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Research Paper

Waste Stratification using Deep Learning

Waste management is one of the most serious problems that practically every country faces. Its goal is to offer sanitary, efficient, and costeffective solid waste storage, collection, transportation, treatment, and disposal without harming the environment, land, or water system. Waste sorting errors can result in incorrect disposal and the loss of opportunity to recycle or reuse items. Monitoring by hand is inefficient and costly. As a result, deep learning and machine learning play a critical role in categorizing and sorting garbage and rubbish, effectively distinguishing between different types of waste. Many tasks, such as garbage collection and waste classification/ segregation, are part of waste management. One of the most important operations is garbage classification, which is carried out in a variety of ways based on the nature of the material.

Published by: Hanumanth K., S. Vidhayini, Pawan Sahu

Author: Hanumanth K.

Paper ID: V8I3-1341

Paper Status: published

Published: May 26, 2022

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Research Paper

Online Exam Portal

Online Examination Portal (OEP) is an electronic assessment framework wherever assessments are given on the online either through the net or utilizing the computer framework. The elemental aim of the web communication device is to properly assess the students via a processed device that saves the specified time and provides speedy and correct outcomes. Advances in innovation in recent and ages have upheld the viability of an online assessment and have rested the cycle of an online assessment throughout the long run. However, several institutes, particularly in higher institutional companies, have standardized written examination contrivance ways in growing countries. The web assessment framework improves the approach toward leading tests and compellingly making ready the outcomes. This work talks about the electronic online assessment framework and a safer instrument to steer AN assessment. AN OEP could be a viable and nice declare a mass coaching assessment.

Published by: Aditya P. Singh, Surendra Singh Chauhan

Author: Aditya P. Singh

Paper ID: V8I3-1334

Paper Status: published

Published: May 26, 2022

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Review Paper

Prediction of traffic congestion using swarm-based long short term memory

The vehicular Adhoc network is a new research area in the smart transport system that offers critical information to the network's cars. Road accidents affect about 150 thousand individuals, and VANET must improve safety. Traffic congestion forecasting is critical for reducing road accidents and enhancing traffic management for people. The dynamic behavior of the cars in the network, on the other hand, reduces the accuracy of deep learning models in predicting traffic congestion on roadways. This research introduces a new hybrid boosted long short-term memory ensemble and convolutional neural network (CNN) model to solve the congestion problem. to effectively handle the vehicle's dynamic behavior and estimate traffic congestion on routes The suggested BLSTME trains and improves the weak classifiers for the prediction of congestion, while the CNN collects characteristics from traffic photos. The suggested model is built with Tensor flow Python modules and evaluated in a real-world traffic situation with SUMO and OMNeT++. Extensive testing is done, and the model's performance is assessed using the performance criteria likely prediction accuracy, precision, and recall. As a consequence, the experimental result indicates 98 percent precision, 96 percent recall, and 94 percent accuracy. The findings show that the suggested model outperforms other current algorithms by 10% in terms of stability and performance when compared to deep learning methods.

Published by: B. Naveen Kumar, K. Sushma, Y. Bharath Reddy, B. Tejaswari, P. Babu Reddy

Author: B. Naveen Kumar

Paper ID: V8I3-1312

Paper Status: published

Published: May 25, 2022

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Research Paper

WeRescue: An initiative to prevent another epidemic

Bird flu, aphtha, BSE, and other major epidemics have happened on a regular basis since the 1980s. Some researchers also believe that the COVID-19 outbreaks we've seen in the last two years originated from bats. The World Organization for Animal Health has more than sixty diseases that affect livestock and more than ten diseases that harm poultry and fowl on its list of specific diseases. Many people became infected with bird flu and other diseases as a result. However, no method for identifying and preventing epidemics exist. So, increasing awareness about a disease that is spreading in a certain location can be accomplished by alerting health officials about the circumstance and cases that are happening nearby. But, how can this be managed to accomplish? Hence, in this overview of challenges, we have proposed a system that will prevent and minimize suspected outbreaks with the help of web technology and data analysis.

Published by: Rakhi Bharadwaj, Ranjana Burange, Aniruddha Bargaje, Deven Bhadane, Shubham Bodake

Author: Rakhi Bharadwaj

Paper ID: V8I3-1330

Paper Status: published

Published: May 25, 2022

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Research Paper

Effect of In Vitro Protein Digestibility on Bioavailable Protein in Cereals, Pseudo Cereals, Pulses and Super Seeds in both Uncooked and Cooked form

The nutritive value of protein in any food matrix depends on protein digestibility. Protein digestibility determines the bioavailability of the protein. Hence it is important that one should know protein digestibility to understand the nutritional value of the food matrix. The purpose was to study protein digestibility and understand the influence of protein digestibility on bioavailable protein. In cereals, protein digestibility is ranging from 59-to 90%, which is the highest and Sorghum is having lowest. 90% protein digestibility was obtained for pseudocereals and is comparable to wheat. Super seeds are rich in protein as well as in bioavailable protein as they exhibited superior digestibility of protein. In the case of pulses, all tested varieties have shown promising protein digestibility (91-84%) except for red kidney beans (75%). Also, a significant difference of p>0.01 was observed between protein content and bioavailable protein based on protein digestibility in both uncooked and cooked samples with few exceptions. These findings suggest that the protein digestibility of the food matrix is an important factor.

Published by: Shilpa S. Shetty, Dr. Kirti Sharma

Author: Shilpa S. Shetty

Paper ID: V8I3-1326

Paper Status: published

Published: May 25, 2022

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Research Paper

Gun mechanism for border security

The aim of this project is to develop and design a semi-automated sentry gun security system in order to detect, track and shoot the target for surveillance operations. This project is of a sentry gun that will be semi-automatic using an Arduino controller. It is a global issue that everyone wants to protect themselves and their beloved nation from various threats and dangers and keep their surroundings safe. This is a Bluetooth-based targeting gun system as the name suggests, it is based on a digitally controlled gun mechanism. This mechanism is built for good performance in the field with high sum accuracy, self-reloading gun, and ultimately used for soldier’s assistance. The gun mechanism used here is called a sentry gun because it has a gun mounted on a wall or stand and an operator can operate it from a control room via remote. It uses an IP camera to scan the area under surveillance and motion in that area is detected by a PIR sensor. It can definitely perform better in areas where human presence is prohibited. It will bring positive outcomes and reduce the death toll, if installed at every border and law enforcement agency, to stop undesirable & illegal intrusion.

Published by: Shweta Ganpat Rathod, Pranav Srinivas Macha, Shrutika Shripat Bhosale, Mayank Prashant Pawar, Jagdish Mandhare

Author: Shweta Ganpat Rathod

Paper ID: V8I3-1342

Paper Status: published

Published: May 25, 2022

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