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Jayalakshmi D.S.,M.S. Ramaiah Institute of Technology | Jayalakshmi D.S.,Universitytamil Nadu | Rashmi Ranjana T.P.,M.S. Ramaiah Institute of Technology | Srinivasan R.,Tamil University
Proceedings - 2015 5th International Conference on Advances in Computing and Communications, ICACC 2015 | Year: 2015

Replication of a popular file and storing its replica in the locations closer to the clients who are making requests is the best choice to reduce the execution time. Although replication helps in increasing availability, the question of how to decide an optimal replication number and correct locations to place the replicas are open challenges. In this paper, a brief survey on various data center selection and replication strategies used are described. Further, a system model with two phases, data center selection and dynamic data replication, is proposed with an aim to effectively increase the data availability and also reduce user waiting time by very small number of replicas is presented in this paper. © 2015 IEEE.

Marappan R.,Universitytamil Nadu | Sethumadhavan G.,Universitytamil Nadu
International Journal of Applied Engineering Research | Year: 2015

Graph coloring is a classical NP-Complete combinatorial optimization problem and it is widely applied in different engineering applications. This paper explores the effectiveness of applying heuristics and recursive backtracking strategy to solve the coloring assignment of a graph G. The proposed method applies heuristics through recursive backtracking to obtain the approximate solution to χ(G), the minimum number of colors needed to color the vertices of G. The proposed heuristics splits V(G) into higher degree and lower degree vertices such that the search space is reduced when calling the recursive backtracking algorithm for higher degree vertices first. The performance of this approximation method is evaluated using some well known benchmark graphs, and the results are found to be proficient. © Research India Publications.

Arunma M.,Universitytamil Nadu | Ezhilmaran D.,Universitytamil Nadu
International Journal of Applied Engineering Research | Year: 2016

In this paper, we propose a new key-agreement protocol using near polynomial ring over a near-ring. We concretely generate the near polynomial ring f (x)ЄN(x) such that (formula presented) It is proved that the proposed protocol meets several security attributes under the assumption that the near polynomial ring over the near-ring defined below. © Research India Publications.

Vickram A.S.,Universitytamil Nadu | Kamini A.R.,Bangalore Assisted Conception Center Healthcare Pvt. Ltd. andrology | Das R.,Universitytamil Nadu | Pathy M.R.,Universitytamil Nadu | And 3 more authors.
Systems Biology in Reproductive Medicine | Year: 2016

Seminal fluid is the secretion from many glands comprised of several organic and inorganic compounds including free amino acids, proteins, fructose, glucosidase, zinc, and other scavenging elements like Mg2+, Ca2+, K+, and Na+. Therefore, in the view of development of novel approaches and proper diagnosis to male infertility, overall understanding of the biochemical and molecular composition and its role in regulation of sperm quality is highly desirable. Perhaps this can be achieved through artificial intelligence. This study was aimed to elucidate and predict various biochemical markers present in human seminal plasma with three different neural network models. A total of 177 semen samples were collected for this research (both fertile and infertile samples) and immediately processed to prepare a semen analysis report, based on the protocol of the World Health Organization (WHO [2010]). The semen samples were then categorized into oligoasthenospermia (n=35), asthenospermia (n=35), azoospermia (n=22), normospermia (n=34), oligospermia (n=34), and control (n=17). The major biochemical parameters like total protein content, fructose, glucosidase, and zinc content were elucidated by standard protocols. All the biochemical markers were predicted by using three different artificial neural network (ANN) models with semen parameters as inputs. Of the three models, the back propagation neural network model (BPNN) yielded the best results with mean absolute error 0.025, -0.080, 0.166, and -0.057 for protein, fructose, glucosidase, and zinc, respectively. This suggests that BPNN can be used to predict biochemical parameters for the proper diagnosis of male infertility in assisted reproductive technology (ART) centres. Abbreviations: AAS: absorption spectroscopy; AI: artificial intelligence; ANN: artificial neural networks; ART: assisted reproductive technology; BPNN: back propagation neural network model; DT: decision tress; MLP: multilayer perceptron; PESA: percutaneous epididymal sperm spiration; RBFN: radical basis function network; SRNN: simple recurrent neural network; SVM: support vector machines; TSE: testicular sperm extraction; WHO: World Health Organization. © 2016 Taylor & Francis.

Rajkumar S.,Universitytamil Nadu | Antony Savarimuthu S.,St Xaviers College | Senthil Kumaran R.,Biocon | Nagaraja C.M.,IIT RoparPunjab | Gandhi T.,Universitytamil Nadu
Chemical Communications | Year: 2016

Ruthenium-catalyzed simple, cascade and one-pot synthesis of cinnoline-fused diones has been carried out by the C-H activation of phthalazinones/pyridazinones accomplished by the unusual deoxygenation of propargyl alcohols. The bond selectivity is accredited to the traceless directing nature of the hydroxyl group of propargyl alcohol. A sequential C-H activation, insertion and deoxy-oxidative annulation has been proposed based on the preliminary mechanistic study. © The Royal Society of Chemistry 2016.

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