• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.382-384
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• 2005

소프트웨어 테스팅에서 테스트 스위트(suite)의 수를 줄이면서도 테스트 커버리지나 오류검출에 있어서 효과적인 방법을 찾기 위한 많은 연구가 시도되어 왔다. 안정성이 높은 설계가 되도록 설계 조건을 결정하기 위하여 제어인자들의 직교 배열을 사용하는 시험방법인 교호작용 테스팅 기법이 소프트웨어의 테스트에서도 효과가 매우 높다는 것이 실험으로 증명되고 있다. 소프트웨어는 상대적으로 몇 안 되는 조건들의 조합들로 오류가 발생할 가능성이 높다는 특징을 가지고 있다. 따라서, 파라미터 간 교호작용 강도 t를 갖는 t-way 테스팅을 통해 효과적으로 테스트 스위트를 줄이면서 많은 오류를 검출할 수 있다. 그러나 t값을 증가시키면 테스트 스위트의 수가 늘어난다는 단점이 발생한다. 또한, 어떠한 파라미터들이 서로 교호작용을 일으키는 것인지 알수 없는 상황을 가정한 단순한 교호작용 테스팅은 자칫 서로 관련 없는 파라미터들도 교호작용 테스팅에 참여하기 때문에 테스트의 낭비가 있을 수 있다는 단점이 있다. 이에, 본 논문에서는 소프트웨어의 입력과 출력간의 관계를 바탕으로 시스템 I-O관계도를 작성한 후, 이를 바탕으로 각 출력에 대한 교호작용을 일으킬 수 있는 파라미터를 중심으로 테스트 스위트를 생성하는 Selective Covering Array를 제안한다.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.163-177
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• 2000

다차원 범주형 자료를 표준화된 링차트로 구현하면, 자료에 적합한 모형이 갖는 일차교호작용의 존재 유무를 파악할 수 있으며 또한 표준화된 조건부 링챠트를 통하여 동시에 두 개 이상의 일차교호작용의 존재유무를 발견할 수 있는데 3차원 자료에서는 최대 두 개의 일차교호작용항을, 그리고 4차원 자료에서는 최대 4개의 일차교호작용항의 존재를 파악할 수 있다.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.177-185
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• 2014

Under bivariate normal distribution assumptions, the interaction and quadratic terms are needed in the logistic regression model with two predictors. However, depending on the correlation coefficient and the variances of two conditional distributions, the interaction and quadratic terms may not be necessary. Although the need for these terms can be determined by comparing the two scatter plots, it is not as useful for interaction terms. We explore the structure and usefulness of the 3-D residual plot as a tool for dealing with interaction in logistic regression models. If predictors have an interaction effect, a 3-D residual plot can show the effect. This is illustrated by simulated and real data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.751-757
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• 2012

An accelerated life test (ALT) is a test method that forces components to fail more quickly than they would under use conditions by applying higher overstresses. When two or more accelerating stresses are involved in an ALT, an interaction effect may occur. In previous studies, mostly ALTs without considering an interaction of accelerated stresses and accelerated life models were proposed. The life data obtained are extrapolated using a life-stress relationship to estimate the life distribution at use conditions. We use the general log-linear relationship to model the dependence of life in the Weibull distribution on stress. Therefore, this study suggests the acceleration factor model between the lives at use conditions and accelerated conditions by using mechanical component life data considering an interaction effect. Further, the accelerated life test method and acceleration factor model proposed in this paper will be the basis for adopting an accelerated life test with accelerated stress interactions.

• Journal of Life Science
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• v.19 no.2
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• pp.271-276
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• 2009

The Purpose of this study was to examine the effects of boxing aerobic training on resting heart rate variability (HRV) in females. The subjects for this study were performed 16 female college students that aged 19-23. The subjects were divided into two groups; boxing aerobic exercise group (9 students) and control group (7 students). Boxing aerobic training program was performed three times a week for twelve weeks with $VO_{2max}$ 60-80% exercise intensity. The results of this study were following; 1. Mean HRT (mean heart rate) had no signigicant difference among the groups and exercise time. 2. SDNN (standard deviation of the normal to normal interval) had no significant difference among the group and exercise time. 3. RMS-SD (square root of the mean squared differences of successive normal to normal interval) had no significant difference among the groups and exercise time. 4. TP (total power) had no significant difference among the groups and exercise time. 5. LF (low frequency) had no significant difference among the groups and exercise time. 6. HF (high frequency) had no significant difference among the groups and exercise time. 7. LF/HF (low frequence/high frequency ratio) had no significant difference among the groups and exercise time. 8. VLF (very low frequency) had no significant difference among the groups and exercise time.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.201-211
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• 1994

Ignoring interaction effects has been pointed out to be one of serious drawbacks in analysis of the parameter designs which are constructed by using orthogonal arrays. In this paper a detecting procedure of influential 2-factor inteactions with minimum expeimental runs is described, when each contrl factor has two levels. The presented method is based on the near orthogonal arrays which are very similar to orthogonal arrays in the statistical structure. And those arrarys are the same as trace-optimal balanced saturated two-level fractional factorial designs of resolution V.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1067-1078
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• 2018

Water resources projection typically consists of several stages including emission scenarios, global circulation models (GCMs), downscaling techniques, and hydrological models, and each stage is a source of total uncertainty in water resources projection. Several studies proposed methods to quantify the relative contribution of each stage to total uncertainty, and we call such analysis uncertainty decomposition. Uncertainty decomposition enables us to investigate the stages yielding large uncertainties and to establish the uncertainty reduction plan that reflects them. Interactions between stages is one of the important issues to be considered in uncertainty decomposition. This study suggests a new uncertainty decomposition method considering interaction effect. The proposed method has an advantage of decomposing the total uncertainty to the uncertainty from each stage considering both the main and interactions effects. We apply the proposed method to streamflow projection for Chungju Dam basin. The results show that the uncertainties from the main effects are larger than the uncertainties from interaction effects in both summer and winter. Using the proposed uncertainty decomposition method, we show that the GCM stage is the largest source of the total uncertainty in summer and the downscaling technique stage is the one in winter among the following four stages: emission scenarios, GCMs, downscaling techniques, and hydrological models.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.593-601
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• 2013

We often need to include categorial variables as explanatory variables in regression models. The categorial variables in regression models can be quantified through dummy variables. In this study, we provide an education tool using Excel VBA for displaying regression lines along with test results for regression models with a continuous explanatory variable and one or two categorical explanatory variables. The regression lines with test results are provided step by step for the model(s) with interaction(s), the model(s) without interaction(s) but with dummy variables, and the model without dummy variable(s). With this tool, we can easily understand the meaning of dummy variables and interaction effect through graphics and further decide which model is more suited to the data on hand.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.633-644
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• 1998

혼합설계의 교호작용에 대한 F 검정이 유효하려면 다표본 구형성(multisample sphericity) 가정과 다변량 정규분포 가정이 만족되어야 한다. F 검정을 실시하기 위한 가정들이 위반된 조건하에서 혼합설계의 교호작용에 대한 검정법들의 1종오류가 비교되었다. 비교된 검정법들은 (1) F 검정(F), (2) 절사평균을 사용한 F 검정($F_T$)(3)$\varepsilon$-수정 F 검정($\varepsilon)$(4) 절사평균을 사용한 $\varepsilon$-수정 F 검정$(\varepsilon_T$) (5) CIGA검정(CIGA), (6) 절사평균을 사용한 CIGA검정($CIGA_T$)이었다. 결과는 CIGA와 $CIGA_T$는 1종오류를 대체로 잘 관리하나, F검정들과 ($\varepsilon$)검정들은 일부 조건에서 아주 작은 1종오류나 아주 큰 1종오류를 갖는 것으로 나타났다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.186-187
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• 2006

본 논문에서는 PECVD를 이용하여 증착시킨 실리콘 산화막에 영향을 주는 파라미터 입력에 따른 박막의 특성을 평가하기 위하여 먼저 통계적 실험계획을 통해 산화막 특성에 유의한 영향을 미치는 요인을 분석하고, 분석된 결과를 이용하여 가장 유의한 교호작용을 신경망 모델링에서 입력파라미터로 포함시킴으로서 교호작용을 고려하지 않은 경우와의 학습결과를 비교하여 두가지 모델링 방법 중 교호작용을 고려한 신경망 모델의 경우가 PECVD의 물리적 현상을 더 명확히 설명할 수 있음을 확인했다.