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| Author | : L. Jean Camp |
| Publisher | : MIT Press |
| Total Pages | : 298 |
| Release | : 2001-06-24 |
| Genre | : Business & Economics |
| ISBN | : 9780262531979 |
This book provides information on trust and risk to businesses that are developing electronic commerce systems and helps consumers understand the risks in using the Internet for purchases and show them how to protect themselves.
| Author | : L. Jean Camp |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 300 |
| Release | : 2006-04-11 |
| Genre | : Computers |
| ISBN | : 1402080905 |
Designed for managers struggling to understand the risks in organizations dependent on secure networks, this book applies economics not to generate breakthroughs in theoretical economics, but rather breakthroughs in understanding the problems of security.
| Author | : Harry Henderson |
| Publisher | : Infobase Publishing |
| Total Pages | : 593 |
| Release | : 2009 |
| Genre | : Computers |
| ISBN | : 1438110030 |
Presents an illustrated A-Z encyclopedia containing approximately 600 entries on computer and technology related topics.
| Author | : Chris Kempes |
| Publisher | : Seminar |
| Total Pages | : 500 |
| Release | : 2018-09 |
| Genre | : Science |
| ISBN | : 9781947864184 |
Why do computers use so much energy? What are the fundamental physical laws governing the relationship between the precise computation run by a system, whether artificial or natural, and how much energy that computation requires? This volume integrates concepts from diverse fields, cultivating a modern, nonequilibrium thermodynamics of computation.
| Author | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 287 |
| Release | : 1992-02-01 |
| Genre | : Computers |
| ISBN | : 0309047404 |
Computers are increasingly the enabling devices of the information revolution, and computing is becoming ubiquitous in every corner of society, from manufacturing to telecommunications to pharmaceuticals to entertainment. Even more importantly, the face of computing is changing rapidly, as even traditional rivals such as IBM and Apple Computer begin to cooperate and new modes of computing are developed. Computing the Future presents a timely assessment of academic computer science and engineering (CS&E), examining what should be done to ensure continuing progress in making discoveries that will carry computing into the twenty-first century. Most importantly, it advocates a broader research and educational agenda that builds on the field's impressive accomplishments. The volume outlines a framework of priorities for CS&E, along with detailed recommendations for education, funding, and leadership. A core research agenda is outlined for these areas: processors and multiple-processor systems, data communications and networking, software engineering, information storage and retrieval, reliability, and user interfaces. This highly readable volume examines: Computer science and engineering as a discipline-how computer scientists and engineers are pushing back the frontiers of their field. How CS&E must change to meet the challenges of the future. The influence of strategic investment by federal agencies in CS&E research. Recent structural changes that affect the interaction of academic CS&E and the business environment. Specific examples of interdisciplinary and applications research in four areas: earth sciences and the environment, computational biology, commercial computing, and the long-term goal of a national electronic library. The volume provides a detailed look at undergraduate CS&E education, highlighting the limitations of four-year programs, and discusses the emerging importance of a master's degree in CS&E and the prospects for broadening the scope of the Ph.D. It also includes a brief look at continuing education.
| Author | : Nathan L. Ensmenger |
| Publisher | : MIT Press |
| Total Pages | : 331 |
| Release | : 2012-08-24 |
| Genre | : Computers |
| ISBN | : 0262302829 |
The contentious history of the computer programmers who developed the software that made the computer revolution possible. This is a book about the computer revolution of the mid-twentieth century and the people who made it possible. Unlike most histories of computing, it is not a book about machines, inventors, or entrepreneurs. Instead, it tells the story of the vast but largely anonymous legions of computer specialists—programmers, systems analysts, and other software developers—who transformed the electronic computer from a scientific curiosity into the defining technology of the modern era. As the systems that they built became increasingly powerful and ubiquitous, these specialists became the focus of a series of critiques of the social and organizational impact of electronic computing. To many of their contemporaries, it seemed the “computer boys” were taking over, not just in the corporate setting, but also in government, politics, and society in general. In The Computer Boys Take Over, Nathan Ensmenger traces the rise to power of the computer expert in modern American society. His rich and nuanced portrayal of the men and women (a surprising number of the “computer boys” were, in fact, female) who built their careers around the novel technology of electronic computing explores issues of power, identity, and expertise that have only become more significant in our increasingly computerized society. In his recasting of the drama of the computer revolution through the eyes of its principle revolutionaries, Ensmenger reminds us that the computerization of modern society was not an inevitable process driven by impersonal technological or economic imperatives, but was rather a creative, contentious, and above all, fundamentally human development.
| Author | : Kashyap, Ramgopal |
| Publisher | : IGI Global |
| Total Pages | : 318 |
| Release | : 2019-10-04 |
| Genre | : Computers |
| ISBN | : 1799801845 |
Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.
| Author | : Adrian Mackenzie |
| Publisher | : MIT Press |
| Total Pages | : 269 |
| Release | : 2017-11-16 |
| Genre | : Social Science |
| ISBN | : 0262036827 |
If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought? Machine learning—programming computers to learn from data—has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking. Mackenzie focuses on machine learners—either humans and machines or human-machine relations—situated among settings, data, and devices. The settings range from fMRI to Facebook; the data anything from cat images to DNA sequences; the devices include neural networks, support vector machines, and decision trees. He examines specific learning algorithms—writing code and writing about code—and develops an archaeology of operations that, following Foucault, views machine learning as a form of knowledge production and a strategy of power. Exploring layers of abstraction, data infrastructures, coding practices, diagrams, mathematical formalisms, and the social organization of machine learning, Mackenzie traces the mostly invisible architecture of one of the central zones of contemporary technological cultures. Mackenzie's account of machine learning locates places in which a sense of agency can take root. His archaeology of the operational formation of machine learning does not unearth the footprint of a strategic monolith but reveals the local tributaries of force that feed into the generalization and plurality of the field.
| Author | : Robert J. Moore |
| Publisher | : Morgan & Claypool |
| Total Pages | : 318 |
| Release | : 2019-05-29 |
| Genre | : Computers |
| ISBN | : 1450363040 |
With recent advances in natural language understanding techniques and far-field microphone arrays, natural language interfaces, such as voice assistants and chatbots, are emerging as a popular new way to interact with computers. They have made their way out of the industry research labs and into the pockets, desktops, cars and living rooms of the general public. But although such interfaces recognize bits of natural language, and even voice input, they generally lack conversational competence, or the ability to engage in natural conversation. Today’s platforms provide sophisticated tools for analyzing language and retrieving knowledge, but they fail to provide adequate support for modeling interaction. The user experience (UX) designer or software developer must figure out how a human conversation is organized, usually relying on commonsense rather than on formal knowledge. Fortunately, practitioners can rely on conversation science. This book adapts formal knowledge from the field of Conversation Analysis (CA) to the design of natural language interfaces. It outlines the Natural Conversation Framework (NCF), developed at IBM Research, a systematic framework for designing interfaces that work like natural conversation. The NCF consists of four main components: 1) an interaction model of “expandable sequences,” 2) a corresponding content format, 3) a pattern language with 100 generic UX patterns and 4) a navigation method of six basic user actions. The authors introduce UX designers to a new way of thinking about user experience design in the context of conversational interfaces, including a new vocabulary, new principles and new interaction patterns. User experience designers and graduate students in the HCI field as well as developers and conversation analysis students should find this book of interest.
