AUROC Graphs of RF Model and ResNet. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Model Workflow Diagram. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

Structural Diagrams of RF Model and ResNet Model. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN model convergence curve. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Structure Diagram. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

Comparison of Model Five-classification Results. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCAECG-GAN K-fold experiment table. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Pseudocode Table. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Ablation Experiment Results. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

Renamed 05c60. by Hongjun Sun (12554742)

“…The study reveals three key findings. (1) Contribution levels of China’s eight comprehensive economic zones to national standard development have significantly increased. The Northern Coastal comprehensive economic zone has the highest contribution levels, followed by the Eastern and Southern Coastal zones, whereas the Northwestern and Northeastern zones have lower contribution levels. (2) The overall regional disparity in national standard development contribution levels is decreasing, with the largest intraregional disparities found in the Northern and Southern Coastal zones. …”

Region Division. by Hongjun Sun (12554742)

“…The study reveals three key findings. (1) Contribution levels of China’s eight comprehensive economic zones to national standard development have significantly increased. The Northern Coastal comprehensive economic zone has the highest contribution levels, followed by the Eastern and Southern Coastal zones, whereas the Northwestern and Northeastern zones have lower contribution levels. (2) The overall regional disparity in national standard development contribution levels is decreasing, with the largest intraregional disparities found in the Northern and Southern Coastal zones. …”

Acoustic Startle at 28 dpf. by Morgan Barnes (7876373)

“…(C) There is a significant decrease of PPI in the 48+ and 72 + fish (p < 0.0001). …”

Schematic diagram of monitoring points and units. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”

The analysis procedure. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”

Model monitoring points and units coordinates. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”

Soil mechanical parameters. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”

Parameters of the contact surface. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”

The schematic diagram of free-field boundary. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”

Residual deformation parameters of soil. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”

Soil fluid and liquefaction parameters. by Jie Zhao (49409)

“…Results demonstrate that unreinforced foundations exhibit systematic residual deformation due to liquefaction-induced sand flow, which is significantly reduced by gravel pile reinforcement. Both excess pore water pressure and pore pressure ratio decrease markedly after reinforcement. …”