• Journal of Environmental Policy
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• v.12 no.4
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• pp.71-92
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• 2013

Unlike general public investment projects, when it comes to environmental public investment projects, there is a gap between those who pay the costs, and those who receive the benefits. This is because of the long term nature of environmental investments, which entails that the majority of the costs are paid by the current generation, while the benefits are reaped by future generations. Because of this, when the social discount rate is set at a standard, singular rate, an issue of relative underestimation of the benefits reaped by future generations may occur during the analytic process. This paper begins with the recognition of this problem, and attempts to estimate a suitable social discount rate that can be applied to environmental investment projects. Taking into account recent economic situations, the social discount rate is currently being estimated at between 2.9 ~ 4.9%. Also, this paper used preliminary feasibility studies that took place so far, to analyze the standard pattern of benefit generation. This revealed that alterations in social discount rates can bring significant changes in economic feasibility test results. Simulation results showed that roughly 6% of B/C ratios could be increased by 1%p. resulting in a decrease in social discount rates. Also if we use hyperbolic discount rates, instead of using the current singular rate, there would be a meaningful increase in the benefits for the future generation.

• Journal of the Korean Geotechnical Society
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• v.17 no.6
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• pp.25-36
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• 2001

The purpose of this paper is to discuss the effects of soil properties such as liquid limit, water content, etc. on the compression index and to propose the empirical equation of compression index far regional clay and to verify the application Back Propagation Neural Network(BPNN). The compression index values obtained from laboratory tests are in the range of 0.01 to 3.06 for clay soils sampled in eleven regions. As the compare with the results of laboratory test and the predicted compression index value from the proposed empirical equations, the results of empirical equations including single soil parameter have a possibility to be overestimated. Also, the results of empirical equations including multiple soil parameters closed to the measured value more than that of empirical equations including single soil parameter, but the standard error for measured value obtained larger than 0.05. For these reasons, the empirical equations including single or multiple soil parameters proposed base on the results of laboratory test and the determination coefficient is up to 0.89. The result of BPNN shows that correlation coefficient and standard error between test and neural network result is larger than 0.925 and smaller than 0.0196, which means high correlativity, respectively. Especially, the estimated result by neural network, using only three parameters such as natural water content, dry unit weight and in-situ void ratio among various factors is available to the estimation of compression index and the correlation coefficient is 0.974. This result verified the possibility that if BPNN use, the compression index can be predicted by the parameters, which obtained from simplex field test.

• Journal of the Korean association of regional geographers
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• v.12 no.5
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• pp.614-630
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• 2006

Improved estimates of populations at risk for quick and effective response to natural and man-made disasters require spatial disaggregation of zonal population data because of the spatial mismatch problem in areal units between census and impact zones. This paper implements a dasymetric surface model to facilitate spatial disaggregation of the population of a census block group into populations associated with each constituent pixel and evaluates the performance of the surface-based spatial disaggregation model visually and statistically. The surface-based spatial disaggregation model employed geographic information systems (GIS) to enable dasymetric interpolation to be guided by satellite-derived land use and land cover data as additional information about the geographic distributor of population. In the spatial disaggregation, percent cover based empirical sampling and areal weighting techniques were used to objectively determine dasymetric weights for each grid cell. The dasymetric population surface for the Atlanta metropolitan area was generated by the surface-based spatial disaggregation model. The accuracy of the dasymetric population surface was tested on census counts using the root mean square error (RMSE) and an adjusted RMSE. The errors related to each census track and block group were also visualized by percent error maps. Results indicate that the dasymetric population surface provides high-precision estimates of populations as well as the detailed spatial distribution of population within census block groups. The results also demonstrate that the population surface largely tends to overestimate or underestimate population for both the rural and forested and the urban core areas.

• Journal of the Korean Geotechnical Society
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• v.19 no.1
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• pp.93-102
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• 2003

Unconfined compression test (UC) has been widely used to determine the undrained shear strength ($c_u$) of clay, because it is convenient and economical. However, UC can not represent the behaviour of in-situ stress condition and the strength obtained by the test is generally underestimated compared to that of triaxial compression, due to no confining pressure. Therefore, a simple and practical method to correct the ($c_u$) for sample disturbance and to be used in geotechnical practice is needed. This study is aimed at proposing the method to estimate in-situ undrained shear strength from UC with suction measurement. The proposed method is based on theoretical shear strength equation of perfect sample (Noorany & Seed, 1965), and effective overburden stress and analysis results ($A_f,\phi'$) of effective stress behaviour by UC are needed for the equation. The shear resistance angle ($\phi'$) can be simply estimated through the result that $K_f$-line slope of the UC is 1.6 times higher than that of triaxial compression test. The result of this study shows that the measured strength by this method is very similar to that of the undrained shear strength by triaxial compression test (CK$_0$UC).

• Economic and Environmental Geology
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• v.47 no.2
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• pp.133-146
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• 2014

There are many studies for the economic impact assessment of natural disasters, but there are few for volcanic disasters. Domestic academic research is not under active discussion because of the lack of national and social interest for volcanic eruption. This study investigated the research methodology for the economic impact assessment of natural disasters and discussed whether these can be applied to the economic impact analysis for the Baekdu Mountain volcanic disaster. The main findings are as follows: Firstly, Asia-Pacific region is the most affected by natural disasters and has the largest scale of damage. Asian and American Continent have the most economic damage. Secondly, Considering the types of damage caused by natural disasters and its complex structure, several methodologies that could be possible to estimate economic consequential damages have been compared. When applying each methodology to the Baekdu Mountain volcanic disaster, the scale of damage is likely to be over-estimated or under-estimated because of model-specific features. Thus, estimated values should be compared to each other after calculating the damage results. Thirdly, Japanese academic research on the volcanic disaster will be used as the starting point of the economic impact assessment studies for Baekdu Mountain. Using computer SW such as Hazus which is used in United States and RiskScape from New Zealand is also a good method to predict economic impact of the Baekdu Mountain volcanic disaster.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.581-594
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• 2011

The traditional method of 3+3 standard design and model-based Bayesian continual reassessment method (CRM) are commonly used in Phase I clinical trials to identify the maximal tolerated dose(MTD) of a new drug. In this paper we review clinical examples of Phase I trials that were carried out in patients with refractory or relapsed leukemia and myelodysplastic syndrome. The recently proposed 3+1+1 design and rolling-6 design can shorten the trial duration, when a very slow accrual of patients with a simple 3+3 standard design may result in the untimely termination of trials. Too conservative approaches in determining the dose levels in Phase I clinical trials can leave clinical investigators unable to accurately determine the MTD. When determining future patient doses, the designs that use a time-to-event CRM can cooperate late toxicities by accounting for the proportion of the observation period of each enrolled patient. With the CRM design, simulations under different scenarios during the trial are important in detecting the under- or over-estimation of the initial estimate of the dose-limiting toxicity rate for each dose level. We present the advantages and drawbacks of the designs used in Phase I clinical trials for leukemia patients.

• Journal of Korea Water Resources Association
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• v.49 no.12
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• pp.1007-1014
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• 2016

The FORGEX (Focused Rainfall Growth Extension) method was developed to estimate rainfall quantiles in the United Kingdom. This method does not need any regional grouping and can estimate rainfall quantiles with relatively long return period. The spatial dependence formula (ln $N_e$) was derived to consider the distance from growth curve of proper population to the distributed network maximum (netmax) data using the UK rainfall data. For this reason, there is an inaccurate problem in rainfall quantiles when this formula is applied in Korea. In this study, the new formula was derived in order to improve such shortcomings using rainfall data of 64 sites from the Korea Meteorological Administration (KMA). A 42-year period (1973~2014) was taken as the reference period from rainfall data, then the formula was derived using three parameters such as rainfall duration, number of site, area of network. Then the new formula was applied to the FORGEX method for regional rainfall frequency analysis. In addition, rainfall quantiles were compared with those from the UK formula. As a result, the new formula shows more accurate results than the UK formula, in which the FORGEX method by the UK formula underestimates rainfall quantiles. Finally, the new improved formula may estimate accurate rainfall quantiles for long return period.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.69-81
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• 2011

The soil moisture data of the National Aeronautics and Space Administration(NASA) and the Vrije Universiteit Amsterdam(VUA) in collaboration with NASA, retrieved from Advanced Microwave Scanning Radiometer-Earth observing system(AMSR-E) brightness temperature, were collected to evaluate the applicability of the remote sensed soil moisture in South Korea. The averages of the soil moisture by in-situ sensors, by NASA and by VUA-NASA are approximately 0.218, 0.119, and $0.402m^3/m^3$, respectively. This indicates that the soil moisture of NASA was underestimated and that of VUA-NASA was overestimated. The soil moisture products of VUA-NASA showed a better relationship with the in-situ data than that of NASA data. However, there are still limitations of C-band soil moisture measurements. To improve the applicability of satellite soil moisture measurements, bias correction and other post processings are essential using in-situ soil moisture measurements at various surface conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.253-263
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• 2016

Chrysanthemum production would benefit from crop growth simulations, which would support decision-making in crop management. Chrysanthemum is a typical short day plant of which floral initiation and development is sensitive to photoperiod. We developed a model to predict phenological development and leaf appearance of chrysanthemum (cv. Baekseon) using daylength (including civil twilight period), air temperature, and management options like light interruption and ethylene treatment as predictor variables. Chrysanthemum development stage (DVS) was divided into juvenile (DVS=1.0), juvenile to budding (DVS=1.33), and budding to flowering (DVS=2.0) phases for which different strategies and variables were used to predict the development toward the end of each phenophase. The juvenile phase was assumed to be completed at a certain leaf number which was estimated as 15.5 and increased by ethylene application to the mother plant before cutting and the transplanted plant after cutting. After juvenile phase, development rate (DVR) before budding and flowering were calculated from temperature and day length response functions, and budding and flowering were completed when the integrated DVR reached 1.33 and 2.0, respectively. In addition the model assumed that leaf appearance terminates just before budding. This model predicted budding date, flowering date, and leaf appearance with acceptable accuracy and precision not only for the calibration data set but also for the validation data set which are independent of the calibration data set.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.85-93
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• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.