Volume 14 | Issue 4 |

 Abstract

Early disease detection is crucial - more chances of success, less risk. Standard prediction methods require highly skilled personnel and complex tests, which may delay the process. In this study, we introduce a multiple disease prediction system using Machine Learning and providing rapid, precise, and convenient disease detection.XGBoost is chosen as the algorithm for multiple disease prediction due to high performance, scaling capability, and ability to work with various kinds of input data. The database is cleaned, features are selected, and normalization is applied to improve the quality of prediction. Training of XGBoost on symptom data helps the algorithm detect correlations between symptoms and diseases.Instead of making one suggestion, the output of the model consists of the three top-predicted diseases and their probability scores. A probability-based approach provides a more accurate representation of potential diseases.Alongside the prediction feature, our system includes a hospital recommendation service where the system recommends hospitals depending on predicted diseases. Thus, the user will be directed to appropriate facilities after finding out about his potential condition. A web-based system is designed to help users easily and quickly receive predictions and hospital suggestions. The symptom data is entered by the user, and the results are instantly received. According to experiments, XGBoost improves prediction compared to traditional methods. While not being a replacement for professional healthcare experts, our system serves as an intelligent assistant in disease prediction and risk detection.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Multiple Disease Prediction, XGBoost, Machine Learning, Symptom-Based Prediction, Probability Analysis, Hospital Recommendation, Healthcare Analytics, Web-Based System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Gyaan maarg ke pramukh santon mein se ek Kabir Das ji ke baare mein adhyayan

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gyaan maarg ke pramukh santon mein se ek Kabir Das ji ke baare mein adhyayan

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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

Ansys Maxwell, Buck Converter, Frequency Response, Harmonic Analysis, Series-Series Compensation, Wireless Power Transfer.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's digital era, e-commerce web applications have become an essential part of online business and customer interaction. This project presents Bazario, a responsive MERN stack based e-commerce web application developed for electronics products using MongoDB, Express.js, React.js, and Node.js, with Razorpay integration for secure online payments and checkout. The application is designed according to modern web development standards to provide a smooth, efficient, and professional online shopping experience for both customers and administrators. Bazario includes both user-side and admin-side functionalities. Users can browse electronic products, view detailed product information, manage cart items, add shipping addresses, and place orders through a secure payment system. On the administrative side, the application provides a dedicated admin panel where all product, order, user, and payment-related details can be managed efficiently. The admin dashboard also includes organized management features and data visualization for better monitoring and control of platform activities. The frontend is developed using React.js with Tailwind CSS and ShadCN UI components, while Redux is used for state management. JWT authentication is implemented to secure user sessions and protected routes. The backend is built using Node.js and Express.js, while MongoDB serves as the primary database. The complete system is deployed using Render, making the application accessible as a real-world cloud-hosted web platform. Overall, Bazario demonstrates the practical implementation of modern full stack development in building a secure, scalable, and user-friendly e-commerce solution.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-Commerce, MERN Stack, Razorpay, ShadCN, Web Application.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

(?? ???-???? ?????? ??????? ??????? ?? ??????-????? ?? ???????? ???? ??? ???? ?????? ???? ?? ???????, ?????????? ?? ??????? ???????? ??? ??????????? ?? ??????? ???? ??? ????????? ??????? ?? ???? ??????? ?????????, ??????? ???????????? ?? ????????? ??????-???? ?? ???????????? ?? ??? ??? ??? ??? ??? ??? ?????? ??????? ?? ????? ?????-?????? ?? ?????????? ???? ??? ?????? ?? ??????-???????, ????-???????, ????????? ?? ?????-??????? ?? ????? ?? ?????? ????? ???? ????? ?? ?? ?????? ?? ???????? ??????? ?? ??????????, ??????????? ?? ?????????? ????? ??? ??????? ??????-???????? ??? ?????????, ?????-????, ??????????????? ?? ?????-???????? ?? ???? ?????? ?? ??????????? ?? ?????????? ???????? ????? ????? ??? ???? ??? ??? ??? ??????? ?? ??????-????? ?? ???????, ???????? ?? ????????????? ???? ?????? ???? ??? ?? ???-???? ??? ???????? ??????, ?????????? ????????, ???????? ????? ?? ???????-??????? ?? ?????? ?? ???? ?????? ??????--(1) ????? ?????? ?? ????, (2) ??????-???????, (3) ??????-??????, (4) ?????????? ??? ???????-??????, ??? (5) ?????? ??????-???????? ?? ??????? ?? ?????--?? ????????????? ?????? ???? ??? ??? ?????? ????? ??? ?? ??????? ?? ??????-????? ?? ?? ?????-?????? ??????, ???????, ?????????? ???, ?? ????? ????? ?? ??????? ??? ?????? ?????? ???)

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

????? ????: ????? ??????, ??????-???????, ?????-??????, ???? ????, ??????-??????, ???????????, ?????? ??????-????????, ?????-??????, ???????????? ?????

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Recent developments in Artificial Intelligence have made it possible to produce deepfake photos and videos that look really real. These fake photos and videos cause some worries about people stealing our identities spreading false information violating our privacy and threatening our digital security. This study is, about a deepfake detection system that uses Vision Transformers to examine photos and videos and figure out if they are deepfakes or not. The model is different from convolutional neural networks. These traditional networks mainly focus on the details that we can see. The model uses techniques to look at the whole face. This helps the system find mistakes that people often make when they change media, like videos. The system uses a set of videos to learn and to test itself. There are 3,500 videos in this set. From these videos the system takes out 20,000 pictures. Splits them into two groups: real videos and fake videos. The system puts a number of pictures into each group. This is how the model learns to tell the difference between fake videos, like the facial patterns, in the videos. Experimental evaluation demonstrates that the proposed approach achieves high detection accuracy and stable performance, outperforming traditional CNN- based architectures. The results indicate that the framework is suitable for practical deployment in applications such as digital forensics, online content moderation, identity verification, and cybersecurity.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deepfake detection, Vision Transformer, deep learning, image and video analysis, facial manipulation, Cybersecurity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Voting is an essential part of democratic systems, but manual verification-based traditional voting procedures are laborious and susceptible to mistakes, fraud, and duplicate voting. Facial recognition has become a dependable and unobtrusive method of voter authentication with the development of biometric technologies. In order to prevent spoofing attacks, this paper presents a Smart Voting System Through Face Recognition that combines facial biometrics with liveness detection. A multi-level authentication method utilizing OTP with offline support is integrated to further improve security and dependability, producing a voting solution that is quicker, more secure, and useful for real-world implementation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart Voting System, Face Recognition, Biometric Authentication, Liveness Detection, Offline OTP.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The research paper delves into the interrelation between intellectual property rights and competition law. It is very interesting to identify the impact of both on one another .While IPR provides an exclusive right of the innovator to encourage new creation but competition law promote a healthy competition by penalizing the anti competitive activities .The main objective of this paper is to analyze the structure of their relationship by navigating the policies,provisions and the concept of the two. The structural analysis reveals a complex and often paradoxical relation between IPR and Competition law .To some extent these two looks like antithetical but so far their function is concerned they are complementary with each other.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

intellectual property rights, Competition law, structure ,paradoxical,complementary

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Homestay tourism, which began as an informal activity, has increasingly become a structured approach to rural and community development across various regions. This study analyses the financial, institutional, and governance aspects of homestay initiatives in West Bengal's Darjeeling and Kalimpong districts, placing them within wider national and global frameworks. It explores critical factors affecting the success and long-term viability of these projects, including credit availability, the use of digital financial tools, institutional backing, and the reach of policy initiatives. A key finding is the ongoing disconnect between policy goals and actual implementation, with obstacles like restricted access to financial services, poor infrastructure, and limited awareness of government schemes impeding progress. By focusing on governance mechanisms, institutional capacity-building, and local community involvement, the paper stresses the need for integrated efforts to support inclusive and sustainable growth in homestay tourism across the region.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Homestay tourism, financial inclusion, Institutional support, Sustainable development, Darjeeling and Kalimpong.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Anganwadi workers are part of a rural child care system in India. Anganwadi centres were established by the Government of India in 1975 under the Integrated Child Development Services (ICDS) programme to combat child hunger and malnutrition. The term "Anganwadi" in Hindi means "courtyard shelter."

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Anganwadi workers are part of a rural child care system in India

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Creative Commons Attribution 4.0 and The Open Definition