Buscar recursos académicos

The inherent non-stationarity, weak periodicity, and abrupt transient mutations of wind turbine gearbox vibration signals present substantial challenges to traditional diagnostic frameworks. To improve diagnostic accurac...

Real-time streaming pipelines are increasingly central to data-driven product decisions, yet the data quality literature has focused predominantly on batch systems. We present ADQM (Adaptive Data Quality Monitor), a fram...

Federated learning (FL) in mobile edge computing (MEC) operates over wireless links with time-varying bandwidth, latency, and packet loss, which makes conventional full-model synchronization inefficient and vulnerable to...

Customer churn prediction is essential across data-driven industries such as insurance, digital banking, e-commerce, and subscription platforms, where retaining existing customers is typically more cost-effective than ac...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Emergency evasive maneuvers unfold in short near-limit windows in which combined-slip saturation, load transfer, and rapidly varying friction make onset-computation budget and model mismatch critical to collision-avoidan...

Autonomous underwater vehicles (AUVs) operating in harsh, communication-limited underwater environments require robust fault diagnosis systems to ensure mission success and safety. Existing model-based approaches suffer ...

The growth of variable renewable energy sources has increased the occurrence of curtailment in power systems, particularly in regions affected by transmission constraints and limited operational flexibility. Reliable for...

Sign language is a primary communication channel for millions of people who are deaf or hard of hearing, yet generating signer video directly from text remains difficult because video diffusion models are expensive to tr...

In modern industrial process monitoring of multivariate time series, the effectiveness of data-driven event detection is often constrained by scarce labels and the dynamic complexity of real-world telemetry. While unsupe...

Short-term wind speed forecasting remains challenging due to the inherent nonstationarity and multiscale variability of atmospheric processes. This study proposes a hybrid multiscale forecasting framework combining four-...