• Journal of the Korean Statistical Society
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• v.31 no.3
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• pp.405-413
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• 2002

We consider a finite dam with general inputs and adopt the level crossing approach to obtain explicit formulas of the expected wet period, the expected loss of water due to overflows in a wet period, and the long-run proportion of loss in inputed water.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• Journal of Korea Trade
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• v.24 no.8
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• pp.171-188
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• 2020

Purpose - This is an exploratory study that aims to apply text mining techniques, which computationally extracts words from the large-scale text data, to legal documents to quantify trade claim contents and enables statistical analysis. Design/methodology - This is designed to verify the validity of the application of text mining techniques as a quantitative methodology for trade claim studies, that have relied mainly on a qualitative approach. The subjects are 81 cases of arbitration and court judgments from China published on the website of the UNCITRAL where the CISG was applied. Validation is performed by comparing the manually analyzed result with the automatically analyzed result. The manual analysis result is the cluster analysis wherein the researcher reads and codes the case. The automatic analysis result is an analysis applying text mining techniques to the result of the cluster analysis. Topic modeling and semantic network analysis are applied for the statistical approach. Findings - Results show that the results of cluster analysis and text mining results are consistent with each other and the internal validity is confirmed. And the degree centrality of words that play a key role in the topic is high as the between centrality of words that are useful for grasping the topic and the eigenvector centrality of the important words in the topic is high. This indicates that text mining techniques can be applied to research on content analysis of trade claims for statistical analysis. Originality/value - Firstly, the validity of the text mining technique in the study of trade claim cases is confirmed. Prior studies on trade claims have relied on traditional approach. Secondly, this study has an originality in that it is an attempt to quantitatively study the trade claim cases, whereas prior trade claim cases were mainly studied via qualitative methods. Lastly, this study shows that the use of the text mining can lower the barrier for acquiring information from a large amount of digitalized text.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1044-1051
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• 2002

This paper proposes a two-phase mathematical programming approach by considering classification gap to solve the proposed credit scoring problem so as to complement any theoretical shortcomings. Specifically, by using the linear programming (LP) approach, phase 1 is to make the associated decisions such as issuing grant of credit or denial of credit to applicants. or to seek any additional information before making the final decision. Phase 2 is to find a cut-off value, which minimizes any misclassification penalty (cost) to be incurred due to granting credit to 'bad' loan applicant or denying credit to 'good' loan applicant by using the mixed-integer programming (MIP) approach. This approach is expected to and appropriate classification scores and a cut-off value with respect to deviation and misclassification cost, respectively. Statistical discriminant analysis methods have been commonly considered to deal with classification problems for credit scoring. In recent years, much theoretical research has focused on the application of mathematical programming techniques to the discriminant problems. It has been reported that mathematical programming techniques could outperform statistical discriminant techniques in some applications, while mathematical programming techniques may suffer from some theoretical shortcomings. The performance of the proposed two-phase approach is evaluated in this paper with line data and loan applicants data, by comparing with three other approaches including Fisher's linear discriminant function, logistic regression and some other existing mathematical programming approaches, which are considered as the performance benchmarks. The evaluation results show that the proposed two-phase mathematical programming approach outperforms the aforementioned statistical approaches. In some cases, two-phase mathematical programming approach marginally outperforms both the statistical approaches and the other existing mathematical programming approaches.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.42
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• pp.11.1-11.8
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• 2020

Background: The purpose of this study is to compare the skeletal stability of two-jaw surgery via surgery-first approach with conventional two-jaw surgery in facial asymmetry patients by measuring the skeletal changes after surgery from a three-dimensional analysis. From January 2010 to January 2014, 40 patients with facial asymmetry who underwent two-jaw surgery in Pusan National University Hospital were included in this study. They were classified into experimental group (n = 20) who underwent two-jaw surgery via surgery-first approach and control group (n = 20) who underwent conventional two-jaw surgery. After selection of 24 landmarks and the construction of horizontal and sagittal, coronal reference planes, changes in 10 linear measurements and 2 angular measurements were compared between the surgery-first approach and conventional groups in the preoperative, immediate postoperative, and postoperative periods. The paired t test and Student t test were used for statistical analysis. The mean and standard deviation of the measurement were calculated for the experimental and control groups. Results: The statistical analysis showed that changes in skeletal measurements were similar between the surgery-first approach and conventional groups, according to each period. However, U1-SRP measurement showed statistically significant changes in surgery-first approach groups at postsurgical change (T1 to T2). Also, the mean treatment duration in the treatment group was 15.9 ± 5.48 months whereas that in the control group was 32.9 ± 14.05 months. Conclusion: In facial asymmetry patients, similar results were observed in the postoperative skeletal stability when 2-jaw surgery via surgery-first approach was compared with conventional 2-jaw surgery. However, significant lateral deviation of upper incisor midline was observed. In addition, a shorter average treatment duration was observed. To stabilize the unstable occlusion after surgery, increased wearing of the stent and proactive rubber guidance will be needed.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.95-101
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• 2016

This study proposes a multi-scale dynamic system reliability analysis of control system as a method of quantitative evaluation of its performance in probabilistic terms. In this second paper, we discuss the control effect of the viscous damper on the seismic performance of the structure-level failure. Since the failure of one structural member does not necessarily cause the collapse of the structural system, we need to consider a set of failure scenarios of the structural system and compute the sum of the failure probabilities of the failure scenarios where the statistical dependence between the failure scenarios should be taken into account. Therefore, this computation requires additional system reliability analysis. As a result, the proposed approach takes a hierarchial framework where the failure probability of a structural member is computed using a lower-scale system reliability with the union set of time-sequential member failures and their statistical dependence, and the failure probability of the structural system is again computed using a higher-scale system reliability with the member failure probabilities obtained by the lower-scale system reliability and their statistical dependence. Numerical results demonstrate that the proposed approach can provide an accurate and stable reliability assessment of the control performance of the viscous damper system on the system failure. Also, the parametric study of damper capacity on the seismic performance has been performed to demonstrate the applicability of the proposed approach through the probabilistic assessment of the seismic performance improvement of the damper system.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.63-75
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• 1985

This paper considers a statistical calibration problem in which the standard as wel as the nonstandard measurement is subject to error. Since the classicla approach cannot handle this situation properly, a functional relationship model with additional feature of prediction is proposed. For the analysis of the problem four different approaches-two estimation techniques (ordinary and grouping least squares) combined with two prediction methods (classical and inverse prediction)-are considered. By Monte Carlo simulation the perromance of each approach is assessed in term of the probability of concentration. The simulation results indicate that the ordinary least squares with inverse prediction is generally preferred in interpolation while the grouping least squares with classical prediction turns out to be better in extrapolation.

• Korean Journal of Child Studies
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• v.37 no.5
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• pp.129-144
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• 2016

Objective: This study's purpose was to develop a teaching competency scale for character education for early childhood teachers and to examine its reliability. Methods: The study procedure was as follows: First, scale items were generated by reviewing the literature as a deductive approach and focused interviews with 8 field experts in an inductive approach. Second, face validation was assessed by 7 academic experts, and statistical validation processes were done twice. The data used in the final statistical analyses included 206 questionnaires for early childhood teachers. Statistical validation included item response analysis, item discrimination analysis, exploratory factor analysis, confirmatory factor analysis, and reliability analysis. Results: The 3 factors identified were as follows: Communicate teaching competence, practical teaching competence, and instrumental teaching competence. The validity and reliability of the Teaching Competency Scale for Character Education in Early Childhood Teachers were acceptable. Conclusion: This new scale will be a useful tool to better support character education for early childhood teachers and contribute to providing a basis for developing more sophisticated tools.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.14-20
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• 1997

Pipeline network analysis requires fluid mechanics. A lot of equations have been used for flow analysis according to the behavior of fluid in pipelines and the operative situations. In this paper, simulation and analysis have been performed for the pipeline network system in Kyungin area using a steady-state mathematical model. Then, a statistical model using partial least squares(PLS) method has been developed with the data obtained from the developed mathematical model. The results showed that it is possible to simulate and analyze pipeline network systems using statistical approach.

• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.81-87
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• 2001

A framework for reliability analysis of structural components and systems under conditions of statistical and model uncertainty is presented. The Bayesian parameter estimation method is used to derive the posterior distribution of model parameters reflecting epistemic uncertainties. Point, predictive and bound estimates of reliability accounting for parameter uncertainties are derived. The bounds estimates explicitly reflect the effect of epistemic uncertainties on the reliability measure. These developments are enhance-ments of second-moment uncertainty analysis methods developed by A. H-S. Ang and others three decades ago.