• Journal of Preventive Medicine and Public Health
• /
• v.34 no.4
• /
• pp.437-443
• /
• 2001

Objectives : This study was peformed to assess the association between the social support and blood pressure(BP) in a rural community. Methods : A cross-sectional survey, comprising a health examination including BP, height and weight and a questionnaire-based interview which investigated social support, demographic factors, smoking, drinking, and etc. was peformed between February 10th and March 5th, 1998. The survey included 318 persons who were over than 30-year-old in the rural community of Kwangju, Republic of Korea. We excluded persons who taking antihypertensive medications or who provided incomplete information; we subsequently analyzed the data from 284 persons. In order to test the hypothesis of an association between BP and social support controlling confounders such as age, educational level, working time, body mass index, smoking and drinking, the data was analyzed using multiple linear regression analysis. Results : The subjects were composed of 109(38.4%) males and 175(61.6%) females with mean ages of 62.0 years and 61.1 years, respectively. The hypertension prevalence was 41.3% among males and 45.1% among females. In the correlation analysis, higher total social support scores correlated significantly with lower systolic BP in both males and females. The hypertension prevalence increased significantly with the decreasing of the social support in males. In multiple regression analysis, systolic and diastolic blood pressure showed a negative association with social support in both males and females, although this was not statistically significant. Conclusions : Larger and broader studies are required in the future in order to identify the association between the social support and BP.

• Journal of Korea Port Economic Association
• /
• v.34 no.4
• /
• pp.181-190
• /
• 2018

The goal of this study is empirically to investigate the asymmetric relationship between two variables using the dry cargo freight rates and raw material price data from January 2012 to May 2018. First, we estimate the asymmetry of macroeconomic indicators of commodity prices by using a two - step threshold cointegration test. Second, the asymmetric relation test of the trade balance of existing commodity price changes is tested by bypassing to the high frequency dry cargo freight rate index. As a result of the estimation, in contrast to the existing linear analysis, each boundary value for the lower limit and the upper limit has different asymmetry. This implies that the period of fluctuation of the sudden residual that causes irregular rate of return fluctuations does not establish a long term equilibrium relationship between the raw material price and the dry cargo freight rate. Therefore, in order to consider the sudden price change in the analysis, it is necessary to include the band of inaction that controls the irregular volatility, which is consistent with the asymmetry hypothesis.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.6
• /
• pp.548-556
• /
• 2019

The purpose of this study is to analyze the impact of dietary lifestyles and demographic characteristics on the Brand image of restaurants with Nutritional labeling to provide basic marketing data for establishing differentiated Brand image strategies for restaurant businesses. To that end, the SPSS21.0 (ver.) program, frequency analysis, descriptive statistics, factor analysis, reliability analysis, correlation analysis, and multiple linear regression analysis were conducted to verify the hypothesis. As a result, the Brand image of restaurants with Nutritional labeling improved as the metropolitan area sought safety, non-capital area sought taste, males sought health, and females sought safety. In terms of age, it was analyzed that as more people in their 20s sought taste, those their 30s and 40s sought safety, and both married and unmarried people sought safety, the Brand image of restaurants with Nutritional labeling improved. In other words, it could be seen that people with Dietary lifestyles who pursued health and safety had positive images of restaurants with Nutritional labeling regardless of residential area, age, gender, marital status, or whether they had children.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.31 no.1
• /
• pp.17-27
• /
• 2019

We carry out the numerical simulation to test a hypothesis that freak waves can be triggered by the infragravity waves of bound mode underlying the ever-present swells and its constructive interaction with swells using the Tool Box called the ihFoam that has its roots on the OpenFoam, and Bi-spectrum. Numerical simulation is implemented for the SamChcuk LNG Plant where freak waves have been reported in front of the private wharf during its construction phase due to the uncompleted northern breakwater. Infra-gravity waves of bound mode is generated using the difference wave-wave interaction between the local wind waves of 7 s and a swell of 11.4 s based on the Bi-spectrum. For the sake of comparison, numerical simulation for infra-gravity waves of free mode is also carried out. Numerical results show that stem waves along the private wharf for SamChcuk LNG Plant can be triggered by the infra-gravity waves of bound mode coming from the north, which eventually leads to freak waves when encounters the reflected waves from the south jetty.

• Journal of Integrative Natural Science
• /
• v.13 no.4
• /
• pp.132-140
• /
• 2020

With the recent introduction of artificial intelligence (AI) technology, the use of data is rapidly increasing, and newly generated data is also rapidly increasing. In order to obtain the results to be analyzed based on these data, the first thing to do is to classify the data well. However, when classifying data, if only one classification technique belonging to the machine learning technique is applied to classify and analyze it, an error of overfitting can be accompanied. In order to reduce or minimize the problems caused by misclassification of the classification system such as overfitting, it is necessary to derive an optimal classification by comparing the results of each classification by applying several classification techniques. If you try to interpret the data with only one classification technique, you will have poor reasoning and poor predictions of results. This study seeks to find a method for optimally classifying data by looking at data from various perspectives and applying various classification techniques such as LDA and QDA, such as linear or nonlinear classification, as a process before data analysis in data analysis. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable and the correlation between the variables. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified to suit the purpose of analysis. This is a process that must be performed before reaching the result by analyzing the data, and it may be a method of optimal data classification.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.49 no.4
• /
• pp.311-320
• /
• 2021

A study is performed for the real time fault diagnosis during operation and health estimation relating to performance deterioration in a turbojet engine used for an unmanned air vehicle. For this study the real time dynamic model is derived from the transient thermodynamic gas path analysis. For real fault conditions which are manipulated for the simulation, the detection techniques are applied such as Kalman filter and probabilistic decision-making approach based on statistical hypothesis test. Thereby the effectiveness is verified by showing good fault detection and isolation performances. For the health estimation with measurement parameters, it shows using an assumed performance degradation that the method by adaptive Kalman filter is feasible in practice for a condition based diagnosis and maintenance.

• Journal of Distribution Science
• /
• v.20 no.8
• /
• pp.93-103
• /
• 2022

Purpose: Online shopping festivals have quickly become the newest trend in online shopping worldwide due to the COVID-19 pandemic. This has led to marketing distribution channels that traditionally emphasized traditional techniques having turned to electronic commerce platforms. Although the pandemic scenario encourages online purchasing, other factors, such as the influence of participation intention to shop during the Online Shopping Festival, must also be considered. Research design, data and methodology: Multiple linear regression analysis was used to test the hypothesis based on data from 121 respondents who are actively involved with online shopping activities in Klang Valley, Selangor. Results: The results of this study show that promotion categories and the perceived influence of mass participation have a significant influence on participation intention. Meanwhile, the perceived temptation of price promotion and perceived fun promotional activities did not significantly influence participation intention. Conclusions: Theoretically, this study contributes to the literature by using the Theory of Planned Behavior and Stimulus-Response models to explain the factors that drive participation intention for online shopping. In practice, this study attracts and encourages customers to shop during the festival day because various attractive promotions are offered by sellers in Malaysia.

• Journal of Astronomy and Space Sciences
• /
• v.39 no.2
• /
• pp.43-50
• /
• 2022

The unified scheme of Seyfert galaxies hypothesizes that the observed differences between the two categories of Seyfert galaxies, type 1 (Sy1) and type 2 (Sy2) are merely due to the difference in the orientation of the toroidal shape of the obscuring material in the active galactic nuclei. We used in this paper, a sample consisting of 120 Seyfert galaxies at 1.40 × 10⁹ Hz in radio, 2.52 × 10¹⁷ Hz in X-ray and 2.52 × 10²³ Hz in γ-ray luminosities observed by the Fermi Large Area Telescope (Fermi-LAT) in order to test the unified scheme of radio-quiet Seyfert galaxies. Our main results are as follows: (i) We found that the distributions of multiwave luminosities (L_radio, L_X-ray, and L_γ-ray) of Sy1 and Sy2 are completely overlapped with up to a factor of 4. The principal component analysis result reveals that Sy1 and Sy2 also occupy the same parameter spaces, which agrees with the notion that Sy1 and Sy2 are the same class objects. A Kolmogorov-Smirnov test performed on the sub-samples indicates that the null hypothesis (both are from the same population) cannot be rejected with chance probability p ~ 0 and separation distance K = 0.013. This result supports the fact that there is no statistical difference between the properties of Sy1 and Sy2 (ii) We found that the coefficient of the best-fit linear regression equation between the common properties of Sy1 and Sy2 is significant (r > 0.50) which plausibly implies that Sy1 and Sy2 are the same type of objects observed at different viewing angle.

• Journal of Korea Trade
• /
• v.24 no.8
• /
• pp.121-132
• /
• 2020

Purpose - The principle aim of this study is to further investigate the relationship between market diversity and export performance. We examine the benefits and costs of geographic market diversity regarding the number of countries exported to by firms on their export performance. Based on the financial risk reduction model and the entry costs model, we propose a way to incorporate the costs and benefits aspects of market diversity. Design/methodology - To empirically investigate our research question, the curvilinear relationship between market diversity and export performance, we built a secondary panel data set between 2015 and 2019, containing 17,863 observations of Korean exporting companies. A generalized least squares panel estimator with fixed effects was employed to test the hypothesis, and the statistical package, Stata 14, was used. Findings - Our main findings are as follows: As market diversity increases, export performance increases because exporters can diversify and reduce financial risks in export markets. However, the relationship between the two does not grow. As it peaks, the entry costs increase due to the high market diversity, thereby outweighing the benefits, leading, eventually to decrease in the export performance. Consequently, there is an inverted U-shaped relationship between market diversity and export performance. Originality/value - In the export and trade literature, the impact of market diversity on export performance has not been addressed yet, despite the importance of this subject. Many scholars have assumed a positive linear relationship between the two, considering only the decrease in market risks as the number of overseas markets increases, without examining the increase in the entry and management costs. Therefore, our study contributes by providing a new perspective for analyzing the characteristics and outcomes of market diversity.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.67-76
• /
• 2022

COVID-19 struck labor markets around the world, exposing and exacerbating the gender inequalities within the human capital structure. The last, in its turn, jeopardizes the return of the national economies to the growth trajectory undermined by pandemic impact. The authors assume that COVID-19 disproportionately affected the employment rates of women and men, which led to increased gender inequality in the labor market, which, in turn, affected GDP growth rates in the EU. To prove this hypothesis two research questions are discovered: 1) whether there was a different correlation between the number of COVID-19 cases in the EU and indicators of the labor market for women and men; and 2) whether there was a link between the growth of gender inequality in the EU labor market and the GDP dynamics in these countries. The analysis of the correlation between the number of cases of COVID-19 and indicators of the labor market in the EU revealed faster growth of women's unemployment rates compared to men's ones as the COVID-19 incidence unfolded. Multiple linear regression and factor analysis have been used to investigate the influence of gender inequality in the labor market on GDP dynamics. Despite the methodological limitations, the proposed model is both a sound argument and an analytical basis in favor of gender-responsive economic recovery backed by the systematic and consistent gender equality policy of a government.