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2024, Vol. 41 No. 5

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15 September 2024

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University of Chinese Academy of Sciences
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  • Innovation Article
    An adaptive variance reduction method with negative momentum
    LIU Hai, GUO Tiande, HAN Congying
    2024, 41 (5): 577-588.  DOI: 10.7523/j.ucas.2024.024
    Abstract ( 235 ) PDF (0KB) ( 0 )
    Stochastic variance reduction methods have been successful in solving large scale machine learning problems, and researchers cooperate them with adaptive stepsize schemes to further alleviate the burden of parameter-tuning. In this article, we propose that there exists a trade-off between progress and effectiveness of adaptive stepsize arising in the SVRG-BB algorithm. To enhance the practical performance of SVRG-BB, we introduce the Katyusha momentum to handle the aforementioned trade-off. The linear convergence rate of the resulting SVRG-BB-Katyusha algorithm is proven under strong convexity condition. Moreover, we propose SVRG-BB-Katyusha-SPARSE algorithm which uses Katyusha momentum sparsely in the inner iterations. Numerical experiments are given to illustrate that the proposed algorithms have promising advantages over SVRG-BB, in the sense that the optimality gaps of the proposed algorithms are smaller than the optimality gap of SVRG-BB by orders of magnitude.
    Research Articles
    Dynamic evolution of natural convection in a porous square cavity
    ZHANG Lianping, WANG Shimin
    2024, 41 (5): 589-603.  DOI: 10.7523/j.ucas.2022.077
    Abstract ( 174 ) PDF (0KB) ( 0 )
    Natural convection in fluid-saturated porous cavities is a classical problem in the study of nonlinear hydrodynamics. Limited by the early computing capabilities, previous studies mainly focused on the dynamic mechanism of the spatiotemporal evolution of centrosymmetric convection modes, and could not fully describe the dynamic behavior of real-world porous natural convection systems with all convection modes. Therefore, the available results could not be directly applied to practical engineering problems. In this study, two-dimensional natural convection in a porous square cavity heated from below is numerically simulated with complete convection modes based on the Galerkin method and the collocation pseudo-spectral method, and the complete route for natural convection dynamically evolving from onset towards chaos is obtained for the first time. The modeling results reveal that along with Ra increasing from 4π2 to 1 200, the natural convection evolves across 21 different stages (including one steady convection stage, six single-frequency oscillation stages, nine quasiperiodic oscillation stages, two frequency-locked resonance stages, and three aperiodic chaotic oscillation stages). The spatial variation and temporal oscillation of convection modes are the fundamental reasons for the repeated alternation between different convection patterns. Different characteristics of single-frequency, quasiperiodic, frequency-locked, and chaotic oscillations in the calculated heat flow represented by Nu are systematically compared in terms of four graphical methods, viz. time series, power spectrum, phase portrait, and Lorenz mapping. The calculated average heat flow and primary oscillating frequency as functions of Ra can be fitted by simple analytical formulas, approximately obeying the scaling laws given by the classical boundary layer theory in a wide range of Ra values. This provides convenient calculation tools for practical engineering designs and applications under the corresponding conditions.
    Dynamic friction polishing of single crystal diamond
    ZHANG Haochen, XU Kai, YAN Zengyu, SONG Zhipeng, CHEN Guangchao
    2024, 41 (5): 604-611.  DOI: 10.7523/j.ucas.2023.003
    Abstract ( 177 ) PDF (0KB) ( 0 )
    The dynamic friction polishing (DFP) method has received extensive attention due to its significantly high removal rate comparing with other single crystal diamond polishing methods. In this study, three parameters (polishing load, polishing time, and polishing plate linear velocity) and three clamping types (bonded, inlay, and caliper type) were studied on the influence on the samples’ surface roughness (Ra) improvement and the mass loss. The results showed that the increase of the mass loss and the reduction of roughness occurred with increasing the polishing load, the polishing time, and the polishing plate linear velocity, respectively. Whilst, the X-ray diffraction intensity of (400) crystalline surface of each polished sample was enhanced. Among the three clamping types, the bonded clamping type possessed the fastest removal rates, up to 25.2 nm/h. A polishing evaluation parameter, K, was defined as KRam, i.e., representing the improvement in surface roughness obtained per unit mass loss. According to variation of the parameter K, the DFP procedure could be divided into two stages, “the roughness improvement domination stage” and “the mass loss domination stage”, with the former having higher K values than the latter. K values increased monotonically with the increase of the polishing plate linear velocity, whilst they were influenced complicatedly by the polishing load and the polishing time.
    Influence and driving force of administrative division adjustment on urban spatial expansion: a case study of withdrawal from city into district in Jiutai, Changchun City
    DONG Yaojia, WANG Fuyuan, WANG Kaiyong
    2024, 41 (5): 612-624.  DOI: 10.7523/j.ucas.2022.080
    Abstract ( 243 ) PDF (0KB) ( 0 )
    Removing counties (cities) into districts is one of the main modes of administrative division adjustment, which has an impact on the urban spatial structure. Using multi-temporal remote sensing images of Changchun, administrative division vector graphics and statistical survey data of social and economic conditions, this paper analyzes the evolution of construction land and economic development in Changchun City before and after Jiutai was withdrawn from the city and divided into districts. Utilizing ENVI software, GIS technology, and other means, this paper revealed the impact of Jiutai’s withdrawal from the city and the establishment as a district on the spatial expansion of Changchun City at the two-level spatial scale of Changchun City and Jiutai District. The research found that: 1) Dismantling the city into districts accelerated the expansion process of Jiutai District, which further affected the direction and extent of urban spatial expansion in Changchun City. 2) The decommissioning of the city into districts caused Jiutai and the main urban area of Changchun to converge towards each other, and the spatial distance between the two districts gradually narrowed. 3) The “polarization effect” of the Jiutai District became more pronounced after the city was withdrawn and divided into districts, and high-density clusters appeared in the main urban area of Changchun. 4) The division of counties (cities) into districts is an important driving force for urban spatial expansion, primarily reflected in three aspects: policy, industry, and land use.
    Remote sensing classification and extraction of alpine wetlands information in summer in Dam Qu Watershed, the source of Yangtze River
    XIE Wanrong, LIU Shaochuang, WU Yunjia, ZHANG Shuo
    2024, 41 (5): 625-635.  DOI: 10.7523/j.ucas.2023.031
    Abstract ( 138 ) PDF (0KB) ( 0 )
    As the real source of the Yangtze River, Dam Qu Watershed is covered with a large number of alpine wetlands. Due to the dispute on the determination of the source of the Yangtze River in early years and difficulties in scientific research caused by the harsh natural environment, Dam Qu Watershed has not received widespread attention.Consequently, research on wetlands in this area is limited, particularly in high-resolution wetland classification, leaving a significant gap in the literature. Based on Sentinel-2B images from August 19, 2020, the information on each category of alpine wetlands in Dam Qu Watershed was extracted by using the hierarchical classification method of object-oriented features, and the horizontal and vertical distribution characteristics of wetlands were summarized in combination with the surface morphology and texture of the study area. The results show that the alpine wetlands in Dam Qu Watershed are divided into three first-level categories and nine second-level categories, with a total area of 3 364.74 km2, of which the main part is marsh wetlands, with an area of 2 908.94 km2, accounting for 86.45% of the total area of wetlands. The areas of river wetlands and lake wetlands are similar, at 269.28 km2 and 186.52 km2, respectively. In addition to alpine wetlands, there are permanent glaciers and snow in the watershed, with an area of 107.17 km2.The horizontal distribution of wetlands in the watershed is generally characterized by more wetlands in the southeast and fewer in the northwest. These wetlands are mainly concentrated in the flat beach surrounded by hills or the catchment area with low terrain and poor drainage, as well as the foot of shady slope. In the vertical direction, alpine wetlands are mainly distributed in the range of 4 650-5 100 m above sea level. As the terrain rises, wetland resources gradually decrease. Areas above 5 400 m are mainly covered by glaciers and snow, with almost no alpine wetland. This study provides a scientific basis for the effective protection and rational utilization of wetland resources in the source of the Yangtze River.
    Radiometric correction of multispectral camera based on filter wheel
    LIU Yang, FANG Junyong, LIU Xue, WANG Xiao, ZHANG Xiaohong
    2024, 41 (5): 636-643.  DOI: 10.7523/j.ucas.2022.083
    Abstract ( 178 ) PDF (0KB) ( 0 )
    Aiming at the problems of limited acquisition method, band registration, and data quantification of near-surface multispectral images, this paper introduces a self-developed filter wheel multispectral camera that can work continuously in the field, has simple operation and easy band registration, and completes relative radiometric correction and absolute radiometric calibration with high-precision integrating sphere in the laboratory. The multi-stage brightness calibration method and empirical linear method are used to establish a calibration model to correct the uneven response of multi-band multispectral camera and calculate the spectral radiation brightness at the pupil. In this paper, we design data acquisition and processing experiments of different brightness and integration time, and give the optimal integration time range for each band of the new camera. The results of radiometric correction and calibration show that the selected correction coefficient has high stability and reliability for multispectral images under different imaging conditions, and is suitable for radiometric correction of filter wheel-type multispectral cameras. The calibration results can be used to quantitatively retrieve the target parameters of the land surface, which has broad application prospects in the fields of crop monitoring, environmental monitoring and protection.
    Chirp scaling algorithm based on fractional Fourier transform and image weighted entropy
    SHANG Min, XU Xianghui
    2024, 41 (5): 644-653.  DOI: 10.7523/j.ucas.2022.084
    Abstract ( 216 ) PDF (0KB) ( 0 )
    In order to solve the problem of Doppler parameters varying with skew and low image resolution in the traditional chirp scaling (CS) imaging algorithm based on Fourier transform and matched filtering, an algorithm to optimize CS imaging algorithm using fractional Fourier transform (FRFT) is proposed. Firstly, the echo signal model of squint synthetic aperture radar (SAR) is established, and the echo signal model is derived using FRFT instead of matched filtering. To search for the optimal azimuth rotation angle, the cost function of the image is established according to the weighted minimum entropy, and the gradient descent optimization algorithm of the momentum method is used for iterative calculation. Finally, a higher-resolution SAR image is obtained. To verify the effectiveness of the algorithm, experiments were carried out on point target simulation data and measured SAR data sets respectively. The results show that, compared with the traditional CS imaging algorithm, the proposed algorithm achieves a narrower main lobe width, lower sidelobe, and clearer images.
    Building extraction method based on MFF-Deeplabv3+ network for high-resolution remote sensing images
    CHEN Jingwei, LI Yu, CHEN Jun, ZHANG Hongqun
    2024, 41 (5): 654-664.  DOI: 10.7523/j.ucas.2023.010
    Abstract ( 313 ) PDF (0KB) ( 0 )
    Automatic extraction of building information from high-resolution remote sensing images is of great significance in the fields of environmental monitoring, earthquake mitigation, and land use, making it a research hotspot in the field of high-resolution remote sensing applications. In order to improve the accuracy of building extraction from high-resolution remote sensing images, a building extraction method based on MFF-Deeplabv3+(multiscale feature fusion-Deeplabv3+) network for high-resolution remote sensing images is proposed in this paper. First, the multi-scale feature enhancement module is designed to enable the network to capture more scale context information; then, the feature fusion module is designed to effectively fuse deep features with shallow features to reduce the loss of detail information; finally, the attention mechanism module is introduced to select accurate features adaptively. In the comparison experiments of the Inria building dataset, MFF-Deeplabv3+ achieved the highest accuracy in PA, MPA, FWIoU, and MIoU metrics with 95.75%, 91.22%, 92.12%, and 85.01%, respectively, while the generalization experiments of the WHU building dataset achieved good results. The results show that this method extracts building information from high-resolution remote sensing images with high accuracy and strong generalization.
    A trajectory planning based on characteristic parameter fitting for multi-ground targets of the ground tracks of two satellites
    HUANG Xiongwei, WANG Shuquan, ZHANG Yang, HE Shengmao
    2024, 41 (5): 665-676.  DOI: 10.7523/j.ucas.2022.070
    Abstract ( 245 ) PDF (0KB) ( 0 )
    In order to solve the problems related to the ground tracks of satellites for Earth observation with multiple orbital maneuvering capabilities, multi-detection targets, and multi-detector coordination, a fast calculation method of the ground tracks of satellites based on characteristic parameter fitting is proposed. An optimization model is established based on the database about the splicing method of the ground tracks of satellites. Firstly, the characteristic parameters describing the ground tracks of satellites are analyzed and refined, and polynomials are used to fit these characteristic parameters to achieve fast calculation. Then, an observation code database is established according to the detection target, and the database is further organized into a trajectory database. Finally, an optimization model based on the trajectory database is established to solve all problems on the ground tracks of satellites. The simulation of a fast full coverage task for a fixed target in CTOC11 (the 11th China Trajectory Optimization Competition) was completed within 19.19 days. The results show that the design method and scheme adopted in this paper can be used for the design of ground tracks of satellites in various near-circular orbits.
    A pose estimation algorithm for spatial non-cooperative targets based on point cloud registration
    GUO Sujie, GUO Chongbin
    2024, 41 (5): 677-686.  DOI: 10.7523/j.ucas.2023.027
    Abstract ( 241 ) PDF (0KB) ( 0 )
    Aiming at pose estimation for non-cooperative targets in on-orbit maintenance operations of space robots, we propose a pose estimation algorithm based on point cloud registration. Firstly, the hybrid filtering algorithm preserves the shape of the point cloud to the greatest extent while reducing its density. Then, the principal component analysis algorithm is used to establish the eigenvector transformation. The RANSAC algorithm is employed for coarse registration, followed by the improved ICP algorithm for fine registration, which results in the estimation of the rotation matrix, translation matrix, and attitude. Experiments are carried out to evaluate the performance of the algorithm. Simulated satellite point cloud models processed by rotation-translation transformations and Gaussian noise are used to verify the point cloud registration performance. The satellite model scene collected by a TOF camera point cloud is used to validate the pose estimation algorithm. The results show that the proposed algorithm has improved anti-noise performance, and showed higher robustness compared to traditional registration algorithms, with rotation attitude angle error less than 0.4° and displacement error less than 3 mm.
    Point cloud compression of deep learning based on multi-scale feature and attention mechanism
    HUANG Yulin, LIANG Lei, LI Weijun, XI Xiaohuan
    2024, 41 (5): 687-694.  DOI: 10.7523/j.ucas.2023.077
    Abstract ( 209 ) PDF (0KB) ( 0 )
    3D point clouds have extensive applications in the auto-drive, 3D real scene, and other fields. But complex scene requires massive point clouds to represent which brings great challenges to storage space, data processing and transmission bandwidth. A multi-scale attention point cloud geometry compression (MSA-GPCC) is proposed to compress point cloud data based on multi-scale features, attention mechanism, and variational auto-encoders (VAE). Experiments and analysis are carried out based on MPEG data sets. The results show that MSA-GPCC performs better than those of the traditional G-PCC and deep-learning-based D-PCC algorithms, D1 BD-PSNR is improved by 7.72 and 4.91 dB respectively, and D2 BD-PSNR is improved by 5.56 and 3.09 dB respectively.
    Central node selection strategy of spatial robot cluster based on data and compression ratio prediction
    YANG Xuan, CHEN Hongyu
    2024, 41 (5): 695-704.  DOI: 10.7523/j.ucas.2023.007
    Abstract ( 85 ) PDF (0KB) ( 0 )
    In recent years, the in-orbit service technology of space robot clusters has attracted the attention of various space powers. When the space robot cluster serves the target spacecraft in orbit, the collected target information needs to be transmitted to the central satellite. How to balance the communication power consumption of each node in the cluster is an important research problem. Aiming at the problem of optimal communication power between the space robot cluster and the data hub satellite, a central node selection algorithm (data and data compression ratio prediction,DCP) based on data and compression ratio prediction was proposed in this paper. Since the communication power consumption in the cluster communication is mainly related to the communication distance and communication duration (data volume), the data and compression rate at future times can be predicted based on the movement trajectory of the cluster, thus selecting the optimal central node of the cluster and constructing the communication link. In the experimental simulation, compared to a fixed point, degree centrality, betweenness centrality, and closeness centrality, DCP algorithm can effectively reduce the power consumption of cluster communication, and the error is less than 3% compared with the actual optimal result.
    Seamless image completion via GAN inversion
    YU Yongsheng, LUO Tiejian
    2024, 41 (5): 705-714.  DOI: 10.7523/j.ucas.2022.075
    Abstract ( 402 ) PDF (0KB) ( 0 )
    Image completion is widely used in unwanted object removal and media editing, which aims to find a semantically consistent way to recover corrupted images. This paper is based on generative adversarial network (GAN) inversion, which leverages a pre-trained GAN model as an effective prior to filling in the missing regions with photo-realistic textures. However, existing GAN inversion methods ignore that image completion is a generative task with hard constraints, making final images have noticeable color and semantic discontinuity issues. This paper designs a novel bi-directional perceptual generator and pre-modulation network to seamlessly fill in the images. The bi-directional perceptual generator uses extended latent space to help the model perceive the non-missing regions of the input images in terms of data representations. The pre-modulated networks utilize a multiscale structure further providing more discriminative semantics for the style vectors. In this paper, experiments are conducted on Places2 and CelebA-HQ datasets to verify that the proposed method builds a bridge between GAN inversion and image completion and outperforms current mainstream algorithms, especially in FID metrics up to 49.2% enhancement at most.
    Brief Report
    Low-complexity CA-SCL decoding optimization algorithm for low-orbit satellite communication
    HU Xiuqi, HOU Huiling, LIANG Guang, YU Jinpei
    2024, 41 (5): 715-720.  DOI: 10.7523/j.ucas.2023.016
    Abstract ( 205 ) PDF (0KB) ( 0 )
    Based on the low-orbit satellite communication environment with limited hardware resources, this paper uses polarization code as the channel coding method, and combines the successive redundancy check (CRC) assisted successive cancellation list (SCL) decoder (CA-SCL) with critical sets and adaptive algorithms to propose an optimized CA-SCL decoder (OCASCL). The performance of the OCASCL decoder is better than the classic SCL decoder, the computational complexity can be reduced by 65%-70%.
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    Analysis of Shanghai and Shenzhen stock market using Copula-VaR method
    Hao Li-Xiang, Cheng Xi-Jun
    Journal of University of Chinese Academy of Sciences    2008, 25 (5): 682-686.   DOI: 10.7523/j.issn.2095-6134.2008.5.017
    Abstract1565)      PDF(pc) (727KB)(17292)       Save
    Risk analysis of Portfolio is studied ,by comparing Copula functions and the traditional VaR methods,mixing copula is made. By backtesting ,the empirical research shows that mixing Copula method makes better VaR model .
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    Shape-dependent effects of nanoceria on the activity of Pd/CeO2 catalysts for CO oxidation
    WANG Lei, MAO Junyi, YUAN Qing, HUANG Tao
       2015, 32 (5): 594-604.   DOI: 10.7523/j.issn.2095-6134.2015.05.004
    Abstract563)      PDF(pc) (9359KB)(15099)       Save

    The redox property of palladium nanoparticles (NPs) is pivotal to CeO2 supported Pd catalysts in oxidation reactions and is closely related to the structure of Pd-CeO2 interface. Herein, we report that low-temperature CO oxidation activity of Pd/CeO2 highly depends on the shape and crystal plane of CeO2 supports. Pd/CeO2 catalysts with CeO2 nanoocthedrons (NOCs) and nanocubes (NCs) as supports were prepared by colloidal-deposition method. Results show that Pd/CeO2 NOCs with ceria {111} facets enclosed exhibited much higher catalytic activity than Pd/CeO2NCs with ceria {100} facets exposed. DFT calculations revealed that the redox property of surface Pd species may play important roles in determining the reducibility and activity of catalysts. The PdOx to Pd cycle is more facile on Pd4@CeO2(111) than on Pd4@CeO2(100), which is dictated by the Pd-ceria interaction in the end. Our results show that the redox property of surface Pd is pivotal to the reducibility and activity of Pd/ceria catalysts, which could be tuned by manipulation of the Pd-CeO2 interaction via tuning the exposed facets of ceria support.

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    Advances in light field photography technique
    NIE Yun-Feng, XIANGLI Bin, ZHOU Zhi-Liang
       2011, 28 (5): 563-572.   DOI: 10.7523/j.issn.2095-6134.2011.5.001
    Abstract3154)      PDF(pc) (1045KB)(6559)       Save

    Light field is a representation of full four-dimensional radiance of all rays with spatial and angular information in free space, and capture of light field data enables many new development potentials for computational imaging. The historical development of light field photography is summarized, and typical light field photography devices are categorized in view of capture methods for 4D light field. Based on the principles of light field camera, computational imaging theorem, refocusing theory, synthetic aperture refocusing algorithm, and light field microscopic technology are emphatically described. Finally, the promising application perspectives and existing critical issues of light field imaging are discussed.

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    Upstream promoter sequences of Arabidopsis GH3 gene family
    SUN Tao, CHAI Tuan-Yao, ZHANG Yu-Xiu
       2010, 27 (6): 847-852.   DOI: 10.7523/j.issn.2095-6134.2010.6.017
    Abstract2373)      PDF(pc) (154KB)(6035)       Save

    GH3 genes belong to a primary auxin-response gene family. The 10 promoter sequences of Arabidopsis GH3 genes were analyzed using bioinformatics method. The results show that the transcription start site of these genes is generally 65~145bp away from the start codon, and the TATA boxes are located in the (-24)-(-40)bp. MDB and MatInspector analyses show that most upstream regions of these GH3 genes contain the cis-elements required for tissue and organ-specific expression responding to phytohormones and external environment, indicating that the expressions of GH3 genes are strictly controlled by multi-factors. Gene chip data show that AuxREs is very important for GH3 genes in response to IAA treatment,but it is not the unique cis-element for auxin response.

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    Quality Evaluation for Three Textual Document Clustering Algorithms
    LIU Wu-Hua, LUO Tie-Jian, WANG Wen-Jie
       2006, 23 (5): 640-646.   DOI: 10.7523/j.issn.2095-6134.2006.5.012
    Abstract2837)      PDF(pc) (832KB)(5554)       Save
    Textual document clustering is one of the effective approaches to establish a classification instance of huge textual document set. Clustering Validation or Quality Evaluation techniques can be used to assess the efficiency and effective of a clustering algorithm. This paper presents the quality evaluation criterions from outer and inner. Based on these criterions we take three typical textual document clustering algorithms for assessment with experiments. The comparison results show that STC(Suffix Tree Clustering) algorithm is better than k-Means and Ant-Based clustering algorithms. The better performance of STC algorithm comes from that it takes accounts the linguistic property when processing the documents. Ant-Based clustering algorithm’s performance variation is affected by the input variables. It is necessary to adopt linguistic properties to improve the Ant-Based text clustering’s performance.
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    Investigation on the Preparation of μ-Sized PMMA Microspheres by the Dispersion Polymerization
    WU Shao-Gui, LIU Bai-Ling
       2006, 23 (3): 323-330.   DOI: 10.7523/j.issn.2095-6134.2006.3.007
    Abstract2242)      PDF(pc) (1120KB)(5008)       Save
    The micron-grade PMMA microspheres with narrow size distribution were prepared by dispersion polymerization. The mechanism of the dispersion polymerization was discussed. The factors influencing both the size and size distribution of the microspheres including initial concentrations of the initiator, monomer, stabilizer, the polarity of the medium and the reaction conditions were studied. The results indicated that the size and size distribution of microspheres both increased with initial concentrations of initiator and monomer. Increasing the amount of the stabilizer resulted in decreasing size and narrowing size distribution of microspheres. Other factors such as the polarity of medium and the reaction temperature had great influences too. By controlling these factors, the desired-size monodisperse microspheres could be obtained.
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    SA-DBSCAN:A self-adaptive density-based clustering algorithm
    XIA Lu-Ning, JING Ji-Wu
       2009, 26 (4): 530-538.   DOI: 10.7523/j.issn.2095-6134.2009.4.015
    Abstract3310)      PDF(pc) (268KB)(4538)       Save

    DBSCAN is a classic density-based clustering algorithm. It can automatically determine the number of clusters and treat clusters of arbitrary shapes. In the clustering process of DBSCAN, two parameters, Eps and minPts,have to be specified by uses. In this paper an adaptive algorithm named SA-DBSCAN was introduced to determine the two parameters automatically via analysis of the statistical characteristics of the dataset, which enabled clustering process of DBSCAN fully automated. Experimental results indicate that SA-DBSCAN can select appropriate parameters and gain a rather high validity of clustering.

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    A block Gram-Schmidt algorithm with its application
    ZHAO Tao, JIANG Jin-Rong
       2009, 26 (2): 224-229.   DOI: 10.7523/j.issn.2095-6134.2009.2.011
    Abstract2783)      PDF(pc) (820KB)(4198)       Save

    Gram-Schmidt algorithm is one of the fundamental methods in linear algebra, which is mainly used to compute QR decomposition. The classical and modified Gram-Schmidt are both based on level 1 or level 2 BLAS operations which have low cache reuse. In this paper, a new block Gram-Schmidt algorithm is proposed. The new algorithm ensures the orthogonality of resulting matrix Q is close to machine precision and improves performance because of using level 3 BLAS. Numerical experiments confirm the favorable numerical stability of the new algorithm and its effectiveness on modern computers.

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    Software protection method based on self-modification mechanism
    WANG Xiang-Gen, SI Duan-Feng, FENG Deng-Guo, SU Pu-Rui
       2009, 26 (5): 688-694.   DOI: 10.7523/j.issn.2095-6134.2009.5.015
    Abstract1637)      PDF(pc) (173KB)(4163)       Save

    In this paper, we present a new method based on self-modification mechanism to protect softwares against illegal acts of hacking. The key idea is to converse key codes into data in the original program so as to make programs harder to analyze correctly. Then, we translate data to executable codes by enabling the virtual memory page which stores the hidden code to be executable at run-time. Our experiments demonstrate that the method is practical and efficient.

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    Design of high resolution camera system based on full frame CCDs
    LIU Guang-Lin, YANG Shi-Hong, WU Qin-Zhang, XIA Mo
       2007, 24 (3): 320-324.   DOI: 10.7523/j.issn.2095-6134.2007.3.008
    Abstract2518)      PDF(pc) (1138KB)(4038)       Save
    A design of high resolution camera system based on DALSA’ s CCD evaluation kit EKxxxx was presented. It was composed of a pulse pattern generator (SAA8103), a vertical line driver (TDA9991), four analog-to-digital interfaces (TDA9965) and a system controller (P89LV51RD2). Camera link with medium configuration was adopted to transfer digital images. The software for controlling and debugging the camera was developed. To correct the non-uniformity of 4 outputs, a method based on two-point correction was described. The system can acquire ultra high resolution pictures at a high frame rate thus it is suitable for aero photography.
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    Heavy metals in aerosol in China: pollution, sources,and control strategies
    TAN Ji-Hua, DUAN Jing-Chun
       2013, 30 (2): 145-155.   DOI: 10.7523/j.issn.1002-1175.2013.02.001
    Abstract3594)      PDF(pc) (1395KB)(3816)       Save

    In recent years, the heavy metal pollution incidents in China were frequently reported. However, studies on pollution, sources, and control strategies of atmospheric heavy metals in China are rare. We summarize the research results reported in recent years. The features of pollution level, seasonal variation, regional differences, size distribution of the atmospheric heavy metal elements including Pb, V, As, Mn, Ni, Cr, and Cd in China are analyzed. The main sources, current control status, and control technologies of atmospheric heavy metals are discussed. Comprehensive suggestions for China's heavy metal pollution control are put forward based on the summarization of the progress and experience of the atmospheric heavy metal pollution control in other countries and regions.

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    A CMOS high performance 50MSPS sample/hold circuit
    LI Tie, GUO Li, BAI Xue-fei
       2007, 24 (6): 788-793.   DOI: 10.7523/j.issn.2095-6134.2007.6.010
    Abstract2667)      PDF(pc) (1540KB)(3742)       Save
    A high performance CMOS sample/hold circuit is presented, which achieves the precision of 10-bit over Nyquist band in 50-MHz sampling frequency at 3.3-V supply. This circuit uses full differential circuits, bottom-plate sampling, bootstrap circuits and high performance gain-boost operational amplifier. Simulation in 0.35-μm CMOS process shows the circuit consumes 18-mW of power.
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    An easy-to-deploy behavior monitoring scheme for Android applications
    WANG Xueqiang, LEI Lingguang, WANG Yuewu
       2015, 32 (5): 689-694.   DOI: 10.7523/j.issn.2095-6134.2015.05.016
    Abstract1057)      PDF(pc) (1223KB)(3710)       Save

    Malicious applications pose tremendous threats to Android platform. More than 90% of malicious codes are introduced in the form of Android apps. Hence, behavior monitoring scheme for Android applications are required in order to resolve the problem. However, most of the schemes are based on system customization and hard to deploy on devices for Android's fragmentation problem. In this paper, an easy-to-deploy Android application monitoring method on the basis of process hijacking is proposed after analysis of Android process model and code execution details. The method depends on Dalvik interpreter entry point and system call interception. The authors created a fully usable prototype of the system, and the evaluation results show that the system is easy to deploy, provides a whole-scale behavior of Android applications, and incurs little performance overhead.

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    Experiment and numerical simulation of thermal conductivity of uranium dioxide
    WANG Zeng-Hui, HUANG Xiao-Feng
       2009, 26 (3): 415-418.   DOI: 10.7523/j.issn.2095-6134.2009.3.017
    Abstract2413)      PDF(pc) (929KB)(3613)       Save

    Uranium dioxide is a kind of steady nuclear fuel that has the characteristic of high melting point and steady property. The thermal conductivity of uranium dioxide can directly influence the temperature distribution of nuclear fuel and the max temperature of the center of nuclear fuel. The experimental results and expression of thermal conductivity have been compared in the paper. The deviation between the experiment results has decreased. The non-equilibrium molecular dynamics simulation results are in good agreement with the experiment results in medium temperature region. In low temperature region, it is necessary to add the quantum correction to the kinetic energy computation of phonon. In high temperature region, it is needed to use the accurate potential model and build up the electron gas energy transport model and photon radiation energy transport to study the thermal conductivity well and truly for the nuclear reactor safety design and uranium dioxide engineering application.

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    Optimized Regulation Model of Human-Earth System Based on System Dynamics
    CHENG Ye-Qing
       2006, 23 (1): 83-90.   DOI: 10.7523/j.issn.2095-6134.2006.1.016
    Abstract2103)      PDF(pc) (816KB)(3495)       Save
    study of human-earth system is the most important content in geography; regional sustainable development relies on the reasonable structure optimal model and effective regulation of regional human-earth system. County region is a complex and opening human-earth system, taking Huangling county as an example, the environment, resources exploitation, economic development and structure evolvement of industry were systematically analyzed. And the systematical dynamic model was established and multi-projects were simulated with the theory and method of system dynamic. Optimized regulation models of human-earth system evolvement were educed based on three projects: (1) Traditional evolvement method. The intensity of resource exploitation and environment pollution is the least, but the speed of its economy development is the lowest, which restrict social sustainable development and economic reproduction. (2) Economy development method. The intensity of resource exploitation and environment pollution is the worst, economic development mostly depends on higher investment and pollution, which is a traditional mode of unsustainable development. (3) Harmonious development mode. The mode considers not only economic sustainable development and natural recourses utilizing reasonably, but also gives more attention to environment protection and harmonious development of industry, agriculture, tourism and so on. It is the optimized mode of the human-earth system evolvement.
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    Rice Varietal Improvement and Rice Production in China
    LI Hai-Ming
       2007, 24 (1): 1-8.   DOI: 10.7523/j.issn.2095-6134.2007.1.001
    Abstract1896)      PDF(pc) (832KB)(3463)       Save
    The specific objective of the study is to analyse the adoption of improved varieties and the changes in characteristics of varieties across China. It also estimates the contribution of varietal improvement to rice production in China. The results indicated that the story of rice improvement over the past 50 years stood as an enormous success. Nearly 30% of the net gain in rice production came from varietal improvement. Compared with the beginning of 1980s, the numbers of released varieties have been improved by 1. 5 times, the share of total rice area planted to varieties with resistances has increased 10%, and the planting area of high-quality varieties has increased 50%. However, the declining contribution of varietal improvement since 1997 pointed out that government should encourage breeders to explore elite germplasm, improve breeding level, and break through yield stagnates so that varietal improvement can contribute greater to rice production.
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    Spectrophotometric determination of polyphenols in Quercus mongolicus Fisch leaves by means of Folin-ciocalteu reagent
    ZHANG Guo-You, TANG Ling, CHEN Wei, HE Xing-Yuan, HUANG Wei
       2009, 26 (3): 319-322.   DOI: 10.7523/j.issn.2095-6134.2009.3.005
    Abstract1909)      PDF(pc) (152KB)(3362)       Save

    The total polyphenols(TP)content of Quercus mongolicus Fisch leaves extracts was analyzed by Folin-ciocalteu colorimetry,with gallic acid as standard.The method was improved and verified in the aspects of stability, linearity,precision and accuracy.The results showed that the total polyphenols content of Quercus mongolicus Fisch leaves extracts could be well calculated according to their colorimetric absorption at 760nm by applying Folin-ciocalteu reagent (1mol/L) 0.15mL and 10% volume fraction of Na2CO3 0.15mL at 25℃ for 80min. The (TP)content in Quercus mongolicus Fisch leaves determinated by the method was 6.39% and RSD was 1.90%.

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    Recent Advances in the Biodegradability of PVA and its Derivative Material
    ZHANG Hui-Zhen, LIU Bai-Ling, LUO Rong
       2005, 22 (6): 657-666.   DOI: 10.7523/j.issn.2095-6134.2005.6.001
    Abstract781)      PDF(pc) (1257KB)(3307)       Save

    Poly (vinyl alcohol) (PVA) and its derivatives,the excellent water-soluble polymers,have attracted more and more attention,as they show the usability in many processes,as well as possess the promise of degradation in the presence of some specific microbials.In the present paper,the recent advances in the biodegradation of PVA and its derivatives,including the mechanism,influential factors,evaluation method and degradation environment etc,have been reviewed.Moreover,the latest development of PVA-based blendsPcomposites and their biodegradation is also introduced in the present article.

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    An Improved K-means Algorithm Based on Optimizing Initial Points
    QIN Yu, JING Ji-Wu, XIANG Ji, ZHANG Ai-Hua
       2007, 24 (6): 771-777.   DOI: 10.7523/j.issn.2095-6134.2007.6.008
    Abstract2710)      PDF(pc) (833KB)(3299)       Save
    K-means is an important clustering algorithm. It is widely used in Internet information processing technologies. Because the procedure terminates at a local optimum, K-means is sensitive to initial starting condition. An improved algorithm is proposed, which searches for the relative density parts of the database and then generates initial points based on them. The method can achieve higher clustering accuracies by well excluding the effects of edge points and outliers, as well as adapt to databases which have very skewed density distributions.
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    MEIL--A routing protocol with high throughput over wireless mesh network
    ZHANG Rui, HONG Pei-Lin ,LU Han-Cheng , ZHANG Xing
       2007, 24 (4): 473-479.   DOI: 10.7523/j.issn.2095-6134.2007.4.011
    Abstract2418)      PDF(pc) (977KB)(3131)       Save
    Because of the unique characteristics over wireless mesh networks, such as multi-radio multi-channel and static nodes, traditional Ad hoc network routing protocols can not work very well, which are based on the condition of “shortest path”. This paper presents a novel routing protocol named MEIL for wireless mesh networks. It designs routing metrics according to the wireless link loss, interference between channels and the load of wireless mesh nodes. MEIL chooses the route with lower loss, smaller interference and lighter load, so it can improve the throughput of the network efficiently. The simulation results show that MEIL performs much better than the AODV routing protocol and the DSDV+ETX algorithm under the circumstances of various services, and it is suitable for wireless mesh networks.
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    Learning path planning methods
    LUO Zhongkai, ZHANG Libo
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 11-27.   DOI: 10.7523/j.ucas.2022.061
    Abstract1007)      PDF(pc) (2927KB)(1488)       Save
    This review aims to guide the future development of related research in the field of learning path planning through the analysis of the current research status of learning path planning. Specifically, this review first introduces the definition of learning path planning and the commonly used parameters in learning path planning methods; then, it classifies in detail according to the algorithms used to generate learning path planning and summarizes the advantages and disadvantages of various learning path planning methods. In addition, the data set and evaluation method used by the learning path planning method is introduced. Finally, the challenges faced by the learning path planning method are summarized and the future development trend is predicted.
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    Solving quadratic assignment problem based on actor-critic framework
    LI Xueyuan, HAN Congying
    Journal of University of Chinese Academy of Sciences    2024, 41 (2): 275-284.   DOI: 10.7523/j.ucas.2022.031
    Abstract660)      PDF(pc) (4937KB)(1202)       Save
    The quadratic assignment problem (QAP) is one of the NP-hard combinatorial optimization problems and is known for its diverse applications in real life. The current relatively mature heuristic algorithms are usually problem-oriented to design customized algorithms and lack the ability to transfer and generalize. In order to provide a unified QAP solution strategy, this paper abstracts the flow matrix and distance matrix of QAP problem into two undirected complete graphs and constructs corresponding correlation graphs, thus transforming the assignment task of facilities and locations into node selection task on the association graph. Based on actor-critic framework, this paper proposes a new algorithm ACQAP(actor-critic for QAP). Firstly, the model uses a multi-headed attention mechanism to construct a policy network to process the node representation vectors from the graph convolutional neural network; Then, the actor-critic algorithm is used to predict the probability of each node being output as the optimal node. Finally, the model outputs an action decision sequence that satisfies the objective reward function within a feasible time. The algorithm is free from manual design and is more flexible and reliable as it is applicable to different sizes of inputs. The experimental results show that on QAPLIB instances, the algorithm has stronger transfer and generalization ability under the premise that the accuracy is comparable to the traditional heuristic algorithm, while the assignment cost for solving is less compared to the latest learning-based algorithms such as NGM, and the deviation is less than 20% in most instances.
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    Allometric equation and biomass estimation of Eucalyptus in Fujian
    ZHENG Xiaoman, WENG Xian, OU Linglong, REN Yin
    Journal of University of Chinese Academy of Sciences    2024, 41 (3): 321-333.   DOI: 10.7523/j.ucas.2022.074
    Abstract564)      PDF(pc) (10322KB)(589)       Save
    The estimation of forest biomass at individual tree scale is the basis for the estimation of forest biomass at the regional scale. This paper aims at developing a reliable and effective allometric equation for Eucalyptus in Fujian in order to improve the estimation accuracy of Eucalyptus biomass in this area and to provide basic supporting data for the sustainable forestry development of Eucalyptus. This study takes Eucalyptus, a major fast-growing and productive tree species in Southern China, as the research object. Using 90 Eucalyptus woods harvested in the field, the partitioning of Eucalyptus biomass among organs are studied, the optimal allometric equations are constructed, and the Eucalyptus root/shoot ratios are calculated and applied to estimate Eucalyptus root biomass. Results show Eucalyptus has the following biomass allocation strategies: the biomass proportion of trunks increases with increasing stand age, while that of branches, leaves, and roots decreases. The most feasible and effective way to estimate Eucalyptus root biomass is to use root/shoot ratio data with stand age. In the construction of the allometric equation for Eucalyptus biomass, the multiplicative power equation is better than the linear equation, and the optimal independent variable varied by organ type. This paper provides data and theoretical support for the accurate estimation of Eucalyptus plantation biomass, and has implications for species growth patterns, survival strategies, and even forest ecological management.
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    Identification of core rumor spreaders in online social networks based on multi-stage deep model
    LI Yuan, ZHANG Qi, ZHU Jianming, JIAO Jianbin
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 136-144.   DOI: 10.7523/j.ucas.2022.057
    Abstract504)      PDF(pc) (3614KB)(507)       Save
    Online social networks have become the disaster areas where rumors grow. It is of great significance to identify core rumor spreaders for rumor prevention and control. The traditional rumor control model is mainly based on the dynamics of rumor propagation, and it is mainly focused on in-event or post-event control. In view of the timeliness of rumor control, this paper proposes a multi-stage graph convolutional network based on multi-dimensional features (MSF-GCN) deep learning model to accurately locate core rumor spreaders as early as possible and block rumor diffusion from the source. This work compares the MSF-GCN method with other three baseline methods on rumor data set, and the experimental results verify that our method is more efficient.
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    Mahler measure of a two-variable polynomial
    ZHANG Anhao, TANG Guoping
    Journal of University of Chinese Academy of Sciences    2024, 41 (2): 145-150.   DOI: 10.7523/j.ucas.2022.060
    Abstract480)      PDF(pc) (841KB)(550)       Save
    In this paper, we express the Mahler measure of a two-variable polynomial P(x,y)=(x2+1)y2+2(x2+x)y+x(x2+1) as a linear sum of some Bloch-Wigner Dilogarithm functions. and prove that the Mahler measure of P(x,y) is rationally proportional to L'(χ-3,-1):m(P(x,y))=5/2L'(χ-3,-1).
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    Asset selection based on high frequency Sharpe ratio and robust correlation coefficient
    ZHANG Shanhua, ZHANG Sanguo
    Journal of University of Chinese Academy of Sciences    2023, 40 (6): 834-842.   DOI: 10.7523/j.ucas.2022.039
    Abstract476)      PDF(pc) (4086KB)(307)       Save
    High frequency Sharpe ratio, a measure of return and risk, is commonly used in current portfolio construction method since it can avoid covariance matrix in high dimensional analysis. The newly proposed D-SEV measures the correlation between stock's return and high frequency Sharpe ratio index to further construct portfolio. However, there are some problems with the measure used in D-SEV, such as its lack of robustness and slow computational speed. In this paper, we propose to use a new correlation coefficient proposed by Sourav Chatterjee instead. The new correlation coefficient guarantee robustness, specifically it can reduce the impact of abnormal data on correlation, such as significant events that have a large impact on the asset prices. It is also extremely fast in its calculations. Extensive simulation demonstrate that new correlation coefficient outperforms D-SEV and other traditional methods in several different models. Actual Shanghai Securities Exchange (SSE) and Shenzhen Securities Exchange (SZSE) stock market data for 2019 and 2020 also show that the assets selected by new correlation coefficient earns 8% more excess annualized return than D-SEV, while it also owns a higher Sharpe ratio.
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    Local observation reconstruction for Ad-Hoc cooperation
    CHEN Hao, YANG Likun, YIN Qiyue, HUANG Kaiqi
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 117-126.   DOI: 10.7523/j.ucas.2022.028
    Abstract473)      PDF(pc) (9211KB)(446)       Save
    In recent years, multi-agent reinforcement learning has received a lot of attention from researchers. In the study of multi-agent reinforcement learning, the question of how to perform ad-hoc cooperation, i.e., how to adapt to a changing variety and number of teammates, is a key problem. Existing methods either have strong prior knowledge assumptions or use hard-coded protocols for cooperation, which lack generality and can not be generalized to more general ad-hoc cooperation scenarios. To address this problem, this paper proposes a local observation reconstruction algorithm for ad-hoc cooperation, which uses attention mechanisms and sampling networks to reconstruct local observations, enabling the algorithm to recognize and make full use of high-dimensional state representations in different situations and achieve zero-shot generalization in ad-hoc cooperation scenarios. In this paper, the performance of the algorithm is compared and analyzed with representative algorithms on the StarCraft micromanagement environment and ad-hoc cooperation scenarios to verify the effectiveness of the algorithm.
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    Nucleon resonances in γp→π-Δ++ photoproduction
    ZHU Yiming, YANG Fuzhong
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 35-41.   DOI: 10.7523/j.ucas.2021.0042
    Abstract463)      PDF(pc) (4263KB)(194)       Save
    The first measured high-precision data on the differential cross sections and polarization observable beam asymmetry Σ for the γp→π-Δ++ reaction from the LEPS collaboration are analyzed within a tree-level effective lagrangian approach. In addition to the t-channel π and ρ exchanges, the u-channel Δ exchange, the s-channel N exchange, and the interaction current that is required by the gauge invariance, the s-channel nucleon resonance exchanges are further taken into account to reproduce the data of LEPS. Numerical results show that, the data on Σ can not be well reproduced when no contributions from the s-channel resonance exchanges are introduced. Further analyses show that, by including the contribution from the resonance N(1860)5/2+, both the data on the differential cross sections and beam asymmetry Σ can be well reproduced.
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    Spatial and temporal distribution characteristics and influential factors of PM2.5 pollution in Beijing-Tianjin-Hebei
    SU Mengqian, SHI Yusheng
    Journal of University of Chinese Academy of Sciences    2024, 41 (3): 334-344.   DOI: 10.7523/j.ucas.2023.025
    Abstract461)      PDF(pc) (6043KB)(645)       Save
    The fine particulate matter PM2.5 could be harmful to human health and the atmospheric environment. Beijing-Tianjin-Hebei is one of the most serious regions in China in terms of atmospheric PM2.5 pollution. Based on PM2.5 concentrations data, natural factors data, and human activity factors data, this study used kriging interpolation and statistical analysis to explore the spatial and temporal distribution characteristics of atmospheric PM2.5 pollution in 13 cities of Beijing-Tianjin-Hebei in 2017 and then used correlation analysis models and factor analysis models to explore its influential factors. The results show that in Beijing-Tianjin-Hebei, 1) PM2.5 concentrations are low in the north and high in the south. The gradient of annual average concentrations between the southern and northern cities can reach up to 64μg/m3. 2) PM2.5 concentrations are high in winter and low in summer, high in the morning and evening, and low in the afternoon. PM2.5 concentration in winter is 1.3-2.8 times higher than in summer, and the daily differences in PM2.5 concentrations in all seasons are between 11-29μg/m3. 3) Atmospheric PM2.5 pollution is closely related to natural factors. Terrain and topography affect the processes of PM2.5 aggregation, transport, and dispersion. Wind speed, sunshine hours, and relative humidity are the dominant meteorological factors affecting atmospheric PM2.5 pollution, and PM2.5 concentrations have the strongest correlation with meteorological factors in winter. 4) Atmospheric PM2.5 pollution is closely related to human activities, which can be summarized into social economy factor, industrial pollutant discharge factor, and urban construction factor. The results of this study will help fill the gaps in air pollution prevention and control in Beijing-Tianjin-Hebei.
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    Interference avoidance strategy for LEO satellite based on transmit beam sidelobe nulling
    WANG Haiwang, ZOU Cheng, CHANG Jiachao, SHAO Fengwei, JIANG Quanjiang, LI Guotong
    Journal of University of Chinese Academy of Sciences    2024, 41 (4): 541-549.   DOI: 10.7523/j.ucas.2022.068
    Abstract458)      PDF(pc) (5608KB)(630)       Save
    With the rapid development of broadband low-orbit satellite systems, communication frequency bands such as Ku and Ka tend to be saturated gradually, and non-geostationary orbit (NGSO) satellites will inevitably cause interference to geostationary orbit (GSO) satellites operating at the same frequency. At present, a spatial isolation strategy is often adopted to avoid interference. NGSO satellites always produce the strongest interference to the collinear area. Increasing the isolation angle can reduce the interference, but it will greatly lose the coverage of the LEO satellite. This paper proposes an interference avoidance strategy based on sidelobe nulling of the transmit beam. The antenna array is divided into row and column elements by establishing the LEO satellite coordinate system. In the dimension of column elements, the robust LCMV algorithm is used to realize wide nulling. In the dimension of row elements, it is expanded in combination with beam direction, and finally forms a “null band” in the direction of the collinear area. Through simulation analysis, the proposed strategy can effectively reduce the interference avoidance isolation area of LEO satellites while avoiding collinear interference. The algorithm has low complexity and is easy to implement on satellites.
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    Robust individualized subgroup analysis
    ZHANG Xiaoling, REN Mingyang, ZHANG Sanguo
    Journal of University of Chinese Academy of Sciences    2024, 41 (2): 151-164.   DOI: 10.7523/j.ucas.2022.037
    Abstract453)      PDF(pc) (1144KB)(471)       Save
    Subgroup analysis of heterogeneous groups is a crucial step in the development of individualized treatment and personalized marketing strategies. Regression-based approaches are one of the main schools of subgroup analysis, a paradigm that divides predictor variables into two parts with heterogeneous and homogeneous effects and divides the sample into subgroups based on the heterogeneous effects. However, most of the existing regression-based subgroup analysis methods have two major limitations: First, they still consider the sample homogeneous within subgroups and do not fully consider individual effects; Second, the common contamination phenomenon of homogeneous effect variables is not taken into account, which will lead to large bias in the model results. To address these challenges, we propose a robust individualized subgroup analysis. We use a multidirectional separation penalty function to achieve individualized effects analysis for the heterogeneous part of the model and use γ-divergence to obtain robust estimates for the contaminated homogeneous part. We also propose an efficient alternating iterative two-step algorithm, combining coordinate descent and alternating direction method of multipliers (ADMM) techniques to implement this process. Our proposed method is further illustrated by simulation studies and analysis of a skin cutaneous melanoma dataset.
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    Design and implementation of fuzzy extractor for PUF
    SONG Minte, HOU Kai, RU Zhanqiang, WANG Zhengguang, SONG Helun
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 127-135.   DOI: 10.7523/j.ucas.2022.054
    Abstract452)      PDF(pc) (7892KB)(542)       Save
    The physical unclonable function (PUF) implemented on SRAM and other schemes exists inherent demerit of poor reproducibility for environmental factors such as voltage changes and thermal noise. This disadvantage greatly restricts functional application in cryptography, communication and other fields. In this paper, a fuzzy extractor with large error correction capacity is designed to reconstruct the original data of SRAM by means of BCH codes (Bose-Chaudhuri-Hocquenghem Codes). The SRAM PUF chip applying this design is manufactured on the Hua Hong Grace 0.11 μm CMOS platform with area of 306 267 μm2. The original BCH code has a code length of 127 bits and an error correction capability of 27 bits, which achieves the practical requirements of PUF applications.
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    Cause of thermal event moonquakes by thermos-elastic stress finite element models
    ZHANG Junce, HU Caibo, SHI Yaolin
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 50-64.   DOI: 10.7523/j.ucas.2022.045
    Abstract442)      PDF(pc) (14838KB)(404)       Save
    On the basis of the previous work, considering the solar heat absorbed by the lunar surface inward and the lunar thermal radiation heat released outward, as well as the nonlinearities of the thermodynamic parameters of the lunar soil related to the temperature and depth, we have developed a thermo-elastic coupled finite element parallel program suitable for the study of the temporal and spatial evolutions of the temperature, deformation, and thermal stress of the lunar soil, and have utilized the four sets of finite element models to investigate the effects of the characteristic thicknesses of the lunar soil on the temporal and spatial evolutions of the temperature, deformation and thermal stresses of the lunar surface. The computational results show that the temperature of the lunar surface varies periodically over one lunar day (29.5 Earth days), and the temperature of the equatorial lunar surface varies from 100 to 385 K, with the variation decaying exponentially with the increase of the depth, and the depth of influence reaches to about 50 cm. The temperature cyclic changes also cause the vertical displacement of the lunar surface to rise and fall, and the horizontal normal stress of the lunar surface in the form of compression and tension. In general, the horizontal stresses are compressed during the day and tensile during the night, with the fastest increase in tensile stress at 18:00 and the highest tensile stress at 06:00. The characteristic thickness of the lunar soil has a strong influence on the temporal and spatial distributions of the temperature and the horizontal positive stresses. The magnitude of thermal stresses may reach the tensile strength of the lunar surface. The fastest growth of tensile stress and the period of maximum amplitude coincide with the observed high frequency of thermal events on the lunar surface in the morning and evening.
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    SA-YOLO: self-adaptive loss object detection method under imbalance samples
    SU Yapeng, CHEN Gaoshu, ZHAO Tong
    Journal of University of Chinese Academy of Sciences    2024, 41 (3): 411-426.   DOI: 10.7523/j.ucas.2023.013
    Abstract438)      PDF(pc) (12585KB)(378)       Save
    The phenomenon of sample imbalance refers to the excessive number of background easy samples in the dataset but too few foreground hard samples, which means the sample suffers from inter-class imbalance and hard-easy imbalance. Most of the existing object detection methods are two-stage detectors based on proposed regions or one-stage detectors based on regression. When applied to imbalanced samples, it is impossible to avoid the over-dependence of the prediction bounding box generated in training on a large number of negative samples, which leads to overfitting of the model and low detection accuracy, poor accuracy and generalization. In order to achieve efficient and accurate object detection under imbalanced samples, a new SA-YOLO self-adaptive loss object detection method is proposed in the paper. 1) To address the sample imbalance problem, we propose the SA-Focal Loss function, which adjusts the loss adaptively for different datasets and training stages to balance inter-class samples and hard-easy samples. 2) In this paper, we construct the CSPDarknet53-SP network architecture based on the multi-scale feature prediction mechanism, which enhances the extraction ability of global features of difficult small target samples and improves the detection accuracy of difficult samples. To verify the performance of the SA-YOLO method, extensive simulation experiments are conducted on the sample imbalance dataset and the COCO dataset respectively. The results show that compared with the optimal metrics of YOLO series method, SA-YOLO reaches 91.46% of mAP in the imbalance dataset, which improves 10.87%, and the enhancement of AP50 for all kinds of objects is more than 2%, with excellent specialization; mAP50 in the COCO dataset is upgraded by 1.58%, and all indexes are not lower than the optimal value, with good effectiveness.
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    Spatiotemporal variation in the maximum leaf area index of temperate grassland in northern China and its response to climate change
    FENG Yiming, ZHANG Na, YUE Rongwu, YAN Zhihui, LI Zhenyu, LI Xiaofan, Erridunqimuge
    Journal of University of Chinese Academy of Sciences    2024, 41 (2): 195-211.   DOI: 10.7523/j.ucas.2022.072
    Abstract436)      PDF(pc) (15706KB)(430)       Save
    There might be great differences in spatiotemporal variation in leaf area index (LAI) of different grassland types; the responses of LAI with different annual variations to climate change are probably distinct. To explore these differences, from the long-term LAI data and meteorological data and the grassland type data, we obtained the temporal and spatial varying characteristics of the maximum LAI of different types of temperate grassland in northern China from 1981 to 2017, and explored the responses of LAI with different annual variations to the changes of air temperature and precipitation. The results showed that the average annual maximum LAI of temperate grassland was (0.76±1.07) m2/m2, the higher in the east and the lower in the west. The meadow steppe had the highest LAI ((2.73±1.20) m2/m2) and the steppe desert had the lowest LAI ((0.13±0.17) m2/m2). From 1981 to 2017, the average annual maximum LAI showed a significantly increasing trend. The maximum LAI increased significantly for 32.52% of the area and decreased significantly for 6.31% of the area. The areas with a significantly increasing LAI were greater than those with a significantly decreasing LAI for all the grassland types. The annual average maximum LAI was positively correlated with the annual total precipitation from January to August and the annual mean air temperature for July and August. Both the significant decrease and increase of the maximum LAI was mainly affected by the significant increase of annual mean air temperature for July and August. There existed a critical threshold of the rising rate of air temperature for July and August that influenced the variation in LAI; for the grassland types that accounted for the larger areas, this threshold was 0.042-0.043 ℃/a. LAI increased with the rising air temperature as the rising rate of air temperature was lower than this threshold; conversely, LAI decreased. These results are expected to provide important scientific basis for grassland utilization, protection and restoration in the context of climate change.
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    Calculating the thermal stress of the moon in cooling process with 3-D viscoelastic model
    JIN Yimin, TAO Sha, SHI Yaolin
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 1-10.   DOI: 10.7523/j.ucas.2022.059
    Abstract435)      PDF(pc) (8323KB)(437)       Save
    Thermal stress of the moon due to cooling process is non-negligible in lunar evolution. We calculate the accumulation of thermal stress with 3-D viscoelastic model, and explore the influence of viscosity parameters on thermal stress through comparative experiments. Numerical results suggest that the thermal stress of lithosphere is utterly distinct from deep mantle. The lithosphere is under tangential compression that concentrates at the bottom of the crust because of unevenly distributed cooling rate and elastic strength; on the other hand, the accumulation and relaxation of thermal stress in deep mantle is balanced due to low viscosity, and the thermal stress is in a “hydrostatic” state, which is mainly controlled by the elastic surface. Under the assumption that viscosity of lunar lithosphere is greater than 1028 Pa·s, the tangential compressive stress in lithosphere accumulates to several hundreds of MPa in the present day, while the tensile stress in deep mantle reaches up to 100 MPa. Consequently, part of the shallow moonquake events can be explained by thermal stress. However, the focal mechanism of deep moonquakes is still unclear. We speculate that the tensile thermal stress in deep mantle helps to develop pore structures, and the melting layer provides pore fluid with high pressure, which reduces the fracture strength of mantle medium.
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    Relationships between ΛφBV and BV(q,δ)
    GE Ajun, WANG Heping, YAN Dunyan
    Journal of University of Chinese Academy of Sciences    2023, 40 (6): 721-725.   DOI: 10.7523/j.ucas.2022.035
    Abstract427)      PDF(pc) (819KB)(364)       Save
    In this note, we obtain the sufficient and necessary conditions for the inclusions ΛφBVBV(q,δ), and BV(q,δ)⊂ΛφBV is false when φ satisfies the Δ2 condition.
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    Multi-scale featured convolution neural network-based soybean phenotypic prediction
    LIN Yutong, WANG Hong, CHAI Tuanyao
    Journal of University of Chinese Academy of Sciences    2024, 41 (4): 468-476.   DOI: 10.7523/j.ucas.2023.046
    Abstract406)      PDF(pc) (5008KB)(437)       Save
    In breeding, single nucleotide polymorphisms (SNPs) in the genome are often used to predict quantitative phenotypes to assist breeding, thereby improving breeding efficiency. The traditional statistical analysis method is limited by many factors including missing data, and its performance sometimes can not meet the requirements. In this paper, we proposed a multi-scale feature convolutional neural network model (MSF-CNN) to predict plant traits. The model extracted SNP features at three different scales through convolution and analyzed the significance of SNP sites through the weight of the SNPs input into the model. The test results showed that MSF-CNN model performed with higher accuracy than the known methods and other deep learning models in phenotype prediction on the datasets with missing genotypic data. This paper also studied the contribution of genotype to traits through saliency map, and discovered several significant SNP loci. These results showed that, compared with other known methods available at present, the deep learning model proposed in this paper can obtain more accurate prediction results of quantitative phenotypes, and can also effectively and efficiently identify SNPs associated with genome-wide association research.
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    Seamless image completion via GAN inversion
    YU Yongsheng, LUO Tiejian
    Journal of University of Chinese Academy of Sciences    2024, 41 (5): 705-714.   DOI: 10.7523/j.ucas.2022.075
    Abstract402)      PDF(pc) (10147KB)(403)       Save
    Image completion is widely used in unwanted object removal and media editing, which aims to find a semantically consistent way to recover corrupted images. This paper is based on generative adversarial network (GAN) inversion, which leverages a pre-trained GAN model as an effective prior to filling in the missing regions with photo-realistic textures. However, existing GAN inversion methods ignore that image completion is a generative task with hard constraints, making final images have noticeable color and semantic discontinuity issues. This paper designs a novel bi-directional perceptual generator and pre-modulation network to seamlessly fill in the images. The bi-directional perceptual generator uses extended latent space to help the model perceive the non-missing regions of the input images in terms of data representations. The pre-modulated networks utilize a multiscale structure further providing more discriminative semantics for the style vectors. In this paper, experiments are conducted on Places2 and CelebA-HQ datasets to verify that the proposed method builds a bridge between GAN inversion and image completion and outperforms current mainstream algorithms, especially in FID metrics up to 49.2% enhancement at most.
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    An image matching algorithm combining local and semi-global geometry preservation
    ZHENG Meiyan, CHEN Jun, GE Xiaoqing, ZHANG Hong
    Journal of University of Chinese Academy of Sciences    2024, 41 (1): 107-116.   DOI: 10.7523/j.ucas.2022.019
    Abstract399)      PDF(pc) (26254KB)(367)       Save
    Remote sensing image matching is an essential preprocessing step for many remote sensing applications. However, the distortions caused by elevation differences and the complexity of remote sensing image matching severely limit the matching precision of high-resolution remote sensing images. This paper proposes a robust feature matching algorithm suitable for local distortion and high outlier ratio. First, the Delaunay triangulation algorithm is used to impose geometric constraints on the initial matching point set, and the local adjacency relationship of the feature points is obtained. Second, pre-filter is conducted based on the adjacency information. Third, a multi-scale strategy is used to establish the local adjacency consistent model. Finally, a triangle similarity function is defined to achieve matching recovery. The experimental results on high-resolution images show that the average accuracy of our algorithm is 7.69% higher than that of RANSAC, and it is still robust when the outlier ratio is higher than 90%.
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