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Event-triggered and consensus-based attitude tracking alignment for discrete-time multiple spacecraft system exploiting interference

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Chinese Journal of Aeronautics 2023年第2期36卷 241-255页

作者： Peiran LI Xin WEN haiying liu Yuping LU Department of Astronautics Nanjing University of Aeronautics and AstronauticsNanjing 211100China Nanjing Center for Applied Mathematics Nanjing 211135China

This paper presents a discrete-time attitude control strategy with equi-global practical stabilizability for aligning the attitude of multiple spacecraft to a predesigned configuration according to a time-variant *** utilizing the interference of the wireless channel,the communication scheme designed in this paper can save communication resources,amount of computation,and energy proportionally to the number of *** exact discrete-time model and approximate discrete-time model of the consensus-based spacecraft tracking system are *** the framework for the design of an event-triggered control scheme for the exact discrete-time system via its approximate models is developed,which avoids the periodic actuation,and Zeno behavior is proved to be ***,the control scheme can handle the presence of the unknown fading ***,simulation results are presented to demonstrate the effectiveness of the control strategy.

关键词： Attitude control Cooperative communication Discrete time control systems Multi agent systems Spacecraft

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

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Frontiers of Earth Science 2018年第2期12卷 431-443页

作者： Hongchun ZHU Yipeng ZHAO haiying liu College of Geometries Shandong University of Science and Technology Qingdao 266590 China College of Computer Science and Engineering Shandong University of Science andTechnology Qingdao 266590 China

Scale is the basic attribute for expressing anddescribing spatial entity and phenomena. It offerstheoretical significance in the study of gully structureinformation, variable characteristics of watershed mor-phology, and development evolution at different *** research selected five different areas in China＇s LoessPlateau as the experimental region and used DEM data atdifferent scales as the experimental data. First, the changerule of the characteristic parameters of the data at differentscales was analyzed. The watershed structure informationdid not change along with a change in the data scale. Thiscondition was proven by selecting indices of gullybifurcation ratio and fractal dimension as characteristicparameters of watershed structure information. Then, thechange rule of the characteristic parameters of gullystructure with different analysis scales was analyzed bysetting the scale sequence of analysis at the extractiongully. The gully structure of the watershed changed withvariations in the analysis scale, and the change rule wasobvious when the gully level changed. Finally, the changerule of the characteristic parameters of the gully structure atdifferent areas was analyzed. The gully fractal dimensionshowed a significant numerical difference in differentareas, whereas the variation of the gully branch ratio wassmall. The change rule indicated that the developmentdegree of the gully obviously varied in different regions,but the morphological structure was basically similar.

关键词： watershed scale features gully structure bifurcation ratio fractal dimension scale sequence

Toxic effects of 1-methyl-3-octylimidazolium bromide on the wheat seedlings

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Journal of Environmental Sciences 2010年第12期22卷 1974-1979页

作者： Ping liu Yifeng Ding haiying liu Liping Sun Xiaoyu Li Jianji Wang College of Life Sciences Henan Normal University Xinxiang 453007 China Key Laboratory for Environmental Pollution Control Xinxiang 453007 China College of Chemistry and Environmental Science Henan Normal University Xinxiang 453007 China

The toxic effects of 1-methyl-3-octylimidazolium bromide （[C8mim]Br） on wheat seedlings were evaluated. Wheat seedlings were cultivated in aqueous solution with [C8mim]Br at different concentrations （0, 1, 2, 4, 6, 8 mg/L）. The contents of photosynthetic pigment and proline, peroxidation of membrane lipid, and activities of antioxidation enzymes （superoxide dismutase, catalase, peroxidase and ascorbate peroxidase） in leaves were measured on day 7 after treatment with [C8mim]Br. The results showed that [C8mim]Br significantly decreased the contents of photosynthetic pigments, activities of antioxidant enzymes in the wheat leaves and in dry weight of seedlings, while increased the proline content and membrane lipid peroxidation. The results suggested that [C8mim]Br can inhibit photosynthesis and lead to oxidative stress to wheat seedlings.

关键词： [C8mim]Br wheat seedlings photosynthetic pigments antioxidant enzymes membrane lipid peroxidation

Regulatory effect of vascular endothelial growth factor on blood spinal cord barrier in presyrinx state of experimental syringomyelia

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Neural Regeneration Research 2008年第11期3卷 1181-1186页

作者： Jianfeng Li Changrong Zhou haiying liu Penghui Xing Department of Neurosurgery the Fourth Hospital of Hebei Medical University Shijiazhuang 050011 Hebei Province China Hebei University of Economics and Business Shijiazhuang 050061 Hebei Province China

BACKGROUND： Vascular endothelial growth factor （VEGF） is able to regulate blood spinal cord barrier function as well as influence neovascularization and cause edema. OBJECTIVE： Through establishment of a rabbit model of syringomyelia, to explore the correlation between VEGF protein and mRNA expressions and function of blood spinal cord barrier and edema degree of spinal cord in presyrinx state. DESIGN, TIME AND SETTING： Randomized controlled animal study was performed in the Tumor Institute of the Fourth Hospital, Hebei Medical University from January to June 2007. MATERIALS： Atotal of 0.6 mL Kaolin solution （250 g/L, 37℃） was injected into the cisterna magna of 40 rabbits in the kaolin group to establish syringomyelia models. Goat anti-rabbit VEGF monoclonal antibody was provided by DIACLONE Company, USA; RT-PCR related reagents were provided by Huamei Bioengineering Co., Ltd., Beijing. METHODS： Sixty Chinese white rabbits were divided randomly into two groups： Kaolin group （n = 40） and control group （n = 20）. Physiological saline （0.6 mL at 37℃） was injected in rabbits of control group. On days 1,3, 7, 14 and 21 after kaolin injection, cervical cords samples were harvested after sacrifice of animal. MAIN OUTCOME MEASURES： VEGF protein and mRNA expressions were detected by immunohistochemistry and RT-PCR on days 1, 3, 7, 14, and 21 after kaolin injection. A quantitative analysis of blood spinal cord barrier function was performed by Evans blue technique. Water content of the spinal cord was measured by dry-wet weight technique. The correlation between the expression of VEGF protein and mRNA and the function of blood spinal cord barrier in the upper cervical cord of the presyrinx state was analyzed by linear correlation analysis. RESULTS： The water content and Evans blue content increased in the kaolin group on days 1 and 3 postoperatively compared with the control group （F = 7.387, 61.35, P 〈 0.05, 0.01）, and reached a peak on day 7 （F = 135.94, 528.35, P 〈 0.01）.

关键词： presyrinx state blood spinal cord barrier vascular endothelial growth factor

Extraction and Analysis of Gully Head of Loess Plateau in China Based on Digital Elevation Model

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Chinese Geographical Science 2014年第3期24卷 328-338页

作者： ZHU Hongchun TANG Guoan QIAN Kejian liu haiying Geomatics College Shandong University of Science and Technology Key Laboratory of Virtual Geographic Environment of Ministry of Education Nanjing Normal University College of Information Science and Engineering Shandong University of Science and Technology

In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.

关键词： Loess Plateau loess gully head Digital Elevation Model (DEM) loess landform evolution feature extraction statisticalanalysis

Economical Optimization of Grid Power Factor Using Predictive Data

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 258-267页

作者： Chaojiong Huang Jason Gu haiying liu Yuansheng Lu Jun Luo IEEE the School of Electrical Engineering and Automation Shanghai University the Department of Electrical and Computer Engineering Dalhousie University

We present an electrical grid optimization method for economical benefit. After simplifying an IEEE feeder diagram, we build a compact smart grid system including a photovoltaic-inverter system, a shunt capacitor, an on-load tapchanger(OLTC) and transmission lines. The system power factor(PF) regulation and reactive power dispatching are indispensable to improve power quality. Our control method uses predictive weather and load data to decide engaging or tripping the shunt capacitor, or reactive power injection by the photovoltaic-inverter system, ultimately to keep the system PF in a good range. From the perspective of economics, the economical model is considered as a decision maker in our predictive data control ***-only control strategy is a common photovoltaic(PV)regulation method, which is treated as a baseline case. Simulations with GridLAB-D on profiled loads and residential loads have been carried out. The comparison results with baseline control strategy and our predictive data control method show the appreciable economical benefit of our method.

关键词： Grid optimization GridLAB-D inverter power factor predictive data control shunt capacitor

Anchor-based manifold binary pattern for finger vein recognition

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Science China(Information Sciences) 2019年第5期62卷 129-144页

作者： haiying liu Gongping YANG Lu YANG Kun SU Yilong YIN School of Software Shandong University School of Computer Science and Technology Shandong University of Finance and Economics

This paper proposes a novel learning method of binary local features for recognition of the finger vein. The learning methods existing in local features for image recognition intend to maximize the data variance, reduce quantitative errors, exploit the contextual information within each binary code, or utilize the label information, which all ignore the local manifold structure of the original data. The manifold structure actually plays a very important role in binary code learning, but constructing a similarity matrix for large-scale datasets involves a lot of computational and storage cost. The study attempts to learn a map, which can preserve the manifold structure between the original data and the learned binary codes for large-scale situations. To achieve this goal, we present a learning method using an anchor-based manifold binary pattern(AMBP) for finger vein recognition. Specifically, we first extract the pixel difference vectors(PDVs) in the local patches by calculating the differences between each pixel and its neighbors. Second,we construct an asymmetric graph, on which each data point can be a linear combination of its K-nearest neighbor anchors, and the anchors are randomly selected from the training samples. Third, a feature map is learned to project these PDVs into low-dimensional binary codes in an unsupervised manner, where(i) the quantization loss between the original real-valued vectors and learned binary codes is minimized and(ii) the manifold structure of the training data is maintained in the binary space. Additionally, the study fuses the discriminative binary descriptor and AMBP methods at the image representation level to further boost the performance of the recognition system. Finally, experiments using the MLA and PolyU databases show the effectiveness of our proposed methods.

关键词： finger vein recognition feature learning local linear embedding fusion manifold learning anchor

Deep learning of DEM image texture for landform classification in the Shandong area,China

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Frontiers of Earth Science 2022年第2期16卷 352-367页

作者： Yuexue XU Hongchun ZHU Changyu HU haiying liu Yu CHENG College of Geodesy and Geomatics Shandong University of Science and TechnologyQingdao 266590China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China

Landforms are an important element of natural geographical environment,and textures are the research basis for the spatial differentiation,evolution features,and analysis rules of the *** the regional difference of texture to describe the spatial distribution pattern of macro landform features is helpful to the landform classification and *** elevation model(DEM)image texture,which gives full expression to texture difference,is key data source to reflect the surface features and landform *** the texture analysis,landform features analysis is assistant to different landforms classification,even in landform *** the increasing accuracy requirement of landform information acquisition in geomorphic thematic mapping,hierarchical landform classification has become the focus and difficulty in ***,the pattern recognition represented by Convolutional Neural Network has made great achievements in landform research,whose multichannel feature fusion structure satisfies the network structure of different landform *** this paper,DEM image texture was taken as the data source,and gray level co-occurrence matrix was applied to extract texture *** to the similarity of similar landform and the difference of different landform in a certain scale,a comprehensive texture factor reflecting landform features was proposed,and the spatial distribution pattern of landform features was systematically *** this basis,the coupling relationship between texture and landform type was ***,the deep learning method of Convolutional Neural Network is used to train the texture features,and the second-class landform classification is carried out through *** classification results in small relief and mid-relief low mountains,overall accuracy are 84.35%and 69.95%respectively,while kappa coefficient are 0.72 and 0.40 respectively,were compared to that of traditional unsupervised landf

关键词： DEM image texture comprehensive texture factor texture spatial pattern features Convolutional Neural Network landform classification

Landform classification based on optimal texture feature extraction from DEM data in Shandong Hilly Area, China

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Frontiers of Earth Science 2019年第3期13卷 641-655页

作者： Hongchun ZHU Yuexue XU Yu CHENG haiying liu Yipeng ZHAO College of Geomatics Shandong University of Science and TechnologyQingdao 266590China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China

Texture and its analysis methods are crucial for image feature extraction and classification. Digital elevation model (DEM) is the most important data source of digital terrain analysis and landform classification, and considerable research values are gained from texture feature extraction and analysis from DEM data. In this research, on the basis of optimal texture feature extraction, the hilly area in Shandong, China, was selected as the study area, and DEM data with a resolution of 500 m were used as the experimental data for landform classification. First, second-order texture measures and texture image were extracted from DEM data by using a gray level cooccurrence matrix (GLCM). Second, the variation characteristics of each texture measure were analyzed, and the optimal feature parameters, such as direction, gray level, and texture window, were determined. Meanwhile, the texture feature value, combined with maximum information, was calculated, and the multiband texture image was obtained by resolving three optimal texture measure images. Finally, a support vector machine (SVM) method was adopted to classify landforms on the basis of the multiband texture image. Results indicated that the texture features of DEM data can be sufficiently represented and measured via the quantitative GLCM method. However, the feature parameters during the texture feature value calculation required further optimization. Based on the image texture from DEM data, efficient classification accuracy and ideal classification effect were achieved.

关键词： DEM data image texture feature extraction Gray Level Co-occurrence Matrix (GLCM) optimal parametric analysis landform classification