Regular Sampling Method Research Articles

Spatially varying relationships between land-cover change and driving factors at multiple sampling scales

Modeling the relationships between environment, human activity, and natural conditions is very important for understanding human–environment interactions. This study aims at examining how these relationships vary over spatial sampling scales and investigating the spatially varying relationships between land-cover changes and driving factors, as well as the variations in the relationships at different sampling scales in the Tibetan Autonomous Prefecture of Qinghai Province, P.R. China. Regular sampling methods are used first to generate eight sets of data points at different scales, and then the values for land-cover changes and the factors are extracted for these data points. Geographically weighted regression (GWR) model is applied to analyze the relationships between land-cover changes and the factors at different sampling scales. The results indicate that the influences of the factors (e.g. the signs, significances, and values of coefficients) change greatly over different sampling scales; similarly, for different types of land-cover changes, the contributions of the factors also vary. Generally, roads, rivers, and lakes contribute greatly to land-cover changes, while villages, temples, and elevations contribute less. A possible reason is that the densities of roads, rivers, and lakes is much greater than those of villages and temples, and the populations in temples and villages are too small to have much effect on land-cover changes. The results demonstrate that the sampling scales have an important influence on the relationships between land-cover change and the factors.

Generalized Sturm-Liouville Problems and Chebychev Collocation Method

In this paper, we present an algorithm for approximating the eigenvalues of Sturm-Liouville problems with parameter-dependent boundary conditions. The algorithm is based on the Chebychev method. A few examples shall be presented to illustrate the proposed method and a comparison made with the regularized sampling method. It is shown that the Chebychev method yields better results.

Qualitative Land Suitability Evaluation for Main Irrigated Crops in the Shahrekord Plain, Iran: A Geostatistical Approach Compared with Conventional Method

The purity of soil map units and their quality for various uses like land suitability evaluation are always questioned. The main objective of this study was to compare the precision of qualitative land suitability classification based on geostatistical and conventional soil mapping methods for main irrigated crops in the Shahrekord Plain, Central Iran. A regular grid sampling method consisting 104 sample points was designed and soil samples were collected. Ordinary kriged maps were achieved for all studied soil attributes after physico-chemical analyses. Afterward, to combine kriged maps and ecological requirements of the studied crops, a script was designed in ILWIS 3.4 software and consequently, kriged qualitative land suitability maps were generated. Conventional qualitative land suitability was also mapped based on the representative pedon analysis in each soil map unit. Finally, comparison of the conventional and kriged maps was carried out using the statistical method, error matrix. The results showed that the overall accuracies of wheat, sugar beet, potato and alfalfa maps were 39.8%, 24.3%, 18.7% and 18.6% at subclass category, respectively, whereas these values increased to 80.9%, 82.3%, 23.7% and 82.3% at class level, respectively. Hence, it can be stated that thanks to the relative facility of conventional soil survey compared with geostatistical methods, this method can be expressed as a preferable way for handling a usual land suitability evaluation design; but using soil map units as land suitability delineations may lead to unsatisfactory results in estimation of quantity and type of existing limitations.

Assessment of women's awareness level about symptoms and complications of menopause and methods to their prevention

Context: Since menopause age is constant, an increase in life expectancy has resulted in an increase of the menopause period in women. Aims: This study was done to assess women's awareness level about symptoms and complications of menopause and methods of their prevention. Settings and design: This cross-sectional research was conducted on 220 women, 40 years of age or older referrals in selected health care centers. Methods and material: The research was conducted using a questionnaire with regular random sampling method. Statistical analysis used: The analysis of obtained findings was done by SPSS statistical software and statistical tests. Results: Based on their total score, 48.6% of women had good awareness, 24.1% of them had average awareness, and 27.3% of them had low awareness. Eighty-five percent of the participants had read or heard some topics about menopause from their relatives (26.8%), friends (25.5%), health care staffs (20%), books and journals (10.5%), and television or radio (8.6%). Women's awareness level had significant correlation with child number, job, education, income, hearing or reading text about menopause and their informational source, but awareness did not have significant correlation with age and being menopausal. Conclusions: Based on the findings of this study, the rate of participants' correct answers was lower than 50%. Key message: It is suggested to enhance women's awareness level through all sources including television, radio, journals, newspaper and medical staffs, since education is the most important tool in any prevention programs.

Matrix Converter Based on Asymmetric Regular Sampling Method SPWM Control Strategy

In this paper, the Matrix converter can be viewed as AC-DC-AC converter, the asymmetric regular sampling method SPWM control technique is applied in the control of matrix converter, the asymmetric regular sampling method SPWM control strategy of matrix converter, 48 allowed switch combinations and Four-Step Current Commutation method is presented. Based on Matlab/simulink the simulation of the matrix converter with such strategy is carried out. Inductive load simulation is carried out on the matrix converter prototype. The simulation results verify the workability of the asymmetric regular sampling method SPWM strategy for matrix converter.

On the computation of the eigenvalues of Dirac systems

The main purpose of this paper is to compute the eigenvalues of Dirac systems using a regularized sampling method. The operator examined here is the massless Dirac operator on a finite interval. The problem with singular coefficients is not covered in the present analysis. But problems whose coefficients may involve finite jumps of discontinuities are involved. The regularized technique allows us to insert some parameters to the well known sinc method; strengthening the existing sinc technique and to avoid the aliasing error. Examples are presented to demonstrate the credibility of the method with graphs and numerical illustrations.

Study of variability of some map unit properties and incorporating FAO method and GIS techniques in land suitability evaluation for barley

The quality of soil maps depends on their ability to exhibit the soil variability. This study aims to investigate the soil spatial variability in S2 unit of a semi-detailed qualitative suitability map (1:50000 scale) for irrigated barley. Forty nine soil samples were collected in land unit 2.1 at 0-20 cm depth using regular network sampling method to determine the content of salinity (EC) , alkalinity (ESP), Caco3, pH, Organic Carbon (OC), Caso4, Sand, Silt and Clay parameters. The greatest variability observed in the OC (Coefficient of variation = 300) and Caso4 (Coefficient of variation=0.40) respectively. The obtained result showed that the incorporating of FAO method and GIS techniques in land suitability evaluation for barley gave lower estimate of land index and yield than FAO methods alone (Storie and Square Root methods). The better accordance between estimated yield potential and observed yield potential by Square RootKriging method revealed that it was more accurate than the conventional FAO methods alone. Keywords: Barley, Crop, Land, Soil properties, Spatial variability, Suitability map, Iran

Study of Variability of some Map Unit Properties and Incorporating FAO Method and GIS Techniques in Land Suitability Evaluation for Barley

The quality of soil maps depends on their ability to exhibit the soil variability. This study aims to investigate the soil spatial variability in S2 unit of a semi-detailed qualitative suitability map (1:50000 scale) for irrigated barley. Forty nine soil samples were collected in land unit 2.1 at 0-20 cm depth using regular network sampling method to determine the content of salinity (EC) , alkalinity (ESP), CaCO 3 , pH, Organic Carbon (OC), CaSO 4 , Sand, Silt and Clay parameters. The greatest variability observed in the OC (Coefficient of variation = 300) and Caso 4 (Coefficient of variation=0.40) respectively. The obtained result showed that the incorporating of FAO method and GIS techniques in land suitability evaluation for barley gave lower estimate of land index and yield than FAO methods alone (Storie and Square Root methods). The better accordance between estimated yield potential and observed yield potential by Square Root- Kriging method revealed that it was more accurate than the conventional FAO methods alone.

The Design and Implementation of Three-Phase SPWM Based on DSP

This paper discusses the principle of SPWM, as well as its mathematical models, highlight introduce the generation principle of SPWM wave based on TI digital signal processor TMS320LF2407A. The formula and mathematical model are simplified by using the symmetric regular sampling method. Update the value of the program by comparing the look-up table, this method improves the operational efficiency, and reduces the error generation. The paper detailed analysis the configuration of each register in event manager module, and gives a critical interrupt subroutine. Through online simulation debugging, get the correct SPWM and the corresponding dead-time waveform.

Image quality for diffraction tomography, holographic backpropagation, and regularized sampling with noisy data

We consider the behaviour of inverse image reconstruction quality as a function of forward data SNR. A canonical scatterer geometry is used to obtain an analytical image contrast ratio estimate for Colton–Kirsch regularized sampling. For holographic backpropagation tomography, an estimate is developed for the SNR at which the image contrast ratio transitions from noise-dominated to the noise-free contrast ratio limit. Numerical results confirm the theoretical analyses and extend the results to more complex geometries. Holographic backpropagation exhibits the greatest noise immunity in the sense that the reconstructed image contrast ratio reaches an acceptable threshold at a lower SNR than is the case for standard diffraction tomography or the regularized sampling method.

Regularized Sampling of Multiband Signals

This paper presents a regularized sampling method for multiband signals, that makes it possible to approach the Landau limit, while keeping the sensitivity to noise at a low level. The method is based on band-limited windowing, followed by trigonometric approximation in consecutive time intervals. The key point is that the trigonometric approximation "inherits" the multiband property, that is, its coefficients are formed by bursts of non-zero elements corresponding to the multiband components. It is shown that this method can be well combined with the recently proposed synchronous multi-rate sampling (SMRS) scheme, given that the resulting linear system is sparse and formed by ones and zeroes. The proposed method allows one to trade sampling efficiency for noise sensitivity, and is specially well suited for bounded signals with unbounded energy like those in communications, navigation, audio systems, etc. Besides, it is also applicable to finite energy signals and periodic band-limited signals (trigonometric polynomials). The paper includes a subspace method for blindly estimating the support of the multiband signal as well as its components, and the results are validated through several numerical examples.

Sturm–Liouville problems with impulse effects

This paper deals with the computation of the eigenvalues of Sturm–Liouville problems with several discontinuity conditions inside a finite interval and parameter dependent boundary conditions using the regularized sampling method. A few examples are worked out by computing several eigenvalues and their corresponding eigenfunctions.

Eigenvalues of Sturm–Liouville problems with discontinuity conditions inside a finite interval

In this work, we use the regularized sampling method to compute the eigenvalues of Sturm–Liouville problems with discontinuity conditions inside a finite interval. We work out an example by computing a few eigenvalues and their corresponding eigenfunctions.

Computing the eigenvalues of singular Sturm–Liouville problems using the regularized sampling method

This paper deals with singular Sturm–Liouville problems. We shall extend the domain of application of the regularized sampling method, a method to compute the eigenvalues. A few numerical examples will be presented to illustrate the merit of the method.

Computing the spectrum of non-self-adjoint Sturm–Liouville problems with parameter-dependent boundary conditions

This paper deals with the computation of the eigenvalues of non-self-adjoint Sturm–Liouville problems with parameter-dependent boundary conditions using the regularized sampling method. A few numerical examples among which singular ones will be presented to illustrate the merit of the method and comparison made with the exact eigenvalues when they are available.

Computation of the eigenvalues of Sturm-Liouville problems with parameter dependent boundary conditions using the regularized sampling method

The purpose in this paper is to compute the eigenvalues of Sturm-Liouville problems with quite general separated boundary conditions nonlinear in the eigenvalue parameter using the regularized sampling method, an improvement on the method based on Shannon sampling theory, which does not involve any multiple integration and provides higher order estimates of the eigenvalues at a very low cost. A few examples shall be presented to illustrate the power of the method and a comparison made with the the exact eigenvalues obtained as squares of the zeros of the exact characteristic functions.

Optimal sampling of Gabor features for face recognition

The Gabor feature is effective for facial image representation, while linear discriminant analysis (LDA) can extract the most discriminant information from the Gabor feature for face recognition. In practice, the dimension of a Gabor feature vector is so high that the computation and memory requirements are prohibitively large. To reduce the dimension, one simple scheme is to extract the Gabor feature at sub-sampled positions, usually in a regular grid, in a face region. However, this scheme is not effective enough and degrades the recognition performance. In this paper, we propose a method to determine the optimal position for extracting the Gabor feature such that the number of feature points is as small as possible while the representation capability of the points is as high as possible. The sub-sampled positions of the feature points are determined by a mask generated from a set of training images by means of principal component analysis (PCA). With the feature vector of reduced dimension, a subspace LDA is applied for face recognition, i.e., PCA is first used to reduce the dimension of the Gabor feature vectors generated from the sub-sampled positions, and then a common LDA is applied. Experimental results show that the new sampling method is simple, and effective for both dimension reduction and image representation. The recognition rate based on our proposed scheme is also higher than that achieved using a regular sampling method in a face region.

Locating the support of objects contained in a two-layered background medium in two dimensions

In this paper the inverse problem of determining the boundaries of bounded objects buried in a two-layered medium using the regularized sampling method is considered. The objects are taken to be either impenetrable obstacles or penetrable anisotropic scatterers and contained in the absorbing layer of a two-layered medium. Measurements of the scattered field are restricted to the layer not containing the scatterer.

A Regularized Sampling Method for Solving Three-Dimensional Inverse Scattering Problems

The inverse scattering problem under consideration is to determine the shape of an obstacle in $\RE^3$ from a knowledge of the time harmonic incident acoustic wave and the far field pattern of the scattered wave with frequency in the resonance region. A method for solving this nonlinear and improperly posed problem is presented which is based on solving a linear integral equation of the first kind and avoids the use of nonlinear optimization methods. Numerical examples are given showing the practicality of this new approach.

The resonance self-shielding calculation with regularized random ladders

In the last four years several papers have been published on the calculation of resonance self-shielding (Hwang, 1984; Munoz-Cobos et al., 1982; Sinitsa, 1983; Takano et al., 1980), and an international exercise organized under the auspices of the NEA is going on. Hereafter we shall restrict ourselves to the treatment of the unresolved energy range with the narrow resonance approximation. The straightforward method is to generate one or several resonance ladders, and to process them as resolved resonances. The main drawback of Monte Carlo methods, used to generate the ladders, is the difficulty of reducing the dispersion of data and results. Several methods have been suggested, that we examine, and we strongly recommend one of them. We consider in more detail how this method (a regularized sampling method) improves the accuracy. Analytical methods to compute the effective cross-section have recently appeared: they are basically exempt from dispersion, but are inevitably approximate. We check the accuracy of the most sophisticated one. There is a neutron energy range which is improperly considered as statistical: we examine what happens when it is treated as statistical, and how it is possible to improve the accuracy of calculations in this range. The present renewal of interest by reactor physicists in self-shielding results from the improvement of computer techniques, while it was realized that self-shielding factors may differ by 5–8%, even for important nuclei. They would be happy to reduce this error to 0.5%; we propose less as a long-term goal (10 −3 for systematic errors), and then, within this paper, we will denote attention to differences greater than 10 −4. To illustrate the results we have performed calculations in a simple case: nucleus 238U, at 300 K, between 4250 and 4750 eV, with ENDF-B 4 average parameters: D ̄ = 19.98 eV , \\ ̄ gG o n = 0.0020979 eV and Γ y = 0.0235 eV. More results are given in a previous report (Ribon et al., 1985).