Security teams often spend days manually turning long incident reports and threat writeups into actionable detections by ...

Health insurers are entering a period of mounting pressure. Medical costs continue to rise globally, while regulatory ...

The project focuses on developing an integrated software package designed to process large-scale time-series data generated in smart factory and smart city environments using CNN- and RNN-based AI ...

Discover how to secure AI orchestration workflows using post-quantum cryptography and AI-driven anomaly detection for Model Context Protocol (MCP) environments.

Western capital markets are undergoing a structural realignment as defense technology investment reached $49.1 billion in 2025 1, with institutional capital rotating into platforms designed to secure ...

Abstract: NASA's forthcoming Lunar Gateway space station, which will be uncrewed most of the time, will need to operate with an unprecedented level of autonomy. One key challenge is enabling the ...

Due to the complexity of hotel operation processes, abnormal situations are inevitable, making proactive anomaly prediction essential for ensuring operational stability. Although current deep learning ...

Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...

├── src/ # Source code modules │ ├── lstm_model.py # LSTM implementation with PyTorch │ ├── forecasting_models.py # ARIMA, Prophet, and statistical models │ ├── anomaly_detection.py # Anomaly ...

1 Independent Researcher, Atlanta, GA, USA. 2 Alumni, Nanyang Technological University, Singapore City, Singapore. As digital financial ecosystems expand in scale, complexity, and global reach, ...