• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.643-656
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• 2016

High dimensional data are frequently encountered in various fields where the number of variables is greater than the number of samples. It is usually necessary to select variables to estimate regression coefficients and avoid overfitting in high dimensional data. A penalized regression model simultaneously obtains variable selection and estimation of coefficients which makes them frequently used for high dimensional data. However, the penalized regression model also needs to select the optimal model by choosing a tuning parameter based on the model selection criterion. This study deals with the bias effect of LASSO regression for model selection criteria. We numerically describes the bias effect to the model selection criteria and apply the proposed correction to the identification of biomarkers for lung cancer based on gene expression data.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.7-15
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• 2006

A large sample can Provide more information about the Population. As the sample size Increases, analysts will be more confident about the survey results. On the other hand, the costs for survey will increase in time and manpower. Therefore, determination of the sample size is a trade-off between the required accuracy and the cost. In addition, permitted error and significance level should be considered. Sample size determination in surveys for O/D estimation is also connected with confidence of survey result. However, the past methods were usually too simple to consider confidence. Therefore, a new method for O/D surveys was Proposed and it was accurate enough, but it has too large sample size when we have current budget constraint. In this research, several minimum sample size determination methods for origin-destination survey under budget constraint were proposed. Each method decreased sample size, but has its own advantages. Selection of the sample size will depend on the study Purpose and budget constraint.

• Culinary science and hospitality research
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• v.18 no.1
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• pp.104-119
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• 2012

The purpose of this study is to suggest a way of the efficient operation of university foodservice through the Importance-Performance Analysis and examine a causal relationship between selection attributes and satisfaction. A survey was carried out in class, and after excluding 12(A University) and 20(B University) unusable cases which had an unacceptable level of missing data, 108 out of 120(A University) and 104 out of 124(B University) cases were used for analysis. As for A University, IPA showed that taste, variety, food cleanliness, table cleanliness, and tableware cleanliness were included in the concentrating efforts items. As for B University, IPA showed that taste, variety, and table cleanliness were in the concentrating efforts items that university foodservice managers should improve. Also, through t-test difference analysis on selection attributes of A University and B University in the research model, this study confirmed that both A University and B University displayed positive difference in personal services. And, through regression analysis, food quality had a positive influence on satisfaction.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.129-144
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• 2013

This research focuses on the relationship between influencing factors of users' smartphone application download and consumers' purchase. The results show that there is some difference between them. The factors influencing mobile application download include word of mouth, usability, ease of use, functionality, enjoyment, interoperability, design, and experience while the factors influencing purchase are word of mouth, usability, ease of use, cost, functionality, enjoyment, interoperability, design, experience. An experience factor impacts on both download and purchase. Specially, enjoyment, usability, and functionality have strong effects on purchase. We also found out that mobile application type such as hedonic or utilitarian application also impacts on purchasing application. For utilitarian application, functionality impacts on purchase intension. Therefore this fact suggests that it is very important to understand the accurate purchasing influence of its consumer when setting up the marketing strategy of mobile application.

• Environmental and Resource Economics Review
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• v.14 no.1
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• pp.75-100
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• 2005

This study attempts to empirically investigate the respondents' preference uncertainty involved in stating their willingness to pay (WTP). In the contingent valuation (CV) survey, we employed two approaches using two split samples. The respondents of one sample were given the opportunity to express intensity of preference through polychotomous choice (PC) WTP question. Those of the other sample were given a follow-up question of confidence measure (0~100%). By incorporating the two elicited degrees of preference uncertainty into examining the WTP responses, we take a comparison of the two approaches in terms of the goodness-of-fit of the examination and the efficiency of the mean WTP estimates. In comparing the DC model with the PC models, the DC model provides more efficient estimates. Moreover, the conventional DC model give some gains in terms of the goodness-of-fit and efficiency in comparing with the PC model most similar to this model. In this specific study, incorporating the preference uncertainty in DC model results greater estimates than conventional DC model without loss of goodness-of-fit and efficiency. This implies that the consideration of preference uncertainty on DC model could correct underestimating. We conclude that DC model provides a better estimate of WTP and preference uncertainty could be a critical information on the DC-CV estimation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.71-84
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• 1999

The randomness test for a sequence from an encription algorithm has an important role to make differences between plain and cipher text. Thus it is necessary to investigate and analyze the currently used randomness tests. Also in real time point of views it would be helpful to know a minimum sample size which gives discernment of plain and cipher text. In this paper we analyze the rate of successes for widely used nonparametric randomness tests to discern plain and cipher text through experiments. Moreover for given sample sizes an optimal sample size for each randomness test is proposed using the design of experiments.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.4-4
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• 2017

수문자료의 빈도해석은 자료의 독립성(independence)와 정상성(stationarity)를 가정하여 이뤄진다. 그러나 관측 수문자료에서 비정상성 현상이 발생하고 있다는 사실이 관측되면서 수문자료에 대한 비정상성 빈도해석에 대한 필요성도 커지고 있다. 본 연구의 목적은 수문자료의 빈도해석에서 가장 널리 사용되고 있는 Gumbel 및 GEV 분포에 대한 비정상성 빈도해석 모형을 개발하는 것으로, 이를 위해 비정상성 Gumbel과 GEV 모형의 매개변수를 시간에 따라 변하는 형태로 정의하였다. 비정상성 Gumbel 및 GEV 모형의 정확도를 알아보기 위해 비정상성 모형과정상성 모형을 이용하여 Monte Carlo 모의실험을 수행하였다. 모의실험은 다양한 조건의 재현기간, 표본크기, 매개변수 조건을 고려하여 수행되었다. 그 결과 비정상성 모형의 오차는 비교적 표본크기가 클 때 가장 작은 것으로 나타났다. 또한 복잡한 매개변수의 조합을 가지는 비정상성 모형은 모두 동일한 경향성을 가질 때 가장 작은 오차를 보이는 것으로 나타났다. 비정상성 GEV 모형의 경우는 확률수문량 산정에 음(-)의 형상 매개변수가 큰 영향을 끼치는 것으로 나타났다. 또한 본 연구에서는 비정상성 조건에서 다양하게 존재하는 비정상성 모형 중 어떠한 모형이 주어진 자료에 대해 가장 적절한 모형인지 결정하기 위해 모의실험을 수행하였다. 널리 적용되고 있는 AIC, BIC, likelihood ratio test에 대해 정상성 및 비정상성 Gumbel 모형을 이용하여 모의실험을 수행한 결과, AIC가 비정상성 모형 중 적정 모형 선택에 가장 효과적인 것으로 나타났다. 개발된 비정상성 Gumbel 및 GEV 모형의 적용성을 알아보기 위해 우리나라 연최대강우 자료에 적용한 결과, 위치 매개변수에 시간항을 고려하는 Gumbel 모형이 최적모형으로 가장 많이 선택되는 것으로 나타났다. 따라서 현재 우리나라의 연최대강우자료 중 경향성이 나타나는 자료에 대해서는 위치 매개변수가 시간에 따라 변하는 특성이 가장 많이 나타나고 있는 것으로 판단된다.

• Korea journal of population studies
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• v.11 no.1
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• pp.1-13
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• 1988

This study examines the sampling bias that may have resulted from the large number of missing observations. Despite well-designed and reliable sampling procedures, the observed sample values in DSFH(Demographic Survey on Changes in Family and Household Structure, Japan) included many missing observations. The head administerd survey method of DSFH resulted in a large number of missing observations regarding characteristics of elderly non-head parents and their children. In addition, the response probability of a particular item in DSFH significantly differs by characteristics of elderly parents and their children. Furthermore, missing observations of many items occurred simultaneously. This complex pattern of missing observations critically limits the ability to produce an unbiased analysis. First, the large number of missing observations is likely to cause a misleading estimate of the standard error. Even worse, the possible dependency of missing observations on their latent values is likely to produce biased estimates of covariates. Two models are employed to solve the possible inference biases. First, EM algorithm is used to infer the missing values based on the knowledge of the association between the observed values and other covariates. Second, a selection model was employed given the suspicion that the probability of missing observations of proximity depends on its unobserved outcome.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06b
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• pp.45-50
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• 1999

이진 영상의 압축은 디지털 도서관, 팩시밀리 전송, 문서 입출력 시스템과 같이 한정된 대역폭과 저장 공간을 가진 응용 분야에서 절실히 요구되고 있다. 현재 많은 영상 압축 알고리즘이 채택하고 있는 대역분할 기법을 문서와 같은 이진 영상의 압축에 적용한다면, 점진적 전송, 축소영상을 통한 빠른 검색 등의 장점을 얻을 수 있다. 그러나, 이진 영상 신호가 두 단계의 휘도 값을 가지므로, 이에 적합한 대역분할 방법과 산술부호기를 선택하여야 한다. 본 논문에서는 표본화-XOR 대역분할 기법을 선택하여, 알파벳 수의 증가를 막고 공간영역에서 국부적인 성질을 얻을 수 있다 또한, 넓은 단일-색 영역을 Zerotree로 대표하여 부호화 되는 신호의 수를 줄이고, 대역분할 구조에서 예측성의 저하를 막기 위한 적절한 조건화문맥과 새로운 부호를 선택한다. 이진 영상에 적합한 대역분할 방법과 산술부호기를 선택하여, 대역분할의 장점과 우수한 압축 성능을 달성할 수 있다.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.322-332
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• 2021

In this study, the relationship between Customer Satisfaction and Selection Attributes of Hotel Michelin Restaurant was studied. It was attempted to investigate the influence relationship on whether there is a moderating effect by introducing a variable into the Hotel Brand Image. Convenience sampling was used for customers who have recently experienced Hotel Michelin Restaurant, which is currently located in a hotel in Seoul. It has been held for about 60 days from July 1, 2020. The survey tool constructed through prior research was distributed to customers who have experienced the Michelin Restaurant commissioned by hotels in Seoul. 287 copies of the collected effective specimens were statistically processed using SPSS 22.0. As a result of the empirical analysis of this study, it was found that among the factors of Selection Attributes, physical environment, food quality, service quality, and convenience had a significant positive (+) effect between customer satisfaction. It was found that price fairness had no influence. Finally, it was found that there is a moderating effect on the physical environment and service quality variables by introducing the interaction variable between Selection Attributes and Customer Satisfaction.