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Mingyu Fu,Taiqi Wang,Chenglong Wang 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.6
This paper addresses the fixed-time trajectory tracking control problem of a fully actuated marine surface vehicle with full state constraints and system uncertainties. Acontinuous fixed- time convergence tracking controller is proposed based on fixed-time control and adding a power integrator methods,which achieves system stabilization within a finite time independent of system initial conditions. Moreover, a novel barrier Lyapunov function with a power integrator is designed to ensure the full state tracking error within the constraints. To accurately estimate the lumped disturbances of the vehicle system, a fixed-time disturbance observer is designed to guarantee the settling time of the disturbance observer bounded by a time constant independent of initial estimation errors. Finally, the proposed control scheme is proved to be fixed-time stable via fixed-time Lyapunov stability theorem and the full state constraints can never be violated. A numerical simulation is provided to illustrate the effectiveness and superiority of the proposed control scheme.
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A Tone Mapping Algorithm Based on Multi-scale Decomposition
( Weizhong Li ),( Benshun Yi ),( Taiqi Huang ),( Weiqing Yao ),( Hong Peng ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.4
High dynamic range (HDR) images can present the perfect real scene and rich color information. A commonly encountered problem in practical applications is how to well visualize HDR images on standard display devices. In this paper, we propose a multi-scale decomposition method using guided filtering for HDR image tone mapping. In our algorithm, HDR images are directly decomposed into three layers:base layer, coarse scale detail layer and fine detail layer. We propose an effective function to compress the base layer and the coarse scale detail layer. An adaptive function is also proposed for detail adjustment. Experimental results show that the proposed algorithm effectively accomplishes dynamic range compression and maintains good global contrast as well as local contrast. It also presents more image details and keeps high color saturation.
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Induction of Salivary Gland-Like Tissue by Induced Pluripotent Stem Cells In Vitro
Meng Cen,Huang Shengyuan,Cheng Taiqi,Zhang Xue,Yan Xing 한국조직공학과 재생의학회 2022 조직공학과 재생의학 Vol.19 No.2
Background: To investigate the in vitro induction of salivary gland-like tissue by ips cells in an interferon regulatory factor 6 (IRF6) overexpression and parotid conditioned medium environment. Methods: Urine-derived ips cells were isolated, identified, transfected with IRF6 and cultured in parotid conditioned medium to induce ips cells into salivary gland differentiation, morphological changes of ips cells were observed, CCK-8 was used to determine the cell proliferation efficiency and transcriptome sequencing was used to detect the expression of genes related to parotid gland formation. Results: Immunofluorescence staining showed that the isolated ips cells were positive for NANOG, SSEA4 and OCT4 and had embryonic-like stem cell characteristics; CCK-8 showed that there was no statistical difference in the proliferation efficiency between the IRF6+ induced group and the simple induced group after induction of ips cells into salivary glands. The results of transcriptome sequencing showed that there were a total of 643 differentially expressed genes, including 365 up-regulated genes and 278 down-regulated genes in the IRF6+ induced group compared to the blank control group, and the salivary gland related genes HAPLN1, CCL2, MSX2, ANXA1, CYP11A1, HES1 and LUM were all highly expressed in the IRF6+ induced group. Conclusion: IRF6 promotes salivary gland differentiation in urine-derived iPSCs, and its mechanism of promoting differentiation may be that IRF6 upregulates the expression of HAPLN1, CCL2, MSX2, ANXA1, CYP11A1, HES1 and LUM to promote epithelial differentiation.
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Hierarchical Regression for Single Image Super Resolution via Clustering and Sparse Representation
( Kang Qiu ),( Benshun Yi ),( Weizhong Li ),( Taiqi Huang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.5
Regression-based image super resolution (SR) methods have shown great advantage in time consumption while maintaining similar or improved quality performance compared to other learning-based methods. In this paper, we propose a novel single image SR method based on hierarchical regression to further improve the quality performance. As an improvement to other regression-based methods, we introduce a hierarchical scheme into the process of learning multiple regressors. First, training samples are grouped into different clusters according to their geometry similarity, which generates the structure layer. Then in each cluster, a compact dictionary can be learned by Sparse Coding (SC) method and the training samples can be further grouped by dictionary atoms to form the detail layer. Last, a series of projection matrixes, which anchored to dictionary atoms, can be learned by linear regression. Experiment results show that hierarchical scheme can lead to regression that is more precise. Our method achieves superior high quality results compared with several state-of-the-art methods.
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