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Research Paper

Care: Cardiac attack risk estimation using Machine Learning

We are revolutionizing heart attack risk assessment with our ground-breaking initiative, "CARE: Cardiac Attack Risk Estimation Using Machine Learning," by utilizing machine learning models' predictive power. Our technology uses past data analysis to forecast the likelihood of a subsequent heart attack based on user-supplied details such as physical attributes, symptoms, and medical background. Our project's main goal is to reduce the burden on the healthcare system by providing users with remote access to screening facilities that can identify people at both low and high risk.With the goal of improving the precision of heart attack risk predictions, our ground-breaking platform, the "Heart Attack Risk Predictor," is a groundbreaking venture into the field of machine learning.

Published by: Patan Imran Khan, Kothamasu Surya Ratna, Meda Gopi Krishna, Nutalpati Ashok

Author: Patan Imran Khan

Paper ID: V9I5-1186

Paper Status: published

Published: October 28, 2023

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Research Paper

Analysis of the effectiveness of the digital enrollment and grading system

The Online Enrollment and Grading System of Bato Institute of Science and Technology is a comprehensive platform that helps manage all aspects of student enrollment and grading. It provides an efficient way to store and manage student data, grade reports, and enrollment records, ensuring that all relevant information is tracked from the beginning of a student's course until the end. The system uses a completely computerized process, reducing the chance of human error and maintaining accurate data. The system also includes a backup system that allows for the retrieval of important information in case of any system malfunctions, ensuring that student and organizational data is secure. There are two access modes: administrator and user. The administrator module is responsible for maintaining the system by creating user accounts, scheduling system updates, and making sure everything runs smoothly. The user module allows staff and students to access their grades and other reports. To evaluate the system's effectiveness, the researcher used Descriptive Developmental Research to gather feedback from both staff and students. Based on the results of the data, the researcher concluded that the Online Enrollment and Grading System is highly effective with a "very good" rating. However, there is always room for improvement in any system to prevent potential issues. Therefore, the researchers recommend continuous evaluation and improvement of the platform to maintain high standards of service and efficiency. In conclusion, the Online Enrollment and Grading System of Bato Institute of Science and Technology is an efficient and effective platform that meets the needs of both staff and students, providing a valuable solution for managing enrollment and grading processes.

Published by: Mary Jane Pagay Cierva, Rhoderick D. Malangsa

Author: Mary Jane Pagay Cierva

Paper ID: V9I5-1179

Paper Status: published

Published: October 28, 2023

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Research Paper

Effect of parental involvement on adolescents’ academic performance

The purpose of this study was to analyze parental involvement and the extent to which it has an effect on adolescents, primarily their academic performance and education. Findings indicated that the sample of 25 students felt that their parent(s) played an active role in their life and education and felt motivated by their involvement. The survey research method was used to collect data for the study.

Published by: Shreyasi Jindal

Author: Shreyasi Jindal

Paper ID: V9I5-1184

Paper Status: published

Published: October 26, 2023

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Research Paper

Quantum computing and its potential to revolutionize information processing

Quantum Computing has emerged as a promising field with the potential to revolutionize information processing. Unlike classical computers that rely on the binary system, quantum computers use qubits, which can exist in multiple states simultaneously, which allows them to solve problems more quickly and efficiently. Hence, this research paper explores the principles of quantum computing, its advantages, and how it has the potential to revolutionize information processing. Furthermore, it also considers the challenges that need to be resolved in order to make it a practical reality.

Published by: Shaurya Jindal

Author: Shaurya Jindal

Paper ID: V9I5-1182

Paper Status: published

Published: October 25, 2023

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Thesis

Flexible Pavement Evaluation by Falling Weight Deflectometer Test Using IIT-Pave and KGP Back Software.

It is now possible to regularly apply an analytical-empirical (or mechanistic) method of structural pavement evaluation because to the rapid development of technology and software over the past ten years. It is described how to determine the modulus of each structural layer in a pavement system. These moduli are determined non-destructively and in situ under conditions very similar to those caused by heavy traffic. The method is analyzed using empirical evidence, and some practical examples are given to illustrate its use. An analytical-empirical approach is recommended for the structural design of pavement systems. An "analytical method" or a "mechanistic method," as it has an important empirical component, is often referred to as such, and therefore the term "Analysisal-Empirical" is more appropriate. FWD test has been conducted at the designated sites, with KGP Back software being used to analyze the results (IRC 115-2014), and IIT-Pave software verifying the design.

Published by: Mohd. Irshad Iqbal Ansari, Sachin Bhardwaj

Author: Mohd. Irshad Iqbal Ansari

Paper ID: V9I5-1176

Paper Status: published

Published: October 23, 2023

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Research Paper

Optimizing Regulatory Compliance in Accounting: A Holistic Approach through Audits, Training, and Technology

With the constantly evolving regulatory landscape, organizations face high financial, legal, and reputational risks. To cope with these risks effectively, a holistic approach needs to be implemented, which includes periodic audits, targeted employee training, and cutting-edge regulatory technology. In this paper, we present a framework that employs machine learning techniques to predict regulatory violation rates. By using advanced algorithms and data analytics, our model not only identifies potential compliance breaches but also facilitates proactive decision-making and risk prevention. The use of machine learning enhances the accuracy and efficiency of compliance predictions, thereby enabling organizations to be a step ahead of regulatory challenges. We conduct a detailed analysis of real-world data from different sectors, employing a range of machine-learning algorithms to develop a predictive model. The results of the model demonstrate the efficacy of our approach in accurately forecasting regulatory violations. Additionally, we explore the effects of periodic audits, employee training programs, and regulatory technology to enhance overall compliance. This paper contributes valuable insights to the field of regulatory compliance and machine learning applications. The findings from the research provide a path for companies to proactively prevent financial losses, legal complications, and reputational damage. By embracing this holistic approach, organizations can create a culture of compliance, ensuring sustainable growth and resilience in the face of regulatory challenges. It also emphasizes the importance of continuous improvement, suggesting that a dynamic approach to compliance, informed by real-time data and machine learning insights, is pivotal in maintaining robust regulatory adherence and safeguarding organizational integrity.

Published by: Vaishnav Bhujbal, Dheeraj Nale

Author: Vaishnav Bhujbal

Paper ID: V9I5-1178

Paper Status: published

Published: October 18, 2023

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