• Wind and Structures
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• v.28 no.1
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• pp.63-70
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• 2019

Due to developing environmental concern use of renewable energy source is very essential. The great demand for the energy supply coupled with inadequate energy sources creates an emergency to find a new solution for the energy shortage. The appropriate wind energy distribution is the fundamental requirement for the assessment of wind energy potential available at the particular site essential for the design of wind farms. Hence the proper specification of the wind speed distribution plays a vital role. In this paper the Bimodal Weibull distribution is used to estimate the Capacity factor at the proposed site. The shape and scale parameters estimated using Maximum likelihood method is used as the initial value for extrapolation. Application of this model will give an accurate result overwhelming the concept of overestimation or underestimation of Capacity factor.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.157-158
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• 2020

In order to calculate construction costs properly, it is necessary to add the weight that reflects different worksite conditions. The implementation of the weight, however, is difficult because it is impossible to determine whether wight should be added in basic work or whether weight values are overlapped. Special worksite conditions further complicate the matter. Furthermore, overlapping implementation of weight values result in overestimation of construction costs. The current study clearly analyzed the weight value items in the current construction cost calculation standards, and analyzed the weight value items included under the basic productivity category to propose an improvement of weight standards. Basically, the estimating standards provide 140 weight value items, with different levels of weight given to each item. Among 1,333 items in the estimating standards, 140 include weight values. Some items have two types of weight values.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.

• Nutrition Research and Practice
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• v.5 no.3
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• pp.246-252
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• 2011

Bioelectrical impedance analysis (BIA) models must be validated against a reference method in a representative population sample before they can be accepted as accurate and applicable. The purpose of this study was to compare the eight-electrode BIA method with DEXA as a reference method in the assessment of body composition in Korean adults and to investigate the predictive accuracy and applicability of the eight-electrode BIA model. A total of 174 apparently healthy adults participated. The study was designed as a cross-sectional study. FM, %fat, and FFM were estimated by an eight-electrode BIA model and were measured by DEXA. Correlations between BIA_%fat and DEXA_%fat were 0.956 for men and 0.960 for women with a total error of 2.1%fat in men and 2.3%fat in women. The mean difference between BIA_%fat and DEXA_%fat was small but significant (P < 0.05), which resulted in an overestimation of $1.2{\pm}2.2$%fat (95% CI: -3.2-6.2%fat) in men and an underestimation of $-2.0{\pm}2.4$%fat (95% CI: -2.3-7.1%fat) in women. In the Bland-Altman analysis, the %fat of 86.3% of men was accurately estimated and the %fat of 66.0% of women was accurately estimated to within 3.5%fat. The BIA had good agreement for prediction of %fat in Korean adults. However, the eight-electrode BIA had small, but systemic, errors of %fat in the predictive accuracy for individual estimation. The total errors led to an overestimation of %fat in lean men and an underestimation of %fat in obese women.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.366-372
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• 2020

The Army's rocket missile is a one-shot weapon system, which is produced and used for only one mission, and requires high reliability. While reliability analysis with failure data can result in underestimation of the life distribution, reliability analysis with all the non-failure data can result in overestimation of the life distribution. Under or overestimation of the life distribution can lead to cost increase by early disposal or complete observation of all rocket missiles. In order to overcome this problem, the Army suggests the guideline of the number of samples from non-failure data for reliability analysis with failure data. However, the currently used sampling method can generate errors for predicting the failure rate. To solve this problem, this study proposes a new sampling procedure for predicting a future failure rate using non-failure data. The comparison test between the currently used sampling method and the proposed sampling method is conducted and the result shows that the proposed sampling method can predict the future failure rate more accurately.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.2
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• pp.67-75
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• 1986

This paper introduces the nonlinear Stream Function Wave Theory for design waves efficiently to compute the wave energy and energy transport quantities and to analyze the effects of nonlinearities on them. The Stream Function Wave Theory was developed by Dean for case of the observed waves with assymmetric wave profiles and of the design waves with symmetric theoretical wave profiles. Dalrymple later improved the computational procedure by adding two Lagrangian constraints so that more efficient convergence of the iterative numerical method to a specified wave height and to a zero mean free surface displacement resulted. And the Stream Function coefficients are computed numerically by the improved Marquardt algorithm developed for this study. As the result of this study the effects of nonlinearities on the wave quantities of the average potential energy density, the average kinetic energy density result in overestimation by linear wave theory compared to the Stream Function Wave Theory and increase monotonically with decreasing $L^*/L_O$ and with increasing $H/H_B$. The effects of nonlinearities on the group velocity and the wavelength quantities result in underestimation by linear wave theory and increase monotonically with increasing $H/H_B$. Finally the effect of nonlinearity on the average total energy flux results in overestimation for shallow water waves and underestimation for deep water waves by linear wave theory.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.589-599
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• 2014

This paper analyzes the forecasting errors of traffic volumes by comparing forecasted volumes for the opening year with the observed ones in the years after the urban railway construction in the metropolitan areas. The result shows that the average inaccuracy of traffic volumes for each station was estimated at around 7.27. Based on the confirmed factors of demand estimation errors, this study seeks for an alternative method to reduce estimation errors in feasibility studies. It is noted that there is a tendency that the inaccuracy varies by regions and the longer construction period or the shorter station spacing is, the overestimation increases. If urban railway projects are proceeded as planed, therefore, the level of the inaccuracy for traffic volume forecast will be decreased. In addition, thanks to the theoretical progress, recent estimation results show higher accuracy than before. In that sense, when we introduce the new railway line, it is necessary to make an accurate and realistic demand forecast based on actual outcomes and tendency of the previous estimation. The limitation of our study is that we only cover the errors of the initial period, the opening year and deal with the exogenous variables. Further research including other variables which might be considered to cause overestimation or errors would be needed for increasing the estimation accuracy of traffic volumes.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.727-733
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• 2011

A new Korean standard for the determination of Cr(VI) in soils has been officially published as ES 07408.1 in 2009. This analytical method is based on the hot alkaline digestion and colorimetric detection prescribed by U.S. EPA method 3060A and 7196A. The hot alkaline digestion accomplished using 0.28 M $Na_2CO_3$ and 0.5 M NaOH solution (pH 13.4) at $90{\sim}95^{\circ}C$ determines total Cr(VI) in soils extracting all forms of Cr(VI), including water-soluble, adsorbed, precipitated, and mineral-bound chromates. This aggressive alkaline digestion, however, proved to be problematic for certain soils which contain large amounts of soluble humic substances or active manganese oxides. Cr(III) could be oxidized to Cr(VI) by manganese oxides during the strong alkaline extraction, resulting in overestimation (positive error) of Cr(VI). In contrast, Cr(VI) reduction by dissolved humic matter or Fe(II) could occur during the neutralization and acidic colorimetric detection procedure, resulting in underestimation (negative error) of Cr(VI). Futhermore, dissolved humic matter hampered the colorimetric detection of Cr(VI) using UV/Vis spectrophotometer due to the strong coloration of the filtrate, resulting in overestimation (positive error) of Cr(VI). Without understanding the mechanisms of Cr(VI) and Cr(III) transformation during the analysis it could be difficult to operate the experiment in laboratory and to evaluate the Cr(VI) results. For this reason, in this paper we described the theoretical principles and limitations of Cr(VI) analysis and provided useful guidelines for laboratory work and Cr(VI) data analysis.

• Korean Journal of School Psychology
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• v.17 no.3
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• pp.263-286
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• 2020

The purpose of this study was to explore how overly positive self-estimations in peer relationships relate to subjective well-being and to the occurrence of interpersonal behaviors supporting basic psychological needs among elementary school students. This study tested the optimal margin hypothesis of positive illusion by examining the curvilinear relationship between these variables. The sample consisted of 346 fifth and sixth grade students. The self-criterion residual method was used to derive self-estimation bias scores by regressing the real peer relations index (i.e., In-degree) on their perceived peer relationship qualities. The results showed that girls more strongly overestimated the quality of their peer relationships than boys. Self-estimation biases had a positive curvilinear relationship with negative affects and a negative curvilinear relationship with relatedness needs supporting interpersonal behaviors. These results supported the existence of the optimal margin of positive illusion because overestimations of the quality of peer relationships were associated with lower levels of negative affects and relatedness needs-supporting interpersonal behaviors, though these benefits flattened out and no further benefit was observed after an optimal level of overestimation. However, self-estimation bias was linearly associated with positive affect, autonomy needs-supporting interpersonal behaviors, and competence needs-supporting interpersonal behaviors. These results indicated that optimal margin hypothesis was not supported for all outcome variables.

• Korean Journal of Culture and Social Issue
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• v.21 no.2
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• pp.177-203
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• 2015

The aims of this study were 1) to compare irrational gambling beliefs of gamblers and non-gamblers, 2) to investigate the role of cognitive error on winning probability thinking error, and 3) to examine the relationship between attributional bias and gambling behavior. A total of 248 subjects were recruited for this study. All subjects were classified into non-gamblers, social gamblers and pathological gamblers, and administered self-report questionnaires to measure irrational gambling beliefs, the probability inference error, the attriburional style, and the attributional bias. A pathological gambler group scored highest on irrational gambling beliefs, especially the overestimation of self-ability factor, and a social gambler group and a non-gambler group follow. All three groups scored higher on the magnification of gambling skills than the mean (4.0) of the scale. Pathological gamblers and social gamblers scored higher on the probability thinking error than non-gamblers. Pathological gamblers displayed higher external attribution, lower internal attribution in their daily life events and higher internal attribution in failure situation than social gamblers and non-gamblers. The results indicate that cognitive errors would be a factor that differentiates pathological gamblers from social gamblers and non-gamblers. In predicting gambling behaviors, overestimation of self-ability of irrational gambling beliefs, internal attribution in failure situation, external attribution in daily live event, and probability thinking error were identified as significant factors. It is concluded that a public education about common cognitive bias featured in gamblers might be important in prevention of pathological gambling behaviors.