• 월간산업보건
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• s.74
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• pp.26-31
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• 1994

• Journal of Korea Technology Innovation Society
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• v.14 no.1
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• pp.22-39
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• 2011

This study examines the wage level from a viewpoint of major-job match as part of an analysis on the skill mismatch problem in 4-year college graduates. The empirical analysis explicitly incorporate the sample selection bias as an econometric problem not only suggested but merely introduced in the earlier studies. This study also set up a major-job match variable, which was usually handled as a binary variable for analytical convenience, as a polychotomous choice variable in selection equation as provided by the survey. In particular, it considered multi-cohort survey on graduates of the years 1982, 1992, and 2002 for the empirical analysis. As a result of empirical analysis, the wage premium of a major-job match was identified. This result was consistent after the consideration of a sample selection bias and also after modeling the major-job match variable as polychotomously selective. Through an analysis classified by the major, this study identified a relatively high wage premium among Social Science, Engineering, and Science majors. However, there was a difference in the effect of selection among these majors. Also, by assessing cohort effects this study found that the skill mismatch had rapidly progressed in 1992, while difference between 1992 and 2002 cohorts are insignificant. The analysis suggests that wage level is better understood within the context of both sample selection and major-job match, and regardless of model specification the major-job match affects wage strongly.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.320-334
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• 2018

The purpose of this study is to examine the effect of take-out food selection attributes of Korean restaurant on trust and customer satisfaction and to analyse the mediating effects of trust. Collected data were statistically analyzed by frequency analysis, factor analysis, reliability analysis, correlation analysis and covariance structure analysis using SPSS 22.0 and AMOS 22.0. The results of this study are as follows: First, selection attributes consists of safety, convenience, quality of food and economics. Among selection attributes, safety, convenience, quality of food and economics had a significant influence on trust. Second, among selection attributes, safety, convenience, quality of food and economics had a significant influence on customer satisfaction. Third, trust had a significant influence on customer satisfaction. Fourth, trust had a mediating effect between selection attributes and customer satisfaction. The conclusion section suggested strategic implications to induce selection attributes, trust and customer satisfaction based on the findings.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.765-775
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• 2012

The cross-validation is a popular method to select bandwidth in all types of kernel estimation. The maximum likelihood cross-validation, the least squares cross-validation and biased cross-validation have been proposed for bandwidth selection in kernel density estimation. In the case that the probability density function has a discontinuity point, Huh (2012) proposed a method of bandwidth selection using the maximum likelihood cross-validation. In this paper, two forms of cross-validation with the one-sided kernel function are proposed for bandwidth selection to estimate the location and jump size of the discontinuity point of density. These methods are motivated by the least squares cross-validation and the biased cross-validation. By simulated examples, the finite sample performances of two proposed methods with the one of Huh (2012) are compared.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.459-473
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• 2004

It has well known that an exhaustive search algorithm suggested by Breiman et. a1.(1984) has a trend to select the variable having relatively many possible splits as an splitting rule. We propose an algorithm to overcome this variable selection bias problem and then construct unbiased regression trees based on the algorithm. The proposed algorithm runs two steps of selecting a split variable and determining a split rule for binary split based on the split variable. Simulation studies were performed to compare the proposed algorithm with Breiman et a1.(1984)'s CART(Classification and Regression Tree) in terms of degree of variable selection bias, variable selection power, and MSE(Mean Squared Error). Also, we illustrate the proposed algorithm with real data sets.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.428-435
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• 2015

When I examined the corporate financing statistics in Korea, I have recognized that there are several trends of them. First, large enterprises use bank loan and direct financing like corporate bond as debt. Second, small and medium companies mainly use bank loan only. So I argue that there is sample selection bias in corporate debt choice and using sample selection methodology is more adequate when analysing the behavior in corporate debt choice. Therefore I have tested panel sample selection model, using the listed korean firm data from 1990 to 2013 and I have found that the panel sample selection model is appropriate.

• Journal of Labour Economics
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• v.22 no.2
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• pp.1-33
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• 1999

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.515-530
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• 2007

Stratum-specific likelihood ratio, which is ratio of the sensitivity to 1-the specificity in each stratum of the test, could be biased if the sensitivity and specificity of diagnostic test are affected by verification bias. Therefore, the optimal cutoff point determined by biased stratum-specific likelihood ratios is incorrect. In this study, we derived adjusted stratum-specific likelihood ratios using the adjusted sensitivity and specificity, and obtained the adjusted optimal cutoff point. The influence of the verification bias on the optimal cutoff point was described through the relation between adjusted and unadjusted stratum-specific likelihood ratios.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.375-380
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• 2022

The purpose of this study is to find out consumers' perception and meaning of convenience store convenience food by using big data. For this study, NNAVER and Daum analyzed news, intellectuals, blogs, cafes, intellectuals(tips), and web documents, and used 'convenience store convenience food' as keywords for data search. The data analysis period was selected as 3 years from January 1, 2019 to December 31, 2021. For data collection and analysis, frequency and matrix data were extracted using TEXTOM, and network analysis and visualization analysis were conducted using the NetDraw function of the UCINET 6 program. As a result, convenience store convenience foods were clustered into health, diversity, convenience, and economy according to consumers' selection attributes. It is expected to be the basis for the development of a new convenience menu that pursues convenience and convenience based on consumers' meaning of convenience store convenience foods such as appropriate prices, discount coupons, and events.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.973-975
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• 2005

스크립트 언어는 모듈의 결합이나 조정 등의 여러 목적으로 쓰이고 있는 언어이다. 스크립트 언어는 사용의 편리함과 높은 생산성으로 인해 널리 사용되고 있다. 그러나 현재 너무나 많은 스크립트 언어가 개발$\cdot$제시되고 있어 프로그래머가 스크립트 언어를 선택해야 할 때 어떤 언어를 선택해야 할지 판단하기 힘든 실정이다. 이에 본 논문에서는 프로그래밍 편의성 관점에서의 비교 기준을 제시하고 대표적인 스크립트 언어(VB script, Ruby, Perl, Python, Tcl, Lua, Groovy)를 이 기준에 따라 비교하였다. 비교 결과 각 비교 분야에 강점을 보이는 언어를 발견하였다. 본 논문의 결과는 스크립트 언어를 선택하는데 도움이 될 것이다.