• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.473-481
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• 2010

Forecasting for air demand such as international passengers and freight has been one of the main interests for air industries. This research has mainly focus on the comparison of the performances of the multivariate time series models. In this paper, we used real data such as exchange rates, oil prices and export amounts to predict the future demand on international passenger and freight.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1287-1300
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• 2017

Based on the observation that ignoring the angle dependency of multigroup resonance cross sections within a fuel pellet would result in nontrivial underestimation of the spatial self-shielding of flux, a parametrized spectral superhomogenization (SPH) factor library (PSSL) method is developed as a practical means of resolving the problem. Region-wise spectral SPH factors are calculated by the normal and transport corrected SPH iterations after ultrafine group slowing down calculations over various light water reactor pin-cell configurations. The parametrization is done with fuel temperature, U-238 number density, fuel radius, moderator source represented by ${\Sigma}_{mod}V_{mod}$, and the number density ratio of resonance nuclides to that of U-238 in a form of resonance interference correction factors. The parametrization is successful in that the root mean square errors of the interpolated SPH factors over the fuel regions of various pin-cells are within 0.1%. The improvement in reactivity error of the PSSL method is shown to be superior to that by the original SPH method in that the reactivity bias of -200 pcm to -300 pcm vanishes almost completely. It is demonstrated that the environment effect takes only about 4% in the reactivity improvement so that the pin-cell based PSSL method is effective in the assembly problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.945-945
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• 2012

본 연구에서는 낙동강 수계의 안동댐 유역을 대상지역으로 선정하여 미래 기후변화 시나리오에 따른 댐 유역의 수환경 영향을 예측해 보고자 하였다. 특히 미래기후에 대한 수환경 평가는 기후자료를 입력 값으로 요구하는 강우-유출모형을 이용하거나 유량 이외에 유사, 영양물질과 같은 수질인자를 동시에 모의할 수 있는 유역모형을 이용하여 평가하는 것이 일반적이다. 이를 위해 선행연구로 IPCC(Intergovernmental Panel on Climate Change)에서 제공하는 AR4 시나리오의 RCM 자료를 ANN(Artificial Neural Network)기법을 이용하여 안동댐 유역의 총 4개 기상관측소에 대한 과거 20년(1991~2010) 실측자료를 바탕으로 미래 강수 및 습도 그리고 온도에 대해 상세화 하여 미래 기후 시나리오를 생산하였다. 또한 안동댐 유역 단위의 수질을 예측하기 위해 토양과 토지이용 및 토지관리 상태에 따른 수문-수질 모의가 가능한 유역모형인 SWAT(Soil and Water Assessment Tool)을 이용하였다. 과거의 기상자료와 수질자료를 이용하여 유역모델의 검 보정을 실시하였으며 모형의 보정 및 검증결과에 따른 적합성과 상관성을 판단하기 위해 결정계수($R^2$)와 평균제곱근오차(Root Mean Square Error, RMSE)를 사용하였으며, 모형의 효율성 검증으로는 Nash and Sutcliffe(1970)가 제안한 모형효율성계수(NSE)를 사용하였다. 최종적으로 기후 시나리오에 대해서 전망된 지역상세기후를 유역모형의 입력자료로 이용하여 안동댐 유역의 미래수문 및 수질을 예측하고자 하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• The Korean Journal of Health Service Management
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• v.13 no.4
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• pp.253-263
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• 2019

Objectives: This study evaluated the perception on importance of interprofessional core competencies (PI-ICCP) scale. Methods: Data were collected from 353 college students of health. Content validity was tested using the content validity index for individual items(I-CVI) and for scale(S-CVI). Criterion validity was tested using the professional competencies scale developed by Choi. Reliability was evaluated using Cronbach's coefficient alpha. The goodness-of-fit of the construct validity was determined through exploratory and confirmatory factor analyses. Results: The I-CVI of each item was .8 or higher for all items, and the S-CVI was .98. The reliability of the PI-IPCC was Cronbach's α=.98. The goodness-of-fit indices of the model were χ2=1811.54(p<.001), the comparative fit index (CFI)=.91, and root mean square error of approximation (RMSEA)=.08, which satisfied the criteria. Conclusions: The construct and criterion-related validity of the perception for PI-ICCP scale were a good fit, so the instrument is appropriate for measuring perception on importance of interprofessional core competencies. Further research will be required using this instrument to investigate perception of interprofessional core competencies of health professionals.

• Steel and Composite Structures
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• v.29 no.4
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• pp.465-481
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• 2018

The use of external carbon-fiber-reinforced polymer (CFRP) laminates is one of the most effective techniques existing for the confinement of circular concrete specimens. Currently, several researches have been made to develop models for predicting the ultimate conditions of this type of confinement. As most of the major existing models were developed based on limited experimental database. This paper presents the development of new confinement ultimate conditions, strength and strain models, for concrete cylinders confined with CFRP composites based on a statistical analysis of a large existing experimental database of 310 cylindrical concrete specimens wrapped with CFRP. The database is used to evaluate the performance of the proposed and major existing strength and strain models. Based on the two different statistical indices, the coefficient of determination ($R^2$) and the Root Mean Square Error (RMSE), the two proposed confinement ultimate conditions presents a good performance compared to the major existing models except the models of Lam and Teng (2003) and Youssef et al. (2007) which have relatively similar performance to the proposed models.

• Geomechanics and Engineering
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• v.21 no.4
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• pp.391-399
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• 2020

Brittleness is one of the most important properties of rock which has a major impact not only on the failure process of intact rock but also on the response of rock mass to tunneling and mining projects. Due to the lack of a universally accepted definition of rock brittleness, a wide range of methods, including direct and indirect methods, have been developed for its measurement. Measuring rock brittleness by direct methods requires special equipment which may lead to financial inconveniences and is usually unavailable in most of rock mechanic laboratories. Accordingly, this study aimed to develop a new strength-based index for predicting rock brittleness based on the obtained base form. To this end, an innovative algorithm was developed in Matlab environment. The utilized algorithm finds the optimal index based on the open access dataset including the results of punch penetration test (PPT), uniaxial compressive and Brazilian tensile strength. Validation of proposed index was checked by the coefficient of determination (R²), the root mean square error (RMSE), and also the variance for account (VAF). The results indicated that among the different brittleness indices, the suggested equation is the most accurate one, since it has the optimal R², RMSE and VAF as 0.912, 3.47 and 89.8%, respectively. It could finally be concluded that, using the proposed brittleness index, rock brittleness can be reliably predicted with a high level of accuracy.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.339-345
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• 2000

KOMPSAT-1 was launched on 21 December, 1999 and the main mission of the satellite is the cartography to provide the imagery from a remote earth view for the production of maps of Korean territory. For this purpose, the satellite has capability to tilt the spacecraft utmost $\pm$45 degrees to acquire stereo satellite imagery in different paths. This study aims to estimate the three dimensional positioning accuracy of stereo satellite imagery from EOC(electro-optical camera), a payload of KOMPSAT-1 satellite. For this purpose, the ground control points and check points were obtained by GPS surveying. The sensor modeling and the adjustment was performed by PCI software installed in KARI (Korea Aerospace Research Institute), which contained mathematical analysis module for KOMPSAT-1 EOC. The study areas were Taejon and Nonsan, placed in the middle part of Korea. As a result of this study, we found that the RMSE(root mean square error) value of three dimensional positioning KOMPST-1 stereo imagery can be less than 1 pixel (6.6 m) if we can use about 10 GCPs(ground control points). Then, a standarrd of FGDC (Federal Geographic Data Committee) of USA was applied to the result to estimate the three dimensional positioning accuracy of KOMPSAT-1 stereo imagery.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.65-78
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• 2008

This study compares the relative accuracy and consistency of four split-window land surface temperature (LST) algorithms (Becker and Li, Kerr et ai., Price, Ulivieri et al.) using 24 sets of Terra (Aqua)/Moderate Resolution Imaging Spectroradiometer (MODIS) data, observed ground grass temperature and air temperature over South Korea. The effective spectral emissivities of two thermal infrared bands have been retrieved by vegetation coverage method using the normalized difference vegetation index. The intercomparison results among the four LST algorithms show that the three algorithms (Becker-Li, Price, and Ulivieri et al.) show very similar performances. The LST estimated by the Becker and Li's algorithm is the highest, whereas that by the Kerr et al.'s algorithm is the lowest without regard to the geographic locations and seasons. The performance of four LST algorithms is significantly better during cold season (night) than warm season (day). And the LST derived from Terra/MODIS is closer to the observed LST than that of Aqua/MODIS. In general, the performances of Becker-Li and Ulivieri et al algorithms are systematically better than the others without regard to the day/night, seasons, and satellites. And the root mean square error and bias of Ulivieri et al. algorithm are consistently less than that of Becker-Li for the four seasons.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.432-432
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• 2015

농업용 저수지의 하류유역은 저수지로부터 농업용수를 공급받는 관개지구와 산림지 등 관개를 실시하지 않는 비관개지구의 수문순환이 복합적으로 연계된다. 이러한 저수지 하류유역의 하천유량은 배후 유역에서 발생하는 유역 유출량, 관개지구의 농업용수 회귀수량, 저수지에서 방류되는 환경용수 방류량과 제한수위 및 만수위 방류량, 그리고 지하수 유출량 등으로 구성된다. 본 연구에서는 저수지 하류의 하천유량 구성 요소를 해석하는 하천망 모형을 구성하였고, 대상지구의 자료를 구축하였으며, 모형의 보정 및 검정을 수행하였다. 비관개지구의 유출량 모의는 수정 3단 Tank 모형을 이용하였다. 관개지구의 배수량은 논 포장 배수량과 용수로 배수량을 구분하여 모의하며, 논 포장 배수량은 논 물수지식을 기반으로 모의하였다. 저수지 방류량은 저수지 유입량과 저수지 운영방식을 고려하여 모의하도록 구성하였다. 하도 추적은 Muskingum 방법을 이용하였다. 연구 대상지로 이동저수지 유역을 선정하여 기상, 지형, 수문, 그리고 영농 자료를 수집하여 모형의 입력 자료를 구축하였다. 모형의 평가를 위한 통계적 지표는 Nash-Sutcliffe efficiency (NSE), root mean square error-observations standard deviation ratio (RSR), 그리고 percent bias (PBIAS)를 이용하였다. 보정 및 검정 결과 구성된 모형의 모의 결과는 실측치의 경향을 잘 반영하는 것으로 나타났다. 본 연구 결과는 우리나라 농촌유역 물순환에 대한 이해를 넓히며, 저수지 하류유역 유량 해석을 위한 기초자료로 이용될 수 있을 것으로 사료된다.