• Informatization Policy
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• v.18 no.4
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• pp.42-58
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• 2011

This paper starts from one question: what are the key factors of the web accessibility policy, which is significant for realizing equity in the web and enhancing human dignity in the information society. To find significant factors for complying with web accessibility, this paper analyzes panel data of 16 Korean local governments (for five years: 2004-2009) according to the research design which is based on the demand and supply balance model and consists of four variables : 'legal and institutional environment (including legal infrastructure)', 'financial foundation (fiscal self-reliance ratio)', 'policy inputs (amount of imformatization budget, employee of information experts)'and 'policy demand (internet usage rate, the number of disabled people and elderly people)'. From the results of this study, this paper can explain the mechanism and impact factors on the web accessibility policy of Korean local governments. Some factors are critical to improve web accessibility: (1) the importance of policy demand, (2) the importance of policy inputs, (3) the importance of legal and institutional environment. Finally, this paper concludes with some suggestions to enhance the web accessibility capacity for Korean local governments: (1) improve awareness on web accessibility, (2) develop a standard and invest R&D on web accessibility, (3) foster experts in web accessibility.

• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.519-542
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• 2012

In this paper, we empirically analyzed whether carbon leakage really happened in EU by comparing before and after the period of EU ETS. We regarded foreign direct investment outflows as indicator of carbon leakage and analyzed panel regression between production cost including environment cost and this FDI variable. Also we consider foreign market potential to analyze market oriented FDI. According to this analysis, carbon leakage was observed in some models for manufacturing industry. However carbon leakage did not prove consistently in a variety of models and it is hard to speak carbon leakage was happened in EU ETS. Notwithstanding relatively short time series of data, in the view of the fact that carbon leakage was tested in some models, Korea also should keep in mind the possibility of carbon leakage and design emission trading scheme.

• Management & Information Systems Review
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• v.37 no.2
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• pp.209-233
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• 2018

This study investigates the question of how political and economic factors may affect the export of renewable energy technologies. The relationships are tested using panel data for 19 OECD member countries over the period 1992-2012. Before establishing the empirical model, the current study checks the characteristics of the panel data, which includes various panel framework analyses, such as tests for the presence of normality, structural breaks, first-order autocorrelation, heteroscedasticity, cross-sectional dependence, panel unit-root. From the panel framework analyses, a dynamic panel model is established to test the relationship between the variables examined in this study. In order to reduce the bias of the estimation of the dynamic panel model and obtain efficient parameters, this study uses the bias-corrected least square dummy variable(LSDVC) estimator to estimate the empirical model. The results of this study show that governmental policies expressed as coercive pressure and market size positively affect the export growth of renewable energy technologies. However, public pressure and traditional energy industry have no significant effects on export performance. Policy implications are presented based on the results of this study.

• The Journal of Bigdata
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• v.5 no.2
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• pp.135-143
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• 2020

This paper proposes a pre-processing method and a dimensional reduction method in the analysis of shopping carts where there are many correlations between variables when dividing the types of consumers in the agri-food consumer panel data. Cluster analysis is a widely used method for dividing observational objects into several clusters in multivariate data. However, cluster analysis through dimensional reduction may be more effective when several variables are related. In this paper, the food consumption data surveyed of 1,987 households was clustered using the K-means method, and 17 variables were re-selected to divide it into the clusters. Principal component analysis and factor analysis were compared as the solution for multicollinearity problems and as the way to reduce dimensions for clustering. In this study, both principal component analysis and factor analysis reduced the dataset into two dimensions. Although the principal component analysis divided the dataset into three clusters, it did not seem that the difference among the characteristics of the cluster appeared well. However, the characteristics of the clusters in the consumption pattern were well distinguished under the factor analysis method.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.942-944
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• 2017

High-speed vehicles are subjected to complex loads, such as acoustic pressure from the engine at launch and aerodynamic heating and aerodynamic pressure during flight. A thermal protection system panel is required to protect internal systems such as the fuel tank of the vehicle from the external environment. This study defines analytical models for heat transfer and thermal structure characteristics of the thermal protection system panel. Furthermore, the study performed parameters analysis to achieve the thermal structural integrity and to make it lighter.

• Korea Real Estate Review
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• v.27 no.1
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• pp.33-44
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• 2017

The continuously rising housing prices in major Chinese cities have raised question about whether inflation is the main reason to drive up housing price to skyrocket in recent years. Based on the provincial panel dataset of China from 2006-2014, this paper investigates the impact of inflation on Chinese housing markets within the frameworks of both static and dynamic panel data models. Our empirical results show evidence that inflation has indeed been a main force of accumulating housing bubbles in these housing markets, especially in eastern region of China. We also find an interesting phenomenon in which Chinese housing bubble is, to a certain extent, affected by market self-adjustment mechanism.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.388-395
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• 2015

The purpose of this study is to estimate change of productivity of information and technology industry and to induce policy implications. The method of analysis is panel data analysis based on 11 Korean information and technology industry cross-section and 8 years time series. The result of estimate shows that producitivity of labor and capital and information and technology industry is positive, total factor productivity of information and technology industry is also positive. but total factor productivity decreased after 2008. In addition, the productivity of labor was increased, but the productivity of capital input was decreased. It means that the productivity of Korean information and technology industry was not improved despite increasing of labor and capital investment.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.89-112
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• 2016

In this paper, as a determining factor of the Environment Kuznets Curve hypothesis, we analyzed the impact of technological innovation. In this paper, in order to empirically validate the role of technological innovation to an inverted U-shaped Environments Kuznets Curve hypothesis, we utilize the 2SLS considering relationship between R&D and the GDP per capita. Also, using the Panel VAR (Panel Vector Auto Regression) model to analyze with what time lag R&D per capita has impact on the emissions of greenhouse gases per capita. Empirical results show that R&D per capita(proxy of innovation) is a important factor to explain Environmental Kuznets Curve hypothesis, and that the external shock such as R&D per capita reduces greenhouse gas emissions per capita with about 3 time lag.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.253-261
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• 2001

화장품의 사용감은 개개인에 따라 다양한 기호를 나타내며 상대적이고 감성적인 개념들이 우선하게 된다. 이러한 관능특성들을 보다 객관적이며, 과학적으로 고찰하고자 하는 연구분야가 바로 관능평가이다. 본 연구에서는 메이크업 단계 중 베이스 메이크업에 속하는 제품인 파운데이션의 관능 특성을 보다 객관적이며 신뢰성 있게 평가, 분석하는 전문패널 평가 시스템을 구축하기 위하여 사내 여성을 대상으로 discriminative 및 descriptive 테스트를 실시하였다. 이를 통해 적합한 패널을 선정하였고 일정하게 규정된 일련의 교육과정들을 통해 패널을 훈련시킴으로써 베이스 메이크업 전문 패널 평가 시스템을 구축하였다. 그 후 파운데이션에 대해 질감별 제품을 평가하도록 한 후 이러한 방법으로 수집된 데이터를 신뢰성 있는 통계적 분석법을 이용하여 제품의 사용감 특성이 위치되니 2차원적 공간영역과 제품별 사용감의 특성을 분석하였다. 그 후 분석된 결과를 자사 브랜드 메이크업 라인의 파운데이션 제품에 응용하여 제품을 차별화 시키도록 설계하고 질감별 특징적 사용감과 적합한 특성강도를 제시한 후 이를 나타내는 처방의 제품을 결정하였다. 최종적으로 출시된 제품을 실제 소비자들을 통해 기호형 관능평가를 다시 한번 실시하였으며, 그 결과 실제 느끼는 사용감각 특성과 상품개발 계획 시 소구하고자 했던 관능특성이 일치하게 나타나 사용감 설계의 객관성을 검증하였다. 따라서, 본 연구는 이와 같은 결과를 통해 관능평가를 제품개발에 응용한 활용방안으로 보고자 하였다.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.103-113
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• 2014

This study designed and implemented a query model for consecutive analyses of dynamic multivariate graph data. First, the query model consists of two procedures; setting the discriminant function, and determining an alteration method. Second, the query model was implemented as a query system that consists of a query panel, a graph visualization panel, and a property panel. A Node-Link Diagram and the Force-Directed Graph Drawing algorithm were used for the visualization of the graph. The results of the queries are visually presented through the graph visualization panel. Finally, this study used the data of worldwide import & export data of small arms to verify our model. The significance of this research is in the fact that, through the model which is able to conduct consecutive analyses on dynamic graph data, it helps overcome the limitations of previous models which can only perform discrete analysis on dynamic data. This research is expected to contribute to future studies such as online decision making and complex network analysis, that use dynamic graph models.