• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.294-297
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• 2004

Mean squared error (MSE) is an effective criterion to combine the mean and the standard deviation responses in dual response surface optimization. The bias and variance components of MSE need to be weighted properly in the given problem situation. This paper proposes a systematic method to determine the relative weights of bias and variance in accordance with a decision maker's prior and posterior preference structure.

• Earthquakes and Structures
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• v.25 no.6
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.2
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• pp.39-48
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• 2003

This paper present a summary of the results of statistical study of the ductility factor which is key component of response modification factor(R). To compute the ductility factor, a group of 1,860 ground motions recorded from various earthquake was considered. Based on the local site conditions at the recording station, ground motions were classified into four groups according to average shear wave velocity. Inleastic spectrum were computed for elastic perfectly plastic SDOF systems undergoing different level of inelastic deformation and period. Ductility factors were calculated by deviding elastic response spectrum by inelastic response spectrum. The influence f displacement ductility ratio, site condition, magnitude and epicentral distance on ductility factors were studied. The coefficient of variation was computed to evaluated the dispersion of ductility factors as the defined ratio of the standard deviation to the mean.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.11
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• pp.1527-1576
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• 2002

Quick Response based Mass-Customization can be produced and distributed customized goods and services on mass basis in apparel e-business. Because consumers can: t touch and feel the apparel products in e-business, they tend to have the negative buying behavior. The purpose of this study is to investigate the differences of consumer's texture sensibility of apparel products based on marketing channels (on-line/off-line). Two types of questionnaires for on-line and of f-line were used to assess consumer sensibility on apparel fabric. The 8 swatches were selected in regard to the previous literatures. 205 questionnaires for each type (on-line/off-line) were distributed. Statistical devices were t-test, mean and standard deviation with SPSS10.0. The result of this study was showed that there were partially significant differences on consumers' texture sensibility on apparel products between on-line and off-line. Under on-line environment, consumers perceived corduroy as warm, strong, and sandy. taffeta as warm, sandy, and glossy, denim as sandy, and warm, organza as sandy, and thin, satin as sandy, dense, and modern, chiffon as sandy, and flat, velvet as warm, and soft, single jersey as warm, soft, and comfortable. Therefore, apparel firms cooperating based Mass-Customization in e-business have to pay attention to the differences on consumers’ texture sensibility of on-line apparel products from those of off-line.

• Journal of the Korean Home Economics Association
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• v.40 no.5
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• pp.39-51
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• 2002

The purpose of this study is to investigate prior thinking and posterior thinking formation of children and adolescents in sinking objects. The subjects consisted of twenty eight, 9- and 11-year old children and fourteen, 13-year old adolescents selected from one elementary school and two middle schools. The transcripts were analyzed to classify children and adolescents'prior thinking and posterior thinking frequency, reasoning response(evidence based response, idea based response) and reasoning method(valid method, invalid method). The data were analyzed by frequency, percentile, mean and standard deviation,1 test, ANOVA. Major findings were as followings: 1. Children and adolescents have already had prior thinking in sinking objects. 2. Children and adolescents applies their prior thinking to posterior thinking formation process. 3. There were significant differences in children and adolescent'posterior thinking formation process, especially choices in objects and reasoning methods depending on age. 4. There were significant differences in children and adolescents'reasoning response depending on presented evidences types.5. Through the experimentation, children and adolescents'prior thinking was different from their posterior thinking. There were significant differences in differences between the prior thinking and posterior thinking depending on age.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.19 no.2
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• pp.112-119
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• 2008

Objectives : This study was conducted to examine whether there are qualitative differences in attention problem among children with various psychiatric disorders, including attention-deficit hyperactivity disorder (ADHD), depressive disorder, anxiety disorder, and tic disorder using clinical ADHD diagnostic system (ADS) T-scores. Methods : The subjects were 794 outpatient children aged from 5 to 15 years, including 540 children with ADHD, 95 children with depressive disorder, 86 children with anxiety disorder, and 73 children with tic disorder. Clinical T-scores on the ADS were calculated using the mean and standard deviations of four ADS variables for the ADHD group. Results : All four groups had T-scores on the ADS in the abnormal range. However, when comparing the clinical T-scores, the children with depressive and anxiety disorders performed better than the children with ADHD. We also found that although the four groups seemed to be similar in terms of clinical T-scores for omission and commission errors, there were significant differences in clinical T-scores for reaction time and the standard deviation of response time (RT) between the ADHD and other groups. Conclusions : We concluded that inattention and impulsivity might not be specific only to ADHD and that the clinical T-scores of RT and standard deviation of RT on the ADS could be used to discriminate between ADHD and other clinical groups.

• Journal of Biosystems Engineering
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• v.34 no.1
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• pp.15-20
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• 2009

This study was conducted to develop a moisture sensor for rapeseed, a bio-diesel material. A typical rapeseed, SUNMANG, was used as a raw material. The rapeseed moisture content sensor consists of three components, such as upper and bottom electrodes, a test material dish, and a fixing housing. To evaluate the performance, a data acquisition system was equipped with the rapeseed moisture sensor, computer, printer, and main board. The findings of this study were: 1) the rapeseed moisture content was inversely proportional to electric resistance, and 2) values of electric resistance were recorded in a range of $10{\sim}100\;M{\Omega}$, depending upon a change of the moisture content. The determination of coefficient ($R^2$) and standard error between rapeseed moisture content and electric resistance were 0.9921 and ${\pm}0.289$, which indicated a highly correlative relationship. The response of rapeseed moisture sensor to temperature change was also observed for further performance test. Satisfying results were obtained, such as the determination of coefficient ($R^2$) of 0.9918, predicted standard error of ${\pm}0.373%$, deviation of 0.103%, measurement error of $0.14{\sim}0.48%$, standard deviation of $0.01{\sim}0.22%$, and measurement time of 28.3 s per point, respectively.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1279-1288
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• 2021

Objective: To assess the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 treatment response algorithm (TRA) for the evaluation of hepatocellular carcinoma (HCC) treated with transarterial radioembolization. Materials and Methods: This retrospective study included patients who underwent transarterial radioembolization for HCC followed by hepatic surgery between January 2011 and December 2019. The resected lesions were determined to have either complete (100%) or incomplete (< 100%) necrosis based on histopathology. Three radiologists independently reviewed the CT or MR images of pre- and post-treatment lesions and assigned categories based on the LI-RADS version 2018 and the TRA, respectively. Diagnostic performances of LI-RADS treatment response (LR-TR) viable and nonviable categories were assessed for each reader, using histopathology from hepatic surgeries as a reference standard. Inter-reader agreements were evaluated using Fleiss κ. Results: A total of 27 patients (mean age ± standard deviation, 55.9 ± 9.1 years; 24 male) with 34 lesions (15 with complete necrosis and 19 with incomplete necrosis on histopathology) were included. To predict complete necrosis, the LR-TR nonviable category had a sensitivity of 73.3-80.0% and a specificity of 78.9-89.5%. For predicting incomplete necrosis, the LR-TR viable category had a sensitivity of 73.7-79.0% and a specificity of 93.3-100%. Five (14.7%) of 34 treated lesions were categorized as LR-TR equivocal by consensus, with two of the five lesions demonstrating incomplete necrosis. Interreader agreement for the LR-TR category was 0.81 (95% confidence interval: 0.66-0.96). Conclusion: The LI-RADS version 2018 TRA can be used to predict the histopathologic viability of HCCs treated with transarterial radioembolization.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1047-1061
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• 2015

Stratified random sampling is a powerful sampling strategy to reduce variance of the estimators by incorporating useful auxiliary information to stratify the population. Sample allocation is the one of the important decisions in selecting a stratified random sample. There are two common methods, the proportional allocation and Neyman allocation if we could assume data collection cost for different observation units equal. Theoretically, Neyman allocation considering the size and standard deviation of each stratum, is known to be more effective than proportional allocation which incorporates only stratum size information. However, if the information on the standard deviation is inaccurate, the performance of Neyman allocation is in doubt. It has been pointed out that Neyman allocation is not suitable for multi-purpose sample survey that requires the estimation of several characteristics. In addition to sampling error, non-response error is another factor to evaluate sampling strategy that affects the statistical precision of the estimator. We propose new sample allocation methods using the available information about stratum response rates at the designing stage to improve stratified random sampling. The proposed methods are efficient when response rates differ considerably among strata. In particular, the method using population sizes and response rates improves the Neyman allocation in multi-purpose sample survey.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.6
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• pp.301-309
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• 2019

A methodology to assess seismic fragility of a nuclear power plant (NPP) using a conditional mean spectrum is proposed as an alternative to using a uniform hazard response spectrum. Rather than the single-scenario conditional mean spectrum, which is the conventional conditional mean spectrum based on a single scenario, a multi-scenario conditional mean spectrum is proposed for the case in which no single scenario is dominant. The multi-scenario conditional mean spectrum is defined as the weighted average of different conditional mean spectra, each one of which corresponds to an individual scenario. The weighting factors for scenarios are obtained from a deaggregation of seismic hazards. As a validation example, a seismic fragility assessment of an NPP containment structure is performed using a uniform hazard response spectrum and different single-scenario conditional mean spectra and multi-scenario conditional mean spectra. In the example, the number of scenarios primarily influences the median capacity of the evaluated structure. Meanwhile, the control frequency, a key parameter of a conditional mean spectrum, plays an important role in reducing logarithmic standard deviation of the corresponding fragility curves and corresponding high confidence of low probability of failure (HCLPF) capacity.