• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.1013-1026
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• 2008

Kolmogorov-Smirnov(K-S) statistic has been widely used for the model validation of credit rating models. Validation criteria for the K-S statistic is empirically used at the levels of 0.3 or 0.4 which are much larger than the critical values of K-S test statistic. We examine whether these criteria are reasonable and appropriate through the simulations according to various sample sizes, type II error rates, and the ratio of bads among data. The simulation results say that the currently used validation criteria are too lower than values of K-S statistics obtained from any credit rating models in Korea, so that any credit rating models have good discriminatory power. In this work, alternative criteria of K-S statistic are proposed as critical levels under realistic situations of credit rating models.

• Journal of Engineering Education Research
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• v.21 no.5
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• pp.32-39
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• 2018

The purpose of this study was to develop and validate a behaviorally anchored rating scale for peer evaluation in group projects based on social interdependence theory. A mixed method involving a qualitative and quantitative approach was used in this study. In the qualitative study, both the individual and group interviews were conducted to college students regarding their cooperative learning experiences. Data from this qualitative research was analyzed based on 5 elements of cooperative learning and 'critical incidents' were extracted from students' own voices that would serve as specific rating criteria in the scale. Once the 'critical incidents' have been incorporated into the scale, validation from 3 independent experts was conducted. In the quantitative study, correlations with relevant variables were analyzed to examine the criteria-referenced validity. Findings suggest that the behaviorally anchored rating scale for peer evaluation in group projects can be used in various team-based learning contexts.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.261-272
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• 2009

Kolmogorov-Smirnov (K-S) statistic has been widely used for testing homogeneity of two distributions in the credit rating models. Joseph (2005) used K-S statistic to obtain validation criteria which is most well-known. There are other homogeneity test statistics such as the Cramer-von Mises, Anderson-Darling, and Watson statistics. In this paper, these statistics are introduced and applied to obtain criterion of these statistics by extending Joseph (2005)'s work. Another set of alternative criterion is suggested according to various sample sizes, type a error rates, and the ratios of bads and goods by using the simulated data under the similar situation as real credit rating data. We compare and explore among Joseph's criteria and two sets of the proposed criterion and discuss their applications.

• Journal of the Korean Home Economics Association
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• v.36 no.6
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• pp.95-108
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• 1998

This study is the second study which was aimed to validate the Infant/ Toddler Environment Rating Scale(ITERS). The test-retest reliability included 10 infant/toddler classes among 30 national/public and private child care centers in Inchon city which had been observed in the first validation study. The Spearman's correlation coefficient for test-retest reliability was ranged from .52 to .84. In addition, two raters observed 10 family day care centers in Inchon city, where two observers independently rated each centers on the ITERS during a single visit. The Spearman's correlation coefficient for interrater reliability was ranged from.72 to .99 For the second measure of content validity, experts who were working in day care centers and who were graduate students, lecturers, or professors majoring child studies rated the appropriateness of each ITERS items for the provision of high-quality programs for infants and toddlers, using a 1(low) to 5(high) scale. The mean rating was ranged from 2.52 to 4.52. In sum, when the rating scores were analyzed by the type of child care centers, national/public child care centers have better quality than private or family child care centers.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.789-800
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• 2008

Current credit evaluation models based on financial data make use of smoothing estimated default ratios which are transformed from each financial variable. In this work, some problems of the credit evaluation models developed by financial experts are discussed and we propose improved credit evaluation models based on the stepwise variable selection method and Box-Cox transformed data whose distribution is much skewed to the right. After comparing goodness-of-fit tests of these models, the validation of the credit evaluation models using statistical methods such as the stepwise variable selection method and Box-Cox transformation function is explained.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.679-683
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• 2005

The technique which connects Generalized Regression Neural Networks Model(GRNNM) with Genetic Algorithm (CA) is used to derive rating curve in the river basin. GRNNM architecture consists of 4 layers ; input, hidden, summation and output layer. GA method is applied to estimate the optimal smoothing factor when GRNNM is trained. The derivation of rating curve using GRNNM is considered different kinds of hydraulic characteristics such as water stage, area and mean velocity and is applied two stage stations; Sunsan and Jungam. Furthermore, it is compared with conventional curve-fitting method. Through the training and validation performance, the results show that GRNNM is much superior as compared to the conventional curve-fitting method.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.571-578
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• 2005

Corporate credit rating analysis has drawn a lot of research interests in previous studies, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper applies support vector machines (SVMs) to the corporate credit rating problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, the researcher uses a grid-search technique using 5-fold cross-validation to find out the optimal parameter values of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM, the researcher compares its performance with those of multiple discriminant analysis (MDA), case-based reasoning (CBR), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.1065-1075
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• 2008

For the model validation of credit rating models, Kolmogorov-Smirnov(K-S) statistic has been widely used as a testing method of discriminatory power from the probabilities of default for default and non-default. For the credit rating works, K-S statistics are to test two identical distribution functions which are partitioned from a distribution. In this paper under the assumption that the distribution is known, modified K-S statistic which is formulated by using known distributions is proposed and compared K-S statistic.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.243-253
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• 2008

This paper deals with the analysis, design, and implementation of a single phase AC-DC Zeta converter with high frequency transformer isolation and power factor correction(PFC) in two modes of operation, discontinuous current mode of operation(DCM), and continuous current mode of operation(CCM). A Digital Signal Processor(DSP) based implementation is carried out for validation of the Zeta converter developed design in discontinuous mode of operation. A comparison of both modes of operation is presented for a 1kW power rating from the point of view of steady state and dynamic behavior, power quality, simplicity, control technique, device rating, and converter size. The experimental results of a developed prototype of Zeta converter are presented for validation of the developed design. It is observed that CCM is most suitable for higher power applications where it requires some complex control and sensing of the additional variables.

• Journal of the Korean Home Economics Association
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• v.35 no.6
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• pp.235-248
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• 1997

This study was aimed to validate the Infant/Toddler Environment Rating scale (ITERS). The rating scale was translated and adjusted appropriately by two researchers majoring child studies. An item-by-item comparison of the ITERS with criteria of NAEYC was conducted as the measure of content validity. 88% of the items of the ITERS was covered on the NAEYC criteria. Criterion validity was assessed by comparing ITERS scores and the Assessment Profile for early childhood Programs scores. The total correlation of two scores was .87. The sample for the inetrater reliability and internal consistency studies included 30 infant/toddler classes in 30 day care center in Inchon city. Two observers independently rated each class on the ITERS during a single visit. The Spearman's correlation coefficient for interater reliability on the overall scale was .74. For the measure of internal consistency, the Cronbach's Alpha score on the overall scale was .93. The rating results show that national/public child care centers have better quality in Adult Needs and Learning Activities subscales than private child care centers have.