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Research Paper

A Hyperparameter Tuning Optimized Convolutional Neural Network for Classification of Fruit Type and Quality through Computer Vision

Food poisoning is a problem affecting people on a global scale, killing 420,000 people a year as of 2022. This problem is exacerbated by the distribution of already-rotten food from farms to vendors and can be mitigated by preventing infected food from ever leaving farms in the first place, or by identifying rotten foods before vendors sell them. Thus, this study summarizes the building of a hyperparameter-optimized deep learning model that uses a Convolutional Neural Network (CNN) to identify the kind of fruit and its quality by looking at an image of a fruit, a simple process. This automation of food classification and safety allows lower-income farmers and vendors to escape the time and monetary cost of manually verifying whether or not each fruit they distribute/sell is safe to eat.

Published by: Aarav Kodathala Reddy

Author: Aarav Kodathala Reddy

Paper ID: V10I6-1395

Paper Status: published

Published: December 10, 2024

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Research Paper

Sustainable Solutions for the Disposal of End-of-Life Solar Panels

Solar PV recycling methods currently in use are elaborated in this paper. This paper explains in detail the recycling methods of crystalline, CdTe, and CIGS solar panels which are being currently used in the industries. As there are a lot of recycling methods this paper finds you the best recycling method with a high recovery rate of recycled products up to 99%. The use of plant-based materials to create solar PV modules is also suggested as one of the main innovations needed to fight used solar PV disposal. Because of this, there is still a great deal of effort to be made to develop the subject of solar PV recycling by material scientists and other related professionals.

Published by: Aishwarya S, Karthikeyan S, Sathiyamurthi P, Vijayanand P S

Author: Aishwarya S

Paper ID: V10I6-1393

Paper Status: published

Published: December 10, 2024

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Research Paper

Marital Rape in India: The Intersection of Law, Society, and Structural Inequality

Rape is a serious crime which violates the body and spirit of the victim. Marital rape remains an issue in India where the legal framework fails to protect women from the physical, emotional, and psychological trauma attempted by the husband. After the Nirbhaya Case, there was a lot of media attention on the topic of rape which further led to the implementation of the Criminal Law (Amendment) Act, of 2013. But marital rape is still a problem as the law states specific circumstances in which the husband can be held accountable for committing the crime of raping his wife without consent. This research paper aims to explore and elaborate on the legal framework in place to protect women from the horrific crime of spousal rape. For example how the constitution has laws that contradict themself, how the sacred bond of marriage and the sanctity of the family is more important than a woman facing abuse from her husband, how the law undermines marital rape reports and lets the perpetrator (husband) walk off free, how rape affects a women's body and mind. This paper will answer all these questions and also aim to unfold all the harsh realities that many women in India face every day in the name of marital rape.

Published by: Seerat Khanna

Author: Seerat Khanna

Paper ID: V10I6-1359

Paper Status: published

Published: December 9, 2024

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Research Paper

Assessing the Knowledge and Skills Regarding Partograph Among Nursing Students

The partograph is a critical tool for monitoring labor progress and ensuring maternal and fetal well-being. However, nursing students often face challenges in effectively understanding and utilizing it, influencing labor management outcomes. This cross-sectional descriptive study assessed the knowledge and skill levels regarding partograph use among 125 final-year DGNM and BSc Nursing students in a Chennai college. Data collection involved a 35-item questionnaire for knowledge and case-based scenarios for skill evaluation. Results showed that 66% of students had inadequate knowledge, 33% had moderately adequate knowledge, and only 1% demonstrated sufficient knowledge. Similarly, 67% had inadequate skills, 23% had moderately adequate skills, and 10% demonstrated adequate skills. Significant associations were found between knowledge and skills with demographic variables such as age and educational qualifications (p<0.05), while no significant associations were observed for other variables like religion and participation in in-service education programs. The findings highlight the need for simulation-based training and increased clinical exposure to enhance nursing students' competency in partograph use.

Published by: Blessy Little Christy P

Author: Blessy Little Christy P

Paper ID: V10I6-1386

Paper Status: published

Published: December 9, 2024

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Review Paper

Literature Review on Exoplanets and Detection Techniques

The discovery of exoplanets since 1995 has revolutionized our understanding of planetary systems. This paper reviews major detection techniques such as radial velocity, transit photometry, direct imaging, gravitational microlensing, astrometry, and pulsar timing, focusing on their strengths, limitations, and findings. It also highlights significant missions like Kepler, TESS, Gaia, and future contributions of the JWST. A literature synthesis reveals the critical role of interdisciplinary approaches and advancing technology in the search for habitable exoplanets and extraterrestrial life.

Published by: Anusha S

Author: Anusha S

Paper ID: V10I6-1385

Paper Status: published

Published: December 8, 2024

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Review Paper

Artificial Intelligence in Finance: Transforming Decision-Making, Risk Management, and Economic Dynamics

Artificial intelligence (AI) is revolutionizing the finance sector by enhancing decision-making, risk management, and operational efficiency. This paper explores AI's role in finance, its evolution, applications, and economic impacts, highlighting key techniques such as machine learning and deep learning. AI’s ability to process large datasets and detect patterns offers financial institutions opportunities to optimize performance and mitigate risks. However, AI also presents challenges such as labor displacement and regulatory concerns. This study examines AI's techniques, benefits, and implications while considering the macro and microeconomic effects of AI. The paper also emphasizes the need for adaptive public policies to promote equitable growth

Published by: Sindhushree. KR, Chithra. R, Kavya. L, Mangala. M, Pooja. M

Author: Sindhushree. KR

Paper ID: V10I5-1280

Paper Status: published

Published: December 7, 2024

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