Volume 13 | Issue 4 |

 Abstract

In a nation striving toward economic empowerment, this study uncovers the invisible barriers holding millions back: gaps in financial literacy. Through a behavioral finance lens, we investigate the financial literacy levels of 60 Indian adults (aged 20-60) and their impact on investment diversification practices. Employing a structured questionnaire--anchored in the OECD's Financial Literacy Framework--and a 5-point Likert scale, participants were categorized into high-literacy (score >=35/50) and low-literacy groups. Using an independent samples t-test, results revealed a stark divide: high-literacy individuals (M = 38.2, SD = 3.1) demonstrated significantly better diversification habits than their low-literacy counterparts (M = 28.7, SD = 4.5), with a large effect size (d = 0.89) and statistical significance (p = 0.001). Age emerged as a critical factor, with only 28% of adults over 40 scoring high literacy compared to 43% of those aged 25-35. Gender gaps, however, narrowed in urban settings (52% male vs. 48% female), signaling progress in women's financial inclusion. These findings underscore the urgent need for context-specific financial education--programs tailored to rural communities, older adults, and non-English speakers. By bridging literacy gaps, India can transform financial knowledge from a privilege into a tool for collective resilience, ensuring no one is left behind in its march toward inclusive growth.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Financial literacy, investment diversification, behavioral finance, t-test, India.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study investigates the effect of transparent pay policies on workforce productivity, focusing on employee motivation, satisfaction, and teamwork. It finds that clear compensation structures boost trust and performance, while unclear pay policies lead to dissatisfaction and high turnover. Data from 120 employees in Coimbatore were analyzed using statistical tools. The findings suggest that transparent pay enhances morale and productivity. The study offers recommendations for businesses to improve compensation practices. Limitations include the regional scope and short time frame.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Transparent Pay Policies, Workforce Productivity, Employee Motivation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research addresses the challenge of inefficient and often insecure information retrieval in college settings by proposing an intelligent conversational interface. We developed a chatbot system that allows users including Heads of Departments, Professors, and Students to query a MongoDB database containing institutional data using natural language. The system employs Retrieval-Augmented Generation (RAG) orchestrated by Langchain, using FAISS vector stores and the Gemini 1.5 Flash as the LLM via Google AI API to provide contextually relevant and factually grounded answers, minimizing LLM hallucinations. A key contribution is the tight integration of Role-Based Access Control (RBAC), ensuring data access aligns strictly with user roles through index and metadata filtering. Furthermore, post-retrieval filtering is implemented to enhance the LLM's accuracy when handling specific tasks like counting. Built with Streamlit, the chatbot offers a user-friendly platform for secure, role-appropriate, and efficient access to college information, streamlining data interaction for all user groups.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords - Retrieval Augmented Generation (RAG), Langchain, FAISS, Gemini 1.5 Flash, LLM, Google AI API, Role Based Access Control (RBAC), Streamlit

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The objective of the present study is to concentrate on Sahgal's major issues throughout her novels which is the suffering, anguish, pain, and identity faced by the women in the male-dominated society. I have done my best to convey that Nayantara Sahgal's journey as a female writer begins with her quest for selfhood and culminates in her achievement of it. She detests cruelty and pain because of humanitarianism. She supports Indian women's rights and emancipation and is very sensitive to their plight. Sahgal delves deeply into female psyche in almost of her novels. She has the ability to examine them with empathy and tenderness. As a female novelist, her primary goal is to advocate women's empowerment. Sahgal is incredibly worried about her women's personal fear, the loneliness and alienation, and by the fallout of marriages. Sahgal's female characters suffer because they are always fighting to maintain their uniqueness and individuality at whatever costs. She plays married women who endure a lot of hardships, and when their marriages become oppressive, they ultimately decide to file for divorce. She depicts her women's life filled with suffocation, pain, anxiety and suffering. To get free from this suffocating atmosphere the women choose only divorce.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Identity, Agony, Pain, Suffering, and Patriarchal society

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Heart disease is one of the leading causes of death in the globe. Non-fatal myocardial infractions or sudden deaths without any warning indications occur in around 25% of cardiac patients. Thus, silent myocardial infractions (SMI) are another name for silent heart attacks, which might be completely asymptomatic or have symptoms so mild that patients are unable to identify them. Nevertheless, the symptoms might not always be detectable by the ECG. On the other hand, sobbing, chest discomfort, and chilly chills are symptoms of a conventional heart attack. Despite their subtle look, they are equally harmful to the heart and provide significant long-term health risks. A survey-based study was conducted among 1,000 patients with diagnosed heart disease. Patients were divided into four groups based on their symptoms Group 1 (asymptomatic), Group 2 (mild symptoms), Group 3 (moderate symptoms), and Group 4 (severe symptoms). Electrocardiogram (ECG) and echocardiogram tests were performed to detect silent heart attacks. The prevalence of asymptomatic silent heart attacks was significantly higher in Group 1 (23.1%) compared to Group 2 (12.5%), Group 3 (8.3%), and Group 4 (4.2%). Multivariate analysis revealed that age, diabetes, and hypertension were significant predictors of asymptomatic silent heart attacks.We believed that the fundamental processes of SMI involved a reduction or obstruction in the heart's blood flow, up on forming plaques. The following patient groups are subjected here are like Hypertension and hyper lipidaemia, diabetic, elderly,women, and smoking, Increased awareness regularly screening and preventive measures are essential to mitigate the silent threat by these unrecognised heart attacks. This study highlights the importance of regular cardiac screening for patients with heart disease, regardless of symptoms. Asymptomatic silent heart attacks are more common than expected, and early detection can prevent further cardiac damage.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SMI - Silent Myocardial Infraction, HTN - Hypertension, SOB - shortness of breath, CVD - cardiovascular diseases, DM- Diabetes mellitus, CAD - coronary artery disease.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sleep disorders can significantly impact an individual's overall health and well -being, making early detection crucial for effective intervention. This project presents a machine learning-based approach to detecting and classifying sleep disorders using health-related data. The dataset used included key features such as sleep duration, quality of sleep, physical activity levels, stress levels, body mass index (BMI), blood pressure, heart rate, and daily step count. To ensure accurate classification, multiple preprocessing steps are applied, including categorical encoding, feature scaling, and handling missing or duplicate values. The system utilizes a Random Forest classifier, trained on preprocessed data to predict potential sleep disorders. The model is evaluated using accuracy metrics and a classification report to ensure its reliability. The functionality is made accessible through a Flask-based web application, where users can input their health parameters and receive instant predictions regarding their sleep health. The system is designed to assist individuals in understanding their sleep patterns and taking necessary steps toward improved well-being. By leveraging machine learning, this project provides an efficient and user-friendly tool for sleep disorder prediction and awareness.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sleep Disorders, Machine Learning, Random Forest Classifier, Flask Web Application

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sustainable husbandry is vital due to environmental degeneration, resource reduction, and food movie goods. The devilish use of synthetic mulches contributes to these cases, causing plastic affliction. This project aims to develop biodegradable mulch mats applying natural resources like coconut coir, banana fibers, and neem extract. These biodegradable mats extend an volition to plastic products, furnishing moisture retention, weed control, and perfected soil health. The project tried these mats against usual plastic mulches under real agricultural conditions for moisture retention, weed control, and common or garden or theater or theater crop gain improvement. goods showed off that the biodegradable coconut coir mulch mat held bettered soil moisture than the plastic mulch, and the neem extract was salutary in chording pests and suppressing arising weeds. The mats had a conducive rate of degeneration in soil, making them useful for seasonal husbandry without compromising soil fertility. Crop plant were elevated, especially for thirsty crops. Biodegradable mulches made from coconut coir, banana fiber, and neem extracts have a degeneration rate that is farther permissible than plastic, offering a doable means of minimizing plastic mulching. These mats also support loosen soil's medicinal groupings, retain moisture, and rebut pests. perfecting environmental sustainability in husbandry could enhance productivity and palliate husbandry's negative environmental jolt.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sustainable Agriculture, biodegradable mulch, coconut coir,banana fiber, neem extracts, needle punch.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Regression, Decision Tree, Random Forest Regressor, XGBoost Regressor.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents an AI-powered web application for automating petition analysis and grievance redressal. The system allows users to securely submit petitions, automatically classifies them into appropriate departments, and prioritizes urgent or critical cases. It identifies repetitive grievances to avoid duplication, supports better resource allocation, and sends timely reminders to officials to ensure prompt resolution. To enhance transparency and user trust, the system provides real-time petition tracking and regular status updates to petitioners. It uses sentiment analysis to determine the emotional intensity of each petition, aiding in urgency detection. Additionally, the application is built on a scalable cloud-based infrastructure to ensure reliability and data security. By integrating intelligent automation, sentiment-based prioritization, and real-time communication, the proposed solution streamlines grievance handling, improves administrative efficiency, and fosters accountability in governance.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI-powered petition analysis, grievance redressal system, automated petition tracking, governance transparency.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study explores the socio-economic status of beggars and causes of begging at the Magh Mela in Prayagraj, Uttar Pradesh. It focuses on the disparities among beggars and also on factors influencing beggary. The primary data was collected through interviews schedule of 100 respondents. In this study, the researcher has found variations in socio-economic conditions among beggars and identified key reasons for their beggars. The study shows that Scheduled Tribes (ST) and younger people tend to earn less money compare to other groups. The key causes of begging are insufficient pay, health issues, and family pressure in this study area. The Chi-square tests confirm significant variations in per day income among different community and age categories, which highlight the deep-rooted socio-economic inequalities. The study states that improving wages, enhancing healthcare access and implementing appropriate social support programs will be crucial for addressing the root causes of begging. A comprehensive and integrated strategy of economic, health, and social factors is essential for improving the well-being of beggars and reducing begging in the study area. The research states that it is need to take specific actions to tackle these complex problems that are faced by beggars.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Begging, Magh Mela, per day income, Socio-economic

  License

Creative Commons Attribution 4.0 and The Open Definition