• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.37-60
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• 1992

This paper applies a Structural VAR approach to a 4 variable system in real GNP, M2, GNP deflator and nominal monthly earnings, disentangling 4 structural shocks, i.e., aggregate demand and supply shocks, wage pushes and various forms of regulations reinforced especially during stabilization process. Preliminary diagnostic tests confirm that the log level of each time series has at least one unit root, though the evidence is somewhat ambiguous for real GNP. One co-integration relationship is found among 4 variables, while no co-integration is found in a subsystem consisting of nomina) variables. The absence of co-integration among nominal variables strongly suggested that money is not neutral even in the long-run. The reduced form is estimated and the structural form is recovered using 6 additional identifying restrictions. Recovered structural shocks are able to capture main episodes of past 20 years, ranging from first and second oil shocks, to strong stabilization policy of early 80's and rapid wage hikes of late 80's. Overall responses of the economy to each structural shock are usually consistent with the standard Keynesian predictions, though some responses seem to be specific to Korean economic environment.

• Advances in nano research
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• v.12 no.1
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• pp.81-99
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• 2022

The aim of current work is to evaluate thermo-electrical characteristics of graphene nanoplatelets Reinforced Composite (GNPRC) coupled with magneto-electro-elastic (MEE) face sheet. In this regard, a cylindrical smart nanocomposite made of GNPRC with an external MEE layer is considered. The bonding between the layers are assumed to be perfect. Because of the layer nature of the structure, the material characteristics of the whole structure is regarded as graded. Both mechanical and thermal boundary conditions are applied to this structure. The main objective of this work is to determine critical temperature and critical voltage as a function of thermal condition, support type, GNP weight fraction, and MEE thickness. The governing equation of the multilayer nanocomposites cylindrical shell is derived. The generalized differential quadrature method (GDQM) is employed to numerically solve the differential equations. This method is integrated with Deep Learning Network (DNN) with ADADELTA optimizer to determine the critical conditions of the current sandwich structure. This the first time that effects of several conditions including surrounding temperature, MEE layer thickness, and pattern of the layers of the GNPRC is investigated on two main parameters critical temperature and critical voltage of the nanostructure. Furthermore, Maxwell equation is derived for modeling of the MEE. The outcome reveals that MEE layer, temperature change, GNP weight function, and GNP distribution patterns GNP weight function have significant influence on the critical temperature and voltage of cylindrical shell made from GNP nanocomposites core with MEE face sheet on outer of the shell.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.5 no.1
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• pp.51-63
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• 1997

Generally, air freight forecasting model used to major factor GNP(GDP), Yield, Exchange rate, as its independent variables. We studied about the factors that affect to Air Freight in Korea, and we found six affective variables. Those are GNP, Exchange rate, Flight routes, Flight numbers, Sum of dollars Export and import. To find the relationship between the Air Freight and GNP, Exchange rate, Flight routes, Flight numbers, Sum of dollars Export and import we used regression analysis. Through the regression analysis, we found some problems in the model. There are collieneraities between the variables, so we took the variables selection model to choose the best affective variables of air cargo. We have defined the the Korean air freight forecasting model with two variables and forecast far the $1996{\sim}2010$ period were made by using this model.

• Korean journal of food and cookery science
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• v.6 no.4 s.13
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• pp.41-50
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• 1990

This study aimed to investigate the change in food balance and dietary patterns, caused by the growth of per capita GNP during $1962{\sim}1987$. For the purpose of this analysis, ordinary least square (OLS) was adopted. Per capita GNP was independent variable and the other factors dependent variables. The other factors included Engel coefficient, food supply, energy supply, nutrient intake and the ratio of self-supply of food. The result revealed that the some variables have (+) correlation, the some variables (-) correlation and the other variables no correlation with per capita GNP. If forecasting models are designed with these results, it will be helpful for national health and nutrition, food balance and disease prevention.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.59-61
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• 2002

우리나라는 1960년대 이후 지속적인 경제 성장을 하여 1995년에는 1인당 국민총생산(GNP)이 ＄10,000를 넘어서게 되었다. 그러나 1997년 말 IMF 경제위기의 영향으로 1998년에는 1990년대 초반의 GNP도 못 미치는 ＄6,744로 하락하게 되었으며, 전년대비 -35% 라는 최악의 GNP 하락을 초래하였다. (그림 1, 2. 참조) 이에 IMF 경제위기가 우리나라 대기오염물질의 배출량에는 어떠한 영향을 주었는지 살펴보고자 하였다. (중략)

• Carbon letters
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• v.16 no.1
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• pp.34-40
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• 2015

In this study, in order to improve the thermal and electrical properties of epoxy/graphene nanoplatelets (GNPs), surface modifications of GNPs are conducted using silane coupling agents. Three silane coupling agents, i.e. 2-(3,4-epoxycyclohexyl)-ethyltrimethoxysilane (ETMOS), 3-glycidoxypropyltriethoxysilane (GPTS), and 3-glycidoxypropyltrimethoxysilane (GPTMS), were used. Among theses, GPTMS exhibits the best modification performance for fabricating GNP-incorporated epoxy composites. The effect of the silanization is evaluated using transmission electron microscopy (TEM), scanning electron microscopy, thermogravimetric analysis, and energy dispersive X-ray spectroscopy. The electrical and thermal conductivities are characterized. The epoxy/silanized GNPs exhibits higher thermal and electrical properties than the epoxy/raw GNPs due to the improved dispersion state of the GNPs in the epoxy matrix. The TEM microphotographs and Turbiscan data demonstrate that the silane molecules grafted onto the GNP surface improve the GNP dispersion in the epoxy.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.11a
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• pp.153-154
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• 2017

Graphene is a nanomaterial and is known to have very high mechanical strength, thermal and electrical properties. However, graphene is known to be difficult to disperse among carbon-based materials due to van der Waals force. In this study, to solve the dispersion problem of graphene nanoplatelet, oxidized graphene nanoplatelet was prepared by oxidizing GNP in nitric acid. The prepared GO was dispersed in ethanol and distilled water before incorporation into the epoxy paint to confirm dispersibility. In addition, GNP/Epoxy and GO/Epoxy tensile specimens were prepared by mixing GNP and GO at 0.1, 0.3, 0.5 and 1.0 wt.% In epoxy coatings and tensile stress-strain characteristics were investigated.

• Structural Engineering and Mechanics
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• v.90 no.4
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• pp.403-415
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• 2024

We looked at how the damping qualities of epoxy composites changed when different amounts of graphite nanoplatelets (GNP) were added, from 0% to 6% by weight. A mix of free and forced vibration tests helped us find the key GNP content that makes the damper ability better the most. We also created a Representative Volume Element (RVE) model to guess how the alloys would behave mechanically and checked these models against testing data. An Artificial Neural Network (ANN) was also used to guess how these compounds would react to motion. With proper hyperparameter tweaking, the ANN model showed good correlation (R²=0.98) with actual data, indicating its ability to predict complex material behavior. Combining these methods shows how GNPs impact epoxy composite mechanical properties and how machine learning might improve material design. We show how adding GNPs to epoxy composites may considerably reduce vibration. These materials may be used in industries that value vibration damping.

• Journal of the Korean Electrochemical Society
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• v.10 no.1
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• pp.7-13
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• 2007

We synthesized and investigated $La_{0.75}Sr_{0.25}FeO_3$ by Glycine Nitrate Process(GNP) method used as cathode materials for SOFC(solid oxide fuel cell). Optimized amount of glycine is 3.17 mol. ICP elemental composition analysis indicated that the stoichiometry of the synthesized powders have nearly nominal values. SEM images and XRD patterns reveal that the synthesized powder has uniform size distribution and high degree of crystallinity. The sample powders were isostatically pressed to form a pellet. The green body was sintered at $1200^{\circ}C$ and the relative density of the sintered specimens were measured by Archimedes mettled. We measured electrochemical performance of LSF by AC impedance spectroscopy. Resistance of LSF shows lower value than that of LSM throughout all temperature region. The anode-supported solid oxide fuel cell showed a performance of $342mW/cm^2(0.7V,\;488mA/cm^2)$ at $750^{\circ}C$. The electrochemical characteristics of the single cell were examined by at impedance method.

• Korea journal of population studies
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• v.26 no.2
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• pp.33-62
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• 2003

The purpose of this study is to analyze the relative importance of three factor -socioeconomic development, public health development, egalitarian nature of socioeconomic development- affecting mortality declines. Infant mortality rate and life expectancy at birth are used as the mortality index, that is the dependent variables, while GNP is used as the indicator of socioeconomic development, primary school enrollment ratio of female as the indicator of egalitarian nature of socioeconomic development, population per hospital bed as the indicator of public health. The data of these variables are collected two time-periods -before 1970 and during 1970-1980- over 50 countries. The explanatory data analysis is used as the statistical technique. We can find whether the relationship between dependent variable and independent variables are linear or nonlinear, and which case is the influential case in our model. The main results of this study are followings. First, the association between infant mortality rates and four indices are not linear. The most important factor explaining the variation of infant mortality is GNP, while primary enrollment of female is the second and GINI is the third important factor. However, population per hospital bed does not have a significant effect on the infant mortality rates in this study. Second, life expectancy at birth is log-linearly related to GNP. Unlike infant mortality rates, the most important factor explaining the variation of life expectance at birth is women's education and the next important factor GNP, and then the third one GINI. But, still population per hospital bed is not significantly related to the variation of life expectance in this study.