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Adaptive learning systems require effective mechanisms to model students’ evolving learning states and provide personalized learning path recommendations. Traditional rule-based approaches are limited in capturing...

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...

The increasing penetration of renewable energy sources (RES) reduces power system inertia, causing severe frequency excursions following disturbances. Conventional Automatic Generation Control (AGC) using fixed-gain cont...

Pose-guided image generation aims to generate realistic images based on a reference appearance and target pose. However, existing methods often suffer from structural distortion and texture degradation in visually comple...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

The provision of accurate and explainable captions and answers to visual questions about remote sensing images is essential in areas such as disaster management, land-use supervision, and military analysis, where system ...

Multimodal remote sensing image registration is a fundamental step for multisource data fusion and geospatial analysis. However, nonlinear radiometric, textural, and geometric discrepancies across modalities challenge in...

To address the sensitivity of traditional Two-Dimensional Principal Component Analysis (2DPCA) to outliers and the breakdown of variance-reconstruction equivalence under noise, we propose an Angle-Aware Weighted 2DPCA (A...

Intelligent tire systems (ITS) enable direct sensing of tire and road interaction using sensors mounted inside the tire, providing information that is difficult to obtain from conventional vehicle-mounted sensors. Howeve...

Efficient UAV path planning in large and dynamic environments requires adaptive strategies that account for varying regional importance. Traditional coverage or Reinforcement Learning-based methods often suffer from redu...

Modern software evolves rapidly, accumulates architectural debt, and develops cross-module dependencies that complicate reliable maintenance. We present EvoGraphCoder, an evolutionary graph-reasoning framework for self-a...

Farmer credit default identification in the context of inclusive finance is significantly hindered by sample scarcity, heterogeneous data sources, and the underutilization of “soft information” embedded in ...

Mobility-as-a-Service (MaaS) orchestration faces critical challenges in managing the Service Quality Index (SQI), Fleet Utilization Ratio (FUR), and Dynamic Pricing Index (DPI) under uncertain and time-varying urban dema...

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-...

Intelligent mining area detection is fundamental for ecological monitoring and sustainable development of mining areas. However, current remote sensing detection lacks high-quality multimineral rotated object detection d...

Convolutional neural networks (CNNs) and visual Transformers have become the dominant approaches for hyperspectral image (HSI) classification due to their powerful feature representation capabilities. However, CNNs are l...

Unsupervised anomaly detection identifying both structural and logical anomalies is essential for modern industrial manufacturing. Although multi-score frameworks have been proposed, existing methods tend to reuse identi...

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 ...

Traffic congestion degrades urban mobility and economic productivity, yet existing sensor-based monitoring systems detect only where congestion occurs without distinguishing its underlying infrastructure causes. This pap...