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805 results on '"Chen, Donghui"'

3. Fruquintinib plus paclitaxel versus placebo plus paclitaxel for gastric or gastroesophageal junction adenocarcinoma: the randomized phase 3 FRUTIGA trial

Author

Wang, Feng, Shen, Lin, Guo, Weijian, Liu, Tianshu, Li, Jin, Qin, Shukui, Bai, Yuxian, Chen, Zhendong, Wang, Jufeng, Pan, Yueyin, Shu, Yongqian, Zhao, Fuyou, Cheng, Ying, Ye, Feng, Gu, Kangsheng, Zhang, Tao, Pan, Hongming, Zhong, Haijun, Zhou, Fuxiang, Qin, Yanru, Yang, Lei, Mao, Weidong, Li, Qiu, Dai, Wenxiang, Li, Wei, Wang, Shubin, Tang, Yong, Ma, Dong, Yin, Xianli, Deng, Yanhong, Yuan, Ying, Li, Man, Hu, Wenwei, Chen, Donghui, Li, Guoxin, Liu, Qiqi, Tan, Panfeng, Fan, Songhua, Shi, Michael, Su, Weiguo, and Xu, Rui-Hua

Published
2024
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7. Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting

Author

Chen, Ling, Chen, Donghui, Shang, Zongjiang, Wu, Binqing, Zheng, Cen, Wen, Bo, and Zhang, Wei

Subjects
Computer Science - Machine Learning
Abstract

Multivariate time series (MTS) forecasting plays an important role in the automation and optimization of intelligent applications. It is a challenging task, as we need to consider both complex intra-variable dependencies and inter-variable dependencies. Existing works only learn temporal patterns with the help of single inter-variable dependencies. However, there are multi-scale temporal patterns in many real-world MTS. Single inter-variable dependencies make the model prefer to learn one type of prominent and shared temporal patterns. In this paper, we propose a multi-scale adaptive graph neural network (MAGNN) to address the above issue. MAGNN exploits a multi-scale pyramid network to preserve the underlying temporal dependencies at different time scales. Since the inter-variable dependencies may be different under distinct time scales, an adaptive graph learning module is designed to infer the scale-specific inter-variable dependencies without pre-defined priors. Given the multi-scale feature representations and scale-specific inter-variable dependencies, a multi-scale temporal graph neural network is introduced to jointly model intra-variable dependencies and inter-variable dependencies. After that, we develop a scale-wise fusion module to effectively promote the collaboration across different time scales, and automatically capture the importance of contributed temporal patterns. Experiments on four real-world datasets demonstrate that MAGNN outperforms the state-of-the-art methods across various settings., Comment: Accepted by TKDE

Published
2022

9. Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting

Author

Chen, Donghui, Chen, Ling, Shang, Zongjiang, Zhang, Youdong, Wen, Bo, and Yang, Chenghu

Subjects
Computer Science - Machine Learning
Abstract

Multivariate time series (MTS) forecasting has attracted much attention in many intelligent applications. It is not a trivial task, as we need to consider both intra-variable dependencies and inter-variable dependencies. However, existing works are designed for specific scenarios, and require much domain knowledge and expert efforts, which is difficult to transfer between different scenarios. In this paper, we propose a scale-aware neural architecture search framework for MTS forecasting (SNAS4MTF). A multi-scale decomposition module transforms raw time series into multi-scale sub-series, which can preserve multi-scale temporal patterns. An adaptive graph learning module infers the different inter-variable dependencies under different time scales without any prior knowledge. For MTS forecasting, a search space is designed to capture both intra-variable dependencies and inter-variable dependencies at each time scale. The multi-scale decomposition, adaptive graph learning, and neural architecture search modules are jointly learned in an end-to-end framework. Extensive experiments on two real-world datasets demonstrate that SNAS4MTF achieves a promising performance compared with the state-of-the-art methods.

Published
2021

27. Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of pancreatic cancer

Author

Cui, Jiujie, Jiao, Feng, Li, Qi, Wang, Zheng, Fu, Deliang, Liang, Jun, Liang, Houjie, Xia, Tingyi, Zhang, Tao, Zhang, Yang, Dai, Guanghai, Zhang, Zhihong, Wang, Jian, Bai, Yongrui, Bai, Yuxian, Bi, Feng, Chen, Donghui, Cao, Dan, Chen, Jie, Fang, Weijia, Gao, Yong, Guo, Jianwei, Hao, Jihui, Hua, Haiqing, Huang, Xinyu, Liu, Wenchao, Liu, Xiufeng, Li, Da, Li, Ji, Li, Enxiao, Li, Zhiwei, Pan, Hongming, Shen, Lin, Sun, Yongwei, Tao, Min, Wang, Chengfeng, Wang, Fenghua, Xiong, Jianping, Zhang, Taiping, Zhang, Xuebin, Zhan, Xianbao, Zheng, Leizhen, Ren, Gang, Zhang, Tingting, Zhou, Jun, Ma, Qingyong, Qin, Shukui, Hao, Chunyi, and Wang, Liwei

Published
2022
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29. Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction.

Author

Chen, Donghui, Liu, Jiyao, Zhang, Desheng, Dong, Zhixu, and Xu, Tao

Subjects
MACHINE learning, COGNITIVE bias, RUBBER, BIOPESTICIDES, CONSCIOUSNESS raising, PESTICIDES
Abstract

Some natural rubber farmers mistakenly equate the ecological functions of rubber plantations with those of primary forests. This cognitive bias can hinder pesticide reduction efforts. Meanwhile, natural rubber farmers gain security through price insurance, which helps them adopt a long-term perspective on environmental protection, mitigating the negative impact of cognitive biases on pesticide use decisions. However, existing research often overlooks the influence of ecological cognitive bias on pesticide reduction and the moderating role of price insurance satisfaction. This study utilizes field survey data from Hainan and employs logit models and double machine learning models to empirically analyze the impact of ecological cognitive bias on pesticide reduction among natural rubber farmers. It further tests the underlying mechanisms using moderation models. The results indicate that (1) ecological cognitive bias negatively affects pesticide reduction among natural rubber farmers, and (2) price insurance satisfaction mitigates the impact of ecological cognitive bias on pesticide reduction. Based on these findings, the government should enhance education and training to raise ecological awareness among natural rubber farmers and reduce ecological cognitive biases. Disseminating knowledge about price insurance and establishing a comprehensive insurance system can secure farmers' income and promote the rational use of pesticides. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Investigation and Analysis of Wettability, Anisotropy, and Adhesion in Bionic Upper and Lower Surfaces Inspired by Indocalamus Leaves.

Author

Wang, Bo, Chen, Donghui, Yang, Xiao, and Li, Ming

Subjects
*WETTING, *BIOLOGICAL models, *BIONICS, *ANISOTROPY, *FOLIAGE plants
Abstract

Nature provides us with a wealth of inspiration for the design of bionic functional surfaces. Numerous types of plant leaves with exceptional wettability, anisotropy, and adhesion are extensively employed in many engineering applications. Inspired by the wettability, anisotropy, and adhesion of indocalamus leaves, bionic upper and lower surfaces (BUSs and BLSs) of the indocalamus leaf were successfully prepared using a facile approach combining laser scanning and chemical modification. The results demonstrated the BUSs and BLSs obtained similar structural features to the upper and lower surfaces of the indocalamus leaf and exhibited enhanced and more-controllable wettability, anisotropy, and adhesion. More importantly, we conducted a detailed comparative analysis of the wettability, anisotropy, and adhesion between BUSs and BLSs. Finally, BUSs and BLSs were also explored for the corresponding potential applications, including self-cleaning, liquid manipulation, and fog collection, thereby broadening their practical utility. We believe that this study can contribute to the enrichment of the research on novel biological models and provide significant insights into the development of multifunctional bionic surfaces. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Comparison and utilization of point cloud tools for 3D reconstruction of small assets in built environment using a monocular camera.

Author

Chen, Donghui, Ju, Ha Kyun, and Kang, Kyubyung

Subjects
*POINT cloud, *BUILT environment, *MONOCULARS, *HYDRANTS, *GRAPHICAL projection, *OPTICAL scanners, *CAMERAS
Abstract

Two-dimensional (2D) images are acquired from the projection of three-dimensional (3D) objects on specific planes. Due to the information loss in this process, it is difficult to recover the 3D model from 2D image sequences, which represents a technique called Image-based 3D reconstruction. The method involves knowledge from many fields, such as image processing, computer vision, and computer graphics, making it a challenging but versatile topic. The authors implemented a 3D reconstruction program based on the Structure from Motion (SfM) framework in the project. Starting from the video taken using a monocular camera, first this study converted it into consistent image sequences. Then, the authors applied the SIFT operator to finish the feature detection and matching. Next, the parameters for each camera are estimated with the matching feature points. Finally, triangulation and bundle adjustments are utilized to achieve the 3D sparse point cloud. This study discussed the comparative 3D point cloud results of fire hydrants that were created using VisualSfM and MySfM. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Wide and Recurrent Neural Networks for Detection of False Data Injection in Smart Grids

Author

Wang, Yawei, Chen, Donghui, Zhang, Cheng, Chen, Xi, Huang, Baogui, Cheng, Xiuzhen, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Biagioni, Edoardo S., editor, Zheng, Yao, editor, and Cheng, Siyao, editor

Published
2019
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44. Multiplicative Iteration for Nonnegative Quadratic Programming

Author

Xiao, Xiao and Chen, Donghui

Subjects
Mathematics - Numerical Analysis
Abstract

In many applications, it makes sense to solve the least square problems with nonnegative constraints. In this article, we present a new multiplicative iteration that monotonically decreases the value of the nonnegative quadratic programming (NNQP) objective function. This new algorithm has a simple closed form and is easily implemented on a parallel machine. We prove the global convergence of the new algorithm and apply it to solving image super-resolution and color image labelling problems. The experimental results demonstrate the effectiveness and broad applicability of the new algorithm., Comment: 11 pages, 4 figures

Published
2014

45. 'Plug-and-Play' Edge-Preserving Regularization

Author

Chen, Donghui, Kilmer, Misha E., and Hansen, Per Christian

Subjects
Mathematics - Numerical Analysis, Mathematics - Optimization and Control, 65F22, 65F30
Abstract

In many inverse problems it is essential to use regularization methods that preserve edges in the reconstructions, and many reconstruction models have been developed for this task, such as the Total Variation (TV) approach. The associated algorithms are complex and require a good knowledge of large-scale optimization algorithms, and they involve certain tolerances that the user must choose. We present a simpler approach that relies only on standard computational building blocks in matrix computations, such as orthogonal transformations, preconditioned iterative solvers, Kronecker products, and the discrete cosine transform -- hence the term "plug-and-play." We do not attempt to improve on TV reconstructions, but rather provide an easy-to-use approach to computing reconstructions with similar properties., Comment: 14 pages, 7 figures, 3 tables

Published
2014

46. Safety Profile and Adverse Events of Special Interest for Fruquintinib in Chinese Patients with Previously Treated Metastatic Colorectal Cancer: Analysis of the Phase 3 FRESCO Trial

Author

Li, Jin, Guo, Weijian, Bai, Yuxian, Deng, Yanhong, Yang, Lei, Chen, Zhendong, Zhong, Haijun, Xu, Ruihua, Pan, Hongming, Shu, Yongqian, Yuan, Ying, Zhou, Jianfeng, Xu, Nong, Liu, Tianshu, Ma, Dong, Wu, Changping, Cheng, Ying, Xu, Jianming, Chen, Donghui, Li, Wei, Sun, Sanyuan, Yu, Zhuang, Cao, Peiguo, Shen, Lin, Chen, Haihui, Wang, Shubin, Wang, Hongbing, Fan, Songhua, Guo, Xiaojun, Wang, Ning, Han, Rubing, Zhang, Bin, and Qin, Shukui

Published
2020
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