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The book covers cutting-edge and advanced research in modelling and graphics. Gathering high-quality papers presented at the First International Conference on Emerging Technology in Modelling and Graphics, held from 6 to 8 September 2018 in Kolkata, India, it addresses topics including: image processing and analysis, image segmentation, digital geometry for computer imaging, image and security, biometrics, video processing, medical imaging, and virtual and augmented reality.
Technology management education and business education are visibly intertwined in the current educational system. Certain efforts that have taken place in the recent past are the interinstitutional discourse around the world. Technology management is a dynamic and evolving profession, driven by changes in technology, globalization, sustainability, and the increasing importance of the service economy. The Handbook of Research on Future Opportunities for Technology Management Education is a comprehensive reference book that enables readers to comprehend the trends in technological changes and the need to orient business education and technology management in workplaces. The book serves to support with the formation and implementation of appropriate policies for technology management. Covering topics such as big data analytics, cloud computing adoption, and massive open online courses (MOOCs), this text is an essential resource for managers, technologists, teachers, executives, instructional designers, libraries, university researchers, students, faculty, and industry taught leaders.
Models and modelling play a central role in the nature of science, in its conduct, in the accreditation and dissemination of its outcomes, as well as forming a bridge to technology. They therefore have an important place in both the formal and informal science education provision made for people of all ages. This book is a product of five years collaborative work by eighteen researchers from four countries. It addresses four key issues: the roles of models in science and their implications for science education; the place of models in curricula for major science subjects; the ways that models can be presented to, are learned about, and can be produced by, individuals; the implications of all these for research and for science teacher education. The work draws on insights from the history and philosophy of science, cognitive psychology, sociology, linguistics, and classroom research, to establish what may be done and what is done. The book will be of interest to researchers in science education and to those taking courses of advanced study throughout the world.
This book provides an introduction to decision analytic cost-effectiveness modelling, giving the theoretical and practical knowledge required to design and implement analyses that meet the methodological standards of health technology assessment organisations. The book guides you through building a decision tree and Markov model and, importantly, shows how the results of cost-effectiveness analyses are interpreted. Given the complex nature of cost-effectiveness modelling and the often unfamiliar language that runs alongside it, we wanted to make this book as accessible as possible whilst still providing a comprehensive, in-depth, practical guide that reflects the state of the art – that includes the most recent developments in cost-effectiveness modelling. Although the nature of cost effectiveness modelling means that some parts are inevitably quite technical, across the 13 chapters we have broken down explanations of theory and methods into bite-sized pieces that you can work through at your own pace; we have provided explanations of terms and methods as we use them. Importantly, the exercises and online workbooks allow you to test your skills and understanding as you go along.
Benoît Godin is a Professor at the Institut national de la recherche scientifique, Montreal. Models abound in science, technology, and society (STS) studies and in science, technology, and innovation (STI) studies. They are continually being invented, with one author developing many versions of the same model over time. At the same time, models are regularly criticized. Such is the case with the most influential model in STS-STI: the linear model of innovation. In this book, Benoît Godin examines the emergence and diffusion of the three most important conceptual models of innovation from the early twentieth century to the late 1980s: stage models, linear models, and holistic models. Godin first traces the history of the models of innovation constructed during this period, considering why these particular models came into being and what use was made of them. He then rethinks and debunks the historical narratives of models developed by theorists of innovation. Godin documents a greater diversity of thinkers and schools than in the conventional account, tracing a genealogy of models beginning with anthropologists, industrialists, and practitioners in the first half of the twentieth century to their later formalization in STS-STI. Godin suggests that a model is a conceptualization, which could be narrative, or a set of conceptualizations, or a paradigmatic perspective, often in pictorial form and reduced discursively to a simplified representation of reality. Why are so many things called models? Godin claims that model has a rhetorical function. First, a model is a symbol of “scientificity.” Second, a model travels easily among scholars and policy makers. Calling a conceptualization or narrative or perspective a model facilitates its propagation.
The authors have done a masterful job of charting the important story of DARPA, one of the key catalysts of technological innovation in US recent history. By plotting the development, achievements and structure of the leading world agency of this kind, this book stimulates new thinking in the field of technological innovation with bearing on how to respond to climate change, pandemics, cyber security and other global problems of our time. The DARPA Model provides a useful guide for governmental agency and policy leaders, and for anybody interested in the role of governments in technological innovation. —Dr. Kent Hughes, Woodrow Wilson International Center for Scholars This volume contains a remarkable collection of extremely insightful articles on the world’s most successful advanced technology agency. Drafted by the leading US experts on DARPA, it provides a variety of perspectives that in turn benefit from being presented together in a comprehensive volume. It reviews DARPA’s unique role in the U.S. innovation system, as well as the challenges DARPA and its clones face today. As the American model is being considered for adoption by a number of countries worldwide, this book makes a welcome and timely contribution to the policy dialogue on the role played by governments in stimulating technological innovation. — Prof. Charles Wessner, Georgetown University The U.S. Defense Advanced Research Projects Agency (DARPA) has played a remarkable role in the creation new transformative technologies, revolutionizing defense with drones and precision-guided munitions, and transforming civilian life with portable GPS receivers, voice-recognition software, self-driving cars, unmanned aerial vehicles, and, most famously, the ARPANET and its successor, the Internet. Other parts of the U.S. Government and some foreign governments have tried to apply the ‘DARPA model’ to help develop valuable new technologies. But how and why has DARPA succeeded? Which features of its operation and environment contribute to this success? And what lessons does its experience offer for other U.S. agencies and other governments that want to develop and demonstrate their own ‘transformative technologies’? This book is a remarkable collection of leading academic research on DARPA from a wide range of perspectives, combining to chart an important story from the Agency’s founding in the wake of Sputnik, to the current attempts to adapt it to use by other federal agencies. Informative and insightful, this guide is essential reading for political and policy leaders, as well as researchers and students interested in understanding the success of this agency and the lessons it offers to others.
Autofrettage Processes: Technology and Modeling deals with the technology and modeling of autofrettage processes, explaining the subject in a lucid manner. It highlights how the theory of plasticity and finite element modeling are applied in the modeling of autofrettage processes. Aimed at senior students of mechanical, production, automobile, and chemical engineering, it has the potential to directly benefit practicing engineers and industrials, owing to the inclusion of topics like thermal autofrettage. Key Features: Provides a general introduction to autofrettage Covers the application of theory of plasticity and finite element modeling of autofrettage processes Offers exposure to newer autofrettage processes that to date have not been implemented in industries, along with useful practical data
Advances in machine learning techniques and ever-increasing computing power has helped create a new generation of hardware and software technologies with practical applications for nearly every industry. As the progress has, in turn, excited the interest of venture investors, technology firms, and a growing number of clients, implementing intelligent automation in both physical and information systems has become a must in business. Handbook of Research on Smart Technology Models for Business and Industry is an essential reference source that discusses relevant abstract frameworks and the latest experimental research findings in theory, mathematical models, software applications, and prototypes in the area of smart technologies. Featuring research on topics such as digital security, renewable energy, and intelligence management, this book is ideally designed for machine learning specialists, industrial experts, data scientists, researchers, academicians, students, and business professionals seeking coverage on current smart technology models.
The "laws" that govern our physical universe come in many guises-as principles, theorems, canons, equations, axioms, models, and so forth. They may be empirical, statistical, or theoretical, their names may reflect the person who first expressed them, the person who publicized them, or they might simply describe a phenomenon. However they may be named, the discovery and application of physical laws have formed the backbone of the sciences for 3,000 years. They exist by thousands. Laws and Models: Science, Engineering, and Technology-the fruit of almost 40 years of collection and research-compiles more than 1,200 of the laws and models most frequently encountered and used by engineers and technologists. The result is a collection as fascinating as it is useful. Each entry consists of a statement of the law or model, its date of origin, a one-line biography of the people involved in its formulation, sources of information about the law, and cross-references. Illustrated and highly readable, this book offers a unique presentation of the vast and rich collection of laws that rule our universe. Everyone with an interest in the inner workings of nature-from engineers to students, from teachers to journalists-will find Laws and Models to be not only a handy reference, but an engaging volume to read and browse.
This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important and innovative changes in theories and concepts. Gathering revised contributions presented at the international conference on Model-Based Reasoning (MBR18), held on October 24–26 2018 in Seville, Spain, the book is divided into three main parts. The first focuses on models, reasoning, and representation. It highlights key theoretical concepts from an applied perspective, and addresses issues concerning information visualization, experimental methods, and design. The second part goes a step further, examining abduction, problem solving, and reasoning. The respective papers assess different types of reasoning, and discuss various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies, this part is intended to foster new discussions and stimulate new ideas. All in all, the book provides researchers and graduate students in the fields of applied philosophy, epistemology, cognitive science, and artificial intelligence alike with an authoritative snapshot of the latest theories and applications of model-based reasoning.