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384 results on '"Li, Wen-Xin"'

1. Real-time chaotic video encryption based on multithreaded parallel confusion and diffusion

Author

Jiang, Dong, Yuan, Zhen, Li, Wen-xin, and Lu, Liang-liang

Subjects
Computer Science - Cryptography and Security, Computer Science - Distributed, Parallel, and Cluster Computing, 68P25 (Primary) 68W10 (Secondary), E.3
Abstract

Due to the strong correlation between adjacent pixels, most image encryption schemes perform multiple rounds of confusion and diffusion to protect the image against attacks. Such operations, however, are time-consuming, cannot meet the real-time requirements of video encryption. Existing works, therefore, realize video encryption by simplifying the encryption process or encrypting specific parts of video frames, which results in lower security compared to image encryption. To solve the problem, this paper proposes a real-time chaotic video encryption strategy based on multithreaded parallel confusion and diffusion. It takes a video as the input, splits the frame into subframes, creates a set of threads to simultaneously perform five rounds of confusion and diffusion operations on corresponding subframes, and efficiently outputs the encrypted frames. The encryption speed evaluation shows that our method significantly improves the confusion and diffusion speed, realizes real-time 480x480, 576x576, and 768x768 24FPS video encryption using Intel Core i5-1135G7, Intel Core i7-8700, and Intel Xeon Gold 6226R, respectively. The statistical and security analysis prove that the deployed cryptosystems have outstanding statistical properties, can resist attacks, channel noise, and data loss. Compared with existing works, to the best of our knowledge, the proposed strategy achieves the fastest encryption speed, and realizes the first real-time chaotic video encryption that reaches the security level of image encryption. In addition, it is suitable for many confusion, diffusion algorithms and can be easily deployed with both hardware and software., Comment: 14 pages, 11 figures, 9 tables

Published
2023
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9. Automated diffusion‐weighted image analysis along the perivascular space index reveals glymphatic dysfunction in association with brain parenchymal lesions.

Author

Li, Wen‐Xin, Liu, Zi‐Yue, Zhai, Fei‐Fei, Han, Fei, Li, Ming‐Li, Zhou, Li‐Xin, Ni, Jun, Yao, Ming, Zhang, Shu‐Yang, Cui, Li‐Ying, Jin, Zheng‐Yu, and Zhu, Yi‐Cheng

Subjects
*DIFFUSION tensor imaging, *IMAGE analysis, *BRAIN damage, *WHITE matter (Nerve tissue), *CEREBRAL atrophy
Abstract

Brain glymphatic dysfunction is critical in neurodegenerative processes. While animal studies have provided substantial insights, understandings in humans remains limited. Recent attention has focused on the non‐invasive evaluation of brain glymphatic function. However, its association with brain parenchymal lesions in large‐scale population remains under‐investigated. In this cross‐sectional analysis of 1030 participants (57.14 ± 9.34 years, 37.18% males) from the Shunyi cohort, we developed an automated pipeline to calculate diffusion‐weighted image analysis along the perivascular space (ALPS), with a lower ALPS value indicating worse glymphatic function. The automated ALPS showed high consistency with the manual calculation of this index (ICC = 0.81, 95% CI: 0.662–0.898). We found that those with older age and male sex had lower automated ALPS values (β = −0.051, SE = 0.004, p <.001, per 10 years, and β = −0.036, SE = 0.008, p <.001, respectively). White matter hyperintensity (β = −2.458, SE = 0.175, p <.001) and presence of lacunes (OR = 0.004, 95% CI < 0.002–0.016, p <.001) were significantly correlated with decreased ALPS. The brain parenchymal and hippocampal fractions were significantly associated with decreased ALPS (β = 0.067, SE = 0.007, p <.001 and β = 0.040, SE = 0.014, p =.006, respectively) independent of white matter hyperintensity. Our research implies that the automated ALPS index is potentially a valuable imaging marker for the glymphatic system, deepening our understanding of glymphatic dysfunction. [ABSTRACT FROM AUTHOR]

Published
2024
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10. 26‐1: Embedded a‐Si Photo‐Transistor Sensors Integration in Remote Optical Touch‐input Panel Using Four‐Mask Process Architecture Technology.

Author

Cho, An‐Thung, Yang, Feng‐yun, Zhang, Young, Wang, Ming‐liang, Feng, Jin‐chang, Chen, Ni, Li, Wen‐xin, Ruan, Ting‐ting, Guo, Dong‐sheng, Lin, Steve, Hsu, James, and Chen, Wade

Subjects
HYDROGENATED amorphous silicon, DETECTOR circuits, IMAGE sensors, OPTICAL sensors, AMORPHOUS silicon, PIXELS
Abstract

An optical type touch‐input flat panel is designed. The driving system is based on the passive pixel sensor (PPS) array with amorphous silicon (a‐Si) TFT technology. The embedded sensing structure of the optical sensor is using the a‐Si TFT phototransistor and four‐mask process architecture technology. This paper presents a primary optical pixel sensor circuit that utilizes hydrogenated amorphous silicon photo‐transistor sensor. The a‐Si TFT phototransistor sensor is high reliability by using Multi‐N+ layer in the a‐Si TFT structure. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Effectiveness and Safety of Chinese Herbal Injections Combined with SOX Chemotherapy Regimens for Advanced Gastric Cancer: a Bayesian Network Meta-Analysis

Author

Bu, Zhi-jun, primary, Wan, Shu-run, additional, Steinmann, Peter, additional, Yin, Ze-tao, additional, Tan, Jin-ping, additional, Li, Wen-xin, additional, Tang, Zhen-yan, additional, Jiang, Shuo, additional, Ye, Meng-meng, additional, Xu, Jin-yang, additional, Zheng, You-you, additional, Wang, Xue-hui, additional, Liu, Jian-ping, additional, and Liu, Zhao-lan, additional

Published
2024
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23. Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching

Author

Ma, Wei-Ping, Li, Wen-Xin, and Cao, Peng-Xia

Abstract

In order to improve the low positioning accuracy and execution efficiency of the robot binocular vision, a binocular vision positioning method based on coarse-fine stereo matching is proposed to achieve object positioning. The random fern is used in the coarse matching to identify objects in the left and right images, and the pixel coordinates of the object center points in the two images are calculated to complete the center matching. In the fine matching, the right center point is viewed as an estimated value to set the search range of the right image, in which the region matching is implemented to find the best matched point of the left center point. Then, the similar triangle principle of the binocular vision model is used to calculate the 3D coordinates of the center point, achieving fast and accurate object positioning. Finally, the proposed method is applied to the object scene images and the robotic arm grasping platform. The experimental results show that the average absolute positioning error and average relative positioning error of the proposed method are 8.22 mm and 1.96% respectively when the object's depth distance is within 600 mm, the time consumption is less than 1.029 s. The method can meet the needs of the robot grasping system, and has better accuracy and robustness.

Published
2024
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32. Operando High‐Valence Cr‐Modified NiFe Hydroxides for Water Oxidation

Author

Wang, Ming Hua, primary, Lou, Zhen Xin, additional, Wu, Xuefeng, additional, Liu, Yuanwei, additional, Zhao, Jia Yue, additional, Sun, Kai Zhi, additional, Li, Wen Xin, additional, Chen, Jiacheng, additional, Yuan, Hai Yang, additional, Zhu, Minghui, additional, Dai, Sheng, additional, Liu, Peng Fei, additional, and Yang, Hua Gui, additional

Published
2022
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