Daily Archives: March 31, 2026

Authors: Akshay Mahajan, Sahil Hashmi, Tannish Galhate, Anas Dange

Abstract: People's use of smartphones has increased rapidly in today's world, and as a result, a smartphone can be used effectively for personal security or various other protection purposes. On one hand, we get optimistic hope through a list of facts pertaining to woman empowerment, but on the other hand, we are chastised due to the crimes against women. Problems may come from anywhere and anytime, as women are also growing equally like men so for that purpose they have to travel alone at night where ever they go, they have to travel alone in public transport as well, and for that reason we need to understand and solve this problem of women so they also should not feel any fear regarding their safety. BESAFE aims at delivering a simple yet operational elucidation to this problem. BESAFE aims at developing a simple yet effective solution for empowering womanhood as well as installing a sense.

Published by: vikaspatanker

Authors: Jn Chandra Sekhar, P Nagasri, V Nithinreddy, Sk Yaseen, S Praveen Kumar

Abstract: The rapid growth of digital education has exposed critical limitations in existing e- learning platforms, which predominantly rely on static, pre-built content repositories requiring substantial manual creation and maintenance effort. This paper presents EduVoxus, an AI- powered adaptive e-learning platform that integrates OpenAI's GPT-4o-mini model for dynamic content generation with ten machine learning algorithms implemented entirely from scratch, without reliance on external ML libraries such as scikit-learn, scipy, or numpy. The platform offers four distinct AI-driven learning modes: MCQ quizzes with adaptive difficulty, voice-based practice with speech recognition and AI evaluation, theory question generation and an AI chatbot for instant doubt resolution. The ten from-scratch ML algorithms span multiple domains of educational data mining: Exponential Weighted Moving Average (EWMA) for adaptive difficulty adjustment, SM-2 SuperMemo algorithm for spaced repetition flashcard scheduling, TF-IDF with cosine similarity for content-based recommendations, Ordinary Least Squares linear regression for score trend prediction, K- Means with K-Means++ initialization for learner clustering, user-based collaborative filtering with Pearson correlation, Bayesian Knowledge Tracing (BKT) for mastery estimation, Ebbinghaus forgetting curve modeling for optimal review scheduling, first- order Markov chains for study sequence prediction, and Gaussian Naive Bayes for at-risk learner classification. The platform additionally features comprehensive gamification (points, badges, streaks, leaderboards), role-based access control with user approval workflows, course management with study material uploads, community discussion forums with AI-assisted answers, SM-2 scheduled flashcard decks, bookmarkable Q&A, AI-generated study notes and automatic certificate generation. Built with Flask 3.1.3, SQLAlchemy, Bootstrap 5, Chart.js and Web Speech API, with PostgreSQL support for production deployment on Render.com. Comparative analysis demonstrates that EduVoxus offers capabilities not found in any single existing platform including BYJU'S, Coursera, Udemy and Khan Academy.

Published by: vikaspatanker

Authors: ASR Reddy, S. Trisha, R. Venu Gopal, G. Sathvika, M. Venkatesh

 

Abstract: In this paper a new class of adjustable window function is proposed using a combination of Tangent hyperbolic function and Blackman-Harris 4-term window function. To derive the Tangent Hyperbolic Window function, the authors used the scaled independent variable Tangent hyperbolic functions shifted in opposite directions. The proposed window has the advantage of having 4-shape parameters that have lot of flexibility to vary the shape of the window for the desired spectral characteristics. The performance is compared with Hamming, Hanning, Kaiser and Gaussian windows in terms of the First Null Beam Width, Main Lobe Beam Width, Ripple ratio and Sidelobe roll-off ratio for the same window length with other windows presented for comparison. Simulation results show that Tanh window combined with Blackman-Harris window provides better sidelobe roll off characteristics and other spectral metrics that may be useful for some applications such as filter design and beamforming. Moreover, the paper presents the application of the proposed window in the field of array synthesis, and the comparison is performed with Hamming, Hanning, Kaiser and Gaussian windows. The results show that the array design with Tanh- Blackman-Harrish window provides better results in terms of the spectral metrics such as First Null Beam Width, Main Lobe Beam Width, Ripple ratio and Sidelobe roll-off ratio.

DOI: https://doi.org/10.5281/zenodo.19349175

 

Published by: vikaspatanker