Kaplan-Meier Survival Curve of three 2-Categorical Variables: (a) Survival Curve by Preceding Vehicle Drop-off Status Groups; (b) Survival Curve by Drop-off Duration Groups; (c) Su... by Fangyi Yang (18867853)

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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

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Kaplan-Meier Survival Curve of four 3-Categorical Variables: (a) Survival Curve by Forced Stop Count Groups; (b) Survival Curve by Cumulative Forced Stop Duration Groups; (c) Survi... by Fangyi Yang (18867853)

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Spatio-Temporal Diagram of Vehicle Trajectory in FIFO System. by Fangyi Yang (18867853)

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Transcriptomics Points-of-Departure (tPODs) to Support Hazard Assessment of Benzo[<i>a</i>]pyrene in Early-Life-Stage Rainbow Trout by Alper James Alcaraz (20977320)

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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

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Kaplan-Meier Survival Curve of Forced Stop Duration. by Fangyi Yang (18867853)

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Out-of-sample Test Results of the Drop-off Decision Models: (a) ROC Curve of the First Forced Drop-off Decision Models; (b) ROC Curve for Second and More Forced Parking and Drop-of... by Fangyi Yang (18867853)

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Characteristics of the respondents (n = 2,151). by Mohammad Delwer Hossain Hawlader (11558838)

Subjects: “…considered statistically significant…”

Determinants of HPV vaccine acceptance. by Mohammad Delwer Hossain Hawlader (11558838)

Subjects: “…considered statistically significant…”

A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

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Results of redundancy analysis. by Bianhua Zhang (22430652)

“…The positive connection proportion and modules of bacteria in LFA was higher than that in NL, while the aggregation coefficient decreased. …”

Predicted chronic activation of the cardiomyocyte signaling network during VO. by Johane H. Bracamonte (12883844)

Overall model framework. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Key parameters of LSTM training model. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Comparison chart of model evaluation results. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Model performance evaluation results. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

The result compared with other existing methods. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Results of MC simulations of VO and agonist infusion. by Johane H. Bracamonte (12883844)

Test equipment. by Haotian Guo (6620120)

“…The cooling rate significantly affected the frost heave ratio: under closed conditions, the ratio decreased, whereas under open water supply conditions, the vertical frost heave displacement increased with higher cooling rates.Moisture migration within the specimen was notably different under the two replenishment conditions. …”