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Institution

University of Macau

EducationMacao, Macau, China
About: University of Macau is a education organization based out in Macao, Macau, China. It is known for research contribution in the topics: Population & Control theory. The organization has 6636 authors who have published 18324 publications receiving 327384 citations. The organization is also known as: UM & UMAC.


Papers
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Journal ArticleDOI
TL;DR: Experimental results show the superiority of the region kernel method over the classical point kernel methods.
Abstract: This paper proposes a region kernel to measure the region-to-region distance similarity for hyperspectral image (HSI) classification. The region kernel is designed to be a linear combination of multiscale box kernels, which can handle the HSI regions with arbitrary shape and size. Integrating labeled pixels and labeled regions, we further propose a region-kernel-based support vector machine (RKSVM) classification framework. In RKSVM, three different composite kernels are constructed to describe the joint spatial–spectral similarity. Particularly, we design a desirable stack composite kernel that consists of the point-based kernel, the region-based kernel, and the cross point-to-region kernel. The effectiveness of the proposed RKSVM is validated on three benchmark hyperspectral data sets. Experimental results show the superiority of our region kernel method over the classical point kernel methods.

136 citations

Journal ArticleDOI
TL;DR: A novel algorithm named Double Transfer Boosting (DTB) is introduced to improve the performance of cross-company defects prediction by reducing negative samples in CC data and demonstrating that it could be an effective model for early software defects detection.
Abstract: Context Software defect prediction has been widely studied based on various machine-learning algorithms. Previous studies usually focus on within-company defects prediction (WCDP), but lack of training data in the early stages of software testing limits the efficiency of WCDP in practice. Thus, recent research has largely examined the cross-company defects prediction (CCDP) as an alternative solution. Objective However, the gap of different distributions between cross-company (CC) data and within-company (WC) data usually makes it difficult to build a high-quality CCDP model. In this paper, a novel algorithm named Double Transfer Boosting (DTB) is introduced to narrow this gap and improve the performance of CCDP by reducing negative samples in CC data. Method The proposed DTB model integrates two levels of data transfer: first, the data gravitation method reshapes the whole distribution of CC data to fit WC data. Second, the transfer boosting method employs a small ratio of labeled WC data to eliminate negative instances in CC data. Results The empirical evaluation was conducted based on 15 publicly available datasets. CCDP experiment results indicated that the proposed model achieved better overall performance than compared CCDP models. DTB was also compared to WCDP in two different situations. Statistical analysis suggested that DTB performed significantly better than WCDP models trained by limited samples and produced comparable results to WCDP with sufficient training data. Conclusions DTB reforms the distribution of CC data from different levels to improve the performance of CCDP, and experimental results and analysis demonstrate that it could be an effective model for early software defects detection.

136 citations

Journal ArticleDOI
TL;DR: In this article, the authors argue that better developed home country institutional environment promotes emerging market firms' expansion to foreign markets more advanced than the home country, while institutional instability in the homecountry reduces this propensity.

136 citations

Journal ArticleDOI
TL;DR: The proposed 3D HPGA is expected to provide an important platform that can promote the development of 3D topological porous systems in a range of energy storage and generation fields.
Abstract: New and novel 3D hierarchical porous graphene aerogels (HPGA) with uniform and tunable meso-pores (e.g., 21 and 53 nm) on graphene nanosheets (GNS) were prepared by a hydrothermal self-assembly process and an in-situ carbothermal reaction. The size and distribution of the meso-pores on the individual GNS were uniform and could be tuned by controlling the sizes of the Co3O4 NPs used in the hydrothermal reaction. This unique architecture of HPGA prevents the stacking of GNS and promises more electrochemically active sites that enhance the electrochemical storage level significantly. HPGA, as a lithium-ion battery anode, exhibited superior electrochemical performance, including a high reversible specific capacity of 1100 mAh/g at a current density of 0.1 A/g, outstanding cycling stability and excellent rate performance. Even at a large current density of 20 A/g, the reversible capacity was retained at 300 mAh/g, which is larger than that of most porous carbon-based anodes reported, suggesting it to be a promising candidate for energy storage. The proposed 3D HPGA is expected to provide an important platform that can promote the development of 3D topological porous systems in a range of energy storage and generation fields.

136 citations

Journal ArticleDOI
Qingsong Xu1
TL;DR: Wang et al. as mentioned in this paper proposed a continuous third-order integral terminal sliding mode control (3-ITSMC) strategy dedicated to motion tracking control of a piezoelectric-driven nanopositioning system.
Abstract: This paper presents the design and testing of a novel continuous third-order integral terminal sliding mode control (3-ITSMC) strategy dedicated to motion tracking control of a piezoelectric-driven nanopositioning system. In comparison with the available sliding mode controllers, the significant improvement of the proposed controller lies in the fact that it completely eliminates the chattering effect, achieves a finite-time convergence, and produces a higher sliding mode precision. The model uncertainty involving the hysteresis effect is estimated by the perturbation estimation technique. Higher order derivatives of the position are generated by using a robust exact differentiator. Based on an integral terminal type of sliding surface, a third-order sliding mode precision is obtained by resorting to the third-order supertwisting algorithm. The convergence and stability have been proved in theory. The performance improvement of the developed controller versus the conventional second-order and third-order sliding mode controllers is validated by carrying out both simulation and experimental studies. Results demonstrate that the proposed 3-ITSMC controller provides quicker transient response speed and smaller steady-state error for the piezoelectric nanopositioning system along with a better robustness against model uncertainty and external disturbance.

135 citations


Authors

Showing all 6766 results

NameH-indexPapersCitations
Henry T. Lynch13392586270
Chu-Xia Deng12544457000
H. Vincent Poor109211667723
Peng Chen10391843415
George F. Gao10279382219
MengChu Zhou96112436969
Gang Li9348668181
Rob Law8171431002
Zongjin Li8063022103
Han-Ming Shen8023727410
Heng Li7974523385
Lionel M. Ni7546628770
C. L. Philip Chen7448220223
Chun-Su Yuan7239721089
Joao P. Hespanha7241839004
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202345
2022307
20212,579
20202,357
20192,075
20181,714