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Evolution of Knowledge Science
Myth to Medicine: Intelligent Internet-Based Humanist Machines
A thorough examination of how to design and build the next generation of intelligent machines to solve social and environmental problems
Syed V. Ahamed (Author)
9780128054789
Paperback, published 11 November 2016
578 pages
23.4 x 19 x 3.6 cm, 1.18 kg
"Information Science is on the cusp of defining the transition from Big Data to Knowledge. This movement is being fueled by an urgency in addressing grand challenges in fields as diverse as health, public safety and climate change. Domain experts in these fields are looking to information science to provide a quantitative basis for solving hard problems in their data-intensive fields....Prof. Ahamed’s book represents a rigorous and optimistic declaration of this revolutionary trend. I recommend it heartily to teachers and students in communications and computing, and to those in pursuit of incisive mathematical philosophy." --From the Foreword by Professor Dr. Nikil Jayant, Eminent Scholar (Emeritus), Georgia Research Alliance
Evolution of Knowledge Science: Myth to Medicine: Intelligent Internet-Based Humanist Machines explains how to design and build the next generation of intelligent machines that solve social and environmental problems in a systematic, coherent, and optimal fashion. The book brings together principles from computer and communication sciences, electrical engineering, mathematics, physics, social sciences, and more to describe computer systems that deal with knowledge, its representation, and how to deal with knowledge centric objects. Readers will learn new tools and techniques to measure, enhance, and optimize artificial intelligence strategies for efficiently searching through vast knowledge bases, as well as how to ensure the security of information in open, easily accessible, and fast digital networks. Author Syed Ahamed joins the basic concepts from various disciplines to describe a robust and coherent knowledge sciences discipline that provides readers with tools, units, and measures to evaluate the flow of knowledge during course work or their research. He offers a unique academic and industrial perspective of the concurrent dynamic changes in computer and communication industries based upon his research. The author has experience both in industry and in teaching graduate level telecommunications and network architecture courses, particularly those dealing with applications of networks in education.
Part I: Knowledge, Wisdom and Values Section I: From Early Thinker to Social Scientists Chapter 1. Knowledge and Wisdom Across Cultures Chapter 2. From Philosophers to Knowledge Machines Chapter 3. Affirmative Knowledge and Positive Human Nature Chapter 4. Negative Knowledge and Aggressive Human Nature Chapter 5. Role of Devices, Computers and Networks Section II: Information Machines and Social Progress Chapter 6. Recent Changes to the Structure of Knowledge Chapter 7. Origin and Structure of Knowledge Energy Chapter 8. Bands of Knowledge Chapter 9. Frustums of Artificial Behavior Chapter 10. Computer-Aided Knowledge Design and Validation Section III: Knowledge Science and Social Influence Chapter 11. Knowledge and Information Ethics Chapter 12. From Primal Thinking to Potential Computing Chapter 13. Action (VF) ? (*) ? Object (NO) Based Processors and Machines Chapter 14. Aphorism and Truism in Knowledge Domain Chapter 15. Timing Sequences and Influence of Time Part II: Summary Section I. The Scientific basis for Knowledge Flow Chapter 16. General Flow Theory of Knowledge Chapter 17. Transmission Flow Theory of Knowledge Chapter 18. Quantum Flow Theory of Knowledge Chapter 19. Inspiration Flow Theory of Knowledge Chapter 20. Dynamic Nature of Knowledge: Fragmentation and Flow Section II: Preface Chapter 21. Knowledge Potential and Utility Chapter 22. Elements of Knowledge as Elements in Nature Chapter 23. Knowledge Element Machine Design: Pathways of Knowledge in Machines Chapter 24. Elements of Knowledge in Societies Chapter 25. Role of Human Discretion in Society and Its Impact on Ecosystems Section III: Preface Chapter 26. Scientific Foundations of Knowledge Chapter 27. Real Space, Knowledge Space and Computational Space Chapter 28. General Structure of Knowledge (no*? vf and vf*? no) Chapter 29. The Architecture of a Mind-Machine Chapter 30. The Architecture of a Medical Machine
Subject Areas: Machine learning [UYQM], Expert systems / knowledge-based systems [UYQE], Artificial intelligence [UYQ], Computer programming / software development [UM]
