Journal of University of Chinese Academy of Sciences

FU Sheng, XUE Yuan, ZHANG Sanguo

2019, 36 (3): 289-298. DOI: 10.7523/j.issn.2095-6134.2019.03.001

Statistical classification problems are widely encountered in many applications, e.g., face recognition, fraud detection, and hand-written character recognition. In this article we make a comprehensive analysis on statistical methods for supervised classification problems. Specifically, we introduce the angle-based classification structure, which combines binary and multicategory problems in a unified framework. Several new variants of the angle-based classifiers are also discussed, such as robust learning and weighted learning. Furthermore, we show some theoretical results about Fisher consistency for these angle-based classifiers.

The geometry of conformal minimal surfaces in HP³

GAO Zijuan, JIAO Xiaoxiang

2019, 36 (3): 299-310. DOI: 10.7523/j.issn.2095-6134.2019.03.002

Abstract ( 272 ) PDF (KB) ( 0 )

In this work, we construct six examples of conformal minimal two-spheres surfaces with constant curvatures of 4/7, 4/19, and 4/27 by the twistor map π:CP⁷→HP³. By the twistor map, we know that the horizontal minimal surfaces in CP²ⁿ⁺¹ are equivalent to the minimal surfaces in HPⁿ, and many conclusions about conformal minimal two-spheres with constant curvatures in CPⁿ have been given. Based on Bolton's conclusion and Chen's general method to construct conformal minimal two-spheres, we get some conformal minimal two-sphere surfaces in HP³.

Exsitence of positive solutions for matrix-type partial differential equations with strongly singular nonlinearities

SHUANG Zhen, SUN Yijing

2019, 36 (3): 311-319. DOI: 10.7523/j.issn.2095-6134.2019.03.003

Abstract ( 319 ) PDF (KB) ( 0 )

We investigate the strongly singular partial differential equations of matrix-type,

where Ω is a bound and open set in Rⁿ, M(x) is a real symmetric matrix on Ω, -p<-1,0 < q < 1,λ>0 are parameters, f(x)∈L¹(Ω),f(x)>0 a.e. in Ω. We prove that the above-mentioned equation admits at least one positive H₀¹-solution when λ>0 if there exists u₀ ∈H₀¹(Ω) such that ∫_Ωf(x)|u₀|^1-pdx <+∞. It should be noted that a classical solution, namely, the C²(Ω)∩C(Ω)-solution, is not necessarily a H₀¹(Ω)-solution for singular equations.

Experimental study on multilayer liquid GaInSn film flow under horizontal magnetic field

QI Tianyu, YANG Juancheng, NI Mingjiu

2019, 36 (3): 320-325. DOI: 10.7523/j.issn.2095-6134.2019.03.004

Abstract ( 220 ) PDF (KB) ( 0 )

In this work, the flow characteristics of the liquid GaInSn film in the multilayer channel in the organic glass cavity under the spanwise magnetic field are studied. Three laser level instruments are used to simultaneously capture the liquid 2D contour changes at three positions, and measure the thickness of film. The experimental results show that the surface fluctuation of the liquid film increases obviously with Reynolds number in the organic glass channel. The magnetic field effectively inhibits the surface fluctuation along the magnetic lines, but has little influence on the surface fluctuation along the streamwise direction. The thickness of the film decreases with the increase of the magnetic field at small Reynolds numbers, the thickness decreases first and then increases at the medium Reynolds numbers, and the thickness of film increases monotonically when Reynolds numbers are large. The larger Reynolds number is, the more obvious the effect of magnetic field's obstruction of the flow is. The results illustrate that the multilayer film flow device effectively improves the spreading of film flow and makes the spreading easier.

Study of the stellar orbital eccentricity based on LAMOST survey

LIU Shuai, DU Cuihua

2019, 36 (3): 326-330. DOI: 10.7523/j.issn.2095-6134.2019.03.005

Abstract ( 234 ) PDF (KB) ( 0 )

Based on A/F/G/K giant stars from LAMOST data,we pick out halo sample stars according to the space and metallicity distribution to study the orbital eccentricity distribution of the halo stars in the Galaxy. We find that the observed halo stellar orbital eccentricity distribution has the peak of 0.8 and it does not change with the distance in the 5<|z|<15 kpc range. In addition, the inner-halo stars and outer-halo stars have different eccentricity distributions in the 5<|z|<25 kpc range. The peak eccentricity of inner-halo is about 0.65, and that of outer-halo is about 0.8. Compared to the inner-halo stars, the outer-halo stars are more concentrated in the area beyond e~0.6. Maybe this different kinematics represents different formation mechanisms of inner-halo and outer-halo.

Spatio-temporal analysis of differences among atmospheric CO₂ concentrations retrieved from different satellite observations

WU Changjiang, LEI Liping, ZENG Zhaocheng

2019, 36 (3): 331-337. DOI: 10.7523/j.issn.2095-6134.2019.03.006

Abstract ( 293 ) PDF (KB) ( 0 )

Quantitative analysis of the differences among the CO₂ concentrations retrieved from different satellites is important for understanding possibility of combining different satellites for observing the spatio-temporal variations in global atmospheric CO₂ concentration. In this study, we investigated the differences among the atmospheric CO₂ concentrations derived from SCIAMACHY, GOSAT, and OCO-2 by comparing with CO₂ simulations from CarbonTracker. Firstly, the sensitivities of the three satellites to CO₂ concentrations were quantified by adjusting the measurements based on the CO₂ profiles from CarbonTracker. Secondly, the spatio-temporal patterns of XCO₂ retrievals from the three satellites were further compared. The results show that SCIAMACHY shows averaged biases of (-0.25 ±0.15)×10^-6 and (-0.38 ±0.25)×10^-6 at high and low latitude regions, respectively, which are significantly larger than those showed by the other two satellites. Moreover, we found that, after removing these differences, the observations from the three satellites demonstrate similar seasonal and annual variations as well as similar spatial patterns. These results show that model simulations can be utilized to remove or reduce the differences among the XCO₂ retrievals from different satellites.

Characteristics and models of village-town development in Fujian coastal area: a case study of Dongshan County

CHEN Xiji, GUO Qinghai, XIAO Lishan, ZHU Ling, LI Mingfeng, YANG Dewei

2019, 36 (3): 338-346. DOI: 10.7523/j.issn.2095-6134.2019.03.007

Abstract ( 212 ) PDF (KB) ( 0 )

Economic opening and rapid urbanization have caused profound impacts on rural areas. Numerous studies have focused on industrial types and relationship between urban and rural areas in a macro scale. However, micro scale study at village level will identify the actual characteristics of villages and also the heterogeneity of development elements so as to generate village-town models and form reference resolutions. Based on the political background of rural revitalization strategy, we took 60 administrative villages of Dongshan County in Fujian Province as an empirical study case. Bright spot analysis was applied to detect bright spots based on annual per capita income of the 60 villages. Based on social-economic and geographical indexes, a multiple regression model was developed to quantitatively analyze the differences among the selected villages. The results indicate that different economic levels among the villages were related to geographical location, population, industrial development, and financial system. Coast accessibility, distance to the county center, migrant population, fishery production, and per capita fiscal expenditure were significantly correlated to the economic levels of the bright spots. Two types of development models were generated. One type is motivated by urbanization, which has a balanced development of diverse non-agricultural industries including construction, transportation, and commercial service. The other is dominated by characteristic industries which has developed marine fishery and related industrial schemes. Furthermore, urban-oriented village and new type of fishing village were identified. This research demonstrated the characteristics and deficiency of villages and towns in Dongshan County, and further discussed the diversified development models formed by multiple factors in Fujian Province. The results provide micro insights into village-town development models in coastal areas of China and lay scientific foundation and decision-support for rural areas to decide countermeasures and development models according to local advantages.

Effects of road network on landscape ecological risk: a case study of “China and Indochina Peninsula economic corridor”

BI Kaiyi, NIU Zheng, HUANG Ni, KOU Peiying

2019, 36 (3): 347-353. DOI: 10.7523/j.issn.2095-6134.2019.03.008

Abstract ( 318 ) PDF (KB) ( 0 )

Taking "China and Indochina Peninsula economic corridor" as a case, with the support of GIS technology, this study analyzed the spatial pattern of road network and its impacts on landscape ecological risk. The results are showed as follows. 1) The effects of road network on landscape pattern were related to the landscape types, among which the impervious surface was affected the most. 2) There were obvious spatial differences in landscape ecological risk throughout the whole study area, and the risks in China and Thailand were relatively higher than those in the other countries. 3) There was a certain correlation between road network and landscape ecological risk. As the density and level of road increased, landscape ecological risk presented an upward trend accordingly. The above results suggest that the corresponding road construction and planning strategies should be developed for different regions and landscape types.

Crowdsourcing assessment model combined with quality control for collapsed buildings after the earthquake

JIA Yingyu, LIU Shibin, DUAN Jianbo, XIE Shuai

2019, 36 (3): 354-362. DOI: 10.7523/j.issn.2095-6134.2019.03.009

Abstract ( 221 ) PDF (KB) ( 0 )

In the field of remote sensing disaster assessment, crowdsourcing assembles the intelligence of the network users to complete the disaster assessment tasks. However, there is a problem that the quality of the workers' answers is not reliable in the real crowdsourcing platform. In this study, a new model combined with quality control for crowdsourcing assessment of collapsed buildings after the earthquake is proposed. A case study of Yushu earthquake was presented and the experimental platform was set up to collect crowdsourcing disaster assessment data. First, the gold data and consistency test method were used to filter out low-quality crowdsourcing data. Then, the reliable disaster interpretation results were derived by the crowdsourcing assessment model. The experimental results show that the assessment accuracies of the collapsed buildings in the test area were 70.59% without the quality control and 85.29% with the quality control, which indicates that the proposed model effectively increases the accuracy of the crowdsourcing disaster interpretation. Therefore, crowdsourcing provides reliable visual interpretation results based on the proposed method, which is of importance for remote sensing disaster assessment.

The improvement in solar position calculations in the ellipsoid model of the earth

LI Wen, ZHAO Yongchao

2019, 36 (3): 363-375. DOI: 10.7523/j.issn.2095-6134.2019.03.010

Abstract ( 320 ) PDF (KB) ( 0 )

Accurate and efficient calculation of the solar position is of great value in the fields of remote sensing radiation calibration and solar energy acquisition. Firstly, in this work we use the numerical fitting method to improve the calculation of the solar declination aiming at solving the problem that the differences in data among different years has not been considered enough in the original algorithms. According to the periodicity represented by the error curves, an improved algorithm for solar declination calculation based on a period of four years is proposed by using the Fourier expansion method. Then the formula of the solar elevation angle under the earth ellipsoid model is derived. Finally, the improved formula of the atmosphere refraction at elevation angles of 0°-30° is proposed to solve the problem of excessive errors of the original algorithms at small elevation angles, because the atmosphere refraction affects the observation and calculation of the solar position. The results show that the algorithms given in this paper significantly reduce the errors in the calculations of the solar declination angle, the solar elevation angle, and the atmosphere refraction at small elevation amgles. The calculation process is simple and efficient, which accords with the requirements of the relevant project.

Effects of ionospheric dispersion on spaceborne SAR imaging

TIAN Dong, YU Weidong

2019, 36 (3): 376-384. DOI: 10.7523/j.issn.2095-6134.2019.03.011

Abstract ( 324 ) PDF (KB) ( 0 )

In the process of SAR signal propagation, the velocities of signal propagating at different frequencies are different due to the ionospheric dispersion effect. For the LFM signal with wide bandwidth, the dispersion effect results in the propagation delay of SAR signal, leading to additional advanced phase. In this study, the effects of ionospheric dispersion on SAR imaging under different carrier frequencies, different bandwidths, and different ionospheric TEC values are simulated and analyzed by using the time-domain simulation method. The results show that the ionospheric dispersion effect causes the SAR image to be shifted in distance with the sidelobe increase and pulse broadening. The P-band and L-band are obviously affected by the ionospheric dispersion effect. For C-band and X-band high resolution spaceborne SAR, the ionospheric dispersion effect leads to the degradation of imaging quality when the signal bandwidth carrier ratio is large.

A graph cut-based approach for individual tree detection using airborne LiDAR data

WANG Pu, XING Yanqiu, WANG Cheng, XI Xiaohuan

2019, 36 (3): 385-391. DOI: 10.7523/j.issn.2095-6134.2019.03.012

Abstract ( 376 ) PDF (KB) ( 0 )

The accuracy of individual tree segmentation using airborne LiDAR (light detection and ranging) data is generally low for dense forests. A new method, which considers the vertical stratification of forest canopy,is proposed in this study to detect individual tree with high accuracy using airborne LiDAR data. First, several data preprocessing steps are conducted, including noise removal, point cloud filtering, and elevation normalization. Secondly, the initial canopy segmentation is achieved by the normalized cut (Ncut) segmentation with a prior knowledge of individual tree position derived from the local maximum of the canopy height model (CHM). Finally, the Ncut method is used to reduce the leakage rate of individual tree detection by setting the global maximum of CHM as the individual tree position and considering the shape and the minimum point number of the canopy. The results show that the proposed method effectively improves the accuracy of tree detection,which contributes to the quantitative description and parameter inversion in individual tree scale.

Radiometric characteristics of the intensity data of laser scanner

DU Song, LI Xiaohui, LIU Zhaoyan, CHEN Yuwei, WANG Zhen, TANG Lingli, HE Wenjing

2019, 36 (3): 392-400. DOI: 10.7523/j.issn.2095-6134.2019.03.013

Abstract ( 434 ) PDF (KB) ( 7 )

The intensity data of the echo record the information about the radiometric characteristics of the object and can be effectively used in the object extraction and other remote sensing quantitative applications. Therefore the study on radiometric characteristics of intensity data has become a new hot spot in the field of LiDAR. The radar equation is studied on the basis of the theoretical derivation of radiation transmission mechanism, and the radiation properties and key influences of intensity data are systematically discussed and analyzed. Finally, these theories are verified and discussed by using the experimental platform of LiDAR system. The results and conclusions provide the necessary theoretical basis and technical support for radiometric calibration, object classification, and other quantitative applications of the waveform data.

A ship target detection method of SAR image based on saliency detection

YAN Chengzhang, LIU Chang

2019, 36 (3): 401-409. DOI: 10.7523/j.issn.2095-6134.2019.03.014

Abstract ( 350 ) PDF (KB) ( 0 )

Ship detection is an important direction of SAR image application in maritime surveillance. A multi-scale optimization threshold saliency detection is proposed in this study, for detecting ship targets of SAR image.The SAR image is first decomposed into a pyramid image sequence. Then the saliency detection is performed by using the spectral residual method for each layer in the sequence, and the salient subgraphs that contain ship targets are obtained. Finally, the subgraphs are fused and the optimization threshold segmentation method that applies to the saliency map is used to produce the final result. Experimental results show that the proposed approach has better detection performance, and it has low complexity and high detection accuracy and greatly reduces the dependence on prior knowledge.

An improved FastICA algorithm based on kurtosis index

MENG Lingbo, GENG Xiurui, YANG Weitun

2019, 36 (3): 410-416. DOI: 10.7523/j.issn.2095-6134.2019.03.015

Abstract ( 263 ) PDF (KB) ( 0 )

Independent component analysis (ICA) is a popular signal processing method based on the high-order statistical characteristics of data. It has been widely used in imagery processing. However, classical FastICA algorithm achieves independent components (ICs) of the data by the fixed-point iteration method. It needs cyclic iterations to get every IC, and in the iterative process the solution of each IC requires the participation of all pixels. Therefore, when the amount of data or the number of pixels is large, FastICA is time-consuming. At this point, its speed advantage is greatly reduced. The remote sensing data generally has a large size. So how to directly apply FastICA to remote sensing data is a practical problem. In this study, by introducing the cokurtosis tensor, the fixed point iteration problem of FastICA is transformed into tensor computation in algebraic form, and the participation of all pixels is avoided, thus greatly reducing the computational complexity. Experimental results for multispectral images show that the proposed algorithm is faster than the classical FastICA algorithm based on kurtosis.

Experiment simulation of the changes in wheat quality and color in the process of carbonization

SU Xin, LI Yumei, GU Yongjian

2019, 36 (3): 417-424. DOI: 10.7523/j.issn.2095-6134.2019.03.016

Abstract ( 228 ) PDF (KB) ( 0 )

The remains of wheat are important paleoethnobotany materials for studying the early types of human food. Most of the remains of unearthed wheat have been carbonized, but the conditions for carbonization are not clear. The indoor carbonization experiments were conducted under different temperature conditions by baking modern wheat to study the changes in wheat mass, surface color, and powder color with time, in order to reveal the carbonization conditions for the wheat remains. The mass and color changes of wheat under 200℃ were relatively small, and the mass and color of wheat varied greatly at 250℃ and above.At temperatures below 200℃, the main changes in the mass of wheat were caused by the loss of water. At temperatures above 250℃, there were significant losses of organic and inorganic substances besides the loss of water. Under different temperature conditions, the changes in L^* values (light or white) of wheat surface color and powder color were nearly synchronous, and the changes in a^* values (red-green) and b^* values (yellow-blue) were asynchronous. The change tendencies for the a^* value and b^* value were similar. Although the values of the colors of the surface and the powder were different at the beginning of the experiment, the values of wheat surface color and powder color were almost the same when wheat was completely carbonized. Experimental simulation results show the mass losses and color changes in wheat carbonization at different temperatures and provide valuable information for understanding the formation of carbonized wheat.

Positive effect of key player detection in social networks

WANG Xindong, YU Hua, JIANG Cheng

2019, 36 (3): 425-432. DOI: 10.7523/j.issn.2095-6134.2019.03.017

Abstract ( 271 ) PDF (KB) ( 0 )

Identifying influential nodes has been one of the most intensive studies among network analysis, and it is essential to control social networks. However, most of the existing methods are based on local features and lack the modeling of the overall network structure. In order to solve the key player problem positive (KPP-POS) problem effectively, we propose a 0-1 integer linear programming model (IP-KPP-POS) based on the detection standard D_R of KPP-POS. Then, we design a local search heuristic algorithm that significantly reduces the computational complexity and simultaneously achieves high accuracy. Finally, the effectiveness of our methods are validated by experiments with various synthetic networks and real-world networks.

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