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| 1 | Sliding Mode Control Approach with Integrated Disturbance Observer for PMSM Speed System显示文摘The research on high-performance vector control of permanent magnet synchronous motor(PMSM)drive system plays an extremely important role in electrical drive system.To further improve the speed control performance of the system,a fast non-singular end sliding mode(FNTSM)surface function based on traditional NTSM control is developed.The theoretical analysis proves that the FNTSM surface function has a faster dynamic response and more finite-time convergence.In addition,for the self-vibration problem caused by high sliding mode switching gain,an FNTSM control method with anti-disturbance capability was designed based on the linear disturbance observer(DO),i.e.the FNTSMDO method was employed to devise the PMSM speed regulator.The comparative simulation and experiment results with traditional PI control and NTSM control methods indicate that the FNTSMDO method could improve the dynamic performance and anti-interference of the system. | Lei Yuan Yunhao Jiang Lu Xiong Pan Wang | 2023 | CES Transactions on Electrical Machines and Systems2023，7，1： | 3 |
| 2 | Probability hypothesis density filter with adaptive parameter estimation for tracking multiple maneuvering targets显示文摘The probability hypothesis density(PHD) filter has been recognized as a promising technique for tracking an unknown number of targets. The performance of the PHD filter, however, is sensitive to the available knowledge on model parameters such as the measurement noise variance and those associated with the changes in the maneuvering target trajectories. If these parameters are unknown in advance, the tracking performance may degrade greatly. To address this aspect, this paper proposes to incorporate the adaptive parameter estimation(APE) method in the PHD filter so that the model parameters, which may be static and/or time-varying, can be estimated jointly with target states. The resulting APE-PHD algorithm is implemented using the particle filter(PF), which leads to the PF-APE-PHD filter. Simulations show that the newly proposed algorithm can correctly identify the unknown measurement noise variances, and it is capable of tracking multiple maneuvering targets with abrupt changing parameters in a more robust manner, compared to the multi-model approaches. | Yang Jinlong Yang Le Yuan Yunhao Ge Hongwei | 2016 | Chinese Journal of Aeronautics2016，29，6： | 2 |
| 3 | Does wireless sensor network scale?A measurement study on Green Orbs显示文摘 | Liu Yunhao He Yuan Li Mo | 2013 | IEEE Transactions on Parallel Distributed Systems2013，24，10： | 1 |
| 4 | Fractional-order Sparse Representation for Image Denoising显示文摘Sparse representation models have been shown promising results for image denoising. However, conventional sparse representation-based models cannot obtain satisfactory estimations for sparse coefficients and the dictionary. To address this weakness, in this paper, we propose a novel fractional-order sparse representation(FSR) model. Specifically, we cluster the image patches into K groups, and calculate the singular values for each clean/noisy patch pair in the wavelet domain. Then the uniform fractional-order parameters are learned for each cluster.Then a novel fractional-order sample space is constructed using adaptive fractional-order parameters in the wavelet domain to obtain more accurate sparse coefficients and dictionary for image denoising. Extensive experimental results show that the proposed model outperforms state-of-the-art sparse representation-based models and the block-matching and 3D filtering algorithm in terms of denoising performance and the computational efficiency. | Leilei Geng Zexuan Ji Yunhao Yuan Yilong Yin | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，2： | 1 |
| 5 | Measurement and analysis on the packet delivery performance in a large-scale sensor network显示文摘 | Dong Wei Liu Yunhao He Yuan | 2014 | IEEE/ACM Transactions on Networking2014，22，6： | 1 |
| 6 | Degradation behavior of ZE21C magnesium alloy suture anchors and their effect on ligament-bone junction repair显示文摘Current materials comprising suture anchors used to reconstruct ligament-bone junctions still have limitation in biocompatibility,degradability or mechanical properties.Magnesium alloys are potential bone implant materials,and Mg^(2+) has been shown to promote ligament-bone healing.Here,we used Mg-2 wt.%Zn-0.5 wt.%Y-1 wt.%Nd-0.5 wt.%Zr(ZE21C)alloy and Ti6Al4V(TC4)alloy to prepare suture anchors to reconstruct the patellar ligament-tibia in SD rats.We studied the degradation behavior of the ZE21C suture anchor via in vitro and in vivo experiments and assessed its reparative effect on the ligament-bone junction.In vitro,the ZE21C suture anchor degraded gradually,and calcium and phosphorus products accumulated on its surface during degradation.In vivo,the ZE21C suture anchor could maintain its mechanical integrity within 12 weeks of implantation in rats.The tail of the ZE21C suture anchor in high stress concentration degraded rapidly during the early implantation stage(0-4weeks),while bone healing accelerated the degradation of the anchor head in the late implantation stage(4-12weeks).Radiological,histological,and biomechanical assays indicated that the ZE21C suture anchor promoted bone healing above the suture anchor and fibrocartilaginous interface regeneration in the ligament-bone junction,leading to better biomechanical strength than the TC4 group.Hence,this study provides a basis for further research on the clinical application of degradable magnesium alloy suture anchors. | Delin Ma Jun Wang Mingran Zheng Yuan Zhang Junfei Huang Wenxiang Li Yiwen Ding Yunhao Zhang Shijie Zhu Liguo Wang Xiaochao Wu Shaokang Guan | 2023 | Bioactive Materials2023，，8： | 1 |
| 7 | Treatment Effects of Integrated TCM and Western Medicine Treatment Scheme on COVID-19: A Single-armed Clinical Trial显示文摘Backgroud:The outbreak of COVID-19 has brought unprecedented perils to human health and raised public health concerns in more than two hundred countries.Safe and effective treatment scheme is needed urgently.Objective:To evaluate the effects of integratedTCM and western medicine treatment scheme on COVID-19.Methods:A single-armed clinical trial was carried out in Hangzhou Xixi Hospital,an affiliated hospital with Zhejiang Chinese Medical University.102 confirmed cases were screened out from 725 suspected cases and 93 of them were treated with integrated TCM and western medicine treatment scheme.Results:83 cases were cured,5 cases deteriorated,and 5 cases withdrew from the study.No deaths were reported.The mean relief time of fever,cough,diarrhea,and fatigue were(4.78±4.61)days,(7.22±4.99)days,(5.28±3.39)days,and(5.28±3.39)days,respectively.It took(14.84±5.50)days for SARS-CoV-2 by nucleic acid amplification-based testing to turn negative.Multivariable cox regression analysis revealed that age,BMI,PISCT,BPC,AST,CK,BS,and UPRO were independent risk factors for COVID-19 treatment.Conclusion:Our study suggested that integrated TCM and western medicine treatment scheme was effective for COVID-19. | Jianfeng Bao Zhijun Xie Shourong Liu Lin Huang Jing Sun Yujun Tang Haiping Chen Jianjiang Qi Jianchun Guo Liangbin Miao Zhaoyi Li Hui Yang Yi Zhang Zhiyu Li Yuan Xu Shengyou Lin Yunhao Xun Li Zhang Jie Bao Zhaobin Cai Jinsong Huang Chengping Wen | 2021 | Clinical Complementary Medicine and Pharmacology2021，1，1： | 0 |
| 8 | Representation learning via an integrated autoencoder for unsupervised domain adaptation显示文摘The purpose of unsupervised domain adaptation is to use the knowledge of the source domain whose data distribution is different from that of the target domain for promoting the learning task in the target domain.The key bottleneck in unsupervised domain adaptation is how to obtain higher-level and more abstract feature representations between source and target domains which can bridge the chasm of domain discrepancy.Recently,deep learning methods based on autoencoder have achieved sound performance in representation learning,and many dual or serial autoencoderbased methods take different characteristics of data into consideration for improving the effectiveness of unsupervised domain adaptation.However,most existing methods of autoencoders just serially connect the features generated by different autoencoders,which pose challenges for the discriminative representation learning and fail to find the real cross-domain features.To address this problem,we propose a novel representation learning method based on an integrated autoencoders for unsupervised domain adaptation,called IAUDA.To capture the inter-and inner-domain features of the raw data,two different autoencoders,which are the marginalized autoencoder with maximum mean discrepancy(mAE)and convolutional autoencoder(CAE)respectively,are proposed to learn different feature representations.After higher-level features are obtained by these two different autoencoders,a sparse autoencoder is introduced to compact these inter-and inner-domain representations.In addition,a whitening layer is embedded for features processed before the mAE to reduce redundant features inside a local area.Experimental results demonstrate the effectiveness of our proposed method compared with several state-of-the-art baseline methods. | Yi ZHU Xindong WU Jipeng QIANG Yunhao YUAN Yun LI | 2023 | Frontiers of Computer Science2023，17，5： | 0 |
| 9 | Lexical simplification via single-word generation显示文摘1 Introduction Lexical simplification(LS)aims to simplify a sentence by replacing complex words with simpler words without changing the meaning of the sentence,which can facilitate comprehension of the text for people with non-native speakers and children.Traditional LS methods utilize linguistic databases(e.g.,WordNet)[1]or word embedding models[2]to extract synonyms or high-similar words for the complex word,and then sort them based on their appropriateness in context.Recently,BERT-based LS methods[3,4]entirely or partially mask the complex word of the original sentence,and then feed the sentence into pretrained modeling BERT[5]to obtain the top probability tokens corresponding to the masked word as the substitute candidates.They have made remarkable progress in generating substitutes by making full use of the context information of complex words,that can effectively alleviate the shortcomings of traditional methods. | Jipeng QIANG Yang LI Yun LI Yunhao YUAN Yi ZHU | 2023 | Frontiers of Computer Science2023，17，6： | 0 |
| 10 | Multiple unpinned Dirac points in group-Va single-layers with phosphorene structure显示文摘Emergent Dirac fermion states underlie many intriguing properties of graphene,and the search for them constitutes one strong motivation to explore two-dimensional(2D)allotropes of other elements.Phosphorene,the ultrathin layers of black phosphorous,has been a subject of intense investigations recently,and it was found that other group-Va elements could also form 2D layers with similar puckered lattice structure.Here,by a close examination of their electronic band structure evolution,we discover two types of Dirac fermion states emerging in the low-energy spectrum.One pair of(type-I)Dirac points is sitting on high-symmetry lines,while two pairs of(type-II)Dirac points are located at generic k-points,with different anisotropic dispersions determined by the reduced symmetries at their locations.Such fully-unpinned(type-II)2D Dirac points are discovered for the first time.In the absence of spin-orbit coupling(SOC),we find that each Dirac node is protected by the sublattice symmetry from gap opening,which is in turn ensured by any one of three point group symmetries.The SOC generally gaps the Dirac nodes,and for the type-I case,this drives the system into a quantum spin Hall insulator phase.We suggest possible ways to realise the unpinned Dirac points in strained phosphorene. | Yunhao Lu Di Zhou Guoqing Chang Shan Guan Weiguang Chen Yinzhu Jiang Jianzhong Jiang Xue-sen Wang Shengyuan A Yang Yuan Ping Feng Yoshiyuki Kawazoe Hsin Lin | 2016 | npj Computational Materials2016，，1： | 0 |
| 11 | Unsupervised statistical text simplification using pre-trained language modeling for initialization显示文摘Unsupervised text simplification has attracted much attention due to the scarcity of high-quality parallel text simplification corpora. Recent an unsupervised statistical text simplification based on phrase-based machine translation system (UnsupPBMT) achieved good performance, which initializes the phrase tables using the similar words obtained by word embedding modeling. Since word embedding modeling only considers the relevance between words, the phrase table in UnsupPBMT contains a lot of dissimilar words. In this paper, we propose an unsupervised statistical text simplification using pre-trained language modeling BERT for initialization. Specifically, we use BERT as a general linguistic knowledge base for predicting similar words. Experimental results show that our method outperforms the state-of-the-art unsupervised text simplification methods on three benchmarks, even outperforms some supervised baselines. | Jipeng QIANG Feng ZHANG Yun LI Yunhao YUAN Yi ZHU Xindong WU | 2023 | Frontiers of Computer Science2023，17，1： | 0 |
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