• Journal of the Korean Data and Information Science Society
• /
• v.18 no.4
• /
• pp.1145-1155
• /
• 2007

In this paper, we consider the permutation tests for the multivariate data under the two-sample problem setting. We review some testing procedures, which are parametric and nonparametric and compare them with the permutation ones. Then we consider to try to apply the permutation tests to the multivariate data having the continuous and discrete components together by choosing some suitable combining function through the partial testing. Finally we discuss more aspects for the permutation tests as concluding remarks.

• Women's Health Nursing
• /
• v.30 no.1
• /
• pp.9-17
• /
• 2024

• Environmental and Resource Economics Review
• /
• v.23 no.3
• /
• pp.409-434
• /
• 2014

This paper estimates household demand for electricity using a micro-level household expenditure data set. A two-stage estimation method where the endogenous block price estimates are obtained from a discrete block choice model is used. This method successfully identifies a downward sloping conditional demand function with the data, while both the usual two-stage method with instrumental variable estimation and the Hewitt-Hanemann discrete-continuous model fail to do that. The paper simulates the impacts of two hypothetical pricing reforms that reduce the number of blocks and make the price gap smaller. It is shown that the reform may increase the overall consumer benefit, but is regressive.

• Journal of Wetlands Research
• /
• v.21 no.4
• /
• pp.365-373
• /
• 2019

In this study, we investigated the effect of wave height in coastal areas using discrete wavelet transform in Taehwa river basin in Ulsan. Through the decomposition result of tide data using daubechies level 7 wavelet and Curve Fitting Function, we confirmed that detail components of d₃ and d₄ were semidiurnal and diurnal components and approximation component(a₆) was the long period of lunar fortnight constituent. The decomposed tide data in six level was divided into tide component with periodicity and wave component with non-periodicity using autocorrelation function and fourier transform. Finally, we confirmed that the tide component is consisted 66% and wave component is consisted 34%. So, we quantitatively assessed the effect of wave on coastal areas. The result could be used for coastal flood risk management considering the effect of wave.

• Journal of Biosystems Engineering
• /
• v.38 no.1
• /
• pp.48-54
• /
• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.

• Computers and Concrete
• /
• v.28 no.5
• /
• pp.521-532
• /
• 2021

Present paper focuses on the modeling of size effect on the compressive strength of normal concrete with the application of Discrete Element Method (DEM). Test specimens with different size and shape were cast and uniaxial compressive strength test was performed on each sample. Five different concrete mixes were used, all belonging to a different normal strength concrete class (C20/25, C30/37, C35/45, C45/55, and C50/60). The numerical simulations were carried out by using the PFC 5 software, which applies rigid spheres and contacts between them to model the material. DEM modeling of size effect could be advantageous because the development of micro-cracks in the material can be observed and the failure mode can be visualized. The series of experiments were repeated with the model after calibration. The relationship of the parallel bond strength of the contacts and the laboratory compressive strength test was analyzed by aiming to determine a relation between the compressive strength and the bond strength of different sized models. An equation was derived based on Bazant's size effect law to estimate the parallel bond strength of differently sized specimens. The parameters of the equation were optimized based on measurement data using nonlinear least-squares method with SSE (sum of squared errors) objective function. The laboratory test results showed a good agreement with the literature data (compressive strength is decreasing with the increase of the size of the specimen regardless of the shape). The derived estimation models showed strong correlation with the measurement data. The results indicated that the size effect is stronger on concretes with lower strength class due to the higher level of inhomogeneity of the material. It was observed that size effect is more significant on cube specimens than on cylinder samples, which can be caused by the side ratios of the specimens and the size of the purely compressed zone. A limit value for the minimum size of DE model for cubes and cylinder was determined, above which the size effect on compressive strength can be neglected within the investigated size range. The relationship of model size (particle number) and computational time was analyzed and a method to decrease the computational time (number of iterations) of material genesis is proposed.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1407-1419
• /
• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of Aerospace System Engineering
• /
• v.16 no.6
• /
• pp.1-7
• /
• 2022

A simulated radar terrain scan data generation method is employed for terrain following. This method scans the discrete terrain by sequentially radiating beams from the radar to the desired scan area with the same azimuth but varying elevation angles. The terrain data collected from the beam is integrated to generate the simulated radar terrain scan data, which comprises radar-detected points. However, these points can be located far from the beam centerline when the radar is far from them due to beam divergence. This paper proposes a geometry-based terrain scan data generation method for analysing simulated radar terrain scan data. The method involves detecting geometric points along the beam centerline, which forms the geometry-based terrain scan data. The analysis of the simulated radar terrain scan data utilising this method confirms that the beam width effects are accounted for in the results.

• Communications for Statistical Applications and Methods
• /
• v.21 no.4
• /
• pp.349-361
• /
• 2014

This paper compares of lasso type estimators in various high-dimensional data situations with sparse parameters. Lasso, adaptive lasso, fused lasso and elastic net as lasso type estimators and ridge estimator are compared via simulation in linear models with correlated and uncorrelated covariates and binary regression models with correlated covariates and discrete covariates. Each method is shown to have advantages with different penalty conditions according to sparsity patterns of regression parameters. We applied the lasso type methods to Arabidopsis microarray gene expression data to find the strongly significant genes to distinguish two groups.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.05a
• /
• pp.255-258
• /
• 2003

Recently, Digital Watermarking is used to authenticate data and to determine whether the data are distorted or not in medical images which is digitalized. The Fourier Mellin method using the Fourier Transform and the Log-Polar coordinate transform gets an invariant feature for RST distortion in images. But there are several problems in the real materialization. Interpolation of the image value should be considered according to the pixel position and so a watermark loss, original image distortion, numerical approximation is happened. Therefore there should be solved to realization of the Fourier Mellin method. Using the Look up table, there reduce the data loss caused by the conversion between Rectangular and Polar coordinate. After diagnose, medical images are transformed the Polar coordinate and taken the Discrete Fourier transform in the center of ROI region. Maintaining the symmetry in Fourier magnitude coefficient, the gaussian distributed random vectors and binary images are embedded in medical images.