Daily Archives: November 11, 2025

Authors: M. Kumaraguru, B. Bhuvaneswari

Abstract: Cloud gaming is a rapidly evolving domain that provides seamless access to immersive, high-quality gaming experiences. Despite its advantages, reducing latency remains a significant hurdle, especially under varying network conditions. This study introduces an innovative solution that leverages artificial intelligence (AI) to tackle these issues. The proposed system integrates AI techniques to enhance multiple facets of cloud gaming, such as video compression, traffic routing, resource distribution, and prediction of user interactions. Machine learning algorithms continuously fine-tune streaming configurations in response to live network metrics and individual user preferences, thereby lowering latency and boosting visual fidelity. Furthermore, reinforcement learning is employed to optimize backend resource management, improving both scalability and operational efficiency. The use of AI-powered predictive analytics facilitates customized gameplay by forecasting user behavior and dynamically adjusting game mechanics. Through behavioral analysis and preference modeling, the system personalizes content delivery, difficulty settings, and in-game support.

Published by: vikaspatanker

Authors: Mrs. Khatal Kavita, Miss Akanksha Vishwasrao, Miss Nikita Shinde, Miss Apeksha Vishwasrao

Abstract: Managing daily expenses is an important task for people who want to keep track of their finances. The Expense Tracker Web Application is built to make it easier to record, manage, and understand personal financial data. The backend runs on Python Flask, and the front end uses HTML, CSS, and JavaScript to create a user-friendly and responsive interface. The backend supports basic functions like adding, editing, deleting, and viewing expense records, while also ensuring that the data is valid and accurate. It stores information securely in a SQLite database, which allows users to keep and access their financial records easily. The application uses Pandas for handling data and Matplotlib or Plotly for creating visual graphs. This lets users see their spending patterns by category and over time through pie charts and bar or line charts. Additionally, the project focuses on security by cleaning up inputs, checking user data, and optimizing queries for better performance. The system helps users manage daily expenses by organizing data and providing login protection and visual insights to support effective tracking and analysis of spending..

Published by: vikaspatanker

Authors: Prof. Sangeeta Alagi, , Priti Jagdale, Swati More, Vaibhav Prasad

Abstract: The rapid advancement of deep learning technologies has enabled the creation of highly realistic synthetic media, commonly known as deepfakes. These manipulated videos pose serious threats to information integrity, personal privacy, national security, and public trust. This comprehensive literature survey examines the state-of-the-art approaches in deepfake detection, with particular emphasis on methods that combine Convolutional Neural Networks (CNNs) for spatial feature extraction with temporal analysis techniques. We systematically review detection methodologies, benchmark datasets, evaluation metrics, current challenges, and emerging research directions. This survey synthesizes findings from over 50 research papers published between 2018 and 2024, providing insights into the evolution of detection techniques and the ongoing arms race between deepfake generation and detection technologies.

Published by: vikaspatanker