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Knowledge Computing and Its Applications

Author: S. Margret Anouncia

Publisher: Springer

Published: 2018-02-15

Total Pages: 293

ISBN-13: 9811066809

This book provides a major forum for the technical advancement of knowledge management and its applications across diversified domains. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, data mining, recommender systems, image processing, pattern recognition and predictions using machine learning techniques is the major strength of this book. Effective knowledge management has become a key to the success of business organizations, and can offer a substantial competitive edge. So as to be accessible to all scholars, this book combines the core ideas of knowledge management and its applications in numerous domains, illustrated in case studies. The techniques and concepts proposed here can be extended in future to accommodate changing business organizations’ needs as well as practitioners’ innovative ideas.

Guide to the Software Engineering Body of Knowledge (Swebok(r))

Author: IEEE Computer Society

Publisher:

Published: 2014

Total Pages: 348

ISBN-13: 9780769551661

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In the Guide to the Software Engineering Body of Knowledge (SWEBOK(R) Guide), the IEEE Computer Society establishes a baseline for the body of knowledge for the field of software engineering, and the work supports the Society's responsibility to promote the advancement of both theory and practice in this field. It should be noted that the Guide does not purport to define the body of knowledge but rather to serve as a compendium and guide to the knowledge that has been developing and evolving over the past four decades. Now in Version 3.0, the Guide's 15 knowledge areas summarize generally accepted topics and list references for detailed information. The editors for Version 3.0 of the SWEBOK(R) Guide are Pierre Bourque (Ecole de technologie superieure (ETS), Universite du Quebec) and Richard E. (Dick) Fairley (Software and Systems Engineering Associates (S2EA)).

Primary Computing and Digital Technologies: Knowledge, Understanding and Practice

Author: Keith Turvey

Publisher: Learning Matters

Published: 2016-09-14

Total Pages: 432

ISBN-13: 1473995078

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What do you need to know to teach computing in primary schools? How do you teach it? This book offers practical guidance on how to teach the computing curriculum in primary schools, coupled with the subject knowledge needed to teach it. This Seventh Edition is a guide to teaching the computing content of the new Primary National Curriculum. It includes many more case studies and practical examples to help you see what good practice in teaching computing looks like. It also explores the use of ICT in the primary classroom for teaching all curriculum subjects and for supporting learning in every day teaching. New chapters have been added on physical computing and coding and the importance of web literacy, bringing the text up-to-date. Computing is both a subject and a powerful teaching and learning tool throughout the school curriculum and beyond into many areas of children’s learning lives. This book highlights the importance of supporting children to become discerning and creative users of digital technologies as opposed to passive consumers.

Knowledge and Computing

Author: Tibor Vámos

Publisher: Central European University Press

Published: 2010-02-20

Total Pages: 228

ISBN-13: 6155211809

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The result of the author's extensive practical experience: a decade in computer process control using large scale systems, another decade in machine pattern-recognition for vision systems, and nearly a decade dealing with artificial intelligence and expert systems. These real-life projects have taught Vámos a critical appreciation of, and respect for, both abstract theory and the practical methodology that grows out of—and, in turn, shapes—those theories.Machine representation means a level of formalization that can be expressed by the instruments of mathematics, whereas programming is not more and not less than a special linguistic translation of these mathematical formulae. How these all are related and controlled is a most practical philosophical and computation professional task. Wide experience in the practical fields of computer science, and the research of the underlying theoretical issues have led Vámos to the development of the attitude and activity of constructive skepticism.

Ancestral Knowledge Meets Computer Science Education

Author: Cueponcaxochitl D. Moreno Sandoval

Publisher: Springer

Published: 2019-03-25

Total Pages: 178

ISBN-13: 113747520X

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This book illustrates a pathway for knowledge production to benefit from interweaving the seemingly disparate historical experiences of Indigenous Peoples and computer science education. The resulting practice of ancestral computing for sustainability holds the power to mitigate the destructive forces of the field, while extending the potential of traditionally underserved and unheard populations. Reimagining the field of computer science, interwoven with traditional lifeways, presents compelling new discoveries in research and harnesses the rich tapestries that are Indigenous populations. Returning healthy lifeways to a center stage long-occupied by tightly controlled, Eurocentric learning methods opens worlds of opportunity that have felt lost to time.

Cloud Computing

Author: Nayan B. Ruparelia

Publisher: MIT Press

Published: 2016-05-13

Total Pages: 278

ISBN-13: 0262529092

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Why cloud computing represents a paradigm shift for business, and how business users can best take advantage of cloud services. Most of the information available on cloud computing is either highly technical, with details that are irrelevant to non-technologists, or pure marketing hype, in which the cloud is simply a selling point. This book, however, explains the cloud from the user's viewpoint—the business user's in particular. Nayan Ruparelia explains what the cloud is, when to use it (and when not to), how to select a cloud service, how to integrate it with other technologies, and what the best practices are for using cloud computing. Cutting through the hype, Ruparelia cites the simple and basic definition of cloud computing from the National Institute of Science and Technology: a model enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources. Thus with cloud computing, businesses can harness information technology resources usually available only to large enterprises. And this, Ruparelia demonstrates, represents a paradigm shift for business. It will ease funding for startups, alter business plans, and allow big businesses greater agility. Ruparelia discusses the key issues for any organization considering cloud computing: service level agreements, business service delivery and consumption, finance, legal jurisdiction, security, and social responsibility. He introduces novel concepts made possible by cloud computing: cloud cells, or specialist clouds for specific uses; the personal cloud; the cloud of things; and cloud service exchanges. He examines use case patterns in terms of infrastructure and platform, software information, and business process; and he explains how to transition to a cloud service. Current and future users will find this book an indispensable guide to the cloud.

Knowledge Computing and its Applications

Author: S. Margret Anouncia

Publisher: Springer

Published: 2018-04-03

Total Pages: 346

ISBN-13: 9811082588

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This book highlights technical advances in knowledge management and their applications across a diverse range of domains. It explores the applications of knowledge computing methodologies in image processing, pattern recognition, health care and industrial contexts. The chapters also examine the knowledge engineering process involved in information management. Given its interdisciplinary nature, the book covers methods for identifying and acquiring valid, potentially useful knowledge sources. The ideas presented in the respective chapters illustrate how to effectively apply the perspectives of knowledge computing in specialized domains.

Feature Selection for Knowledge Discovery and Data Mining

Author: Huan Liu

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 225

ISBN-13: 1461556899

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As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Affective Computing

Author: Rosalind W. Picard

Publisher: MIT Press

Published: 2000-07-24

Total Pages: 308

ISBN-13: 9780262661157

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According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more—that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.

Basic Category Theory for Computer Scientists

Author: Benjamin C. Pierce

Publisher: MIT Press

Published: 1991-08-07

Total Pages: 117

ISBN-13: 0262326450

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Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Contents Tutorial • Applications • Further Reading