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968 results on '"He, Tingting"'

17. Guidelines for safe use of Polygoni Multiflori Radix

Author

Xiao, Xiaohe, Wang, Jiabo, Song, Haibo, Ouyang, Dongsheng, Zou, Zhengsheng, Wang, Ruilin, He, Tingting, Jing, Jing, Guo, Yuming, Bai, Zhaofang, Zhan, Xiaoyan, Niu, Ming, Ma, Zhijie, Li, Chunyu, Xiaohe, Xiao, Jiabo, Wang, Haibo, Song, Dongsheng, Ouyang, Zhengsheng, Zou, Ruilin, Wang, Tingting, He, Jing, Jing, Yuming, Guo, Zhaofang, Bai, Ming, Niu, Jianyu, Li, Fengyi, Li, Yun, Zhu, Zhijie, Ma, Chunyu, Li, Jinfa, Tang, Pengyan, Li, Le, Zhang, Chaopeng, Li, and Can, Tu

Published
2024
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34. Focusing on 'Online + Offline' Interaction, Exploring the Civic and Political Construction of Public English Courses in Higher Vocational Colleges and Universities

Author

He Tingting, Lai Yonghui, and Yao Jiguo

Subjects
rough set, bp neural network, markov chain, teaching quality evaluation, 97b20, Mathematics, QA1-939
Abstract

The significance of interactive pedagogy in English education cannot be overstated, as it fosters student engagement, collaboration, and active learning, thereby enhancing both academic performance and comprehensive capabilities. This article presents a structured three-step strategy designed to integrate curriculum thinking into the teaching of English at higher vocational levels through a blended online and offline approach. Central to this methodology is the development of a robust “online + offline” teaching quality evaluation index system, innovatively constructed using a combination of rough set theory and a backpropagation (BP) neural network algorithm. Furthermore, the effectiveness of this pedagogical approach is quantitatively analyzed using a Markov chain model, which evaluates the progression of students’ English proficiency. The analysis reveals that sustained application of the proposed teaching methodology is likely to elevate students’ English performance to an estimated score of 84.273, marking a substantial improvement of 5.443 points over traditional methods. Empirical validation of the model’s effectiveness was achieved through student evaluations across three critical areas: Civic Integration Effectiveness, Pre-Class Preview, and Follow-Up Testing. The results of the post-test assessments yielded mean scores of 3.565, 3.564, and 3.695, respectively, indicating a significant enhancement in learning outcomes, as evidenced by p-values of less than 0.05. This statistical analysis confirms the significant impact of the innovative pedagogical strategy on student learning outcomes.

Published
2024
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35. Power Mechanism and Practical Path of Agricultural Insurance to Help Rural Revitalization

Author

He Tingting

Subjects
entropy weight method, three-stage dea model, malmquist index model, rural revitalization, 70b15, Mathematics, QA1-939
Abstract

This paper firstly explores the power mechanism of agricultural insurance to help rural revitalization from three aspects of agriculture, farmers and rural three farmers, respectively, and constructs the rural revitalization development index system by combining the entropy power method. Then, the three-stage DEA model and the three-stage Malmquist index model are used to measure the efficiency of agricultural insurance boosting rural revitalization by combining the selected agricultural insurance boosting indicators. Finally, taking province A as an example, after descriptive statistical analysis, the method of this paper is combined with empirical analysis, and the practical path of agricultural insurance to help farmers is proposed from the three aspects of the insurance system, publicity as well and supply. The results show that after the optimization of agricultural insurance, the value of technical efficiency is distributed in [0.600, 0.738], the value of pure technical efficiency is distributed in [0.716, 0.826], and the value of scale efficiency is distributed in [0.738, 0.833] from 2010 to 2019. The mean value of the agricultural technical efficiency index in each city is 1.091, the mean value of the progress index is 1.033, and the mean value of total factor productivity is 1.029, which is an upward trending technology, and all of them have a growth rate of more than 5%. Based on this study, agricultural insurance can help improve the efficiency of rural revitalization.

Published
2024
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50. Tomato surface defect detection method based on image local variance considering brightness correction

Author

HE Tingting, YAO Jichao, ZHANG Zhonglili, LU Tiangang, and YUE Huanfang

Subjects
machine vision, defect detection, calyx, stem scar, brightness correction, image local variance, Food processing and manufacture, TP368-456
Abstract

Objective: In order to solve the problem of inaccurate defect extraction caused by complex and variable color and irregular texture changes of tomato surface defects, the defect segmentation method based on image local variance with brightness correction was proposed. Methods: On the basis of using histogram threshold segmentation method to segment calyx and stem scar and the method of domain pixel weighted sum to replace the original pixel to complete the brightness correction, the gray image of tomato surface was divided into several image blocks, and the color of each block was characterized by image pixel variance, and then the defect and healthy area were separated. SVM model was used to detect the proportion of tomato surface defect area in the original tomato area. Results: Considering the brightness correction, the accuracy of tomato defect area extraction could be improved by 27.74%. On this basis, compared with the global threshold, dynamic threshold and regional growth algorithm, the defect extraction method based on image local variance could accurately achieve the quasi-deterministic and complete extraction of tomato surface defects, and the accuracy of the Gauss-SVM model with the defect area ratio as the input for tomato surface defect detection reached 96%. Conclusion: Considering brightness correction, the SVM defect extraction method based on image local variance is suitable for tomato surface defect detection.

Published
2023
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