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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In recent day’s parallel string matching problem catch the attention of so many researchers because of the importance in different applications like IRS, Genome sequence, data cleaning etc.,. 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. The algorithm is designed to work on omega model parallel architecture where text is divided for parallel processing and special searching at division point is required for consistent and complete searching. This algorithm reduces the number of comparisons and parallelization improves the time efficiency. 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.
K Butchi Raju. 2013. \u201cA Parallel Computational Approach for String Matching- A Novel Structure with Omega Model\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C12): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 107
Country: India
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: K Butchi Raju, Dr. S. Viswanadha Raju (PhD/Dr. count: 1)
View Count (all-time): 208
Total Views (Real + Logic): 9328
Total Downloads (simulated): 2420
Publish Date: 2013 12, Sat
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In recent day’s parallel string matching problem catch the attention of so many researchers because of the importance in different applications like IRS, Genome sequence, data cleaning etc.,. 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. The algorithm is designed to work on omega model parallel architecture where text is divided for parallel processing and special searching at division point is required for consistent and complete searching. This algorithm reduces the number of comparisons and parallelization improves the time efficiency. 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.
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