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Research Paper

Sentiment analysis on Twitter

With the rise of social networking epoch, there has been a surge of user-generated content. Micro-blogging sites have millions of people sharing their thoughts daily because of its characteristic short and simple manner of expression. We propose and investigate a paradigm to mine the sentiment from a popular real-time micro-blogging service, Twitter, where users post real-time reactions to and opinions about everything. In this project, we expound a hybrid approach using both corpus-based and dictionary-based methods to determine the semantic orientation of the opinion words in tweets. We know that there are almost 111 microblogging sites. Microblogging websites are nothing but social media site to which user makes short and frequent posts. Twitter is one of the famous microblogging services where the user can read and post messages which are 148 characters in length. Twitter messages are also called as Tweets. We will use these tweets as raw data. We will use a method that automatically extracts tweets into positive, negative or neutral sentiments. By using the sentiment analysis the customer can know the feedback about the product or services before making a purchase.

Published by: Shruti Vinay Narkhede, Rohini Pramod Mahajan, Sayali Sanjay Nemade, Shivani Manoj Badgujar

Author: Shruti Vinay Narkhede

Paper ID: V4I3-1816

Paper Status: published

Published: June 9, 2018

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Research Paper

FAUX leather exploration: A creative approach

Fashion conscious consumers demand updated and up style look for themselves. They not only look at the functions of the product but also the aesthetics according to the current fashion. They are now more conscious of what they buy, about the style, visual appearance, etc. The use of faux leather instead of natural leather can cater the demand of fashion products as well as will also take care of the environmental, economic and religious concerns of the consumers. This research is on the utilization of faux leather as the design element for the apparels. Using different techniques, innovative designs collection is developed. Further, the selected techniques have been applied as the surface enhancement on Indo-western outfits.

Published by: Simran Kaur, Dr. Amita Walia, Deepika Birhman

Author: Simran Kaur

Paper ID: V4I3-1805

Paper Status: published

Published: June 9, 2018

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Thesis

Clustering technique in WSN using PSO algorithm

The lifetime maximization of the network is taken into account because of the major task while deploying a WSN. Some sort of protocols was designed to satisfy the necessity. Clustering technique is taken into account collectively of the necessary technique for the topology control to attain the target. This paper focuses on the lifetime maximization of the nodes by using Particle Swarm Optimization (PSO) algorithm. The proposed protocol shows higher ends up in a well-balanced clustering system that improves the network lifetime. Analysis, MATLAB Simulation, and the Experimental result were illustrated in this paper.

Published by: Mariyakkutty V V, Ajit Joseph

Author: Mariyakkutty V V

Paper ID: V4I3-1806

Paper Status: published

Published: June 9, 2018

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Research Paper

Knowledge of nurses on essential newborn care

Introduction Essential newborn care is a care that every newborn baby needs regardless of where it is born or its size. Essential newborn care should be applied immediately after the baby is born and continued for at least the first 7 days after birth (WHO). This study was conducted to assess the knowledge of nurses on essential newborn care. Methods The study was conducted using descriptive correlational research design. The samples included 30 nurses working in Apollo Cradle for Women & Children who were selected using purposive sampling technique. Data was collected using demographic variable proforma and structured questionnaire to assess the knowledge of nurses on essential newborn care through a non-experimental descriptive method. Results revealed that the mean and standard deviation of knowledge of nurses on essential newborn care was (M = 14.93, SD = 3.35). The study findings revealed that there was the significant association between selected demographic variables and knowledge of the nurses -years of experience and knowledge of nurses on essential newborn care (p < 0.05).

Published by: Jennifer G, Nesa Sathya Satchi, Dr. Latha Venkatesan

Author: Jennifer G

Paper ID: V4I3-1795

Paper Status: published

Published: June 9, 2018

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Review Paper

Vehicle detection using MATLAB

Automatic detection and counting of vehicles in an unsupervised videos on highways is very challenging in computer vision with important practical applications like monitoring traffic activities.Counting the number of objects is integral part of image processing.Knowing the number of objects present in the image is very useful in wide range of applications.The main objective of our study is to develop methodology for automatic vehicle detection and its counting on highways.A system has been developed to detect and count objects efficiently.We present a system for detecting and tracking vehicles in surveillance video which uses segmentation with initial background substraction using morphological operator to determine salient regions in sequence of video frames.

Published by: Roshni M., Maleka Anjum, Noorain Fatima

Author: Roshni M.

Paper ID: V4I3-1617

Paper Status: published

Published: June 9, 2018

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Research Paper

Identifying disease treatment by support vector machine with polynomial kernel

The Machine Learning field has gained its thrust in almost any domain of research and just recently has become a reliable tool in the medical domain. The experiential domain of automatic learning is used in tasks such as medical decision support, medical imaging, protein-protein interaction, extraction of medical knowledge, and for overall patient management care. ML is envisioned as a tool by which computer-based systems can be integrated into the healthcare field in order to get a better, well-organized medical care. It describes an ML-based methodology for building an application that is capable of identifying and disseminating healthcare information. It extracts sentences from published medical papers that mention diseases and treatments and identifies semantic relations that exist between diseases and treatments. Results for these tasks show that the proposed methodology obtains reliable outcomes that could be integrated into an application to be used in the medical care domain. The potential value of this method stands in the ML settings that are proposed and in the fact that it outperforms previous results on the same dataset.

Published by: Girish Vijay Agrawal, Kunal Sunil Ingale, Arpit Nitin Behede, Prashant Somnath Jadhav

Author: Girish Vijay Agrawal

Paper ID: V4I3-1820

Paper Status: published

Published: June 8, 2018

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