The investigation of a new fast timing system based on DRS4 waveform sampling system

Jinda Chen,Chengming Du,Jinda Chen,Herun Yang,Jie kong,Haibo Yang,Peng Ma,Guozhu Shi,limin Duan,Zhengguo Hu 한국원자력학회 2019 Nuclear Engineering and Technology Vol.51 No.2

In the study of nuclear structure, the fast timing technique can be used to measure the lifetime of excitedstates. In the paper, we have developed a new fast timing system, which is made up of two LaBr3:Cedetectors and a set of waveform sampling system. The sampling system based on domino ring samplerversion 4 chip (DRS4) can digitize and store the waveform information of detector signal, with a smallervolume and higher timing accuracy, and the waveform data are performed by means of digital waveformanalysis methods. The coincidence time resolution of the fast timing system for two annihilation 511 keVg photon is 200ps (FWHM), the energy resolution is 3.5%@511 keV, and the energy linear response in thelarge dynamic range is perfect. Meanwhile, to verify the fast timing performance of the system, the152Gd-21þ state form bþ decay of 152Eu source is measured. The measured lifetime is 45.3(±5.0)ps, veryclose to the value of the National Nuclear Data Center (NNDC: 46.2((±3.9)ps). The experimental resultsindicate that the fast timing system is capable of measuring the lifetime of dozens of ps. Therefore, thesystem can be widely used in the research of the fast timing technology.

Particle swarm optimization of fuzzy PI control for PMSMs

Shijiao Wang,Chengming Jiang,Qunzhang Tu,Huidong Shu,Changlin Zhu 전력전자학회 2023 JOURNAL OF POWER ELECTRONICS Vol.23 No.10

To solve the problems of the slow response speed and poor adaptive capability of a permanent magnet synchronous motor (PMSM) under a fuzzy PI control system, a particle swarm optimization (PSO) fuzzy PI method is proposed as a parameter optimization control scheme in this paper. The proportion factor and quantization factor in fuzzy PI control are optimized through the iteration of a PSO algorithm. In addition, the parameters of the PI control are intelligently adjusted through thefuzzy control. A simulation model is developed using MATLAB/Simulink, and an experimental platform is constructed to verify the proposed algorithm. Test results demonstrate that the fuzzy PI control optimized by PSO improves the convergence accuracy of a system and reduces the speed ring overshoot to a minimum. Furthermore, the PSO-optimized fuzzy PI control exhibits characteristics such as small torque ripple, strong anti-interference capability, and fast dynamic response.

CSI-based human sensing using model-based approaches: a survey

Zhengjie Wang,Zehua Huang,Chengming Zhang,Wenwen Dou,Yinjing Guo,Da Chen 한국CDE학회 2021 Journal of computational design and engineering Vol.8 No.2

Currently, human sensing draws much attention in the field of ubiquitous computing, and human sensing based on WiFi CSI (channel state information) becomes a hot research topic due to the easy deployment and availability of WiFi devices. Although various human sensing applications based on the CSI signal model are emerging, the model-based approach has not been studied thoroughly. This paper provides a comprehensive survey of the latest model-based human sensing methods and their applications. First, the CSI signal and framework of model-based human sensing methods are introduced. Then, related models and fundamental signal preprocessing techniques are described. Next, typical human sensing applications are investigated, and the crucial characteristics are summarized. Finally, the advantages, limitations, and future research trends of model-based human sensing methods are concluded in this paper.

Recognition of damage pattern and evolution in CFRP cable with a novel bonding anchorage by acoustic emission

Wu, Jingyu,Lan, Chengming,Xian, Guijun,Li, Hui Techno-Press 2018 Smart Structures and Systems, An International Jou Vol.21 No.4

Carbon fiber reinforced polymer (CFRP) cable has good mechanical properties and corrosion resistance. However, the anchorage of CFRP cable is a big issue due to the anisotropic property of CFRP material. In this article, a high-efficient bonding anchorage with novel configuration is developed for CFRP cables. The acoustic emission (AE) technique is employed to evaluate the performance of anchorage in the fatigue test and post-fatigue ultimate bearing capacity test. The obtained AE signals are analyzed by using a combination of unsupervised K-means clustering and supervised K-nearest neighbor classification (K-NN) for quantifying the performance of the anchorage and damage evolutions. An AE feature vector (including both frequency and energy characteristics of AE signal) for clustering analysis is proposed and the under-sampling approaches are employed to regress the influence of the imbalanced classes distribution in AE dataset for improving clustering quality. The results indicate that four classes exist in AE dataset, which correspond to the shear deformation of potting compound, matrix cracking, fiber-matrix debonding and fiber fracture in CFRP bars. The AE intensity released by the deformation of potting compound is very slight during the whole loading process and no obvious premature damage observed in CFRP bars aroused by anchorage effect at relative low stress level, indicating the anchorage configuration in this study is reliable.

Large-Scale Image Retrieval with Bag-of-Words and k-NN Re-Ranking

Pang Haibo,Liu Chengming,Zhao Zhe,Li Zhanbo 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.6

Image retrieval methods have been significantly developed in the last decade. The BOW (Bag-of-words) model lacks spatial information. Some methods stem from BOW approach which is recently extended to a vector aggregation model. Most of them are either too strict or too loose so that they are only effective in limited cases. In this study, we present a novel feature extraction method for image retrieval. We acquire the gradients features from the p.d.f (Probability density function) because of essentially representing the image. We construct the features by the histogram of the oriented p.d.f gradients via aggregation of the orientation codes. Then, we adopt the PCA (Principal component analysis) method to reduce the dimensionality of BOW. Furthermore, we introduce a novel and robust re-ranking method with the k-nearest neighbors. We estimate our method using various datasets. In the experiments on scene retrieval, the proposed method is efficient, and exhibits superior performances compared to the other existing methods.

Control Over the Branched Structures of Platinum Nanocrystals for Electrocatalytic Applications

Ma, Liang,Wang, Chengming,Gong, Ming,Liao, Lingwen,Long, Ran,Wang, Jinguo,Wu, Di,Zhong, Wei,Kim, Moon J.,Chen, Yanxia,Xie, Yi,Xiong, Yujie American Chemical Society 2012 ACS NANO Vol.6 No.11

<P>Structural control of branched nanocrystals allows tuning two parameters that are critical to their catalytic activitythe surface-to-volume ratio, and the number of atomic steps, ledges, and kinks on surface. In this work, we have developed a simple synthetic system that allows tailoring the numbers of branches in Pt nanocrystals by tuning the concentration of additional HCl. In the synthesis, HCl plays triple functions in tuning branched structures <I>via</I> oxidative etching: (i) the crystallinity of seeds and nanocrystals; (ii) the number of {111} or {100} faces provided for growth sites; (iii) the supply kinetics of freshly formed Pt atoms in solution. As a result, tunable Pt branched structurestripods, tetrapods, hexapods, and octopods with identical chemical environmentcan be rationally synthesized in a single system by simply altering the etching strength. The controllability in branched structures enables to reveal that their electrocatalytic performance can be optimized by constructing complex structures. Among various branched structures, Pt octopods exhibit particularly high activity in formic acid oxidation as compared with their counterparts and commercial Pt/C catalysts. It is anticipated that this work will open a door to design more complex nanostructures and to achieve specific functions for various applications.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancac3/2012/ancac3.2012.6.issue-11/nn304237u/production/images/medium/nn-2012-04237u_0010.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/nn304237u'>ACS Electronic Supporting Info</A></P>

Gesture Recognition Based on Hexagonal Structure Histograms of Oriented Gradients

Pang Haibo,Liu Chengming,Zhao Zhe,Zhang Shuyan 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.8

Feature extraction methods of image directly affect the feature recognition results based on computer vision-based gesture recognition. This paper proposed a gesture feature extraction method of hexagonal structure, which is based on histograms of oriented gradients. This paper transforms the quadrilateral structure into hexagonal structure of the image and defines hexagonal block structure. Using different structures, different sizes of hexagonal blocks extract gesture feature and recognize on different sizes image. Experimental results show that hexagonal structure block is more appropriate than conventional histograms of oriented gradients structure block, the hexagonal structure histograms of oriented gradients feature extraction method is more efficient than the square and circular structure histograms of oriented gradients feature, using gentle_adaboost classifier achieved higher recognition rate.

Polarization Error Analysis of an All-Optical Fibre Small Current Sensor for Partial Discharge

Gaifang Xin,Jun Zhu,Chengming Luo,Jing Tang,Wei Li,Yuxin Cao,Haiyan Xu 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.5

In view of the characteristics of the small amplitude of a current signal, an all-optical fi bre small-current sensor for partial discharge is devised. A novel type of sensor head with electric winding light is proposed. A complete optical model of the optical fi bre current sensor is developed under the eff ect of polarization error factors. In addition, the eff ect of polarization error factors on the optical fi bre sensing system is simulated. The simulation results show that as the extinction ratio increases, the output relative error of the optical fi bre small-current sensor decreases. The eff ect of the fast and slow axis misalignment errors of a polarizing beam splitter is similar to the eff ect of the alignment angle error of an optical fi bre polarizer. It is observed that the relative error curve follows a sine function. Meanwhile, the output relative error increases fi rst and then oscillates with an increase in the linear birefringence. We conclude that the linear birefringence of the sensing optical fi bre is the main error source for the measurement accuracy of the sensing system. Finally, an experimental system for the optical fi bre small-current sensor is implemented. The experimental results show that the eff ect of linear birefringence on the fi bre current sensing system can be suppressed by introducing a large amount of circular birefringence into the sensing optical fi bre. The theoretical mechanism of these errors is analysed, which can be applied to implement corresponding measures to reduce the eff ect of error factors on the sensing system and further improve the measurement accuracy of the optical fi bre small-current sensor.

High expression of microRNA-127 is involved in cell cycle arrest in MC-3 mucoepidermoid carcinoma cells

SHIN, JI-AE,LI, CHENGMING,CHOI, EUN-SUN,CHO, SUNG-DAE,CHO, NAM-PYO Spandidos Publications 2013 MOLECULAR MEDICINE REPORTS Vol.7 No.2

<P>microRNAs (miRs) are small endogenous non?coding RNAs and are associated with the pathogenesis of a number of types of human cancer. However, miR?127?3p in mucoepidermoid carcinoma (MEC) has not been studied. The present study aimed to analyze the importance of miR?127?3p in MC?3 human MEC cells. Analyses of the growth inhibitory effect and the associated mechanism of miR?127?3p were performed using 3?(4,5?dimethylthiazol?20yl)?(3?carboxymethoxyphenyl)?2?(4?sulphophenyl)?2H?tetrazolium assay, flow cytometry, 4'?6?diamidino?2?phenylindole staining, anchorage?independent cell transformation assay and western blot analysis. Transfection of exogenous miR?127?3p into MC?3 cells inhibited cell viability and led to G1/S cell cycle arrest. In addition, miR?127?3p also decreased neoplastic cell transformation in TPA?induced JB6 mouse epidermal and MC?3 cells. In addition, miR?127?3p decreased specificity protein 1 (Sp1) expression and increased p21 and p27 expression which are Sp1?dependent cell cycle?related proteins. However, miR?127?3p did not induce apoptosis or affect expression levels of myeloid cell leukemia?1 or survivin. miR?127?3p induced G1/S cell cycle arrest and increased p21 and p27 expression via modulation of Sp1. Therefore, miR?127?3p may be a therapeutic target for human MEC.</P>

Trajectory Learning and Reproduction for Tracked Robot Based on Bagging-GMM/HSMM

Lu En,Zhao Zhan,Yin Jianjun,Luo Chengming,Tian Zhongming 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.6

Learning and reproducing the tracked robot’s demonstration trajectory is a promising intelligent path planning solution that can summarize and extract the relevant characteristics of the tracked robot’s desired trajectory. However, the existing methods are difficult to ensure the robustness when there are deviations in the demonstration trajectory data or when the task constraints are added. In order to address the problem, this paper proposes a novel trajectory learning and reproduction method for tracked robots that is based on Bagging algorithm and GMM/HSMM. The Bagging algorithm is used to randomly resample the demonstration trajectory data and construct the sub trajectory data sets. Then, GMM/HSMM is used to train and learn these sub trajectory data sets, and the output probability density function of the hidden state and the Gaussian component with the largest average position probability are selected as the motion elements. According to the mean and variance of these motion elements, the least square method is used to reconstruct the tracked robot’s trajectory. On the basis of using the IPSO algorithm to optimize the position of constraint points in each sub trajectory data sets, combined with the weight method, the learning results are integrated to realize the trajectory reproduction of a tracked robot under task constraints. The final results and analysis show that the proposed method can successfully realize the trajectory learning and reproduction of tracked robot, as well as ensure that the reproduced trajectory can pass through the required task constraint points without increasing the algorithm’s complexity.