• 무역학회지
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• 제42권1호
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• pp.217-236
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• 2017

본 연구는 2000~2014년 기간 동안 한국의 16개 지역에 유입된 IFDI가 지역성장에 미치는 영향을 동태적 패널모형인 시스템 GMM을 적용하여 분석하였다. 분석결과, 한국에 유입된 IFDI는 지역 내 경제성장 즉 자본형성, 고용창출, 수출확대 등에서 정(+)의 효과가 나타났으나, 수입은 부(-)의 효과가 발생하였다. 반면, 인적자본은 정(+)의 효과를 보였으나 통계적으로 유의하지 않았다. 한편 권역별로 유입된 IFDI의 성장효과를 살펴보면, 수도권과 동남권은 GRDP의 성장에 부(-)의 효과를 보인 반면, 대경권에서는 정(+)의 효과를 보였다. IFDI유입과 인적자본 간 보완관계에서도 유사하게 나타났다. 본 연구는 한국에 유입된 IFDI가 지역성장에 중요한 요인이지만, 지역 내 GRDP에 미치는 성장효과는 지역특성에 따라 차이가 존재한다는 것을 확인하였다. 따라서 지역 내 유입된 IFDI의 성장효과를 확대하기 위해서는 지역특성에 맞는 IFDI유치전략과 함께 산업구조개편이 시급하다고 판단된다.

• 한국도로학회논문집
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• 제14권5호
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• pp.1-9
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• 2012

PURPOSES: A viscoelastic axisymmetric finite element analysis code has been developed for stress analysis of asphalt pavement structures. METHODS: Generalized Maxwell Model (GMM) and 4-node isoparametric element were employed for finite element formulation. The code was developed using $C^{+}^{+}$ computer program language and named as KICTPAVE. For the verification of the developed code, a structural model of a pavement system was constructed. The structural model was composed of three layers: asphalt layer, crushed stone layer, and soil subgrade. Two types of analysis were considered for the verification: (1)elastic static analysis, (2)viscoelastic time-dependent analysis. For the elastic static analysis, linear elastic material model was assigned to all the layers, and a static load was applied to the structural model. For the viscoelastic time-dependent analysis, GMM and linear elastic material model were assigned to the asphalt layer and all the other layers respectively, and a cyclic loading condition was applied to the structural model. RESULTS: The stresses and deformations from KICTPAVE were compared with those from ABAQUS. The analysis results obtained from the two codes showed good agreement in time-dependent response of the element under the loading area as well as the surface deformation of asphalt layer, and horizontal and vertical stresses along the axisymmetric axis. CONCLUSIONS: The validity of KICTPAVE was confirmed by showing the agreement of the analysis results from the two codes.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.419-429
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• 2022

The aim of this research is to examine how globalization affects coffee exports in the producing countries. This research used secondary data obtained from the International Coffee Organization, Pen World Table, World Bank, Food and Agricultural Organization, and KoF Globalization Index to achieve its goals. We used secondary data from 1990 to 2018 from various foreign databases. The research used a two-step system GMM (sys-GMM) to analyze the effect of globalization on coffee export in twenty-four producing countries. We found that export lag, gross domestic product (GDP), exchange rate, and the political globalization index (PGI) positively and significantly impact coffee exports. Meanwhile, coffee exports were unaffected by the level of export prices and the human capital index. Surprisingly, the trade globalization index has a negative impact on coffee exports. This demonstrates the unpreparedness of coffee-producing countries to face tough competition in trade globalization. The political globalization index, the final variable, has a positive impact on exports. With the opening up of world politics, it seems that the environment of democracy in producing countries is increasing. As a result, governments in these countries have adopted a policy of aggressively supporting coffee exports.

• The Journal of Asian Finance, Economics and Business
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• 제9권2호
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• pp.81-92
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• 2022

The necessity for a theoretical explanation of the negative association between capital structure and company performance is identified in this study. By focusing on accounting metrics of business performance, this study is the first to investigate the moderating effects of firm size between these variables using logical reasoning. Due to the possibility of endogeneity, this study applies a two-step system GMM approach with data from 285 non-financial enterprises from PSX over a 21-year period. For robustness, we employed pooled OLS, fixed effect, and two-step difference GMM. Our data show that leverage has a detrimental impact on business performance, with size acting as a moderator in the same direction. Our analysis empirically supports some studies while refuting others due to inconsistent results in the literature, but no study has theoretically justified their negative link. We believe that because larger companies have more and easier access to capital markets, they focus primarily on the amount of return, even if the investment is inefficient in terms of the rate of return, but small businesses do not. As a result of this thinking, firm managers' performance suffers as a result of leverage.

• 지역연구
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• 제32권3호
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• pp.45-62
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• 2016

본 연구는 우리나라 16개 광역자치단체의 재정자립도 격차가 줄어들고 있는지 여부를 분석하고 그에 따른 해결책을 마련하기 위해 1998~2013년까지 총 16년간의 패널 데이터를 구축하고 Pooled OLS, 시스템 GMM 분석을 실시하였다. 재정자립도의 추이를 살펴본 결과, 시간이 지남에 따라 하향하는 추세를 보였으며, 광역자치단체를 대상으로 한 ${\beta}$-수렴 분석에서 절대적, 조건부 수렴 모두 재정자립도의 수렴이 나타났다. 또한 노인인구, 실질 GRDP, 인구밀도 변수를 통제한 조건부 분석 시 절대적 수렴보다 더 빠르게 수렴하는 것을 확인하였다. 특 광역시와 도를 나누어 분석한 결과, 특 광역시와 도 모두에서 재정자립도의 절대적, 조건부 수렴현상을 확인하였으며 도보다 특 광역시에서 빠르게 수렴이 진행되고 있었다. 단체별 지역 환경 및 재정운영의 차이에 따라서 재정자립도의 결정요인이 다를 것으로 판단하여 결정요인분석을 실시한 결과, 특 광역시의 경우, 3차 산업 취업자 비중 변수가 재정자립도에 긍정적인 효과를 가지며, 도에서 1인당 자동차 등록대수 변수는 재정자립도에 긍정적인 영향을 주고, 노인인구의 증가는 재정자립도에 부정적 영향을 주는 것으로 나타났다.

• 경제분석
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• 제17권4호
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• pp.30-51
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• 2011

무역자유화의 파급효과를 분석한 선행 연구의 대부분은 어떤 시점에 이루어진 무역자 유화가 해당연도 또는 그 다음연도와 같은 특정시점의 경제성과(economic performance)에만 영향을 미치는 것처럼 암묵적으로 가정하기 때문에 본질적으로 정태분석의 한계를 벗어나지 못한다. 이러한 선행연구와는 달리 본 연구는 무역자유화가 경제성과에 지속적으로 영향을 미칠 수 있는 동태적 실증분석모형을 설정하여 무역자유화의 누적효과(cumulative effects)를 분석한다. 또한 무역자유화의 파급효과에 대한 실증분석에서 제기되는 내생성(endogeneity)의 문제를 통제하기 위해 수준방정식과 차분방정식을 동시에 이용하는 동태적 패널 데이터 분석방법인 시스템 일반화적률법(system GMM)을 적용한다. 본 연구는 1988-2005년 기간의 한국 제조업을 대상으로 무역자유화의 정태 효과 및 동태적 누적효과를 추정하였는데, 무역자유화의 파급효과는 상당 기간 동안 지속되고, 동태적 누적효과는 정태효과에 비해 훨씬 더 크게 나타났다.

• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.181-187
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• 2021

The purpose of this study is to examine empirically the short- and long-run determinants of entrepreneurial activity in a sample of 15 the Middle East and North African economies between 2006 and 2018. More specifically, four groups of determinants are considered in the analysis, namely economic, demographic, business environment, and institutional. Given the autoregressive feature of the entrepreneurial activity process, a dynamic panel data model is estimated using the system GMM estimator. Findings reveal that unemployment, trade openness, population density, and economic freedom are the main drivers of new business creation in the short-run, while the cost and number of procedures to start a new business negatively affect entrepreneurship. In the long-run, the same findings hold true. Moreover, education and political stability and the absence of violence/terrorism positively affect entrepreneurial activity. Policy recommendations are accordingly designed.

• 융합경영연구
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• 제11권3호
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• pp.25-35
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• 2023

Purpose: This paper examines whether foreign aid influences public sector efficiency in policy areas of administration, education, and stability. Research design, data and methodology: The study uses panel data of 77 aid recipient developing countries over the period 2000-2020 and employs various panel data techniques to estimate. Results: We found that a percentage change in foreign aid increases administrative efficiency by 0.02 to 0.04 on average ceteris paribus in the short run. On the other hand, a percentage increase in foreign aid decreases education efficiency by 0.005 to 0.006 on average. While the impact of foreign aid on the policy area of stability is insignificant. Conclusions: The empirical results of this study have important implications for both donors and aid recipient countries. It suggests that to get positive influence from foreign aid, in the area of education and stability, the recipient countries need to increase accessibility of secondary schools with quality education especially; technical and vocational. Also, the donor should provide a minimum threshold amount of foreign aid to developing countries for reforming the institutions' capacity building.

• 정보처리학회논문지B
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• 제12B권1호
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• pp.9-16
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• 2005

본 논문은 얼굴인증 시스템 구현과 조명변화에 견인한 얼굴인증 방법들에 관한 연구에 초점을 둔다. 얼굴인증 시스템 구현을 위한 방법으로 PCA(Principal Component Analysis), GMM(Gaussian Mixture Models), 1차원 HMM(1 Dimensional Hidden Markov Models), 준 2차원 HMM(Pseudo 2 Dimensional Hidden Markov Models) 방법을 이용한다. 네 가지 다른 얼굴인증 방법들의 조명변화에 대한 성능비교 실험을 수행한다. 조명변화실험을 위해 얼굴이미지의 왼쪽에서 오른쪽으로 인공적인 조명효과(${\delta}=0,40,60,80$)를 준다. 얼굴특징벡터는 얼굴이미지에서 분할한 각 블록에 대한 2D DCT(2 Dimensional Discrete Cosine Transform) 계수를 이용하고 실험은 ORL(Olivetti Research Laboratory) 얼굴데이터베이스를 사용한다. 실험결과 모든 경우 조명변화 값이 커질수록 성능저하가 발생한다. 또한 조명변화가 없는 경우(${\delta}=0$) 준 2차원 HMM이 $2.54{\%}$, 1차원 HMM이 $3.18{\%}$, PCA가 $11.7{\%}$, GMM이 $13.38{\%}$의 EER(Equal Error Rate) 성능을 나타낸다. 조명변화가 없는 경우(${\delta}=0$) 1차원 HMM 방법이 PCA 방법보다 좋은 성능을 나타내지만 조명변화 ${\delta}{\geq}40$인 때에는 반대로 PCA 방법이 더 좋은 성능을 나타낸다. 마지막으로 준 2차원 HMM의 경우 조명변화에 관계없이 가장 좋은 EER성능을 나타낸다.

• 대한의생명과학회지
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• 제25권1호
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.