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Recent Papers

Biosynthesis of Silver Nanoparticles Using Lactobacillus Acidophilus and White Rot Fungus- A Comparative Study

Future perspective of nanotechnology is to enhance the biological approach. In the present investigation biosynthesis of silver nanoparticles was evolved by bioreduction of silver by mixture (AgNO3+ filtrate). The confirmation of silver nanoparticle synthesis was characterized using SPR band shown in UV-Visible spectroscopy and FTIR analysis. SEM micrographs depict puff shaped structure ranging from 20-50nm in size. Antimicrobial activity of biosynthesized Ag nanoparticle showed inhibitory activity against strains. While comparing strains, effective anticancerous activity was found in white rot fungus. This, in turn, gives the insight to develop new formulations for the conventional method in pharmaceutical companies.

Published by: Kalaivani .K, Dr. Puniethaa Prabhu

Author: Kalaivani .K

Paper ID: V3I2-1256

Paper Status: published

Published: March 20, 2017

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Implementation of 3 Phase 4 Wire Energy Meter of Class 0.5 Accuracy

Electricity is one of the vital requirements for sustainment of comfort of life. It should be used very judiciously for its proper utilization. The main purpose of this project is to measure the energy with high accuracy for industrial applications. In industry, There are lots of control panels in which the energy meters are used to measure the amount of energy consumed. Today with several manufacturers in the market , There are lots of parameters has to be considered like accuracy, cost, the size of meter etc. while designing the product. In the market, many types of energy meters are available for industrial applications but the high accuracy meters are not available that’s why it is the necessity of the market to propose an energy meter with high accuracy.

Published by: Sanjay Dhumal, Vinodpuri R. Gosavi

Author: Sanjay Dhumal

Paper ID: V3I2-1253

Paper Status: published

Published: March 20, 2017

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Healthcare Prediction Analysis in Big Data using Random Forest Classifier

An infrastructure build in the big data platform is reliable to challenge the commercial and not- commercial IT development communities of data streams in high dimensional data cluster modeling. The knowledge discovery in database (KDD) is alarmed by the development of methods and techniques for making use of data. The data size is generally growing from day to day. One of the most important steps of the KDD is the data mining which is the ability to extract useful knowledge hidden in this large amount of data. Both the data mining and healthcare industry have emerged some of reliable early detection systems and other various healthcare related systems from the clinical and diagnosis data. In this paper propose the enhanced data mining algorithm for healthcare application. It consists of three steps they are anomaly detection, clustering, and classification. In this classification algorithm use the random forest algorithm for accurately predict the patient result from a large amount of data. Finally, our experimental result shows our proposed method can achieve more accuracy result.

Published by: Subhapriya. P, R. Sujatha, K. Meghana

Author: Subhapriya. P

Paper ID: V3I2-1255

Paper Status: published

Published: March 20, 2017

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Assessment of Mortality (Lc50) Of Cythion and Dieldrine by Filter Paper Contact Test on Earthworm Esenia Feotida

We used filter paper contact test method for obtaining LC50 for python and dieldrin. This Organophosphate is very poisonous, which affects the body and Growth of Earthworm. We had seen in the test solution of 0.8mg/cm2, 0.9m g/cm2 and 1mg/cm2of 1% dieldrin, all earthworms died and melt. Similarly, cythion 0.3 and 0.27 showed the same result. This concentration was shown super toxic to earthworms. In the test solutions of 0.1mg/cm2 and 0.2mg, the earthworms were very active and not stationary. In test solutions of 0.3mg/cm2 and 0.4mg/cm2 the earthworm was slightly less active, and in 0.5mg/cm2, the concentration of test solution earthworm was live and less active in this experiment. Similarly the 0.03m g/cm2, 0.06 mg/cm2 and 0.09 mg/cm2 concentration showed same effect for cythion. We used three replica test set for the better resulting and calculated mortality. At the end of the experiment, we observed that 0.5 mg/cm2concentration of dieldrin and 0.15m g/cm2 for cythion was shown LC50 value of mortality. In some set like 1 mg/cm2, 0.9 mg/cm2 was very highly affected on earthworm they had been broken, melt and the body had destroyed. It was shown directly effect on the earthworm’s body and growth.

Published by: Ahmad Shahzad, S. S Pawar

Author: Ahmad Shahzad

Paper ID: V3I2-1262

Paper Status: published

Published: March 20, 2017

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IOT Based Water Management System for Smart City

During the past decade, water needs have increased unpredictably in India. Increasing demand of water supply has become a major challenge for the world. Wasteful usage of water, climatic changes and Urbanization has further depleted the resource. Conservation and management of the resource must be given utmost importance. In this paper, we present an IoT design for water monitoring and control approach which supports internet based data collection on real time basis. The system addresses new challenges in the water sector -flow rate measuring and the need for a study of the supply of water in order to curb water wastage and encourage its conservation. We also measure the quality of water distributed to every household by deploying pH and conductivity sensors. The traditional water metering systems require periodic human intervention for maintenance making it inconvenient and often least effective.For shortcoming of the existing models for a ubiquitous usage of wireless systems for smart quality monitoring and communicate data wirelessly.

Published by: Patawala Amatulla Hakimuddin, Bansode Navanath Pandurang, Bhong Yogesh .P, Zadbuke Ashwini .S

Author: Patawala Amatulla Hakimuddin

Paper ID: V3I2-1252

Paper Status: published

Published: March 20, 2017

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Automated Performance Evaluation System

Accurately predicting student performance is useful in different contexts in universities. Educational data mining (EDM) is an emerging discipline, concerned with various approaches such as predicting student performance, Analysis and data visualization, providing feedback for supporting instructors, recommendations for students and so on that automatically extracts meaning from large data generated by or related to people's learning activities in an educational setting. For example, identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. One of the biggest challenges is to improve the quality of the educational processes so as to enhance student’s performance. The results of these studies give insight into techniques for accurately predicting student performance.

Published by: Sana Akhai, Ruchi Karia, Aniket Mahadik, Akshat Shah, Manya Gidwani

Author: Sana Akhai

Paper ID: V3I2-1249

Paper Status: published

Published: March 20, 2017

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