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Detection and identification of high-quality cereals

Agricultural product grading is helpful in assessing the quality of a product and classifying it into categories. Presently, the grade analysis procedures involve the manual analysis of grains which is highly subjective and is influenced by human factors and the working environment. Thus, determining the quality of grains is a big challenge. In this paper, we have proposed a system that determines the quality of grains using image processing techniques. A variety of approaches were utilized to automate the screening process through machine vision approaches. Initially, the grain samples run on the conveyor belt, and then random images of grains are captured by the camera. The image processing algorithm is applied to the grain samples through MATLAB. Quality analysis of rice grains is determined by morphological features of rice grains. Various standards and procedures are then used to determine grades for the sample under test. The process of grading helps farmers to get the value for their produce, particularly rice, depending upon the results of quality inspections. Deep learning and machine learning models involving image processing has been tried in this paper to observe the computational accuracy

Published by: Aiswarya K.

Author: Aiswarya K.

Paper ID: V7I3-1694

Paper Status: published

Published: June 7, 2021

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Review Paper

A Practical approach for Firmware Reverse Engineering

Embedded products have become widely used entities in the network of households and enterprises. The exponential increment in its use has resulted in a lapse in security measures taken while building these products, leaving them vulnerable to security attacks. An important feature is that embedded devices work on what is commonly known as Firmware, Firmware, a piece of software that helps the embedded devices to work on the shared task. Securing the firmware will be an important step in securing the embedded product setup. To secure the firmware one needs to understand how the firmware works. One way to do so is to reverse engineering. Through reverse engineering, one can attempt to understand the device architecture, functionality, and potential vulnerabilities present in the device. A better understanding of the firmware implementation also helps in adding features if needed. This project aims to apply several types of reverse engineering techniques to increase the efficiency of reverse-engineering the firmware and find the vulnerabilities in a firmware-based setup. Also, estimate the level of damage the identified vulnerabilities can cause through rigorous penetration testing.

Published by: Akash C. Koturwar, Dr. V. K. Pachghare, Sharad Hange

Author: Akash C. Koturwar

Paper ID: V7I3-1488

Paper Status: published

Published: June 7, 2021

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Research Paper

A study on consumer behaviour towards UPI (Unified Payment Interface) payment application based in Nilgiris District

It is imperative in the current period that digital payment is one important area where all the consumers and customers should be aware. The reasons are enormous like digital India and mechanization of e-documentation. Nowadays the physical payment mode becomes critical due to various reasons like time and safety. This enabled e-payment methods like internet banking and this again made simpler with android mobile phones. Keeping this concept the research work framed based on the consumer behavior towards UPI (Unified payments interface). The objective of this study is to know the Consumer awareness, Consumer Perception, and Consumer Satisfaction. The research design used in this study is descriptive research design, with the primary data collection method along with a structured questionnaire which constitutes 105 respndents and the statistical techniques used are chi-square, ANOVA analysis and Multiple Regression. On UPI payment application, the study was restricted only to the village Erumadu, Nilgiris district.

Published by: Dr. M. Bhuvaneswari, Dr. S. Kamalasaravanan, V. Kanimozhi

Author: Dr. M. Bhuvaneswari

Paper ID: V7I3-1686

Paper Status: published

Published: June 7, 2021

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Research Paper

Trickle Impregnation for insulating motors

This is a method of insulating the windings of a motor with epoxy resin. There are different processes involved- preheating the windings, dispensing of resin and curing the resin by heating. Here only the trickling process has been performed where the resin is dispensed on the winding coil with help of pneumatic motor at a designated flow rate.

Published by: Aditya Dhamale, Vaijayanti Deshpande, Suhas Chikale

Author: Aditya Dhamale

Paper ID: V7I3-1674

Paper Status: published

Published: June 7, 2021

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Research Paper

Google Loon: Balloon Powered Internet for All

The world has acknowledged the opportunities and possibilities the Internet offers. The Internet has been considered as a global community that is not only convenient, but genuinely helps to improve many different and important aspects of life including education, health, and economy. Sadly, only around 1/3rd of the global population at present has access to it. Providing cost-effective and efficient connectivity to rural areas is a very challenging task that has been given many different solution models over the years. One solution model that seems to offer a substantial business case is based on the Google Loon project, which provides many advantages. In this paper, we’ve tried to give an overview of the Loon project and also highlighted some key finds and observations.

Published by: Nisha Maria Shaji, Flavia Gonsalves

Author: Nisha Maria Shaji

Paper ID: V7I3-1708

Paper Status: published

Published: June 7, 2021

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Research Paper

Viral vs Bacterial Pneumonia Image Classification using Transfer Learning

The Purpose of this Project is to Develop a Project to Detect Covid-19 Viral and Bacterial Pneumonia using Transfer Learning form Medical images. Covid 19 2nd wave is spreading Rapidly and more deadly than the first wave we need effective and accurate models to Detect Covid-19 using AI and the challenges are quite big we don’t have that big datasets so instead of building model from scratch we used prebuild CNN Model and Transfer Learning for accurate prediction on test Dataset. This one is just Binary Classification model which uses images Bacterial and viral pneumonia images for the training

Published by: Shekhar Gaikwad, Yogita Shinde, Arti Vadavale, Nilam Gaikwad, Sunil S. Khatal

Author: Shekhar Gaikwad

Paper ID: V7I3-1704

Paper Status: published

Published: June 7, 2021

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