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Your search keyword '"Xu, Yunjing"' showing total 22 results
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22 results on '"Xu, Yunjing"'

8. CANVuS: Context-Aware Network Vulnerability Scanning

Author

Xu, Yunjing, Bailey, Michael, Vander Weele, Eric, Jahanian, Farnam, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Jha, Somesh, editor, Sommer, Robin, editor, and Kreibich, Christian, editor

Published
2010
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9. Chemical peeling with 35% glycolic acid for the treatment of disseminated facial verruca plana: A randomized, split‐face, evaluator‐blinded trial

Author

Liu, Zhenfeng, primary, Ai, Jing, additional, Zhu, Zhenlai, additional, Huang, Lixia, additional, Yi, Zhen, additional, Wu, Linshan, additional, Xu, Yunjing, additional, Zhu, Dingheng, additional, Li, Huizhong, additional, Yan, Yunling, additional, Zhang, Lichun, additional, Zhong, Xinyi, additional, and Yang, Bin, additional

Published
2022
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10. Property‐based shadow detection and removal method for licence plate image

Author

Yuanming Zhang, Xu Yunjing, Shufang Lu, Fei Gao, and Ge Yisu

Subjects
Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020206 networking & telecommunications, Image processing, 02 engineering and technology, Filter (signal processing), Edge (geometry), GeneralLiterature_MISCELLANEOUS, Edge detection, Object detection, Image (mathematics), Signal Processing, Shadow, 0202 electrical engineering, electronic engineering, information engineering, Median filter, 020201 artificial intelligence & image processing, Computer vision, Computer Vision and Pattern Recognition, Artificial intelligence, Electrical and Electronic Engineering, business, Software, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Shadow detection and removal is a classic research in the field of image processing. This work aims to address the problem of shadow detection and removal for licence plate. The shadow detection and removal method based on inherent properties of licence plate is presented in this study. First, an S–V-channel-property-based shadow detection algorithm is investigated to extract the background-shaded area of licence plate. Afterwards, a shadow edge location algorithm is proposed to detect the complete shadow edge. Then, the shadow is removed on H, S, and V channels with different strategies, respectively. Also, a filter-based median filtering algorithm is employed to remove the pseudo-edge. Finally, the proposed method is verified through comparing with other generic shadow detection and removal methods quantitatively and qualitatively.

Published
2020

17. Small is better

Author

Xu, Yunjing, primary, Bailey, Michael, additional, Noble, Brian, additional, and Jahanian, Farnam, additional

Published
2013
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20. Correction: Hui, Y., et al. Spatio-Temporal Validation of AIRS CO 2 Observations Using GAW, HIPPO and TCCON. Remote Sens. 2020, 12 , 3583.

Author

Yang, Hui, Feng, Gefei, Xiang, Ru, Xu, Yunjing, Qin, Yong, and Li, Songnian

Subjects
CARBON dioxide, DATA libraries, ATMOSPHERIC composition
Abstract

TCCON Data from Darwin (AU), Release GGG2014.R0 (Version GGG2014.R0) [Data set]. Darwin and Wollongong TCCON stations are supported by ARC grants DP160100598, LE0668470, DP140101552, DP110103118 and DP0879468. The TCCON data were obtained from the TCCON Data Archive hosted by CaltechDATA at https://tccondata.org (accessed on 26 February 2021). [Extracted from the article]

Published
2021
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21. Spatio-Temporal Validation of AIRS CO 2 Observations Using GAW, HIPPO and TCCON.

Author

Yang, Hui, Feng, Gefei, Xiang, Ru, Xu, Yunjing, Qin, Yong, and Li, Songnian

Subjects
ATMOSPHERIC carbon dioxide, FOURIER transform spectrometers, SURFACE of the earth, AIR, CARBON dioxide
Abstract

Carbon dioxide (CO2) is a significant atmospheric greenhouse gas and its concentrations can be observed by in situ surface stations, aircraft flights and satellite sensors. This paper investigated the ability of the CO2 satellite observations to monitor, analyze and predict the horizontal and vertical distribution of atmospheric CO2 concentration at global scales. CO2 observations retrieved by an Atmospheric Infrared Sounder (AIRS) were inter-compared with the Global Atmosphere Watch Program (GAW) and HIAPER Pole-to-Pole Observations (HIPPOs), with reference to the measurements obtained using high-resolution ground-based Fourier Transform Spectrometers (FTS) in the Total Carbon Column Observing Network (TCCON) from near-surface level to the mid-to-high troposphere. After vertically integrating the AIRS-retrieved values with the column averaging kernels of TCCON measurements, the AIRS observations are spatio-temporally compared with HIPPO-integrated profiles in the mid-to-high troposphere. Five selected GAW stations are used for comparisons with TCCON sites near the surface of the Earth. The results of AIRS, TCCON (5–6 km), GAW and TCCON (1 km) CO2 measurements from 2007 to 2013 are compared, analyzed and discussed at their respective altitudes. The outcomes indicate that the difference of about 3.0 ppmv between AIRS and GAW or other highly accurate in situ surface measurements is mainly due to the different vertical altitudes, rather than the errors in the AIRS. The study reported here also explores the potential of AIRS satellite observations for analyzing the spatial distribution and seasonal variation of CO2 concentration at global scales. [ABSTRACT FROM AUTHOR]

Published
2020
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22. Characterizing and Mitigating Virtual Machine Interference in Public Clouds.

Author

Xu, Yunjing

Subjects
Cloud, Interference, Performance, Security, Virtualization
Abstract

This dissertation studies the mitigation of the performance and security interference between guest virtual machines (VMs) in public clouds. The goals are to characterize the impact of VM interference, uncover the root cause of the negative impact, and design novel techniques to mitigate such impact. The central premise of this dissertation is that by identifying the shared resources that cause the VM interference and by exploiting the properties of the workloads that share these resources with adapted scheduling policies, public cloud services can reduce conflicts of resource usage between guests and hence mitigate their interference. Current techniques for conflict reduction and interference mitigation overlook the virtualization semantic gap between the cloud host infrastructure and guest virtual ma- chines and the unique challenges posed by the multi-tenancy service model necessary to support public cloud services. This dissertation deals with both performance and security interference problems. It characterizes the impact of VM interference on inter-VM network latency using live measurements in a real public cloud and studies the root cause of the negative impact with controlled experiments on a local testbed. Two methods of improving the inter-VM net- work latency are explored. The first approach is a guest-centric solution that exploits the properties of application workloads to avoid interference without any support from the underlying host infrastructure. The second approach is a host-centric solution that adapts the scheduling policies for the contented resources that cause the interference without guest cooperation. Similarly, the characteristics of cache-based cross-VM attacks are studied in detail using both live cloud measurements and testbed experiments. To mitigate this security interference, a partition-based VM scheduling system is designed to reduce the effectiveness of these cache-based attacks.

Published
2014

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