• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.88-99
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• 2007

Soil moisture is one of the essential components in determining surface hydrological processes such as infiltration, surface runoff as well as meteorological, ecological and water quality responses at watershed scale. This paper discusses soil moisture transfer processes measured at hillslope scale in the Gwangneung forest catchment to understand and provide the basis of stochastic structures of soil moisture variation. Measured soil moisture series were modelled based upon the developed univariate model platform. The modeling consists of a series of procedures: pre-treatment of data, model structure investigation, selection of candidate models, parameter estimation and diagnostic checking. The spatial distribution of model is associated with topographic characteristics of the hillslope. The upslope area computed by the multiple flow direction algorithm and the local slope are found to be effective parameters to explain the distribution of the model structure. This study enables us to identify the key factors affecting the soil moisture distribution and to ultimately construct a realistic soil moisture map in a complex landscape such as the Gwangneung Supersite.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.83-94
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• 2010

The objective of this study was to determine the best probability distributions of annual, seasonal and monthly precipitation in Korea. Data observed at 32 stations in Korea were analyzed using the L-moment ratio diagram and the average weighted distance (AWD) to identify the best probability distributions of each precipitation. The probability distribution was best represented by 3-parameter Weibull distribution (W3) for the annual precipitation, 3-parameter lognormal distribution (LN3) for spring and autumn seasons, and generalized extreme value distribution (GEV) for summer and winter seasons. The best probability distribution models for monthly precipitation were LN3 for January, W3 for February and July, 2-parameter Weibull distribution (W2) for March, generalized Pareto distribution (GPA) for April, September, October and November, GEV for May and June, and log-Pearson type III (LP3) for August and December. However, from the goodness-of-fit test for the best probability distributions of the best fit, GPA for April, September, October and November, and LN3 for January showed considerably high reject rates due to computational errors in estimation of the probability distribution parameters and relatively higher AWD values. Meanwhile, analyses using data from 55 stations including additional 23 stations indicated insignificant differences to those using original data. Further studies using more long-term data are needed to identify more optimal probability distributions for each precipitation.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1096-1127
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• 2011

This research focus on estimating the economic effects of TOD system development from the perspective of new market creation, R&D planning cost reduction and increase of R&D projects' commercialization success rates. The research is conducted through simulation and scenario analysis with assumptions about economic effect parameters. Scenario analysis shows that scenario 1 (the application ratio of the new TOD system to total Korean R&D programs' planning is 1.4%) results in total economic effects, 921.3 billion won in 2011 price with B/C ratio 6.15, that scenario 2 (the application ratio is 1.9%) results in total economic effects, 1,250.3 billion won in 2011 price with B/C ratio 8.34, and that scenario 3 (the application ratio is 0.9%) results in total economic effects, 592.2 billion won in 2011 price with B/C ratio 3.95. The research contributed to the prior evaluation of economic validity of "R&D on Technology Opportunity Development (TOD) system" and to cultivating the new methodology of economic benefit estimation in the area of R&D on system development.

• Geophysics and Geophysical Exploration
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• v.10 no.3
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• pp.163-172
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• 2007

A seafloor curvature measurement method was developed to extract redundant topographic features from the multi-beam bathymetry data, and then applied to the data of abyssal plain area in the Pacific. Any seafloor might be modeled to a quadratic surface determined in a linear least squares sense, and its curvature could be derived from the eigen values related with quadratic model parameters. The curvature's magnitude as well as polarity showed distinct relationship with geometric characteristics of the seafloor like as ridge and valley. From the investigation of curvature's variation with the number of data in the quadratic surface, the optimal size of data aperture could be applied to real bathymetry data. The application to real data also required the determination of the accompanying threshold values to cope with corresponding topographic features. The calculation method of previous studies were reported to be sensitive to the background noise. The improved curvature measurement method, incorporating the sum of eigen values has reduced unwanted artifacts and enhanced ability to extract lineament features along strike direction. The result of application shows that the curvature measurement method is effective tool for the estimation of a possible mining area in the seamount free abyssal hill area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.70-81
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• 2020

Point-by-point data, which is abundantly collected by vehicles with embedded GPS (Global Positioning System), generate useful information. These data facilitate decisions by transportation jurisdictions, and private vendors can monitor and investigate micro-scale driver behavior, traffic flow, and roadway movements. The information is applied to develop app-based route guidance and business models. Of these, speed data play a vital role in developing key parameters and applying agent-based information and services. Nevertheless, link speed values require different levels of physical storage and fidelity, depending on both collecting and reporting intervals. Given these circumstances, this study aimed to establish an appropriate collection interval to efficiently utilize Space Mean Speed information by vehicles with embedded GPS. We conducted a comparison of Probe-vehicle data and Image-based vehicle data to understand PE(Percentage Error). According to the study results, the PE of the Probe-vehicle data showed a 95% confidence level within an 8-second interval, which was chosen as the appropriate collection interval for Probe-vehicle data. It is our hope that the developed guidelines facilitate C-ITS, and autonomous driving service providers will use more reliable Space Mean Speed data to develop better related C-ITS and autonomous driving services.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.1-15
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• 2004

For the simulation of flow phenomenon that calculate basin outflow, it is required to estimate effective precipitation which contributes to direct runoff. This paper is focused on using detailed soil map which is one of the data required to estimate effective precipitation by SCS CN method. Korean detailed soil map must be reclassified as SCS hydrologic soil group when it is applied to SCS CN method. In this study, Korean detailed soil maps which are reclassified as SCS hydrologic soil group by the methods of Her and Jung (1987) and Jung et al. (1995) are applied to flow simulation and the results are analyzed. The study sites are Wichon watershed and Pyungchang river basin which are studied by International Hydrological Program(IHP). HEC-1 and WMS v6.1 are used to simulate flow phenomenon and calculate geographic parameters. The difference of flow analysis results from each soil reclassification method is different from each sites. But the results of flow analysis approximate observed data by using Jung et al. (1995) method more than Her and Jung (1987) method.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.199-226
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• 2009

We examine the intertemporal relation between risk and return in the Korean stock market and foreign exchange market based on the two factor ICAPM framework. The standard GARCH model and the GJR(1993) model are employed to estimate conditional variances of the stock returns and foreign exchange rates. The covariance between the rates of stock returns and changes in the exchange rates are estimated by the constant conditional correlation model of Bollerslev(1990) and the dynamic conditional correlation model of Engle(2002). The multivariate GARCH in mean model and quasi-maximum likelihood estimation method, consequently, are applied to investigate riskreturn relation jointly. We find that the estimated coefficient of relative risk aversion is negative and statistically significant in the post-financial crisis sample period in the Korean stock market. We also show that the expected stock returns are negatively related to the dynamic covariance with foreign exchange rates. Both estimated parameters of conditional variance and covariance in the foreign exchange market, however, are not statistically significant. The GJR model is better than the standard GARCH model to estimate the conditional variances. In addition, the dynamic conditional correlation model has higher explanatory power than the constant correlation model. The empirical results of this study suggest following two points to investors and risk managers in hedging and diversifying strategies for their portfolios in the Korean stock market: first, the variability of foreign exchange rates should be considered, and second, time-varying correlation between stock returns and changes in foreign exchange rates supposed to be considered.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.297-307
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• 2017

The epidemic model is used to model the spread of disease and to control the disease. In this research, we utilize SEIR model which is one of applications the SIR model that incorporates Exposed step to the model. The SEIR model assumes that a people in the susceptible contacted infected moves to the exposed period. After staying in the period, the infectee tends to sequentially proceed to the status of infected, recovered, and removed. This type of infection can be used for research in cases where there is a latency period after infectious disease. In this research, we collected respiratory infectious disease data for the Middle East Respiratory Syndrome Coronavirus (MERSCoV). Assuming that the spread of disease follows a stochastic process rather than a deterministic one, we utilized the Poisson process for the variation of infection and applied epidemic model to the stochastic chemical reaction model. Using observed pandemic data, we estimated three parameters in the SIER model; exposed rate, transmission rate, and recovery rate. After estimating the model, we applied the fitted model to the explanation of spread disease. Additionally, we include a process for generating the Exposed trajectory during the model estimation process due to the lack of the information of exact trajectory of Exposed.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.723-728
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• 2006

Since the forest succession is changing process in the structure and function of a forest for the long period of time, the objectivity of the process could be improved through the development of model or statistical methodology. This study was carried out to estimate succession index based on climax index and species composition parameters, thereupon to compare the succession index with life form and species diversity so as to grasp the information of quantitative successional process for the six community types in the natural deciduous forest of Mt. Jumbong area. The results indicated that Quercus mongolica-Tilia amurensis community had the greatest succession index of 67.5, followed by Abies holophylla-Fraxinus mandshurica community with 67.4. Juglans mandshurica-Cornus controversa community was recorded the smallest value of 60.5. The succession index of overstory tended to increase considerably at the stage of steady state for all community types except Quercus mongolica-Tilia amurensis community. However, The index of midstory hardly varied as the forest succession would progress for all community types. The succession index was negatively correlated to wind-water dispersion type of life form and positively to animal dispersion type at the 5% probability level. On the other hand, the index was not significantly correlated to the species richness and Shannon's species diversity index.

• Journal of Bio-Environment Control
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• v.25 no.3
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• pp.146-152
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• 2016

Due to complicate canopy structures of Irwin mangoes grown in greenhouses, it is difficult to determine their growth parameters accurately. Leaf area, leaf fresh weight, and leaf dry weight are widely used as indicators to diagnose the tree growth. Therefore, it is necessary to establish models that can non-destructively estimate these growth indicators. The objective of this study was to establish regression models to estimate leaf area, leaf fresh weight, and leaf dry weight of Irwin mangoes (Mangifera indica L. cv. Irwin) by using leaf length, leaf width, petiole length, and SPAD value. The input values of leaf length, leaf width, petiole length, and SPAD value of 6-year old Irwin mangoes were measured, and the corresponding output values of leaf area, leaf fresh weight, and leaf dry weight were also measured. After 14 models were selected among the existing models, coefficients of the models were estimated by regression analysis. Three models with higher $R^2$ and lower RMSE values selected. In validation the $R^2$ values for the selected models were 0.967, 0.743, and 0.567 in the leaf area, leaf fresh weight, and leaf dry weight models, respectively. It is concluded that this models will be helpful to conveniently diagnose the growth of the Irwin mango.