Undue Burden on Broker-Dealers + Misalignment of SEC Resources: Total private-sector compliance expenditures to report CAT ...

Artificial intelligence (AI) has become a foundational technology in the development of autonomous vehicles (Garikapati Shetiya, 2024), enabling these systems to perceive their environment, make ...

Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...

Google Cloud has expanded its enterprise cybersecurity push with AI Threat Defense, as the market shifts towards AI-native threat detection, contextual triage, and supervised remediation. The launch ...

The action director Renny Harlin combines two different kinds of disaster movies, with lots of gory shark scenes. By Glenn Kenny When you purchase a ticket for an independently reviewed film through ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...

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 ...

Abstract: Lithium-ion batteries, which store energy, can experience thermal runaway and capacity degradation. A hybrid deep learning architecture integrates LSTM, GRU, and RNN autoencoders with ...

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

5.1 RQ1: How does our proposed anomaly detection model perform compared to the baselines? 5.2 RQ2: How much does the sequential and temporal information within log sequences affect anomaly detection?