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1,434 results on '"Wu, Haotian"'

101. On the precise asymptotics of Type-IIb solutions to mean curvature flow

Author

Isenberg, James, Wu, Haotian, and Zhang, Zhou

Subjects
Mathematics - Differential Geometry, Mathematics - Analysis of PDEs
Abstract

In this paper, we study the precise asymptotics of noncompact Type-IIb solutions to the mean curvature flow. Precisely, for each real number $\gamma>0$, we construct mean curvature flow solutions, in the rotationally symmetric class, with the following precise asymptotics as $t\nearrow\infty$: (1) The highest curvature concentrates at the tip of the hypersurface (an umbilical point) and blows up at the Type-IIb rate $(2t+1)^{(\gamma-1)/2}$. (2) In a neighbourhood of the tip, the Type-IIb blow-up of the solution converges to a translating soliton known as the bowl soliton. (3) Near spatial infinity, the hypersurface has a precise growth rate depending on $\gamma$., Comment: Comments are welcome. arXiv admin note: text overlap with arXiv:1911.07282, arXiv:1603.01664

Published
2020

103. Mean curvature flow of noncompact hypersurfaces with Type-II curvature blow-up. II

Author

Isenberg, James, Wu, Haotian, and Zhang, Zhou

Subjects
Mathematics - Differential Geometry, Mathematics - Analysis of PDEs
Abstract

We continue the study, initiated by the first two authors in \cite{IW19}, of Type-II curvature blow-up in mean curvature flow of complete noncompact embedded hypersurfaces. In particular, we construct mean curvature flow solutions, in the rotationally symmetric class, with the following precise asymptotics near the "vanishing" time $T$: (1) The highest curvature concentrates at the tip of the hypersurface (an umbilical point) and blows up at the rate $(T-t)^{-1}$. (2) In a neighbourhood of the tip, the solution converges to a translating soliton known as the bowl soliton. (3) Near spatial infinity, the hypersurface approaches a collapsing cylinder at an exponential rate., Comment: Comments are welcome. arXiv admin note: text overlap with arXiv:1603.01664

Published
2019

116. Polyacrylonitrile as an Efficient Transfer Medium for Wafer‐scale Transfer of Graphene

Author

Shang, Mingpeng, primary, Bu, Saiyu, additional, Hu, Zhaoning, additional, Zhao, Yixuan, additional, Liao, Junhao, additional, Zheng, Chunyang, additional, Liu, Wenlin, additional, Lu, Qi, additional, Li, Fangfang, additional, Wu, Haotian, additional, Shi, Zhuofeng, additional, Zhu, Yaqi, additional, Xu, Zhiying, additional, Guo, Bingbing, additional, Yu, Beiming, additional, Li, Chunhu, additional, Zhang, Xiaodong, additional, Xie, Qin, additional, Yin, Jianbo, additional, Jia, Kaicheng, additional, Peng, Hailin, additional, Lin, Li, additional, and Liu, Zhongfan, additional

Published
2024
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119. Bayesian Two-Level Model for Repeated Partially Ordered Responses: Application to Adolescent Smoking Behavior Analysis

Author

Wang, Xiaoqing, Wu, Haotian, Feng, Xiangnan, and Song, Xinyuan

Abstract

Given the questionnaire design and the nature of the problem, partially ordered data that are neither completely ordered nor completely unordered are frequently encountered in social, behavioral, and medical studies. However, early developments in partially ordered data analysis are very limited and restricted only to cross-sectional data. In this study, we propose a Bayesian two-level regression model for analyzing repeated partially ordered responses in longitudinal data. The first-level model is defined for partially ordered observations of interest that are taken at each time point nested within individuals, while the second-level model is defined for individuals to assess the effects of their characteristics on the first-level model. A full Bayesian approach with the Markov chain Monte Carlo algorithm is developed for statistical inference. Simulation studies demonstrate the satisfactory performance of the developed methodology. The methodology is then applied to a longitudinal study on adolescent smoking behavior.

Published
2021
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120. Password Guessing Model Based on Reinforcement Learning

Author

LI Xiaoling, WU Haotian, ZHOU Tao, LU Hui

Subjects
password guessing, deep learning, reinforcement learning, actor-critic algorithm, generative adversarial network, Computer software, QA76.75-76.765, Technology (General), T1-995
Abstract

Password guessing is an important research direction in password security.Password guessing based on generative adversarial network(GAN) is a new method proposed in recent years,which guides the update of the generator according to evaluation results on passwords generated by the discriminator.Consequently,password guessing sets can be generated with trained GANs.However,the existing GAN-based password guessing models have low efficiency due to inadequate guidance of the discriminator to the generator.To solve this problem,an improved GAN password guessing model AC-Pass based on reinforcement learning Actor-Critic algorithm is proposed.The AC-Pass model guides the update of the generation strategy of the Actor network at each time step through the output rewards of the discriminator and the Critic network,and realizes the reinforce guidance of password sequence generation process.The proposed AC-Pass model is implemented on RockYou,LinkedIn and CSDN data sets and compared with PCFG model and the existing GANs-based password guessing models such as PassGAN and seqGAN.Results on homologous testing sets and heterologous testing sets indicate that password cracking rate of AC-Pass model on the guessing set is higher than that of PassGAN and seqGAN.Moreover,AC-Pass shows better guessing performance than PCFG when the password spatial distribution between the testing set and the training set is significant.In addition,the AC-Pass model has a large password output space.As the size of password guessing set increases,the cracking rate continues to rise.

Published
2023
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147. Large-area transfer of two-dimensional materials free of cracks, contamination and wrinkles via controllable conformal contact

Author

Zhao, Yixuan, Song, Yuqing, Hu, Zhaoning, Wang, Wendong, Chang, Zhenghua, Zhang, Yan, Lu, Qi, Wu, Haotian, Liao, Junhao, Zou, Wentao, Gao, Xin, Jia, Kaicheng, Zhuo, La, Hu, Jingyi, Xie, Qin, Zhang, Rui, Wang, Xiaorui, Sun, Luzhao, Li, Fangfang, Zheng, Liming, Wang, Ming, Yang, Jiawei, Mao, Boyang, Fang, Tiantian, Wang, Fuyi, Zhong, Haotian, Liu, Wenlin, Yan, Rui, Yin, Jianbo, Zhang, Yanfeng, Wei, Yujie, Peng, Hailin, Lin, Li, and Liu, Zhongfan

Published
2022
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