• 멤브레인
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• 제33권1호
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• pp.34-45
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• 2023

본 연구에서는 투과 유량 모델을 개발하기 위하여, 시간, 막 전후의 압력 차, 회전 속도, 막의 기공 크기, 동점도, 농도 및 공급 유체의 밀도 등 7개의 입력 변수에 기반한 두 종류(ANN 및 SVM) 인공지능 기법을 이용하였다. 시행착오법과 실험데이터와 예측 데이터 간의 결정 계수(R²) 와 평균절대상대편차(AARD)를 포함한 두 가지 통계 변수를 통해 최적의 모델을 선정하였다. 최종적으로 얻어진 결과에서 최적화된 ANN 모델이 R² = 0.999 및 AARD% = 2.245인 투과 플럭스 예측 정확도를 보여서, R² = 0.996 및 AARD% = 4.09의 정확도를 보인 SVM 모델에 비해 더 정확함을 알 수 있었다. 또한, ANN 모델은 SVM 방식에 비해 투과 유속을 예측하는 능력도 더 높은 것으로 나타났다.

• 한국환경과학회지
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• 제15권2호
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• 한국지리정보학회지
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• 제17권1호
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• pp.129-143
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• 2014

본 연구는 충주댐 유역($6,625.8km^2$)을 대상으로 지점강우와 소백산 이중편파 레이더강우자료를 격자기반 분포형 강우-유출 모형인 KIMSTORM(KIneMatic wave STOrm Runoff Model)에 적용하여 홍수추적을 수행하여 레이더의 적용성을 검토하였다. 2012년 4개의 강우 이벤트(집중호우, 카눈, 볼라벤, 산바)에 대하여 한강홍수통제소로부터 보정된 소백산 레이더 강우자료를 제공받아 사용하였다. 레이더 강우와 지점 강우를 비교분석한 결과, 41개 지점의 지상강우보다 레이더의 면적평균강우량을 비교한 결과, 강우의 시공간적 패턴은 상당히 일치하였고 지상강우에 대한 레이더 강우의 비율은 0.97로 분석되었다. 이후 분포형 홍수추적을 위해 KIMSTORM을 이용하였으며, 격자크기 $500{\times}500m$ 해상도의 198행${\times}$231열의 총 45,738개의 셀로 모형을 구축하였다. KIMSTORM 모형의 보정 결과, 평균 $R^2$(coefficient of determination), ME(model efficiency), VCI(volume conservation index)는 지상강우의 경우, 각각 0.83, 0.68, 1.10로 분석되었고, 레이더강우의 경우는 각각 0.80, 0.62, 1.08의 결과를 보였다.

• Membrane and Water Treatment
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• 제10권6호
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• pp.431-440
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• 2019

A novel composite membrane was synthesized using crosslinked polyamide and fly ash ceramic substrate for phenol removal. Glutaraldehyde was used as crosslinker. Characterization shows that synthesized membrane possesses good permeability ($0.184l.m^{-2}.h^{-1}.kPa^{-1}$), MWCO (1.7 kDa), average pore size (1.08 nm) and good chemical stability. RSM was adopted for phenol removal studies. Box-Behnken-Design using quadratic model was chosen for three operating parameters (feed phenol concentration, pH and applied pressure) against two responses (phenol removal, flux). ANOVA shows that model is statistically valid with high coefficient of determination ($R^2$)value for flux (0.9897) and phenol removal (0.9302). The optimum conditions are obtained as pH 2, $46mg.l^{-1}$ (feed phenol concentration) and 483 kPa (applied pressure) with 92.3% phenol removal and $9.2l.m^{-2}.h^{-1}$ flux. Data validation with deviation of 4% confirms the suitability of model. Obtained results reveal that prepared composite membrane can efficiently separate phenol from aqueous solution.

• 한국관개배수논문집
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• 제14권1호
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• pp.41-49
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• 2007

In this study, Kajiyama equation and SWAT model were used to estimate the available water resources from 1967 to 2003 at the small scale watershed, located in Dongnae-Myeon, Chunchen, Gangwon. The annual average streamflow for dry years estimated using the Kajiyama equation and the SWAT model were $2,593,779m^3$ and $2,579,162m^3$. The annual average streamflow for wet years were $7,223,804m^3$ and $7,035,253m^3$, respectively. The annual arrange streamflow for the entire 36 year period were $14,868,601m^3$ and $14,214,292m^3$, respectively. The coefficient of determination ($R^2$) and the Nash-Sutcliffe coefficient for comparison between Kajiyama and SWAT were 0.90 and 0.79, respectively. The comparison indicates that the Kajiyama equation and the SWAT model can be used to estimate the streamflow at th study watershed with reasonable accuracy, although the estimated values were not compared with measured streamflow data, which is not available at the small scale study watershed. However, the Kajiyama equation is recommended for estimating available water resources at Dongnae-Myeon watershed because of its ease-of-use and reasonable accuracy compared with the SWAT model, requiring numerous model input and expensive GIS software in operating the model

• Bulletin of the Korean Chemical Society
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• 제31권5호
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• pp.1159-1164
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• 2010

Several triterpenoid saponins from root of Pulsatilla koreana Nakai (Ranunculaceae) were studied and their biological activities were reported. It is difficult to analyze triterpenoid saponins using HPLC-UV due to the lack of chromophores. So, evaporative light scattering detection (ELSD) is used as a valuable alternative to UV detection. More recently, a charged aerosol detection (CAD) has been developed to improve the sensitivity and reproducibility of ELSD. In this study, we developed and validated a novel method of high performance liquid chromatography coupled with a charged aerosol detector for the simultaneous determination of four triterpenoid saponins: pulsatilloside E, pulsatilla saponin H, anemoside B4 and cussosaponin C. Analytes were separated by the Supelco Ascentis$^{(R)}$ Express C18 column (4.6 mm ${\times}$ 150 mm, 2.7 ${\mu}m$) with gradient elution of methanol and water at a flow rate of 0.8 mL/min at $30^{\circ}C$. We examined various factors that could affect the sensitivity of the detectors, including various concentrations of additives, the pH of the mobile phase, and the CAD range. Linear calibration curves were obtained within the concentration ranges of 2 - 200 ${\mu}g$/mL for pulsatilloside E, anemoside $B_4$ and cussosaponin C, and 5 - 500 ${\mu}g$/mL for pulsatilla saponin H with correlation coefficient ($R^2$) greater than 0.995. The limit of detection (LOD) and quantification (LOQ) were 0.04 - 0.2 and 2 - 5 ${\mu}g$/mL, respectively. The validity of the developed HPLC-CAD method was confirmed by satisfactory values of linearity, intra- and inter-day accuracy and precision. This method could be successfully applied to quality evaluation, quality control and monitoring of Pulsatilla koreana.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• 설비공학논문집
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• 제30권4호
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• pp.159-166
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• 2018

The Korean fenestration energy consumption efficiency rating system only considers thermal performance of the heat transfer coefficient (U-value) and airtightness excluding optical characteristics of the solar heat gain coefficient (SHGC). This study analyzed annual heating and cooling energy requirements on the middle floor of apartment by optical and thermal performance of windows to evaluate the suitability of the rating system. One hundred and twenty-eight windows were analyzed using THERM and WINDOW 7.4, and energy simulation for a reference model of an apartment house facing south was performed using TRNSYS 17. The results showed that window performance was the main factor in the heating and cooling load. The heating load of the reference model was 539 kWh to 2,022 kW, and the cooling load was 376 kWh to 1,443 kWh. The coefficient of determination ($R^2$) of the heating and cooling loads driven from the SHGC were 0.7437 and 0.9869, which are more compatible than those from the U-value, 0.0558 and 0.4781. Therefore, it is not reasonable to evaluate the energy performance of windows using only the U-value, and the Korean fenestration energy consumption efficiency rating system requires a new evaluation standard, including SHGC.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.85-85
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• 2021

CDOM(Colored or Chromophoric Dissolved Organic Matter)은 바다, 호수 및 강에서 담수, 오수, 퇴적물 등으로부터 공급된 유기물질의 일종으로 가시광선에서 빛을 흡수하는 성질을 가지며, 2016년부터 환경부에서 선정한 하천, 호수 등 방류수의 수질오염 표준인 TOC(Total Organic Carbon)를 간접 추정할 수 있는 매개변수가 될 수 있다. 따라서, 본 연구에서는 백제보 상류 23 km 구간을 대상으로 2개년(2016~2017) 중 7일의 초분광영상 자료를 활용하여 내륙지역의 CDOM에 대한 적정 반사도 밴드값(R_rs)과 CDOM을 추정하는 알고리즘을 개발하고자 한다. CDOM은 흡수계수(α_CDOM)를 통해 간접 추정되며, 흡수계수의 기준 파장값(λ)은 연구별로 350 nm, 375 nm, 400 nm, 412 nm 및 440 nm 등 다르게 나타난다. 초분광영상은 AsaFENIX 초분광 센서에서 관측된 380~970 nm까지 4 nm 간격, 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 영상을 활용하였으며, 자료의 연속성을 위해 smoothing 기법을 활용하여 가공하였다. 추정 알고리즘은 Random forest를 활용하였으며, 70%의 trainning과 30%의 test로 구분하여 적용하였다. 산출된 CDOM은 결정계수(R²), Nash-Sutcliffe efficiency(NSE)를 이용하여 실측 CDOM과 비교하였다. 흡수계수별 CDOM의 산정 결과 α_CDOM(350 nm)의 trainning, test에서 각각 R²가 0.71, 0.74, NSE가 0.25, 0.49로 가장 높았으며, 적정 반사도 밴드값은 R_rs(466), R_rs(493), R_rs(548), R_rs(641)를 사용하였을 때 trainning, test에서 각각 R²가 0.93, 0.90, NSE가 0.85, 0.69로 가장 높게 나타났다.

• 문화기술의 융합
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• 제4권1호
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• pp.41-50
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• 2018

본 연구는 대학생의 스마트폰 중독과 스트레스, 회복탄력성과의 관계를 확인하고, 스마트폰 중독에 미치는 영향을 파악하기 위해 실시하였다. 연구대상자는 전라남도 소재 4년제 대학생 241명이다. 자료수집은 2017년 7월 6일부터 8월 31일까지 실시하였다. 연구결과, 대상자의 스마트폰 중독과 스트레스(r=.37, P<.001)는 양의 상관관계가 있었으며, 회복탄력성(r=.-25, p<.001)과는 음의 상관관계가 있었다. 대상자의 스트레스 중 당면과제(r=.40, p<.001)와 대인관계(r=.25, p<.001)는 양의 상관관계가 있었으며, 회복탄력성 중 자기조절능력(r=-.32, p<.001)과 대인관계능력(r=-.21, p=.001)은 음의 상관관계가 있었다. 스마트폰 중독에 영향을 미치는 변수는 학업문제(${\beta}=.15$, p=.047)와 자기조절능력(${\beta}=-.21$, p=.007)으로 총 설명력($R^2$)은 22.1%였다. 따라서 대학생의 스마트폰 중독을 예방하고 관리하기 위한 체계적인 교과외 프로그램의 개발이 필요할 것으로 사료된다.