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Full crowns overrated: save the tooth, salvage the tooth structure with aid of intraoral scanner- A case report

Dentistry has evolved in the recent era whether in the technology of digital impressions or conservative restoration of endodontically treated tooth. Intraoral scanners (IOS) are devices for capturing direct optical impressions in dentistry. Optical impressions reduce patient discomfort. IOS are time-efficient and simplify clinical procedures for the dentist, eliminating plaster models and allowing better communication with the dental technician and with patients. The images of the dentogingival tissues captured by imaging sensors are processed by the scanning software, which generates point clouds. These point clouds are then triangulated by the same software, creating a 3D surface model (mesh). The 3D surface models of the dentogingival tissues are the result of the optical impression and are the ‘virtual’ alternative to traditional plaster models. Porcelain veneers have long been a popular restorative option that have evolved into a well-accepted treatment that can be fabricated in various ways. With the availability of newer high-strength materials such as lithium disilicate and processing technologies like CAD/CAM and heat pressing, dental professionals are now able to produce highly esthetic, high-strength restorations that blend seamlessly with the natural dentition while also withstanding posterior occlusal forces. This has resulted in innovative methods of providing minimally invasive dentistry. So instead of full crowns lets try to save the tooth and salvage the tooth structure. The purpose of this article is to summarize the restorations that may compete the full crowns so that they are kept into the minds of dentists when a tooth is planned to receive cuspal coverage.

Published by: Dr. Pradnya V., Dr. Seema D. Pathak, Dr. Madhuri B. Wavdhane, Dr. Lipsita Priyadarshini

Author: Dr. Pradnya V.

Paper ID: V7I4-1254

Paper Status: published

Published: July 8, 2021

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Research Paper

Statistical analysis of the change in accuracy of tabla players with increasing mathematical abilities

Tabla has been the principal percussion instrument in Indian classical music for decades. In this paper, accuracy will be considered as the ability to stay on beat and within the taal, while also increasing the tempo. This paper analyses the difference in the accuracy of a player’s performance based on their mathematical ability. The performances were collected from 5 tabla players with varying mathematical expertise. The performances were analyzed and based on the accuracy, statistical tools were used to compute whether a higher mathematical aptitude will lead to more accuracy.

Published by: Malank Goel

Author: Malank Goel

Paper ID: V7I4-1223

Paper Status: published

Published: July 8, 2021

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Case Study

A Wrist drop case study

A 30-year-old man had experienced a humerus shaft fracture. Afterward, he underwent open reduction internal fixation surgery. wrist drop case study

Published by: Gourab Maji

Author: Gourab Maji

Paper ID: V7I4-1221

Paper Status: published

Published: July 8, 2021

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Research Paper

Mechanical ventilation for COVID- 19 patients

The main aim of the project is to design a mechanical ventilator and connect it remotely using the Internet of things. With the advancement in technology and IoT devices, a ventilator can be operated remotely. During the COVID-19 pandemic, it is difficult for the doctors to operate a patient on the ventilator from a nearby distance. In order to safeguard our medical staff, a ventilator is designed to operate it remotely. In this system, a ventilator and IoT device/laptop/smartphone are connected to each other over the internet and can take necessary decisions. It can also have communication between each other. It is built using NodeMCU an IoT device

Published by: A. Ramesh Naik, Justin Jose, Umar Fazil M. J., R. Chaithra, P. Kiran Kumar

Author: A. Ramesh Naik

Paper ID: V7I4-1251

Paper Status: published

Published: July 8, 2021

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Research Paper

Automated air pollution monitoring and forecasting system using Machine Learning

Various Air Quality Monitoring systems have been recently developed and installed in some of the cities such as Mumbai, Bangalore, Delhi, Hyderabad, etc. But the actual results do not satisfy enough. Several issues in the existing system were the number of gases detected were very few. There was a need for such a system that monitors more amounts of gases in less amount of time. Time was also an issue regarding the monitoring of the gases. Some gases consumed an enormous amount of time, so it became crucial to decrease them and make a more efficient system. The proposed system is automated air pollution monitoring and forecasting system using machine learning which uses an Arduino Mega, MQ gas sensors module for its development along with some other basic components like16x2LCD, Buzzer, Potentiometer. MQ135 gas sensor detects gases like NH3, NOx, alcohol, benzene, smoke, CO2, SO2, etc. which are the main reason for degrading air quality. Wi-Fi module is used to connect our system to the Cloud so that all the readings and the data can be transferred to the desired server for forecasting purposes. A trained model is expected to use the ARIMA algorithm for the best prediction purposes. This model is then applied to the upcoming data and forecasting is done. The various existing system was learned which are developed till date, it was found that the air quality numerical model such as WRF-Chem, community Multi-scale air quality model (CMAQ), CAMx, NAQPMS was used. The drawbacks in these models were found like, Source list was not updated in time for WRF-Chem, Detailed information about the source of the pollutants, and other variables are generally not known. After knowing all the facts from the study, this system is expected to use a Scikit machine learning tool for forecasting. The proposed model monitors the upcoming data in no time and if the value goes beyond the threshold value it activates the buzzer and the server is notified.

Published by: Vinayak Pragada, Romil Keniya, Abhijeet Chauhan, Beena Ballal

Author: Vinayak Pragada

Paper ID: V7I4-1199

Paper Status: published

Published: July 8, 2021

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Research Paper

Genotypic, phenotypic, and heritability studies in groundnut (Arachis hypogaea)

A total of 36 different genotypes maintained under Goldking Research Centre were evaluated in Kharif, 2019 for some variability parameters like GCV, PCV, Heritability, and Genetic advance as percent of the mean. The statistical analysis shows that the estimates of GCV and PCV along with heritability and genetic advance were found to be high for pod yield per plant, plant height number of aerial pegs per plant, biological yield per plant 100 pod weight, and harvest index which indicate that these quantitative characters are preponderantly governed by additive genes so there is a good scope of selection for further improvement in these traits and ultimately pod yield.

Published by: Mempal Dhanyan, S. I. Kapadia, K. S. Patel, P. K. Patel, Sunil Sapavadiya, K.N. Patel

Author: Mempal Dhanyan

Paper ID: V7I4-1242

Paper Status: published

Published: July 8, 2021

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