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5,045 results on '"Li, Hongliang"'

204. New Nonconforming Elements for Linear Strain Gradient Elastic Model

Author

Li, Hongliang, Ming, Pingbing, and Shi, Zhong-ci

Subjects
Mathematics - Numerical Analysis
Abstract

Based on a new H$^2-$Korn's inequality, we propose new nonconforming elements for the linear strain gradient elastic model. The first group of elements are H$^1-$conforming but H$^2-$nonconforming. The tensor product NTW element [Tai:2001] and the tensor product Specht triangle are two typical representatives. The second element is based on Morley's triangle with a modified elastic strain energy. We proved new interpolation error estimates for all these elements, which are key to prove uniform rates of convergence for the proposed elements. Numerical results are reported and they are consistent with the theoretical prediction., Comment: 1 figure

Published
2018

238. A Perceptually Weighted Rank Correlation Indicator for Objective Image Quality Assessment

Author

Wu, Qingbo, Li, Hongliang, Meng, Fanman, and Ngan, King N.

Subjects
Computer Science - Computer Vision and Pattern Recognition, I.4.0, I.4.3
Abstract

In the field of objective image quality assessment (IQA), the Spearman's $\rho$ and Kendall's $\tau$ are two most popular rank correlation indicators, which straightforwardly assign uniform weight to all quality levels and assume each pair of images are sortable. They are successful for measuring the average accuracy of an IQA metric in ranking multiple processed images. However, two important perceptual properties are ignored by them as well. Firstly, the sorting accuracy (SA) of high quality images are usually more important than the poor quality ones in many real world applications, where only the top-ranked images would be pushed to the users. Secondly, due to the subjective uncertainty in making judgement, two perceptually similar images are usually hardly sortable, whose ranks do not contribute to the evaluation of an IQA metric. To more accurately compare different IQA algorithms, we explore a perceptually weighted rank correlation indicator in this paper, which rewards the capability of correctly ranking high quality images, and suppresses the attention towards insensitive rank mistakes. More specifically, we focus on activating `valid' pairwise comparison towards image quality, whose difference exceeds a given sensory threshold (ST). Meanwhile, each image pair is assigned an unique weight, which is determined by both the quality level and rank deviation. By modifying the perception threshold, we can illustrate the sorting accuracy with a more sophisticated SA-ST curve, rather than a single rank correlation coefficient. The proposed indicator offers a new insight for interpreting visual perception behaviors. Furthermore, the applicability of our indicator is validated in recommending robust IQA metrics for both the degraded and enhanced image data., Comment: This paper has been submitted to IEEE Transactions on Image Processing

Published
2017
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239. Seamounts Enhance the Local Emission of CO2 in the Northern South China Sea.

Author

Zhang, Gong, Han, Bo, Yang, Qinghua, Zhu, Xueming, Wang, Xiaojing, He, Honge, Li, Hongliang, Wang, Xinyang, Xie, Wei, and Chen, Dake

Abstract

The South China Sea is a typical marginal sea characterized by the presence of numerous seamounts. However, the effect of seamounts on the air‐sea CO2 flux has not yet been well studied. In September 2021, the air‐sea CO2 flux was measured directly using eddy covariance (EC), and discrete waterside sampling was conducted. The results indicate that the northern South China Sea is a source of atmospheric CO2. Furthermore, EC measurements show that the seamount emits CO2 at an average rate of 0.34 mmol m−2 hr−1, nearly double that of non‐seamount areas. We suggest that the upwelling around the seamount transports deep water rich in dissolved inorganic carbon to the upper ocean, increasing the partial pressure of CO2 there. In addition, the increase in nutrients caused by the upwelling would increase the concentration of chlorophyll‐a, resulting in a productive area that emits CO2. Plain Language Summary: The South China Sea (SCS) serves as a minor CO2 source, and the air‐sea CO2 flux in its northern region demonstrates challenging spatiotemporal variations. In our investigation, we conducted underway assessments in the northern SCS and validated its emission of CO2, particularly in the vicinity of seamount ocean zones. CO2 emissions may have been intensified by the upward movement of seawater surrounding the seamount region. Key Points: The northern South China Sea emitted CO2 into the atmosphere at a mean rate of 0.28 mmol m−2 hr−1 in September 2021The CO2 flux almost doubled as the seamount was approached, indicating an increase in CO2 emissions near the seamountUpwelling releases high dissolved inorganic carbon, which increases the partial pressure of CO2 on the sea surface around the seamount [ABSTRACT FROM AUTHOR]

Published
2024
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240. Carbon Nanospheres Loaded with Ir Single Atoms: Enhancing the Activity toward Formic Acid Oxidation by Increasing the Porosity.

Author

Jeskey, Jacob, Ding, Yong, Chen, Yidan, Hood, Zachary D., Li, Hongliang, Sterbinsky, George E., and Xia, Younan

Subjects
OXIDATION of formic acid, SURFACE area, IRIDIUM, ATOMS, CATALYSTS
Abstract

Theoretically, single‐atom catalysts (SACs) offer 100 % atom utilization, making them strong candidates to replace expensive nanoparticles for catalysis. However, the structural supports used to anchor the SACs dramatically reduce the utilization efficiency of atoms (i. e., the percent of atoms actually accessible by reactants) by either encapsulating the SACs completely or creating severe diffusion limitation. Either of which leads to an overall low atom utilization and thus poor electrocatalytic activity similar to that of nanoparticles. In addressing this issue, we systematically investigated how the porous structure of carbon nanospheres affects the activity of Ir‐SACs toward formic acid oxidation (FAO). Specifically, we utilized a kinetically‐controlled growth strategy to produce uniform carbon nanospheres featuring yolk‐shell, mesoporous, and hollow structures with Ir‐SACs loaded throughout the structure. At a high specific surface area of 441 m2 g−1 and exposed metal content of 1.82 wt %, the Ir‐SACs based on mesoporous carbon nanospheres showed a remarkable FAO peak current density of 30.6 mA cm−2, which was 283 and 46 times greater when benchmarked against the catalysts based on solid carbon nanospheres and 20 wt % Ir/C, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
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241. Influence of Ce 3+ Doping on Photoluminescence Properties and Stability of Cs 4 SnBr 6 Zero-Dimensional Perovskite.

Author

Lu, Xinye, Wu, Haixia, Xu, Jisheng, Chen, Jianni, Huang, Yaqian, Li, Hongliang, Song, Jie, and Huang, Rui

Subjects
OPTICAL properties, BINDING energy, LIGHT intensity, PEROVSKITE, EXCITON theory
Abstract

Zero-dimensional tin-based halide perovskites have garnered considerable interest owing to their remarkable optical properties, including broad-band emission, high photoluminescence (PL) efficiency, and low self-absorption. Nevertheless, enhancing the PL efficiency and stability of these materials remains a pressing challenge. In this study, the enhancement of PL and stability in Cs4SnBr6 zero-dimensional perovskite was investigated through Ce3+ doping. Our experimental results demonstrate that the incorporation of Ce3+ can significantly boost the light emission intensity from self-trapped excitons (STEs) in Cs4SnBr6, achieving over a 150% increase compared to the undoped sample, with a PL quantum yield of approximately 64.7%. Moreover, the thermal stability of the corresponding doped sample is markedly enhanced. Through comprehensive analyses, including X-ray diffraction, energy-dispersive spectroscopy, time-resolved PL, and temperature-dependent PL measurements, we elucidate that the enhanced light emission is attributed to the distortion of the [SnBr6]4− octahedral structure induced by Ce3+ doping, which strengthens electron–phonon coupling and elevates the binding energy of STEs. [ABSTRACT FROM AUTHOR]

Published
2024
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243. Few-Shot Segmentation via Complementary Prototype Learning and Cascaded Refinement

Author

Luo, Hanxiao, Li, Hui, Wu, Qingbo, Li, Hongliang, Ngan, King Ngi, Meng, Fanman, Xu, Linfeng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ma, Huimin, editor, Wang, Liang, editor, Zhang, Changshui, editor, Wu, Fei, editor, Tan, Tieniu, editor, Wang, Yaonan, editor, Lai, Jianhuang, editor, and Zhao, Yao, editor

Published
2021
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244. Single Image Deraining via Multi-scale Gated Feature Enhancement Network

Author

Luo, Hao, Luo, Hanxiao, Wu, Qingbo, Ngan, King Ngi, Li, Hongliang, Meng, Fanman, Xu, Linfeng, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Zhai, Guangtao, editor, Zhou, Jun, editor, Yang, Hua, editor, An, Ping, editor, and Yang, Xiaokang, editor

Published
2021
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246. Face Detection of Innovation Base Based on Faster RCNN

Author

Guan, Haixing, Li, Hongliang, Li, Rongqiang, Qi, Mingyang, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Abawajy, Jemal, editor, Xu, Zheng, editor, Atiquzzaman, Mohammed, editor, and Zhang, Xiaolu, editor

Published
2021
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247. ICDAR 2021 Competition on Script Identification in the Wild

Author

Das, Abhijit, Ferrer, Miguel A., Morales, Aythami, Diaz, Moises, Pal, Umapada, Impedovo, Donato, Li, Hongliang, Yang, Wentao, Ota, Kensho, Yao, Tadahito, Hung, Le Quang, Cuong, Nguyen Quoc, Kim, Seungjae, Gattal, Abdeljalil, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Lladós, Josep, editor, Lopresti, Daniel, editor, and Uchida, Seiichi, editor

Published
2021
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248. Towards Fast, Accurate and Compact Online Handwritten Chinese Text Recognition

Author

Peng, Dezhi, Xie, Canyu, Li, Hongliang, Jin, Lianwen, Xie, Zecheng, Ding, Kai, Huang, Yichao, Wu, Yaqiang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Lladós, Josep, editor, Lopresti, Daniel, editor, and Uchida, Seiichi, editor

Published
2021
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249. Improving Machine Understanding of Human Intent in Charts

Author

Wu, Sihang, Xie, Canyu, Huang, Yuhao, Tang, Guozhi, Liao, Qianying, Wang, Jiapeng, Chen, Bangdong, Li, Hongliang, Chang, Xinfeng, Li, Hui, Ding, Kai, Huang, Yichao, Jin, Lianwen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Lladós, Josep, editor, Lopresti, Daniel, editor, and Uchida, Seiichi, editor

Published
2021
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