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Prediction of the stock price using Machine Learning techniques

As people's interest in forecasting stock prices has been increased in recent years, research on stock price analysis using big data and artificial intelligence. In this paper, we performed sentimental analysis by this work by creating and analyzing a sentimental vocabulary using news items. We can get the positive index of news stories using the sentimental dictionary. We can get the positive index of news stories for each date using the emotive dictionary. We can get the positive index of news stories for each date using the emotive dictionary. We can confirm the utility and possibility of sentimental analysis in the stock market by examining the correlation value between the positive index value and the stock return value.

Published by: Apoorva Y.

Author: Apoorva Y.

Paper ID: V7I4-1686

Paper Status: published

Published: August 9, 2021

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Research Paper

Production, assay, and optimization of Chitinase enzyme produce by bacterial isolates from fish waste dumped soil

The effective chitinase enzyme reducing organisms were isolated from prawn shell dumped soil. The isolates were named as FS1 &FS2. The chitinase enzyme was produced only when the organisms was grown on medium containing the prawn shell powder. Optimizations of enzyme production (pH, temparture, substrate concentration) were carried out. In this study both FS1(46.7U/ml) FS2 (77.8U/ml) bacterial strain produced maximum chitinase at pH 7.0. maximum chitinase enzyme was obtained in 0.5% substrate concentration (140U/ml) in 96hrs by FS1 and in 0.8% in substrate concentration (93.3U/ml) in 72 hrs. This enzyme was highly used for antifungal activity.

Published by: K. Shameem Rani, S. Kulandaivel

Author: K. Shameem Rani

Paper ID: V7I4-1704

Paper Status: published

Published: August 9, 2021

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Research Paper

Social distancing monitoring system using computer vision and YOLOv3

In the fight against COVID-19, social separation has proven to be an extremely successful strategy for slowing the disease's transmission. People are being motivated to limit their interactions with one another to reduce the risk of the virus spreading through physical or close touch. In the past, AI/Deep Learning has shown promise in solving a variety of everyday problems. We shall see a full explanation of how we may utilize Python, Computer Vision, and Deep Learning to detect social distancing in public spaces and workplaces in this suggested system. By analyzing the real-time video streams from the camera, the social distancing detection tool can determine whether people have kept a safe distance from each other in public settings and the workplace. We can integrate this tool into their security video systems to check if people at work, in factories, and in stores are keeping a safe distance from one another.

Published by: Devanshi Gupta, Saumya Srivastava, Sonali P. Dash

Author: Devanshi Gupta

Paper ID: V7I4-1676

Paper Status: published

Published: August 9, 2021

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Research Paper

Fundamental Frequency estimation and analysis of speech signal

The fundamental frequency is a critical component in speech signal processing analysis. The fundamental frequency (fo) is the rate at which the vocal cords vibrate, and the fundamental frequency range for a person is 120 to 400 Hz. This basic frequency varies depending on the size and form of the vocal cords, and it might differ for males, females, and children. Different time domain and frequency domain pitch detection techniques are utilized. The time-domain methods include autocorrelation and AMDF (Average Magnitude Difference Function), whereas the frequency domain algorithm is Cepstrum. The fundamental frequency may be determined by pitch preprocessing and extraction.

Published by: Mahesh M. Kamble, Tejal S.Bandgar

Author: Mahesh M. Kamble

Paper ID: V7I4-1681

Paper Status: published

Published: August 9, 2021

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Research Paper

Study on heat transfer analysis of AC condenser by varying materials and refrigerants

An AC condenser is a vitally important part of an air conditioning system that performs much of the cooling function. The condenser causes latent heat rejection by the refrigerant. The design of the condenser can vary from system to system. One of the most commonly used designs is the finned tube design. The material of the tubes and the fins, become the decisive factor in the rate of heat rejection and ultimately in the performance of the condenser. In this work, an air-cooled finned tube condenser is designed for a vapor compression cycle-based air conditioning system. The modeling is done using Solidworks and the fluid flow and heat transfer analysis are done in Ansys. To evaluate the effects of different materials on the performance of the condenser, copper is used as the tube material while, Aluminium alloys, 1060, 6060, and 7050 are used for fins. Two different types of refrigerants, namely, R32 and R134a have been used for analysis. Thermal analysis is done to determine the temperature distribution and heat flux for different sets of materials and different refrigerants. By comparing the results obtained with different combinations, the optimal combination can be determined.

Published by: Vemula Nagarjuna, Vasili Srinivas

Author: Vemula Nagarjuna

Paper ID: V7I4-1720

Paper Status: published

Published: August 9, 2021

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Research Paper

Web-based system for face mask detection and face recognition

Even though people are now getting vaccinated, it might still take time for things to come back to normal. Until then, wearing masks and social distancing is the most effective preventive measure against the spread of COVID-19. This leads to the necessity of a system that will detect face masks in real-time video streams. Our solution detects whether a person is wearing a mask or not. If he/she is not wearing a mask then his/her photo would be captured and given as input to a face recognition system that will identify the person. The solution further provides the person’s information to the administrator and allows him to take any further action if needed. The above solution is implemented using neural networks to detect masks and the website is created using the Google Flutter framework. The ‘Web-Based System for Face Mask Detection and Face Recognition can be used to ensure the safety of people by implementing it in the large crowd gathering places like college campuses and offices.

Published by: Pranjal Rane, Ritvik Patil, Ojas Natu, Prahlad Pore, Pranay Shridhar

Author: Pranjal Rane

Paper ID: V7I4-1684

Paper Status: published

Published: August 9, 2021

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