Accurate airway segmentation from computed tomography (CT) images is critical for planning navigation bronchoscopy and realizing a quantitative assessment of airway-related chronic obstructive pulmonary disease (COPD). Existing methods face difficulty in segmentation, particularly the small branches airway. These difficulties arise due to constraints limited labeling failure meet clinical use r...

Prior studies in the field of motion predictions for autonomous driving tend to focus on finding a trajectory that is close ground truth trajectory, which highly biased toward straight maneuvers. Such problem formulations and imbalanced distribution datasets, however, frequently lead loss diversity predictions. Therefore, they are unsuitable real-world driving, where diverse road-dependent mult...

the development of optimization and mathematical models for closed loop supply chain (clsc) design has attracted considerable interest over the past decades. however, the uncertainties that are inherent in the network design and the complex interactions among various uncertain parameters are challenging the capabilities of the developed tools. the aim of this paper, therefore, is to propose a n...

The thick-slice magnetic resonance (MR) images are often structurally blurred in coronal and sagittal views, which causes harm to diagnosis image post-processing. Deep learning (DL) has shown great potential reconstruct the high-resolution (HR) thin-slice MR from those low-resolution (LR) cases, we refer as slice interpolation task this work. However, since it is generally difficult sample abun...

The existing nonuniformity correction methods generally have the defects of image blur, artifacts, over-smoothing, and nonuniform residuals. It is difficult for these to meet requirements enhancement in various complex application scenarios. In particular, when are applied dim small target images, they may remove targets as noise points due over-smoothing. This paper draws on idea a residual ne...

The increasing flexibility of active distribution systems (ADSs) coupled with the high penetration renewable distributed generators (RDGs) leads to increase complexity. It is practical significance achieve largest amount RDG in ADSs and maintain optimal operation. This study establishes an alternating current (AC)/direct (DC) hybrid ADS model that considers dynamic thermal rating, soft open poi...