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Review Paper

Unemployment Trends in India

The increase in the young population due to demographic dividends or the rise in young people seems to be one of the sources of future economic growth in India. Although with the increase in school and college enrolment rates, the proportion of youth in the labor force has been declining their high proportions in the labor force indicate that the problem of youth unemployment and underemployment would remain a serious policy issue for many more years to come in India. During the last two & half decades, from 1983 to 2007-2008, it analyses labor and workforce participation rate trends. Unemployment, joblessness, working poor, growth and employment elasticities, etc. the poor employability of the workforce would hamper the advantages due to demographic dividend if measures are not taken to improve the educational attainment and skill development of the youth. The present paper has focused on the causes of unemployment, various types of unemployment, and possible measures have been suggested.

Published by: Sushmitha M, Deepu.M, Shalini.K, Aswini.B, Rehana Banu

Author: Sushmitha M

Paper ID: V10I5-1272

Paper Status: published

Published: December 3, 2024

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Thesis

Enhanced Security in Signature Verification System Using Dynamic Sign Retrieval

Signature verification is the process of automatically and instantly determining whether a signature is genuine. Our system helps to determine whether the user’s new signature matches the original signature in the database. Every person has a unique signature used primarily for personal identification and verification of important documents or legal transactions. Mostly used to authenticate checks, draughts, certificates, approvals, letters, and other legal documents. Verifying its authenticity is essential because a signature is used in such critical activities. This type of verification is critical in preventing document forgery and falsification in a variety of financial, legal, and commercial settings. Traditionally, signatures were manually verified by comparing them to copies of genuine signatures. This simple method may not be sufficient as technology advances, bringing with it new techniques for forgery and falsification of signatures.

Published by: Dhanush.M, Tharneesh.S.R, Arun.R, Ramya.S

Author: Dhanush.M

Paper ID: V10I6-1353

Paper Status: published

Published: December 2, 2024

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Research Paper

ConnectCraft – Simplifying Network Choices

In our increasingly connected world, network quality is a fundamental concern for users. We propose an AI-powered solution to assist individuals in making informed decisions about their network service providers. This innovative application harnesses historical network data and real-time user feedback to predict and display potential network quality issues in specific geographic areas, by employing advanced Artificial Intelligence and Machine Learning algorithms, identifying trends and anomalies within this data, allowing it to forecast potential network issues accurately. Key features include predictive analytics, a visual representation of network quality problems on an interactive map, integration of real-time user feedback, provider comparisons based on historical data and reviews, personalized recommendations, and proactive alerts about potential network problems. This comprehensive solution empowers users to select the most suitable network provider for their specific needs, ultimately enhancing their network experiences and satisfaction in networks like JIO, Airtel, Idea, etc. It bridges the gap between consumers and network providers by providing transparency and data-driven insights into network quality, ensuring users can confidently make choices that align with their connectivity requirements.

Published by: Suyog Karpe, Atharva Ostwal, Yashshree Kirad, Atharva Pawar

Author: Suyog Karpe

Paper ID: V10I6-1341

Paper Status: published

Published: December 1, 2024

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Research Paper

Mentorship in Education: A Revolutionary Approach for Teachers

This research explores the transformative role of mentorship in education, focusing on five key elements: Emotional Intelligence (EQ), Ethical Passion, Active Listening, Adaptive Communication, and Values and Knowledge Education (VaKE). Through qualitative analysis of interviews with 50 teachers and case studies from three mentorship-driven schools, the study highlights the significant impact of these elements on student engagement, academic performance, and ethical behavior. The findings reveal that teachers with high EQ foster environments that increase student engagement by 85%, while those demonstrating Ethical Passion contribute to a 90% improvement in student ethical behavior. Active Listening and Adaptive Communication are shown to enhance comprehension and performance by 40%. The research underscores the importance of integrating mentorship into teacher training and recommends practical strategies for its institutionalization. These include mandatory mentorship training, continuous professional development, and curriculum integration of mentorship principles. The paper concludes that effective mentorship is essential for nurturing socially responsible and ethically aware students, capable of becoming future leaders.

Published by: Anu Kaushal

Author: Anu Kaushal

Paper ID: V10I6-1343

Paper Status: retracted

Submitted: November 30, 2024

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Research Paper

How Sports Affect One’s Mental Health

Sports offer significant mental health benefits, including improved self-esteem, stress relief, and resilience. There is a difference between the health benefits derived by amateurs versus professionals regular participation enhances physical health and mental well-being, boosting mood and confidence. Research also found a correlation between certain sports and nationalistic behavior. While sports are generally positive for mental health, they also come with challenges, including performance and public perception pressures. Additionally, sports can impact societal issues such as aggression and unrealistic beauty standards.

Published by: Alexa Gloria Galan

Author: Alexa Gloria Galan

Paper ID: V10I6-1294

Paper Status: published

Published: November 30, 2024

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Review Paper

Predictive Maintenance for Industrial Equipment using IIOT, AI and ML

In Industry 4.0, predictive maintenance is transforming the way efficiency and reliability are enhanced in manufacturing. This study introduces a system with machine learning approaches, with a strong emphasis on the Random Forest algorithm., and embedded technology to predict and prevent equipment failures. By utilizing real-time data from IoT sensors, our approach accurately assesses machine health and schedules maintenance before any issues arise. The use of the Random Forest model ensures high predictive accuracy by analyzing complex, nonlinear relationships in data, enabling a robust estimation of equipment conditions. This proactive strategy significantly reduces unexpected downtime, lowers maintenance costs, and prolongs machinery lifespan. We review recent advancements in Prognostics and health management (PHM), estimation of the remaining useful life (RUL) of equipment, and condition-based maintenance (CBM). Additionally, We explore challenges such as model interpretability, scalability, and data diversity within industrial environments.

Published by: Nandini Nalawade, Swati D. Jakkan, Shweta Mangnale, Pradnya Patil

Author: Nandini Nalawade

Paper ID: V10I6-1334

Paper Status: published

Published: November 29, 2024

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