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Malik M.B.,University | Asger M.,University | Ali R.,Aligarh Muslim University | Sarvar A.,University of JammuJ and K
2015 International Conference on Computing for Sustainable Global Development, INDIACom 2015 | Year: 2015

Data mining is branch of computer science that delivers valuable information hidden in large volumes of data. The success of data mining depends on the quality of data and the algorithms used to extract information. A large number of tools and techniques have been developed for the purpose. Soft Computing methods have also emerged as a powerful tool for data mining as soft computing is tolerant to uncertainty, partial truth and imprecision. It helps in achieving solutions that are low cost, robust and tractable. Neural Networks are being extensively used for analysis purposes in every field of life from business to health sectors. In the current scenario where privacy of an individual is an important issue, people are reluctant to share their confidential information. Thereby privacy preserving in data mining (PPDM) has emerged as an indistinguishable component of data mining. The aim of this paper is to propose a model that preserves the privacy of individuals without affecting the final results of the Neural Networks. © 2015 IEEE. Source

Bala M.,University of JammuJ and K | Devanand,University of JammuJ and K
2015 International Conference on Computing for Sustainable Global Development, INDIACom 2015 | Year: 2015

Traditionally, the primary focus of datacenter and network designers has been on the performance improvement and high system throughput. Energy consumption has been rarely a design consideration. But in the recent years, the ICT sector has grown exponentially and many studies, on energy consumption of datacenters, reveal that there is requirement of developing new mechanisms, for using energy efficiently in ICT area. Datacenters comprising of computing and communicating devices, are responsible for Green House Gas (like CO2) emissions and adds a lot to carbon footprints due to non power aware hardware and software designs. In the present work, various green computing concepts that can be implemented at hardware as well as software levels to reduce power consumption, have been studied. The experimental work presents the simulation environment that captures the energy consumption of computing and communicating devices of the cloud environment. It also demonstrates the effectiveness of various green computing tactics over the classical methods of computing using various datacenter architectures. © 2015 IEEE. Source

Bhagat M.,University of JammuJ and K | Rajput S.,University of JammuJ and K | Arya S.,University of JammuJ and K | Khan S.,University of JammuJ and K | Lehana P.,University of JammuJ and K
Bulletin of Materials Science | Year: 2015

In this work, silver nanoparticles (AgNPs) were synthesized biochemically at room temperature using aqueous extract of rhizome of Rheum australe plant. The as-synthesized AgNPs were further studied for their morphological, biological and electrical characterization. The morphological studies, such as scanning electron microscopy, X-ray diffraction and UV-vis spectrum confirmed their successful synthesis. Biological analysis revealed their antioxidant activity by 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. Electrical characterization showed that the conductivity of the mixture of AgNPs with DPPH assay is more than the AgNPs dispersed in distilled water. The obtained results may have potential applications as sensors. © 2015 Indian Academy of Sciences. Source

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