• Management & Information Systems Review
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• v.13
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• pp.141-162
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• 2003

This article discusses the issues of the estimated size and characteristics of irregular employment work force in Korea after IMF economic crisis in 1997. The issues of the estimated size of irregular employment work force originated from different concepts and its operationalizations among the labor economists, despite their utilization of the same labor force data, 'Economically Active Population Survey(EAPA)' collected from Korea National Statistical Office(KNSO). And the issues contribute toward the understandings of the irregular employment and the limits of the EAPA, despite its various usefulness. This article also describes the summary characteristics of irregular employment work force from both sides of labor supply and its demand. The major characteristics of irregular employment work force on the labor supply side appears in the concentration of social minorities, i.e. woman, the aged, lower educated and skilled populations. On the labor demand of irregular employment work force, the majority of it concentrated on the establishments under 10 employees, and probably the important incentives for irregular employment work force of the firms is labor cost efficiency. Finally, this article propose an alternative against the discrimination between the regular and irregular work force.

• Journal of Digital Convergence
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• v.5 no.1
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• pp.117-130
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• 2007

This paper examines whether there exists discrimination of the information usage pattern between tenants of permanent and temporary public rental housing in Korea. Moreover, we focus to examine on that matters between two groups, $7{\sim}12$ pyeongs and $11{\sim}24$ pyeongs that indicate permanent and temporary public rental housing respectively. The results derived in this paper can be summarized as follows: there exists statistical significance in using computer, internet, communication and broadcasting, on the other hand, insignificance in using satellite communication and telephone between them. The implication of this results shows that as widen income gap, also widen gaps in using computer and internet between them. Thus government public rental housing policy should focus to make narrow income gap to diminish information gap between those groups.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05b
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• pp.100-103
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• 2004

In this paper, BP learning algorithm is studied to apply as a PD source classification in GIS specimens. For occurred partial discharge, three defected models are made; floating particle, surface discharge of spacer, needle to plane. And PD data for discrimination were acquired from PD detector. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.272-288
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• 1990

The uncertainty quantification process in probabilistic Risk Assessment usually involves a specification of the uncertainty in the input data and the propagation of this uncertainty to the final risk results. The distributional sensitivity analysis is to study the impact of the various assumptions made during the quantification of input parameter uncertainties on the final output uncertainty. The uncertainty importance of input parameters, in this case, should reflect the degree of changes in the whole output distribution and not just in a point estimate value. A measure of the uncertainty importance is proposed in the present paper. The measure is called the distributional sensitivity measure(DSM) and explicitly derived from the definition of the Kullback's discrimination information. The DSM is applied to three typical discrimination information. The DSM is applied to three typical cases of input distributional changes: 1) Uncertainty is completely eliminated, 2) Uncertainty range is increased by a factor of 10, and 3) Type of distribution is changed. For all three cases of application, the DSM-based importance ranking agrees very well with the observed changes of output distribution while other statistical parameters are shown to be insensitive.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.14 no.2
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• pp.110-116
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• 2003

Background and Objectives : Laryngeal cancer discrimination using voice signals is a non-invasive method that can carry out the examination rapidly and simply without giving discomfort to the patients. n appropriate analysis parameters and classifiers are developed, this method can be used effectively in various applications including telemedicine. This study examines voice analysis parameters used for laryngeal disease discrimination to help discriminate laryngeal diseases by voice signal analysis. The study also estimates the laryngeal cancer discrimination activity of the Gaussian mixture model (GMM) classifier based on the statistical modelling of voice analysis parameters. Materials and Methods : The Multi-dimensional voice program (MDVP) parameters, which have been widely used for the analysis of laryngeal cancer voice, sometimes fail to analyze the voice of a laryngeal cancer patient whose cycle is seriously damaged. Accordingly, it is necessary to develop a new method that enables an analysis of high reliability for the voice signals that cannot be analyzed by the MDVP. To conduct the experiments of laryngeal cancer discrimination, the authors used three types of voices collected at the Department of Otorhinorlaryngology, Pusan National University Hospital. 50 normal males voice data, 50 voices of males with benign laryngeal diseases and 105 voices of males laryngeal cancer. In addition, the experiment also included 11 voices data of males with laryngeal cancer that cannot be analyzed by the MDVP, Only monosyllabic vowel /a/ was used as voice data. Since there were only 11 voices of laryngeal cancer patients that cannot be analyzed by the MDVP, those voices were used only for discrimination. This study examined the linear predictive cepstral coefficients (LPCC) and the met-frequency cepstral coefficients (MFCC) that are the two major cepstrum analysis methods in the area of acoustic recognition. Results : The results showed that this met frequency scaling process was effective in acoustic recognition but not useful for laryngeal cancer discrimination. Accordingly, the linear frequency cepstral coefficients (LFCC) that excluded the met frequency scaling from the MFCC was introduced. The LFCC showed more excellent discrimination activity rather than the MFCC in predictability of laryngeal cancer. Conclusion : In conclusion, the parameters applied in this study could discriminate accurately even the terminal laryngeal cancer whose periodicity is disturbed. Also it is thought that future studies on various classification algorithms and parameters representing pathophysiology of vocal cords will make it possible to discriminate benign laryngeal diseases as well, in addition to laryngeal cancer.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.280-289
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• 2021

The purpose of this study is to examine the effect of self-esteem on relationships between experience of discrimination and school life maladjustment. This study utilized 648 elementary school students who participated in Community Child Center Children's Panel Survey. Collected data was analyzed through correlation analysis and regression analysis using SPSS Win 21.0 statistical program. First, the experience of being discriminated and discriminating against others were positively related school life maladjustment but were negatively related self-esteem. Second, self-esteem had partially mediated school life maladjustment during discriminating against others. And self-esteem had totally mediated school life maladjustment during being discriminated. Based on these results, this study discusses practical implications for preventing discrimination of children attending community child center.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.723-738
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• 2020

In this paper, we study a method to discriminate between trend stationary and difference stationary processes. Since a crucial ingredient of this discrimination is to determine the existence of unit root, we can use a unit root testing strategy. So, we introduce a discrimination based on unit root testing and propose the method using the adaptive lasso. Our Monte Carlo simulation experiments show that the adaptive lasso improves the discrimination accuracy when the process is trend stationary, but has lower accuracy than unit root strategy where the process is difference stationary.

• The Korea Journal of Herbology
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• v.39 no.3
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• pp.23-35
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• 2024

Objective : In this study, we performed quantitative comparison on the content of 10 marker compounds in cinnamon barks from different species and found chemical discrimination between genuine Cinnamomum cassia and other Cinnamomum species (Non C. cassia). Methods : Cinnamon bark samples were extracted using the ultrasonication in 100% methanol for 30 minutes. The samples were analysed using high-performance liquid chromatography with statistical analysis. Results : The analytical method developed in this study met all validation criteria and was applied to the quantification of the 10 marker compounds in cinnamon bark samples. The major chemical discrimination of C. cassia were identified as low content of epicatechin and eugenol, and high contents of benzaldehyde, cinnamaldehyde and cinnamic acid compared to other Non C. cassia samples. Especially, among other compounds, the content of cinnamaldehyde was the highest in the C. cassia and Non C. cassia samples. The result of principal component analysis showed that the samples of C. cassia and Non C. cassia were clearly differentiated via benzaldehyde, cinnamaldehyde, cinnamic acid, eugenol, and epicatechin, which influenced on clustering C. cassia and Non C. cassia samples. Conclusion : C. cassia and Non C. cassia samples were chemically discriminated using the quantitative HPLC analysis. Based on this, it is possible to control the quality of herbal medicines containing Cinnamomi Cortex. It is necessary to further improve the accuracy of discrimination between C. cassia and Non C. cassia species to evaluate cinnamon bark quality.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.555-563
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• 2004

In classification and discrimination, we often face with incomplete group variable arising typically from many missing values and/or incredible cases. This paper suggests the use of K-means clustering for pre-adjusting incompleteness and in turn classification based on generalized statistical distance is performed. For illustrating the proposed procedure, simulation study is conducted comparatively with CART in data mining and traditional techniques which are ignoring incompleteness of group variable. Simulation study manifests that our methodology out-performs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.29-37
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• 2019

Textile quality management targets the physical properties of fabrics and the subjective discriminations of color and fitting. Color is the most representative quality factor that consumers can use to evaluate quality levels without any instruments. For this reason, quantification using a color discrimination device has been used for statistical quality management in the textile industry. However, small and medium-sized domestic textile manufacturers use only visual inspection for color discrimination. As a result, color discrimination is different based on the inspectors' individual tendencies and work procedures. In this research, we want to develop a textile industry-friendly quality management method, evaluating the possibility of rapid color discrimination using a digital imaging device, which is one of the office-automation instruments. The results show that an imaging process-based color discrimination method is highly correlated with conventional color discrimination instruments ($R^2=0.969$), and is also applicable to field discrimination of the manufacturing process, or for different lots. Moreover, it is possible to recognize quality management factors by analyzing color components, ${\Delta}L$, ${\Delta}a$, ${\Delta}b$. We hope that our rapid discrimination method will be a substitute technique for conventional color discrimination instruments via elaboration and optimization.