• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.445-457
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• 2017

In this study, we developed an approach to better account for uncertainties in estimated contributions from fine particulate matter ($PM_{2.5}$) modeling. Our approach computes a Concentration Correction Factor (CCF) which is a ratio of observed concentrations to baseline model concentrations. We multiply modeled direct contribution estimates with CCF to obtain revised contributions. Overall, the modeling system showed reasonably good performance, correlation coefficient R of 0.82 and normalized mean bias of 2%, although the model underestimated some PM species concentrations. We also noticed that model biases vary seasonally. We compared contribution estimates of major source sectors before and after applying CCFs. We observed that different source sectors showed variable magnitudes of sensitivities to the CCF application. For example, the total primary $PM_{2.5}$ contribution was increased $2.4{\mu}g/m^3$ or 63% after the CCF application. Out of a $2.4{\mu}g/m^3$ increment, line sources and area source made up $1.3{\mu}g/m^3$ and $0.9{\mu}g/m^3$ which is 92% of the total contribution changes. We postulated two major reasons for variations in estimated contributions after the CCF application: (1) monthly variability of unadjusted contributions due to emission source characteristics and (2) physico-chemical differences in environmental conditions that emitted precursors undergo. Since emissions-to-$PM_{2.5}$ concentration conversion rate is an important piece of information to prioritize control strategy, we examined the effects of CCF application on the estimated conversion rates. We found that the application of CCFs can alter the rank of conversion efficiencies of source sectors. Finally, we discussed caveats of our current approach such as no consideration of ion neutralization which warrants further studies.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.1 s.53
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• pp.45-57
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• 2007

The mean shear wave velocity to the depth of 30 m (Vs30) derived from the western Vs is the current site classification criterion for determining the design seismic ground motion taking into account the site amplification potential. In order to evaluate the Vs30 at a site, a shear wave velocity (Vs) Profile extending to at least 30 m in depth must be acquired from in-situ seismic test. In many cases, however, the resultant depth of the Vs profile may not extend to 30 m, owing to the unfavorable field condition and the limitation of adopted testing techniques. In this study, the Vs30 and the mean shear wave velocity to a depth shallower, than 30 m (VsDs) were computed from the Vs profiles more than 30 m in depth obtained by performing various seismic tests at total 72 sites in Korea, and a correlation between Vs30 and VsDs was drawn based on the computed mean Vs data. In addition, a method for extrapolating the Vs profile from shallow depth to 30 m was developed by building a shape curve based on the average data of all Vs profiles. For evaluating the Vs30 from the shallow Vs profiles, both the methods using VsDs and shape curve result in less bias than the simplest method of extending the lowermost Vs equally to 30 m in depth, and are usefully applicable particularly in the cases of the Vs profiles extending to at least 10 m in depth.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.141-153
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• 1991

The optimal choice of the tax rate and the inflation rate framework is extended to yield relevant interpretations for the optimal fiscal and monetary policy regime in Korea. To study the relationship between the government budget and monetary growth in different environments of policy coordination, two models assuming different degrees of fiscal dominance are developed. By modelling differing institutional arrangements of the fiscal and the monetary authority from an optimal government finance viewpoint, we find the optimal relationship among some important fiscal and monetary variables. By testing the existence of the relationship empirically, we find the characteristics of the optimal policy-mix regime in Korea. The first model-the strong from of fiscal dominance-studies the optimal collection of seigniorage in a period-by-period optimization with standard assumptions on the income velocity of money, deriving a general testable result: the optimal inflation/tax rate ratio co-vary with the marginal revenue ratio. The second model-the weak form of fiscal dominance-studies an implication of the inflationary bias of discretionary monetary policy in the presence of fiscal side distortions. This model shows that the tax rate and the inflation rate can have a positive correlation. Empirical tests of the theoretical results are done for the Korean economy for 1972-1989 period. The test results show that the macroeconomic policy regime in Korea can be characterized by the strong form of fiscal dominance, implying the importance of the government budget in explaining money growth and inflation.

• Journal of the Korean earth science society
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• v.32 no.3
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• pp.249-264
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• 2011

A multi-Gaussian kriging approach extended to space-time domain is presented for uncertainty modeling as well as time-series mapping of environmental variables. Within a multi-Gaussian framework, normal score transformed environmental variables are first decomposed into deterministic trend and stochastic residual components. After local temporal trend models are constructed, the parameters of the models are estimated and interpolated in space. Space-time correlation structures of stationary residual components are quantified using a product-sum space-time variogram model. The ccdf is modeled at all grid locations using this space-time variogram model and space-time kriging. Finally, e-type estimates and conditional variances are computed from the ccdf models for spatial mapping and uncertainty analysis, respectively. The proposed approach is illustrated through a case of time-series Particulate Matter 10 ($PM_{10}$) concentration mapping in Incheon Metropolitan city using monthly $PM_{10}$ concentrations at 13 stations for 3 years. It is shown that the proposed approach would generate reliable time-series $PM_{10}$ concentration maps with less mean bias and better prediction capability, compared to conventional spatial-only ordinary kriging. It is also demonstrated that the conditional variances and the probability exceeding a certain thresholding value would be useful information sources for interpretation.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.5761-5767
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• 2013

The potential correlation of X-ray repair cross-complementing group 1 (XRCC1) Arg399Gln polymorphism with hepatocellular carcinoma (HCC) susceptibility is ambiguous. Taking account of inconsistent results of previous meta-analyses and new emerging literatures, we conducted a meta-analysis covering 15 case-control datasets to evaluate the relationship. Relevant studies from Medline, Embase and CNKI were retrieved. A fixed-effect model or a random-effect model, depending on between-study heterogeneity, were applied to estimate the association between XRCC1 polymorphism Arg399Gln and HCC risk with the results presented as odds ratios (ORs) and 95% confidence intervals (95% CIs). In accordance with Hardy-Weinberg equilibrium, 15 studies with data for 6,556 individuals were enrolled in this systematic review. For overall HCC,thr XRCC1 polymorphism Arg399Gln was significantly associated with HCC susceptibility in a homozygote model as well as in a dominant model (G/G vs. A/A, OR=1.253, p=0.028; G/G+A/G vs. A/A, OR= 1.281, p=0.047, respectively), but not in a heterozygote model (A/G vs. A/A, OR=1.271, p=0.066) or a recessive model (G/G vs. A/G + A/A, OR= 1.049, p=0.542). Similar results were also observed on stratification analysis by ethnicity (A/G vs. A/A, OR=1.357, p=0.025; G/G vs. A/A, OR=1.310, p=0.011; G/G+A/G vs. A/A, OR= 1.371, p=0.013). However, no potential contribution of XRCC1 Arg399Gln polymorphism to HCC susceptibility in HBV/HCV subgroups was identified. No publication bias was found in this study. In conclusion, the XRCC1 Arg399Gln polymorphism contributes to HCC susceptibility. Due to the lack of studies in Western countries, further large-sample and rigorous studies are needed to validate the findings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.372-383
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• 2017

This paper attempted to verify that Investigative Enterprising(IE) axis in the Holland hexagonal model can measure the internal and external job value. This study analyzed internal and external job values of 19 subjects who participated in the 150 Job cards classification test. The results of this study are as follows: First, the study group with Holland hexagonal model centered on the Investigative Enterprising type(IE) axis and artistic type(A) and social type(S) showed internal job value and supported the hypothesis. Second, the hypothesis that the group with the hexagonal model centered on the Investigative Enterprising(IE) axis and the bias toward the realistic type(R) and the conventional type(C) would pursue external job value was rejected. This is due to the Korean cultural context that pursues psycho-cultural value in Confucian culture. There is also a Holland hexagonal model that is not exactly distributed to the left of the Investigative Enterprising(IE) axis. Third, the group of amphibolic job value based on the Investigative Enterprising(IE) axis, and the Holland hexagonal model is expressed in artisic type(A), social type(S), realistic type(R), and conventional type(C) supported some hypotheses. This paper is the first to suggest that the Investigative Enterprising(IE) axis of the Holland hexagonal model can be used to measure job value, and the Holland hexagonal model can predict job value as well as career choice. This paper is intended to expand the foundation of the Holland theories, and to provide meaningful contribution to the basis for vocational studies.

• Journal of Distribution Science
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• v.13 no.10
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• pp.73-82
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• 2015

Purpose - This paper aims to investigate whether information asymmetry could explain capital structures in Korean corporations. According to Myers (1984), firms prefer internal funding to external financing due to the costs associated with information asymmetry. When external financing is necessary, firms prefer to issue debt rather than equity by the same reasoning. Since Shyam-Sunder and Myers (1999), numerous studies continue to debate the validity of the theory. In this paper, we show how the theory depends on assumptions and incorporated variables. We hope our investigation can provide helpful implications regarding capital structure, information asymmetry, and other firm characteristics. Specifically, our empirical results are complementary to the analysis of Son and Lee's (2015), a recent study that examines the pecking order theory prediction for Korean retail firms. Research design, data, and methodology - We test empirical models that are some variants of model used in Shyam-Sunder and Myers (1999). The financial and accounting data are provided by WISEfn for the firms listed on the KOSPI during 1990 to 2013. Bond ratings are supplied by the Korea Investor Service (KIS). We take into account the heterogeneity in debt capacity; a firm's debt capacity is measured by using the method of Lemmon and Zender (2010) based on its bond ratings. Finally, we estimate empirical models suggested by Shyam-Sunder and Myers (1999), Frank and Goyal (2003), and Lemmon and Zender (2010). Results - First, we find that Shyam-Sunder and Myers' (1999) prediction fails to explain total debt changes of Korean firms. Second, we find a non-monotonic relationship between total debt changes and financial deficits with respect to debt capacity. This contradicts the prediction of Lemmon and Zender (2010) that argues the pecking order theory survives with a monotonically increasing relationship. Third, we estimate a negative correlation coefficient between financial deficit and current debt changes. The result is the complete opposite of the prediction of Lemmon and Zender (2010). Finally, we also confirm the non-monotonic relationship between non-current debt changes and financial deficits with respect to debt capacity. Yet, the slope of coefficient is smaller than that of total debt change case. Indeed, the results are, to some extent, consistent with the prediction of pecking order theory, if we exclude the mid-debt capacity firms. Conclusions - Our empirical results complementary to the analysis of Son and Lee (2015), a recent study focusing on capital structure in Korean retail firms; their paper suggests interesting topics regarding capital structure, information asymmetry, and other firm characteristics in Korean corporations. Contrary to Son and Lee (2015), our results show that total debt changes and current debt changes are inconsistent with the prediction of Shyam-Sunder and Myers (1999). However, similar to Son and Lee (2015), non-current debt changes are consistent with the pecking order prediction, in the case of excluding the mid-level debt capacity firms. This contrast allows us to infer that industry characteristics significantly affect the validity of the pecking order prediction. Further studies are needed to analyze the economics behind this phenomenon, which is beyond the scope of our paper. In addition, the estimation bias potentially matters regarding the firm-level debt capacity calculation. We also reserve this topic for future research.

• Journal of Microbiology and Biotechnology
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• v.17 no.9
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• pp.1437-1444
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• 2007

A response surface model was developed for predicting the growth rates of Staphylococcus aureus in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10, 20, 30, and $40^{\circ}C$. In all experimental variables, the primary growth curves were well ($r^2=0.9000$ to 0.9975) fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. aureus were generally decreased by basic (pH 9-10) or acidic (pH 5-6) conditions and higher NaCl concentrations. The response surface model was identified as an appropriate secondary model for growth rates on the basis of correlation coefficient (r=0.9703), determination coefficient ($r^2=0.9415$), mean square error (MSE=0.0185), bias factor ($B_f=1.0216$), and accuracy factor ($A_f=1.2583$). Therefore, the developed secondary model proved reliable for predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. aureus in TSB medium.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.741-746
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• 2016

Albedo is one of the climate variables that modulate absorption of solar energy, and its retrieval is important process for climate change study. High spatial resolution and long-term consistent periods are important considerations in order to efficiently use the retrieved albedo data. This study retrieved surface broadband albedo based on Landsat 8 as high resolution which is consistent with Landsat 7. First of all, we analyzed consistency of Landsat 7 channel and Landsat 8 channel. As a result, correlation coefficient(R) on all channels is average 0.96. Based on this analysis, we used multiple linear regression model using Landsat 7 albedo, which is being used in many studies, and Landsat 8 reflectance channel data. The regression coefficients of each channel calculated by regression analysis were used to derive a formula for converting the Landsat 8 reflectance channel data to broadband albedo. After Landsat 8 albedo calculated using the derived formula is compared with Landsat 7 albedo data, we confirmed consistency of two satellite using Root Mean Square Error (RMSE), R-square ($R^2$) and bias. As a result, $R^2$ is 0.89 and RMSE is 0.003 between Landsat 7 albedo and Landsat 8 albedo.

• International Journal of Highway Engineering
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• v.5 no.1 s.15
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• pp.11-18
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• 2003

Road roughness, as the key factor influencing not only drivers' ride quality and safety but also pavement deterioration, is one of the most important pavement performance indicator to be evaluated by users' subjective assessment. For this reason, a specific number of the pavement roughness has been adopted to monitor the condition of a road for pavement management systems and to evaluate the quality of newly constructed sections, however, none of the unified methodology was internationally accepted. In Korea highway network, road roughness has been used mainly to evaluate newly placed pavement by using 7.6m CP (California Profile meter) to calculate PrI (Profile Index). But this instrument is manually operated to measure road profiles by traffic closure and their interpretation depends on personal bias. Therefore, problems arisen from the manually operated instrument will be overcome by using the APL (Longitudinal Profile Analyzer) which can be operated in the speed of 80km per hour. A study was conducted to correlate the relation from both concrete and asphalt pavement between IRI (measured by APL) and PrI (measured by 7.6m CP). Test results showed that there was a good correlation between IRI and PrI.