Search

Your search keyword '"Wang, Haijiang"' showing total 1,284 results
Start Over Author "Wang, Haijiang" Publication Year Range Last 50 years
1,284 results on '"Wang, Haijiang"'

2. 3D Wind Field Construction with Multiple Wind Profilers

Author

Gu, Taofeng, Wang, Jiamin, Shen, Feng, Yue, Haiyan, Wu, Guangsheng, Wu, Hao, Wang, Haijiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2024
Full Text
View/download PDF

12. CACA guidelines for holistic integrative management of rectal cancer

Author

Wang, Guiyu, Fan, Daiming, Gu, Jin, Ding, Kefeng, Fang, Xuedong, Shen, Lin, Xu, Zhongfa, Xu, Jianmin, Cai, Jianchun, Cai, Lianming, Cai, Sanjun, Chen, Gong, Chen, Jiansi, Cheng, Longwei, Cheng, Yong, Chi, Pan, Cui, Binbin, Dai, Guanghai, Fu, Chuangang, Gu, Yanhong, He, Guodong, Hu, Junhong, Huang, Jing, Huang, Rui, Huang, Zhongcheng, Jiang, Zheng, Jie, Zhigang, Ju, Haixing, Li, Hai, Li, Jian, Li, Jun, Li, Ming, Li, Yaoping, Li, Yunfeng, Lin, Guole, Liu, Haiying, Liu, Ming, Liu, Qian, Pan, Zhizhong, Peng, Yifan, Qian, Niansong, Qiu, Meng, Ren, Li, Sun, Yueming, Tang, Jianqiang, Tang, Qingchao, Tang, Yuan, Tao, Kaixiong, Tao, Min, Wang, Haijiang, Wang, Meng, Wang, Zejun, Wang, Zhengguang, Wang, Ziqiang, Wang, Ziwei, Wei, Shaozhong, Xing, Baocai, Xiong, Bin, Xu, Ye, Yan, Su, Yang, Bin, Yang, Chunkang, Yao, Qinghua, Ye, Yingjiang, Yuan, Ying, Zhang, Guozhi, Zhang, Haizeng, Zhang, Hongmei, Zhang, Zhen, Zhong, Yunshi, Zhu, Ji, Zhu, Yuan, Zhu, Yuping, Zou, Shuangmei, Wang, Yuliuming, Lv, Jingfang, Liu, Enrui, Yang, Ming, Zhang, Qian, Zhang, Weiyuan, Zhang, Lin, Luo, Jun, Zheng, Zhaoxu, Zhao, Zhixun, Liu, Zheng, Tao, Jinhua, Huang, Haiyang, Chen, Tianli, and Wang, Xishan

Published
2023
Full Text
View/download PDF

16. Efficacy and safety of ripretinib vs. sunitinib in patients with advanced gastrointestinal stromal tumor previously treated with imatinib: A phase 2, multicenter, randomized, open-label study in China

Author

Li, Jian, Zhang, Jun, Zhang, Yanqiao, Qiu, Haibo, Zhou, Yanbing, Zhou, Yongjian, Zhang, Xinhua, Zhou, Ye, Zhu, Yuping, Li, Yong, Wang, Ming, Shen, Kuntang, Tao, Kaixiong, Wu, Xin, Wang, Haijiang, Zhang, Bo, Ling, Jiayu, Ye, Yingjiang, Wu, Xingye, Qu, Hongyan, Ma, Yue, Jiao, Xuelong, Zheng, Hualong, Jin, Jiejie, Liu, Zhuo, Tan, Ming, Fang, Yong, Zhang, Peng, Zhang, Nan, Lei, Cheng, Cai, Zhaolun, Liang, Bin, Peng, Zhangyan, Huang, Zhao, Dong, Juan, and Shen, Lin

Published
2024
Full Text
View/download PDF

17. TEAM: We Need More Powerful Adversarial Examples for DNNs

Author

Qian, Yaguan, Zhang, Ximin, Wang, Bin, Li, Wei, Gu, Zhaoquan, Wang, Haijiang, and Swaileh, Wassim

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Although deep neural networks (DNNs) have achieved success in many application fields, it is still vulnerable to imperceptible adversarial examples that can lead to misclassification of DNNs easily. To overcome this challenge, many defensive methods are proposed. Indeed, a powerful adversarial example is a key benchmark to measure these defensive mechanisms. In this paper, we propose a novel method (TEAM, Taylor Expansion-Based Adversarial Methods) to generate more powerful adversarial examples than previous methods. The main idea is to craft adversarial examples by minimizing the confidence of the ground-truth class under untargeted attacks or maximizing the confidence of the target class under targeted attacks. Specifically, we define the new objective functions that approximate DNNs by using the second-order Taylor expansion within a tiny neighborhood of the input. Then the Lagrangian multiplier method is used to obtain the optimize perturbations for these objective functions. To decrease the amount of computation, we further introduce the Gauss-Newton (GN) method to speed it up. Finally, the experimental result shows that our method can reliably produce adversarial examples with 100% attack success rate (ASR) while only by smaller perturbations. In addition, the adversarial example generated with our method can defeat defensive distillation based on gradient masking., Comment: 14 pages,13 figures

Published
2020

26. Robust Network Architecture Search via Feature Distortion Restraining

Author

Qian, Yaguan, Huang, Shenghui, Wang, Bin, Ling, Xiang, Guan, Xiaohui, Gu, Zhaoquan, Zeng, Shaoning, Zhou, Wujie, Wang, Haijiang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Avidan, Shai, editor, Brostow, Gabriel, editor, Cissé, Moustapha, editor, Farinella, Giovanni Maria, editor, and Hassner, Tal, editor

Published
2022
Full Text
View/download PDF

27. Filter Pruning via Feature Discrimination in Deep Neural Networks

Author

He, Zhiqiang, Qian, Yaguan, Wang, Yuqi, Wang, Bin, Guan, Xiaohui, Gu, Zhaoquan, Ling, Xiang, Zeng, Shaoning, Wang, Haijiang, Zhou, Wujie, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Avidan, Shai, editor, Brostow, Gabriel, editor, Cissé, Moustapha, editor, Farinella, Giovanni Maria, editor, and Hassner, Tal, editor

Published
2022
Full Text
View/download PDF

28. Preliminary Study on the Mosaic Algorithm of Weather Radar Network in Sichuan Province

Author

Zhang, Wei, Yang, Jie, Huang, Yi, Sun, Min, Wang, Haijiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2022
Full Text
View/download PDF

29. Retrieval of Small and Medium-Scale Wind Field Based on Doppler Radar

Author

Zhang, Liwei, Wang, Xu, Wang, Caili, Wang, Haijiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2022
Full Text
View/download PDF

30. Correlation Between Hail Diameter and VILD in Bayannur

Author

Xu, Yunong, Su, Debin, Yang, Ning, Sun, Xiaoguang, Wang, Haijiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2022
Full Text
View/download PDF

42. Preliminary Exploration of Information Supervison System for Harmless Disposal of Laboratory Animal Carcasses and Related Wastes

Author

LI Yong, ZHOU Liang, HE Yong, YAN Zhifeng, and WANG Haijiang

Subjects
laboratory animal carcasses, wastes, harmless disposal, biosafety, information management system, Medicine
Abstract

At present, there is still a lack of standardized and institutionalized management of laboratory animal carcasses and related wastes in China, and effective supervision of their harmless disposal process, especially an effective whole-process biosafety supervision system. Using computer networks, global satellite positioning systems, wireless communications, geographic information systems and other multidisciplinary cutting-edge technologies, we preliminarily established an information management system for harmless disposal of laboratory animal carcasses and related wastes, which could be closely combined with biosafety supervision to realize dynamic tracking and monitoring in the whole process. The established system can strengthen the standardization and institutionalization management of experimental animal carcasses and related wastes, promote the safety control of medical waste, prevent the spread of diseases, protect the environment and ensure human health.

Published
2022
Full Text
View/download PDF

48. Efficient federated learning for pediatric pneumonia on chest X-ray classification.

Author

Pan, Zegang, Wang, Haijiang, Wan, Jian, Zhang, Lei, Huang, Jie, and Shen, Yangyu

Subjects
*FEDERATED learning, *MACHINE learning, *DATA privacy, *DATA security, *PRIOR learning, *X-rays
Abstract

According to the World Health Organization (WHO), pneumonia kills about 2 million children under the age of 5 every year. Traditional machine learning methods can be used to diagnose chest X-rays of pneumonia in children, but there is a privacy and security issue in centralizing the data for training. Federated learning prevents data privacy leakage by sharing only the model and not the data, and it has a wide range of application in the medical field. We use federated learning method for classification, which effectively protects data security. And for the data heterogeneity phenomenon existing in the actual scenario, which will seriously affect the classification effect, we propose a method based on two-end control variables. Specifically, based on the classical federated learning FedAvg algorithm, we modify the loss function on the client side by adding a regular term or a penalty term, and add momentum after the average aggregation on the server side. The federated learning approach prevents the data privacy leakage problem compared to the traditional machine learning approach. In order to solve the problem of low classification accuracy due to data heterogeneity, our proposed method based on two-end control variables achieves an average improvement of 2% and an accuracy of 98% on average, and 99% individually, compared to the previous federated learning algorithms and the latest diffusion model-based method. The classification results and methodology of this study can be utilized by clinicians worldwide to improve the overall detection of pediatric pneumonia. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

49. Study on Valley Shrink Deformation of the High Arch Dam with Large Faults near Dam Area during Initial Impoundment.

Author

Liu, Yaolai, Wang, Haijiang, Yan, Long, Yu, Jiyuan, Zeng, Wei, and Xu, Weiya

Subjects
WATER levels, DAM design & construction, DAM safety, PHENOMENOLOGICAL theory (Physics), DEFORMATIONS (Mechanics), ARCH dams
Abstract

Valley shrink deformation is a common physical and mechanical phenomenon during the reservoir operation of high arch dams. This phenomenon is particularly significant in the initial stages of impoundment and can severely impact the operational safety of the arch dam. This study focuses on the arch dam under construction in the upstream of the Lancang River. By considering the secondary structural planes F115 and F111 at the dam site, a numerical model of valley shrink deformation was established. The study investigates the characteristics of valley shrink deformation during the initial impoundment phase of the arch dam. The results show that during the impoundment process, the valley slopes on both sides of the reservoir shrink towards the center of the valley. The deformation on the right bank is greater than that on the left bank due to the influence of the F115 fault. When the elevation is lower than the exposure position of F115, the deformation on the right bank increases with elevation; when it is higher than this position, the deformation decreases. On the left bank, due to the influence of F111 and the seepage field, the deformation value increases first and then decreases with the increase in elevation. After the water level stabilizes, the deformation rate decreases and approaches zero. This research results provide a reference for addressing valley shrink deformation issues during the initial impoundment of the arch dam. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results