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- 저자 : Hongxu Liu (검색결과 5 건)
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Hongxu Liu,Di Wang,Chenang Li,Guangyong Jin 한국광학회 2020 Current Optics and Photonics Vol.4 No.4
We report on the relationship between output current for quadrant photodetector (QPD) and bias voltage in silicon-based p-i-n (positive-intrinsic-negative) QPD examined using millisecond pulse laser (ms pulse laser) irradiation. The mechanism governing the relationship was further studied experimentally. The output current curves were obtained by carrying out QPD under different bias voltages (0~40 V) irradiated by ms pulse laser. Compared to other photodetectors, the relaxation was created in the output current for QPD which is never present in other photodetectors, such as PIN and avalanche photodetector (APD), and the maximum value of relaxation was from 6.8 to 38.0 µA, the amplitude of relaxation increases with bias value. The mechanism behind this relaxation phenomenon can be ascribed to the bias voltage induced Joule heating effect. With bias voltage increasing, the temperature in a QPD device will increase accordingly, which makes carriers in a QPD move more dramatically, and thus leads to the formation of such relaxation.
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Hongxue Li,Liangsheng Liu,Longxin Zhen,Xianyi Xie,Yi Xu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.1
Hydraulically interconnected suspension (HIS) system has theoretically and experimentally been proved to suppress rollover of non-articulated vehicle, but lacking of vibration studies on more complex nonlinear systems such as multi-axle combination vehicle. Hence, this paper presents rollover threshold prediction and active disturbance rejection controller (ADRC) of a tractor semitrailer fitted with HIS based on experimental test to reduce instability of mechanical system. Firstly, a roll resistant verification of a tractor semitrailer fitted with HIS is conducted under a steady circle experiment. Furthermore, the prediction for rollover threshold to extreme maneuver is presented by incorporating robust Kalman filter (RKF) and Back Propagation neural network with genetic algorithm (GA-BP) that are both designed. Finally, an ADRC control is proposed based on control model reduced by applying least square identification and model reduction method. The results are obtained including three aspects: experimental results verify the superior anti-roll performance of vehicle fitted with HIS in comparison with traditional vehicle and are also used to assist the subsequent prediction at high speed. Prediction results highlight that the RKF algorithm performs better filtering accuracy over KF, UKF and PF methods and developed GA-BP supply the higher precision compared with the conventional BP method for the prediction, by which the lateral acceleration threshold is achieved. The results of control show ADRC control strategy obviously has faster response and smaller overshoot than fuzzy PID and regular PID controller for the stability of system.
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Fengqiu Liu,Jianmin Wang,Hongxu Zhang,Pengfei Li 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.1
A new discrete-time neural network is proposed for solving convex quadratic programming problems with hybrid constraints. Based on the projection operator and convex optimization technologies, a single layer discrete-time neural network with monotonic descent dynamic step sizes is constructed. It is proved that the equilibrium points of the discrete-time neural network are globally exponentially convergent to the optimal solutions of the programming problem. Moreover, an algorithm is given based on the proposed neural network and the scheme of backtracking step-size adaptation. Finally, the proposed algorithm is applied to three types of quadratic programming problems and the gas oven identification via a support vector regression algorithm. The numerical experiments are performed to show the correctness and effectiveness of the results in this paper.
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Application of artificial neural network for the critical flow prediction of discharge nozzle
Hong Xu,Tao Tang,Baorui Zhang,Yuechan Liu 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.3
System thermal-hydraulic (STH) code is adopted for nuclear safety analysis. The critical flow model(CFM) is significant for the accuracy of STH simulation. To overcome the defects of current CFMs (lowprecision or long calculation time), a CFM based on a genetic neural network (GNN) has been developedin this work. To build a powerful model, besides the critical mass flux, the critical pressure and criticalquality were also considered in this model, which was seldom considered before. Comparing with thetraditional homogeneous equilibrium model (HEM) and the Moody model, the GNN model can predictthe critical mass flux with a higher accuracy (approximately 80% of results are within the ±20% errorlimit); comparing with the Leung model and the Shannak model for critical pressure prediction, the GNNmodel achieved the best results (more than 80% prediction results within the ±20% error limit). For thecritical quality, similar precision is achieved. The GNN-based CFM in this work is meaningful for the STHcode CFM development
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Functional mechanisms for diabetic nephropathy-associated genetic variants
Hong Xu,Chengxin Gong,Yonghu Xu,Yongfang Fan,Xingzi Liu,Chaopeng Xiong,Luling He,Changle Liu,Shenqiang Rao,Wen Xiao,Lu Ding,Lan Tang,Fangfang Hu,Mengqi Xiong,Mei Yang,Shangdong Liang 한국유전학회 2016 Genes & Genomics Vol.38 No.7
Diabetic nephropathy (DN) is one of the major complications of diabetes. A tremendous amount of genetic variations have been identified to be associated with DN. However, most of them only generate from statistical associations at the DNA level, generally without direct functional evidence regarding their association mechanisms underlying DN. Based on the publicly available datasets and resources, this study performed integrative analyses (expression quantitative trait loci analysis, differential gene expression analysis and functional prediction analysis) to detect the molecular functional mechanisms underlying the associations for DN. Among 150 selected (P\E-4) genetic associations that were archived in the public databases, two single nucleotide polymorphisms (SNPs) (rs3135377 and rs9469220) have been found to act as cis-effect regulators of the ‘‘identified’’ gene (HLADRA and HLA-DRB1). These eQTL genes have differential expression signals in the DN-associated cell groups. These SNPs were predicted as regulatory sites by utilizing online prediction tools. Our data suggest potential mechanistic links underlying the association between DN and two identified SNPs. These results could help us to have a deeper understanding of the functional relevance of genetic variants with susceptibility to DN, which is useful for pursuit of in-depth validation studies to dissect their involvements and molecular functional mechanisms in DN.
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