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156. Research on key technologies of crop growth process simulation model and morphological 3D visualization

Author

Zhu Yeping, Li Shijuan, Li Shuqin

Subjects
crop simulation model, growth process visualization, morphology visualization, agent, technology 3d, Agriculture (General), S1-972, Technology (General), T1-995
Abstract

According to the demand of digitized analysis and visualization representation of crop yield formation and variety adaptability analysis, aiming at improving the timeliness, coordination and sense of reality of crop simulation model, key technologies of crop growth process simulation model and morphological 3D visualization were studied in this research. The internet of things technology was applied to collect the field data. The multi-agent technology was used to study the co-simulation method and design crop model framework. Winter wheat (Triticum aestivum L.) was taken as an example to conducted filed test, the 3D morphology visualization system was developed and validated. Taking three wheat varieties, Hengguan35 (Hg35), Jimai22 (Jm22) and Heng4399 (H4399) as research objects, logistic equation was constructed to simulate the change of leaf length, maximum leaf width, leaf height and plant height. Parametric modeling method and 3D graphics library (OpenGL) were used to build wheat organ geometry model so as to draw wheat morphological structure model. The R2 values of leaf length, maximum leaf width, leaf height and plant height were between 0.772-0.999, indicating that the model has high fitting degree. F values (between 10.153-4359.236) of regression equation and Sig. values (under 0.05) show that the model has good significance. Taking wheat as example, this research combined wheat growth model and structure model effectively in order to realize the 3D morphology visualization of crop growth processes under different conditions, it will provide references for developing the crop simulation visualization system, the method and related technologies are suitable for other field crops such as corn and rice, etc.

Published
2019
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157. The Influencing Factor Analysis of Micro-blog User Adding Attend Object

Author

Li, Shuqin, Yuan, Xiaohua, Ling, Xiaobin, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Xhafa, Fatos, editor, Patnaik, Srikanta, editor, and Yu, Zhengtao, editor

Published
2017
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158. Scanpath Prediction Based on High-Level Features and Memory Bias

Author

Shao, Xuan, Luo, Ye, Zhu, Dandan, Li, Shuqin, Itti, Laurent, Lu, Jianwei, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Xie, Shengli, editor, Li, Yuanqing, editor, Zhao, Dongbin, editor, and El-Alfy, El-Sayed M., editor

Published
2017
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159. Sampling Hierarchical Position-Based Dynamics Simulation

Author

Wang, Meili, Zheng, Hua, Qian, Kun, Li, Shuqin, Yang, Xiaosong, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chang, Jian, editor, Zhang, Jian Jun, editor, Magnenat Thalmann, Nadia, editor, Hu, Shi-Min, editor, Tong, Ruofeng, editor, and Wang, Wencheng, editor

Published
2017
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169. Dynamic Evaluation of Water Resources Management Performance in the Yangtze River Economic Belt.

Author

Sun, Fuhua, Miao, Caiqin, Li, Shuqin, Shen, Juqin, Huang, Xin, and Zhang, Shengnan

Abstract

The evaluation of water resources management performance (WRMP) can provide guidance for water resources management. This paper constructs a scientific WRMP evaluation index system based on "water resources–water environment–water ecology". Secondly, the game variable weight matter–element extension model is appropriately introduced to dynamically evaluate the WRMP level of the provinces (cities) in the YREB from 2012 to 2021, and Arcgis is used to analyze the spatial and temporal variations in the performance level of each sub-system. Lastly, a geographical detector model is used to explore the main factors influencing the WRMP in the Yangtze River Economic Balt (YREB). The main findings are as follows: (1) The overall provincial WRMP level in the YREB has been improving from 2012 to 2021, and the performance of water resource utilization (WRU) and water environment treatment (WET) are high in the east and low in the west, while the performance of water ecological protection (WEP) shows a trend of continuous improvement. (2) Compared with the model without variable weight modification, the game variable weight matter–element extension model can reflect the influence of the measured value of the index on the evaluation result as much as possible. (3) The top eight factors that have a greater impact on the WRMP level are the industrial water conservation rate, water resource development and utilization rate, water resource sustainability index, sewage diameter ratio, urban water penetration rate, industrial wastewater treatment completion rate, ecological construction and protection of the year to complete the investment in GDP, and the water ecological carrying capacity growth rate. The interaction types of each influence factor are nonlinear enhancement and two-factor enhancement. [ABSTRACT FROM AUTHOR]

Published
2024
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181. Abstract 3428: Discovery of a highly potent and selective dual PROTAC degrader of CDK12 and CDK13

Author

Chang, Yu, primary, Yang, Jianzhang, additional, Tien, Jean Ching-Yi, additional, Wang, Zhen, additional, Zhou, Yang, additional, Zhang, Pujuan, additional, Huang, Weixue, additional, Vo, Josh, additional, Apel, Ingrid J., additional, Wang, Cynthia, additional, Zeng, Victoria Zhixuan, additional, Cheng, Yunhui, additional, Li, Shuqin, additional, Wang, George Xiaoju, additional, Ding, Ke, additional, and Chinnaiyan, Arul M., additional

Published
2023
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