Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...
Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...
A new airborne imaging approach can reliably detect unexploded weapons that lie in shallow coastal waters and remain an ...
AI's role in data centers enhances operational efficiency, predictive maintenance, and cybersecurity, paving the way for ...
Abstract: In recent years, Artificial Intelligence for IT Operations (AIOps) has gained popularity as a solution to various challenges in IT operations, particularly in anomaly detection. Although ...
Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adaptive anomaly detection ...
Abstract: The industrial control anomaly detection algorithm effectively monitors and identifies anomalies in industrial control systems, ensuring timely issue detection to maintain system reliability ...
ABSTRACT: We introduce in this paper MIES-TR, an intelligent model for real-time syllable boundary detection during keyboard typing. This innovative approach positions the syllable as an intermediate ...
ABSTRACT: This study investigates whether anomaly-aware modeling can improve stock price forecasting by incorporating signals that highlight unusual market behavior. Financial time series often ...
The framework encompasses two principal phases: the offline model training phase and the online anomaly detection phase. During the offline model training phase, we first preprocess the raw MTS. We ...
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