Near-surface geological defects pose a serious threat to human life and infrastructure.Hence,the exploration of geological hazards is essential.Currently,there are various geological hazard exploration methods;however...Near-surface geological defects pose a serious threat to human life and infrastructure.Hence,the exploration of geological hazards is essential.Currently,there are various geological hazard exploration methods;however,those require improvements in terms of economic feasibility,convenience,and lateral resolution.To address this,this study examined an extraction method to determine spatial autocorrelation velocity dispersion curves for application in near-surface exploration.展开更多
We present a new global model of collinear autocorrelation based on second harmonic generation nonlinearity.The model is rigorously derived from the nonlinear coupled wave equation specific to the autocorrelation meas...We present a new global model of collinear autocorrelation based on second harmonic generation nonlinearity.The model is rigorously derived from the nonlinear coupled wave equation specific to the autocorrelation measurement configuration,without requiring a specific form of the incident pulse function.A rigorous solution of the nonlinear coupled wave equation is obtained in the time domain and expressed in a general analytical form.The global model fully accounts for the nonlinear interaction and propagation effects within nonlinear crystals,which are not captured by the classical local model.To assess the performance of the global model compared to the classic local model,we investigate the autocorrelation signals obtained from both models for different incident pulse waveforms and different full-widthes at half-maximum(FWHMs).When the incident pulse waveform is Lorentzian with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 399.9 fs,while the classic local model predicts an FWHM of 331.4 fs.The difference between the two models is 68.6 fs,corresponding to an error of 17.2%.Similarly,for a sech-type incident pulse with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 343.9 fs,while the local model predicts an FWHM of 308.8 fs.The difference between the two models is 35.1 fs,with an error of 10.2%.We further examine the behavior of the models for Lorentzian pulses with FWHMs of 100 fs,200 fs and 500 fs.The differences between the global and local models are 17.1 fs,68.6 fs and 86.0 fs,respectively,with errors approximately around 17%.These comparative analyses clearly demonstrate the superior accuracy of the global model in intensity autocorrelation modeling.展开更多
Secret key generation(SKG)is a promising solution to the problem of wireless communications security.As the first step of SKG,channel probing affects it significantly.Although there have been some probing schemes,ther...Secret key generation(SKG)is a promising solution to the problem of wireless communications security.As the first step of SKG,channel probing affects it significantly.Although there have been some probing schemes,there is a lack of research on the optimization of the probing process.This study investigates how to optimize correlated parameters to maximize the SKG rate(SKGR)in the time-division duplex(TDD)mode.First,we build a probing model which includes the effects of transmitting power,the probing period,and the dimension of sample vectors.Based on the model,the analytical expression of the SKGR is given.Next,we formulate an optimization problem for maximizing the SKGR and give an algorithm to solve it.We conclude the SKGR monotonically increases as the transmitting power increases.Relevant mathematical proofs are given in this study.From the simulation results,increasing appropriately the probing period and the dimension of the sample vector could increase the SKGR dramatically compared to a yardstick,which indicates the importance of optimizing the parameters related to the channel probing phase.展开更多
To overcome the shortcomings of the single-shot autocorrelation SSA where only one pulse width is obtained when the SSA is applied to measure the pulse width of ultrashort laser pulses a modified SSA for measuring the...To overcome the shortcomings of the single-shot autocorrelation SSA where only one pulse width is obtained when the SSA is applied to measure the pulse width of ultrashort laser pulses a modified SSA for measuring the spatiotemporal characteristics of ultrashort laser pulses at different spatial positions is proposed. The spatiotemporal characteristics of femtosecond laser pulses output from the Ti sapphire regenerative amplifier system are experimentally measured by the proposed method. It was found that the complex spatial characteristics are measured accurately.The pulse widths at different spatial positions are various which obey the Gaussian distribution.The pulse width at the same spatial position becomes narrow with the increase in input average power when femtosecond laser pulses pass through a carbon disulfide CS2 nonlinear medium.The experimental results verify that the proposed method is valid for measuring the spatiotemporal characteristics of ultrashort laser pulses at different spatial positions.展开更多
Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information syst...Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.展开更多
Relationship between vegetation and environmental factors has always been a major topic in ecology, but it has also been an important way to reveal vegetation＇s dynamic response to and feedback effects on climate cha...Relationship between vegetation and environmental factors has always been a major topic in ecology, but it has also been an important way to reveal vegetation＇s dynamic response to and feedback effects on climate change. For the special geographical location and climatic characteristics of the Qaidam Basin, with the support of traditional and remote sensing data, in this paper a vegetation coverage model was established. The quantitative prediction of vegetation coverage by five environmental factors was initially realized through multiple stepwise regression （MSR） models. However, there is significant multicollinearity among these five environmental factors, which reduces the performance of the MSR model. Then through the introduction of the Moran Index, an indicator that reflects the spatial autocorrelation of vegetation distribution, only two variables of average annual rainfall and local Moran Index were used in the final establishment of the vegetation coverage model. The results show that there is significant spatial autocorrelation in the distribution of vegetation. The role of spatial autocorrelation in the establishment of vegetation coverage model has not only improved the model fitting R2 from 0.608 to 0.656, but also removed the multicollinearity among independents.展开更多
This paper uses a spatial statistics method based on the calculation of spatial autocorrelation as a possible approach for modeling and quantifying the distribution of urban land price in Changzhou City, Jiangsu Provi...This paper uses a spatial statistics method based on the calculation of spatial autocorrelation as a possible approach for modeling and quantifying the distribution of urban land price in Changzhou City, Jiangsu Province. GIS and spatial statistics provide a useful way for describing the distribution of urban land price both spatially and temporally, and have proved to be useful for understanding land price distribution pattern better. In this paper, we apply the statistical analysis method to 8379 urban land price samples collected from Changzhou Land Market, and it is turned out that the proposed approach can effectively identify the spatial clusters and local point patterns in dataset and forms a general method for conceptualizing the land price structure. The results show that land price structure in Changzhou City is very complex and that even where there is a high spatial autocorrelation, the land price is still relatively heterogeneous. Furthermore, lands for different uses have different degrees of spatial autocorrelation. Spatial autocorrelation of commercial lands is more intense than that of residential and industrial lands in regional central district. This means that treating land price as integration of homogeneous units can limit analysis of pattern, over-simplifying the structure of land price, but the methods, just as the autocorrelation approaches, are useful tools for quantifying the variables of land price.展开更多
Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently so...Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently some methods of exploratory spatial data analysis such as spatial autocorrelation have provided effective tools to analyze spatial agglomeration and cluster, which can reveal the pattern of regional inequality. This article attempts to use spatial autocorrelation at county level to get refined spatial pattern of regional disparity in Chinese northeast economic region over 2000-2006 (2001 absent). The result indicates that the basic trend of regional economy is an increasing concentration of growth among counties in northeast economic region, and there are two geographical clusters of poorer counties including the counties in western Liaoning Province and adjacent counties in Inner Mongolia, poorer counties of Heihe, Qiqihar and Suihua in Heilongjiang Province. This article also reveals that we can use the methods of exploratory spatial data analysis as the supplementary analysis methods in regional economic analysis.展开更多
This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of li...This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of linear frequency modulation, phase code, and frequency code. Firstly, it improves the coherent integration of LPI radar signals by adding the periodicity of the ambiguity function. Then, it develops a frequency domain detection method based on fast Fourier transform (FFT) and segmented autocorrelation function to detect signals without features of linear frequency modulation by virtue of the distribution characteristics of noise signals in the frequency domain. Finally, this paper gives a verification of the performance of the method for different signal-to-noise ratios by conducting simulation experiments, and compares the method with existing ones. Additionally, this method is characterized by the straightforward calculation and high real-time performance, which is conducive to better detecting all kinds of LPI radar signals.展开更多
This study focuses on spatial autocorrelation and the spatial distribution of urban land prices from a regional perspective.Taking Hubei province,China,as a case study area,spatial autocorrelation degree,spatial autoc...This study focuses on spatial autocorrelation and the spatial distribution of urban land prices from a regional perspective.Taking Hubei province,China,as a case study area,spatial autocorrelation degree,spatial autocorrelation pattern,and the mechanism of its formation were discussed.The study employs Moran’s I,local Moran’s I,and Moran’s I correlogram to analyze spatial autocorrelation degree and its change along with contiguity order.Some local clustering hot spots are found.This paper uses semi-variance statistic for land price based on route distance to find the spatial autocorrelation scale.We also adopt spatial clustering based on a kind of composite distance to probe into the clustering characteristic of land prices.By Moran’s I and Moran’s I correlogram,we find that datum price of the cities in Hubei province has faint spatial autocorrelation degree at the first and the second-order contiguity.Spatial variance hints that the scale of the autocorrelation is about 200 km in route distance.Spatial clustering result indicates that the spatial distribution of city land price is a kind of hierarchy structure similar to administrative regions.From principal factors analysis and stepwise linear regression,we find that the value added of city secondary and tertiary industry and the urban population are two of the most influential factors to urban datum land price.The value added of city secondary and tertiary industry has higher spatial autocorrelation than urban datum land price and has a bigger autocorrelation scale.But urban population has little spatial autocorrelation.It can be inferred that the spatial autocorrelation of urban land price is mainly caused by economic spatial autocorrelation.But its spatial autocorrelation degree is lower than economic factors because urban datum land price is also influenced by other special local factors,such as population,city infrastructure,land supply,etc.展开更多
Let p,q be distinct primes with gcd（p-1,q-1） = 4.In this paper,we calculate the autocorrelation values of binary sequences of generalized cyclotomic sets of order four in Z pq and get conditions of p and q such that...Let p,q be distinct primes with gcd（p-1,q-1） = 4.In this paper,we calculate the autocorrelation values of binary sequences of generalized cyclotomic sets of order four in Z pq and get conditions of p and q such that they are four-valued.展开更多
Massive spatio-temporal big data about human mobility have become increasingly available.Revealing underlying dynamic patterns from these data is essential for understanding people’s behavior and urban deployment.Spa...Massive spatio-temporal big data about human mobility have become increasingly available.Revealing underlying dynamic patterns from these data is essential for understanding people’s behavior and urban deployment.Spatio-temporal autocorrelation analysis is an exploratory approach to recognizing data distribution in space and time.The most widely used spatial autocorrelation measurements,such as Moran’s I and local indicators of spatial association(LISA),only apply to static data,so are powerless to spatio-temporal big data about human mobility.Thus,we proposed a new method by extending Moran’s I to measure the spatial autocorrelation of time series data.Then the method was applied to taxi ride data in Beijing,China to reveal the spatial pattern of collective human mobility.The result shows that there is strong positive spatio-temporal autocorrelation within the 5th Ring Road,weak negative spatio-temporal autocorrelation nearby the Sixth Ring Road,and almost no spatiotemporal autocorrelation between the roads.Local spatial patterns of taxi travel were also recognized.This method is useful for discovering underlying patterns from spatio-temporal big data to understand human mobility.展开更多
According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Ma...According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.展开更多
Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is of...Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.展开更多
A nonlinear analysis of urban evolution is made by using of spatial autocorrelation theory. A first-order nonlinear autoregression model based on Clark’s negative exponential model is proposed to show urban populatio...A nonlinear analysis of urban evolution is made by using of spatial autocorrelation theory. A first-order nonlinear autoregression model based on Clark’s negative exponential model is proposed to show urban population density. The new method and model are applied to Hangzhou City, China, as an example. The average distance of population activities, the auto-correlation coefficient of urban population density, and the auto-regressive function values all show trends of gradual increase from 1964 to 2000, but there always is a sharp first-order cutoff in the partial auto- correlations. These results indicate that urban development is a process of localization. The discovery of urban locality is significant to improve the cellular-automata-based urban simulation of modeling spatial complexity.展开更多
Laser speckle imaging has been widely used for in-vivo visualization of blood perfusion in biological tissues.However,existing laser speckle imaging techniques suffer from limited quantification accuracy and spatial r...Laser speckle imaging has been widely used for in-vivo visualization of blood perfusion in biological tissues.However,existing laser speckle imaging techniques suffer from limited quantification accuracy and spatial resolution.Here we re-port a novel design and implementation of a powerful laser speckle imaging platform to solve the two critical limitations.The core technique of our platform is a combination of line scan confocal microscopy with laser speckle autocorrelation imaging,which is termed Line Scan Laser Speckle Autocorrelation Imaging(LS-LSAI).The technical advantages of LS-LSAI include high spatial resolution(~4.4μm)for visualizing and quantifying blood flow in microvessels,as well as video-rate imaging speed for tracing dynamic flow.展开更多
In order to measure the axial flowing velocity of carbon particle suspension with particle diameter of tens of micrometers, the photoacoustic Doppler(PAD) frequency shift is calculated based on a series of individual ...In order to measure the axial flowing velocity of carbon particle suspension with particle diameter of tens of micrometers, the photoacoustic Doppler(PAD) frequency shift is calculated based on a series of individual A scans using an autocorrelation method. A 532 nm pulsed laser with repetition rate of 20 Hz is used as a pumping source to generate photoacoustic signal. The photoacoustic signals are detected using a focused piezoelectric(PZT) ultrasound transducer with central frequency of 5 MHz. The suspension of carbon particles is driven by a syringe pump. The complex photoacoustic signal is calculated by the Hilbert transformation from time-domain photoacoustic signal, and then it is autocorrelated to calculate the Doppler frequency shift. The photoacoustic Doppler frequency shift is calculated by averaging the autocorrelation results of some individual A scans. The advantage of the autocorrelation method is that the time delay in autocorrelation can be defined by user, and the requirement of high pulse repetition rate is avoided. The feasibility of the proposed autocorrelation method is preliminarily demonstrated by quantifying the motion of a carbon particle suspension with flow velocity from 5 mm/s to 60 mm/s. The experimental results show that there is an approximately linear relation between the autocorrelation result and the setting velocity.展开更多
Considering the calculated result and higher degeneracy existing in the calculation of autocorrelation topological index totally depend on experimental parameters, a new group of autocorrelation topological index as ...Considering the calculated result and higher degeneracy existing in the calculation of autocorrelation topological index totally depend on experimental parameters, a new group of autocorrelation topological index as A t, B t, C t and D t was designed and developed based on the vertex degree of molecular topology and autocorrelation function of mathematics. Autocorrelation function f(i) was calculated from the square root of the vertex degree, revised vertex degree and their combination, and they are (δ i) 1/2 , (δ V i) 1/2 ,(δ V i+δ i) 1/2 and (δ E i-δ i) 1/2 / N. With the matrix description method achieved, and the unit input in matrix of unsaturated bond and heteroatoms revised based on the adjacency matrix and distance matrix of organic molecular graph, the corresponding computer software has also been designed and developed. Better results have been obtained for the application of these indexes in QSAR study of organic chemicals.展开更多
Cyclotomic sequences have good cryptographic properties and are closely related to difference sets.This paper proposes a new class of binary generalized cyclotomic sequences of order two and length pqr.Its linear comp...Cyclotomic sequences have good cryptographic properties and are closely related to difference sets.This paper proposes a new class of binary generalized cyclotomic sequences of order two and length pqr.Its linear complexity,minimal polynomial,and autocorrelation are investigated.The results show that these sequences have a large linear complexity when 2∈D1,which means they can resist the Berlekamp-Massey attack.Furthermore,the autocorrelation values are close to 0 with a probability of approximately 1?1/r.Therefore,when r is a big prime,the new sequence has a good autocorrelation.展开更多
Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation ...Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran＇s heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord Gi statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.展开更多
基金supported by the Henan Province science and technology research project(Grant No.242102321031)National Natural Science Foundation of China(grant numbers 42207200).
文摘Near-surface geological defects pose a serious threat to human life and infrastructure.Hence,the exploration of geological hazards is essential.Currently,there are various geological hazard exploration methods;however,those require improvements in terms of economic feasibility,convenience,and lateral resolution.To address this,this study examined an extraction method to determine spatial autocorrelation velocity dispersion curves for application in near-surface exploration.
基金Project supported by the Science and Technology Project of Guangdong(Grant No.2020B010190001)the National Natural Science Foundation of China(Grant No.11974119)+1 种基金the Guangdong Innovative and Entrepreneurial Research Team Program(Grant No.2016ZT06C594)the National Key R&D Program of China(Grant No.2018YFA0306200)。
文摘We present a new global model of collinear autocorrelation based on second harmonic generation nonlinearity.The model is rigorously derived from the nonlinear coupled wave equation specific to the autocorrelation measurement configuration,without requiring a specific form of the incident pulse function.A rigorous solution of the nonlinear coupled wave equation is obtained in the time domain and expressed in a general analytical form.The global model fully accounts for the nonlinear interaction and propagation effects within nonlinear crystals,which are not captured by the classical local model.To assess the performance of the global model compared to the classic local model,we investigate the autocorrelation signals obtained from both models for different incident pulse waveforms and different full-widthes at half-maximum(FWHMs).When the incident pulse waveform is Lorentzian with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 399.9 fs,while the classic local model predicts an FWHM of 331.4 fs.The difference between the two models is 68.6 fs,corresponding to an error of 17.2%.Similarly,for a sech-type incident pulse with an FWHM of 200 fs,the global model predicts an autocorrelation signal FWHM of 343.9 fs,while the local model predicts an FWHM of 308.8 fs.The difference between the two models is 35.1 fs,with an error of 10.2%.We further examine the behavior of the models for Lorentzian pulses with FWHMs of 100 fs,200 fs and 500 fs.The differences between the global and local models are 17.1 fs,68.6 fs and 86.0 fs,respectively,with errors approximately around 17%.These comparative analyses clearly demonstrate the superior accuracy of the global model in intensity autocorrelation modeling.
基金supported in part by the national natural science foundation of China (NSFC) under Grant61871193in part by the R&D Program of key science and technology fields in Guangdong province under Grant 2019B090912001in part by the Guangzhou Key Field R&D Program under Grant 202206030005
文摘Secret key generation(SKG)is a promising solution to the problem of wireless communications security.As the first step of SKG,channel probing affects it significantly.Although there have been some probing schemes,there is a lack of research on the optimization of the probing process.This study investigates how to optimize correlated parameters to maximize the SKG rate(SKGR)in the time-division duplex(TDD)mode.First,we build a probing model which includes the effects of transmitting power,the probing period,and the dimension of sample vectors.Based on the model,the analytical expression of the SKGR is given.Next,we formulate an optimization problem for maximizing the SKGR and give an algorithm to solve it.We conclude the SKGR monotonically increases as the transmitting power increases.Relevant mathematical proofs are given in this study.From the simulation results,increasing appropriately the probing period and the dimension of the sample vector could increase the SKGR dramatically compared to a yardstick,which indicates the importance of optimizing the parameters related to the channel probing phase.
基金The National Natural Science Foundation of China(No.61171081,No.61471164)the Natural Science Foundation of Hunan Province(No.14JJ6043)
文摘To overcome the shortcomings of the single-shot autocorrelation SSA where only one pulse width is obtained when the SSA is applied to measure the pulse width of ultrashort laser pulses a modified SSA for measuring the spatiotemporal characteristics of ultrashort laser pulses at different spatial positions is proposed. The spatiotemporal characteristics of femtosecond laser pulses output from the Ti sapphire regenerative amplifier system are experimentally measured by the proposed method. It was found that the complex spatial characteristics are measured accurately.The pulse widths at different spatial positions are various which obey the Gaussian distribution.The pulse width at the same spatial position becomes narrow with the increase in input average power when femtosecond laser pulses pass through a carbon disulfide CS2 nonlinear medium.The experimental results verify that the proposed method is valid for measuring the spatiotemporal characteristics of ultrashort laser pulses at different spatial positions.
基金financially supported by the National Natural Science Foundation of China (41471365,41531179)
文摘Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.
基金National Natural Science Foundation of China, No.90302009 Project of the Ministry of Water Resources of China, No.201101047
文摘Relationship between vegetation and environmental factors has always been a major topic in ecology, but it has also been an important way to reveal vegetation＇s dynamic response to and feedback effects on climate change. For the special geographical location and climatic characteristics of the Qaidam Basin, with the support of traditional and remote sensing data, in this paper a vegetation coverage model was established. The quantitative prediction of vegetation coverage by five environmental factors was initially realized through multiple stepwise regression （MSR） models. However, there is significant multicollinearity among these five environmental factors, which reduces the performance of the MSR model. Then through the introduction of the Moran Index, an indicator that reflects the spatial autocorrelation of vegetation distribution, only two variables of average annual rainfall and local Moran Index were used in the final establishment of the vegetation coverage model. The results show that there is significant spatial autocorrelation in the distribution of vegetation. The role of spatial autocorrelation in the establishment of vegetation coverage model has not only improved the model fitting R2 from 0.608 to 0.656, but also removed the multicollinearity among independents.
基金Under the auspices of the National Natural Science Foundation of China (No. 40371091), Land Monitoring Project ofthe Ministry of Land and Resources of P. R. China (No. 2005-6.1-6)
文摘This paper uses a spatial statistics method based on the calculation of spatial autocorrelation as a possible approach for modeling and quantifying the distribution of urban land price in Changzhou City, Jiangsu Province. GIS and spatial statistics provide a useful way for describing the distribution of urban land price both spatially and temporally, and have proved to be useful for understanding land price distribution pattern better. In this paper, we apply the statistical analysis method to 8379 urban land price samples collected from Changzhou Land Market, and it is turned out that the proposed approach can effectively identify the spatial clusters and local point patterns in dataset and forms a general method for conceptualizing the land price structure. The results show that land price structure in Changzhou City is very complex and that even where there is a high spatial autocorrelation, the land price is still relatively heterogeneous. Furthermore, lands for different uses have different degrees of spatial autocorrelation. Spatial autocorrelation of commercial lands is more intense than that of residential and industrial lands in regional central district. This means that treating land price as integration of homogeneous units can limit analysis of pattern, over-simplifying the structure of land price, but the methods, just as the autocorrelation approaches, are useful tools for quantifying the variables of land price.
基金supported by the National Natural Science Foundation for Distinguished Young Scholar of China (Grant No.40225004)
文摘Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently some methods of exploratory spatial data analysis such as spatial autocorrelation have provided effective tools to analyze spatial agglomeration and cluster, which can reveal the pattern of regional inequality. This article attempts to use spatial autocorrelation at county level to get refined spatial pattern of regional disparity in Chinese northeast economic region over 2000-2006 (2001 absent). The result indicates that the basic trend of regional economy is an increasing concentration of growth among counties in northeast economic region, and there are two geographical clusters of poorer counties including the counties in western Liaoning Province and adjacent counties in Inner Mongolia, poorer counties of Heihe, Qiqihar and Suihua in Heilongjiang Province. This article also reveals that we can use the methods of exploratory spatial data analysis as the supplementary analysis methods in regional economic analysis.
基金supported by the National Natural Science Foundation of China(61571462)Weapons and Equipment Exploration Research Project(7131464)
文摘This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of linear frequency modulation, phase code, and frequency code. Firstly, it improves the coherent integration of LPI radar signals by adding the periodicity of the ambiguity function. Then, it develops a frequency domain detection method based on fast Fourier transform (FFT) and segmented autocorrelation function to detect signals without features of linear frequency modulation by virtue of the distribution characteristics of noise signals in the frequency domain. Finally, this paper gives a verification of the performance of the method for different signal-to-noise ratios by conducting simulation experiments, and compares the method with existing ones. Additionally, this method is characterized by the straightforward calculation and high real-time performance, which is conducive to better detecting all kinds of LPI radar signals.
基金This research was funded by the National Natural Science Foundation of China(Nos.41171312 and 40901188).
文摘This study focuses on spatial autocorrelation and the spatial distribution of urban land prices from a regional perspective.Taking Hubei province,China,as a case study area,spatial autocorrelation degree,spatial autocorrelation pattern,and the mechanism of its formation were discussed.The study employs Moran’s I,local Moran’s I,and Moran’s I correlogram to analyze spatial autocorrelation degree and its change along with contiguity order.Some local clustering hot spots are found.This paper uses semi-variance statistic for land price based on route distance to find the spatial autocorrelation scale.We also adopt spatial clustering based on a kind of composite distance to probe into the clustering characteristic of land prices.By Moran’s I and Moran’s I correlogram,we find that datum price of the cities in Hubei province has faint spatial autocorrelation degree at the first and the second-order contiguity.Spatial variance hints that the scale of the autocorrelation is about 200 km in route distance.Spatial clustering result indicates that the spatial distribution of city land price is a kind of hierarchy structure similar to administrative regions.From principal factors analysis and stepwise linear regression,we find that the value added of city secondary and tertiary industry and the urban population are two of the most influential factors to urban datum land price.The value added of city secondary and tertiary industry has higher spatial autocorrelation than urban datum land price and has a bigger autocorrelation scale.But urban population has little spatial autocorrelation.It can be inferred that the spatial autocorrelation of urban land price is mainly caused by economic spatial autocorrelation.But its spatial autocorrelation degree is lower than economic factors because urban datum land price is also influenced by other special local factors,such as population,city infrastructure,land supply,etc.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 107711001097125011171150)
文摘Let p,q be distinct primes with gcd（p-1,q-1） = 4.In this paper,we calculate the autocorrelation values of binary sequences of generalized cyclotomic sets of order four in Z pq and get conditions of p and q such that they are four-valued.
基金This work is funded by the National Natural Science Foundation of China[grant numbers 41830645 and 41625003].
文摘Massive spatio-temporal big data about human mobility have become increasingly available.Revealing underlying dynamic patterns from these data is essential for understanding people’s behavior and urban deployment.Spatio-temporal autocorrelation analysis is an exploratory approach to recognizing data distribution in space and time.The most widely used spatial autocorrelation measurements,such as Moran’s I and local indicators of spatial association(LISA),only apply to static data,so are powerless to spatio-temporal big data about human mobility.Thus,we proposed a new method by extending Moran’s I to measure the spatial autocorrelation of time series data.Then the method was applied to taxi ride data in Beijing,China to reveal the spatial pattern of collective human mobility.The result shows that there is strong positive spatio-temporal autocorrelation within the 5th Ring Road,weak negative spatio-temporal autocorrelation nearby the Sixth Ring Road,and almost no spatiotemporal autocorrelation between the roads.Local spatial patterns of taxi travel were also recognized.This method is useful for discovering underlying patterns from spatio-temporal big data to understand human mobility.
基金Under the auspices of Major Special Technological Program of Water Pollution Control and Management (No.2009ZX07106-001)National Natural Science Foundation of China (No. 51079037, 50909063)
文摘According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA092303)the Public Science and Technology Research Funds Projects of Ocean(No.20155014)+2 种基金the Shanghai Leading Academic Discipline Projectthe Funding Program for Outstanding Dissertation in Shanghai Ocean UniversitySupported by SHOU International Center for Marine Studies and Shanghai 1000 Talent Program
文摘Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.
基金Under the auspices of the National Natural Science Foundation of China (No. 40371039)
文摘A nonlinear analysis of urban evolution is made by using of spatial autocorrelation theory. A first-order nonlinear autoregression model based on Clark’s negative exponential model is proposed to show urban population density. The new method and model are applied to Hangzhou City, China, as an example. The average distance of population activities, the auto-correlation coefficient of urban population density, and the auto-regressive function values all show trends of gradual increase from 1964 to 2000, but there always is a sharp first-order cutoff in the partial auto- correlations. These results indicate that urban development is a process of localization. The discovery of urban locality is significant to improve the cellular-automata-based urban simulation of modeling spatial complexity.
基金supports from Ministry of Education-Singapore(MOE2019-T2-2-094,R-397-000-327-114).
文摘Laser speckle imaging has been widely used for in-vivo visualization of blood perfusion in biological tissues.However,existing laser speckle imaging techniques suffer from limited quantification accuracy and spatial resolution.Here we re-port a novel design and implementation of a powerful laser speckle imaging platform to solve the two critical limitations.The core technique of our platform is a combination of line scan confocal microscopy with laser speckle autocorrelation imaging,which is termed Line Scan Laser Speckle Autocorrelation Imaging(LS-LSAI).The technical advantages of LS-LSAI include high spatial resolution(~4.4μm)for visualizing and quantifying blood flow in microvessels,as well as video-rate imaging speed for tracing dynamic flow.
基金supported by the Joint Funds of the National Natural Science Foundation of China(No.U1204612)Natural Science Foundation of He’nan Educational Committee(No.13A416180)
文摘In order to measure the axial flowing velocity of carbon particle suspension with particle diameter of tens of micrometers, the photoacoustic Doppler(PAD) frequency shift is calculated based on a series of individual A scans using an autocorrelation method. A 532 nm pulsed laser with repetition rate of 20 Hz is used as a pumping source to generate photoacoustic signal. The photoacoustic signals are detected using a focused piezoelectric(PZT) ultrasound transducer with central frequency of 5 MHz. The suspension of carbon particles is driven by a syringe pump. The complex photoacoustic signal is calculated by the Hilbert transformation from time-domain photoacoustic signal, and then it is autocorrelated to calculate the Doppler frequency shift. The photoacoustic Doppler frequency shift is calculated by averaging the autocorrelation results of some individual A scans. The advantage of the autocorrelation method is that the time delay in autocorrelation can be defined by user, and the requirement of high pulse repetition rate is avoided. The feasibility of the proposed autocorrelation method is preliminarily demonstrated by quantifying the motion of a carbon particle suspension with flow velocity from 5 mm/s to 60 mm/s. The experimental results show that there is an approximately linear relation between the autocorrelation result and the setting velocity.
文摘Considering the calculated result and higher degeneracy existing in the calculation of autocorrelation topological index totally depend on experimental parameters, a new group of autocorrelation topological index as A t, B t, C t and D t was designed and developed based on the vertex degree of molecular topology and autocorrelation function of mathematics. Autocorrelation function f(i) was calculated from the square root of the vertex degree, revised vertex degree and their combination, and they are (δ i) 1/2 , (δ V i) 1/2 ,(δ V i+δ i) 1/2 and (δ E i-δ i) 1/2 / N. With the matrix description method achieved, and the unit input in matrix of unsaturated bond and heteroatoms revised based on the adjacency matrix and distance matrix of organic molecular graph, the corresponding computer software has also been designed and developed. Better results have been obtained for the application of these indexes in QSAR study of organic chemicals.
基金supported by the National Key Research and Development Program of China(2016YFB0800601)the Natural Science Foundation of China(61303217+3 种基金61502372)the Fundamental Research Funds for the Central Universities(JB140115)the Natural Science Foundation of Shaanxi Province(2013JQ80022014JQ8313)
文摘Cyclotomic sequences have good cryptographic properties and are closely related to difference sets.This paper proposes a new class of binary generalized cyclotomic sequences of order two and length pqr.Its linear complexity,minimal polynomial,and autocorrelation are investigated.The results show that these sequences have a large linear complexity when 2∈D1,which means they can resist the Berlekamp-Massey attack.Furthermore,the autocorrelation values are close to 0 with a probability of approximately 1?1/r.Therefore,when r is a big prime,the new sequence has a good autocorrelation.
文摘Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran＇s heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord Gi statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.
