Kamala Sundaram

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A primary source of difficulty in automated assembly is the uncertainty in the relative position of the parts being assembled. This thesis focuses on a machine learning approach embedded in a logic branching structure to accomodate this uncertainty in peg and hole assemblies. Force sensor information, responses to recent moves, and results from previous(More)
A distributed and collaborative nature of wireless sensor network cause many challenges to provide security in network. Most of the outsider's attacks are prevented by encryption and authentication technology, but to control insider attacks are difficult. A malicious sensor node causes lot of packet losses, energy wastage and increase in time to reach final(More)
Mining provides useful information from the huge volume of the data stored in repositories. The present study focus on implementing five different algorithms using the data mining WEKA. The algorithm in the study includes Naive Bayes, Zero R, One R, J48 and Random Tree algorithm. All these well-known familiar algorithms are used in classification rule(More)
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