Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Chinta Someswara Rao
Now a day’s parallel string matching problem is attracted by so many researchers because of the importance in information retrieval systems. While it is very easily stated and many of the simple algorithms perform very well in practice, numerous works have been published on the subject and research is still very active. In this paper we propose a omega parallel computing model for parallel string matching. Experimental results show that, on a multi-processor system, the omega model implementation of the proposed parallel string matching algorithm can reduce string matching time by more than 40%.
K Butchi Raju. 2014. \u201cA Frame Work for Parallel String Matching- A Computational Approach with Omega Model\u201d. Global Journal of Computer Science and Technology - A: Hardware & Computation GJCST-A Volume 13 (GJCST Volume 13 Issue A2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 108
Country: India
Subject: Global Journal of Computer Science and Technology - A: Hardware & Computation
Authors: K Butchi Raju, Chinta Someswara Rao, Dr. S. Viswanadha Raju (PhD/Dr. count: 1)
View Count (all-time): 241
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Publish Date: 2014 01, Tue
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Neural Networks and Rules-based Systems used to Find Rational and
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Now a day’s parallel string matching problem is attracted by so many researchers because of the importance in information retrieval systems. While it is very easily stated and many of the simple algorithms perform very well in practice, numerous works have been published on the subject and research is still very active. In this paper we propose a omega parallel computing model for parallel string matching. Experimental results show that, on a multi-processor system, the omega model implementation of the proposed parallel string matching algorithm can reduce string matching time by more than 40%.
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