http://hdl.handle.net/123456789/144 Tue, 21 May 2013 22:05:38 GMT 2013-05-21T22:05:38Z http://hdl.handle.net/123456789/1516 Title: Energy Aware Cluster-based Multihop Routing Protocol for Sensor Networks Authors: Santhosh Kumar, G; Poulose Jacob, K; Sitara, A Abstract: Clustering combined with multihop communication is a promising solution to cope with the energy requirements of large scale Wireless Sensor Networks. In this work, a new cluster based routing protocol referred to as Energy Aware Cluster-based Multihop (EACM) Routing Protocol is introduced, with multihop communication between cluster heads for transmitting messages to the base station and direct communication within clusters. We propose EACM with both static and dynamic clustering. The network is partitioned into near optimal load balanced clusters by using a voting technique, which ensures that the suitability of a node to become a cluster head is determined by all its neighbors. Results show that the new protocol performs better than LEACH on network lifetime and energy dissipation Tue, 23 Nov 2010 18:30:00 GMT http://hdl.handle.net/123456789/1516 2010-11-23T18:30:00Z http://hdl.handle.net/123456789/1195 Title: ICT For Education Authors: Santhosh Kumar, G Mon, 01 Nov 2010 18:30:00 GMT http://hdl.handle.net/123456789/1195 2010-11-01T18:30:00Z http://hdl.handle.net/123456789/1194 Title: ICT For Education Authors: Santhosh Kumar, G Mon, 01 Nov 2010 18:30:00 GMT http://hdl.handle.net/123456789/1194 2010-11-01T18:30:00Z http://hdl.handle.net/123456789/984 Title: Alignment Model and Training Technique in SMT from English to Malayalam Authors: Sebastian, Mary Priya; Kurian, Sheena; Kumar, G Santhosh Abstract: This paper investigates certain methods of training adopted in the Statistical Machine Translator (SMT) from English to Malayalam. In English Malayalam SMT, the word to word translation is determined by training the parallel corpus. Our primary goal is to improve the alignment model by reducing the number of possible alignments of all sentence pairs present in the bilingual corpus. Incorporating morphological information into the parallel corpus with the help of the parts of speech tagger has brought around better training results with improved accuracy. Sun, 29 Aug 2010 18:30:00 GMT http://hdl.handle.net/123456789/984 2010-08-29T18:30:00Z