By Syed V. Ahamed
"Intriguing . . . [filled with] new principles approximately overarching highbrow issues that govern our applied sciences and our society." —Nikil Jayant , Eminent pupil, Georgia study Alliance
"Dr. Ahamed is true in staring at that 'silicon and glass have altered the rhythm of brain' and that pcs must be extra 'human.'" —Bishnu S. Atal , Member, nationwide Academy of Engineering
This publication combines philosophical, societal, and synthetic intelligence suggestions with these of machine technology and data expertise to illustrate novel ways that desktops can simplify information mining on the web. It describes quite a few leading edge equipment that move way past info retrieval to permit desktops to complete such initiatives as processing, classifying, prioritizing, and reconstituting wisdom.
The ebook is split into 5 elements:
New wisdom sensing and filtering environments
thought development and knowledge machines
normal constitution and idea of data
Verb capabilities and noun items
Humanistic and semi-human platforms
This publication bargains new mathematical methodologies and urban HW/SW/FW configurations for the IT expert to assist their firms discover, make the most, compete, and win worldwide industry proportion.
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Additional info for Computational Framework for Knowledge: Integrated Behavior of Machines
Traditionally, most of the messages processed by the human mind enhance knowledge or understanding in the context (vectorial direction) in which the message is perceived. In the same vein, every executable statement of a knowledge program needs at least one kopc and one kopr. The format of multiple kopcs and koprs for the command structures of knowledge processors is discussed in . Invariably, a certain duration of time is essential for the verb function (force) to complete any change in the status of the object.
In most cases, human beings are ill equipped for these tasks and the result is distraction and lack of focus to solve the immediate problem. The purpose of this book is to introduce methods of implanting some of the low-level human functions, such as selective filtering, pattern recognition, enhancing, and relevancy checking, in machines and knowledge-processing systems. Humans function at a higher level in terms of innovation, invention, creation, transformation, transmutation, etc. The interaction between a human being and a machine will be that of rider and an intelligent horse in the connected terrain of knowledge, concepts, and wisdom.
Storage allocation becomes an integral part of programming knowledge-based problems. 2 The Processing of Knowledge The processing of knowledge assumes two components: (1) the filtering of raw information to create “knowledge-rich” information by selecting appropriate “noun objects” with most dominant structural relationships with other noun objects and (2) the processing of “noun objects” with machine-executable “verb functions” or knowledge operation codes on such operand noun objects. The execution of a series of verb functions on a collection of interrelated noun objects thus modifies the structural relationship between the noun objects and creates new noun objects.
Computational Framework for Knowledge: Integrated Behavior of Machines by Syed V. Ahamed