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Research Paper

3D reconstruction of regular objects from multiple 2D images using a reference object

The dimensional analysis of an object from an image reduces a lot of burden for a user, like the traditional measuring tape method. Using the dimensions will make reconstruction of the 3D model of the real-time object easier. However, this method is not used in the current implementation. Dimensional analysis can also be helpful in online shopping where the user’s availability for fitting is not possible. 3D model replaces the fitting stage in online shopping. Once the dimensions of an object’s surface are found, it is easy to calculate surface areas, given surface areas we can calculate volume. But the calculation of volume requires more than one dimension of the object. In this paper, an approach using a reference object, whose real-time dimensions are already known is used. The whole process is divided into three tasks - Object detection using SURF algorithm, Dimensional Analysis of the 2D object using pixel per metric ratio given that there is a reference object on the same plane and 3D reconstruction using Structure from Motion algorithm.

Published by: Krishna Sai Joga, K. Kavya Sree, Navya Spandana, G. Gowri Pushpa

Author: Krishna Sai Joga

Paper ID: V5I2-1477

Paper Status: published

Published: March 26, 2019

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Research Paper

Forensic Criminology

This research focuses on the history development of forensic science and also shed light on the fusion of science and law that is how forensic science has brought in the administration of justice. This research aims to point out the flaws in the laws with reference to forensic evidence.

Published by: Barani Manikantan

Author: Barani Manikantan

Paper ID: V5I2-1317

Paper Status: published

Published: March 25, 2019

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Case Study

Fire monitoring system using RF module

The objective of this project is to design and monitor system for the fire alerts in the surrounding environment using Flame sensor. It is transmitted wirelessly using an RF module. The output is displayed in LCD and Lab-VIEW GUI.

Published by: Vedashree J., Abinaya S., Ganesh Babu C., Muchenedi Hari Kishor

Author: Vedashree J.

Paper ID: V5I2-1268

Paper Status: published

Published: March 25, 2019

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Survey Report

Twitter sentimental analysis

This paper presents the effectiveness of linguistic features to identify the sentiment of Twitter messages using the apache storm framework. We calculate the effectiveness of present lexical resources and features that capture information about the informal and creative language used in microblogging. In the past few years, there has been a huge growth in the use of microblogging platforms such as Twitter. Influenced by intensification, companies, and media organizations are increasingly seeking ways to excavate Twitter information about what people think and feel about their products and services. Here we download Twitter messages for a particular hashtag and carry out sentiment analysis i.e. to find a positive, negative or neutral sense of that tweet using apache storm framework. Each hashtag may have 1000 of comments and new comments are added every minute, in order to handle so many live tweets we are using apache storm framework.

Published by: Mandar Menjoge, Vedant Bhawalkar, Mazhar Sayyad, Jainam Gosaliya

Author: Mandar Menjoge

Paper ID: V5I2-1396

Paper Status: published

Published: March 25, 2019

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Case Study

Anomaly detection in code base

Any product when under development, goes through numerous changes before finally being released to the customer. While these changes are being done, it adds new features, modifies existing ones. How do we know if a product is in good shape to be released? Yes, we test the product, run the existing unit, functional, performance tests etc. What if the number of tests is in 10000s. How do we analyse each test result? Is there an automated way to detect the overall health of the product using the results of regression tests? Anomaly Detection using machine learning algorithms gives us a way to find out the overall health of the product. Using Anomaly Detection, we can quickly find out about the code base and if new changes should be allowed in before the existing code base is stabilized. It helps to determine, how far the existing code base is away from being released to the customer. It can help the code base to be almost always stable irrespective of the number of code changes that are merged into it.

Published by: Sudipto Nandan

Author: Sudipto Nandan

Paper ID: V5I2-1418

Paper Status: published

Published: March 25, 2019

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Research Paper

Bus tracking system using Android and web application

Transportation becomes very difficult in cities like Mumbai. The public transports, especially BUSES are developing around the globe. Such public transports reduce the usage of personal vehicles so reducing fuel consumption and mollifying traffic congestion. The problem with BUSES is that the commuters DO NOT know the exact temporal arrangement of the arrival of BUSES at their stops. This leads to looking ahead to BUSES for 30-35 minutes because the commuters are not aware of what time exactly the BUS is to arrive. The approximate arrival time of BUSES is known but there could also be a delay in arrival thanks to traffic. Seeing that people started avoiding public transports and started victimization non-public vehicles, many applications were developed; but these applications were unable to mitigate the problems. Some applications provided only the arrival time and point in time of BUSES at their supply and destination. Some of them provided time-tables, but even they weren't correct as they failed to contemplate the delay thanks to unpredictable factors like – traffic, harsh weather situation, etc. The timetables were not timely updated leading to waiting for BUSES.

Published by: Mayur Kharat, Manoj Mishra, Sanket Panchal, Pooja Walve, Suyog Kadge

Author: Mayur Kharat

Paper ID: V5I2-1434

Paper Status: published

Published: March 25, 2019

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