• Economic and Environmental Geology
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• v.43 no.1
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• pp.53-66
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• 2010

We report petrologic characteristics including $^{40}Ar-^{39}Ar$ absolute ages of the subsurface lavas recovered from borehole cores in two islets, Marado and Gapado, off the southwestern coast of Jeju in southernmost Korea and discuss on the volcanism in the region. The lavas in Gapado are apparently divided into one unit with bright colored, aphanitic texture and sheet jointed, and another unit with dark colored and massive. The outcrops often show differentially weathered pattern due to textural difference. While, the lavas in Marado have vesicular and glomerporphyric texture, even though each lava flow unit in Marado has slight unique texture with variation of vesicularity and phenocrysts. The chemical composition of rock core samples from Gapa borehole and Mara borehole shows that the lavas from Gapado and Marado are classified into basaltic trachyandesite($SiO_2$ 52.6-53.6 wt%, $Na_2O+K_2O$ 7.3-7.5 wt%) and tholeiitic andesite($SiO_2$ 51.7-52.8 wt%, $Na_2O+K_2O$ 3.6-4.1 wt%), respectively. The measured $^{40}Ar-^{39}Ar$ plateau ages range from $824{\pm}32\;Ka$(MSL -69 m) to $758{\pm}\;Ka$(MSL 19 m) for core samples of Gapa borehole and $259{\pm}168\;Ka$(MSL -26 m) for a core sample of Mara borehole, respectively. The absolute age of Gapado basaltic trachyandesite is well correlated with that of Sanbangsan trachyte(Won et al., 1986). Meanwhile, the age of a sample in Marado has $259{\pm}168\;Ka$(MSL -26 m) with poor plateau age formation and high error range. We report the data in caution but the rock composition and absolute age of Marado tholeiitic andesite are relatively correlated with those of lava units from Duksu and Sangmo-2 boreholes, indicating the volcanism during 260-150 Ka. On the basis of interpretation of occurrences of exposed and subsurface volcanic rocks of the study area, stratigraphic relationship with adjacent borehole cores and the bathymetry chart of surrounding area, it indicates that the lavas in Gapado were formed around 800 Ka during relatively early stage of volcanic activity in Jeju Island. Meanwhile, Marado may have originated around 260-150 Ka during relatively young stage of volcanism in Jeju Island. It is inferred that the volcanisms have originated in land and these islets were individual ancient volcanoes. The apparent topography has been re-shaped by tidal erosion due to transgression.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.169-206
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• 2009

This study stems from a question, "How should we understand the pattern of the Korean economy after the 1990s?" Among various analytic methods applicable, this study chooses a Structural Vector Autoregression (SVAR) with long-run restrictions, identifies diverse impacts that gave rise to the current status of the Korean economy, and differentiates relative contributions of those impacts. To that end, SVAR is applied to four economic models; Blanchard and Quah (1989)'s 2-variable model, its 3-variable extensions, and the two other New Keynesian type linear models modified from Stock and Watson (2002). Especially, the latter two models are devised to reflect the recent transitions in the determination of foreign exchange rate (from a fixed rate regime to a flexible rate one) as well as the monetary policy rule (from aggregate targeting to inflation targeting). When organizing the assumed results in the form of impulse response and forecasting error variance decomposition, two common denominators are found as follows. First, changes in the rate of economic growth are mainly attributable to the impact on productivity, and such trend has grown strong since the 2000s, which indicates that Korea's economic growth since the 2000s has been closely associated with its potential growth rate. Second, the magnitude or consistency of impact responses tends to have subsided since the 2000s. Given Korea's high dependence on trade, it is possible that low interest rates, low inflation, steady growth, and the economic emergence of China as a world player have helped secure capital and demand for export and import, which therefore might reduced the impact of each sector on overall economic status. Despite the fact that a diverse mixture of models and impacts has been used for analysis, always two common findings are observed in the result. Therefore, it can be concluded that the decreased rate of economic growth of Korea since 2000 appears to be on the same track as the decrease in Korea's potential growth rate. The contents of this paper are constructed as follows: The second section observes the recent trend of the economic development of Korea and related Korean articles, which might help in clearly defining the scope and analytic methodology of this study. The third section provides an analysis model to be used in this study, which is Structural VAR as mentioned above. Variables used, estimation equations, and identification conditions of impacts are explained. The fourth section reports estimation results derived by the previously introduced model, and the fifth section concludes.

• Management & Information Systems Review
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• v.34 no.3
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• pp.17-39
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• 2015

This study examined the structural changes and volatility in the global stock markets using a Markov Regime Switching ARCH model developed by the Hamilton and Susmel (1994). Firstly, the US, Italy and Ireland showed that variance in the high volatility regime was more than five times that in the low volatility, while Korea, Russia, India, and Greece exhibited that variance in the high volatility regime was increased more than eight times that in the low. On average, a jump from regime 1 to regime 2 implied roughly three times increased in risk, while the risk during regime 3 was up to almost thirteen times than during regime 1 over the study period. And Korea, the US, India, Italy showed ARCH(1) and ARCH(2) effects, leverage and asymmetric effects. Secondly, 278 days were estimated in the persistence of low volatility regime, indicating that the mean transition probability between volatilities exhibited the highest long-term persistence in Korea. Thirdly, the coefficients appeared to be unstable structural changes and volatility for the stock markets in Chow tests during the Asian, Global and European financial crisis. In addition, 1-Step prediction error tests showed that stock markets were unstable during the Asian crisis of 1997-1998 except for Russia, and the Global crisis of 2007-2008 except for Korea and the European crisis of 2010-2011 except for Korea, the US, Russia and India. N-Step tests exhibited that most of stock markets were unstable during the Asian and Global crisis. There was little change in the Asian crisis in CUSUM tests, while stock markets were stable until the late 2000s except for some countries. Also there were stable and unstable stock markets mixed across countries in CUSUMSQ test during the crises. Fourthly, I confirmed a close relevance of the volatility between Korea and other countries in the stock markets through the likelihood ratio tests. Accordingly, I have identified the episode or events that generated the high volatility in the stock markets for the financial crisis, and for all seven stock markets the significant switch between the volatility regimes implied a considerable change in the market risk. It appeared that the high stock market volatility was related with business recession at the beginning in 1990s. By closely examining the history of political and economical events in the global countries, I found that the results of Lamoureux and Lastrapes (1990) were consistent with those of this paper, indicating there were the structural changes and volatility during the crises and specificly every high volatility regime in SWARCH-L(3,2) student t-model was accompanied by some important policy changes or financial crises in countries or other critical events in the international economy. The sophisticated nonlinear models are needed to further analysis.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.4
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• pp.15-24
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• 2017

The major goal of this paper falls on developing new rational valuation model, to help companies and investors in the early stage of growth as to preparing and negotiating valuation of investment, by applying new reasonable discount indexes of calculating Discount Cash Flow in valuation of the start-up which has been recognized the critical fatal flaws of DCF with them. There are three specific studies done in this paper. First, this paper found the solid and viable bases of rational discount indexes as to applying DCF in valuing companies in the early growth stage with reviewing the previous studies including Berkus method, Scorecard Method, and Risk factor Summation method classified the most effective tools of valuing pre-revenue generating companies. Second, this paper quoted and analyzed the previous models and studies, so called, 'DCF-Prime' of applying DCF method as to value companies in the early growth stage by taking all risk factors innate to the companies in the early growth stage as the discount rate Beta coefficient. Third, this paper propose more viable and solid valuation models, so called, 'DCF-Plus'of combing all validated valuation factors in Berkus, Scorecard, and Risk Factor Summation methods into applying separate discount bracket after DCF Valuation over the companies in the early growth stage instead of taking them as the factors of discount rate, beta coefficient, like the previous model of DCF-Prime. DCF-Plus mainly developed in this paper will not only provide more rational valuation bases as to investment negotiation between companies and investors in the early growth stage, but also providing more accountable guidelines to companies in the early growth as to prepare investment raising and accelerating their company's value by themselves.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.509-520
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• 2015

College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.

• Journal of Korean Society of Forest Science
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• v.34 no.1
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• pp.21-30
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• 1977

Japanese larch (Larix leptolepis) is one of main timber species in Korea that could find much plantation and growing stands on all over the country. It is thought to be in meaningful that a guiding diagram for density control of Japanese larch stands is made to estimate easily the density conditions in the quantitaive, ecological and economic viewpoint. Sample plots for this study are selected from the stands that have not been thinned in recent years, and mean height, mean diameter, dominant height, tree numbers per hectare and stem volume of mean tree are calculated from the each sample plots among total 165 plots In this study, especially, the theory of slenderness of mean tree are applied, that have been identified through the results of the spacing trial. Relative growth characteristics of this species are calculated from the general logistic curve and its formula is $Y=ax^b$. Relatwion between the measured items are found out as follows: 1. Relation between the mean height and tree numbers per hectare by slender class is showing the high correlation as table 1 and fig. 2, and between mean diameter and tree numbers per hectare is also high correlation as table 1 and fig 3. 2. The stem volume can be correctly estimated from height in case that slender class may be known, as showing in table 3 and fig. 4. 3. The stem volume can be more correctly estimated from the relation with $D^2H$ as formula, $Log_e\;V=0.9569\;Log_eD^2H-9.8431$, and relation between stem volume of single tree or volume per hectare and tree numbers per hectare are as following formulas: $Log_e$ stem volume=9.5026-1.6800 $Log_e$ tree numbers per hectare $Log_e$ stem volume per hectare=9.4911-0.6784 $Log_e$ tree numbers per hectare. Stem volume of mean tree, tree numbers per hectare and stem volume per hectare correspond to the mean tree height are calculated to slender class as table 5, 6, 7. Through the above steps, the diagram for density control of Japanese larch are produced as fig. 9. It is thought that this diagram could be applied to control the density of Japanese larch stands.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.353-365
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• 1998

Light absorption coefficient per unit mass of particles, i.e., specific absorption coefficient, is important as one of the main parameters in developing algorithms for ocean color remote sensing. Specific absorption coefficient of chlorophyll ($a^*_{ph}$) and suspended sediment ($a^*_{ss}$) were analyzed with a spectrophotometer using the "wet filter technique" and "Kishino method" for the seawater collected in the Yellow and Mediterranean Sea. An improved data-recovery method for the filter technique was also developed using spectrum slopes. This method recovered the baselines of spectrum that were often altered in the original methods. High $a^*_{ph}({lambda})$ values in the oligotrophic Mediterranean Sea and low values in the Yellow Sea were observed, ranging 0.01 to 0.12 $m^2$/mg at the chlorophyll maximum absorption wavelength of 440 nm. The empirical relationship between $a^*_{ph}$(440nm) and chlorophyll concentrations () was found to fit a power function ($a^*_{ph}$=0.039 $^{-0.369}$), which was similar to Bricaud et al. (1995). Absorption specific coefficients for suspended sediment ($a^*_{ss}$) did not show any relationship with concentrations of suspended sediment. However, an average value of $a^*_{ss}$ ranging 0.005 - 0.08 $m^2$/g at 440nm, was comparable to the specific absorption coefficient of soil (loess) measured by Ahn (1990). The morepronounced variability of $a^*_{ss}$ than $a^*_{ph}$ was determined from the variable mixing ratio values between particulate organic matter and mineral. It can also be explained by a wide size-distribution range for SS which were determined by their specific gravity, bottom state, depth and agitation of water mass by wind in the sea surface.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.835-848
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• 2021

In Jeju Island which has peculiarity for its geological features and hydrology system, hydrological factor analysis for the effective water management is necessary. Because in-situ hydro-meteorological data is affected by surrounding environment, the in-situ dataset could not be the spatially representative for the study area. For this reason, remote sensing data may be used to overcome the limit of the in-situ data. In this study, applicability assessment of MOD16 evapotranspiration data, Globas Land Data Assimilation System (GLDAS) based evapotranspiration/soil moisture data, and Advanced SCATterometer (ASCAT) soil moisture product which were evaluated their applicability on other study areas was conducted. In the case of evapotranspiration, comparison with total precipitation and flux-tower based evapotranspiration were conducted. And for soil moisture, 6 in-situ data and ASCAT soil moisture product were compared on each site. As a result, 57% of annual precipitation was calculated as evapotranspiration, and the correlation coefficient between MOD16 evapotranspiration and GLDAS evapotranspiration was 0.759, which was a robust value. The correlation coefficient was 0.434, indicating a relatively low fit. In the case of soil moisture, in the case of the GLDAS data, the RMSE value was less than 0.05 at all sites compared to the in-situ data, and a statistically significant result was obtained as a result of the significance test of the correlation coefficient. However, for satellite data, RMSE over than 0.05 were found at Wolgak and there was no correlation at Sehwa and Handong points. It is judged that the above results are due to insufficient quality control and spatial representation of the evapotranspiration and soil moisture sensors installed in Jeju Island. It is estimated as the error that appears when adjacent to the coast. Through this study, the necessity of improving the existing ground observation data of hydrometeorological factors is emphasized.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1657-1667
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• 2021

Anthropogenic activities and natural processes have been causes of land subsidence which is sudden sinking or gradual settlement of the earth's solid surface. Mexico City, the capital of Mexico, is one of the most severe land subsidence areas which are resulted from excessive groundwater extraction. Because groundwater is the primary water resource occupies almost 70% of total water usage in the city. Traditional terrestrial observations like the Global Navigation Satellite System (GNSS) or leveling survey have been preferred to measure land subsidence accurately. Although the GNSS observations have highly accurate information of the surfaces' displacement with a very high temporal resolution, it has often been limited due to its sparse spatial resolution and highly time-consuming and high cost. However, space-based synthetic aperture radar (SAR) interferometry has been widely used as a powerful tool to monitor surfaces' displacement with high spatial resolution and high accuracy from mm to cm-scale, regardless of day-or-night and weather conditions. In this paper, advanced interferometric approaches have been applied to get a time-series of land subsidence of Mexico City using four-year-long twenty ALOS PALSAR L-band observations acquired from Feb-11, 2007 to Feb-22, 2011. We utilized persistent scatterer interferometry (PSI) and small baseline subset (SBAS) techniques to suppress atmospheric artifacts and topography errors. The results show that the maximum subsidence rates of the PSI and SBAS method were -29.5 cm/year and -27.0 cm/year, respectively. In addition, we discuss the different subsidence rates where the study area is discriminated into three districts according to distinctive geotechnical characteristics. The significant subsidence rate occurred in the lacustrine sediments with higher compressibility than harder bedrock.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.