Institution
Civil Aviation University of China
Education•Tianjin, China•
About: Civil Aviation University of China is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Air traffic control & Civil aviation. The organization has 5647 authors who have published 4559 publications receiving 29825 citations. The organization is also known as: Zhōngguó Mínháng Dàxué.
Topics: Air traffic control, Civil aviation, Hilbert space, Variational inequality, Fault (power engineering)
Papers published on a yearly basis
Papers
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05 Dec 2011TL;DR: Wang et al. as mentioned in this paper used a Gaussian-PSF model to restore the finger-vein images degraded by the camera lens, and two depth PSF models were built to further restore the images considering the optical properties of skin layers.
Abstract: Recently, finger-vein recognition has been studied extensively for personal identification. Since veins exist inside the finger, the finger-vein images are often not in high quality due to light scattering and absorption of the skin tissue. According to the optical properties of the biological tissues, the multilayered human skin is a kind of inhomogeneous medium, and different skin layers hold different optical properties. Therefore, this paper focuses on finger-vein image restoration considering the layered skin structure. First a Gaussian-PSF model is used to restore the finger-vein images degraded by the camera lens. Then, two depth-PSF models are built to further restore the images considering the optical properties of skin layers. Third, a fused finger-vein image is generated by the combination of the depth-depended restored images. Finally, experimental results show that the proposed method exhibits an exciting performance in finger-vein image quality improvement.
17 citations
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TL;DR: Sources contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period, and provide useful tools to better understand PM pollution status and to develop effective pollution control strategies.
Abstract: Long-term and synchronous monitoring of PM10 and PM2.5 was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models (PMF2, ME2-2way and ME2-3way). Consistent results were found: the primary source categories contributed 63.4% (PMF2), 64.8% (ME2-2way) and 66.8% (ME2-3way) to PM10, and contributed 60.9% (PMF2), 65.5% (ME2-2way) and 61.0% (ME2-3way) to PM2.5. Secondary sources contributed 31.8% (PMF2), 32.9% (ME2-2way) and 31.7% (ME2-3way) to PM10, and 35.0% (PMF2), 33.8% (ME2-2way) and 36.0% (ME2-3way) to PM2.5. The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment (SDA) was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east (ENE) contributed the highest to both PM10 (12.7%) and PM2.5 (9.7%) in Chengdu, followed by the crustal dust from south-east (SE) for PM10 (9.8%) and secondary nitrate & secondary organic carbon from ENE for PM2.5 (9.6%). Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and to develop effective pollution control strategies.
17 citations
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TL;DR: In this article, the authors studied the surface morphology of a spherical polyelectrolyte brush in the presence of trivalent counterions using molecular dynamics simulations and found a nonmonotonic dependence of surface morphology on electrostatic strength, which represents clearly the electrostatic correlation effect mediated by the multivalent counterions.
Abstract: We study surface morphologies of a spherical polyelectrolyte brush in the presence of trivalent counterions using molecular dynamics simulations. Solvent quality and electrostatic interaction strength are varied to generate a series of structures. Through a careful analysis on snapshots of morphologies, shape factor of tethered chains, and monomer–monomer pair correlation function we find a nonmonotonic dependence of surface morphology on electrostatic strength, which represents clearly the electrostatic correlation effect mediated by the multivalent counterions. Due to the very importance of counterions, we further study the correlation effect by classifying counterions into four states, calculating the monomer–counterion pair correlation function and diffusion coefficient of counterions. Our simulation results clearly demonstrate that ordered patterns can be induced by the electrostatic correlation effect in the presence of trivalent counterions, which is absent in the system with monovalent ions. Also,...
17 citations
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TL;DR: In this paper, the initial concentration of Cu(NO{sub 3}sub 2} solution was an important parameter for determining whether CuO nanoparticles assembled into corn-like or flower-like structures.
17 citations
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TL;DR: In this article, the authors proposed two different methods for solving pseudomonotone and strongly pseudo-monotone equilibrium problems, and examined these methods as an extension and improvement of the Pop...
Abstract: In this paper, we proposed two different methods for solving pseudomonotone and strongly pseudomonotone equilibrium problems. We can examine these methods as an extension and improvement of the Pop...
17 citations
Authors
Showing all 5670 results
Name | H-index | Papers | Citations |
---|---|---|---|
Lei Zhang | 130 | 2312 | 86950 |
Tao Wang | 97 | 2720 | 55280 |
Peide Liu | 54 | 300 | 10339 |
Xuan Wang | 53 | 317 | 15482 |
Zheng Yan | 47 | 420 | 8786 |
Weidong Liu | 46 | 275 | 9746 |
Zengqiang Chen | 43 | 543 | 7595 |
Zhiming Li | 42 | 212 | 8336 |
Yao Sun | 40 | 208 | 5820 |
Li Li | 37 | 142 | 7563 |
Mark Hansen | 36 | 201 | 4355 |
Richard J. Langley | 35 | 302 | 5174 |
Sang-Bing Tsai | 34 | 131 | 2618 |
Mingchao Wang | 33 | 117 | 3641 |
Xijun Liu | 32 | 92 | 3372 |