Vol. 2 No. 2 (2025)

The second issue of the International Journal of Emerging Technologies and Advanced Applications (IJETAA) for 2025 features a single cutting-edge research paper by Chuanyong Zhao and Yuan Xi . The article titled "Real-time Fault Detection and Stability Enhancement Mechanism Based on Large Models" presents an innovative framework for identifying system faults through advanced machine learning techniques.

The authors introduce a self-supervised learning approach that leverages transformer architecture and attention mechanisms to analyze system logs and operational data in real time. Their method demonstrates significant improvements over traditional approaches, reducing fault detection latency by 47.3% and system recovery time by 35.8%. This groundbreaking research offers valuable insights for enhancing reliability in distributed systems through continuous adaptation to emerging fault patterns.

IJETAA continues its commitment to showcasing pioneering technologies with this focused issue highlighting advancements in system reliability and large model applications.