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
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
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
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
Effect of Microwave (Mw) Treatments of Resistant and Native Starches
Instead of consumption of traditional natural foods the refined foods containing high calories are consumed everyday leading several diseases. The consumption of high amount of resistant starches may improve glucose and lipid metabolism can reduce the risk of several diseases. The main aim of the study was to examine the effect of microwave (MW) treatment of resistant and native starches as in present day there is an increasing trend to use microwave in food preparation. The objective of the study was to examine the effect of microwave (MV) treatment on resistant and native starches. Two samples of untreated native starches and resistant starches were microwave treated according to 2^2 experimental design. Result shows that the cooking step affect significantly higher degradability in wheat, maize and Rs4 stanches compared to RS2 starch. Different types of RS behave similarly in case of dry heat treatment more over, the more intense moisture heat treatment cause different changes in the properties of RS.
Published by: Asha Kumari
Author: Asha Kumari
Paper ID: V3I2-1251
Paper Status: published
Published: March 20, 2017
A Review on Improve Energy Efficiency in Cognitive Radio Ad Hoc Networks by Selecting Secondary User
Wireless networks combining the advantages of both mobile ad-hoc networks and infrastructure wireless networks have been receiving increased attention due to their ultra-high performance. Users have the capability to sense available spectrum in Cognitive Radio Networks (CRNs).Users can opportunistically access to the spectrum. Paper proposed for energy consumption for CRNs, Which is higher in traditional Cognitive Radio Ad Hoc Network (CRAHNs). Users mainly depend on spectrum access so the requirement of network architecture is user spectral. In the proposed network architecture, only parts of user’s are equipped with Cognitive Radio (CR) module. Additionally, user management done, a minimum number of users are selected to sense available spectrum, which aims at reducing the energy consumption further. The minimum number of users selection problem is formulated as an optimal routing algorithm problem under the constraints of energy efficiency and the real-time available spectrum information. Hence, a distributed optimal routing algorithm is proposed to calculate the optimal solution. The optimal routing algorithm in the proposed network architecture outperforms and traditional Cognitive Radio Ad Hoc Networks in energy efficiency.
Published by: Raghunath K. Borkar, Prof. Sheshnarayan Ghungrad
Author: Raghunath K. Borkar
Paper ID: V3I2-1246
Paper Status: published
Published: March 20, 2017
