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Family impact on students’ motivation in Kanyakumari district

This study tries to identify the impact of some family important variable on students' Motivation. Several studies had stressed out the significance of study students' motivation as a move toward to improve their academic performance and develop the firm image. The families and society's changing values and cultures have a great impact on the students' motivation and their academic integration and recital. The questionnaire has consisted of some items. Results showed that students tend to attribute their academic success to internal factors such as hard working while they feature their failure to external factors such as family crisis.

Published by: T. Karthika Devi

Author: T. Karthika Devi

Paper ID: V5I2-1141

Paper Status: published

Published: March 7, 2019

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Survey Report

A survey on motion picture prediction using data mining

In this study, a mathematical model used to predict an upcoming movie success class. This will help to suggest as your interest before release based on several attributes and It will take the suggestion from different linked social sites to determine the interest of the audience. It also shows the most interesting result on top of your list. Many film studios collectively produce several hundred movies every year; the budget of this movie is of the order of hundreds of millions, making their Box office success absolutely essential for the survival of the Industry. Knowing which movie is going to succeed and which are going to fail before the release could benefit the Industry. In this paper, we have enlisted some existing movie prediction using data mining for predicting success and failure by considering their advantages and disadvantages.

Published by: Abhishek More, Sharique Khan, Thabreez Izzudeen

Author: Abhishek More

Paper ID: V5I2-1156

Paper Status: published

Published: March 7, 2019

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Research Paper

Analysis of psychological variables between training under a coach and self training athletes

Sports Psychology addresses the interactions between psychology and sports performance, including the psychological aspects of optimal athletic performance, the psychological care and well-being of athletes, coaches, and sports organizations, and the connection between physical and psychological functioning. Sports psychologists can participate in various activities, mostly focused on working to understand what motivates athletes and how athletes can improve their performance. The purpose of the study is to find out Psychological variables between training under a coach and self-training athletes. Thirty athletes training under a coach (15) and self-training (15) was selected randomly from Virudhunagar district, their age group between 22 to 26 years. The subjects were divided into two groups as under a coach group and self-training group. As per the available works of literature, the standardized questioners were used to collect relevant data on the selected variables as stress, anxiety, achievement motivation, and happiness. The collected data were statistically analyzed by using an independent t-test. In all the cases 0.05 level of confidence was fixed as a level of confidence to test the hypothesis. The result shows that there was significantly different between training under a coach group and self-training group on stress, anxiety, achievement motivation, and happiness.

Published by: Dr. G. Peter Michael Raj

Author: Dr. G. Peter Michael Raj

Paper ID: V5I2-1144

Paper Status: published

Published: March 6, 2019

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Research Paper

Evaluating Alzheimer’s patients’ assistance systems in HCI Domain

Nowadays, computer systems play a very important role in the health care context. However, many of these systems are also becoming increasingly complex. In particular, the design of these systems should be compatible with Alzheimer’s situation, as the condition of Alzheimer patients is growing worse, especially with the poor understanding of the disease, lack of support language difficulties, and memory loss. These systems should meet the various needs of such patients. In this paper, we are focusing on evaluating Alzheimer's assistance systems. Usually, in designing those systems, the human-computer interaction (HCI) is left behind. Thus, we demonstrate several aspects to improve Alzheimer’s patient ability to interact with these systems. Moreover, we discussed the key factors that affect the success or failure of those systems taking into consideration criterion such as bringing down health care costs, learnability, usability, dependability, readability, and facilitate automating. At the end, the paper illustrates using charts, and tables to show the impact of applying HCI when designing an interface to achieve user-friendly, intuitive interfaces, and higher usability of the systems.

Published by: Master Prince, Bashayer A. Alafri, Maram S. Alqueflie, Reem A. Almijmaj, Yassmeen A. Alnasser

Author: Master Prince

Paper ID: V5I2-1164

Paper Status: published

Published: March 6, 2019

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Research Paper

Multi domain sentiment classification approach using supervised learning

Digital info out there on the net is increasing day by day. As a result of this, the demand for tools that facilitate individuals to find and analyzing of these resources also are growing in variety. Text Classification, particularly, has been terribly helpful in managing the information. Text Classification is that the method of assignment language text to 1 or a lot of classes supported the content. Its several necessary applications within the globe. As an example, finding the sentiment of the reviews, denote by people on restaurants, movies and different such things area unit all applications of Text Classification. During this project, the focus has been ordered on Sentiment Analysis that identifies the opinions expressed in a very piece of text. It involves categorizing opinions in text into classes like 'positive' or 'negative'. Existing works in Sentiment Analysis centered on decisive the polarity (Positive or negative) of a sentence. This comes below binary classification, which suggests classifying the given set of components into 2 teams. The aim of this analysis is to handle a unique approach for Sentiment Analysis known as Multi category Sentiment Classification. During this approach the sentences area unit classified below multiple sentiment categories like positive, negative, neutral then on. Classifiers area unit engineered on the prognostic Model, that consists of multiple phases. Analyses of various sets of options on the info set, like stemmers, n-grams, tf-idf then on, are thought of for classification of the info. Totally different classification models like Bayesian Classifier, Random Forest and SGD classifier area unit taken into thought for classifying the info and their results area unit compared. Frameworks like woodhen, Apache driver and sickest area unit used for building the classifiers

Published by: Parineeta Jha, Sajid Khan

Author: Parineeta Jha

Paper ID: V5I2-1167

Paper Status: published

Published: March 6, 2019

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Research Paper

Content based Image Retrieval System using K-Means Clustering Algorithm and SVM Classifier Technique

The dramatic rise in the sizes of pictures databases has blended the advancement of powerful and productive recovery frameworks. The improvement of these frameworks began with recovering pictures utilizing printed implications however later presented picture recovery dependent on substance. This came to be known as Content Based Image Retrieval or CBIR. Frameworks utilizing CBIR recover pictures dependent on visual highlights, for example, surface, shading and shape, rather than relying upon picture depictions or printed ordering. In the proposed work we will use various types of image features like colour, texture, shape, energy, amplitude and cluster distance to classify the images according to the query image. We will use multi-SVM technique along with clustering technique to compare the features of the input image with the input dataset of images to extract the similar images as that of the query image.

Published by: Harleen Kaur Maur, Puneet Jain

Author: Harleen Kaur Maur

Paper ID: V5I2-1143

Paper Status: published

Published: March 6, 2019

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