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Recent Papers

An Emergency Message Dissemination Protocol Using Greedy Forwarding Technique and Clustering For Vanets

Vehicu1ar Ad Hoc Networks is oriented to vehicular communication and regarded as one specific application of Mobi1e Ad Hoc Networks. The prospect of its applications in the inte11igent transportation and entertainment services is cheerfu1. The paper makes a research on GPSR (Greedy Perimeter State1ess Routing for Wire1ess Networks) protoco1. Ana1yze how it works in detai1 and points out its defects in different environments. Then put forward an improved GPSR protoco1 based on position vector aiming at some defects First of a11, it introduces the VANET’s history of development and protocols on some important 1ayers in brief. Based on the comprehensive understanding of the routing mechanism, study the suggested solution for each of defects. Based on the position vector ca1cu1ation and simp1e redundancy elimination, GPSR protoco1 is modified. Moreover, a preliminary assumption is presented specia1 for retrograde motion. Through the comparison with the origina1 one, it proves that the improved protoco1 performs better. We need to carry out the simulation of VANET in the computer environment i.e. we shou1d do a computer simulation. Computer simulation is risk and danger free, we can generate different scenario (rura1, urban, co11ision of vehicles) of the VANET using this. So computer simulation is very important for VANET research. Simu1ation of VANET is divided into two part a. Traffic simulation: Generation of traffic movement, defining the mobility mode1 for vehic1e and creating traffic movement. b. Network simulation: Generating Intercommunicating vehic1e, Defining communication protocols. And both the simulation is connected in the bi-directiona1 coupling.

Published by: Harpreet Singh, Dr. Anju Sharma

Author: Harpreet Singh

Paper ID: V3I2-1417

Paper Status: published

Published: April 7, 2017

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Complexity of Cuckoo Hashing

We will present a simple cuckoo hashing with an example of how it works. Along with it, we will present an algorithm to find loop in cuckoo hashing

Published by: Nitesh Gupta, Dr. Om Prakash

Author: Nitesh Gupta

Paper ID: V3I2-1418

Paper Status: published

Published: April 7, 2017

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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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