• 응용통계연구
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• 제29권1호
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• pp.123-132
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• 2016

패널 시계열 자료를 소개하고 패널 1차 자기회귀 모형을 고려하였다. 패널 1차 자기회귀 모형의 동질성 검정을 위한 검정 통계량으로 Rao 통계량과 Wald 통계량을 제안하고, 그 극한분포를 제시하였다. 모의실험을 통해 패널의 수가 작을 때에도 패널의 수가 많을 때와 마찬가지로 두 검정 통계량의 분포가 카이제곱분포를 따르는 것을 확인하였으며, 패널의 수가 작을 때 Rao 통계량이 Wald 통계량 보다 더 우수한 검정력을 가짐을 모의실험을 통해 확인하였다. 시도별 월별 경제활동인구수 자료를 패널 1차 자기회귀 모형으로 적합하여 동질성 검정을 수행한 결과 동질성을 만족하였다. 동질성 검정을 만족한 자료를 시점별 평균을 이용하여 종합하고 이를 1차 자기회귀모형으로 적합하였다. 각각의 시도별로 적합한 모형과 시점별 평균을 이용하여 적합한 모형의 예측력을 비교한 결과 동질성 검정을 통과한 패널 1차 자기회귀모형의 경우 자료를 종합하여 적합한 모형의 예측력이 더 우수함을 확인하였다.

• 대한교통학회지
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• 제20권6호
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• pp.129-140
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• 2002

본 연구에서는 개인의 사회, 경제적 특성과 활동참여, 통행행동의 관계를 규명하기 위하여 개인의 사회 경제적 특성을 시간 변동 외생변수와, 시간 불변동 외생변수로 설정하고 개인의 활동참여와 통행행동에 관한 변수를 내생변수로 설정하여 모형을 구축하였다. 모형의 실효성을 검증하기 위하여 분석에 사용된 자료는 1991년, 1992년 미국 Puget Sound 지역의 Transportation Survey 자료를 이용하였으며, Panel 자료의 변수 간 복잡한 상호관계를 규명해 내기 위하여 Dynamic Structural Equation Model을 구축하였다. 활동참여와 통행행 동에 관한 10개의 내생변수와 개인의 사회, 경제적 특성인 10개의 외생변수를 사용하여 모형추정을 한 결과, 개인의 생계활동에 의해 유지활동과 여가활동은 시간적 제약을 받고, 여가활동은 유지활동에 제약을 받게 된다는 것을 알게 되었으며, 개인의 사회경제지표에 의해 영향을 받는 것으로 나타났다. 또한, 개인의 활동 패턴은 과거 연도의 각 활동 지속시간과 통행패턴에 영향을 받는 것으로 나타나 Panel 자료 분석의 필요성이 부각되었다. 본 연구의 결과로부터 보다 충실한 활동기반모형의 구축을 위해서는 Panel 자료의 구축의 필요성이 더욱 요구된다.

• 응용통계연구
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• 제27권7호
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• pp.1163-1170
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• 2014

간헐적인 패널 시계열 자료의 개념과 구조를 소개하고, 간헐적인 패널 시계열 자료의 모형으로 간헐적인 패널 1차 자기회귀 모형을 고려하였다. 간헐적인 패널 1차 자기회귀 모형의 동질성 검정을 위하여 Wald 검정통계량을 제안하고, 그 극한분포를 제시하였다. 또한 동질성이 만족되는 경우 시점 별 평균을 이용하여 종합한 자료로 모형을 적합하였다. 이 모형의 동질성 검정 통계량의 극한분포가 $^x2$분포에 잘 따르는지를 알아보기 위해 모의실험을 실시하고, 실제 자료 분석으로 지역별 월별 Mumps 자료에 간헐적인 패널 1차 자기회귀 모형을 적합하여 동질성 검정을 수행한 결과 동질성을 만족하였다. 동질성이 만족된 지역별 월별 Mumps 자료를 시점 별 평균을 이용하여 종합하고 1차 자기회귀 모형으로 적합하였다.

• 한국기계가공학회지
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• 제15권5호
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• pp.25-30
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• 2016

This study investigates the heat transfer due to a change in the shape of a radiator panel inside a computer. As with models of radiator panels, models have the same surface areas. As the gap between heat transfer surfaces in model 1 becomes wider than those in model 2, the heat transfer at model 1 becomes smoother than that of model 2. By comparing the cooling processes between models 1 and 2 with respect to natural convection, a maximum temperature of $47.432^{\circ}C$ at model 1 becomes lower than that of model 2, at $49.821^{\circ}C$. Within the radiator panel, model 1 has been shown to be more effective than model 2. Accordingly, these results can be effectively applied to the shape design of radiator panels to imbue them with smoother and faster heat transfer through the finite element method.

• Structural Engineering and Mechanics
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• 제30권2호
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• pp.211-223
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• 2008

A number of studies have suggested that the use of high ductile and high shear materials, such as Engineered Cementitious Composites (ECC) and High Performance Fiber Reinforced Cementitious Composites (HPFRCC), significantly enhances the shear capacity of structural elements, even with/without shear reinforcements. The present study emphasizes the development of a nonlinear model of shear behaviour of a HPFRCC panel for application to the seismic retrofit of reinforced concrete buildings. To model the shear behaviour of HPFRCC panels, the original Modified Compression Field Theory (MCFT) for conventional reinforced concrete panels has been newly revised for reinforced HPFRCC panels, and is referred to here as the HPFRCC-MCFT model. A series of experiments was conducted to assess the shear behaviour of HPFRCC panels subjected to pure shear, and the proposed shear model has been verified through an experiment involving panel elements under pure shear. The proposed shear model of a HPFRCC panel has been applied to the prediction of seismic retrofitted reinforced concrete buildings with in-filled HPFRCC panels. In retrofitted structures, the in-filled HPFRCC element is regarded as a shear spring element of a low-rise shear wall ignoring the flexural response, and reinforced concrete elements for beam or beam-column member are modelled by a finite plastic hinge zone model. An experimental study of reinforced concrete frames with in-filled HPFRCC panels was also carried out and the analysis model was verified with correlation studies of experimental results.

• Advances in Computational Design
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• 제1권3호
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• pp.235-251
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• 2016

We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.

• Steel and Composite Structures
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• 제20권4호
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• pp.851-867
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• 2016

Cruciform sections are an appropriate option for columns of orthogonal moment resisting frames for equal bending strength and stiffness about two main axes and the implementation is easier for continuity plates. These columns consist of two I-shaped sections, so that one of them is cut out in middle and two generated T-shaped sections be welded into I-shaped profile. Furthermore, in steel moment frames, unbalance moment at the beam-column connection leads to shear deformation in panel zone. Most of the obtained relations for panel zone strength derived from experimental and analytical results are on I-shaped columns with almost thin flanges. In this paper, a parametric study has been carried out using Finite Element Method (FEM) with effective parameters at the panel zone behavior. These parameters consist of column flange thickness, column web thickness, and thickness of continuity plates. Additionally, a mathematical model has been suggested to determine strength of cruciform column panel zone and has been shown its accuracy and efficiency.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.958-961
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• 2004

This paper presents a plant control panel model for the analysis. Seismic qualification analysis for the plant control panel is carried out to confirm the structural integrity under the seismic conditions represented by required response spectra(RRS). For the analysis finite element method(FEM) is used. And mode combinations are adopted to obtain the reliability of the spectrum analysis. The analysis results shows that the plant control panel system is designed as a dynamically rigid assembly, without any resonance frequency below 33Hz. The calculated stress of the plant control panel system is much less than yield stress of used steel.

• 한국컴퓨터정보학회논문지
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• 제22권10호
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• pp.145-150
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• 2017

This study aims to analyze panel data using OECD Health data of 34 years to examine how significant the inequality of income is to the inequality of health. The data was from OECD's pooled Health data of 32 countries from 1980 to 2013. The process of determining analysis model was as follows; First, through the descriptive statistics, we examined averages and standard deviation of variables. Second, Lagrange multiplier test has done. Third, through the F-test, we compared Least squares method and Fixed effect model. Lastly, by Hausman test, we determined proper model and examined effective factor using the model. As a result, rather than Pooled OLS Model, Fixed Effect Model was shown as effective in order to consider the characteristics of individual in the panel. The results are as follows: First, as relative poverty rate(${\beta}=-19.264$, p<.01) grows, people's life expectancy decreases. Second, as the rate of smoking(${\beta}=-.125$, p<.05) and the rate of unemployment (${\beta}=-.081$, p<.01) grows, people's life expectancy decreases. Third, as health expenditure(${\beta}=.414$, p<.01) shares more amount of GDP and as the number of hospital beds(${\beta}=-.190$, p<.05) grows, people's life expectancy increases.

• 농업과학연구
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• 제47권4호
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• pp.769-782
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• 2020

Interest in fruit and vegetables has increased due to changes in consumer consumption patterns, socioeconomic status, and family structure. This study determined the factors influencing the demand for fruit and vegetables (strawberries, paprika, tomatoes and cherry tomatoes) using a panel of Rural Development Administration household-level purchases from 2010 to 2018 and compared the ability to the prediction performance. An artificial neural network model was constructed, linking household characteristics with final food expenditure. Comparing the analysis results of the artificial neural network with the results of the panel model showed that the artificial neural network accurately predicted the pattern of the consumer panel data rather than the fixed effect model. In addition, the prediction for strawberries was found to be heavily affected by the number of families, retail places and income, while the prediction for paprika was largely affected by income, age and retail conditions. In the case of the prediction for tomatoes, they were greatly affected by age, income and place of purchase, and the prediction for cherry tomatoes was found to be affected by age, number of families and retail conditions. Therefore, a more accurate analysis of the consumer consumption pattern was possible through the artificial neural network model, which could be used as basic data for decision making.