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Evolution of Knowledge Science: Myth to Medicine: Intelligent Internet-Based Humanist Machines
     

Evolution of Knowledge Science: Myth to Medicine: Intelligent Internet-Based Humanist Machines

by Syed V. Ahamed
 

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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

Overview

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.

  • Presents a current perspective of developments in central, display, signal, and graphics processor-units as they apply to designing knowledge systems
  • Offers ideas and methodologies for systematically extending data and object processing in computing into other disciplines such as economics, mathematics, and management
  • Provides best practices and designs for engineers alongside case studies that illustrate practical implementation ideas across multiple domains

Editorial Reviews

From the Publisher
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

Product Details

ISBN-13:
9780128093559
Publisher:
Elsevier Science
Publication date:
10/25/2016
Sold by:
Barnes & Noble
Format:
NOOK Book
Pages:
578
File size:
43 MB
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Meet the Author

Syed V. Ahamed taught at the University of Colorado for 2 years before joining Bell Laboratories. After 15 years of research, he returned to teaching as a Professor of Computer Science at the City University of New York. The author has been a Telecommunications consultant to Bell Communications Research, AT&T Bell Laboratories and Lucent Technologies for the last 25 years. He received numerous prizes for his papers from IEEE. He was elected a Fellow of the IEEE for his seminal contribution to the simulation and design studies of the High-speed Digital Subscriber Lines. He has authored and coauthored several books in two broad areas of intelligent AI-based broadband multimedia networks and computational framework for knowledge.

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