• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.33-40
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• 2013

From March 2012 to January 2013, this study was conducted as a part of the project for making a precise electronic ecological zoning map of vegetation on a highly reduced scale of 1 to 5,000 with a view to improving management efficiency of national parks and enlarging the availability of the data produced from the basic research monitoring the resources of national parks. For the research accuracy and rapidity, a vegetation map was specially created for the on-the-site-vegetation research. To make the map more meticulous, we categorized the vegetation database into five groups: broadleaved forest, coniferous forest, mixed forest, rock vegetation and miscellaneous one. After comparing the results of the data built for the vegetation research and the actual research findings, it was made clear that vegetation of both categories was almost the same in case of broad-leaved forest with 72.20% and 78.45% respectively, and also equivalent in other groups like, for example, coniferous forest (16.70%, 13.41%), mixed forest (9.50%, 7.49%) and rock vegetation (0.60%, 0.15%). According to the precise vegetation map produced from the research, the deciduous broad-leaved forest was the most widely prevalent type in the correlated hierarchical classification of vegetation, occupying 65.78% of the overall vegetation. It was followed by mountain valley forest (15.17%), coniferous forest (10.90%), and plantation forest (7.00%) in order. It is particularly noteworthy that Mt. Deogyusan national park has retained a very stable and versatile forest vegetation in the outstanding state since approximately 20% of the mountain turns out to belong to the I grade vegetation conservation classification which contains climax forests, unique vegetation, subalpine vegetation, matured stands which are older than 50 years and etc.

• Food Science of Animal Resources
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• v.24 no.4
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• pp.349-354
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• 2004

Stress-susceptible pigs have been known as the porcine stress syndrome (PSS), swine PSS, also known as malignant hyperthermia (MH), is characterized as sudden death and production of poor meat quality such as PSE (pale, soft and exudative) meat after slaughtering. PSS and PSE meat cause major economic losses in the pig industry. A point mutation in the gene coding for the ryanodine receptor (RYR1) in porcine skeletal muscle, also known calcium (Ca$^{2+}$) release channel, has been associated with swine PSS and halothane sensitivity. We used the PCR-RFLP(restriction fragment length polymorphism) and PCR-SSCP (single strand conformation polymorphism) methods to detect the PSS gene mutation (C1843T) in the RYR1 gene and to estimate genotype frequencies of PSS gene in Korean pig breed populations. In PCR-RFLP and SSCP analyses, three genotypes of homozygous normal (N/M), heterozygous carrier (N/n) and homozygous recessive mutant (n/n) were detected using agarose or polyacrylamide gel electrophoresis, respectively. The proportions of normal, carrier and PSS pigs were 57.1, 35.7 and 7.1％ for Landrace, 82.5, 15.8 and 1.7％ far L. Yorkshire, 95.2, 4.8 and 0.0％ for Duroc and 72.0, 22.7 and 5.3％ for Crossbreed. Consequently, DNA-based diagnosis for the identification of stress-susceptible pigs of PSS and pigs producing PSE meat is a powerful technique. Especially, PCR-SSCP method may be useful as a rapid, sensitive and inexpensive test for the large-scale screening of PSS genotypes and pigs with PSE meat in the pork industry.y.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.35-44
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• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.537-546
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• 2014

Surface image velocimetry was introduced as an efficient and sage alternative to conventional river flow measurement methods during floods. The conventional surface image velocimetry uses a pair of images to estimate velocity fields using cross-correlation analysis. This method is appropriate to analyzing images taken with a short time interval. It, however, has some drawbacks; it takes a while to analyze images for the verage velocity of long time intervals and is prone to include errors or uncertainties due to flow characteristics and/or image taking conditions. Methods using spatio-temporal images, called STIV, were developed to overcome the drawbacks of conventional surface image velocimetry. The grayscale-gradient tensor method, one of various STIVs, has shown to be effectively reducing the analysis time and is fairly insusceptible to any measurement noise. It, unfortunately, can only be applied to the main flow direction. This means that it can not measure any two-dimensional flow field, e.g. flow in the vicinity of river structures and flow around river bends. The present study aimed to develop a new method of analyzing spatio-temporal images in two-dimension using cross-correlation analysis. Unlike the conventional STIV, the developed method can be used to measure two-dimensional flow substantially. The method also has very high spatial resolution and reduces the analysis time. A verification test using artificial images with lid-driven cavity flow showed that the maximum error of the method is less than 10 % and the average error is less than 5 %. This means that the developed scheme seems to be fairly accurate, even for two-dimensional flow.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.821-831
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• 2013

Recently image velocimetries, including particle image velocimetry (PIV) and surface image velocimetry (SIV), are often used to measure flow velocities in laboratories and rivers. The most difficult point in using image velocimetries may be how to determine the sizes of the interrogation areas and the measurement uncertainties. Especially, it is a little hard for unskilled users to use these instruments, since any standardized measuring techniques or measurement uncertainties are not well evaluated. Sometimes the user's skill and understanding on the instruments may make a wide gap between velocity measurement results. The present study aims to evaluate image velocimetry's uncertainties due to the changes in the sizes of interrogation areas and searching areas with the error analyses. For the purpose, we generated 12 series of artificial images with known velocity fields and various numbers and sizes of particles. The analysis results showed that the accuracy of velocity measurements of the image velocimetry was significantly affected by the change of the size of interrogation area. Generally speaking, the error was reduced as the size of interrogation areas became small. For the same sizes of interrogation areas, the larger particle sizes and the larger number of particles resulted smaller errors. Especially, the errors of the image velocimetries were more affected by the number of particles rather than the sizes of them. As the sizes of interrogation areas were increased, the differences between the maximum and the minimum errors seemed to be reduced. For the size of the interrogation area whose average errors were less than 5%, the differences between the maximum and the minimum errors seemed a little large. For the case, in other words, the uncertainty of the velocity measurements of the image velocimetry was large. In the viewpoint of the particle density, the size of the interrogation area was small for large particle density cases. For the cases of large number of particle and small particle density, however, the minimum size of interrogation area became smaller.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.807-819
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• 2013

This study proposes a new methodology for future water balance projection considering climate change by assigning a weight to each scenario instead of inputting future streamflows based on GCMs into a water balance model directly. K-nearest neighbor algorithm was employed to assign weights and streamflows in non-flood period (October to the following June) was selected as the criterion for assigning weights. GCM-driven precipitation was input to TANK model to simulate future streamflow scenarios and Quantile Mapping was applied to correct bias between GCM hindcast and historical data. Based on these bias-corrected streamflows, different weights were assigned to each streamflow scenarios to calculate water shortage for the projection periods; 2020s (2010~2039), 2050s (2040~2069), and 2080s (2070~2099). As a result by applying the proposed methodology to project water shortage over the Korean Peninsula, average water shortage for 2020s is projected to increase to 10~32% comparing to the basis (1967~2003). In addition, according to getting decreased in streamflows in non-flood period gradually by 2080s, average water shortage for 2080s is projected to increase up to 97% (516.5 million $m^3/yr$) as maximum comparing to the basis. While the existing research on climate change gives radical increase in future water shortage, the results projected by the weighting method shows conservative change. This study has significance in the applicability of water balance projection regarding climate change, keeping the existing framework of national water resources planning and this lessens the confusion for decision-makers in water sectors.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.427-436
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• 2020

It is uncertain how global climate change will influence future drought characteristics over the Korean peninsula. This study aims to project the future droughts using climate change and land use change scenarios over the Korean peninsula with the land surface modeling system, i.e., Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro). The Representative Concentration Pathways (RCPs) 2.6 and 8.5 are used as future climate scenarios and the Shared Socio-economic Pathways (SSPs), specifically SSP2, is adopted for the land use scenario. The using Threshold Level Method (TLM), we identify future hydrological and ecological drought events with runoff and Net Primary Productivity (NPP), respectively, and assess drought characteristics of durations and intensities in different scenarios. Results show that the duration of drought is longer over RCP2.6-SSP2 for near future (2031-2050) and RCP8.5-SSP2 (2080-2099) for the far future for hydrological drought. On the other hand, RCP2.6-SSP2 for the far future and RCP8.5-SSP2 for the near future show longer duration for ecological drought. In addition, the drought intensities in both hydrological and ecological drought show different characteristics with the drought duration. The intensity of the hydrological droughts was greatly affected by threshold level methods and RCP2.6-SSP2 for far future shows the severest intensity. However, for ecological drought, the difference of the intensity among the threshold level is not significant and RCP2.6-SSP2 for near future and RCP2.6-SSP2 for near future show the severest intensity. This study suggests a possible future drought characteristics is in the Korea peninsula using combined climate and land use changes, which will help the community to understand and manage the future drought risks.

• Journal of Radiation Protection and Research
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• v.40 no.4
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• pp.252-260
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• 2015

This paper describes the technical background for the Korean wildlife radiation dose assessment code, K-BIOTA, and the summary of its application. The K-BIOTA applies the graded approaches of 3 levels including the screening assessment (Level 1 & 2), and the detailed assessment based on the site specific data (Level 3). The screening level assessment is a preliminary step to determine whether the detailed assessment is needed, and calculates the dose rate for the grouped organisms, rather than an individual biota. In the Level 1 assessment, the risk quotient (RQ) is calculated by comparing the actual media concentration with the environmental media concentration limit (EMCL) derived from a bench-mark screening reference dose rate. If RQ for the Level 1 assessment is less than 1, it can be determined that the ecosystem would maintain its integrity, and the assessment is terminated. If the RQ is greater than 1, the Level 2 assessment, which calculates RQ using the average value of the concentration ratio (CR) and equilibrium distribution coefficient (Kd) for the grouped organisms, is carried out for the more realistic assessment. Thus, the Level 2 assessment is less conservative than the Level 1 assessment. If RQ for the Level 2 assessment is less than 1, it can be determined that the ecosystem would maintain its integrity, and the assessment is terminated. If the RQ is greater than 1, the Level 3 assessment is performed for the detailed assessment. In the Level 3 assessment, the radiation dose for the representative organism of a site is calculated by using the site specific data of occupancy factor, CR and Kd. In addition, the K-BIOTA allows the uncertainty analysis of the dose rate on CR, Kd and environmental medium concentration among input parameters optionally in the Level 3 assessment. The four probability density functions of normal, lognormal, uniform and exponential distribution can be applied.The applicability of the code was tested through the participation of IAEA EMRAS II (Environmental Modeling for Radiation Safety) for the comparison study of environmental models comparison, and as the result, it was proved that the K-BIOTA would be very useful to assess the radiation risk of the wildlife living in the various contaminated environment.

• Journal of The Korean Association For Science Education
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• v.31 no.1
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• pp.78-98
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• 2011

The purpose of this study was to analyze elementary school students' interpretation of data characteristics by cognitive style. Participants were elementary students in sixth grade who can use integrated inquiry process skills. The students were divided into two groups, analytic cognitive style and wholistic cognitive style according to their response to Cognitive Style Analysis. They performed scientific interpretation of data activity. To collect data for this study, participants recorded the result on scientific interpretation of data activity paper and researcher recorded the situation on videotape and interviewed with participants after the end of interpretation of data to get additional data. And the findings of this study were as follows: First, the study analyzed interpretation of data characteristics by the operator regarding different situations of interpreting data according to cognitive style. For example, in the intermediate state, analytic-cognitive style students showed high achievement in identifying variables, and wholistic-cognitive style students were active in using prior knowledge to interpret data. Second, the result of analysis on the direction of interpreting data and preference for data types in interpreting data activities according to cognitive style are as follows: Wholistic-cognitive style students showed relatively high perception of information through the top-down approach. On the other hand, analytic-cognitive style students usually used the bottom-up approach gradually expanding detailed information to the scientific question-related answer and showed a preference data of the table type. Through the result, this study aimed to help establish a data interpretation strategy for learners to solve problems based on understanding of interpretation of data characteristics according to learners' cognitive style, and purposed the instruction design suggesting the data requiring various data interpretation strategies to develop learners' data interpretation ability.

• 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.