Comparison experiment of accuracy improvement. 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. …”

Comparison of different pruning rates. 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. …”

Comparison of experimental results at ablation. 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. …”

Result of comparison of different lightweight. 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. …”

DyHead 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. …”

The parameters of the training phase. 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. …”

Structure of GSConv network. 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. …”

Comparison experiment of accuracy improvement. 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. …”

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. …”

Complementary conditioning measures in healthy subjects. by Gabriela Ribeiro (4748373)

“…<b>(F) Intake</b> volumes were higher for CS⁺ than CS^- (F_(1,102) = 5.5, <i>P</i> = 0.02), and decreased across conditioning days (F_(1,102) = 8.1, <i>P</i> = 0.005; Interaction: F_(1,102) = 0.5, <i>P</i> = 0.5; repeated-measures 2-way ANOVA). …”

Changes in the separation and spread of evidence distributions induced by energy, contrast, and variability manipulations. by Medha Shekhar (19502698)

TSA alleviates the induction of inflammatory cytokines in <i>Col4a3</i> KO mice. by Yoon Seok Nam (20678482)

“…<p>(A) The mRNA level of proinflammatory cytokines IL-1β and TGF-β1 was higher in the cochlea of <i>Col4a3</i> KO mice, while IL-6 and TNF-α were significantly increased compared to wild-type (WT) mice. …”

Graphical overview of study. by Brian Foo (19273132)

Morphological Change of Hydrate Caused by Ostwald Ripening and Sintering by Zelin Xu (14002343)

“…Hydrate Ostwald ripening and sintering were observable several weeks after the onset of formation, leading to a decrease in the particle number. Simultaneously, the particle size increased significantly without alteration of the overall hydrate saturation. …”

Morphological Change of Hydrate Caused by Ostwald Ripening and Sintering by Zelin Xu (14002343)

“…Hydrate Ostwald ripening and sintering were observable several weeks after the onset of formation, leading to a decrease in the particle number. Simultaneously, the particle size increased significantly without alteration of the overall hydrate saturation. …”

Sex- and age-related changes in individual variance and behavioural repeatability. by Andréa L. Johnson (22505376)

Data_Sheet_1_Loneliness, online learning and student outcomes in college students living with disabilities: results from the National College Health Assessment Spring 2022.docx by William Bevens (9319157)

“…Several disability groups reported decreased odds of higher CGA compared to students without disabilities.…”

Image_1_Loneliness, online learning and student outcomes in college students living with disabilities: results from the National College Health Assessment Spring 2022.pdf by William Bevens (9319157)

“…Several disability groups reported decreased odds of higher CGA compared to students without disabilities.…”

A Hydrate-Bearing Sediment Gas Replacement Mechanical Behavior Regulation Mechanism and Slope Stability Analysis by Lei Huang (35191)

“…As saturation increases, the Γ value of the critical state line decreases, while the λ value increases. (3) For slope simulations, increased hydrate saturation significantly raises the safety factor for gentler slopes, while the reinforcing effect of gas replacement is weaker for steeper slopes with higher saturation.…”

A Hydrate-Bearing Sediment Gas Replacement Mechanical Behavior Regulation Mechanism and Slope Stability Analysis by Lei Huang (35191)

“…As saturation increases, the Γ value of the critical state line decreases, while the λ value increases. (3) For slope simulations, increased hydrate saturation significantly raises the safety factor for gentler slopes, while the reinforcing effect of gas replacement is weaker for steeper slopes with higher saturation.…”