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Evaluation of Antioxidant Activity of Phenol, Hibiscus Rosasinensis, Neem and Leaves Extract at Different Infusion Times

The present study reveals that the selected plants would exert several benefits by virtue of their antioxidant activity and could be harnessed as antimicrobial, anti-inflammatory and anti-corrosive agents. The aqueous and Ethanol crude extract of Neem, Hibiscus leaves and the mixture of both leaves' extract were screened for their free radical scavenging properties. Free radical scavenging activity was evaluated using DPPH, NO, FRAP and H2O2 free radicals. The aim of this study was to evaluate the antioxidant activity of Phenol, Flavonoids and Tannins content in Neem extract (Azadirachta Indica), Hibiscus leaves and the mixture of both leaves' extract at different infusion times and determination of the protective effect of metallic corrosion caused by soil microbes.

Published by: R. Prasanna

Author: R. Prasanna

Paper ID: V3I1-1243

Paper Status: published

Published: January 21, 2017

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Research Paper

Novel Approach Of Diabetes Disease Classification By Support Vector Machine With RBF Kernel

Early diagnosis of any disease with less cost is always preferable. Diabetes is one such disease. It has become the fourth leading cause of death in developed countries and is also reaching epidemic proportions in many developing and newly industrialized nations. Diabetes leads to increase in the risks of developing kidney disease, blindness, nerve damage, blood vessel damage and heart disease also. In this research work, Support Vector Machine with RBF Kernel is used for finding out the classification accuracy of diabetes dataset. In the given method, the advance algorithm of SVM-RBF kernel is used; it contains some of the extended parameters for feature selection as well as the proposed correlation with SVM method obtains on UCI dataset. In this work, investigation is done on automatic approach to diagnose diabetes disease based on Support vector machine with RBF kernel and MLP (Multilayer perceptrons). The concept of data mining is used, in which the proposed SVM-RBF method obtains 88% accuracy on UCI diabetes dataset, which is better than other models.

Published by: Preeti Verma, Inderpreet Kaur, Jaspreet Kaur

Author: Preeti Verma

Paper ID: V3I1-1242

Paper Status: published

Published: January 20, 2017

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Research Paper

Medical Tumour Image Segmentation by BAT Optimization

In the field of medical images, automatic segmentation of ROI region accuracy plays the most important role. For tumor segmentation, a network should be optimized with precise weights for the respective features. Till yet researchers used many features like intensity and area with various optimization techniques. Accuracy mostly depends upon the features. It is directly proportional to the number of features. Our proposed algorithm going to use energy feature like LESH with BAT colony optimization to enhances the optimization problem for weights. The proposed work will include all the features of time and spatial domain so is more sensitive to optimize the weights in spite of using only time domain features.

Published by: Nagampreet kaur, Natasha sharma

Author: Nagampreet kaur

Paper ID: V3I1-1239

Paper Status: published

Published: January 20, 2017

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Study of Adsorption Impact of Wood Ash and Fly Ash on Spent Wash Quality for Irrigation Purpose

Adsorption treatment of distillery spent wash has great potential as a sustainable method as it is a low-cost method. The aim of this investigation is to study the treatment method for purification of distillery spent wash by using Fly ash and Wood ash. For this, the study comprising evaluation of reduction of various physical-chemical parameters (Color, Odor, pH, COD, TS, TDS, Ca, Mg, Na, and K) of distillery spent wash was checked by passing through the columns of Fly ash and Wood ash. The distillery effluent was acidic (pH 4.7) and dark brown in color which often cause psychological fear in farmers for utilization. Fly ash treatment of spent wash exhibited a good reduction in COD, TS, TDS, Mg, Na, Ca, after 72-hour treatment and increase in pH toward pH 7 followed by Fly ash + Wood ash (1:1).

Published by: Bharat Kumar, Arun Upreti, Prashant Singh Rawat, Sakshi Rana

Author: Bharat Kumar

Paper ID: V3I1-1236

Paper Status: published

Published: January 20, 2017

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Multi Bank System

The project title is “Multi Banking System” the system interface is targeted to the future banking solution for the users who is having multiple bank accounts in multiple banks. This interface integrates all existing banks and provides business solutions for both retail and corporate. Multi-bank system is an innovative .Net web application. The main focus of the application is maintaining multiple bank accounts a user has. A person can have bank account in any number of banks. But it’s hard to remember every bank logins. So we have developed a web application where a person can handle all his bank accounts in a secure manner.

Published by: A. Anitha, R. Abirami, V. Vaneeswari

Author: A. Anitha

Paper ID: V3I1-1233

Paper Status: published

Published: January 20, 2017

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Research Paper

Novel approach for IDS Classification Support vector machine and adaptive boost

we perform three sets of experiments. From the first experiment, the systems are trained using all the 41 features. The second experiment where we perform feature selection by using Gain Ratio as to select the best features instead of using all the 41 features and perform the experiment with Linear SVM, SGD and Adaptive Boost and compare the results. The third experiment where we perform feature extraction by using Gain Ratio as to select the best features instead of using all the 41 features and perform the experiment with Linear SVM, SGD and Adaptive Boost and compare the results.

Published by: Aanchal Kumar, Jaspreet Kaur, Inderpreet Kaur

Author: Aanchal Kumar

Paper ID: V3I1-1232

Paper Status: published

Published: January 19, 2017

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