• Journal of Wetlands Research
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• v.13 no.3
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• pp.547-565
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• 2011

Different types of schemes have been used in stage prediction involving conceptual and physical models. Nevertheless, none of these schemes can be considered as a single superior model. To overcome disadvantages of existing physics based rainfall-runoff models for stage predicting because of the complexity of the hydrological process, recently the data-derived models has been widely adopted for predicting flood stage. The objective of this study is to evaluate model performance for stage prediction of the Neuro-Fuzzy and regression analysis stage prediction models in these data-derived methods. The proposed models are applied to the Wangsukcheon in Han river watershed. To evaluate the performance of the proposed models, fours statistical indices were used, namely; Root mean square error(RMSE), Nash Sutcliffe efficiency coefficient(NSEC), mean absolute error(MAE), adjusted coefficient of determination($R^{*2}$). The results show that the Neuro-Fuzzy stage prediction model can carry out the river flood stage prediction more accurately than the regression analysis stage prediction model. This study can greatly contribute to the construction of a high accuracy flood information system that secure lead time in medium and small streams.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1698-1702
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• 2009

효과적인 저수지 수질관리를 위해서는 신뢰도 높은 수리 및 수질모델이 필요하며, 이러한 모델의 성능은 다양한 수문사상에 대하여 적용함으로써 검증할 수 있다. CE-QUAL-W2 모델(이후 W2)은 횡방향 평균 2차원 수리 수질 해석 모델로써 수체의 길이에 비해 폭이 상대적으로 좁고 수심이 깊은 우리나라 대부분의 저수지 지형에 적합한 모델이다. 본 연구의 목적은 기존 연구에서 가뭄년인 2001년과 평수년인 2004년 수문사상에 대하여 보정한 대청호 W2 부영양화모델을 최근 평수년인 2006년과 가뭄년인 2008년을 대상으로 검증하는데 있다. 모델의 검증은 물수지, 수온성층 구조 변화, 부영양화 해석에 중점을 두었으며, 실측자료와 모의결과의 적합성 비교 평가는 결정계수값$(R^2)$, AME(absolute mean error)와 RMSE(root mean square error)를 이용하였다. 저수지 물수지의 적합성을 검증하기 위하여 모의수위와 실측수위를 비교한 결과, $R^2$값이 2006년과 2008년에 각각 0.9945, 0.9972로 나타나 신뢰도가 높은 것으로 확인되었다. 계절별 성층구조 변화 모의 성능을 검증하기 위해 회남수역과 댐 앞 지점에서 수심별 수온의 모의값과 실측값을 비교하였다. 2006년의 경우 모델은 홍수기 동안 안정적으로 수온 성층현상을 모의하였으나, 댐 앞 지점에서 수온 약층이 형성된 구간에서 실측값과 다소 편차를 보였으며, 오차크기는 AME가 $0.561\sim2.088^{\circ}C$, RMSE는 $0.797\sim2.762^{\circ}C$범위였다. 반면, 가뭄년인 2008년에는 전 기간에 걸쳐 모두 안정적으로 저수지 수온 성층현상을 모의하였으며, 오차크기는 AME $0.413\sim1.162^{\circ}C$, RMSE $0.546\sim1.415^{\circ}C$ 범위였다. 조류의 생산성이 높은 표층에서 T-N, T-P 및 Chl-a 농도 모의결과를 장계교, 대정리, 회남대교, 댐 앞, 추동취수탑 및 문의취수탑에서 시계열로 실측값과 비교 검증한 결과, T-N과 T-P는 2006년과 2008년 모두 모든 비교 지점에서 모의값과 실측값의 시계열 변동이 매우 잘 일치하였으며, 홍수기 이외 기간에는 큰 변동 폭을 보이지 않았다. 그러나 기존 연구에서 확인된 바와 같이 7월 이후부터 T-P 모의값이 실측값을 과대 산정하는 경향을 보였는데, 그 원인은 산소 결핍상태에서 저니층에서 용출되는 철(Fe) 또는 망간(Mn)과 같은 이온 성분이 인과 흡착하여 침전되는 기작이 모의과정에 적절히 반영되지 않은 것이 원인으로 판단된다. 조류(Chl-a)농도의 경우, 2006년과 2008년에 모든 지점에서 모델은 조류의 발생과 시계열 변화를 적절히 모의하였으나, 2008년 1월부터 8월까지 댐 앞과 추동 및 문의취수탑에서는 모의값이 실측값을 과대 산정하는 경향을 보였다. 이는 해마다 그리고 계절별로 우점하는 조류 종이 상이한 반면, 모델에서는 이에 대한 매개변수를 적절히 고려하지 못한 것이 원인으로 판단된다.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.111-123
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• 2017

The phycocyanin pigment (PC) is a marker for cyanobacterial presence in eutrophic inland water. Accurate estimation of low PC concentration in turbid inland water is challenging due to the optical complexity and criticalforissuing an early warning of potentialrisks of cyanobacterial bloom to the public. To monitor cyanobacterial bloom in eutrophic inland waters, an approach is proposed to partition non-water absorption coefficient from measured reflectance and to retrieve absorption coefficient of PC with the aim of improving the accuracy in remotely estimated PC, in particular for low concentrations. The proposed inversion model retrieves absorption spectra of PC ($a_{pc}({\lambda})$) with $R^2{\geq}0.8$ for $a_{pc}(620)$. The algorithm achieved more accurate Chl-a and PC estimation with $0.71{\leq}R^2{\leq}0.85$, relative root mean square error (rRMSE) ${\leq}39.4%$ and mean relative error(RE) ${\leq}78.0%$ than the widely used semi-empirical algorithm for the same dataset. In particular, low PC ($PC{\leq}50mg/m^3$) and low PC: Chl-a ratio values of for all datasets used in this study were well predicted by the proposed algorithm.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.626-632
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• 2013

In this study the GPS Precipitable Water Vapor (PWV) was derived and evaluated by a radiosode measure during the winter intensive observation in Gangneung site from January 5 till February 29 in 2012. Bernise 5.0 software was used to derive the GPS data. GPS-derived PWV from Zero difference (GANG) and Single difference (GANG and DAEJ) was high variance in time and about 5 times the PWV of radiosonde. GPS post-processing has been performed from two additional IGS site (Xian Dao, Ibaraki-ken) in order to correct the absolute troposphere errors. As a result, the mean bias error (MBE) and root mean square error (RMSE) and correlation compared with radiosonde measure were 0.67 mm, 6.40 mm, and 0.93, respectively. In order to correct the relative troposphere errors from the altitudinal difference between the two GPS receivers, we calculated the GPS-derived PWV by adding the data of GPS that was installed in Gangneung-Wonju University near the Gangwon Regional Meteorological Administration. In the end, the improved result showed that MBE, RMSE and correlation in comparison with radiosonde measures were 0.61 mm, 5.79 mm, and 0.93, respectively.

• Safety and Health at Work
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• v.10 no.4
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.579-588
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• 2015

Recent climage changes have resulted in increases in rainfall intensity and flood frequency as well as the risk of flood damage due to typhoons during the summer season. Water-friendly facilities such as ecological parks and sports facilities have been established on floodplains of rivers since the river improvement project was implemented and increases in the flood levels of rivers due to typhoons can lead to direct flood damage to such facilities. To analyze the hydraulic influence of these water-friendly facilities on floodplains or to evaluate their stability, numerical analysis should be performed in advance. In addition, it is crucial to address the drying and wetting processes generated by water level fluctuations. This study uses a Nays2D model, which analyzes drying and wetting, to examine its applicability to simple terrain in which such fluctuations occur and to natural rivers in which drying occurs. The results of applying this model to sites of actual typhoon events are compared with values measured at water level observatories. Through this comparison, it is determined that values of coefficient of determination ($R^2$), mean absolute error (MAE), and root-mean-square error (RMSE) are 0.988, 0.208, and 0.239, respectively, thus showing a statistically high correlation. In addition, the results are used to calculate flood risk indices for evaluation of such risk for water-friendly facilities constructed on floodplains.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.221-228
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• 2019

The effects of wind speed on the temperature change during day time could be insignificant in a region with a complex terrain. The objective of this study was to derive empirical relationship between solar radiation and hourly temperature under a windy condition for the period from sunrise to sunset in order to improve hourly air temperature at a site-specific scale. The deviation of the temperature measurements was analyzed along with the changes of the hourly sunlight at weather observation sites located on the east and west slopes under given wind speed. An empirical model where wind speed use used as an independent variable was obtained to quantify the solar effects on the temperature change (MJ/㎡). This model was verified estimating the hourly temperature during the daytime (0600-1900 h) at 25 weather observation sites located in the study area that has complex topography for the period from January to December 2018. The mean error (ME) and root mean square error (RMSE)of the estimated and measured values ranged from -0.98 to 0.67 ℃, and from 0.95 to 2.04 ℃, respectively. The daytime temperature at 1500 h were estimated using new and previous models. It was found that to the model proposed in the present study reduced the measurement errors of the hourly temperature in the afternoon in comparison with the previous model. For example, the ME and RMSE of the previous model were (ME -0.91 ℃ and 1.47 ℃, respectively. In contrast, the values of ME and RMSE were -0.45 ℃ and 1.22 ℃ for the new model, respectively. Our results suggested that the reliability of hourly temperature estimates at a specific site could be improved taking into account the effect of wind as well as solar radiation.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.571-586
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• 2014

Moderate Resolution Imaging Spectroradiometer (MODIS) provides air temperature (Tair) and dew point temperature (Tdew) profiles at a spatial resolution of 5 km. New Collection 6 (C006) MODIS07_L2 atmospheric profile product has been produced since 2012. The Collection 6 algorithm has several modifications from the previous Collection 5 (C005) algorithm. This study evaluated reliabilities of two alternative datasets of surface-level Tair and Tdew derived from C005 and C006 Aqua MODIS07_L2 (MYD07_L2) products using ground measured temperatures from 77 National Weather Stations (NWS). Saturated and actual vapor pressures were calculated using MYD07_L2 Tair and Tdew. The C006 Tair showed lower mean error (ME, -0.76 K) and root mean square error (RMSE, 3.34 K) than the C005 Tair (ME = -1.89 K, RMSE = 4.06 K). In contrasts, ME and RMSE of C006 Tdew were higher than those (ME = -0.39 K, RMSE = 5.65 K) of C005 product. Application of ambient lapse rate for Tair showed appreciable improvements of estimation accuracy for both of C005 and C006, though this modification slightly increased errors in C006 Tdew. The C006 products provided better estimation of vapor pressure datasets than the C005-derived vapor pressure. Our results indicate that, except for Tdew, C006 MYD07_L2 product showed better reliability for the region of South Korea than the C005 products.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.393-400
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• 2021

Body weight of livestock is a crucial indicator for assessing feed requirements and nutritional status. This study was performed to estimate the body weight of Korean cattle (Hanwoo) using body volume determined from three-dimensional (3-D) image. A TOF camera with a resolution of 640×480 pixels, a frame rate of 44 fps and a field of view of 47°(H)×37°(V) was used to capture the 3-D images for Hanwoo. A grid image of the body was obtained through preprocessing such as separating the body from background and removing outliers from the obtained 3-D image. The body volume was determined by numerical integration using depth information to individual grid. The coefficient of determination for a linear regression model of body weight and body volume for calibration dataset was 0.8725. On the other hand, the coefficient of determination was 0.9083 in a multiple regression model for estimating body weight, in which the age of Hanwoo was added to the body volume as an explanatory variable. Mean absolute percentage error and root mean square error in the multiple regression model to estimate the body weight for validation dataset were 8.2% and 24.5kg, respectively. The performance of the regression model for weight estimation was improved and the effort required for estimating body weight could be reduced as the body volume of Hanwoo was used. From these results obtained, it was concluded that the body volume determined from 3-D of Hanwoo could be used as an effective variable for estimating body weight.

• Land and Housing Review
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• v.12 no.4
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• pp.93-101
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• 2021

As the number of small households (1 to 2 persons per household) in Korea gradually increases, so does the importance of housing supply policies for small households. In response to the increase in small households, the government has been continuously supplying urban housing for these households. Since housing for small households is a sales and rental business similar to apartments and general business facilities, it is important for the building owner to calculate the project's estimated construction duration during the planning stage. Review of literature found a model for estimating the duration of construction of large-scale buildings but not for small-scale buildings such as urban housing for small households. Therefore this study aimed to develop and verify a model for estimating construction duration for urban housing at the planning stage based on multiple regression analysis. Independent variables inputted into the estimation model were building site area, building gross floor area, number of below ground floors, number of above ground floors, number of buildings, and location. The modified coefficient of determination (R_a²) of the model was 0.547. The developed model resulted in a Root Mean Square Error (RMSE) of 171.26 days and a Mean Absolute Percentage Error (MAPE) of 26.53%. The developed estimation model is expected to provide reliable construction duration calculations for small-scale urban residential buildings during the planning stage of a project.