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Research Paper

Investigation on the diffusion of chlorides into concrete

This paper discusses Rapid Chloride Permeability Test investigations on the penetration of chloride ions into the concrete. Concrete samples of M40 and M50 Grades have been tested. The concrete specimens are made using standard molds of 100mm diameter x 50mm height. After curing the concrete samples are experimented. Specimens were cast and tested for 28 days. One chamber is filled with sodium chloride (NaCl) and another sodium hydroxide solution is filled. The strength of sodium chloride solution is varied from 1000ppm-35000ppm and the strength of sodium hydroxide solution are 0.04N. For all the combinations, RCPT was carried out and the charge passed through the specimens was noted. The Rapid Chloride Permeability Test values are found, the penetration charge through the concrete decreased with an increase in the grade of concrete.

Published by: Sandesh N. S., Sudeep Y. H.

Author: Sandesh N. S.

Paper ID: V7I3-2219

Paper Status: published

Published: June 30, 2021

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Research Paper

Malaria Parasite Detection System using Deep Learning and Image Processing

Malaria is a mosquito-borne blood disease caused by Plasmodium parasites which are deadly, infectious, and life-threatening. The conventional and standard way of diagnosing malaria is by visual examination of blood smears via microscope for parasite-infected red blood cells under the microscope by qualified technicians. The given method is inefficient, time-consuming and the diagnosis depends on the experience and the knowledge of the person doing the examination. Image processing based Automatic image recognition technologies has been applied to malaria blood smears for diagnosis before. However, the practical performance has not been up to expectation. With the early prediction results, healthcare professionals can provide better decisions for patient diagnosis and treatments. This motivates us to make malaria detection and diagnosis fast, easy and efficient. To get quick results for the malaria tests, we proposed a model that involves Deep Learning and Image Processing. In this paper, we developed a model using Convolutional Neural Networks (CNNs) classifier that predicts whether the input image is malaria parasitized or not. The CNN model has many convolution blocks that detect even the tiniest possibility of plasmodium parasite present in our input. The proposed model is also evaluated using a large amount of data to increase its accuracy and correctness while detecting the malaria parasite.

Published by: Gaddayi Pravallika, M. Sion Kumari, Dora Aasritha, Gandepalli Vandana, Gandrapu Suswitha

Author: Gaddayi Pravallika

Paper ID: V7I3-2221

Paper Status: published

Published: June 30, 2021

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Others

House rate prediction system using Machine Learning

Everyone's desire is to purchase a home. When it comes to getting the best price, some people spend more than the property is actually worth. To tackle this challenge, we devised a method for predicting the price of a property using Machine Learning's Linear Regression model. We took into account all of the factors that one considers when purchasing a home, such as the neighborhood, the number of bedrooms, and the number of restrooms. It will undoubtedly assist the buyer in obtaining the best possible price.

Published by: Pratyush Kumar Mishra, Richa Tiwary, Harshitha T., Jagbeer Poonia, Dr. Shantakumar B. Patil

Author: Pratyush Kumar Mishra

Paper ID: V7I3-2218

Paper Status: published

Published: June 30, 2021

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Research Paper

Sentiment analysis for Twitter data

Sentiment Analysis or analyzing emotion can be the process of understanding various textual opinions. Also known as opinion mining or emotional AI. People are interested in posting comments on social media that refer to their event experience to understand if most people had a positive or negative experience with the same incident. This classification is being achieved using Sentiment Analysis. Sentiment analysis takes a few unstructured text comments, events, etc. In all comments posted by multiple users and classifies the comments into different categories as positive or negative opinions. This is also called the Polarity classification. Sentimental Analysis is performed by text analysis and linguistics. This work aims to compare the performance of various machine learning algorithms when performing sentiment analysis for Twitter data.

Published by: Sampada Mohan Naik, Mythri B., Neha T. S., Prathiksha M., Sunil G. L.

Author: Sampada Mohan Naik

Paper ID: V7I3-2217

Paper Status: published

Published: June 30, 2021

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Thesis

Waste minimization in construction using lean six sigma

In India, the construction industry is one of the largest industries after the agriculture industry. It produces a large quantity of waste and consumes more resources, which makes construction a troubling task. The application of new technology, the Lean Six Sigma concept is likely to be effective for improving the efficiency of the construction industry. It aims to eliminate all defects and also to minimize the wastage of materials, time, and effort in order to generate the maximum possible amount of value. The aim of this study is to evaluate, Lean six sigma as a process improvement method to improve the construction process by, understanding and analyzing the factors affecting the formation of construction wastes. It is not possible to implement a lean philosophy into a company, without understanding the basics and purpose for which they were introduced. The practical part of the study is devoted to a detailed analysis construction process using the well-known Six Sigma cycle DMAIC - an abbreviation of the words: Define - Measure - Analyze - Improve - Control. The analysis was carried out on the basis of net study and interviews with the construction management and employees of subcontracting companies present at the construction site. The set of 45 potential factors which contribute most to waste generation was identified. A questionnaire survey was developed and sent to architects, contractors, and project managers involved with on-site construction activities. It can be said that using quality management tools (Lean and Sig Sigma principles) it is possible to visibly improve building processes and it is likely to achieve waste minimization before and during construction works.

Published by: Irene Devakirubai, V. Vidya Naveen

Author: Irene Devakirubai

Paper ID: V7I3-2209

Paper Status: published

Published: June 30, 2021

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Research Paper

Virtual telepresence robot

This paper proposes a method for a Virtual Telepresence Robot. That is a user can control a wireless robot remotely from any part of the world along with the live video transmission from the robot’s location. The 3 components of this project are the wheeled-robot, the camera with pan-tilt head mechanism and a web server (Flask Web Server). Raspberry Pi is the central component that interfaces user and the virtual telepresence robot over internet. The web interface is built on a flask Micro-web server application, which used to control the robot in localhost, further Ngrok is used for tunnelling local host web server to internet, through which the user can control the robot over the internet. The web server sends a wireless command which is received by Raspberry pi thus actuating robot and camera directions. The MJPEG streamer application is used for streaming video that gets mjpeg data and sends it through the HTTP session. The Raspberry pi is programmed in python language.

Published by: Lavanya M., M. L. Vaishnavi, M. Raaga Vaishnavi, Manish T. J., Veerappa Chikkagoudar

Author: Lavanya M.

Paper ID: V7I3-2208

Paper Status: published

Published: June 30, 2021

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