7 results for “K. Muneeswaran”

Research ArticleOpen accessIn the author namesREDUCING CALL BLOCKING PROBABILITY IN HYBRID MULTICAST WAVELENGTH DIVISION MULTIPLEXING NETWORKS USING WEIGHTED ROUTING AND WAVELENGTH ASSIGNMENT ALGORITHMD. V. Pradeep Sankar, K. MuneeswaranIn the proposed work, the focus is on increasing the available wavelength in the all-optical networks, for which the Routing and Wavelength Assignment plays a vital role. In the earlier reported work, the wavelengths were assigned to the links which covers a set of destinations but not all the intended destinations. However this proposed work, attempts were made to create … …Journal of Computer Science, Vol. 10, Issue 2 · 13 Nov 2013 · 6,854 accessesView PDF Cite

Research ArticleOpen accessIn the author namesIntelligent Apriori Algorithm for Complex Activity Mining in Supermarket ApplicationsV. Ganesh Kumar, K. MuneeswaranAs shopping becomes a shared experience and joint process with friends or family members nowadays, the most important problems arise with variety of products and the product information available in the supermarkets. This study proposes a system that uses Intelligent Apriori algorithm to support consumers in getting the required items from various supermarkets. Also this work intelligently suggests the best … …Journal of Computer Science, Vol. 9, Issue 4 · 9 May 2013 · 6,366 accessesView PDF Cite

Research ArticleOpen accessIn the author namesEfficacious Geospatial Information Retrieval Using Density Probabilistic Document Correlation ApproachR. Uma, MuneeswaranInformation Retrieval (IR) is a profound technique to find information that addresses the need of query. Processing of normal text is easier and information can be retrieved efficiently. There are plenty of algorithms in hand to carry out the normal text retrieval. Whereas retrieving geospatial information is very complex and requires additional operations to be performed. Since geospatial data contain … …Journal of Computer Science, Vol. 9, Issue 1 · 16 Feb 2013 · 7,017 accessesView PDF Cite

Research ArticleOpen accessIn the author namesAn Improved Face Recognition Technique Based on Modular LPCA ApproachMathu Soothana S. Kumar, Retna Swami, Muneeswaran KaruppiahProblem statement: A face identification algorithm based on modular localized variation by Eigen Subspace technique, also called modular localized principal component analysis, is presented in this study. Approach: The face imagery was partitioned into smaller sub-divisions from a predefined neighborhood and they were ultimately fused to acquire many sets of features. Since a few of the normal facial features of … …Journal of Computer Science, Vol. 7, Issue 12 · 22 Oct 2011 · 6,954 accessesView PDF Cite