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2025, Vol. 42 No. 2

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15 March 2025

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    Krull dimension and primary decomposition of Rep(F[C2α])
    LU Xin, TANG Guoping
    2025, 42 (2): 145-152.  DOI: 10.7523/j.ucas.2023.057
    Abstract ( 247 ) PDF (0KB) ( 0 )
    Let F be a field with characteristic 2 and C2α be a cyclic group with order 2α. The ring, which has a Z-basis by finite dimensional indecomposable F[C2α] modules and multiplications by tensor product of F module, is called representation ring and denoted by Rep(F[C2α]). Based on Higman’s work, we further get the Krull dimension and the concrete forms of all prime ideals of Rep(F[C2α]). And then, we prove that Rep(F[C2α]) is a reduced ring and find the minimal primary decomposition of the zero ideal. At last, we prove that Spec(Rep(F[C2α])) is a connected topological space.
    A new cross-domain recommendation method with cluster effect
    ZHAI Haoran, ZHANG Sanguo
    2025, 42 (2): 153-158.  DOI: 10.7523/j.ucas.2023.040
    Abstract ( 186 ) PDF (0KB) ( 0 )
    In recent years, the recommender system has been widely used in online platforms, which can extract useful information from giant volumes of data and recommend suitable items to the user according to user preferences. In this article, we put forward a crossdomain recommendation method based on the rating data of the different projects from similar users, introducing project cluster effect in the target domain of the study, the use of this specific group of singular value decomposition with the method of extracting information associated with a project with similar characteristics. This method could effectively solve the problem of data sparsity. Due to the sparsity of the target domain, most items in the test set of the target domain have few scores, and their information is challenging to obtain from the training set. A strictly related problem is the one of collaborative filtering in recommender systems, where an algorithm tries to extrapolate missing information about the items from the rating activity of the users in order to provide a specific ad-hoc ranking for each user also on the items that have not been rated (on this see discuss how to aggregate the information from multilayer networks, while showing the importance of centrality measures for this issue). MovieLens data analysis indicated that, compared with the existing recommendation methods and cross-domain recommendation methods, the proposed new method of cross-domain recommendation with cluster effect has a significant improvement in the prediction accuracy.
    Thermoelectric effect on the flow and heat transfer of liquid metal in a conducting pipe under the magnetic field
    CHEN Zhaoqi, WANG Zenghui
    2025, 42 (2): 159-166.  DOI: 10.7523/j.ucas.2023.036
    Abstract ( 210 ) PDF (0KB) ( 0 )
    The seebeck effect produced by metal fluid under the influence of a stable magnetic field and temperature gradient can effectively enhance its heat transfer efficiency. The flow phenomena of liquid lithium and stainless steel in partially conducting pipes are simulated by using the consistent conservative numerical scheme developed for magnetohydrodynamics and the partitioned iterative algorithm for multi-domain coupled physical problems. The magnetic field direction is along the span of the pipe. The flow phenomena of liquid metal in the partially conductive tube under the action of the thermoelectric effect at Reynolds number (Re=745.6) are studied. It is found that the Lorentz force produced by the thermoelectric effect and magnetic field forms the reverse flow vortex structure at the four corners of the square tube. The reverse flow vortex increases the velocity in the central region and promotes the convective heat transfer of the liquid metal in the vortex structure at the four corners of the square tube. The reverse flow vortex increases the velocity in the central region and promotes the convective heat transfer of the liquid metal in the central region. With the increase of magnetic field intensity, the flow changes from unsteady flow to steady flow, the flow in the central region is dominated by the magnetic damping effect, the scale of the thermoelectric effect gradually shrinks to the vicinity of the boundary, and the relationship between velocity and temperature changes from two-way coupling under weak magnetic field to one-way coupling under strong magnetic field.
    Rice plant density inversion using polarimetric SAR considering planting methods
    XU Jingxuan, LI Kun, QIN Yi, ZHANG Bolin, ZHANG Fengli
    2025, 42 (2): 167-175.  DOI: 10.7523/j.ucas.2023.032
    Abstract ( 313 ) PDF (0KB) ( 0 )
    Plant density is an important factor affecting rice growth and yield. Because planting methods affect the distribution characteristics of rice in the field, and then cause the difference in density, it is necessary to consider the influence of planting methods in the inversion of rice plant density. Synthetic aperture radar (SAR) has been proved to be one of the important means of rice monitoring due to its advantages of all-day, all-weather and penetrability. Polarimetric SAR not only has the advantages of traditional SAR, but also is very sensitive to target structure and distribution characteristics. It has greater application potential in rice plant density inversion. Based on RADARSAT-2 full polarimetric SAR data, this study fully excavates the polarimetric information, considers the planting methods of transplanting and sowing, and uses the elastic network model to realize the inversion of rice plant density. The results show that polarimetric SAR has a good effect on the inversion of rice plant density. The RMSE of plant density in transplanting and sowing fields is 25 and 39 plants/m2 respectively. Compared with the inversion results without considering planting methods, the accuracy is improved by more than 30%.
    Characterization of lake area and number change in western Mongolia from 1992 to 2021
    YANG Song, ZHOU Hongfei, YAN Yingjie
    2025, 42 (2): 176-185.  DOI: 10.7523/j.ucas.2023.083
    Abstract ( 221 ) PDF (0KB) ( 0 )
    Climate change and human activities have impacted greatly on many lakes in western Mongolia, whereas they were seldom studied. Using Landsat images as the data source, lakes with an area larger than 1 km2 from 1992 to 2021 were extracted based on Google Earth Engine (GEE). Spatio-temporal changes of lake area were characterized, and causes were analyzed combining meteorological data and socioeconomic data. The results showed that: 1) The change of lake area could be divided into two phases, i.e., the expansion phase from 1992 to 1996 and the shrinking phase after 1996; 2) There are obvious spatial variations in lake area change. In Khovd Province and Gobi-Altai Provinces lake area shows a trend of decreasing first and then increasing, whereas the trend is opposite in Uvs Province and Zavkhan Provinces; 3) The causes are obvious different temporally and spatially. The increase of summer mean temperature and potential evapotranspiration had a negative impact on the decrease of lake area in Khovd Province and Gobi-Altai Provinces during 1992-2001. However, human activities, including agricultural irrigation and overgrazing, were the dominant negative drivers for the shrinkage of lakes in Uvs Province and Zavkhan Provinces from 1996 to 2019.
    Medical accessibility of affordable housing and commercial housing in Xiamen from the perspective of equity
    LIU Wenhui, ZHANG Guoqin, WANG Yang
    2025, 42 (2): 186-198.  DOI: 10.7523/j.ucas.2023.059
    Abstract ( 197 ) PDF (0KB) ( 0 )
    The rational planning and equitable allocation of medical facilities are closely related to public health and social justice. This paper takes Xiamen as an example and combines real-time traffic data from Baidu Maps to measure the medical accessibility of affordable housing and commercial housing by driving and public transportation, and explores the spatial equity of medical services for different housing groups by analyzing the differences in accessibility between the two types of housing and their characteristics under different zoning and transportation modes in the city. The results indicate that: 1) Compared with commercial housing, affordable housing is more disadvantaged in terms of site selection and the construction of supporting medical facilities in the surrounding area; 2) Regardless of the travel mode and regional scale, the accessibility of affordable housing is lower than that of commercial housing, and the spatial inequity between the two is more obvious in the peripheral urban areas and when using public transportation; 3) Even in the core urban areas where medical facilities are adequate, the accessibility of housing is better, and the spatial equity of medical care is better by car, the spatial inequity of medical services exists when using public transportation. The results of the study reflect the uneven and biased spatial allocation of medical facilities among different housing types in Xiamen, and also show the lower spatial equity of medical services faced by people living in affordable housing in the peripheral urban areas and are more dependent on public transportation. The relevant government departments should focus on strengthening the construction of medical facilities around affordable housing in the peripheral urban areas, and pay attention to the construction of the public transportation system around affordable housing. In addition, when planning new affordable housing in the future, the fairness of site selection should be emphasized, and the planning of public service facilities should be done at the same time to put the concept of social equity into practice in planning.
    Medium-term prediction of earthquakes in Southern California using LSTM neural network
    WANG Yixuan, ZHANG Huai, SHI Yaolin, CHENG Shu
    2025, 42 (2): 199-208.  DOI: 10.7523/j.ucas.2023.068
    Abstract ( 308 ) PDF (0KB) ( 0 )
    This paper explores earthquake prediction using neural networks, focusing mainly on using long-short-time memory (LSTM) neural networks to construct an earthquake prediction model. Based on the Southern California earthquake catalog data from 1932 to 2021, the earthquake catalog from January 1932 to March 2002 was used as the training set(80% of the entire earthquake catalog), and the earthquake catalog from March 2002 to September 2021 was used as the test set (the remaining 20%). The LSTM neural network was selected, and 11 earthquake prediction factors reflecting the spatiotemporal intensity distribution characteristics of the earthquake time series data were calculated from the training set. The maximum magnitude label corresponding to these factors was used to construct the model. The test set was then used for retrospective prediction testing. The model’s prediction performance was evaluated using metrics such as accuracy, precision, and R-value, which were calculated based on the values in the confusion matrix. The results show that the prediction has achieved certain results, predicting the M7.2 earthquake in April 2010. The R-value of some models is significantly higher than China’s current medium-term prediction level. However, the value of the evaluation model is still not ideal, and further exploration is needed.
    Classification of S- and I-type detrital zircon by machine learning and its application to supercontinental evolution
    SUN Zhihan, ZHANG Yigang
    2025, 42 (2): 209-220.  DOI: 10.7523/j.ucas.2023.065
    Abstract ( 209 ) PDF (0KB) ( 0 )
    Supercontinent evolution and distribution of detrital zircon with time is a long-term hot research topic. By using the stacking framework involving eight different machine learning methods and the area under curve (AUC) and accuracy proxy, a model is established to classify S- and I-type zircons. Applying the model to global detrital zircon dataset gives the distribution of S- and I-type zircon with time. After comparing the distribution with paleomagnetism and geological records, it is found that the S-type zircon distribution peak corresponds to the end of a supercontinent breakup and the start of assembly of the next supercontinent, and that the S-type zircon distribution valley (also the small peak of I-type zircon) is related to the maximum packing of a supercontinent and the start of its breakup. Based on the correlation of S-type zircon peak with global zircon big peak and the valley of S-type zircon with the global zircon small peak, it is proposed that big peaks of global zircon distribution with time represent a dispersive state of continents, during which magmatic activity is high producing both I- and S-type granites with also a high velocity of continent movement. By comparison, the small peaks in global zircon distribution represent a packing state of continents during which the supercontinent is stable with low magmatic activity producing mainly I-type granites and with a low velocity of continent movement. Finally, a high-accuracy decision function is provided to judge S- and I-type zircons and can be applied in related studies.
    “Caochi” in Dunhuang and Turpan document
    CHEN Tao, AILIJIANG Aisha, JIANG Hong'en
    2025, 42 (2): 221-226.  DOI: 10.7523/j.ucas.2023.023
    Abstract ( 237 ) PDF (0KB) ( 0 )
    Based on the historical literature, unearthed documents, and plant morphology, this paper made a detailed study on the word “Caochi” from the aspects of function, origin, and plant trait. The result showed that “Caochi” was Nigella glandulifera and it was used as medicine and condiment by the inhabitant in Dunhuang and Turpan during the period of Tang and Five Dynasties.
    A fast recursive calculation method of projection coefficients without starting point constraint
    WANG Ping, ZHOU Mei, CHEN Jiuying, ZHOU Chuncheng
    2025, 42 (2): 227-235.  DOI: 10.7523/j.ucas.2023.018
    Abstract ( 210 ) PDF (0KB) ( 0 )
    The two-dimensional gas concentration distribution obtained based on mobile laser gas telemetry technology is mainly achieved through an image reconstruction algorithm. Fast calculation of the projection coefficient is the key for such algorithm. However, the telemetry starting point based on mobile laser gas telemetry technology is randomly distributed in the grid or on the grid line of the reconstruction area, and the existing fast recursive calculation methods of projection coefficient are not applicable. This paper proposes a fast recursive calculation method of projection coefficient without starting point constraint. Three optical path accumulation factors are designed, which unify the recursive process of telemetry starting point in the grid and on the grid line without increasing the amount of calculation and realize the fast calculation of projection coefficient without starting point constraint. Algebraic reconstruction technology is used for reconstruction experiments, which verifies the effectiveness of this method. The minimum relative root mean square error is about 0.113%, and the maximum calculation speed is about 13.9 times that of the classical Siddon algorithm. The recursive calculation method proposed in this paper has a wider range of applications. It is the first time to realize the recursive calculation of projection coefficients without starting point constraints.
    Cross-modal retrieval method based on MFF-SFE for remote sensing image-text
    ZHONG Jinyan, CHEN Jun, LI Yu, WU Yewei, GE Xiaoqing
    2025, 42 (2): 236-247.  DOI: 10.7523/j.ucas.2024.025
    Abstract ( 301 ) PDF (0KB) ( 0 )
    Remote sensing image-text cross-modal retrieval technology can quickly obtain valuable information from massive remote sensing data. However, existing remote sensing image-text retrieval methods have limitations in utilizing multi-scale information within remote sensing images, and the weak recognition of target information leads to relatively low retrieval accuracy. To address these issues, this paper proposes a new method for remote sensing image-text cross-modal retrieval. This method mainly comprises a multi-scale feature fusion module and a salient feature enhancement module, which are designed to integrate multi-scale information of remote sensing images and enhance the expression of target information in remote sensing images, so as to improve the precision of remote sensing image-text cross-modal retrieval. Experimental validation was conducted on two publicly available remote sensing image-text datasets. The results demonstrate that the proposed method outperforms other methods across most evaluation metrics in the remote sensing image-text cross-modal retrieval task and exhibits the best overall retrieval performance.
    Flow aggregation with constrained resource for in-network computation
    SHENG Jiahua, HONG Peilin, WANG Hang
    2025, 42 (2): 248-259.  DOI: 10.7523/j.ucas.2023.044
    Abstract ( 107 ) PDF (0KB) ( 0 )
    In-network computation can greatly reduce the traffic generated during many-to-one transmission by establishing aggregation trees to merge data streams at the aggregation nodes. In this paper, we consider finding the minimum-cost aggregation tree under the constraints of a given amount of resources and the capacity of switch nodes. Since this problem is an NP-hard problem, a linear integer programming model and a heuristic algorithm called greedy cost aggregation tree (GCAT) are given to solve it. Simulation results show that the GCAT algorithm can generate a tree with less cost and utilize the resource more efficiently than other heuristics, and the performance is close to the optimal solution for small-scale networks.
    Industrial MCU oriented transcendental function unit design
    SONG Minte, LIU Nan, RU Zhanqiang, YIN Zhizhen, DING Peng, WANG Zhengguang, CHENG Suzhen, SONG Helun
    2025, 42 (2): 260-267.  DOI: 10.7523/j.ucas.2023.009
    Abstract ( 224 ) PDF (0KB) ( 0 )
    The calculation of transcendental functions is one of the necessary steps in industrial control algorithms. As the complexity of industrial control systems increases, calculating the transcendental function by software approximation algorithm takes up a large number of CPU cycles, compressing the computational resources of real-time control algorithms and reducing the accuracy of closed-loop control. Equipped with hardware accelerating units, industrial microcontroller unit architecture becomes the preferred solution to solve this contradiction. In this paper, a multi-threaded, high-performance, configurable transcendental function unit based on digital iterative algorithms was designed, which supports trigonometric function, exponential, and logarithmic calculations. The design was synthesized by standard cell library of SMIC 40 nm eFlash platform, resulting in a clock frequency of 200 MHz and an area of 301 074 μm2.
    Solutions of cross-entropy loss with spectral decoupling regularization
    HU Yinhan, GUO Tiande, HAN Congying
    2025, 42 (2): 268-275.  DOI: 10.7523/j.ucas.2023.071
    Abstract ( 188 ) PDF (0KB) ( 0 )
    In this paper, we study the effect of spectral decoupling with different strengths on over-parameterized models. In the absence of weight decay, we show that the models obtained by spectral decoupling of different strengths are equivalent. When there is a small weight decay, we use the second-order Taylor expansion of the objective function to obtain an approximate solution. Analyzing the approximate solution, we find that reducing the spectral decoupling has the effect of enhancing the weight decay, which is directly equivalent in the binary classification problem. Finally, we verify our analytical conclusions through experiments.
    Brief Report
    Impact and mechanism of relocation of urban administrative center on spatial expansion: taking Qingdao as an example
    XU Shaojie, WANG Kaiyong, WANG Fuyuan
    2025, 42 (2): 276-288.  DOI: 10.7523/j.ucas.2023.075
    Abstract ( 378 ) PDF (0KB) ( 0 )
    The administrative center is a core element in the framework of administrative division research. The location, adjustment, and change of a city’s administrative center can significantly impact the spatial form and structure of the city. This paper takes Qingdao City as a case study and utilizes the CLCD dataset, along with GIS spatial analysis methods, to quantitatively measure the spatial and temporal patterns of urban construction land expansion after the relocation of the administrative center. It analyzes the differences in urban built-up area spatial expansion before and after the relocation and explores the mechanisms of how the relocation of the administrative center influences urban spatial expansion. The results show that:1) After relocating the administrative center, Qingdao’s construction land area exhibits higher average values for the number, rate, and intensity of expansion compared to before relocation, indicating that the relocation of the administrative center accelerates urban construction land expansion in Qingdao; 2) The relocation of the administrative center has led to an agglomeration trend in Qingdao’s urban spatial expansion, with a shift towards polycentric agglomeration, and the primary hotspot of spatial expansion lies along the Jiaozhou Bay Ring; 3) Land finance is the direct cause of urban spatial expansion following the relocation of Qingdao’s administrative center. The strengthening of land finance enhances the spatial governance capacity of the government, further promoting the reconfiguration of production factors, urban planning, and urban functions in Qingdao. As a result, this process indirectly influences the city’s spatial expansion. The findings of this study emphasize the significance of incorporating the spatial impact of administrative center relocation into urban planning and development strategies. These findings can serve as a reference for the strategic relocation of urban administrative centers and the planning of future urban development directions.
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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
    Abstract1633)      PDF(pc) (727KB)(17401)       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
    Abstract653)      PDF(pc) (9359KB)(15195)       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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    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
    Abstract2480)      PDF(pc) (154KB)(6782)       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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    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
    Abstract3359)      PDF(pc) (1045KB)(6755)       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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    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
    Abstract2919)      PDF(pc) (832KB)(5775)       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
    Abstract2387)      PDF(pc) (1120KB)(5629)       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
    Abstract3582)      PDF(pc) (268KB)(4896)       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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    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
    Abstract984)      PDF(pc) (1257KB)(4774)       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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    Glycobiology-Essential for Discovery of Gene's Function
    Jin Cheng
       2001, 18 (1): 66-75.   DOI: 10.7523/j.issn.2095-6134.2001.1.011
    Abstract1086)      PDF(pc) (427KB)(4650)       Save

    This paper overviews the significance, advances and future direction in the glycobiology field. Special emphasis is given to cell cell adhesion which is mediated by the interaction between carbohydrates and carbohydrates binding proteins (CBP). The roles of carbohydrates in the folding of nascent polypeptides, immune system, and cellular signal transductions are also reviewed. The scope also covers carbohydrates in infections, carbohydrates in diseases,and chemical synthesis/structural analysis of carbohydrates. Finally,the features and future directions of glycobiological research are pointed out by the author.

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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
    Abstract2919)      PDF(pc) (820KB)(4636)       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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    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
    Abstract2592)      PDF(pc) (1138KB)(4278)       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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    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
    Abstract1715)      PDF(pc) (173KB)(4271)       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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    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
    Abstract3930)      PDF(pc) (1395KB)(4050)       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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    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
    Abstract2608)      PDF(pc) (929KB)(3977)       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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    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
    Abstract2727)      PDF(pc) (1540KB)(3939)       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
    Abstract1143)      PDF(pc) (1223KB)(3901)       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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    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
    Abstract1330)      PDF(pc) (2927KB)(3806)       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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    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
    Abstract1967)      PDF(pc) (832KB)(3700)       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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    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
    Abstract2189)      PDF(pc) (816KB)(3676)       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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    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
    Abstract2778)      PDF(pc) (833KB)(3517)       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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    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
    Abstract823)      PDF(pc) (10322KB)(1117)       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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    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
    Abstract752)      PDF(pc) (6043KB)(1330)       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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    An adaptive variance reduction method with negative momentum
    LIU Hai, GUO Tiande, HAN Congying
    Journal of University of Chinese Academy of Sciences    2024, 41 (5): 577-588.   DOI: 10.7523/j.ucas.2024.024
    Abstract694)      PDF(pc) (3480KB)(952)       Save
    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.
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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
    Abstract674)      PDF(pc) (5608KB)(1134)       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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    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
    Abstract663)      PDF(pc) (10147KB)(1068)       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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    Temporal and spatial variation of summer soil moisture and its driving factors in Yellow River basin during the last 20 years
    ZHANG Ya'nan, SONG Xiaoning, LENG Pei, GAO Liang, YIN Dewei
    Journal of University of Chinese Academy of Sciences    2024, 41 (4): 477-489.   DOI: 10.7523/j.ucas.2023.041
    Abstract633)      PDF(pc) (12970KB)(575)       Save
    Based on the moderate resolution imaging spectroradiometer products and global land data assimilation system meteorological data from 2001 to 2020, soil moisture in summer in the Yellow River basin was retrieved based on the vegetation index/land surface temperature trapezoid feature spatial model. The spatial-temporal pattern and driving factors of soil moisture in the Yellow River basin were analyzed using the Sen slope method, Mann-Kendall method, and geographical detector. The results showed that soil moisture in the Yellow River basin had apparent spatial heterogeneity. The source and lower reaches of the Yellow River are humid, while the middle reaches are relatively dry. From 2001 to 2020, soil moisture in the Yellow River basin showed an insignificant increase and an insignificant decrease in space, accounting for 39.54% and 58.01% of the regional area, respectively. The growth rate of soil moisture in the upper reaches was the fastest. Precipitation is the dominant factor of temporal variation of soil moisture in the Yellow River basin. Temperature and elevation are the main factors affecting the spatial variation of soil moisture in the upper reaches, and normalized difference vegetation index and precipitation are the main driving factors influencing soil moisture change in the middle reaches of the Yellow River.
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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
    Abstract626)      PDF(pc) (12585KB)(587)       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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    Remote sensing inversion of CO2 emissions from super-large coal-fired power plants in China based on OCO-2/3 satellite
    GUO Wenyue, SHI Yusheng
    Journal of University of Chinese Academy of Sciences    2024, 41 (4): 490-502.   DOI: 10.7523/j.ucas.2023.050
    Abstract625)      PDF(pc) (21553KB)(1086)       Save
    Coal-fired power plants are important contributors to CO2 emissions in China. Due to the low timeliness of statistical data and inaccurate emission factors, the existing emission inventories gradually fail to reflect the CO2 emissions of power plants. This study provides a method to estimate CO2 emissions from power plants based on Orbiting Carbon Observatory 2/3 (OCO-2/3) satellite data and Gaussian plume model, retrieving the images of super-large coal-fired power plants (≥5 000 MW) in China from the OCO-2 (September 6,2014-October 1, 2021) and OCO-3 (August 6, 2019-October 1, 2021) dataset, and identifying a total of seven plumes near Tuoketuo, Waigaoqiao, and Jiaxing power plants. Using a combination of three atmospheric background value determination methods, the CO2 emissions estimated by the Gaussian plume model range from 43 to 77 kt/d, with correlation coefficients ranging from 0.50 to 0.87. The uncertainties of individual plumes varied from 8% to 32% (1σ), with wind speed being the largest uncertainty (6%-31%), followed by background values (5%-18%), enhanced values (1%-21%), and plume rise (1%-8%). The estimates are verified to be in high agreement with Carbon Monitoring for Action, Carbon Brief, and the Global Power Emissions Database (Tuoketuo: (76.48±15.75), Waigaoqiao: (55.98±6.90), Jiaxing: (64.55±15.89) kt/d). This study helps monitor and estimate important point source carbon emissions, which is not only a prerequisite for the power industry to carry out carbon reduction efforts but also helps develop specific regional carbon reduction policies, thereby reducing anthropogenic carbon emissions.
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    Building extraction method based on MFF-Deeplabv3+ network for high-resolution remote sensing images
    CHEN Jingwei, LI Yu, CHEN Jun, ZHANG Hongqun
    Journal of University of Chinese Academy of Sciences    2024, 41 (5): 654-664.   DOI: 10.7523/j.ucas.2023.010
    Abstract591)      PDF(pc) (20364KB)(627)       Save
    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.
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    Comparison study on classification accuracy of 11 common water indices based on Landsat 8 OLI images
    LI Longjie, YANG Yonghui
    Journal of University of Chinese Academy of Sciences    2024, 41 (6): 755-765.   DOI: 10.7523/j.ucas.2023.088
    Abstract585)      PDF(pc) (13417KB)(572)       Save
    Water index is one of the most effective methods to extract water bodies from remote sensing images. There are many kinds of water index, each with its own characteristics. It is, therefore, necessary to select the index with best classification accuracy. Taking Shijiazhuang City as the research area, 11 common water indices were used to extract water bodies from Landsat 8 OLI images. The accuracy of the water index extraction results is validated by using the visual interpretation (VI) result as the standard classification map from Sentinel-2 MSI based on the area test method in combination with transition matrix and sampling test method. Results show little difference in the extraction of large water bodies among different water indices. Small ponds and rivers can better check the extraction ability of water index. It is proved that Water Index 2019 (WI2019) has the best water classification. WI2019 is then used to find out the recent expansion of water bodies after the start of South-to-North Water Diversion Project for water transfer. It was found that the area of surface water body in Shijiazhuang excluding large reservoirs increased significantly, from 42 km2 in 2014 to 62 km2 in 2020, an increase of 20 km2. In view of the canal seepage control treatment at the bottom of most newly added water bodies, with poor groundwater recharge function, and more ineffective evaporation, it is recommended to properly control the scale of water bodies in order to effectively reduce the waste of water transferred from outside.
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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
    Abstract578)      PDF(pc) (5008KB)(1064)       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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    Remote sensing extraction method of agricultural greenhouse based on an improved U-Net model
    WANG Yinda, PENG Ling, CHEN Deyue, LI Weichao
    Journal of University of Chinese Academy of Sciences    2024, 41 (3): 375-386.   DOI: 10.7523/j.ucas.2023.060
    Abstract532)      PDF(pc) (27690KB)(895)       Save
    The agricultural greenhouse is a kind of agricultural facility, which is divided into transparent and non-transparent according to the surface transmittance. The large-scale statistics of agricultural greenhouses are of great significance to the survey of agricultural facilities, the formulation of agricultural policies, and the planning of county economic development. Aiming at the problem that manual statistics are time-consuming and laborious, this paper utilizes the convolutional neural network to extract agricultural greenhouses information from high-resolution remote sensing images. To solve the problems of insufficient semantic information extraction in remote sensing images and insufficient utilization of edge information of the U-Net model, this paper proposes the following improvements: 1) The semantic segmentation task is optimized, and ConvNeXt and attention mechanism is utilized to extract deep semantic information of agricultural greenhouses in remote sensing images. 2) The edge detection task is introduced, and the gated convolution layer and concate operation are used to fuse the semantic features of the encoder and the image gradient output by the decoder, and then the edge information is combined to optimize the segmentation results. After testing, the improved model can extract both transparent and non-transparent agricultural greenhouses information at the same time and the recognition effect is good, which is greatly improved compared with the traditional method.
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    Lightweight network for fast ship detection in SAR images
    ZHOU Wenxue, ZHANG Huachun
    Journal of University of Chinese Academy of Sciences    2024, 41 (6): 776-785.   DOI: 10.7523/j.ucas.2023.017
    Abstract532)      PDF(pc) (34205KB)(663)       Save
    In the field of SAR image ship detection based on deep learning, traditional models are usually complex in structure and require a large amount of calculation, making them unsuitable for low computing power platforms and real-time detection. And convolutional neural networks that rely on preset anchor boxes will lead to a lot of computational redundancy due to the difficulty of setting a reasonable anchor box. To solve these problems, an end-to-end lightweight convolutional neural network based on anchor-free design is proposed, and a lightweight channel attention module (EESE) is designed and applied to the detection head (ED-head), to resolve the conflict between classification and localization tasks. In addition, an optimized EIOU loss function is proposed, which enables the model to effectively improve the network performance without increasing the inference time. The proposed method is tested on the SSDD dataset, and the experimental results show that compared to YOLOX-nano, AP50 and AP are increased by 2.1 and 7.4 percentage points, respectively, with the CPU latency being only 5.33 ms, much less than 13.13 ms of YOLOX-nano. The proposed method achieves a balance between accuracy and efficiency.
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    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
    Journal of University of Chinese Academy of Sciences    2024, 41 (5): 612-624.   DOI: 10.7523/j.ucas.2022.080
    Abstract516)      PDF(pc) (11064KB)(595)       Save
    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.
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    Super-resolution reconstruction of high-resolution remote sensing images for real scenes
    ZHAO Jiayi, MA Yong, CHEN Fu, YAO Wutao, SHANG Erping, ZHANG Shuyang, LONG An
    Journal of University of Chinese Academy of Sciences    DOI: 10.7523/j.ucas.2024.054
    Accepted: 11 June 2024

    Remote sensing semantic segmentation method based on high-resolution relational graph convolutional network
    WANG Yinda, CHEN Jiahui, PENG Ling, LI Zhaobo, YANG Lina
    Journal of University of Chinese Academy of Sciences    2025, 42 (1): 107-115.   DOI: 10.7523/j.ucas.2023.079
    Abstract459)      PDF(pc) (7470KB)(574)       Save
    Semantic segmentation of remote sensing images is an important task in remote sensing image processing and analysis, especially in multi-category semantic segmentation. Current methods mainly revolve around convolutional neural networks, but convolution only focuses on the local information of the image while ignoring the global information. Therefore, inspired by high resolution network (HRNet) and relational graph convolutional network (R-GCN), this paper proposes a high-resolution relational graph convolutional network (HRGCN) for multi-category semantic segmentation. Firstly, simple linear iterative clustering (SLIC) is done on the original image, and the result is used to segment the feature map output from HRNet to obtain superpixel blocks with high homogeneity and containing multi-resolution information; then graph nodes and edges are constructed based on the superpixel blocks, and R-GCN is used to classify the graph nodes, so as to learn the long-distance dependency between different features and complete the extraction and classification of remote sensing images. The HRGCN model designed in this paper is experimented on Potsdam and Vaihingen datasets, and the results are compared with the existing methods, and the $\bar{F}_1$ values and MIoU values are improved to certain degrees, which proves that the method has good advancement.
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    Detection method and characterization of ramp events of wind speed and wind power based on swinging door algorithm
    LIANG Zhi, ZHANG Zhe, SHI Yu, LIU Lei
    Journal of University of Chinese Academy of Sciences    2024, 41 (6): 821-829.   DOI: 10.7523/j.ucas.2023.014
    Abstract457)      PDF(pc) (13853KB)(2163)       Save
    The ramp event of wind speed is a large increase or decrease in wind speed within a short period, causing a significant change in wind farm power, affecting the safe operation of the grid and even triggering accidents such as frequency reduction and voltage collapse. This paper selects the simultaneous data of wind turbines and meteorological towers in wind farms, identifies the ramp events by the swinging door algorithm (SDA), analyzes the duration, magnitude and change rate of the ramp events, and discusses the influence of mountainous terrain on them. In this paper, the recognition algorithm of the ramp event of wind speed and power is designed based on the SDA, and the algorithm parameters are set as follows: the time threshold 4 h, wind speed threshold 6 m·s-1, and power threshold 1 000 kW. For the recognition of ramp events in other wind turbines, this paper suggests using 2/3 value of the difference between rated wind speed and cut-in wind speed as the wind speed threshold parameter, and 2/3 value of rated power as the power threshold parameter. The terrain influence on the ramp event is significant, and the ramp event is more related to the altitude and average wind speed at the turbine, and the time proportion of the ramp event under different terrain ranges from 6.5% to 9.8%, with the average value of 7.8%.
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    Continuity of truncated Hardy-Littlewood maximal function
    WANG Yidong, WU Jia, YAN Dunyan
    Journal of University of Chinese Academy of Sciences    2024, 41 (6): 721-727.   DOI: 10.7523/j.ucas.2023.045
    Abstract455)      PDF(pc) (854KB)(268)       Save
    This paper focuses on the continuity of the truncated Hardy-Littlewood maximal function. We first show that the truncated Hardy-Littlewood maximal function is lower semi-continuous. Then by investigating the behavior of the truncated Hardy-Littlewood maximal function when the truncated parameter γ changes, we obtain an equivalent condition of the continuity of the truncated Hardy-Littlewood maximal function.
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    Numerical study of natural convection heat transfer from neck folds of the frill-neck lizard
    JIA Chongxi, WANG Hao, LIU Jie, LU Wenqiang
    Journal of University of Chinese Academy of Sciences    2024, 41 (6): 736-745.   DOI: 10.7523/j.ucas.2022.078
    Abstract439)      PDF(pc) (11787KB)(555)       Save
    In this paper, the physical modeling of frill-neck lizard, a reptile with special heat dissipation structure, was carried out, and the natural convection heat transfer properties of it were numerically studied. It was found that there was only one maximum heat transfer coefficient in the range of 45°-85°, which was obtained at around 65° for the simulation of different field angle adjustments of frill-neck lizard neck fold. At the same time, by changing the size of frill-neck lizard neck fold, it was also observed that there was a unique maximum convection heat transfer coefficient in the range of 6.3≤ L0/d ≤6.6. In addition, the field angle and area corresponding to the maximum heat transfer rate were close to the natural state of Australian subspecies. Therefore, it can be inferred that the evolution direction of frill-neck lizard neck fold may be beneficial to improving the natural convection heat transfer rate. Hence, the natural convection between frill-neck lizard and external environment may be considered as an important reason affecting the evolution direction of Chlamydosaurus kingii neck fold.
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    Impact of atmospheric stability on vertical wind shear and wind veer in atmospheric boundary layer
    LIANG Zhi, SHI Yu, ZHANG Zhe, HU Fei
    Journal of University of Chinese Academy of Sciences    2024, 41 (3): 365-374.   DOI: 10.7523/j.ucas.2022.063
    Abstract436)      PDF(pc) (10747KB)(896)       Save
    Vertical wind shear in the atmospheric boundary layer (ABL) is an important factor affecting safety in high-rise buildings, aviation and wind energy industry, therefore the detection and study of vertical wind shear is very important for application and research. In this paper, the accuracy of Lidar and meteorological mast (met mast) on the vertical wind shear was verified by field measurements, and the influence of atmospheric stability on vertical wind shear was studied. The results showed that: 1) the atmospheric stability had a significant effect on wind speed shear and wind direction veer, and the correlation coefficients of wind speed shear and wind direction veer with atmospheric stability are 0.48 and 0.54, respectively; 2) The wind speed shear increased with the potential temperature gradient, and remained 0.35-0.4 when the potential temperature gradient reaches 0.08 K·m-1; 3) Under the neutral atmospheric condition, the wind direction of the upper and lower layers was more consistent, and the wind direction deflected counterclockwise with the increase of height under stable atmospheric condition, and deflected clockwise with the increase of height under the unstable atmospheric condition. The conclusion in this paper modeled the relationship between wind shear and atmospheric stability by the vertical observation of wind field, which is a good reference and valuable for the research and application related to the vertical structure of wind field.
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