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Recent Papers

CAD Diagnosis Using PSO, BAT, MLR And SVM

Coronary artery disease (CAD) is a most common type of heart disease. CAD happen when a blood clot cuts off the heart’s blood supply, causing permanent heart damage. Diagnosis of CAD can be done using angiography, echocardiogram, electrocardiogram, which are complex methods. Therefore, studies are done to predict CAD using machine learning algorithms. This study proposes, feature selection by particle swarm optimization(PSO) and Bat algorithms, clustering using K-means and classification using Multinomial logistic regression (MLR) and support vector machine (SVM) algorithms. This technique is cross checked upon 14 attributes with 303 instances. A benchmark dataset from Cleveland heart disease data is used. The Bat-SVM model achieves the highest prediction accuracy of 97 %. The proposed model has an increased accuracy from the existing systems.

Published by: Hinduja .R, Mettildha Mary .I, Ilakkiya .M, Kavya .S

Author: Hinduja .R

Paper ID: V3I2-1431

Paper Status: published

Published: April 7, 2017

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Intelligent Street Light

This project efficiently defines the control of the street lighting system and thereby saving electricity as well as helping in monitoring other aspects of the environment which are a major concern worldwide. It also describes the use of A reader module for vehicle monitoring and control. The proposed system also has vehicle theft control is also integrated into the system. The proposed system also helps to monitor pollution levels, carbon emission also the sound levels of the vehicles in traffic. The efficiency of the system is designed such that it can be readily installed in present on road conditions with the extra cost of controlling computer and the sensors.

Published by: Mrs. Anuja A. Borkar, Mr. Mandar Patil, Mr. Vedant Jangam, Mr. Akshay Adkurkar, Mr. Rishabh Narkar

Author: Mrs. Anuja A. Borkar

Paper ID: V3I2-1446

Paper Status: published

Published: April 7, 2017

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Automatic Mammogram Tumor Detection Using Supervised Learning Method

Breast cancer is the most occupied type of cancer in women that caused the most deaths among women. The early detection of breast cancer is more important for the chances of survival of the patient. This work has mainly four modules: Pre-processing, Segmentation is carried out by Active Contour algorithm and Advanced K-means algorithm, Feature extraction is done by Gray Level Co-occurrence Matrix (GLCM), Expectation Maximization (EM) and Principle Component Analysis (PCA), finally classification is done by Random Forest Classification. To achieve the objective of this work, MIAS (Mammographic Image Analysis Society) and IN breast databases are used as input images. The Accuracy achieved in this system is 95.83%.

Published by: Chandana Saipriya. V, Dhanalakshmi. B, Gnanasoundari. S, Mercy Therasa. M, Hemadevi. J

Author: Chandana Saipriya. V

Paper ID: V3I2-1450

Paper Status: published

Published: April 7, 2017

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Feature and Processing Of Recognition of Characters, Words & Connecting Motions

Recognition & Modeling of characters, words & connecting motions is accomplished based on six-degree-of-freedom hand motion data. We address air-writing on two levels: motion characters and motion words. Isolated air-writing characters can be recognized similar to motion gestures although with increased sophistication and variability. For motion word recognition in which letters are connected and superimposed in the same virtual box in space, we build statistical models for words by concatenating clustered ligature models and individual letter models. A hidden Markov model is used for air-writing modeling and recognition. We show that motion data along dimensions beyond a 2-D trajectory can be beneficially discriminating for air-writing recognition

Published by: Deepa .D, R. Dharmalingam

Author: Deepa .D

Paper ID: V3I2-1455

Paper Status: published

Published: April 7, 2017

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Review On Social Media Analytics

This paper highlights the wealth of social media analytics available. It provides a comprehensive review of the social networking media, wikis, blogs, newspaper group chat etc. Social media Analytics is an emerging interdisciplinary research field that aims on combining, extending and adapting methods for analytics of social media data. For completeness, it includes introduction to analytics on data based on social media scraping storage, data cleaning and sentiment analytics. Major research area and business activities are based on analysing social media, in particular Twitter feeds for sentiment analysis.

Published by: Divya Kataria

Author: Divya Kataria

Paper ID: V3I2-1459

Paper Status: published

Published: April 7, 2017

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Design and Manufacturing of Seed Sowing Machine

The basic objective of showing operation is to put the seed and fertilizer in rows at desired depth and seed to seed spacing, cover the seeds with soil and provide proper compaction over the seed. The recommended row to row spacing, seed rate, seed to seed spacing and depth of seed placement vary from crop to crop and for different agro-climatic conditions to achieve optimum yields. The comparison between the traditional sowing method and the new proposed machine which can perform a number of simultaneous operations and has a number of advantages. As day by day the labor availability becomes the great concern for the farmers and labor cost is more, this machine reduces the efforts and total cost of sowing the seeds and fertilizer placement.

Published by: Nagesh B. Adalinge, Ganesh P. Ghune, Ganesh B. Lavate, Rahul R. Mane

Author: Nagesh B. Adalinge

Paper ID: V3I2-1407

Paper Status: published

Published: April 3, 2017

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