• Journal of Environmental Science International
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• v.14 no.12
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• pp.1203-1209
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• 2005

Basic dyes, Rhodamine 6G(R6G), Rhodamine B(RB), and Methylene Blue(MB), dissolved in water were used to investigate single-component adsorption affinity to the pearl layer fractionated according to the size. Unfractionated pearl layers were also used as adsorbents for the R6G and RB. The Langmuir and the Redlich-Peterson(RP) models were used to fit the adsorption data, and the goodness of fit was examined by using determination coefficient($R^2$) and standard deviation(SSE). The 3-parameter RP model was found to be better in describing the dye adsorption data than the 2 parameter Langmuir model, as can be expected from the number of parameters involved in the model. The adsorption affinity to the fractionated pearl layer was higher than that to the unfractionated layer The affinity order to the fractionated Conchiolin layer was found to be R6G > MB > RB. Furthermore, the dye adsorption capacity of the various types of pearl layer was found to be in the order, the fractionated pearl > powdered pearl > unfractionated pearl, exhibiting different adsorption isotherms according to the types of layer used in the study.

• Journal of Ecology and Environment
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• v.40 no.1
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• pp.34-44
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• 2016

Background: Little is known about how chemical water quality is associated with ecological stream health in relation to landuse patterns in a watershed. We evaluated spatial characteristics of water quality characteristics and the ecological health of Dongjin-River basin, Korea in relation to regional landuse pattern. The ecological health was assessed by the multi-metric model of Index of Biological Integrity (IBI), and the water chemistry data were compared with values obtained from the health model. Results: Nutrient and organic matter pollution in Dongjin-River basin, Korea was influenced by land use pattern and the major point sources, so nutrients of TN and TP increased abruptly in Site 4 (Jeongeup Stream), which is directly influenced by wastewater treatment plants along with values of electric conductivity (EC), bacterial number, and sestonic chlorophyll-a. Similar results are shown in the downstream (S7) of Dongjin River. The degradation of chemical water quality in the downstream resulted in greater impairment of the ecological health, and these were also closely associated with the landuse pattern. Forest region had low nutrients (N, P), organic matter, and ionic content (as the EC), whereas urban and agricultural regions had opposite in the parameters. Linear regression analysis of the landuse (arable land; $A_L$) on chemicals indicated that values of $A_L$ had positive linear relations with TP ($R^2=0.643$, p < 0.01), TN ($R^2=0.502$, p < 0.05), BOD ($R^2=0.739$, p < 0.01), and suspended solids (SS; ($R^2=0.866$, p < 0.01), and a negative relation with TDN:TDP ratios ($R^2=0.719$, p < 0.01). Conclusions: Chemical factors were closely associated with land use pattern in the watershed, and these factors influenced the ecological health, based on the multimetric fish IBI model. Overall, the impairments of water chemistry and the ecological health in Dongjin-River basin were mainly attributes to point-sources and land-use patterns.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.63-70
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• 2017

The purpose of this study was to calibrate the hydrologic parameters of SWAT model and analyze the daily runoff for the study watershed using SWAT-CUP. The Hardware watershed is located in Virginia, USA. The watershed area is $356.15km^2$, and the land use accounts for 73.4 % of forest and 23.2 % of pasture. Input data for the SWAT model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1990 to 1994 was used for calibration and from 1997 to 2005 was for validation. The SUFI-2 module of the SWAT-CUP program was used to calibrate the hydrologic parameters. The parameters were calibrated for the highly sensitive parameters presented in previous studies. The P-factor, R-factor, $R^2$, Nash-Sutcliffe efficiency (NS), and average flow were used for the goodness-of-fit measures. The applicability of the model was evaluated by sequentially increasing the number of applied parameters from 4 to 11. In this study, 10-parameter set was accepted for calibration in consideration of goodness-of-fit measures. For the calibration period, P-factor was 0.85, R-factor was 1.76, $R^2$ was 0.51 and NS was 0.49. The model was validated using the adjusted ranges of selected parameters. For the validation period, P-factor was 0.78, R-factor was 1.60, $R^2$ was 0.60 and NS was 0.57.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.291-298
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• 2012

Objective: The aim of this study is to predict Korean text entry on touchscreens using ACT-R cognitive architecture. Background: Touchscreen application in devices such as satellite navigation devices, PDAs, mobile phones, etc. has been increasing, and the market size is expanding. Accordingly, there is an increasing interest to develop and evaluate the interface to enhance the user experience and increase satisfaction in the touchscreen environment. Method: In this study, Korean text entry performance in the touchscreen environment was analyzed using ACT-R. The ACT-R model considering the characteristics of the Korean language which is composed of vowels and consonants was established. Further, this study analyzed if the prediction of Korean text entry is possible through the ACT-R cognitive model. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed model can predict the accurate physical movement time as well as cognitive processing time. Application: This study is useful in conducting model-based evaluation on the text entry interface of the touchscreen and enabled quantitative and effective evaluation on the diverse types of Korean text input interfaces through the cognitive models.

• Applied Chemistry for Engineering
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• v.31 no.5
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• pp.520-525
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• 2020

In this study, we developed a machine learning-based model for predicting the production stage temperature of distillation process. It is necessary to predict an accurate temperature for control because the control of the distillation process is done through the production stage temperature. The temperature in distillation process has a nonlinear complex relationship with other variables and time series data, so we used the recurrent neural network algorithms to predict temperature. In the model development process, by adjusting three recurrent neural network based algorithms, and batch size, we selected the most appropriate model for predicting the production stage temperature. LSTM₁₂₈ was selected as the most appropriate model for predicting the production stage temperature. The prediction performance of selected model for the actual temperature is RMSE of 0.0791 and R² of 0.924.

• Journal of the military operations research society of Korea
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• v.2 no.1
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• pp.111-125
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• 1976

This paper is to explore technological forecasting methodologies and their application to military R&D programming. Among a number of forecasting methodologies, eight frequently used methods are explained. They are; Delphi method, analogy, growth curve, trend extrapolation, analytical model, breakthrough, normative method, and combined method. Due to the characteristic situation of a developing country, the application of technological forecasting to the Korean military R&D programming is limited. Therefore, only two forecasting methods such as Delphi and normative method are utilized in the development of a decision model for the military R&D programming. The model consists of a dynamic programming using decision tree model, which optimizes the total cost to equip a certain military item under a given range of risk during a given period. Some pitfalls in forecasting methodologies and of the model are discussed.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.3
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• pp.251-258
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• 2001

Indoor and outdoor nitrogen dioxide(NO$_2$) concentrations of 122 houses were measured and compared with measurements of personal NO$_2$ exposure simultaneously . Time activity patterns were used to determine the impacts on NO$_2$ exposure assessment and time weighed average model to estimate the personal NO$_2$ exposure. Most people spent their times more than 80% of indoor and more than 50% in home, respectively. Personal NO$_2$ esposure was found to be significantly associated with both indoor NO$_2$ concentration(r=0.70) and outdoor NO$_2$ concentration (r=0.68). Using time weighted average model, personal NO$_2$ exposure was estimated with NO$_2$ measurements in indoor home, indoor workplace and outdoor home. The estimated NO$_2$ measurements were significantly correlated with measured personal exposures(r=0.69, N=122). For the difference between measured and estimated NO$_2$ exposures by multiple regression analysis showed that NO$_2$ concentrations in near workplace and other outdoors of no NO$_2$ measurements affected the personal NO$_2$ exposures(p=0.023).

• Experimental and Molecular Medicine
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• v.50 no.11
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• pp.9.1-9.10
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• 2018

Although the positive effects of recombinant fibroblast growth factor-2 (rFGF-2) in chronic obstructive pulmonary disease (COPD) have been implicated in previous studies, knowledge of its role in COPD remains limited. The mechanism of FGF2 in a COPD mouse model and the therapeutic potential of rFGF-2 were investigated in COPD. The mechanism and protective effects of rFGF-2 were evaluated in cigarette smoke-exposed or elastase-induced COPD animal models. Inflammation was assessed in alveolar cells and lung tissues from mice. FGF-2 was decreased in the lungs of cigarette smoke-exposed mice. Intranasal use of rFGF-2 significantly reduced macrophage-dominant inflammation and alveolar destruction in the lungs. In the elastase-induced emphysema model, rFGF-2 improved regeneration of the lungs. In humans, plasma FGF-2 was decreased significantly in COPD compared with normal subjects (10 subjects, P = 0.037). The safety and efficacy of inhaled rFGF-2 use was examined in COPD patients, along with changes in respiratory symptoms and pulmonary function. A 2-week treatment with inhaled rFGF-2 in COPD (n = 6) resulted in significantly improved respiratory symptoms compared with baseline levels (P < 0.05); however, the results were not significant compared with the placebo. The pulmonary function test results of COPD improved numerically compared with those in the placebo, but the difference was not statistically significant. No serious adverse events occurred during treatment with inhaled rFGF-2. The loss of FGF-2 production is an important mechanism in the development of COPD. Inhaling rFGF-2 may be a new therapeutic option for patients with COPD because rFGF-2 decreases inflammation in lungs exposed to cigarette smoke.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.589-599
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• 1995

The frictional pressure drop of a capillary tube flow is experimentally investigated for pure refrigerants such as R32, R125, and R134a and refrigerant mixtures such as R32/R134a(30/70 by mass percent), R32/R125(60/40), R125/R134a(30/70), and R32/R125/R134a(23/25/52). The binary interaction parameters for the calculation of viscosities of refrigerant mixtures are found based upon the data in the open literature. Several homogeneous flow models predicting the viscosity of two-phase region are compared to select the best model. Cicchitti's equation is known to be the most adequate for the prediction of the viscosity for refrigerant mixtures, which is used in the analysis of adiabatic capillary flows. A model for the prediction of the frictional pressure drop of single and two-phase flow is developed for refrigerant mixtures in this study. This model may be used to design and analyze the performance of a capillary tube in the refrigerating system.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.342-357
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• 2014

The present study analyzes the relationship between research and development (R&D) inputs and performance of a national technology innovation R&D program using successive binary Logistic regression models based on a typical R&D logic model. In particular, this study focuses on to answer the following three main questions; (1) "To what extent, do the R&D inputs have an effect on the performance creation?"; (2) "Is an obvious relationship verified between the immediate predecessor and its successor performance?"; and (3) "Is there a difference in the performance creation between R&D government subsidy recipient types and between R&D collaboration types?" Methodologically, binary Logistic regression models are established successively considering the "Success-Failure" binary data characteristic regarding the performance creation. An empirical analysis is presented analyzing the sample n = 2,178 R&D projects completed. This study's major findings are as follows. First, the R&D inputs have a statistically significant relationship only with the short-term, technical output, "Patent Registration." Second, strong dependencies are identified between the immediate predecessor and its successor performance. Third, the success probability of the performance creation is statistically significantly different between the R&D types aforementioned. Specifically, compared with "Large Company", "Small and Medium-Sized Enterprise (SMS)" shows a greater success probability of "Sales" and "New Employment." Meanwhile, "R&D Collaboration" achieves a larger success probability of "Patent Registration" and "Sales."