The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide ...The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide future policy discussions of equality,firm localization and service allocation.Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China.Yet,few adopt longitudinal analysis to examine the temporal dynamics in the stregnth of existing associations.Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China.Using four-year city-level data from national population censuses and 1%population sample surveys conducted every five years between 2000 and 2015,we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time.Results reveal that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015.It also shows gradually strengthened and significantly positive spatial autocorrelation in the distribution of talent.An eigenvector spatial filtering negative binomial panel is employed to model the spatial determinants of talent distribution.Results indicate the influences of both economic opportunities and urban amenities,particularly urban public services and greening rate,on the distribution of talent.These results highlight that urban economic-and amenity-related factors have simultaneously driven China’s talent’s settlement patterns over the first fifteen years of the 21st century.展开更多
Spatial filtering velocimetry(SFV)has the advantages of simple structure,good stability,and wide applications.However,the traditional linear CCD-based SFV method requires an accurate angle between the direction of lin...Spatial filtering velocimetry(SFV)has the advantages of simple structure,good stability,and wide applications.However,the traditional linear CCD-based SFV method requires an accurate angle between the direction of linear CCD and the direction of moving object,so it is not suitable for measuring a complex flow field or two-dimensional speed in a granular media.In this paper,a new extension of spatial filtering method(SFM)based on high speed array CCD camera is proposed as simple and effective technique for measuring two-dimensional speed field of granular media.In particular,we analyzed the resolution and range of array CCD-based SFV so that the reader can clarify the application scene of this method.This method has a particular advantage for using orthogonal measurement to avoid the angle measurement,which were problematic when using linear CCD to measure the movement.Finally,the end-wall effects of the granular flow in rotating drum is studied with different experimental conditions by using this improved technique.展开更多
Snow water equivalent(SWE)is an important factor reflecting the variability of snow.It is important to estimate SWE based on remote sensing data while taking spatial autocorrelation into account.Based on the segmentat...Snow water equivalent(SWE)is an important factor reflecting the variability of snow.It is important to estimate SWE based on remote sensing data while taking spatial autocorrelation into account.Based on the segmentation method,the relationship between SWE and environmental factors in the central part of the Tibetan Plateau was explored using the eigenvector spatial filtering(ESF)regression model,and the influence of different factors on the SWE was explored.Three sizes of 16×16,24×24 and 32×32 were selected to segment raster datasets into blocks.The eigenvectors of the spatial adjacency matrix of the segmented size were selected to be added into the model as spatial factors,and the ESF regression model was constructed for each block in parallel.Results show that precipitation has a great influence on SWE,while surface temperature and NDVI have little influence.Air temperature,elevation and surface temperature have completely different effects in different areas.Compared with the ordinary least square(OLS)linear regression model,geographically weighted regression(GWR)model,spatial lag model(SLM)and spatial error model(SEM),ESF model can eliminate spatial autocorrelation with the highest accuracy.As the segmentation size increases,the complexity of ESF model increases,but the accuracy is improved.展开更多
This study is to assess the prevalence rates spatial pattern of neural tube defects with geographic information system and spatial filtering technique. A total of 80 infants who diagnosed from neural tube defects in t...This study is to assess the prevalence rates spatial pattern of neural tube defects with geographic information system and spatial filtering technique. A total of 80 infants who diagnosed from neural tube defects in the area being studied between 1998 and 2001 were analyzed. Firstly, the geographic information system （GIS） software ArcGIS was used to map the crude prevalence rates. Secondly, the data were smoothed by the method of spatial filtering. We evaluated that the effect of changes in spatial filtering radius size was assessed by creating maps based on various filtering radius sizes. The 3 miles or larger filtering radius gives better section variability than the 2 and 2.5 miles or smaller ones. The maps produced by the spatial filtering technique indicate that prevalence rates in the villages in the southeastern region are to produce higher prevalence than that in the other regions. The smoothed maps based on Heshun County display a more adequate data representation than the raw prevalence rate map.展开更多
The filter made up of two gratings performs as a two-dimensional non-spatial filtering. This paper reports that the volume Bragg gratings are fabricated by interfering two collimated coherent laser beams in photopolym...The filter made up of two gratings performs as a two-dimensional non-spatial filtering. This paper reports that the volume Bragg gratings are fabricated by interfering two collimated coherent laser beams in photopolymer. Diffraction efficiency of a single grating is up to 78% in Bragg＇s condition, then a two-dimensional non-spatial filter, which consists of two volume Bragg gratings and a half-wave plate, enables the laser beam filtered in two dimensions with the diffraction efficiency of 54%. The Bragg＇s condition and effect of polarisation on performances of the two-dimension filter are also discussed.展开更多
A position sensor based on grating projection with spatial filtering and polarization modulation is presented. A grating is projected onto the object to be measured through a 4f optical system with a spatial filter. A...A position sensor based on grating projection with spatial filtering and polarization modulation is presented. A grating is projected onto the object to be measured through a 4f optical system with a spatial filter. After reflected by the object, the grating projection is imaged on a detection grating through another 4f optical system to form moiré fringes, The polarization modulated moiré signal is detected to obtain the position information of the object. In the position sensor, the moiré signal varies sinusoidally with the position of object. The measurement is independent of the incident intensity on the projection grating and the reflectivity of the object to be measured, In experiments, the effectiveness of the position sensor is proved, and the root mean square （RMS） error at each measurement position is less than 13 nm.展开更多
As one of the interesting optical techniques for measurements of the velocity,the spatial filtering method is treated briefly in this paper.We shown theoretical analysis and calculation of spatial filtering velocimetr...As one of the interesting optical techniques for measurements of the velocity,the spatial filtering method is treated briefly in this paper.We shown theoretical analysis and calculation of spatial filtering velocimetry,and discussed two-dimensional measurements of the velocity.About the data processing,we used A/D conversion and interfaced with a microcomputer,so that the data can be processed automatically by the microcomputer.The preliminary experiment was performed and the experimental results show the usefulness of the present method for measurements of the velocity.展开更多
We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays （PDFAs） with elemental images in computational integral imaging....We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays （PDFAs） with elemental images in computational integral imaging. The multiple PDFAs, whose spatial periods correspond to object＇s depths with the elemental image array （EIA）, can generate a set of spatially filtered EIAs for multiple object depths compared with the conventional method for the depth of a single object. We analyze a controllable spatial filtering effect by the proposed method. To show the feasibility of the proposed method, we carry out preliminary experiments for multiple objects and present the results.展开更多
A spatial mask filter algorithm （SMF） for partial discharge （PD） pulse extraction is proposed in this paper. In this algorithm, firstly, a ＇Teager＇ operator is used to strengthen wavelet coefficient local energy...A spatial mask filter algorithm （SMF） for partial discharge （PD） pulse extraction is proposed in this paper. In this algorithm, firstly, a ＇Teager＇ operator is used to strengthen wavelet coefficient local energy; then direct multiplication of coefficients at two adjacent scales is used to detect singularity points of the signal and to obtain scale based spatial mask filter; finally, an ＇ AND＇ logic operator is used in different filters to obtain the last spatial mask filter. By multiplication of wavelet coefficients with the final mask filter and wavelet reconstruction process, partial discharge pulses are extracted. The results of digital simulation and practical experiment show that this method is superior to traditional wavelet shrinkage method （TWS）. This algorithm not only can increase the signal to noise ratio （SNR）, but also can preserve the encrgy and pulse amplitude.展开更多
To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesi...To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesis of the residual and the error is proposed in this paper.It chooses the best subset of measurements to calculate the coordinates of the unknown node by comparing the residuals obtained with different subsets of beacons.To reduce the time complexity of the IMR algorithm,Spatial Correlation Filter (SCF) is also proposed,which can remove the most serious NLoS distance with low calculation cost.Combined with the proposed SCF and IMR algorithm,nodes can be localized with high accuracy and low time complexity.Experimental results with real dataset demonstrate that the proposed algorithm can identify the NLoS range effectively with about 50% time cost of employing SCF only.展开更多
Dynamic load imposed on the bridge by mov- ing vehicle depends on several bridge-vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been...Dynamic load imposed on the bridge by mov- ing vehicle depends on several bridge-vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been used to identify vehicle mass, suspension stiffness, and damping including tyre parameters from simulated bridge accelerations at different locations. A closed-form expres- sion is derived to generate independent response samples for the idealized bridge-vehicle coupled system consider- ing spatially non-homogeneous pavement unevenness. Thereafter, it is interfaced with the iterative process of particle filtering algorithm. The generated response sam- ples are contaminated by adding artificial noise in order to reflect field condition. The mean acceleration time history is utilized in particle filtering technique. The vehicle- imposed dynamic load is reconstructed with the identified parameters and compared with the simulated results. The present identification technique is examined in the presence of different levels of artificial noise with bridge response simulated at different locations. The effect of vehicle velocity, bridge surface roughness, and choice of prior probability density parameters on the efficiency of the method is discussed.展开更多
The true-time delay(TTD)units are critical for solving beam squint and frequency selective fading inWideband Large-Scale Antenna Systems(LSASs).In this work,we propose a TTD array architecture for wideband multi-beam ...The true-time delay(TTD)units are critical for solving beam squint and frequency selective fading inWideband Large-Scale Antenna Systems(LSASs).In this work,we propose a TTD array architecture for wideband multi-beam tracking that eliminates the beam squint phenomenon and filters out interference signals by applying a spatial filter and time delay estimations(TDEs).The paper presents a novel approach to spatial filter design by introducing a transformation matrix that can optimize the beam response in a specific direction and at a specific frequency.Using the variable fractional delay(VFD)filters,we propose a TDE algorithm with a Newton-Raphson iteration update process that corrects the arrival time delay difference between sensors.Simulations and examples have demonstrated that the proposed architecture can achieve beam tracking within 10 ms at the low signalto-noise ratio(SNR)and demodulation loss is less than 0.5 dB in wideband multi-beam scenarios.展开更多
Frequency selective surfaces(FSSs)play an important role in wireless systems as these can be used as filters,in isolating the unwanted radiation,in microstrip patch antennas for improving the performance of these ante...Frequency selective surfaces(FSSs)play an important role in wireless systems as these can be used as filters,in isolating the unwanted radiation,in microstrip patch antennas for improving the performance of these antennas and in other 5G applications.The analysis and design of the double concentric ring frequency selective surface(DCRFSS)is presented in this research.In the sub-6 GHz 5G FR1 spectrum,a computational synthesis technique for creating DCRFSS based spatial filters is proposed.The analytical tools presented in this study can be used to gain a better understanding of filtering processes and for constructing the spatial filters.Variation of the loop sizes,angles of incidence,and polarization of the concentric rings are the factors which influence the transmission coefficient as per the thorough investigation performed in this paper.A novel synthesis approach based on mathematical equations that may be used to determine the physical parameters ofDCRFSSbased spatial filters is presented.The proposed synthesis technique is validated by comparing results from high frequency structure simulator(HFSS),Ansys electronic desktop circuit editor,and an experimental setup.Furthermore,the findings acquired from a unit cell are expanded to a 2×2 array,which shows identical performance and therefore proves its stability.展开更多
The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information.However,traditional data assimilation methods cannot better extract the valuable information due to the ...The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information.However,traditional data assimilation methods cannot better extract the valuable information due to the complicated variability of the sea ice concentration in the marginal ice zone.A successive corrections analysis using variational optimization method,called spatial multi-scale recursive filter(SMRF),has been designed in this paper to extract multi-scale information resolved by sea ice observations.It is a combination of successive correction methods(SCM)and minimization algorithms,in which various observational scales,from longer to shorter wavelengths,can be extracted successively.As a variational objective analysis scheme,it gains the advantage over the conventional approaches that analyze all scales resolved by observations at one time,and also,the specification of parameters is more convenient.Results of single-observation experiment demonstrate that the SMRF scheme possesses a good ability in propagating observational signals.Further,it shows a superior performance in extracting multi-scale information in a two-dimensional sea ice concentration(SIC)experiment with the real observations from Special Sensor Microwave/Imager SIC(SSMI).展开更多
The spatial matrix filter was designed and used for solving the problem to detect a weak target who was influenced by the strong nearby platform noise interference of the towed line array sonar. The MFP technology and...The spatial matrix filter was designed and used for solving the problem to detect a weak target who was influenced by the strong nearby platform noise interference of the towed line array sonar. The MFP technology and the DOA estimation technology were combined together by using the sound propagation characteristics of both target and interference. The spatial matrix filter with platform noise zero response constraint was designed by the near-field platform noise normal modes copy vectors and the far-field plane wave bearing vectors together. The optimal solution of the optimization problem for designing the spatial matrix filter was deduced directly, and it was simplified by the generalized singular value decomposition. The total response error to the plane wave bearing vectors and the total response to the platform noise copy vectors were given. The phenomena that strong interferences existed in the bearing course and blind areas existed after filtering were analyzed by the correlation between the plat- form noise copy vectors and the plane wave bearing vectors. It could be found from simulations that it has less blind area and higher detection ability by using the spatial matrix filtering technology.展开更多
Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body d...Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body deformation occur frequently. A spatial-confidential proposal filtering method(SCPF) is proposed for efficient and accurate human detection. It consists of two filtering phases: spatial proposal filtering and confidential proposal filtering. A compact spatial proposal is generated in the first phase to minimize the search space to reduce the computation cost. The human detector only estimates the confidence scores of the candidate search regions accepted by the spatial proposal instead of global scanning. At the second phase, each candidate search region is assigned with a supplementary confidence score according to their reliability estimated by the confidential proposal to reduce missing detections. The performance of the SCPF method is verified by extensive tests on several video sequences from available public datasets. Both quantitatively and qualitatively experimental results indicate that the proposed method can highly improve the efficiency and the accuracy of human detection.展开更多
A new type of real-time holographic three-slit interferometer is presented. It uses a calcite polarized optical element to obtain objective light and reference light to record a hologram. Its remarkable feature is to ...A new type of real-time holographic three-slit interferometer is presented. It uses a calcite polarized optical element to obtain objective light and reference light to record a hologram. Its remarkable feature is to use a beam of fixed slit diffracted light as the reference light to record the lateral slit diffracted wave front, and to use also the same diffracted light as the illuminating light to reconstruct the wave front. This insures the phase distribution of the reconstructed wave front against the influence by the small natural direction drift of the laser beam and also by the tiny external vibration. The stability, reliability and measuring accuracy of this apparatus are improved notably.展开更多
We present a general formulation based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Gray-level images degraded with Gaussian white noise have been considered. Based on the pixel loca...We present a general formulation based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Gray-level images degraded with Gaussian white noise have been considered. Based on the pixel local neighborhood, fuzzy logic has been employed intelligently to avoid unnecessary estimation of a pixel. The intensity estimation of the selected pixels is then carried out by employing punctual kriging in conjunction with the method of Lagrange multipliers and estimates of local semi-variances. Application of such a hybrid technique performing both selection and intensity estimation of a pixel demonstrates substantial improvement in the image quality as compared to the adaptive Wiener filter and existing fuzzykriging approaches. It has been found that these filters achieve noise reduction without loss of structural detail information, as indicated by their higher structure similarity indices, peak signal to noise ratios and the new variogram based quality measures.展开更多
Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and pop...Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and population at the administrative-unit-level(AUlevel)and transfer it to generate the gridded population.However,the statistical characteristic of attributes at the pixel-level differs from that at the AU-level,thus leading to prediction bias via the cross-scale modeling(i.e.scale mismatch problem).In addition,integrating multi-source data simply as covariates may underutilize spatial semantics,and lead to incorrect population disaggregation;while neglecting the spatial autocorrelation of population generates excessively heterogeneous population distribution that contradicts to real-world situation.To address the scale mismatch in downscaling,this paper proposes a Cross-Scale Feature Construction(CSFC)method.More specifically,by grading pixel-level attributes,we construct the feature vector of pixel grade proportions to narrow the scale differences in feature representation between AU-level and pixel-level.Meanwhile,fine-grained building patch and mobile positioning data are utilized to adjust the population weighting layer generated from POI-density-based regression modeling.Spatial filtering is furtherly adopted to model the spatial autocorrelation effect of population and reduce the heterogeneity in population caused by pixel-level attribute discretization.Through the comparison with traditional feature construction method and the ablation experiments,the results demonstrate significant accuracy improvements in population spatialization and verify the effectiveness of weight correction steps.Furthermore,accuracy comparisons with WorldPop and GPW datasets quantitatively illustrate the advantages of the proposed method in fine-scale population spatialization.展开更多
Although China was one of the countries with the fastest-growing aging population in the world,limited scholarly attention has been paid to migration among older adults in China.The full picture of their migration in ...Although China was one of the countries with the fastest-growing aging population in the world,limited scholarly attention has been paid to migration among older adults in China.The full picture of their migration in the entire country over time remains unknown.This study examines the spatial patterns of older interprovincial migration flows and their drivers in China over the period 1995 to 2015,using four waves of census data and intercensal population sample survey data.Results from eigenvector spatial filtering negative binomial regressions indicate that older adults tend to migrate away from low cost-of-living rural areas to high cost-of-living urban and rural areas,moving away from areas with extreme temperature differences.The location of their grandchildren is among the most important attractions.Our findings suggest that family-oriented migration is more common than amenity-led migration among retired Chinese older adults,and the cost-of-living is an indicator of economic opportunities for adult children and the quality of senior care services.展开更多
基金Under the auspices of the National Social Science Foundation of China(No.17ZDA055).
文摘The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide future policy discussions of equality,firm localization and service allocation.Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China.Yet,few adopt longitudinal analysis to examine the temporal dynamics in the stregnth of existing associations.Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China.Using four-year city-level data from national population censuses and 1%population sample surveys conducted every five years between 2000 and 2015,we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time.Results reveal that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015.It also shows gradually strengthened and significantly positive spatial autocorrelation in the distribution of talent.An eigenvector spatial filtering negative binomial panel is employed to model the spatial determinants of talent distribution.Results indicate the influences of both economic opportunities and urban amenities,particularly urban public services and greening rate,on the distribution of talent.These results highlight that urban economic-and amenity-related factors have simultaneously driven China’s talent’s settlement patterns over the first fifteen years of the 21st century.
基金Project supported by the National Natural Science Foundation of China(Grant No.11902190)the Construction Project of Shanghai Key Laboratory of Molecular Imaging(Grant No.18DZ2260400)the Fund from the Shanghai Municipal Education Commission,China(Class II Plateau Disciplinary Construction Program of Medical Technology of SUMHS,2018-2020).
文摘Spatial filtering velocimetry(SFV)has the advantages of simple structure,good stability,and wide applications.However,the traditional linear CCD-based SFV method requires an accurate angle between the direction of linear CCD and the direction of moving object,so it is not suitable for measuring a complex flow field or two-dimensional speed in a granular media.In this paper,a new extension of spatial filtering method(SFM)based on high speed array CCD camera is proposed as simple and effective technique for measuring two-dimensional speed field of granular media.In particular,we analyzed the resolution and range of array CCD-based SFV so that the reader can clarify the application scene of this method.This method has a particular advantage for using orthogonal measurement to avoid the angle measurement,which were problematic when using linear CCD to measure the movement.Finally,the end-wall effects of the granular flow in rotating drum is studied with different experimental conditions by using this improved technique.
基金funded by the National Key S&T Special Projects of China(grant number:2018YFB0505302)the National Nature Science Foundation of China(grant number:41671380)。
文摘Snow water equivalent(SWE)is an important factor reflecting the variability of snow.It is important to estimate SWE based on remote sensing data while taking spatial autocorrelation into account.Based on the segmentation method,the relationship between SWE and environmental factors in the central part of the Tibetan Plateau was explored using the eigenvector spatial filtering(ESF)regression model,and the influence of different factors on the SWE was explored.Three sizes of 16×16,24×24 and 32×32 were selected to segment raster datasets into blocks.The eigenvectors of the spatial adjacency matrix of the segmented size were selected to be added into the model as spatial factors,and the ESF regression model was constructed for each block in parallel.Results show that precipitation has a great influence on SWE,while surface temperature and NDVI have little influence.Air temperature,elevation and surface temperature have completely different effects in different areas.Compared with the ordinary least square(OLS)linear regression model,geographically weighted regression(GWR)model,spatial lag model(SLM)and spatial error model(SEM),ESF model can eliminate spatial autocorrelation with the highest accuracy.As the segmentation size increases,the complexity of ESF model increases,but the accuracy is improved.
基金Supported by the National Basic Reserch Program of China (973 Program) (2001CB5103)the National Natural Science Foundation of China (40471111 and 70571076).
文摘This study is to assess the prevalence rates spatial pattern of neural tube defects with geographic information system and spatial filtering technique. A total of 80 infants who diagnosed from neural tube defects in the area being studied between 1998 and 2001 were analyzed. Firstly, the geographic information system （GIS） software ArcGIS was used to map the crude prevalence rates. Secondly, the data were smoothed by the method of spatial filtering. We evaluated that the effect of changes in spatial filtering radius size was assessed by creating maps based on various filtering radius sizes. The 3 miles or larger filtering radius gives better section variability than the 2 and 2.5 miles or smaller ones. The maps produced by the spatial filtering technique indicate that prevalence rates in the villages in the southeastern region are to produce higher prevalence than that in the other regions. The smoothed maps based on Heshun County display a more adequate data representation than the raw prevalence rate map.
基金supported by the Joint Fund of the National Natural Science Foundation of China and the China Academy of Engineering Physics (NSAF) (Grant No. 10676038)
文摘The filter made up of two gratings performs as a two-dimensional non-spatial filtering. This paper reports that the volume Bragg gratings are fabricated by interfering two collimated coherent laser beams in photopolymer. Diffraction efficiency of a single grating is up to 78% in Bragg＇s condition, then a two-dimensional non-spatial filter, which consists of two volume Bragg gratings and a half-wave plate, enables the laser beam filtered in two dimensions with the diffraction efficiency of 54%. The Bragg＇s condition and effect of polarisation on performances of the two-dimension filter are also discussed.
文摘A position sensor based on grating projection with spatial filtering and polarization modulation is presented. A grating is projected onto the object to be measured through a 4f optical system with a spatial filter. After reflected by the object, the grating projection is imaged on a detection grating through another 4f optical system to form moiré fringes, The polarization modulated moiré signal is detected to obtain the position information of the object. In the position sensor, the moiré signal varies sinusoidally with the position of object. The measurement is independent of the incident intensity on the projection grating and the reflectivity of the object to be measured, In experiments, the effectiveness of the position sensor is proved, and the root mean square （RMS） error at each measurement position is less than 13 nm.
文摘As one of the interesting optical techniques for measurements of the velocity,the spatial filtering method is treated briefly in this paper.We shown theoretical analysis and calculation of spatial filtering velocimetry,and discussed two-dimensional measurements of the velocity.About the data processing,we used A/D conversion and interfaced with a microcomputer,so that the data can be processed automatically by the microcomputer.The preliminary experiment was performed and the experimental results show the usefulness of the present method for measurements of the velocity.
基金supported by the information technology(IT)research and development program of MKE/KEIT(10041682Development of High-Definition 3D Image Processing Technologies Using Advanced Integral Imaging with Improved Depth Range)
文摘We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays （PDFAs） with elemental images in computational integral imaging. The multiple PDFAs, whose spatial periods correspond to object＇s depths with the elemental image array （EIA）, can generate a set of spatially filtered EIAs for multiple object depths compared with the conventional method for the depth of a single object. We analyze a controllable spatial filtering effect by the proposed method. To show the feasibility of the proposed method, we carry out preliminary experiments for multiple objects and present the results.
文摘A spatial mask filter algorithm （SMF） for partial discharge （PD） pulse extraction is proposed in this paper. In this algorithm, firstly, a ＇Teager＇ operator is used to strengthen wavelet coefficient local energy; then direct multiplication of coefficients at two adjacent scales is used to detect singularity points of the signal and to obtain scale based spatial mask filter; finally, an ＇ AND＇ logic operator is used in different filters to obtain the last spatial mask filter. By multiplication of wavelet coefficients with the final mask filter and wavelet reconstruction process, partial discharge pulses are extracted. The results of digital simulation and practical experiment show that this method is superior to traditional wavelet shrinkage method （TWS）. This algorithm not only can increase the signal to noise ratio （SNR）, but also can preserve the encrgy and pulse amplitude.
基金supported by the National Natural Science Foundation of China under Grants No.60973110,No.61003307the Natural Science Foundation of Beijing City of China under Grant No.4102059the Major Projects of Ministry of Industry and Information Technology under Grants No.2010ZX03006-002-03,No.2011ZX03005-005
文摘To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesis of the residual and the error is proposed in this paper.It chooses the best subset of measurements to calculate the coordinates of the unknown node by comparing the residuals obtained with different subsets of beacons.To reduce the time complexity of the IMR algorithm,Spatial Correlation Filter (SCF) is also proposed,which can remove the most serious NLoS distance with low calculation cost.Combined with the proposed SCF and IMR algorithm,nodes can be localized with high accuracy and low time complexity.Experimental results with real dataset demonstrate that the proposed algorithm can identify the NLoS range effectively with about 50% time cost of employing SCF only.
文摘Dynamic load imposed on the bridge by mov- ing vehicle depends on several bridge-vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been used to identify vehicle mass, suspension stiffness, and damping including tyre parameters from simulated bridge accelerations at different locations. A closed-form expres- sion is derived to generate independent response samples for the idealized bridge-vehicle coupled system consider- ing spatially non-homogeneous pavement unevenness. Thereafter, it is interfaced with the iterative process of particle filtering algorithm. The generated response sam- ples are contaminated by adding artificial noise in order to reflect field condition. The mean acceleration time history is utilized in particle filtering technique. The vehicle- imposed dynamic load is reconstructed with the identified parameters and compared with the simulated results. The present identification technique is examined in the presence of different levels of artificial noise with bridge response simulated at different locations. The effect of vehicle velocity, bridge surface roughness, and choice of prior probability density parameters on the efficiency of the method is discussed.
基金supported by the foundation of National Key Laboratory of Electromagnetic Environment(Grant No.202103012).
文摘The true-time delay(TTD)units are critical for solving beam squint and frequency selective fading inWideband Large-Scale Antenna Systems(LSASs).In this work,we propose a TTD array architecture for wideband multi-beam tracking that eliminates the beam squint phenomenon and filters out interference signals by applying a spatial filter and time delay estimations(TDEs).The paper presents a novel approach to spatial filter design by introducing a transformation matrix that can optimize the beam response in a specific direction and at a specific frequency.Using the variable fractional delay(VFD)filters,we propose a TDE algorithm with a Newton-Raphson iteration update process that corrects the arrival time delay difference between sensors.Simulations and examples have demonstrated that the proposed architecture can achieve beam tracking within 10 ms at the low signalto-noise ratio(SNR)and demodulation loss is less than 0.5 dB in wideband multi-beam scenarios.
文摘Frequency selective surfaces(FSSs)play an important role in wireless systems as these can be used as filters,in isolating the unwanted radiation,in microstrip patch antennas for improving the performance of these antennas and in other 5G applications.The analysis and design of the double concentric ring frequency selective surface(DCRFSS)is presented in this research.In the sub-6 GHz 5G FR1 spectrum,a computational synthesis technique for creating DCRFSS based spatial filters is proposed.The analytical tools presented in this study can be used to gain a better understanding of filtering processes and for constructing the spatial filters.Variation of the loop sizes,angles of incidence,and polarization of the concentric rings are the factors which influence the transmission coefficient as per the thorough investigation performed in this paper.A novel synthesis approach based on mathematical equations that may be used to determine the physical parameters ofDCRFSSbased spatial filters is presented.The proposed synthesis technique is validated by comparing results from high frequency structure simulator(HFSS),Ansys electronic desktop circuit editor,and an experimental setup.Furthermore,the findings acquired from a unit cell are expanded to a 2×2 array,which shows identical performance and therefore proves its stability.
基金The National Key Research and Development Program of China under contract Nos 2017YFC1404103 and 2016YFC1401701the National Programme on Global Change and Air-Sea Interaction of China under contract GASI-IPOVAI-04the National Natural Science Foundation of China under contract Nos 41876014 and 41606039.
文摘The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information.However,traditional data assimilation methods cannot better extract the valuable information due to the complicated variability of the sea ice concentration in the marginal ice zone.A successive corrections analysis using variational optimization method,called spatial multi-scale recursive filter(SMRF),has been designed in this paper to extract multi-scale information resolved by sea ice observations.It is a combination of successive correction methods(SCM)and minimization algorithms,in which various observational scales,from longer to shorter wavelengths,can be extracted successively.As a variational objective analysis scheme,it gains the advantage over the conventional approaches that analyze all scales resolved by observations at one time,and also,the specification of parameters is more convenient.Results of single-observation experiment demonstrate that the SMRF scheme possesses a good ability in propagating observational signals.Further,it shows a superior performance in extracting multi-scale information in a two-dimensional sea ice concentration(SIC)experiment with the real observations from Special Sensor Microwave/Imager SIC(SSMI).
基金supported by the National Natural Science Foundation of China(60532040,11374001)
文摘The spatial matrix filter was designed and used for solving the problem to detect a weak target who was influenced by the strong nearby platform noise interference of the towed line array sonar. The MFP technology and the DOA estimation technology were combined together by using the sound propagation characteristics of both target and interference. The spatial matrix filter with platform noise zero response constraint was designed by the near-field platform noise normal modes copy vectors and the far-field plane wave bearing vectors together. The optimal solution of the optimization problem for designing the spatial matrix filter was deduced directly, and it was simplified by the generalized singular value decomposition. The total response error to the plane wave bearing vectors and the total response to the platform noise copy vectors were given. The phenomena that strong interferences existed in the bearing course and blind areas existed after filtering were analyzed by the correlation between the plat- form noise copy vectors and the plane wave bearing vectors. It could be found from simulations that it has less blind area and higher detection ability by using the spatial matrix filtering technology.
基金Projects(61175096,60772063)supported by the National Natural Science Foundation of China
文摘Traditional human detection using pre-trained detectors tends to be computationally intensive for time-critical tracking tasks, and the detection rate is prone to be unsatisfying when occlusion, motion blur and body deformation occur frequently. A spatial-confidential proposal filtering method(SCPF) is proposed for efficient and accurate human detection. It consists of two filtering phases: spatial proposal filtering and confidential proposal filtering. A compact spatial proposal is generated in the first phase to minimize the search space to reduce the computation cost. The human detector only estimates the confidence scores of the candidate search regions accepted by the spatial proposal instead of global scanning. At the second phase, each candidate search region is assigned with a supplementary confidence score according to their reliability estimated by the confidential proposal to reduce missing detections. The performance of the SCPF method is verified by extensive tests on several video sequences from available public datasets. Both quantitatively and qualitatively experimental results indicate that the proposed method can highly improve the efficiency and the accuracy of human detection.
文摘A new type of real-time holographic three-slit interferometer is presented. It uses a calcite polarized optical element to obtain objective light and reference light to record a hologram. Its remarkable feature is to use a beam of fixed slit diffracted light as the reference light to record the lateral slit diffracted wave front, and to use also the same diffracted light as the illuminating light to reconstruct the wave front. This insures the phase distribution of the reconstructed wave front against the influence by the small natural direction drift of the laser beam and also by the tiny external vibration. The stability, reliability and measuring accuracy of this apparatus are improved notably.
基金This work has been sponsored by the Higher Education Commission,Government of Pakistan under the Scholarship Grant No.17-6(176)Sch/2001.
文摘We present a general formulation based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Gray-level images degraded with Gaussian white noise have been considered. Based on the pixel local neighborhood, fuzzy logic has been employed intelligently to avoid unnecessary estimation of a pixel. The intensity estimation of the selected pixels is then carried out by employing punctual kriging in conjunction with the method of Lagrange multipliers and estimates of local semi-variances. Application of such a hybrid technique performing both selection and intensity estimation of a pixel demonstrates substantial improvement in the image quality as compared to the adaptive Wiener filter and existing fuzzykriging approaches. It has been found that these filters achieve noise reduction without loss of structural detail information, as indicated by their higher structure similarity indices, peak signal to noise ratios and the new variogram based quality measures.
基金National Natural Science Foundation of China[Grant Nos.42090010,U20A2091,41971349,and 41930107]National Key R&D Program of China[Grant Nos.2018YFC0809800 and 2017YFB0503704].
文摘Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and population at the administrative-unit-level(AUlevel)and transfer it to generate the gridded population.However,the statistical characteristic of attributes at the pixel-level differs from that at the AU-level,thus leading to prediction bias via the cross-scale modeling(i.e.scale mismatch problem).In addition,integrating multi-source data simply as covariates may underutilize spatial semantics,and lead to incorrect population disaggregation;while neglecting the spatial autocorrelation of population generates excessively heterogeneous population distribution that contradicts to real-world situation.To address the scale mismatch in downscaling,this paper proposes a Cross-Scale Feature Construction(CSFC)method.More specifically,by grading pixel-level attributes,we construct the feature vector of pixel grade proportions to narrow the scale differences in feature representation between AU-level and pixel-level.Meanwhile,fine-grained building patch and mobile positioning data are utilized to adjust the population weighting layer generated from POI-density-based regression modeling.Spatial filtering is furtherly adopted to model the spatial autocorrelation effect of population and reduce the heterogeneity in population caused by pixel-level attribute discretization.Through the comparison with traditional feature construction method and the ablation experiments,the results demonstrate significant accuracy improvements in population spatialization and verify the effectiveness of weight correction steps.Furthermore,accuracy comparisons with WorldPop and GPW datasets quantitatively illustrate the advantages of the proposed method in fine-scale population spatialization.
基金National Natural Science Foundation of China,No.42001153,No.42001161。
文摘Although China was one of the countries with the fastest-growing aging population in the world,limited scholarly attention has been paid to migration among older adults in China.The full picture of their migration in the entire country over time remains unknown.This study examines the spatial patterns of older interprovincial migration flows and their drivers in China over the period 1995 to 2015,using four waves of census data and intercensal population sample survey data.Results from eigenvector spatial filtering negative binomial regressions indicate that older adults tend to migrate away from low cost-of-living rural areas to high cost-of-living urban and rural areas,moving away from areas with extreme temperature differences.The location of their grandchildren is among the most important attractions.Our findings suggest that family-oriented migration is more common than amenity-led migration among retired Chinese older adults,and the cost-of-living is an indicator of economic opportunities for adult children and the quality of senior care services.
