• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1169-1180
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• 2013

The objectives of this study are to construct the natural streamflow in the Bokhacheon middle-upper watershed using the SWAT-K model and to assess the impacts of groundwater withdrawals, water intake, treated sewage water release on streamflow. The simulated natural streamflow from 2006 to 2013 showed the minimum discharge of $1.7m^3/s$, the annual average discharge of $26.2m^3/s$, the drought flow of $2.0m^3/s$ at the outlet of the study area. The simulated results indicated that the groundwater pumping has induced the decrease of 34% in drought flow against the natural condition and the net water release has caused the increase of 15%, while the combined effects of the groundwater pumping and the net water release have induced the decrease of 19%. It was found out from the simulated natural streamflow data that the specific discharges of the abundant flow, normal flow, low flow, drought flow in the upper-middle channels of the Bokha-cheon watershed have a tendency to increase as the drainage area increases, but the specific discharges showed almost constant values at any downstream point with drainage area more than about 180 $km^2$.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.277-307
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• 2016

Since 2011, DCF(Discounted Cash Flow) method has been used initiatively for valuating R&D technology assets in the agricultural food industry and recently technology valuation based on royalties comparison among technology transfer transactions has been also carried out in parallel when evaluating the technology assets such as new seed development technologies. Since the DCF method which has been known until now has many input variables to be estimated, sophisticated estimation has been demanded at the time of technology valuation. In addition, considering more similar trading cases when applying sales transaction comparison or industry norm method based on information of technology transfer royalty, it is an important issue that should be taken into account in the same way in the Agri-Food industry. The main input variables used for technology valuation in the Agri-Food industry are life cycle of technology asset, the financial information related to the Agri-Food industry, discount rate, and technology contribution rate. The latest infrastructure building and data updating related to technology valuation has been carried out on a regular basis in the evaluation organization of the Agri-Food segment. This study verifies the key variables that give the most important impact on the results for the existing technology valuation in the Agri-Food industry and clarifies the difference between the existing valuation result and the outcome by referring the support information that is derived through the latest input information applied in DCF method. In addition, while presenting the scheme to complement fragment information which the latest input data just influence result of technology valuation, we tried to perform comparative analysis between the existing valuation results and the evaluated outcome after the latest of reference data for making a decision the input values to be estimated in DCF. To perform these analyzes, it was first selected the representative cases evaluated past in the Agri-Food industry, applied a sensitivity analysis for input variables based on these selected cases, and then executed a simulation analysis utilizing the key input variables derived from sensitivity analysis. The results of this study is to provide the information which there are the need for modernization of the data related to the input variables that are utilized during valuating technology assets in the Agri-Food sector and for building the infrastructure of the key input variables in DCF. Therefore it is expected to provide more fruitful information about the results of valuation.

• Korean Journal of Environment and Ecology
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• v.25 no.5
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• pp.787-798
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• 2011

An arboretum is defined as a collection of facilities that conserve plant species by surveying, collecting, and proliferating and preserving the plants in nature, perform diverse researches on plants and display the plants in exhibition spaces or outdoors as well as provide the public with educational programs and refreshment spaces according to the laws concerned. The public, however, recognizes the exhibition and education functions on plants of arboretum more importantly compared with the roles to survey, collect, and proliferate plants as regulated by the laws. In particular, arboretum plays a role to offer a pivotal educational place in urban area where the public can obtain an hands-on experience and understanding on a wide range of plant species and natural environment. The study aims to estimate the non market environmental values of Daegu Arboretum operated by Daegu Metropolitan City government by using the Contingent Valuation Methods (CVM), which yields the current monetary estimates for the arboretum. The value estimation was undertaken by using the Double-Bound Dichotomous Choice (DBDC) method, and each estimated value was derived from respective functions based on a logit distribution known to include relatively stable estimates according to the shape of the distribution. Considering the statistical fitness test results, the author estimated the amounts of the Willingness To Pay (WTP) such as mean WTP of 12,718 KRW, median WTP of 11,033 KRW, and truncated mean WTP of 11,468 KRW, which represented the annual recreational values per a person visiting Daegu Arboretum respectively. The analysis showed that Daegu Arboretum created the annual environmental values which were estimated to be approximately 16 to 19 billion KRW. The study also has an implication that the valuation method for the environment of Daegu Arboretum may be effectively applied for estimating the values of other types of environmental goods by altering the locations or goods to be analyzed.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.477-483
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• 2020

We constructed a stand yield table for Chamaecyparis obtusa based on data from an actual forest. The previous stand yield table had a number of disadvantages because it was based on actual forest information. In the present study we used data from more than 200 sampling plots in a stand of Chamaecyparis obtusa. The analysis included theestimation, recovery and prediction of the distribution of values for diameter at breast height (DBH), and the result is a valuable process for the preparation ofstand yield tables. The DBH distribution model uses a Weibull function, and the site index (base age: 30 years), the standard for assessing forest productivity, was derived using the Chapman-Richards formula. Several estimation formulas for the preparation of the stand yield table were considered for the fitness index, and the optimal formula was chosen. The analysis shows that the site index is in the range of 10 to 18 in the Chamaecyparis obtusa stand. The estimated stand volume of each sample plot was found to have an accuracy of 62%. According to the residuals analysis, the stands showed even distribution around zero, which indicates that the results are useful in the field. Comparing the table constructed in this study to the existing stand yield table, we found that our table yielded comparatively higher values for growth. This is probably because the existing analysis data used a small amount of research data that did not properly reflect. We hope that the stand yield table of Chamaecyparis obtusa, a representative species of southern regions, will be widely used for forest management. As these forests stabilize and growth progresses, we plan to construct an additional yield table applicable to the production of developed stands.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.3
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• pp.375-388
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• 2019

Accurate evaluation of sea-to-air $CO_2$ flux and its variability is crucial information to the understanding of global carbon cycle and the prediction of atmospheric $CO_2$ concentration. $fCO_2$ observations are sparse in space and time in the East Sea. In this study, we derived high resolution time series of surface $fCO_2$ values in the southwest East Sea, by feeding sea surface temperature (SST), salinity (SSS), chlorophyll-a (CHL), and mixed layer depth (MLD) values, from either satellite-observations or numerical model outputs, to three machine learning models. The root mean square error of the best performing model, a Random Forest (RF) model, was $7.1{\mu}atm$. Important parameters in predicting $fCO_2$ in the RF model were SST and SSS along with time information; CHL and MLD were much less important than the other parameters. The net $CO_2$ flux in the southwest East Sea, calculated from the $fCO_2$ predicted by the RF model, was $-0.76{\pm}1.15mol\;m^{-2}yr^{-1}$, close to the lower bound of the previous estimates in the range of $-0.66{\sim}-2.47mol\;m^{-2}yr^{-1}$. The time series of $fCO_2$ predicted by the RF model showed a significant variation even in a short time interval of a week. For accurate evaluation of the $CO_2$ flux in the Ulleung Basin, it is necessary to conduct high resolution in situ observations in spring when $fCO_2$ changes rapidly.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.4
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• pp.307-325
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• 1995

IN order to gain a fundamental data for forecast or control of fish behavior and evaluated the feasibility of an application of the modeling technique to a field, in this paper a numerical model for describing the behavior of fishes in a water tank was presented. The parameters of the model were estimated by using the time-series data on the three-dimensional position of fishes and by applying the least squares algorithm. The estimated parameters were standardized to examine the variation of parameters according to the number of individuals and flow speed that the mean values of parameters were to be zero and their variances were to be one. The results obtained can be summarized as follows: (1) The standardized parameter $a^*$of propulsive force decreased according to increased the number of individuals and the flow speed. (2) The standardized parameter ${k_b}^*$ of interactive force increased according to increased the number of individuals, but decreased according to the flow speed. (3) The standardized parameter ${k_c}^*$ of schooling force increased according to │increased the number of individuals and the flow speed. (4) The standardized parameter │${k_w}^{+*}$│ of repulsive force against wall or bottom increased according to increased the number of individuals, but decreased according to the flow speed. (5) The standardized parameter │${k_w}^{-*}$│ of attractive force against wall or bottom was generally constant according to increased the number of individuals, but increased according to the flow speed. (6) The standardized parameter $\upsilon$ super(*) of damping force increased according to increased the number of individuals, but decreased according to the flow speed.

• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.720-734
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• 2023

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (M_e) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between M_e and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between M_e and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the M_e, the higher the accuracy of EBV.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.438-449
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• 2020

This study is to improve the method of calculating the risk of liability that arise from release and dispersion of chemicals outside the plant in process industries such as chemical and petrochemical plants. To achieve this goal, the correlation factors with the risk of chemical release accident is derived by simulating release and dispersion of substances (14 types) designated by Ministry of Environment as preparation for accident, analyzing the cases of chemical release and effects of plant life damage. The method of calculating chemical liability risk was modified and supplemented based on the results obtained from the study. The correlation coefficient between the probit value of 14 chemical types and the liability risk by EURAM (European Union Risk Ranking Method) was -0.526, while the correlation coefficient with the modified chemical release accident risk was 0.319. Thus, the value from modified method shows that they appear to be correlated. According to modified calculating methodology, the correlation between ERPG-2 value and liability risk of 97 chemical types was -0.494 which is 19 times higher than existing liability risk correlation as absolute value. And the correlation coefficient of corrosion risk was 0.91. The standardized regression coefficients (β) value of correlation factors that affected the increase and decrease of risk were derived in order of Corrosion Index(0.713), ERPG-2 (0.400) and NFPA Health Index (0.0680) by values. It is expected that these findings this study result will also enable the calculation of reasonable chemical release liability risk for existing and new chemical, and will help use them as quantitative liability risk management indicators for chemical plant site.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.69 no.3
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• pp.154-162
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• 2024

In response to the increasing impact of climate change on agriculture, various cultivation technologies have been recently developed to improve agricultural productivity and reduce carbon emissions for carbon neutrality. This study presents an algorithm for estimating rice planting density in agriculture using drone-captured images and deep learning-based image analysis technology. The algorithm utilizes images collected from various paddies; these images are processed through pre-processing steps and serve as training data for the YOLOv5x deep learning model. The trained model demonstrated high precision and recall, effectively estimating the position information of rice plants in each image. By accurately estimating the position of rice plants based on the central coordinates in diverse unpaved environments, the model allowed for estimation of rice plant density in each paddy, producing values closely aligned with actual measurements. Moreover, the algorithm proposed in this study provides a novel approach for precise determination of rice planting density based on the position information of rice plants in the images. Analysis of drone footage from different regions capturing portions of paddies revealed that the developed algorithm exhibited a significant correlation (R² =0.877) with actual planting density. This finding suggests the potential effective application of the algorithm in real-world agricultural settings. In conclusion, we believe that this research contributes to the ongoing digital transformation in agriculture by offering a valuable technology that supports the goals of enhancing efficiency, mitigating methane emissions, and achieving carbon neutrality, in response to the challenges posed by climate change.

• Korean Journal of Food Science and Technology
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• v.32 no.3
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• pp.519-524
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• 2000

This study has been carried out to estimate the amount of the daily intake on artificial sweetener(aspartame and sodium saccharin) and antioxidants(propyl gallate, BHA, BHT and TBHQ) in food consumed by Korean. The mean daily intake for each food item were obtained from the report of National Nutrition Survey carried by Ministry of Health and Welfare in 1997. The contents of artificial sweetener and antioxidants have been analyzed by HPLC. Aspartame was detected on 22 of 239 samples in the range of $33.4{\sim}3308.0\;mg/kg$, sodium saccharin was detected on 6 of 115 samples in the range of $8.3{\sim}41.8\;mg/kg$. BHA(204.9 mg/kg) was detected in Chewing gum only. Total estimated daily intake(EDI) of each additives per capita per day are as follows; 2.336 mg/person/day for aspartame, 0.259 mg/person/day for sodium saccharin and 0.002 mg/person/day for BHT. These values were less than 1% of FAO/WHO's acceptable daily intake(ADI).