A Novel Composite Sensor for UHF Partial Discharge and Gas State Measurement in GIS

Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories

FedViT: Federated continual learning of vision transformer at edge

ElasticDNN: On-Device Neural Network Remodeling for Adapting Evolving Vision Domains at Edge

A Self-Bias-Flip with Charge Recycle Interface Circuit with No External Energy Reservoir for Piezoelectric Energy Harvesting Array

Recognition of Unsafe Onboard Mooring and Unmooring Operation Behavior Based on Improved YOLO-v4 Algorithm

Microstructural evolutions and impact toughness in simulated welding heat affected zones for a high-strength carbide-free bainitic rail steel

Rapid extraction of pavement aggregate gradation based on point clouds using deep learning networks

Fast DRL-based scheduler configuration tuning for reducing tail latency in edge-cloud jobs

The Impact of Public Opinion Pressure on Construction Company Green Innovations: The Mediating Effect of Leaders' Environmental Intention and the Moderating Effect of Environmental Regulation

Frozen soil hydrological modeling for a mountainous catchment northeast of the Qinghai-Tibet Plateau

An online data driven fault diagnosis and thermal runaway early warning for electric vehicle batteries

Determinants of villagers’ satisfaction with post-disaster reconstruction: Evidence from surveys ten years after the Wenchuan earthquake

Federated Learning With Heterogeneity-Aware Probabilistic Synchronous Parallel on Edge

Lightweight and Accurate DNN-Based Anomaly Detection at Edge

Large Region Targets Observation Scheduling by Multiple Satellites Using Resampling Particle Swarm Optimization

Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G

Knitting 4D garments with elasticity controlled for body motion

Microwave roasting of blast furnace slag for carbon dioxide mineralization and energy analysis

Workload-Adaptive Configuration Tuning for Hierarchical Cloud Schedulers