SinoXivDeep learning models for automated knee osteoarthritis (OA) grading achieve high in-distribution accuracy but frequently exploit spurious image-acquisition cues — a phenomenon termed shortcut learning...
This article focuses on the sustainable development of electric vehicle equipment to ensure the safety of people and property. It contributes to improving the thermal management of lithium-ion batteri...
Trusted computing systems and blockchain-enabled security applications increas- ingly rely on Graph Neural Networks (GNNs) for trust graph analysis, fraud detection, and anomaly identification. In the...
Machine elements frequently operate under variable conditions, resulting in significant variations in interfacial friction across different lubrication regimes. The Stribeck curve is a well-establishe...
This study quantitatively analyzes the dynamic acceleration performance of medium to-large agricultural tractors (60HP and 75HP classes) and validates the reliability of a system-level simulation mode...
Predictive simulation of sintering-induced distortion remains challenging for ceramic components subjected to gravity and mechanical constraint. Classical constitutive sintering laws reproduce free de...
Deep learning has achieved remarkable success across various fields, however, most research in this area has primarily focused on increasing network depth, leading to a relative lack of systematic exp...
This study presents a forecasting and comparative analysis of moderate geomagnetic storms using artificial neural networks (ANNs). Four moderate geomagnetic storm events that occurred during 2022, in ...
Current phytopathological diagnostic systems rely on manual inspections or laboratory analyses, which delay early detection and limit in-field responsiveness. Phytopathogenic fungal diseases pose a pe...
The transition from effortful to automatic processing is a defining feature of skill acquisition, and converging evidence implicates theta-gamma phase-amplitude coupling as the neural signature of thi...
