Geography of Talent in China During 2000-2015:An Eigenvector Spatial Filtering Negative Binomial Approach

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.

Application of GIS-Based Spatial Filtering Method for Neural Tube Defects Disease Mapping

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.

Improved spatial filtering velocimetry and its application in granular flow measurement

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.

An enhanced method for estimating snow water equivalent in the central part of the Tibetan Plateau using raster segmentation and eigenvector spatial filtering regression model

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.

Two-dimensional non-spatial filtering based on holographic Bragg gratings

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.

Application of Spatial Filtering Techniques in the Measurement of the Velocity

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.

A position sensor based on grating projection with spatial filtering and polarization modulation

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.

3D image reconstruction with controllable spatial filtering based on correlation of multiple periodic functions 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.

Matched field noise suppression: A generalized spatial filtering approach

An approach to improving the performance of matched field localization by introducing a generalized spa-tial filter to suppress interference noise and pass the signal of interest with minimal distortion is presented. The spatial filter is designed by minimizing the maximum distortion of the filtered replica vectors within passband while guaran- teeing the norm of the filter response within the stopband to be lower than some given threshold values. We show that the design problem can be formulated as the second-order cone programming (SOCP) which can be solved efficiently via the well-established interior point method. A modified matched field processor is given to ultimately eliminate the effect of the distortion in the spatially filtered replica vectors. Computer simulation results confirm the effectiveness of the proposed approach by localizing a weak source in the pres-ence of a strong interferer and noise.

Improved SMB speckle filtering of polarimetric SAR data with synergistic use of orientation angle compensation and spatial majority rule

The scattering-model-based(SMB)speckle filtering for polarimetric SAR(Pol SAR)data is reasonably effective in preserving dominant scattering mechanisms.However,the efficiency strongly depends on the accuracies of both the decomposition and classification of the scattering properties.In addition,a relatively weak speckle reduction particularly in distributed media was reported in the related literatures.In this work,an improved SMB filtering strategy is proposed considering the aforementioned deficiencies.First,the orientation angle compensation is incorporated into the SMB filtering process to remedy the overestimation of the volume scattering contribution in the Freeman-Durden decomposition.In addition,an algorithm to select the homogenous pixels is developed based on the spatial majority rule for adaptive speckle reduction.We demonstrate the superiority of the proposed methods in terms of scattering property preservation and speckle noise reduction using L-band Pol SAR data sets of San Francisco that were acquired by the NASA/JPL airborne SAR(AIRSAR)system.

Improvement of instantaneous positioning by spatial stacking and modified sidereal filtering methods with application to the 2008 Ms8.0 Wenchuan earthquake

We obtained several displacement time series from the Sichuan permanent GPS net and processed the 1-Hz data observed during a few days before the 2008 Ms8.0 Wenchuan earthquake by double-difference instantaneous positioning technique. We filtered the data by the spatial stacking and the modified sidereal filte- ring methods to reduce correlation bias in space and time. The results indicate that these methods can improve the precision significantly.

Spatial mask filtering algorithm for partial discharge pulse extraction of large generators

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.

利用Spatial处理空间数据

主要解释Oracle Spatial的核心概念,尤其是它在存储和分析空间数据方面的作用.首先介绍了数据模型的概念,然后通过实例解释了如何把一个复杂的空间图形输入到数据库中,最后对如何高效地查询指定内容进行了详细的描述.

An E-Commerce Recommender System Based on Content-Based Filtering

Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products informa tion, the recommender lists were obtained. Since the system can adapt to the users＇ feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.

NLoS Mitigation in ToA Localization Based on Spatial Correlation Filter and Iterative Minimum Residual

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.

A Topology-Based Conflict Detection System for Firewall Policies using Bit-Vector-Based Spatial Calculus

Firewalls use packet filtering to either accept or deny packets on the basis of a set of predefined rules called filters. The firewall forms the initial layer of defense and protects the network from unauthorized access. However, maintaining firewall policies is always an error prone task, because the policies are highly complex. Conflict is a misconfiguration that occurs when a packet matches two or more filters. The occurrence of conflicts in a firewall policy makes the filters either redundant or shadowed, and as a result, the network does not reflect the actual configuration of the firewall policy. Hence, it is necessary to detect conflicts to keep the filters meaningful. Even though geometry-based conflict detection provides an exhaustive method for error classification, when the number of filters and headers increases, the demands on memory and computation time increase. To solve these two issues, we make two main contributions. First, we propose a topology-based conflict detection system that computes the topological relationship of the filters to detect the conflicts. Second, we propose a systematic implementation method called BISCAL (a bit-vector-based spatial calculus) to implement the proposed system and remove irrelevant data from the conflict detection computation. We perform a mathematical analysis as well as experimental evaluations and find that the amount of data needed for topology is only one-fourth of that needed for geometry.

Robust Spatial Filters on Three-Class Motor Imagery EEG Data Using Independent Component Analysis

Independent Component Analysis (ICA) was often used to separate movement related independent components (MRICs) from Electroencephalogram (EEG) data.?However, to obtain robust spatial filters, complex characteristic features, which were manually selected in most cases, have been commonly used. This study proposed a new simple algorithm to extract MRICs automatically, which just utilized the spatial distribution pattern of ICs. The main goal of this study was to show the relationship between spatial filters performance and designing samples. The EEG data which contain?mixed brain states (preparing, motor imagery and rest) were used to design spatial filters. Meanwhile, the single class data was also used to calculate spatial filters to assess whether the MRICs extracted on different class motor imagery spatial filters are similar. Furthermore, the spatial filters constructed on one subject’s EEG data were applied to extract the others’ MRICs. Finally, the different spatial filters were then applied to single-trial EEG to extract MRICs, and Support Vector Machine (SVM) classifiers were used to discriminate left hand、right-hand and foot imagery movements of BCI Competition IV Dataset 2a, which recorded four motor imagery data of nine subjects. The results suggested that any segment of finite motor imagery EEG samples could be used to design ICA spatial filters, and the extracted MRICs are consistent if the position of electrodes are the same, which confirmed the robustness and practicality of ICA used in the motor imagery Brain Computer Interfaces (MI-BCI) systems.

Relative Contributions of Spatial and Environmental Processes and Biotic Interactions in a Soil Collembolan Community

Understanding the underlying processes of how communities are structured remains a central question in community ecology. However, the mechanisms of the soil animal community are still unclear, especially for communities on a small scale. To evaluate the relative roles of biotic interactions and environmental and spatial processes in a soil collembolan community, a field experiment was carried out on a small scale(50 m) in the farmland ecosystem of the Sanjiang Plain, Northeast China. In August and October, 2011, we took 100 samples each month in a 50 m × 50 m plot using a spatially delimited sampling design. Variation partitioning was used to quantify the relative contributions of the spatial and environmental variables. A null model was selected to test for the non-randomness pattern of species co-occurrence and body size in assemblages of collembolans and to test whether the pattern observed was the result of environmental or biotic processes that structured the community on a small scale. The results showed that large variance was accounted for by spatial variables(18.99% in August and 21.83% in October, both were significant). There were relatively lower effects of environmental variation(3.56% in August and 1.45% in October, neither was significant), while the soil water content, soil p H and soybean height explained a significant portion of the variance that was observed in the spatial pattern of the collembolan community. Furthermore, the null model revealed more co-occurrence than expected by chance, suggesting that collembolan communities had a non-random co-occurrence pattern in both August and October. Additionally, environmental niche overlap and the body size ratio of co-occurrence showed that interspecific competition was not influential in collembolan community structuring. Considering all of the results together, the contributions of spatial and environmental processes were stronger than biotic interactions in the small-scale structuring of a soil collembolan community.

A Methodology for Estimating Leaf Area Index by Assimilating Remote Sensing Data into Crop Model Based on Temporal and Spatial Knowledge

In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.

Obtaining vehicle parameters from bridge dynamic response:a combined semi-analytical and particle filtering approach

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.