• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1262-1287
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• 2017

Recently, forecasting for next-generation technologies have influenced the competitiveness of companies. However, in previous studies, only extract factors influencing the adoption of technology have been investigated. Also, there are few researches on the importance of each decision factors or the competition between technologies. In this research, Lotka-Volterra model is used to confirm the technological competition in the new technology choice timing when the competition is intensified due to the emergence of new technologies. For purpose of this study, estimate the LVC model based on the data of the past competition and then derived the factors affecting the technology of competition and substitution from the literature survey. After that, we confirmed the factor value between the past and the present technology competition. The difference between the factor values derived from the previous step is used to revise the model estimated from the past data base. At this stage, regression analysis is used to derive the importance of each factor and use it as the weight. Through the correction model, the competitiveness is identified through 1:1 comparison with competition candidate technology and existing dominant design technology. In this research, we quantitatively propose the possibility that a specific technology can become a dominant design in the next generation, based on the difference in factor values and importance. This results will help the company's R&D strategy and decision making.

• Journal of Korea Water Resources Association
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• v.39 no.3 s.164
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• pp.241-252
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• 2006

Numerical models for seepage analysis are useful tools to analyze problems and design protection techniques that are related to seepage through a levee. Though every model may have its own limitations and shortcomings, there were no generalized verifications or calibrations for the commercial models. It means that users can run the model and get the result without understanding nor taking any enough training. This paper Investigates applicability and suitability of some seepage numerical models by comparing analytical solutions with experiments in the user's viewpoint. The results showed that it is more desirable to use analyses with unsaturated-unsteady condition rather than those with saturated-steady conditions, since seepage phenomenon of real levees are changed according to water level and soil property. This study also compared the calculated unsteady solutions with the calculated steady solutions for the levee at Koa of the Nakdong River The comparison revealed that as the result, the safety factor of $2.0{\sim}3.5$ has the same effects for seepage protection techniques when they are designed on the basis of steady-state analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.120-134
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• 2015

InVEST Water Yield model developed by Natural Capital Project was applied for South Korea to assess domestic forest ecosystem's water provisioning services. The InVEST Water Yield model required 8 input dataset, including six spatial map data and two derived by coefficients. By running the model with relatively easy acquired and modified data, the result of domestic forest ecosystem's water provisioning services was 9,409,622,083 ton using the standard of the year 2011. The result showed similar patterns and distribution of rainfall in 2011, but showed difference when compared with existing researches spatially driven in nationwide statistical analysis results. This difference is assumed to occur with different model mechanism in spatial implementation and statistical analysis. So given that the model is currently still developing, applications should be taken on qualitative perspectives rather than on quantitative perspectives. Additionally, for advancing the application of InVEST water yield model, quantification of suitable input data and comparison using multi-modeling is required.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.90-104
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• 2015

The purpose of this paper is to build a spatio-temporal evapotranspiration(ET) estimation model using Terra MODIS satellite image and by calibrating with the flux tower ET data from watershed. The fundamentals of spatial ET model, Surface Energy Balance Algorithm for Land(SEBAL) was adopted and modified to estimate the daily ET of Yongdam Dam watershed in South Korea. The daily Normalized Distribution Vegetation Index(NDVI), Albedo, and Land Surface Temperature(LST) from MODIS and the ground measured wind speed and solar radiation data were prepared for 2 years(2012-2013). The SEBAL was calibrated with the forest ET measured by Deokyusan flux tower in the study watershed. Among the model parameters, the important parameters were surface albedo, NDVI and surface roughness in order for momentum transport during calculation of sensible heat flux. As a result of the final calibration, the monthly averaged albedo and NDVI were used because the daily values showed big deviation with unrealistic change. The determination coefficient($R^2$) between SEBAL and flux data was 0.45. The spatial ET reflected the geographical characteristics showing the ET of lowland areas was higher than the highland ET.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.3
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• pp.323-335
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• 2020

In this study, a series of site measurement of particulate and gases pollutants at five tunnels were carried out along with case studies to review the suitability of the current road tunnel ventilation design standards. Previous studies by other researchers have shown that the ratios of the level of measurement to the standard were 27.9%, 1.6% and 3.4% for TSP, CO and NOx, respectively. Those measured in this site study shows even lower ratios; the ratios were 2.6%, 0.8% and 0.3%, for TSP, CO and NOx, respectively. The particle size analysis of TSP for the five tunnels shows that PM10 including tire wear and re-suspended road dust exceeded 20.4%. This implies that non-exhaust particulate matter must be taken into account, since the current design standards for the particulate matter (visibility) include only the engine emission. Based on the recent research results, for vehicle emission rate and slope-speed correction factors, revision of ventilation design standards for pollutants is required. WRA (PIARC) also emphasizes the necessity of the ventilation design standards for pollutants. In addition, enactment of a new road tunnel ventilation system operation standard or guideline is strongly recommended when considering the low operating rate of the ventilation system with jet-fans.

• Journal of agriculture & life science
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• v.44 no.1
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• pp.33-42
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• 2010

This study was conducted to estimate the effects of breed, sex, Farm-Scale and environment on average daily gain, age at 90kg, backfat thickness, eye muscle area and lean percent of pig. The total number of pig used in this study was 30,525 head consisted of 5,902 Landrace, 18,022 Yorkshire, and 6,601 Duroc on 2004 to 2008. The covariance used in the model to adjust age at the final test. The average daily gain, age at 90kg, and lean percent were significantly superior in medium Farm-Scale. However Backfat thickness and Eye muscle Area were significantly superior in small Farm-Scale. In conclusion this study suggest that breed, sex, test year, test season, Farm-Scale and environment may affect to average daily gain, age at 90kg, backfat thickness, eye muscle area and lean percent. The study about the Farm-Scale has to do continually more than now, and this study will be contributed to development of the pig industry.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.583-590
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• 2008

This study presents a correlation between timber Age, image bands and vegetation indices for timber age estimation. Basically, this study used Landsat TM images of three difference years (1994, 1994, 1998) and difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED). Bands of 4, 5 and 7, Normalized Difference Vegetation Index (NDVI), Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SA VI) were obtained from Landsat TM images. Tasseled cap - greenness and wetness images were also made by Tasseled cap transformation. Finally, analysis of correlation between timber age, difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED), individual TM bands (4, 5, 7), Normalized Difference Vegetation Index (NDVI), Tasseled cap-Greenness, Wetness, Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SAVI) using regression model. In this study about 1,992 datasets were analyzed. The Tasseled cap - Wetness, Infrared Index (II) and Vegetation Condition Index (VCI) showed close correlation for timber age estimation.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.239-249
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• 2010

The Geostationary Ocean Color Imager (GOCI) data-processing system (GDPS), which is a software system for satellite data processing and analysis of the first geostationary ocean color observation satellite, has been developed concurrently with the development of th satellite. The GDPS has functions to generate level 2 and 3 oceanographic analytical data, from level 1B data that comprise the total radiance information, by programming a specialized atmospheric algorithm and oceanic analytical algorithms to the software module. The GDPS will be a multiversion system not only as a standard Korea Ocean Satellite Center(KOSC) operational system, but also as a basic GOCI data-processing system for researchers and other users. Additionally, the GDPS will be used to make the GOCI images available for distribution by satellite network, to calculate the lookup table for radiometric calibration coefficients, to divide/mosaic several region images, to analyze time-series satellite data. the developed GDPS system has satisfied the user requirement to complete data production within 30 minutes. This system is expected to be able to be an excellent tool for monitoring both long-term and short-term changes of ocean environmental characteristics.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.189-207
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• 2010

Several ocean color algorithms have been developed for GOCI (Geostationary Ocean Color Imager) using in-situ bio-optical data sets. These data sets collected around the Korean Peninsula between 1998 and 2009 include chlorophyll-a concentration (Chl-a), suspended sediment concentration (SS), absorption coefficient of dissolved organic matter ($a_{dom}$), and remote sensing reflectance ($R_{rs}$) obtained from 1348 points. The GOCI Chl-a algorithm was developed using a 4-band remote sensing reflectance ratio that account for the influence of suspended sediment and dissolved organic matter. The GOCI Chl-a algorithm reproduced in-situ chlorophyll concentration better than the other algorithms. In the SeaWiFS images, this algorithm reduced an average error of 46 % in chlorophyll concentration retrieved by standard chlorophyll algorithms of SeaWiFS. For the GOCI SS algorithm, a single band was used (Ahn et al., 2001) instead of a band ratio that is commonly used in chlorophyll algorithms. The GOCI $a_{dom}$ algorithm was derived from the relationship between remote sensing reflectance band ratio ($R_{rs}(412)/R_{rs}(555)$) and $a_{dom}(\lambda)$). The GOCI Chl-a fluorescence and GOCI red tide algorithms were developed by Ahn and Shanmugam (2007) and Ahn and Shanmugam (2006), respectively. If the launch of GOCI in June 2010 is successful, then the developed algorithms will be analyzed in the GOCI CAL/VAL processes, and improved by incorporating more data sets of the ocean optical properties data that will be obtained from waters around the Korean Peninsula.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.395-395
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• 2018

기후변화 및 토지이용변화에 따라 강우량 및 증발산량 등과 같은 물순환계 구성요소가 변화하면 유역에서의 물순환계가 영향을 받게 된다. 이렇게 변화된 유역의 물순환계를 종합적으로 관리하기 위해서는 물순환 개선 기술을 통한 지속가능하고 건전한 물순환체계의 구축이 필요하다. 유역 물순환 개선 기술은 기후변화가 진행 중에 있거나 예상되는 지역에 대하여 강우-유출수를 지연, 저류, 침투시켜 지속가능한 물순환체계를 유지 회복하도록 하는 기술이라 할 수 있다. 한국건설기술연구원에서는 기후변화 대비 수자원 적응기술 개발 연구단(CCAW, Climate Change Adaptation for Water resources)의 연구비 지원을 받아 유역 건전성 및 취약성을 평가 하고 취약한 유역에 대한 물순환 개선기술을 확보하기 위한 연구를 수행 중에 있다. 특히, 수년간 국가연구개발사업을 통해 개발되고 사업화에 성공한바 있는 유역 물순환 평가 모형인 CAT(Catchment hydrologic cycle Assessment Tool)을 수정 개선하여 수요자 중심의 활발한 현장 적용을 도모하고 있다. 본 연구에서는 개발된 유역 물순환 개선 및 평가시스템의 적용성 평가를 위하여 대상유역으로 태국의 Lam Takhong 저수지 유역을 선정하였다. Lam Takhong 저수지 유역은 유역면적은 $1,423km^2$이며 저류량은 약 $440{\times}106m^3$이다. 입력자료인 DEM, Land Cover 자료는 USGS Hydro1K (https://earthexplorer.usgs.gov/), 하천망 및 유역경계 자료는 USGS HydroSHEDS (https://hydrosheds.cr.usgs.gov/dataavail.php), 기상 및 관측 유입량, 저수지 제원 등의 자료는 APEC 기후센터의 협조를 받아 1976년부터 2016년까지의 일단위 자료를 이용하였다. 모의결과는 저수지 월별 관측 유입량과 상류 유역의 모의 유출량을 이용하여 비교-분석 하였다. Lam Takhong 저수지 상류 유역은 APEC 기후센터에서 SWAT 모형을 이용하여 저수지 유입량 분석을 수행한 바 있다. 따라서 본 연구의 결과를 SWAT 모의결과와 비교하여 그 적용성을 검증하였다. 월별 관측 유입량과 저수지 상류 유역 모의 유출량을 비교한 결과 CAT의 경우 결정계수(R2) 값이 0.86, SWAT은 0.76으로 나타나 CAT의 적용 결과가 좀 더 우수한 것으로 나타났다. 모의 결과는 매개변수 최적화 과정을 거치지 않은 결과이며 SWAT 모형과의 결과 비교를 위하여 매개변수는 동일하게 적용하였다. 향후 매개변수 최적화 모듈을 통해 검 보정 단계를 거친다면 정밀한 분석이 가능할 것으로 판단된다.