• KSBB Journal
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• v.20 no.2 s.91
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• pp.106-111
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• 2005

The functional relationship between the number of mole of an i-fatty acid (Si) included in fish oil and the hydrolysis time(t) was expressed as a mathematical model, $S_i=-{\alpha_i}1n(t)+\beta_i$. The average errors of calculated values on the basis of the measured values were distributed in the range of less than $5\%$ for all the 15 fatty aids composing of fish oil. The equation of hydrolysis rate of each fatty acid was deduced as $v_i={\gamma_i}exp(\frac{S_i}{\alpha_i})$ from the above-mentioned $S_i=-{\alpha_i}ln(t)+{\beta_i}$. Therefore the hydrolysis yields of fatty acids were analyzed using the equation of $S_i\;Vs.\;t.$. The 15 fatty acids were categorized into 4groups from the view point of hydrolysis yield. The hydrolysis yields of the first group, including C14:0, C16:0, C16:1, C18:0, C18:1 (n-7) and 1l8:1 (n-9), were higher than $70\%$ at 48 hr of hydrolysis. Those of the second group, C20:1, C22:1, C18:3, C20:4 and C20:5, were distributed from $40\%,\;to\;60\%$, and third group were around $30\%$. The final group containing only C22:6 was very hard to be hydrolyzed and the yield was less than $20\%$ at the same time.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.821-832
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• 1998

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.5
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• pp.519-526
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• 2018

In this study, an algorithm to predict evacuation routes in support of shipboard lifesaving activities is presented. As the first step of algorithm development, the feasibility and necessity of an evacuation route prediction algorithm are shown numerically. The proposed algorithm can be explained in brief as follows. This system continuously obtains and analyzes passenger movement data from the ship's monitoring system during non-disaster conditions. In case of a disaster, evacuation route prediction information is derived using the previously acquired data and a prediction tool, with the results provided to rescuers to minimize casualties. In this study, evacuation-related data obtained through fire evacuation trials was filtered and analyzed using a statistical method. In a simulation using the conventional evacuation prediction tool, it was found that reliable prediction results were obtained only in the SN1 trial because of the conceptual and structural nature of the tool itself. In order to verify the validity of the algorithm proposed in this study, an industrial engineering tool was adapted for evacuation characteristics prediction. When the proposed algorithm was implemented, the predicted values for average evacuation time and route were very similar to the measured values with error ranges of 0.6-6.9 % and 0.6-3.6 %, respectively. In the future, development of a high-performance evacuation route prediction algorithm is planned based on shipboard data monitoring and analysis.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.225-238
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• 2019

Migration velocity analysis (MVA) for creating optimum depth-domain velocities in seismic imaging was applied to marine long-offset multi-channel data, and the effectiveness of the MVA approach was demonstrated by the combinations of conventional data processing procedures. The time-domain images generated by conventional time-processing scheme has been considered to be sufficient so far for the seismic stratigraphic interpretation. However, when the purpose of the seismic imaging moves to the hydrocarbon exploration, especially in the geologic modeling of the oil and gas play or lead area, drilling prognosis, in-place hydrocarbon volume estimation, the seismic images should be converted into depth domain or depth processing should be applied in the processing phase. CMP-based velocity analysis, which is mainly based on several approximations in the data domain, inherently contains errors and thus has high uncertainties. On the other hand, the MVA provides efficient and somewhat real-scale (in depth) images even if there are no logging data available. In this study, marine long-offset multi-channel seismic data were optimally processed in time domain to establish the most qualified dataset for the usage of the iterative MVA. Then, the depth-domain velocity profile was updated several times and the final velocity-in-depth was used for generating depth images (CRP gather and stack) and compared with the images obtained from the velocity-in-time. From the results, we were able to confirm the depth-domain results are more reasonable than the time-domain results. The spurious local minima, which can be occurred during the implementation of full waveform inversion, can be reduced when the result of MVA is used as an initial velocity model.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.807-816
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• 2015

In general, the water stage-discharge relationship curve is established based on the assumptions of linearity and homoscedasticity. However, the relationship between the water stage and discharge is affected from geomorphological factors, which violates the basic assumptions of the water stage-discharge relationship curve. In order to reduce the error due to the violations, the curve is divided into several sections based on the manager's judgement considering change of cross-sectional shape. In this research, the objective-splitting criteria of the curve is proposed based on the measured data without the subjective decision. First, it is assumed that the coefficient of variation follows the normal distribution. Then, if the newly calculated coefficient of variation is outside of the 95% confidential interval, the curve is divided. Namely, the groups is divided by the characteristics of the coefficient of variation and the reasonable criteria is provided for establishing a multi-segmented rating curve. To validate the proposed method, it was applied to the data generated by three artificial power functions. In addition, to confirm the applicability of the proposed method, it is applied to the water stage and discharge data of the Muju water stage gauging station and Sangegyo water stage gauging station. As a result, it is found that the automatically divided rating curve improves the accuracy and extrapolation accuracy of the rating curve. Finally, through the residual analysis using Shapiro-Wilk normality test, it is confirmed that the residual of water stage-discharge relationship curve tends to follow the normal distribution.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.10
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• pp.691-697
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• 2014

Though the upper stream basin area of Gwanpyung-Cheon in Daejeon, Korea is protected as Green Belt Zone, the stream is under constant environmental pressure due to current agricultural practices and infrastructure development in its basin area. To develop appropriate integrated water resources management plan for the stream, it is necessary to consider not only water quality problems but also water quantity aspect. In this study, Storm Water Management Model (SWMM) was calibrated and validated with sets of field measurements to predict for future water flow and water quality conditions for any rainfall event. While flow modeling results showed good agreement by showing correlation coefficient is greater than 0.9, water quality modeling results showed relatively less accurate levels of agreements with correlation coefficient between 0.67 and 0.87. Hypothetical basin development scenarios were developed to compare effect on stream water quality and quantity when Low Impact Development (LID) technologies are applied in the basin. The results of this study can be used effectively in decision making processes of urban development Gwanpyung-Cheon area by comparing basin management alternatives such as LID methods.

• Journal of Korean Society of Forest Science
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• v.86 no.1
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• pp.17-24
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• 1997

As the first step to estimate the potential natural vegetation distribution of the globe, the best spherical interpolation method was developed to the temperature and precipitation which have close relation to the distribution pattern of world natural vegetation. For developing the interpolation method, a named Light Climatic Dataset composed of 1,060 stations around the globe was randomly divided into halves of feeding side and target side. The discrepancy between the observed and estimated values at the target stations was compared with combinations of parameters and methods. The estimated values were calculated to each combination which is all-out, constant radius and constant station methods in the selection of the feeding stations, n square reciprocal and negative exponential functions in weighting function of distance between feeding stations and each target, and oval weighting in direction of the feeding stations from each target. As a result, it turned out that the spherical interpolation with negative exponential weighting function fed from the constant radius stations ovally weighed yields the best estimates both for temperature and for precipitation. The parameters for temperature are $30^{\circ}$ in constant radius, 0.78 in negative exponential function and 0.4 in oval weighting, and for precipitation are $30^{\circ}$, 0.53 and 0.4, respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.99-118
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• 2012

The aim of this study is to define a correlation between spatial distribution characteristics of FFG(Functional Feeding Groups) of aquatic insects and related environmental factors in the Geum River based on the theory of RCC(River Continuum Concept). For that objective we had used SMRA(Stepwise Multiple Regression Analysis) method to analyze close relationship between the distribution of aquatic insects and the physical and chemical factors that may affect their inhabiting environment in the study area. And then, a probabilistic method named Frequency Ratio Model(FRM) and spatial analysis function of GIS were applied to produce a predictive distribution map of biota community considering their distribution characteristics according to the environmental factors as related variables. As a result of SMRA, the values of decision coefficient for factors of elevation, stream width, flow velocity, conductivity, temperature and percentage of sand showed higher than 0.5. Therefore these 6 environmental factors were considered as major factors that might affect the distribution characteristics of aquatic insects. Finally, we had calculated RMSE(Root Mean Square Error) between the predicted distribution map and prior survey database from other researches to verify the result of this study. The values of RMSE were calculated from 0.1892 to 0.4242 according to each FFG so we could find out a high reliability of this study. The results of this study might be used to develop a new estimation method for aquatic ecosystem with macro invertebrate community and also be used as preliminary data for conservation and restoration of stream habitats.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1115-1128
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• 2013

The purpose of this study is to evaluate the suspended solids and eutrophication processes relationships in Chungju lake using CE-QUAL-W2, two-dimensional (2D) longitudinal/vertical hydrodynamic and water quality model. For water quality modeling, the lake segmentation was configured as 7 branches system according to their shape and tributary distribution. The model was calibrated (2010) and validated (2008) using 2 years of field data of water temperature, suspended solids (SS), total nitrogen (TN), total phosphorus (TP) and algae (Chl-a). The water temperature began to increase in depth from April and the stratification occurred at about 10 m early July heavy rain. The high SS concentration of the interflow density currents entering from the watershed was well simulated especially for July 2008 heavy rainfall event. The simulated concentration range of TN and TP was acceptable, but the errors might occur form the poor reflection for sedimentation velocity of nitrogen component and adsorption-sediment of phosphorus in model. The concentration of Chl-a was simulated well with the algal growth patterns in summer of 2010 and 2008, but the error of under estimation may come from the use of width-averaged velocity and concentration, not considering the actual to one side inclination by wind effect.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.569-583
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• 2013

This study is to evaluate the future climate change impact on hydrological components in the Seolmacheon ($8.54km^2$) mixed forest catchment located in the northwest of South Korea using SWAT (Soil and Water Assessment Tool) model. To reduce the uncertainty, the model was spatially calibrated (2007~2008) and validated (2009~2010) using daily observed streamflow, evapotranspiration, and soil moisture data. Hydrological predicted values matched well with the observed values by showing coefficient of determination ($R^2$) from 0.74 to 0.91 for streamflow, from 0.56 to 0.71 for evapotranspiration, and from 0.45 to 0.71 for soil moisture. The HadGEM3-RA future weather data of Representative Concentration pathway (RCP) 4.5 and 8.5 scenarios of the IPCC (Intergovernmental Panel on Climate Change) AR5 (Assessment Report 5) were adopted for future assessment after bias correction of ground measured data. The future changes in annual temperature and precipitation showed an upward tendency from $0.9^{\circ}C$ to $4.2^{\circ}C$ and from 7.9% to 20.4% respectively. The future streamflow showed an increase from 0.6% to 15.7%, but runoff ratio showed a decrease from 3.8% to 5.4%. The future predicted evapotranspiration about precipitation increased from 4.1% to 6.8%, and the future soil moisture decreased from 4.3% to 5.5%.