By Sundarapandian Vaidyanathan (auth.), Natarajan Meghanathan, Dhinaharan Nagamalai, Nabendu Chaki (eds.)
The overseas convention on Advances in Computing and data know-how (ACITY 2012) presents a great foreign discussion board for either teachers and pros for sharing wisdom and leads to concept, method and functions of machine technological know-how and knowledge know-how. the second one foreign convention on Advances in Computing and data expertise (ACITY 2012), held in Chennai, India, in the course of July 13-15, 2012, lined a few issues in all significant fields of laptop technology and knowledge expertise together with: networking and communications, community safety and purposes, internet and net computing, ubiquitous computing, algorithms, bioinformatics, electronic photograph processing and trend popularity, synthetic intelligence, smooth computing and purposes. Upon a power assessment technique, a couple of top quality, proposing not just leading edge rules but additionally a based review and a powerful argumentation of an identical, have been chosen and picked up within the current complaints, that's composed of 3 varied volumes.
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Additional resources for Advances in Computing and Information Technology: Proceedings of the Second International Conference on Advances in Computing and Information Technology (ACITY) July 13-15, 2012, Chennai, India - Volume 2
J. Computer Sci. Eng. Inform. Tech. 1(2), 1–14 (2011) 10. : Adaptive synchronization of chaotic systems and its applications to secure communications. Chaos, Solitons & Fractals 11, 1387–1396 (2000) 11. : Adaptive synchronization of hyperchaotic Lorenz and hyperchaotic L¨u systems. Internat. J. Instrument. Control Sys. 1(1), 1–18 (2011) 12. : Adaptive stabilization and synchronization of L¨u-like chaotic attractor. Internat. J. Comp. Sci. Eng. Informat. Tech. 1(4), 15–26 (2011) 13. : Control of chaos using sampled-data feedback control.
Ontology matching helps establish semantic correspondence rules that are used for query rewriting and translation in interoperation systems. For information systems that want maximum privacy, the privacy of their ontologies must be maintained. Our system gives a method to map ontologies which are secured. Limitations of our system is accuracy in terms of precision and recall. The future work would be to improve this. : Privacy preserving data integration and sharing. In: Proc. : Privacy preserving data mining.
1 Introduction In non-parametric density estimation algorithms, the distribution of data is calculated without any particular assumption on its parameters. Two popular approaches in these algorithms are: Kernel Density Estimation (KDE) and k-Nearest Neighbor (k-NN). KNN is a simple classifier that has been used in various real world applications. In some cases k-NN is vulnerable with some problems, such as few instances, noisy data and too many features, which decrease the performance of k-NN. To improve the performance of this classifier, many solutions are introduced.