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Fast pothole detection with the YOLO algorithm

Roads play a very important role in our daily life for the transit of goods and passengers. So, we have to be very careful about all the activities which may lead to the damage of roads to avoid major or minor road accidents. One of the main causes of this accident is due to the potholes created on the roads. These potholes are caused by the augmentation and dwindle of ground water after the water has plunged into the ground under the footway. To avoid such incidents a real-time-based road damage identification system is required. Our project proposal is how a real-time-based pothole detection system can be developed to avoid such accidents in the future.

Published by: Rupsha Debnath, Sayandeep Dutta, Soumajit Karmakar, Pratik Kumar Dewan, Ritasri Ghosh, Subhayu Das, Subarna Ghosh, Dr. Sangita Roy

Author: Rupsha Debnath

Paper ID: V8I4-1199

Paper Status: published

Published: July 26, 2022

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Research Paper

Study of corrosion resistance chemical for steel structural material

Research projects and field investigations have been conducted since 1970 on methods for protecting reinforced structures or steel structures from corrosion damage. This method includes various alternative techniques and also use of different materials and processes. Usually, corrosion problem is seen in coastal areas and structures near the coastal areas. Each method is briefly described and their results in the field are also reviewed. The different materials in corrosion protection, protection, prevention, and control are a subject of interest. The process of corrosion should always be prevented to avoiding the steel from getting of bad quality. Different chemicals and materials such as Rust Guard, Zinc Rich Primer, Steel Guard, Corro Guard, Cement Polymer, sulfuric acid, and sodium chloride have been used. Anticorrosive refers to steel protection from atmospheric reactions. By application of anti-corrosive chemicals on steel, the increase and decrease in are corrosion is determined

Published by: Rajendra Sukhdev Chavan, Vishnu Sudhakar Patil, Shalini Satyanarayan Bhandari, Sarvesh Santosh Deshmukh, Sourabh Ananta Survase, Shruti Shrinivas Ekkaldevi

Author: Rajendra Sukhdev Chavan

Paper ID: V8I4-1212

Paper Status: published

Published: July 26, 2022

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Research Paper

Promoting merchandise activity in rural India: An analysis

Merchandise activity has expanded the horizon and dimension of business universally. In India, villages are considered to be the spine and strength of our economy which contribute 25-30% of GDP. Unfortunately, due to lack of connectivity to town, deficient network, poor telecommunication, undeveloped transportation and inefficient planning of rural development has slumped rural markets in India. Nevertheless, rural India has the potential to contribute more in percentile by better connectivity and Livestock committee to promote indigenous products of 6,00,000 Indian villages. Globalisation in agricultural sector, exposure of unique handicrafts, textiles, arts, handlooms and treasure of diverse economic opportunity has brought faith among investors. This research paper attempts to analyse issues and address the challenges which have caused hindrance to promote Rural markets across India. The researcher aims to suggest parallel tech-savy solutions to approach global markets and boost economy. The aim of this paper is to give suggestions to promote native products grown and manufactured in villages throughout the world. Further, the role of Panchayat and financial distribution patterns is also discussed in this paper.

Published by: Jayesh P. K.

Author: Jayesh P. K.

Paper ID: V8I4-1206

Paper Status: published

Published: July 25, 2022

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Research Paper

Predicting stock market direction: hit songs’ sentiment analysis by using bert

Various machine learning algorithms have been used to predict stock market prices and perform analyses. Investor sentiment has been taken into account to predict the prices. However, there are different ways in which investor mood or sentiment can be influenced. Studies have confirmed that people’s mood or sentiment influences their choice of songs and likewise, songs influence people’s mood or sentiment and in fact their buying behavior. This paper proposes a prediction of whether the stock market will be bearish or bullish on the basis of daily hit songs listened to by people on a popular music streaming platform. Only a few types of research have been conducted that propose a correlation between popular songs’ sentiments and predicting the stock market. In this paper, the direction of the Dow Jones Industrial Average (DJIA) index is predicted from the lyrics of daily hit songs on Spotify listened to in the region of the United States of America. The model is trained on the dataset of lyrics of daily top 50 songs on Spotify from January 2017 to February 2022. The BERT (Bidirectional Encoder Representations from Transformers) model in Natural Language Processing (NLP) has been used to predict the direction of the DJIA index for the next day.

Published by: Sagar Bansal, Snigdha Patil

Author: Sagar Bansal

Paper ID: V8I4-1201

Paper Status: published

Published: July 25, 2022

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Research Paper

A study of factors that influence the level of impulse buying

This paper tries to investigate the fashion industry's irrational purchasing behavior. Comparisons between the internet and offline channels are made to see which is thought to encourage greater impulsive purchasing.

Published by: Ram Talreja

Author: Ram Talreja

Paper ID: V8I4-1197

Paper Status: published

Published: July 25, 2022

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Research Paper

Assess the burnout syndrome among staff nurses and nursing teachers working in selected settings of Aurangabad city.

Nursing is to bring those who are suffering from disease to a condition for nature to act for preserving health, prevent diseases and injury, and restore health and cure disease. A Comparative study survey study was conducted among 80 sample staff nurses (40) and nursing teachers (40) working in the various settings of Aurangabad, samples were selected by non-probability purposive sampling technique. Data was collected by using sociodemographic variables and Maslach burnout inventory score. The result of this study revealed for nurses has got findings for high burnout levels in section A (Burnout) and section B (depersonazation) as well as findings for nursing teachers was having high burnout levels in section C (personal achievement). There was no significant association found between demographic variables and burnout syndrome among staff nurses and nursing teachers. Thus the study concluded that burnout syndrome was high in nurses compared to nursing teachers. Keywords- Burnout syndrome, Maslach inventory, nurses, nursing teachers Burnout syndrome, Maslach inventory, nurses, nursing teachers

Published by: Varsha Bhagwan Kondke, Rameshwari Ashok Bidve, Shaikh Mohammed Hasan Mohammed Aijaj, Shivkanya Devidas Rawate

Author: Varsha Bhagwan Kondke

Paper ID: V8I4-1195

Paper Status: published

Published: July 22, 2022

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