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Research Paper

Altered particle swarm optimization based attribute selection strategy with improved fuzzy Artificial Neural Network classifier for coronary artery heart disease risk prediction

The application of soft computing in decision support system in disease prediction is one of the emerging interdisciplinary research areas in the field of computer science. Machine learning algorithms plays an important role in risk prediction of diseases. Attribute selection among the dataset is the key factor that influences prediction accuracy. Mathew’s correlation coefficient performance metric is also taken into account. Particle swarm optimization algorithm is altered and applied for performing attribute selection. Improved fuzzy artificial neural network classifier performs the prediction task.

Published by: B. Narasimhan, Dr. A. Malathi

Author: B. Narasimhan

Paper ID: V5I2-1783

Paper Status: published

Published: April 6, 2019

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Research Paper

An exploration of the indian women writers

This work is to analyze the progress of Indian women in the field of writing right from the creation and sense the glitches faced by them. The themes of sexuality and man-woman relationship from the origin till the contemporary authors are discussed which became the theme of writing this paper. But they are found not merely as the raw material and each has engrossed various angles and given inimitable solutions. Their versatile treatment of women's issues reveals their sensitive nature as a woman writer, and this quality affirms their works as an outstanding contribution to Indian literature in English proving their uniqueness.

Published by: Dr. S. Bharathi, G. Vadivelmurugan

Author: Dr. S. Bharathi

Paper ID: V5I2-1544

Paper Status: published

Published: April 6, 2019

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Review Paper

Development of a cabin crew utility application (JEDZENIE)

This project is based on advanced computer software named as “JEDZENIE” provided in the aircraft for user-friendly customer care and crew management. The project will be used as advanced software installed in passenger seat utility screen. This software will be handled by airline crew members. This software includes the home page, login page & admin page. The passenger login with his/her seat no. & select the food that needed & proceed. The time when he/she order the food, the information is passed to the screen that is placed in the front of the cabin crew. So the project helps to reduce the work of cabin crews and easily access to passengers regarding food & other services. This will help to take the function into more advances in this generation and also for upcoming advanced passengers. This project is more useful in the case of physically/mentally challenged customers

Published by: M. R. Ranjith, Vignesh V. Nair

Author: M. R. Ranjith

Paper ID: V5I2-1778

Paper Status: published

Published: April 6, 2019

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Research Paper

Nap detection and alert system using OpenCV

In recent years driver fatigue is one of the major causes of vehicle accidents in the world. A direct way of measuring driver fatigue is measuring the state of the driver i.e. drowsiness. So it is very important to detect the drowsiness of the driver to save life and property. This project is aimed towards developing a prototype of a drowsiness detection system. This system is a real-time system which captures image continuously and measures the state of the eye according to the specified algorithm and gives a warning if required. Though there are several methods for measuring the drowsiness, this approach is completely non-intrusive which does not affect the driver in any way, hence giving the exact condition of the driver. For detection of drowsiness eye aspect ratio value of the eye is considered. So when the closure of eye exceeds a certain amount then the driver is identified to be sleepy. Corrections for drowsiness include both in and out vehicle alarms and its repetition turns the engine off after giving a signal to the vehicles behind. We are also providing security for the owner i.e., if the vehicle is driven by another person and does any kind of suspicious activities then ,not the actual person but the owner will face problems, in order to avoid the problem for the owner, when the engine starts we automatically capture the image of the driver along with date and time without knowledge of the driver. Then he can easily identify the person who is driving and the owner will be saved.

Published by: Bapathu Ramakrishna Reddy, Bitragunta Lakshmi Durga Pratyusha, Chakicherla Bala Sai Vagdevi, Annapureddy Venkata Ajaya Kumar Reddy, Ajay Rahul Hari

Author: Bapathu Ramakrishna Reddy

Paper ID: V5I2-1769

Paper Status: published

Published: April 6, 2019

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Research Paper

Disease detection using image processing

Malaria is a life-threatening disease which is caused by a Plasmodium parasite which is transmitted by infected mosquito’s bite. Similarly, Dengue fever is a very painful mosquito-borne disease caused by the dengue virus. Manual Detection of both of the diseases takes too much time and tropical and sub-tropical areas are experiencing these diseases at the high level and due to detection taking too long an automated system for detection of these diseases has become a need which consumes less time and cost. There are existing techniques for prediction of malaria using neural networks, multi-layer perceptron. Based on the survey in this paper we propose a system for prediction of malaria and dengue using image processing concepts such as segmentation techniques and morphological operations such as flood fill. In many laboratories, the blood cell count is done manually and needs to be done by an expert. This project uses a digital camera which works with a traditional microscope where the camera provides microscopic images to the computer. The proposed hardware is cost-efficient.

Published by: Naresh Mali, Shreya Nalawade, Saurabh Singh, Shweta Babar, Swapnil Shinde

Author: Naresh Mali

Paper ID: V5I2-1784

Paper Status: published

Published: April 6, 2019

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Others

SBT to assess the impact of BDA on customer’s online behaviour

With the rise of social network sites, almost every person has a profile. This profile contains various likes and dislikes about various items. It also contains their valence about other users on the network. In this paper a cloud-based recommendation engine is proposed which provides recommendations about various products given that a user likes a product X taking the balance theory of likes and dislikes over the network. This project can be used to provide personalized recommendations for advertisements or can be used by the user to explore other potential items that he may be interested in.

Published by: D. Madhu, Dr. T. Hanumantha Reddy

Author: D. Madhu

Paper ID: V5I2-1749

Paper Status: published

Published: April 6, 2019

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