Volume 14 | Issue 4 |

 Abstract

EduTrack is a web-based application designed to manage the institutional data. In current time, every college and institution collects large number of data and storing that data manually can be hurdle and time consuming. A simple solution we present is EduTrack which is a MERN based web-application which allows users to manage institutional data efficiently. The System is build using MERN stack to meet the current trends in industry. The system includes role based access control (RBAC) for their users to ensure secure access control. This system follows a modular database design where entities such as students, teachers, assignments, attendance, and marks are maintained in separate collections to ensure scalability and efficient data retrieval. It provides dedicated dashboard for each user role, enabling administrators to manage users, teachers to handle attendance, assignments, and marks, and students to view their academic records dynamically. EduTrack follows academic-year grouping, which allows teachers to assign tasks to an entire class without redundancy. The frontend is build using React with Tailwind CSS for a responsive and user-friendly interface. EduTrack practically demonstrates the implementation of full-stack development including RESTful APIs, role-based access control (RBAC), efficient data handling, authentication and authorization.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

MERN Stack, RBAC, JWT, RESTful APIs, MongoDB, cookie-parser, Bcrypt, Student Management System, Web Application

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Financial pressures have become a significant concern for young adults, influencing not only their lifestyle and career choices but also their mental well-being. As young people transition into adulthood, they often face challenges such as managing educational expenses, finding stable employment, and meeting rising living costs. These financial demands can lead to heightened stress, anxiety, and depression, especially in fast-paced urban environments where competition and living expenses are high. Urban cities, while offering diverse opportunities, also expose young adults to greater financial insecurity through factors like job instability, debt, and social comparison. This study aims to explore the relationship between financial pressures and mental health among young adults, with a focus on understanding how these challenges manifest in urban contexts like Bangalore. By examining the psychological and social impacts of financial stress, the research seeks to highlight the need for stronger financial literacy programs, accessible mental health support, and workplace or institutional policies that promote emotional and financial well-being among young adults.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Financial stress, mental health, young adults, anxiety, depression, Bangalore

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The labor market in India is undergoing a profound transformation due to technological advancements, globalization, and the rise of the gig economy. Traditional labor laws, designed for permanent employment, have struggled to accommodate the increasing prevalence of flexible, non-standard work arrangements. The gig economy, characterized by short-term, task-based, and digital platform-mediated work, offers both opportunities and challenges for workers and policymakers. This research paper explores the current landscape of labor law reforms in India, focusing on the integration of gig workers into the legal framework, social security provision, and the challenges of regulating platform-based employment. The paper also examines comparative global practices, identifies gaps in the existing legal system, and proposes reforms to ensure equitable labor protection, social security, and sustainable economic growth in the evolving labor market.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Labor Law Reforms; Gig Economy ; Platform Workers; Social Security; Non-Standard Employment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India's higher-education sector encompasses more than 43 million enrolled students, a demographic that collectively holds an extraordinary breadth of marketable skills, ranging from software development and graphic design to tutoring and digital content creation. Despite this talent density, no campus-specific digital infrastructure exists to channel peer-to-peer service exchange in a structured, transparent, and financially viable manner. This paper presents CampusKart, a web-based freelancing marketplace designed exclusively for the Indian collegiate context. The platform enables students to post skill-based tasks, discover relevant opportunities, and transact via an internal digital currency called Campus Coins, thereby eliminating the payment complexity associated with mainstream freelancing platforms. Built on a React and Vite front-end with Node.js, Express.js, and PostgreSQL forming the full-stack backbone, CampusKart implements secure JWT authentication, CRUD-based task management, a real-time wallet engine, and a timestamped activity tracker. Empirical testing across thirteen functional test cases confirms complete system reliability. Comparative analysis against Fiverr, Upwork, and Internshala validates the platform's unique value proposition in removing entry barriers for first-time student freelancers. The system establishes a replicable model for formalized campus-level digital economies across Indian higher-education institutions.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Campus freelancing, digital marketplace, gig economy, student platform, Campus Coins, React, Node.js, PostgreSQL, peer-to-peer task exchange, higher education technology.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Role Of Regional Political, Parties In India

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Role Of Regional Political, Parties In India

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid rise in municipal solid waste is placing enormous pressure on urban infrastructure, recycling systems, and the natural environment. Proper waste separation at the source remains one of the most effective strategies for reducing landfill burden and improving recyclability, but manual sorting is slow, inconsistent, and hazardous for workers. This paper describes an automated garbage classification system built on a deep learning backbone, designed to sort waste in real time. The system uses MobileNetV2 with transfer learning to classify waste into twelve distinct categories. Training was supported by aggressive data augmentation and a two-phase learning process that first trains a custom classification head, then fine-tunes the deeper feature extraction layers. On a dataset of 15,515 images, the system reached a validation accuracy of 96.97%, which held up well across precision, recall, F1-score, and confusion matrix evaluations. The results confirm that lightweight deep learning architectures can approach the performance of far heavier models while remaining deployable on edge hardware, smart waste bins, and IoT-connected systems.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Garbage Classification, Deep Learning, MobileNetV2, Transfer Learning, Image Classification, Convolutional Neural Networks (CNN)

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The importance of detecting plant diseases is paramount in improving crop production. Conventional methods for detecting plant diseases are, however, cumbersome and demand specialized knowledge to implement successfully. This research project is intended to create a new method for deep learning known as the Attention-Driven Vision Transformer Framework for Leaf Fungal Disease Detection. This approach incorporates a ViT (Vision Transformer) model augmented with attention mechanisms that facilitate effective extraction of global and local features of the images. During the training phase of the model, publicly available databases related to different plant diseases are used so that the system can detect diverse forms of fungal infections. Image processing operations include normalization, augmentation, and resizing, which enable the model to improve its generalization ability. Also, the use of the attention mechanism will allow the system to identify critical features of the leaf image. Results from tests performed on the proposed method suggest that it offers excellent performance in terms of accuracy and precision in identifying various fungal infections. Moreover, the system is robust to varying background illumination conditions. Therefore, it may be applied to automate fungal infection identification using both mobile and web applications. In general, this research shows how powerful transformers can be when applied in agriculture, providing an efficient and intelligent way of detecting diseases on plants at the early stages of their appearance.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Vision Transformer, Attention Mechanism, Deep Learning, Computer Vision, Precision Agriculture

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Romanticism, individualism, emotional depth, nationalism

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Food insecurity and food waste are two paradoxical crises that co-exist in every modern city. Tonnes of edible surplus food are discarded daily by restaurants, households, and institutions while millions of people remain chronically undernourished. This paper presents the Smart Food Donation and Surplus Redistribution System -- a PHP and MySQL web application that digitizes the full donation lifecycle and connects food donors directly with NGOs.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Food Donation, Surplus Redistribution, NGO Coordination, PHP, MySQL, Web Application, Role-Based Access Control, Delivery Tracking, Geo-Location, Leaflet.js, Food Waste Management, Chart.js

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Jal Jeevan Mission (JJM) is the flagship program of Government of India under the Ministry of Jal Shakti, aims to ensure Functional Household Tap Connections (FHTCs) to all rural households and provide safe, adequate, and regular drinking water. The present study is conducted in the village- Sonthi, District - Bilaspur, Chhattisgarh to analysis the impact of the Jal Jeevan Mission on the daily activities and socio-economic engagement of rural women in the village, and health outcomes of rural households in the village. The study's conclusions illustrate that although the program has greatly lessened the tedious task of collecting water, enhanced hygiene standards, and given more time for home and livelihood activities, a number of issues still exist. Problems including inconsistent supply, poor tank cleaning, low water pressure, and ongoing reliance on conventional sources draw attention to deficiencies in infrastructure upkeep and service provision. Despite these drawbacks, JJM has improved socio-economic activities, health knowledge, and community involvement, especially for women who have historically been responsible for water collecting.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key Word : Jal Jeevan Mission (JJM), Functional Household Tap Connections (FHTCs), Swachh Bharat Mission (SBM), Village Water and Sanitation Committees (VWSCs)

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Creative Commons Attribution 4.0 and The Open Definition