• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.399-411
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• 2008

Today, the statistical survey has been carried out variously for the decision-making and administration of the organization. We use the different items in the statistical survey according to the purpose of study. Currently, Gyeongnam province is executing the social index survey to the provincials every year. But, this survey has the limit of the analysis as execution of the different survey per 3 year cycles. The solution for this problem is data fusion technique. Data fusion is generally defined as the use of techniques that collect to combine data including multiple sources in order to raise the quality of information. But, data fusion doesn't mean the ultimate result. Therefor, efficient analysis for the fused data is also important. In this study, we suggest the application methodology of neural network by latent variable through the fused data in statistical survey.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1269-1276
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• 2004

The Parameter Estimation for software existing reliability models, Goel-Okumoto, Yamada-Ohba-Osaki model was reviewed and Rayleigh model based on Rayleigh distribution was studied. In this paper, we discusses comparison of parameter estimation using maximum likelihood estimator and Bayesian estimation based on Gibbs sampling to analysis of the estimator' pattern. Model selection based on sum of the squared errors and Braun statistic, for the sake of efficient model, was employed. A numerical example was illustrated using real data. The current areas and models of Superposition, mixture for future development are also employed.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.357-370
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• 2022

In this paper, Tobit and Heckit models are introduced. These models have been used for analyzing censored data. Censoring occurs at a specific point and a large number of observations are distributed with a positive probability at a certain point. Censoring can occur due to observing limitation or exogenous variables. Tobit and Heckit models are used to correct sample selection bias, which can occur when an ordinary linear regression model is fitted to censored data. However, the difference between the two models is not clearly accounted for; hence, they have often been used interchangeably. Therefore, the suitability of the models was validated through simulated data, and demonstrated through real data. As the result, it was confirmed that both Tobit and Heckit models are well-fitted to the data censored due to observing limitation, although Tobit model was fitted parsimoniously. In contrast, only Heckit model is well-fitted to the data censored due to exogenous variables.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.197-205
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• 2023

This study is to apply the Havruta teaching-learning method to college students' major classes and analyze the relationship between the effectiveness evaluation of communication skills and sub-factors using a structural equation model. As a result of the study, the communication ability score was different before and after Havruta teaching-learning, and it was found that after Havruta teaching-learning was higher than before Havruta teaching-learning. The path effect was found to be significant in all of the total, direct, and indirect effects among latent variables, except for the relationship between interpretation ability, role-playing ability, and goal-setting ability in the direct effect. In this study, it was found that the Havruta teaching-learning method not only improves creativity and thinking ability, but also improves self-directed learning ability. In addition, it was reconfirmed that it is a teaching-learning method that can develop social skills and communication skills as well as problem-solving skills while experiencing opinions different from one's own. As a result, research on a thorough student-centered teaching-learning method suitable for the Homo Machina era must be continued and its application in the educational field must be implemented.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2953-2966
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• 2018

Housing prices are closely related to various variables that indicate macroeconomic conditions. In this paper, empirical analysis based on data is performed referring to previous studies. Focusing on the policy interest rate among the factors affecting the housing price, the non-linear impulse responses of other variables to the interest rate shock are analyzed. Using the random forest algorithm, the variable importance scores of the macroeconomic variables presented in the previous studies are calculated. After selecting the variables through this process, the impulse responses are calculated using a model that can capture non-linearity. According to the model, the responses of housing prices to the policy rate is only significant when the rate is raised. Especially, the impulse response is amplified when the shock increases due to the non-linear characteristics that can not be captured by the traditional VAR methodology. The analysis results suggest that the interest rate as a policy instrument should be approached from a more cautious perspective.

• 한국벤처창업학회:학술대회논문집
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• 2017.04a
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• pp.63-63
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• 2017

국내 경제상황의 어려움으로 인한 기업의 고용감소와 그에 따른 일자리 부족 때문에 청년 실업문제가 사회적 이슈로 대두되었고, 일자리에 대한 취업의 다른 대안으로 창업에 대한 관심이 고조되고 있다. 청년 일자리를 해결하기 위해서는 청년층의 중심이라 할 수 있는 대학생의 창업을 활성화할 필요가 있고, 이를 위해서는 다양한 분야를 전공하고 있는 대학생의 학문적 특성을 고려하여 대학생의 창업의도를 높이는 것이 필요하다. 해외의 경우 다양한 계층에 대한 연구를 통해 계층별 창업의도에 미치는 영향요인을 파악하고 이를 관련 정책 및 교육에 반영함으로써 창업의도를 지속적으로 향상시키고 있다. 본 논문에서는 현재 교양과목으로 이루어진 창업강좌를 수강하는 국내 대학생들이 전공에 따른 창업의지에 대한 생각을 살펴보고자 하며, 그들의 창업의지를 보다 고취시키기 위해 필요한 방안들을 도출하고자 한다. 연구방법으로 국내 창업교육을 받고 있는 대학생을 대상으로 설문조사를 진행하였고, 설문조사결과에 대한 신뢰성 및 타당성을 분석한 후 구조방정식을 통해 본 연구에서 설계한 가설을 검증하며, 가설 검증 결과를 분석하게 된다. 독립변수로는 잠재적 창업가의 특성을 파악할 수 있는 개인적 특성 요인(성취욕구, 위험감수성향, 혁신성), 환경적인식 요인(네트워크, 정부의 창업지원제도), 교육적인식 요인(창업강좌, 창업멘토링)을 선정하였고, 조절변수로서 대학생 전공(이공계와 비이공계), 그리고 종속변수로서 창업의지를 설정하여 연구모형을 구성했다. 본 연구를 통해 대학생들의 전공(이공계와 비이공계)에 따른 창업의지 확인과 함께 창업교육에 대한 교과목 설계, 목표설정, 학습 방향 및 방법들을 보완할 수 있는 기회를 얻을 수 있음을 제시하고자 한다.

• Korean Chemical Engineering Research
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• v.52 no.4
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• pp.467-474
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• 2014

Preliminary design in chemical process furnishes economic feasibility through calculation of both mass balance and energy balance and makes it possible to produce a desired product under the given conditions. Through this design stage, the process possesses unchangeable characteristics, since the materials, reactions, unit configuration, and operating conditions were determined. Unique characteristics could be very economic, but it also implies various potential risk factors as well. Therefore, it becomes extremely important to design process considering both economics and safety by integrating process simulation and quantitative risk analysis during preliminary design stage. The target of this study is LNG liquefaction process. By the simulation using Aspen HYSYS and quantitative risk analysis, the design variables of the process were determined in the way to minimize the inherent explosion risks and operating cost. Instead of the optimization tool of Aspen HYSYS, the optimization was performed by using stochastic optimization algorithm (Covariance Matrix Adaptation-Evolution Strategy, CMA-ES) which was implemented through automation between Aspen HYSYS and Matlab. The research obtained that the important variable to enhance inherent safety was the operation pressure of mixed refrigerant. The inherent risk was able to be reduced about 4~18% by increasing the operating cost about 0.5~10%. As the operating cost increases, the absolute value of risk was decreased as expected, but cost-effectiveness of risk reduction had decreased. Integration of process simulation and quantitative risk analysis made it possible to design inherently safe process, and it is expected to be useful in designing the less risky process since risk factors in the process can be numerically monitored during preliminary process design stage.

• KDI Journal of Economic Policy
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• v.14 no.4
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• pp.3-26
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• 1992

The pupose of this paper is to construct a price determination model of the Korean economy and to find out the propogation mechanism of monetary and fiscal policies. The model is a small-size macroeconometric model consisted of ten core equations : consumption, investment, exports, imports, consumer price index, wage rate, corporate bond rate, potential GNP, capital stock, and GNP identity. The model is a Keynesian model : consumer price index is determined by markup over costs, and wage rate is expressed by Phillipse curve ralation. Two features of the model, however, distinguish this model from other macroeconometric models of the Korean economy. First of all, the estimation of potential GNP and the capital stock is endogenized as suggested by Haque, Lahiri, and Montiel (1990). This allows us to calculate the level of excess demand, which is defined as the difference between the actual GNP and the potential GNP. Second, interest rate, inflation and wages are all estimated as endogenous variables. Moreover, all quantity variables include price variables as important determinants. For instance, interest rate is an important determinant of consumption and investment. Exports and imports are determined by the real effective exchange rate. These two features make the interactions between excess demand and prices the driving forces of this model. In the model, any shock which affects quantity variable(s) affects excess demand, which in turn affects prices. This strong interaction between prices and quantities makes the model look like a classical model over the long run. That is, increases in money supply, government expenditures, and exchange rate (the price of the U.S. dollar in terms of Korean won) all have expansionery effects on the real GNP in the short run, but prices, wage, and interest rate all increase as a result. Over the long run, higher prices have dampenning effects on output. Therefore the level of real GNP turns out to be not much different from the baseline level ; on the other hand, the rates of inflation, wage and interest rate remain at higher levels.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1155-1163
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• 2014

The complementary relationship-based evapotranspiration models, namely, AA model of Brutsaert and Stricker (1979) and the CRAE model of Morton (1983) was applied to two permanent stream watersheds Jeju island for the first time, and their major optimal parameters were suggested in this study. The representative watersheds for model calibration and validation were selected as the Hancheon watershed located in the northern part of the Jeju island and and the Kangjeongcheon watershed in southern Jeju island, respectively. The estimated actual evapotranspiration for the Hancheon watershed was compared with the result by the hydrological model, and the major parameters of the AA and CRAE models were calibrated until their results match the hydrological simulations. Through the iterative estimations, the optimal parameters were determined as ${\alpha}=1.00$, $M=30.0Wm^{-2}$ of the AA model, and $b_1=33.0Wm^{-2}$, $b_2=1.02$ of the CRAE model. The calibrated AA and CRAE models were applied to the Kangjeongcheon watershed for model validation, and it was found out that both models can accurately produce the actual evaporation on annual and semiannual bases.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.95-107
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• 2024

In this study, we explored the mediating effect of grit in the relationship between elementary school science teachers' perceived personal pedagogical content knowledge (pPCK) and enacted pedagogical content knowledge (ePCK). Drawing on insights from a review of the literature, we developed a research hypothesis model that set pPCK, ePCK, and grit as latent variables. Pearson correlation was conducted to examine the interrelationships among the latent variables. Structural equation modeling (SEM) was then employed to analyze the model fit. Additionally, bootstrap analysis was performed to specifically investigate the mediating effect of grit in the relationship between pPCK and ePCK. The Pearson correlation analysis indicated statistically significant correlations among the measurement variables. Meanwhile, the SEM analysis revealed that the measurement model aligned with the research hypothesis model. Furthermore, the bootstrap analysis demonstrated that grit had a statistically significant mediating effect in the relationship between elementary school science teachers' perceived pPCK and ePCK. These findings quantitatively examine the importance and impact of grit in the teacher expertise domain, providing valuable insights for the development of teachers' expertise and teacher education research within elementary school science classes.