Relation between training-related changes in unipedal and bipedal stance. by Cristina Dolciotti (16317330)

Subjects:

Consolidation of training-induced changes in unipedal stance: 95% Area, Y Sway Amplitude and LFS. by Cristina Dolciotti (16317330)

Subjects:

Consolidation of training-induced changes in unipedal stance: Path Length, X Sway Amplitude and Velocity. by Cristina Dolciotti (16317330)

Subjects:

Time course of 95% Area, X and Y Amplitude Sway during postural training. by Cristina Dolciotti (16317330)

Subjects:

Correlations between unipedal and bipedal stance parameters recorded at the beginning of the training and of the control session. by Cristina Dolciotti (16317330)

Subjects:

Flow diagram. by Cristina Dolciotti (16317330)

Subjects:

Details of significantly differentially abundant metabolites (<i>PPP1CC</i>-SSKO vs control). by Jiahong Sun (6497603)

Improved model distillation structure. by Zhongjian Xie (4633099)

“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

Frontier analysis for the potential for improvement in reducing the burden of IBD among WCBA across 204 countries and regions. by Jiefeng Zhao (9090305)

Example of Group C scene material. by Chengmin Zhou (14554562)

Subjects:

Conditional autonomous driving scenario complexity hierarchy. by Chengmin Zhou (14554562)

Subjects:

Mean (SD) of fixation duration, fixation counts, and SAGAT accuracy according to scene complexity and autonomous driving information display type. by Chengmin Zhou (14554562)

Subjects:

Point in time of the first visible deviation from the trail in each scenario. by Chengmin Zhou (14554562)

Subjects:

Displays types of autonomous driving information: a) P3D display on the W-HUD; b) SR display on the W-HUD; c) display on the AR-HUD. by Chengmin Zhou (14554562)

Subjects:

Experiment setting. by Chengmin Zhou (14554562)

Subjects:

Supplementary raw data file of eye-tracking experiment for subjects. by Chengmin Zhou (14554562)

Subjects:

The mean and standard error of SAGAT accuracy for type A, type B, and type C autonomous driving information display types under various scenario complexities. by Chengmin Zhou (14554562)

Subjects:

A path analysis model of the relationship between various scenario elements and traffic scenarios. by Chengmin Zhou (14554562)

Subjects:

Experimental flow. by Chengmin Zhou (14554562)

Subjects:

Schematic flow chart of driving take-over reaction experiment. by Chengmin Zhou (14554562)

Subjects: