Computational Framework for Knowledge

Computational Framework for Knowledge PDF

Author: Syed V. Ahamed

Publisher: John Wiley & Sons

Published: 2009-07-31

Total Pages: 568

ISBN-13: 0470480416

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"Intriguing . . . [filled with] new ideas about overarching intellectual themes that govern our technologies and our society." —Nikil Jayant, Eminent Scholar, Georgia Research Alliance "Dr. Ahamed is correct in observing that 'silicon and glass have altered the rhythm of mind' and that computers need to be more 'human.'" —Bishnu S. Atal, Member, National Academy of Engineering This book combines philosophical, societal, and artificial intelligence concepts with those of computer science and information technology to demonstrate novel ways in which computers can simplify data mining on the Internet. It describes numerous innovative methods that go well beyond information retrieval to allow computers to accomplish such tasks as processing, classifying, prioritizing, and reconstituting knowledge. The book is divided into five parts: New knowledge sensing and filtering environments Concept building and wisdom machines General structure and theory of knowledge Verb functions and noun objects Humanistic and semi-human systems This book offers new mathematical methodologies and concrete HW/SW/FW configurations for the IT specialist to help their corporations explore, exploit, compete, and win global market share.

Computational Frameworks

Computational Frameworks PDF

Author: Mamadou Kaba Traore

Publisher: Elsevier

Published: 2017-07-07

Total Pages: 136

ISBN-13: 0081023162

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Computational Frameworks: Systems, Models and Applications provides an overview of advanced perspectives that bridges the gap between frontline research and practical efforts. It is unique in showing the interdisciplinary nature of this area and the way in which it interacts with emerging technologies and techniques. As computational systems are a dominating part of daily lives and a required support for most of the engineering sciences, this book explores their usage (e.g. big data, high performance clusters, databases and information systems, integrated and embedded hardware/software components, smart devices, mobile and pervasive networks, cyber physical systems, etc.). Provides a unique presentation on the views of frontline researchers on computational systems theory and applications in one holistic scope Cover both computational science and engineering Bridges the gap between frontline research and practical efforts

Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications PDF

Author: Khalid Al-Jabery

Publisher: Academic Press

Published: 2019-11-20

Total Pages: 312

ISBN-13: 0128144831

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Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor

Computational Thinking Education

Computational Thinking Education PDF

Author: Siu-Cheung Kong

Publisher: Springer

Published: 2019-07-04

Total Pages: 377

ISBN-13: 9811365288

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This This book is open access under a CC BY 4.0 license.This book offers a comprehensive guide, covering every important aspect of computational thinking education. It provides an in-depth discussion of computational thinking, including the notion of perceiving computational thinking practices as ways of mapping models from the abstraction of data and process structures to natural phenomena. Further, it explores how computational thinking education is implemented in different regions, and how computational thinking is being integrated into subject learning in K-12 education. In closing, it discusses computational thinking from the perspective of STEM education, the use of video games to teach computational thinking, and how computational thinking is helping to transform the quality of the workforce in the textile and apparel industry.

Current Trends in Knowledge Acquisition

Current Trends in Knowledge Acquisition PDF

Author: Bob Wielinga

Publisher: IOS Press

Published: 1990

Total Pages: 390

ISBN-13: 9789051990362

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Knowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issues of integrating knowledge from different sources and K.A. tools is a salient topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasises the use of generic models of reasoning and its underlying knowledge. An important trend in the area of knowledge modelling aims at the formalisation of knowledge models. Where the field of knowledge acquisition was without tools and techniques years ago, now there is a rapidly growing body of techniques and tools. Apart from the integrated workbenches already mentioned above, several papers in this book present new tools. Although knowledge acquisition and machine learning have been considered as separate subfields of AI, there is a tendency for the two fields to come together. This publication combines machine learning techniques with more conventional knowledge elicitation techniques. A framework is presented in which reasoning, problem solving and learning together form a knowledge intensive system that can acquire knowledge from its own experience.

Computer Aided Systems Theory - CAST '94

Computer Aided Systems Theory - CAST '94 PDF

Author: Tuncer I. Ören

Publisher: Springer Science & Business Media

Published: 1996-07

Total Pages: 456

ISBN-13: 9783540614784

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This volume presents a collection of revised refereed papers selected from the presentations at the Fourth International Workshop on Computer Aided Systems Theory - CAST '94, held in Ottawa, Ontario, Canada in May 1994. The 31 full papers included in the book were chosen from originally 82 submissions and reflect the state of the art in the area of computer aided systems theory. The volume is divided into sections on foundations, methods, and tools and environments.

Artificial Intelligence in the Age of Neural Networks and Brain Computing

Artificial Intelligence in the Age of Neural Networks and Brain Computing PDF

Author: Robert Kozma

Publisher: Academic Press

Published: 2023-10-27

Total Pages: 398

ISBN-13: 0323958168

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Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks

Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems

Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems PDF

Author: Mar Marcos

Publisher: Springer Nature

Published: 2020-01-03

Total Pages: 184

ISBN-13: 3030374467

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This book constitutes revised selected papers from the AIME 2019 workshops KR4HC/ProHealth 2019, the Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care, and TEAAM 2019, the Workshop on Transparent, Explainable and Affective AI in Medical Systems. The volume contains 5 full papers from KR4HC/ProHealth, which were selected out of 13 submissions. For TEAAM 8 papers out of 10 submissions were accepted for publication.

A Framework for K-12 Science Education

A Framework for K-12 Science Education PDF

Author: National Research Council

Publisher: National Academies Press

Published: 2012-02-28

Total Pages: 400

ISBN-13: 0309214459

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Science, engineering, and technology permeate nearly every facet of modern life and hold the key to solving many of humanity's most pressing current and future challenges. The United States' position in the global economy is declining, in part because U.S. workers lack fundamental knowledge in these fields. To address the critical issues of U.S. competitiveness and to better prepare the workforce, A Framework for K-12 Science Education proposes a new approach to K-12 science education that will capture students' interest and provide them with the necessary foundational knowledge in the field. A Framework for K-12 Science Education outlines a broad set of expectations for students in science and engineering in grades K-12. These expectations will inform the development of new standards for K-12 science education and, subsequently, revisions to curriculum, instruction, assessment, and professional development for educators. This book identifies three dimensions that convey the core ideas and practices around which science and engineering education in these grades should be built. These three dimensions are: crosscutting concepts that unify the study of science through their common application across science and engineering; scientific and engineering practices; and disciplinary core ideas in the physical sciences, life sciences, and earth and space sciences and for engineering, technology, and the applications of science. The overarching goal is for all high school graduates to have sufficient knowledge of science and engineering to engage in public discussions on science-related issues, be careful consumers of scientific and technical information, and enter the careers of their choice. A Framework for K-12 Science Education is the first step in a process that can inform state-level decisions and achieve a research-grounded basis for improving science instruction and learning across the country. The book will guide standards developers, teachers, curriculum designers, assessment developers, state and district science administrators, and educators who teach science in informal environments.