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"It is common for us today to associate the practice of science primarily with the act of seeing—with staring at computer screens, analyzing graphs, and presenting images. We may notice that physicians use stethoscopes to listen for disease, that biologists tune into sound recordings to understand birds, or that engineers have created Geiger tellers warning us for radiation through sound. But in the sciences overall, we think, seeing is believing. This open access book explains why, indeed, listening for knowledge plays an ambiguous, if fascinating, role in the sciences. For what purposes have scientists, engineers and physicians listened to the objects of their interest? How did they listen exactly? And why has listening often been contested as a legitimate form of access to scientific knowledge? This concise monograph combines historical and ethnographic evidence about the practices of listening on shop floors, in laboratories, field stations, hospitals, and conference halls, between the 1920s and today. It shows how scientists have used sonic skills—skills required for making, recording, storing, retrieving, and listening to sound—in ensembles: sets of instruments and techniques for particular situations of knowledge making. Yet rather than pleading for the emancipation of hearing at the expense of seeing, this essay investigates when, how, and under which conditions the ear has contributed to science dynamics, either in tandem with or without the eye."

"This book presents state-of-the-art probabilistic methods for the reliability analysis and design of engineering products and processes. It seeks to facilitate practical application of probabilistic analysis and design by providing an authoritative, in-depth, and practical description of what probabilistic analysis and design is and how it can be implemented. The text is packed with many practical engineering examples (e.g., electric power transmission systems, aircraft power generating systems, and mechanical transmission systems) and exercise problems. It is an up-to-date, fully illustrated reference suitable for both undergraduate and graduate engineering students, researchers, and professional engineers who are interested in exploring the fundamentals, implementation, and applications of probabilistic analysis and design methods."

""Callister and Rethwisch?s Fundamentals of Materials Science and Engineering, 4th Edition continues to take the integrated approach to the organization of topics. That is, one specific structure, characteristic, or property type at a time is discussed for all three basic material types -- metals, ceramics, and polymeric materials. This order of presentation allows for the early introduction of non-metals and supports the engineer?s role in choosing materials based upon their characteristics. Also discussed are new, cutting-edge materials. Using clear, concise terminology that is familiar to students, Fundamentals presents material at an appropriate level for both student comprehension and instructors who may not have a materials background"-- Provided by publisher."

"Model-Based Systems Engineering (MBSE), which tackles architecting and design of complex systems through the use of formal models, is emerging as the most critical component of systems engineering. This textbook specifies the two leading conceptual modeling languages, OPM—the new ISO 19450, composed primarily by the author of this book, and OMG SysML. It provides essential insights into a domain-independent,discipline-crossing methodology of developing or researching complex systems of any conceivable kind and size. Combining theory with a host of industrial, biological, and daily life examples, the book explains principles and provides guidelines for architecting complex, multidisciplinary systems, making it an indispensable resource for systems architects and designers, engineers of any discipline, executives at all levels, project managers, IT professionals, systems scientists, and engineering students.Professor Dov Dori is Harry Lebensfeld Chair in Industrial Engineering and Head of the Enterprise System Modeling Laboratory at the Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology. Since 2000 he has been intermittently Visiting Professor at MIT's Engineering Systems Division, where he is currently Lecturer. He received his PhD in Computer Science in 1988 from Weizmann Institute of Science, MSc in Operations Research from Tel Aviv University in 1981, and BSc in Industrial Engineering and Management from Technion in 1975.Professor Dov Dori invented and developed Object-Process Methodology (OPM), recently adopted as ISO 19450. He has authored over 300 publications, including journal and conference papers, books, and book chapters. Prof. Dori has mentored over 50 graduate students. He chaired or was co-chair of nine international conferences and workshops. Among his many editorial duties, Prof. Dori was Associate Editor of IEEE Transaction on Pattern Analysis and Machine Intelligence, and currently he is Associate Editor of Systems Engineering. He is Fellow of INCOSE – International Council on Systems Engineering, Fellow of IAPR – International Association for Pattern Recognition, Member of Omega Alpha Association – International Honor Society for Systems Engineering, and Senior Member of IEEE and of ACM. His research interests include model-based systems engineering, conceptual modeling of complex systems, systems architecture and design, software and systems engineering, and systems biology."

"The book is a collection of high-quality peer-reviewed research papers presented at the Fifth International Conference on Innovations in Computer Science and Engineering (ICICSE 2017) held at Guru Nanak Institutions, Hyderabad, India during 18-19 August 2017. The book discusses a wide variety of industrial, engineering and scientific applications of the engineering techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Data Science and Analytics."