• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.155-167
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• 2014

This study uses a continuous autoregressive (CAR) model to analyze daily average temperature in six Korean metropolitan cities. Data period is Jan. 1, 1954 to Dec. 31, 2010 covering 57 years. Using a relative long time series reveals that the linear time trend components are all statistically significant in the six cities, which was not shown in previous studies. Particularly the plus sign of its coefficient implies the effect on Korea of the global warming. Unit-root test results are that the temperature time series are stationary without unit-root. It turns out that CAR(3) is suitable for stochastic component of the daily temperature. Since developing suitable continuous stochastic model of the underlying weather related variables is crucial in pricing the weather derivatives, the results in this study will likely prove useful in further future studies on pricing weather derivatives.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4506-4513
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• 2012

The purpose of this study is to analyze the causality of electricity consumption and econmic growth and draw policy implications. To do this, we used Testing Prodedures of Unit Root and Cointegration and then VECM and Granger causality test using data taken from China over the period 1971 to 2008. As results, there are long and short term causalities between electricity consumption and economic growth of China. These results provide a few implications to policy analysts in China. First it is still available that the electricity comes before the economic development. The increase of electricity consumption promotes economic growth. Of course there are other factors to the economic growth, but the stable supply of electricity is necessary. Second, this paper confirms the assertion that the increase of GDP expands electric consumption is valid.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.183-208
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• 2022

Purpose - The main purpose of this study is to widely investigate the impact of recent pandemic crises on the synchronization of the world capital markets through 25 stock indices from major developed countries. Design/methodology/approach - This study collects 25 stock indices from major developed countries and the time period is between January 5, 2001 and February 24, 2022. The data sets used in the study include finance.yahoo.com and Investing.com.. The Granger causality analysis, unit-root test, VAR analysis, and forecasting error variance decomposition were hired in order to analyze the data. Findings - First, there are significant inter-relations among 25 countries around recent major pandemic crises(such as SARS, A(H1N1), MERS, and COVID19), which is consistent result with previous literature. Second, COVID19 shows much stronger impact on the world-wide synchronization than other pandemics. Third, the return volatility of each stock market varies, unit root tests show that daily stock index data are unstable while daily stock index returns are stable, and VAR(Vector Auto Regression) analyses presents significant inter-relations among 25 capital markets. Fourth, from the impulse response function analyses, we find that each market affects the other markets for short term periods, about 2~4 days, and no long term effect was not found. Fifth, Granger causality tests show one-side or two-sides synchronization between capital markets and we estimate, through forecasting error variance decomposition method, that the explanatory portions of each capital market on other markets vary from 10 to 80%. Research implications or Originality - The above results all together show that pandemic crises have strong effects on the synchronization of world capital markets and imply that these synchronizations should be carefully considered both in the investment decisions by individual investors and in the financial and economic policies by governments.

• Journal of Biosystems Engineering
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• v.22 no.1
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• pp.11-20
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• 1997

Thin layer drying tests of short gain rough rice were conducted in an experimental dryer equiped with air conditioning unit. The drying tests were performed in triplicate at three air temperatures of $35^circ$, $45^circ$, $55^circ$, and three relative humidities of 40%, 55%, 70%, respectively. Previously published thin layer equations were reviewed and four different models widely used as thin layer drying equations for cereal grains were selected. The selected four models were Pages, simplified diffusion, Lewis's and Thompson's models. Experimental data were fitted to these equations using stepwise multiple regression analysis. The experimental constants involved in tow equations were represented as a function of temperature and relative humidity of drying air. The results of comparing coefficients of determination and root mean square errors of miosture ratio for low equations showed that Page's and Thompsons models were found to fit adequately to all drying test data with coefficient of determination of 0.99 or better and root mean square error of moisture ratio of 0.025.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1465-1475
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• 2016

In order to secure safe meals, the hazards of microorganisms associated with food poisoning accident should be monitored and controlled in real situations. It is necessary to determined the correlation between existing common bacteria number (aerobic plate count; APC) and RLU (relative light unit) in cookware. In this paper, we investigate the correlation between ATP (RUL) and APC (CFU) by using three types of transform (inverse, square root, log transforms) of raw data in two steps. Among these transforms, the log transform at the first step has been found to be optimal for the data of cutting board, knife, soup bowl (stainless), and tray (carbon). The square root-inverse and the square root-square root transform at the second step have been shown to be optimal respectively for the cup and for the soup bowl (carbon) data.

• Imaging Science in Dentistry
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• v.38 no.3
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• pp.169-176
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• 2008

Purpose : To assess the diagnostic accuracy and value in an imaging technique field through the comparison of cone beam computed tomography and conventional panoramic radiography in assessing the topographic relationship between the mandibular canal and impacted third molars. Materials and Methods : Participants consisted of 100 patients offered the images through cone beam computed tomography and panoramic radiography. PSR-$9000^{TM}$ Dental CT system (Asahi Roentgen Ind. Co., Ltd, Japan) was used as the unit of cone beam computed tomography. CE-II (Asahi Roentgen Ind. Co., Ltd, Japan) and Pro Max (Planmeca Oy, Finland) were used as the unit of panoramic radiography. The images obtained through panoramic radiography were classified into 3 types according to the distance between mandibular canal and root of mandibular third molar. And they were classified into 4 types according to the proximity of radiographic feature. The images obtained through cone beam computed tomography based on the classification above were classified into 4 types according to the location between the mandibular canal and the root and were analyzed. And they were classified into buccal, inferior, lingual, and between roots, according to the location between mandibular canal and root. The data were statistically analyzed and estimated by $X^2$-test. Results : 1. There was no statistical significance according to 3 types (type I, type II, type III) through CBCT. 2. The results of 4 types (type A, type B, type C, type D) through CBCT were as high prevalence of CBCT 1 in type A, CBCT 2 in type B, CBCT 3 in type C, and CBCT1 in type D and those of which showed statistical significance (P value=0.03). 3. The results according to location between mandibular canal and root through CBCT recorded each 49, 25, 17, 9 as buccal, inferior, lingual, between roots. Conclusion : When estimating the mandibular canal and the roots through the panoramic radiography, it could be difficult to drive the views of which this estimation was considerable. Thus it is required to have an accurate diagnostic approaching through CBCT that could estimate the location between mandibular canal and roots.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.6
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• pp.1745-1754
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• 2015

This study aimed to analyze the relationship between sea temperatures and anchovy catch of Anchovy drag net fishery using annual time series data from 1970 to 2013. In the analysis, time series data on variables (CPUE, sea surface temperature, and 10m temperature) were estimated to be non-stationary from unit root tests, but one long-term equilibrium relation among variables was found from a cointegration test. From an exclusion test, a 10m temperature would not have relations with CPUE and sea surface temperature. The result of regression analysis on sea surface temperature and anchovy catch indicated that the sea surface temperature would have positive impacts on the anchovy catch. It means that when the sea surface temperature would increase, all other things including the current level of fishing effort being equal, the catch of anchovy was predicted to increase. More specifically, the result showed that when 1% of sea surface temperature increases, CPUE would be increased by 2.81%.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.151-162
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• 2019

The paper examines the effects of Foreign Direct Investment (FDI) on the economic growth of Lao People's Democratic Republic (Lao PDR) between 1993 and 2015. The investigation is based on the influence of growth and economic absorptive capability determinants such as human capital, trade openness, and institutional quality. The methodological analysis uses a multivariate framework accounting capital stock, labor stock, FDI, human capital, trade openness, and institutional quality in regression of the Vector Autoregressive model. Augmented Dickey-Fuller unit root test, Johansen Cointegration test, and Granger Causality test were applied as parts of the econometric time-series analysis approach. The empirical results demonstrate the positive effects of FDI and trade openness, and the negative effects of human capital and institutional quality on the economic growth of the Lao PDR over the 1993 to 2015 period. The findings confirm that trade openness complemented by a sufficient level of infrastructure, education, quality institutions, and transparency significantly influence economic growth and attract more FDI. Research results lend credence to the need for the Lao PDR's government to focus on improving its economic absorptive capability and economic competitiveness regionally and globally by improving wealth and resource management strategies, as failure to take this course of action could lead to the Dutch Disease effects.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.219-228
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• 2020

The study investigates the impact of inflation rate on economic growth to find the best-fit model for economic growth in Vietnam. The study applied Vector Autoregressive (VAR), cointegration models, and unit root test for the time-series data from 1996 to 2018 to test the inflation impact on the economic growth in the short and long term. The study showed that the two variables are stationary at lag first difference I(1) with 1%, 5% and 10%; trace test indicates two cointegrating equations at the 0.05 level, the INF does not granger cause GDP, the optimal lag I(1) and the variables are closely related as R2 is 72%. It finds that the VAR model's results are the basis to perform economic growth; besides, the inflation rate is positively related to economic growth. The results support the monetary policy. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the best-fitted VAR forecast model.

• Korean Management Science Review
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• v.25 no.3
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• pp.13-26
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• 2008

We investigate the effect of government and public sector R&D Investment at IT Industry on the amount of Production, export and nongovernment R&D Investment at IT Industry. We, firstly, examine the stationarity of each variable by the unit root t-test and perform the co-integration test for the pairs of variables. We use YECM(Vector Error Correction Model) according to the results of co-integration test for the examination of Granger-causality between variables. It is found that there exist an Granger-causality between public sector R&D Investment and nongovernment R&D investment and also between public sector R&D Investment and export. Secondly, we analyze the impulse response of government and public sector R&D Investment at IT Industry on the amount of production, export and nongovernment R&D investment at IT Industry based on VECM model. It is found that the response of the amount of production is highest at 3th period and is lowest at 8th period and that of export shows similar pattern.