous use ofexamples as a common thread across chapters this book.“This book provides an excellent road map for designing and producing competitive products.”