Daily Archives: July 27, 2025

Authors: Sharyu Chinchole

Abstract: As climate change continues to reshape coastlines and alter ecosystems, architecture stands at a crossroads—between crisis and creativity. This research explores the architectural response to rising sea levels through the lens of adaptive overwater villas. Traditionally associated with luxury, overwater villas are reimagined here as resilient, climate-responsive habitats that float, adapt, investigates and endure. The study floating systems, modular strategies, sustainable design tools, and precedents from across the globe, aiming to develop a contextual, feasible solution for future-ready living. The final proposition blends engineering and environmentalism into a design that is not only functional but poetic—an architecture that floats with the planet, not against it.

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Published by: vikaspatanker

Authors: Shreyash Akole, Mansi Rakhonde, Saish Desai

Abstract: The rapid growth of online news and digital media has significantly impacted financial markets, where even a single headline can influence investor behavior. With this increasing dependence on news, ensuring the authenticity and sentiment of financial information has become more important than ever. This research presents a dual-purpose system that combines stock market news sentiment analysis with fake news detection. Our model aims to solve this by using Natural Language Processing (NLP) techniques and Machine Learning (ML) algorithms to analyze financial news, detect fake information, and suggest investment actions such as Buy, Sell, or Hold. This system uses Bidirectional Encoder Representations from Transformers (BERT) and Long Short-Term Memory (LSTM) models for sentiment and authenticity analysis, ensuring reliability and accuracy. The framework empowers traders, investors, and institutions to make smarter, safer financial decisions by combining sentiment analysis and fake news detection into a single platform. Most systems only do either sentiment analysis or fake news detection. Our system does both in one place, making it more reliable. It reached 93% accuracy in sentiment analysis and 96% in fake news detection, helping users make better and safer financial decisions.

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Published by: vikaspatanker