• 한국노년학
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• v.38 no.3
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• pp.481-499
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• 2018

The purpose of this study is to examine the impacts of smartphone use on structured social network types in the Korean elderly population. Data was derived from the 2014 survey of living conditions and welfare needs of Korean older persons collected by Korea Institute for Health and Social Affairs. A total of 4,180 participants were selected for the Propensity Score Matching (PSM) analysis. Based on propensity score estimates, the 491 smartphone users (treatment group) and 491 featurephone users (control group) were matched. Ordinary Least Squares (OLS) regression analysis was conducted to examine the relationship between smartphone use and structural social network types. The results showed that among retired older adults, people using smartphone had significantly better structured social networks than those using featurephone even after controlling for covariates. Smartphone users had the higher levels of social contact and social activity. These findings suggested empirical evidence that using smartphone positively affects structured social networks, which might be used as the basis for designing intervention programs to promote social networks and social engagement of retired older adults.

• Translational and Clinical Pharmacology
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• v.25 no.2
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• pp.67-73
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• 2017

Glimepiride, a third generation sulfonylurea, is an antihyperglycemic agent widely used to treat type 2 diabetes mellitus. In this study, an untargeted urinary metabolomic analysis was performed to identify endogenous metabolites affected by glimepiride administration. Urine samples of twelve healthy male volunteers were collected before and after administration of 2 mg glimepiride. These samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and then subjected to multivariate data analysis including principal component analysis and orthogonal partial least squares discriminant analysis. Through this metabolomic profiling, we identified several endogenous metabolites such as adenosine 3', 5'-cyclic monophosphate (cAMP), quercetin, tyramine, and urocanic acid, which exhibit significant metabolomic changes between pre- and posturine samples. Among these, cAMP, which is known to be related to insulin secretion, was the most significantly altered metabolite following glimepiride administration. In addition, the pathway analysis showed that purine, tyrosine, and histidine metabolism was affected by pharmacological responses to glimepiride. Together, the results suggest that the pharmacometabolomic approach, based on LC-MS/MS, is useful in understanding the alterations in biochemical pathways associated with glimepiride action.

• Korea Real Estate Review
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• v.28 no.4
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• pp.37-51
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• 2018

The purpose of this paper is to analyze the effects of location factors on sales by restaurant type in the six districts of Seoul (Jongno-gu, Jung-gu, Yeongdeungpo-gu, Gangnam-gu, Seocho-gu, and Songpa-gu). Ordinary least squares (OLS) regression model is selected for four restaurant types whose spatial autocorrelation is not identified, spatial lag model (SLM) is only selected for seafood restaurant, and spatial error model (SEM) is selected for nine other restaurant types. The floating population and the workers of surrounding businesses have generally positive effects on the sales of restaurants. The floating population elasticity of the sales of restaurants are found to be in the descending order of Oriental food, pub, Western food, and traditional food restaurant, and the elasticity of the workers of surrounding businesses are in the descending order of bakery, Oriental food, and Western food restaurant. The spatial multiplier effects are in the descending order of Oriental food, pub, and Western food restaurant. There is a statistically significant sales gap between roast meat, pub, and bakery in Gangnam-gu and those in five other districts. The results of this research can help in starting a restaurant in that they can provide information on the suitability of location by restaurant type.

• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.1077-1100
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• 2018

The present study analyzed the effect of firms' external research and development (R&D) on corporate productivity, while investigating the moderating effect of firm size on the external R&D-productivity nexus. In the empirical analysis, we estimated South Korean manufacturing firms' total factor productivity (TFP) using the firm level data drawn from the Survey of Business Activities (Korea National Statistical Office) for the years 2006-2015. Thereafter, focusing on the role of external R&D and its interaction with the firm size in determining firms' TFP, the productivity function was estimated as well. To this end, we used ordinary least squares (OLS) and quantile regression to highlight the heterogeneous impacts of external R&D by companies' productivity level. Empirical results confirmed that firms' external R&D significantly enhanced corporate productivity in all manufacturing industries, from high-tech to low-tech. The moderating effect of firm size in determining the productivity effect of external R&D was not as prominent as in the case for internal R&D, which exhibited some degree of the size premium in the productivity-enhancing effect. These results suggest that regardless of the firm size, external R&D can be an important channel for corporate productivity improvement, and can be a particularly effective strategy for SMEs with relatively limited internal R&D capacities.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.320-327
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• 2018

The purpose of this study is to suggest the policy direction for promoting Korean grape, Shine Muscat, export to China. For this, the data were collected from 102 Chinese who live in Guangzhou province. The survey was conducted from Oct 10th to 13th 2017. PLS-SEM model is used to investigate the main factors that cause the Chinese consumers to purchase Korean grape, Shine Muscat. This study finds that the post-evaluation factor is more important to obtain final evaluation and to purchase Korean grape in the future. Thus farmers and research institutes should investigate how to improve the quality for the sweetness and the texture of the grape, reflecting the Chinese consumers' preference.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.63-85
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• 2018

The "About Us" page on the website of a corporation provides information regarding the organization's vision, philosophy, and values. We examine the association between institutional information provided on corporate websites (i.e., the "About Us" section) with present and future financial performance. Utilizing a text mining technique, we analyze the institutional information of S&P500 firms in the year 2016. We conduct a factor analysis including words that are intentionally repeated in the introductory text of corporate websites. The results of the analysis reveal that keywords from this institutional information can be grouped into six factors. We then carry out an ordinary least squares regression analysis to determine the associations between these six factors and present financial performance. The results show that keywords in Factor 2 (those related to Purchasing experience) are positively associated with ROE, a variable representing present financial performance, while keywords in Factor 1 (those related to Note to customers) show a negative relationship with ROE. On the other hand, keywords in Factor 1 have a positive relationship with Tobin's Q, a variable representing future financial performance. These results indicate that there is some relationship between the words used in the institutional information in this section of corporate websites and firms' financial performance. Hence, the institutional information on a website may be a useful indicator of current firm performance and future firm value.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.611-620
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• 2018

With the revitalization of alley market area becoming a major goal of the urban regeneration project, an understanding on customer characteristics that affect the sales of alley market areas is needed. As spatial heterogeneity appears to exist in alley market areas, the use of GWR (Geographically Weighted Regression) is required as an alternative to OLS (Ordinary Least Squares) regression. This study analyzes effects of customer characteristics on sales of 1007 alley market areas in Seoul. Comparing R squared and AICc, results show that GWR is better than OLS regression. According to OLS regression, the ratio of female, the ratio of 40's and 50's, the number of employees, the opening rate of establishment, the density of building and the size of alley market area have positive effects on sales, while the ratio of 20's and 30's, the distance of bus stop and that of subway station have negative effects. As a result of comparing local regression coefficients of geographically weighted regression analysis, the ratio of female customers has the greatest effect on the northwestern region, followed by the southwestern region, the central region and the northeastern region. The ratio of 20's and 30's and that of 40's and 50's effect on the southeastern and northeastern regions, and then the southwestern region. It is expected that this study will help to identify marketing target for each alley market area.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.508-516
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• 2019

Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yr-old ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

• Korean Journal of Ecology and Environment
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• v.52 no.2
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• pp.94-104
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• 2019

In this study, we investigated the spatial variation in land use and topographic effects on water quality at the Geum river watershed in South Korea, using the ordinary least squares(OLS) and geographically weighted regression (GWR) models. Understanding the complex interactions between land use, slope, elevation, and water quality is essential for water pollution control and watershed management. We monitored four water quality indicators -total phosphorus, total nitrogen, biochemical oxygen demand, and dissolved oxygen levels - across three land use types (urban, agricultural, and forested) and two topographic features (elevation and mean slope). Results from GWR modeling revealed that land use and topography did not affect water quality consistently through space, but instead exhibited substantial spatial non-stationarity. The GWR model performed better than the OLS model as it produced a higher adjusted $R^2$ value. Spatial variation in interactions among variables could be visualized by mapping $R^2$ values from the GWR model at fine spatial resolution. Using the GWR model, we were able to identify local pollution sources, determine habitat status, and recommend appropriate land-use planning policies for watershed management.