• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.629-638
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• 2021

Background and objective: This study was conducted to develop diameter growth models for thinned Quercus glauca Thunb. (QGT) stands to inform production goals for treatment and provide the information necessary for the systematic management of this stands. Methods: This study was conducted on QGT stands, of which initial thinning was completed in 2013 to develop a treatment system. To analyze the tree growth and trait response for each thinning treatment, forestry surveys were conducted in 2014 and 2021, and a one-way analysis of variance (ANOVA) was executed. In addition, non-linear least squares regression of the PROC NLIN procedure was used to develop an optimal diameter growth model. Results: Based on growth and trait analyses, the height and height-to-diameter (H/D) ratio were not different according to treatment plot (p > .05). For the diameter of basal height (DBH), the heavy thinning (HT) treatment plot was significantly larger than the control plot (p < .05). As a result of the development of diameter growth models by treatment plot, the mean squared error (MSE) of the Gompertz polymorphic equation (control: 2.2381, light thinning: 0.8478, and heavy thinning: 0.8679) was the lowest in all treatment plots, and the Shapiro-Wilk statistic was found to follow a normal distribution (p > .95), so it was selected as an equation fit for the diameter growth model. Conclusion: The findings of this study provide basic data for the systematic management of Quercus glauca Thunb. stands. It is necessary to construct permanent sample plots (PSP) that consider stand status, location conditions, and climatic environments.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1190-1199
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• 2016

This study proposes a classification and compensation algorithm of two non-ideal output signals of a resolver to reduce position errors. Practically, a resolver generates position errors because of amplitude imbalance and quadrature imperfection between the two output signals of the resolver. In this study, a digital signal processor system based on a resolver-to-digital converter is used to reconstruct the two output signals of the resolver. The two output signals, "sin" and "cos," can be represented by a unit circle on the xy-plot. The classification and compensation of the errors can be obtained by using the radius and area of the circle made by the resolver signals. The method computes the integration of the areas made by the two resolver output signals to classify and compensate the error. This system cannot be applied during transient response given that the area integration during the transient state causes an error in the proposed method. The proposed method does not need any additional hardware. The experimental results verify the effectiveness of the proposed algorithm.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.100-117
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• 1985

This paper describes an outline of the sampling design for crop area survey and product survey in Korea. The design attempts to from a double statification, to obtain an efficient allocation of the sample and to reduce the sampling error by establishign crop concentrated strata. The optimum numbers of sample field and sample plot are investigated. The design is made it possible to reduce the sampling errors as well as to reduce the sample size further than the present survey.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.581-588
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• 1997

Univariate F test is based on the multisample sphericity assumption. Robustness for tests of a main effect of the within-subjects factor was investigated when the assumptions of the onmibus F tests are violated in a split-plot design with one between-subjects factor using untrimmed data and trimmed data. The results indicate that when sample sizes are unbalanced and dispersion matrices are heterogeneous, the CIGA and the $CIGA_T$ tests better control Type I error rates than do the $F_T$test and the$\widetilde{\xi_T}$test.

• Analytical Science and Technology
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• v.12 no.3
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• pp.177-183
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• 1999

The determination method of free acid in spent U-Al nuclear fuel solutions by Gran plot titration was described. Effect of U(VI) and Al(III) on the alkalimetric titration of nitric acid was investigated in oxalate complexing media as well as in noncomplexing media. Positive biases were observed in both titration media when the end-point was estimated by the Gran plot method. It was found that the cause of the bias was U(VI) in the oxalate complexing media, but Al(III) in the noncomplexing media. The relative error was less than 1% in the titration of 0.1 M $HNO_3$ at a U(VI) : Al(III) : $H^+$ mole ratio of up to 2:12:1 as long as the pH of the oxalate titration media was sustained to be below 5.0 at the beginning of titration. The method was successfully applied to the determination of nitric acid in a solution of HANARO reactor fuel with U:Al mole ratio of 1:6.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.15-24
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• 2012

For the construction of fractional factorial designs, the various arrays can be widely used. In this paper we review the statistical properties of fractional designs constructed by two arrays such as orthogonal array and partially balanced array, and develop a quick and easy method for analyzing unreplicated saturated designs. The proposed method can be characterized that we control the error rate by experiment-wise way and exploit the multivariate Student $t$-distribution. Especially the proposed method can be used efficiently together with some exploratory analysis methods, such as half normal probability plot method.

• Journal of Korean Society for Quality Management
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• v.42 no.4
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• pp.607-616
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• 2014

Purpose: This paper reviews popular measurement system indices and proposes a procedure for assessing a measurement system using two parameters with intraclass correlation and a factor for process capability. Methods: Gage Repeatability and Reproducibility(GR&R), precision-to-tolerance ratio(PTR), number of distinct categories, producer's and consumer's risks are employed to assess the measurement capabilities and discuss the relationships between measurement system metrics. Results: Two-dimensional plot by two parameters is presented to assess adequacy of the measurement system and process capability. A numerical example and previously studied case study are provided for illustration. Conclusion: The procedure proposed in this paper using two-dimension parameters provides a valuable procedure and helpful guidelines to quality and production managers in assessing the capabilities of a measurement system and choosing the needed actions to be the most benefit.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1151-1160
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• 2014

In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

• Journal of Drive and Control
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• v.13 no.1
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• pp.34-42
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• 2016

This study studied how the clearance, overlap and mismatch errors of spool-sleeve affect the static pressure characteristics of a servo valve. A computer simulation model was established as a direct acting servo valve and a series of simulations was conducted for various values of clearance, overlap and mismatch errors. Pressure gain decreased as the clearance increased. The overlap also affects the pressure gain and was similar to the effect of clearance. Asymmetry of the pressure plot got worse and worse as the mismatch error increased.