A Fast and Accurate Detection Method of Instantaneous Reactive Current in Single-phase Power System

Xiaokang Liu,Liansong Xiong,Fang Zhuo,Ying Chen,Minghua Zhu 전력전자학회 2015 ICPE(ISPE)논문집 Vol.2015 No.6

Fast and accurate detection of instantaneous reactive current in single-phase power system is a pre-requisite for the precise control of STATCOM (Static Synchronous Compensator). A major solution is based on the construction of virtual orthogonal signal in rotational coordinate transformation; however, conventional methods show weaknesses in the speed of detection and the ability of noise and harmonic suppression. In this paper, a novel method of instantaneous reactive current detection in single-phase system, with fast and accurate property as well as harmonic and noise susceptibility, is proposed. Firstly, a novel virtual orthogonal signal generation algorithm is deduced, remarkably improving the immediacy and precision of detection in synchronous reference frame. Then an enhanced moving average filter (EMAF) is utilized in cascade and its design principle is proposed, sufficiently eliminating the effects of noise and harmonics. Finally, experiments reveal that the proposed detection scheme can achieve the satisfactory control goals.

Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data

Xiaokang Yu,Jinsheng Liang,Jiarui Xu,Xingsong Li,Shan Xing,Huilan Liu,Wan-Li Liu,Dongdong Liu,Jianhua Xu,Lizhen Huang,Hongli Du 한국유방암학회 2018 Journal of breast cancer Vol.21 No.4

Purpose: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers. Methods: To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction. Results: The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively. Conclusion: The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.

Digital finance, absorptive capacity and enterprise dual innovation: an empirical analysis on mediation and threshold effects

Li Yongkui,Liu Xiaokang,Zhao Qingbin 기술경영경제학회 2023 ASIAN JOURNAL OF TECHNOLOGY INNOVATION Vol.31 No.2

Based on the data of listed companies in Chinese A stock marketbetween 2011 and 2020, This paper discusses the empiricalanalysis of digitalfinance on enterprise dual innovation byadopting the mediating effect model and threshold regressionmodel, and estimates the mediation and threshold effects ofabsorptive capacity among them. Our studyfind that thedevelopment of digitalfinance exerts a significant positive effecton enterprise dual innovation. Compared with exploitativeinnovation, digitalfinance exhibits a greater promoting effect onexploratory innovation. Absorptive capacity displays a greatermediating effect between digitalfinance and exploratoryinnovation, and exploitative innovation reveals a significantpositive effect on exploratory innovation. There is non-linearrelationship between digitalfinance and corporate dualinnovation, and the promotion effect shows a leaping growthpattern and significant threshold effect. The heterogeneityanalysis from the perspective of property rights and enterprisesize shows that the incentive effect of digitalfinancedevelopment on enterprises dual innovation is mainly reflected innon-state-owned enterprises and small and medium-sizedenterprises. This research expands the relevant theories ofcorporate innovation and digitalfinance, to provides empiricalevidence for corporate decision-making.

Small Sample Face Recognition Algorithm based on Novel Siamese Network

( Jianming Zhang ),( Xiaokang Jin ),( Yukai Liu ),( Arun Kumar Sangaiah ),( Jin Wang ) 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.6

In face recognition, sometimes the number of available training samples for single category is insufficient. Therefore, the performances of models trained by convolutional neural network are not ideal. The small sample face recognition algorithm based on novel Siamese network is proposed in this paper, which doesn’t need rich samples for training. The algorithm designs and realizes a new Siamese network model, SiameseFace1, which uses pairs of face images as inputs and maps them to target space so that the L2 norm distance in target space can represent the semantic distance in input space. The mapping is represented by the neural network in supervised learning. Moreover, a more lightweight Siamese network model, SiameseFace2, is designed to reduce the network parameters without losing accuracy. We also present a new method to generate training data and expand the number of training samples for single category in AR and labeled faces in the wild (LFW) datasets, which improves the recognition accuracy of the models. Four loss functions are adopted to carry out experiments on AR and LFW datasets. The results show that the contrastive loss function combined with new Siamese network model in this paper can effectively improve the accuracy of face recognition.

Betulin induces reactive oxygen species-dependent apoptosis in human gastric cancer SGC7901 cells

Yang Li,Xiaokang Liu,Dan Jiang,Yingjia Lin,Yushi Wang,Qing Li,Linlin Liu,Ying-Hua Jin 대한약학회 2016 Archives of Pharmacal Research Vol.39 No.9

Betulin, an abundant natural compound, significantly inhibited the cell viability of advanced human gastric cancer SGC7901 cells. Mechanism study demonstrated that betulin induced apoptosis through mitochondrial Bax and Bak accumulation-mediated intrinsic apoptosis pathway. Downregulation of the anti-apoptosis proteins Bcl-2 and XIAP was involved during betulin-induced cell apoptosis. Reactive oxygen species (ROS) was generated in cells after betulin treatment in a time- and dose-dependent manner. Addition of antioxidant N-acetyl-L-cysteine (NAC) significantly attenuated betulin-induced ROS generation as well as Bcl-2 and XIAP downregulation. The mitochondrial accumulation of Bax and Bak, as well as caspase activity, was also remarkably inhibited by NAC treatment, indicating that ROS are important signaling intermediates that lead to betulin-induced apoptosis by modulating multiple apoptosis-regulating proteins in SGC7901 cells.

A Sensorless Rotor Position Estimation Scheme for IPMSM Using HF Signal Injection with Frequency and Amplitude Optimization

Lu, Jiadong,Liu, Jinglin,Hu, Yihua,Zhang, Xiaokang,Ni, Kai,Si, Jikai The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.5

High frequency signal injection (HFI) is an alternative method for estimating rotor position of interior permanent magnet synchronous motor (IPMSM). The general method of frequency and amplitude selection is based on error tolerance and experiments, and is usually set with only one group of HF parameters, which is not efficient for different working modes. This paper proposes a novel rotor position estimation scheme by HFI with optimized frequency and amplitude, based on the mathematic model of IPMSM. The requirements for standstill and low-speed operational modes are met by applying this novel scheme. Additionally, the effects of the frequency and amplitude of the injected HF signal on the position estimation results under different operating conditions are analyzed. Furthermore, an optimization method for HF parameter selection is proposed to make the estimation process more efficient under different working conditions according to error tolerance. The effectiveness of the propose scheme is verified by the experiments on an IPMSM motor prototype.

Function and Molecular Ecology Significance of Two Catechol-Degrading Gene Clusters in Pseudomonas putida ND6

( Sanyuan Shi ),( Liu Yang ),( Chen Yang ),( Shanshan Li ),( Hong Zhao ),( Lu Ren ),( Xiaokang Wang ),( Fuping Lu ),( Ying Li ),( Huabing Zhao ) 한국미생물생명공학회(구 한국산업미생물학회) 2021 Journal of microbiology and biotechnology Vol.31 No.2

Many bacteria metabolize aromatic compounds via catechol as a catabolic intermediate, and possess multiple genes or clusters encoding catechol-cleavage enzymes. The presence of multiple isozyme-encoding genes is a widespread phenomenon that seems to give the carrying strains a selective advantage in the natural environment over those with only a single copy. In the naphthalene-degrading strain Pseudomonas putida ND6, catechol can be converted into intermediates of the tricarboxylic acid cycle via either the ortho- or meta-cleavage pathways. In this study, we demonstrated that the catechol ortho-cleavage pathway genes (catB_IC_IA_I and catB_IIC_IIA_II) on the chromosome play an important role. The cat_I and cat_II operons are co-transcribed, whereas catA_I and catA_II are under independent transcriptional regulation. We examined the binding of regulatory proteins to promoters. In the presence of cis-cis-muconate, a well-studied inducer of the cat gene cluster, CatR_I and CatR_II occupy an additional downstream site, designated as the activation binding site. Notably, CatR_I binds to both the cat_I and cat_II promoters with high affinity, while CatR_II binds weakly. This is likely caused by a T to G mutation in the G/T-N11-A motif. Specifically, we found that CatR_I and CatR_II regulate catB_IC_IA_I and catB_IIC_IIA_II in a cooperative manner, which provides new insights into naphthalene degradation.

A Novel Control Algorithm for the Self-organized Fission Behavior of Flocking System with Time Delay

Panpan Yang,Mingyong Liu,Xiaokang Lei,Cheng Song 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.4

This paper studies the self-organized fission control problem for flocking system with time delay. Bothconstant and time-varying time delay cases are considered. Firstly, a novel information coupling degree (ICD) basedfission control algorithm, which is able to split a coherent flock into multiple sub-groups under conflict externalstimuli, is proposed. Then, for the case of constant time delay, the sufficient conditions for the fission controlalgorithm is derived using Lyapunov-Razumikhin theorem. For the case of time-varying time delay, Lyapunov-Krasovskii functional method is adopted to obtain the sufficient conditions for the fission control algorithm in termsof linear matrix inequalities (LMIs). Finally, numerical simulations are provided to illustrate the effectiveness ofthe theoretical results.

A Sensorless Rotor Position Estimation Scheme for IPMSM Using HF Signal Injection with Frequency and Amplitude Optimization

Jiadong Lu,Jinglin Liu,Yihua Hu,Xiaokang Zhang,Kai Ni,Jikai Si 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.5

High frequency signal injection (HFI) is an alternative method for estimating rotor position of interior permanent magnet synchronous motor (IPMSM). The general method of frequency and amplitude selection is based on error tolerance and experiments, and is usually set with only one group of HF parameters, which is not efficient for different working modes. This paper proposes a novel rotor position estimation scheme by HFI with optimized frequency and amplitude, based on the mathematic model of IPMSM. The requirements for standstill and low-speed operational modes are met by applying this novel scheme. Additionally, the effects of the frequency and amplitude of the injected HF signal on the position estimation results under different operating conditions are analyzed. Furthermore, an optimization method for HF parameter selection is proposed to make the estimation process more efficient under different working conditions according to error tolerance. The effectiveness of the propose scheme is verified by the experiments on an IPMSM motor prototype.

Small Sample Face Recognition Algorithm Based on Novel Siamese Network

Zhang, Jianming,Jin, Xiaokang,Liu, Yukai,Sangaiah, Arun Kumar,Wang, Jin Korea Information Processing Society 2018 Journal of information processing systems Vol.14 No.6

In face recognition, sometimes the number of available training samples for single category is insufficient. Therefore, the performances of models trained by convolutional neural network are not ideal. The small sample face recognition algorithm based on novel Siamese network is proposed in this paper, which doesn't need rich samples for training. The algorithm designs and realizes a new Siamese network model, SiameseFacel, which uses pairs of face images as inputs and maps them to target space so that the $L_2$ norm distance in target space can represent the semantic distance in input space. The mapping is represented by the neural network in supervised learning. Moreover, a more lightweight Siamese network model, SiameseFace2, is designed to reduce the network parameters without losing accuracy. We also present a new method to generate training data and expand the number of training samples for single category in AR and labeled faces in the wild (LFW) datasets, which improves the recognition accuracy of the models. Four loss functions are adopted to carry out experiments on AR and LFW datasets. The results show that the contrastive loss function combined with new Siamese network model in this paper can effectively improve the accuracy of face recognition.