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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Ling Tao Wenjie Li Yu Jin Shuang Yin College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China

Based on the similarity measure of the complex network node and the improved density peak clustering algorithm with information entropy, a community discovery method is proposed in this paper. First of all, the distance between nodes is measured by the Jaccard similarity and the shortest path generation algorithm. Then, the core communities with the improved density peak algorithm are selected automatically. Thirdly, applying the fuzzy clustering mechanism to calculate the membership degree matrix of each point, thus completing the division of the remaining points. Finally, overlapping nodes are distinguished by setting a threshold of degree difference. Experiments are conducted on four real-life networks and the Purity and the Extended Modularity are employed to evaluate the proposed algorithm. The comparison of experiments with some classical algorithms on real networks are given to demonstrate the feasibility and effectiveness of the proposed method.

关键词： Clustering algorithms Complex networks Entropy Information entropy Classification algorithms Clustering methods Dolphins

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Remote Sensing Image Scene Classification via Multi-feature Fusion

Remote Sensing Image Scene Classification via Multi-feature ...

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第30届中国控制与决策会议

作者： Ruiyao Liu Xiaoyong Bian Yuxia Sheng School of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Information Science and Engineenring Wuhan University of Science and Technology

In this papers, classification of remote sensing image scene is investigated. A scene classification approach based on multi-feature fusion has been proposed. In the proposed approach, three types of features are extracted. Specifically, extended multi-attribute profile(EMAP)-based texture feature, saliency-based shape feature and color ones. The texture features are extracted by EMAP. Furthermore, the Hu invariant moments are extracted from the saliency map, where the saliency map is obtained by frequency-tuned saliency detection. Meanwhile, the color moments are extracted as the color features from the image scenes. As for EMAP-based features, dimension reduction via principal component analysis(PCA) is first performed and combined with other two types of features to form a compact feature representation. Finally, support vector machine(SVM) is employed to classify the remote sensing image scenes. The experiments on the two challenging image scene datasets are performed to show that the proposed method is simple, yet efficient to implement, comparing with the state-of-the-arts.

关键词： Scene classification morphological attribute profile saliency map feature extraction

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T-S Fuzzy Logic Control with Genetic Algorithm Optimization for Pneumatic Muscle Actuator

T-S Fuzzy Logic Control with Genetic Algorithm Optimization ...

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International Conference on Modelling, Identification and Control (ICMIC)

作者： Cheng Chen Jian Huang Dongrui Wu Zhikang Song Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Beijing Advanced Innovation Center of Intelligent Robots and Systems Beijing China School of Automation Huazhong University of Science and Technology Wuhan China

Based on the three elements model of pneumatic muscle actuators(PMA), this paper proposed a T-S fuzzy logic control with genetic algorithm optimization and achieved the trajectory tracking control of PMA. To guarantee the stability of control system, the Lyapunov direct method was used. And the LMI Toolbox of Matlab was used in this paper to solve linear matrix inequalities(LMls) and calculate the state feedback gains. Finally, the results of experiment demonstrated that, T-S fuzzy logic control with genetic algorithm optimization can achieve desired control performance, which overcome the chattering of trajectory tracking, reduced tracking error effectively and improved the accuracy of control.

关键词： Genetic algorithms Fuzzy logic Mathematical model Optimization Muscles Actuators Stability analysis

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SPATIALLY ATTENTIVE CORRELATION FILTERS FOR VISUAL TRACKING

SPATIALLY ATTENTIVE CORRELATION FILTERS FOR VISUAL TRACKING

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IEEE International Conference on Image processing

作者： Huai Qin Zhixiong Pi Changqian Yu Changxin Gao Jin-Gang Yu Nong Sang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Huazhong University of Science and Technology Wuhan Hubei CN South China University of Technology Guangzhou China

Although correlation filter based trackers have recently demonstrated excellent performance, they still suffer from the boundary effects. The cosine window is introduced to alleviate the boundary affects, which however may result in poor performance in case of occlusion or fast motion. To address this problem, we propose a simple yet effective framework, which builds a spatially attentive model with multiple features to guide the detection of the correlation filter based trackers. The proposed method not only can breakthrough the spatial extent of cosine window, but also can provides prior information about the target object. Moreover, to model a robust object prior, we propose a generic strategy for adaptive fusion and update of multiple features. Extensive experiments over multiple tracking benchmarks demonstrate the superior accuracy and real-time performance of our methods compared to the state-of-the-art trackers.

关键词： Target tracking Correlation Adaptation models Color Training Mathematical model

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Preparation of Antheraea Pernyi Silk Fibroin Microspheres by a Facile Electrostatic Differentiation Method

Preparation of Antheraea Pernyi Silk Fibroin Microspheres by...

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textile Bioengineering and Informatics Symposium Proceedings

作者： Xiu-Fang Li Shu-Qin Yan Guang-Ming Cai An-Chang Xu Ren-Chuan You State Key Laboratory of New Textile Materials and Advanced Processing Technology School of Textile Science and Engineering Wuhan Textile University

Microsphere carriers have considerable potential as a platform for the delivery of therapeutic *** pernyi silk fibroin(ASF) is a promising biomaterial due to excellent biocompatibility, tailorable degradability, and the presence of intrinsic RGD tripeptide sequence. In this study, ASF microspheres with controllable size were fabricated by high-voltage electrostatic differentiation and freeze-drying. ASF microspheres are spherical in shape as determined by SEM with diameters in the range of 100～600 μm. The effects of solution concentration and voltage on the size and morphology were investigated. The results showed that the microsphere size increased with the increasing concentration, while decreased when voltage is ***-insolubility of ASF microspheres was achieved by inducing structural transition from random/α-helix to β-sheet. Because of mild preparation conditions, the ASF microspheres are a promising drug carrier in biomedical field.

关键词： Silk Protein Wild Silk Fibroin Microspheres Drug Carrier

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Multi-view multi-instance multi-label learning based on collaborative matrix factorization

arXiv

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arXiv 2019年

作者： Xing, Yuying Yu, Guoxian Domeniconi, Carlotta Wang, Jun Zhang, Zili Guo, Maozu College of Computer and Information Science Southwest University Chongqing China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan China Department of Computer Science George Mason University FairfaxVA United States School of Information Technology Deakin University GeelongVIC Australia School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China

Multi-view Multi-instance Multi-label Learning(M3L) deals with complex objects encompassing diverse instances, represented with different feature views, and annotated with multiple labels. Existing M3L solutions only partially explore the inter or intra relations between objects (or bags), instances, and labels, which can convey important contextual information for M3L. As such, they may have a compromised performance. In this paper, we propose a collaborative matrix factorization based solution called M3Lcmf. M3Lcmf first uses a heterogeneous network composed of nodes of bags, instances, and labels, to encode different types of relations via multiple relational data matrices. To preserve the intrinsic structure of the data matrices, M3Lcmf collaboratively factorizes them into low-rank matrices, explores the latent relationships between bags, instances, and labels, and selectively merges the data matrices. An aggregation scheme is further introduced to aggregate the instance-level labels into bag-level and to guide the factorization. An empirical study on benchmark datasets show that M3Lcmf outperforms other related competitive solutions both in the instance-level and bag-level prediction. Copyright © 2019, The Authors. All rights reserved.

关键词： Matrix factorization

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Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma

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Cancer Communications 2018年第1期38卷 50-62页

作者： Jin-Cheng Guo Yang Wu Yang Chen Feng Pan Zhi-Yong Wu Jia-Sheng Zhang Jian-Yi Wu Xiu-E Xu Jian-Mei Zhao En-Min Li Yi Zhao Li-Yan Xu Key Laboratory of Molecular Biology in High Cancer Incidence Coastal Chaoshan Area of Guangdong Higher Education Institutes Shantou University Medical CollegeShantouGuangdong 515041P.R.China Department of Biochemistry and Molecular Biology Shantou University Medical CollegeShantouGuangdong 515041P.R.China Departments of Oncology Surgery Shantou Central HospitalAffiliated Shantou Hospital of Sun Yat-Sen UniversityShantouGuangdong 515041P.R.China Institute of Oncologic Pathology Shantou University Medical CollegeShantouGuangdong 515041P.R.China Key Laboratory of Intelligent Information Processing Advanced Computer Research CenterState Key Laboratory of Computer ArchitectureInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190P.R.China

Background:Esophageal squamous cell carcinoma(ESCC)is the predominant subtype of esophageal carcinoma in *** study was to develop a staging model to predict outcomes of patients with ***:Using Cox regression analysis,principal component analysis(PCA),partitioning clustering,Kaplan-Meier analysis,receiver operating characteristic(ROC)curve analysis,and classification and regression tree(CART)analysis,we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 ***:Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes(PCGs)and 635 long non-coding RNAs(lncRNAs)were associated with the survival of patients with *** categorized these PCGs and lncRNAs into three principal components(PCs),which were used to cluster the patients into three *** analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging(area under ROC curve[AUC]:0.69 vs.0.65,P<0.05).Accord-ingly,we constructed a molecular disaggregated model comprising one lncRNA and two PCGs,which we desig-nated as the LSB staging model using CART analysis in the GSE63624 *** LSB staging model classified the GSE63622 dataset of patients into three different groups,and its effectiveness was validated by analysis of another cohort of 105 ***:The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

关键词： Long non-coding RNA Protein-coding gene Esophageal squamous cell carcinoma Overall survival Staging model Transcriptome

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Motion Blurred Star Image Centroid Optimized Extraction Based on Prior Gaussian Distribution 29

Motion Blurred Star Image Centroid Optimized Extraction Base...

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第29届中国控制与决策会议

作者： Peng Dingbang Chen Hao Sang Xiaochong Li Jianxun School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Institute of Spaceflight Control Technology Shanghai Key Laboratory of Aerospace Intelligent Control Technology

ISBN: (纸本)9781509046584

Star centroid extraction is the precondition of star recognition in star navigation *** image will be motion blurred under high dynamic *** methods such as Wiener filter method,restore the blurred star image with an estimated PSF to calculate the star *** unique characteristic of star images different from general images is ignored in conventional *** addition,the error of motion blur parameters estimation and the approximate linear motion model can decrease the accuracy of star centroids *** paper proposes a method utilizing the prior Gaussian distribution information of star energy to deal with the motion blurred star *** experimental results demonstrate that the proposed method gets smaller error in star centroids calculation compared with the conventional estimation method.

关键词： Motion blur Star image restoration Centroid extraction Gaussian distribution Optimize

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Survey of key technologies on millimeter-wave CMOS integrated circuits

Survey of key technologies on millimeter-wave CMOS integrate...

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2017年第二届可靠性工程国际会议

作者： Fei Yu Lei Gao Lixiang Li Shuo Cai Wei Wang Chunhua Wang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation & School of Computer and Communication Engineering Changsha University of Science and Technology College of Information Science and Engineering Hunan University

In order to provide guidance for the development of high performance millimeter-wave complementary metal oxide semiconductor(MMW-CMOS) integrated circuits(IC), this paper provides a survey of key technologies on MMW-CMOS IC. Technical background of MMW wireless communications is described. Then the recent development of the critical technologies of the MMW-CMOS IC are introduced in detail and compared. A summarization is given, and the development prospects on MMWCMOS IC are also discussed.

关键词： Survey of key technologies on millimeter-wave CMOS integrated circuits

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Silicon Melt Liquid Level Detection Based on Improved Laser Trigonometry

Silicon Melt Liquid Level Detection Based on Improved Laser ...

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第37届中国控制会议

作者： Xinyu Zhang Ding Liu Simi Wang Xiaoguo Zhao Lei Jiang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

In order to improve the robustness of laser triangulation to detect the liquid level of silicon melt, this paper firstly proposes a method of calculating the laser spot coordinates based on the voting mechanism. The vote is taken according to the coordinates of small laser spots, which are formed by the effect of liquid surface fluctuation on the line laser in the liquid level measurement image. Secondly, the Kalman filter method is used to correct the liquid level measurement data and compensate the missing data. Then the linear conversion is performed to obtain the liquid level value. Finally, the experimental results show that this method can effectively improve the robustness of the liquid level measurement by the laser triangulation method, and avoid the generation of impulse noise. The introduction of the Kalman filter can accurately correct the level measurement data and compensate for missing data.

关键词： Single crystal furnace Liquid level detection Coordinate calculation Voting mechanism Kalman filter

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