Volume 13 | Issue 4 |

 Abstract

An AI-powered personalized learning platform is developed using Streamlit, Gemini API, and Python in a VS Code environment. It allows students to take interactive quizzes and receive instant feedback with explanations for both correct and incorrect answers. The system identifies learning gaps and offers focused insights to help students improve specific skills. With a smooth and responsive interface, the platform adapts to individual performance, making learning more effective and engaging. By combining intelligent feedback with real- time progress analysis, it creates a tailored educational experience that encourages continuous learning and helps students achieve better academic results

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 Keywords

AI-powered learning, personalized quizzes, Streamlit, Gemini API, and Python within a VS Code environment, the system focuses on learning gap analysis and skill-based improvement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: Parkinson's disease is one of the main contributory factor that affect adult's quality of life. Aim: To evaluate the impact of the educational module on knowledge regarding Parkinson's disease and its prevention among adults. Method and Materials: A quantitative research approach with a pre-experimental one-group pre-test and post-test design was used for the study. The setting of the study was selected village in Indore. By using the non-probability purposive sampling technique 150 adults were selected. A self-structured questionnaire was used to assess the demographic data and knowledge regarding Parkinson's disease and its prevention among adults. The pretest knowledge was evaluated on day 1 and educational module was administered regarding Parkinson's disease and its prevention to the samples. On the 7th day after intervention post-test knowledge was evaluated. The data analysis was done using descriptive and inferential statistics. Result: In the pretest, 137 (91%) adults obtained poor grade, 8 (5%) participants obtained average grade, 5(4%) obtained good grade and none of the participants obtained excellent grade. In the posttest, none of the participant obtained poor grade, 5 (3%) participants obtained average grade, 33 (22%) participants obtained good grade and 112 (75%) participants obtained excellent grade. The intervention was very helpful in increasing the knowledge grade of the participants. A statistically significant association was found between marital status and any information about Parkinson's Disease and pretest knowledge grade (P>0.05), showing that the pretest knowledge grade is dependent on marital status and any information about Parkinson's Disease. Conclusion: The findings of the study showed information module was effective in increasing the knowledge of adults regarding Parkinson's disease and its prevention. Keywords: Knowledge, adults, Parkinson's disease, prevention.

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 Keywords

THE IMPACT OF EDUCATIONAL MODULE ON KNOWLEDGE REGARDING PARKINSON'S DISEASE AND ITS PREVENTION AMONG ADULTS

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 Abstract

The rapid increase in textual data in navigation tasks for devices like GPS or smart assistants creates challenges for managing and storing data in large-scale systems. Data deduplication, which reduces storage needs by eliminating duplicate data, offers a solution but raises security concerns. This paper introduces DEDUCT, a new method that combines cloud-side and client-side deduplication to achieve high data compression while protecting data privacy. Designed for devices with limited resources, such as IoT devices, DEDUCT includes lightweight preprocessing and safeguards against security risks like side-channel attacks. Testing on a navigation dataset shows that DEDUCT can compress data by up to 66%, significantly cutting storage costs while keeping data secure, making it an efficient choice for managing large-scale data systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Data deduplication, IoT storage optimization, Cloud security, Cryptographic access control.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the relationship between product quality and brand loyalty among Crocs consumers in Coimbatore. Using a structured questionnaire administered to 122 respondents, the study explores how factors such as durability, comfort, material quality, and design aesthetics influence consumer perceptions and loyalty. The findings reveal that durability and brand reputation are primary drivers of repeat purchases. The research underscores the role of consistent product quality in sustaining brand trust and offers actionable strategies for enhancing consumer satisfaction.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Product Quality Brand Loyalty Durability Comfort Material Quality Design Aesthetics Brand Reputation Customer Satisfaction Consumer Behavior Repurchase Intention Footwear Industry Crocs Consumers Customer Trust Marketing Strategies User Experience

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Creative Commons Attribution 4.0 and The Open Definition

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One of the critical multimedia challenges in today's digital landscape is the rapid and effective creation of video content enriched with relevant metadata. This metadata is essential for improving discoverability, organization, and engagement, but the process of manually generating it is both time-consuming and inconsistent. To address this, we propose a Video Metadata Automation System that utilizes recent advancements in artificial intelligence--particularly large language models (LLMs)--to automatically generate key video metadata, including titles, descriptions, captions, and thumbnails. Our system employs an end-to-end automated framework that integrates techniques such as audio extraction, speech-to-text transcription, and video analysis. Using APIs for connection to high-performing LLMs, the extracted transcripts are used to create metadata in a structured and SEO-friendly format. The most suitable LLMs are evaluated and selected for optimal performance in this context. Furthermore, the system features integration with image generation models such as Stability AI's Stable Diffusion to generate thumbnails based on the video's context. This paper explores the effective utilization of open-source tools and state-of-the-art AI technologies, presenting a unified and modular solution that simplifies the video content creation pipeline. By automating the metadata generation process, our system significantly reduces the workload for creators, enhances video accessibility, and enables faster content publication with minimal manual intervention.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Metadata Generation, Large Language Models (LLMs), Speech-to-Text, Audio Extraction.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In modern urban mobility systems, real-time and easily accessible information is crucial for enhancing public transportation efficiency. "MeetRoute" presents a user-centric platform that enables commuters to instantly access comprehensive bus route information and live passenger occupancy through QR code scanning at bus stops. Upon scanning, users are redirected to a mobile-optimized website that displays a list of available bus routes, providing vital details such as bus number, starting and ending points, number of stops, seating capacity, and real-time crowd data captured via onboard cameras. This solution addresses common challenges like uncertainty in travel, overcrowding, and lack of real-time updates. By integrating computer vision technologies with smart web systems, MeetRoute bridges the information gap between commuters and transportation services. This paper discusses the platform's design architecture, implementation methodology, challenges, results, and future directions aimed at creating a sustainable, efficient, and commuter-friendly transportation ecosystem. The research highlights how MeetRoute improves commuter convenience, promotes the adoption of public transportation, and contributes to reduced traffic congestion and environmental impact.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Public Transport, QR Code Navigation, Real-Time Passenger Monitoring, MeetRoute.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Aadivasi Mahilao Ki Panchayati Raj Me Bhagidari Per Ek Samaji Adhayan

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Creative Commons Attribution 4.0 and The Open Definition

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Aadivasi Mahilao Ki Panchayati Raj Me Bhagidari Per Ek Samaji Adhayan

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract The Upper Beas Basin of Kullu valley has experienced a rapid growth in number of visitors in the past few decades, i.e., from a mere 10,000 visitors in the 1960's (Singh, T.V 1989) to more than 28 lakh in2022. (HPTDC 2022). This has resulted in an uncontrolled and unplanned growth of tourism related infrastructure, crowding, congestion and pollution. All this is having a deep impact on the regions environment, economy and society, raising questions of long term sustainability of tourism in the region. As such, the paper tries to assess the impacts of tourism especially on the social and cultural aspect of the region. Socio-Cultural impact assessment is crucial for tourism sustainability because it helps identify and mitigate potential negative effects on local communities, cultures and traditions. By understanding these impacts tourism development can be managed in a way that benefits both visitors and the host communities, ensuring long-term sustainability and harmony between tourism and local cultures. The study clearly demonstrates positive and negative impacts on the socio-cultural aspects of the Upper Beas Basin. Among the negative impacts one sees changes in the occupation, social values, family structure etc. There is a weakening of community bonds, degeneration of social value systems, commercialization of culture, increase in crime and moral laxity. The positive impacts on the other hand were preservation and revival of certain culture and traditions, spread of new ideas (cultural exchange), increasing awareness of the significance of education and a desire to improve their living standards.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Upper Beas Basin (UBB), Tourism, Sustainable tourism, Mountain, Socio-cultural impacts,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

To improve the seamless smart grid integration of renewable energy sources (RES), this research explores the concept of resilient control. The advantages of RES for the economy and environment have made their integration into power grids a top priority, but RES's intermittent nature presents significant challenges to grid flexibility, stability, and reliability. To reduce the uncertainties and disturbances related to RES, the paper examines efficient applications of sophisticated control strategies, such as adaptive control, robust control, and model predictive control. It also examines the importance of communication networks, demand-side management, and cyber-physical security in enhancing the resilience and functionality of smart grids. The challenges of incorporating renewable energy, including energy storage devices, grid interoperability, and legislative barriers, are also covered in detail. This paper provides recommendations for building resilient smart grids that can accommodate large rates of RES penetration while preserving stability and operational security. Initiatives to fill existing research gaps and policy recommendations are also made, emphasizing the value of backup plans and standardized procedures for grid dependability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart Grids, Renewable Energy Sources (RES), Resilient Control, Grid Stability, Grid Reliability

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Mineral exploration in India continues to face the dual challenge of balancing economic urgency with the complexity of its vast and geologically diverse terrain. This study introduces a spatial predictive modeling framework using Geographic Information Systems (GIS) to identify high-potential mineral prospecting zones across selected regions in India. By integrating multi-layered spatial datasets--ranging from lithological, structural, and topographical variables to satellite-derived remote sensing indices--and employing a Random Forest classification model, the research develops a high-resolution mineral potential map calibrated against known mineral occurrences. The results reveal statistically significant spatial patterns, highlighting the predictive value of factors such as proximity to fault lines, lithological transitions, and elevation gradients. This approach not only reduces exploratory costs and environmental disruption but also provides a replicable model for mineral intelligence in resource-rich but data-fragmented environments. Ultimately, the study supports a paradigm shift toward data-driven, precision exploration strategies within India's mineral governance landscape.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Geographic Information Systems (GIS); Mineral Prospectivity Mapping; Spatial Predictive Modeling; Remote Sensing; Random Forest Classification; India; Mineral Exploration; Geospatial Data Analysis; Lithology; Fault Proximity

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Creative Commons Attribution 4.0 and The Open Definition