• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.4 s.54
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• pp.289-293
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• 2005

Nowadays there are many sun protection cosmetics including organic or inorganic UV filter as an active ingredient. Chemically stable inorganic sunsEreen agents, usually metal oxides, we widely employed in high SPF products. Titanium dioxide is one of the most frequently used inorganic UV filters. It has been used as pigments for a long period of cosmetic history. With the development of micronization techniques, it becomes possible to incorporate titanium dioxide in sunscreen formulations without whitening effect and it becomes an important research topic. However, there are very few works related to quantitations of titanium dioxide in sunscreen products. In this research, we analyzed amounts of titanium dioxide in sunscreen cosmetics by adapting redof titration, reduction of Ti(IV) to Ti(III) and reoxidation to Ti(IV). After calcification of other organic ingredients of cosmetics, titanium dioxide is dissolved by hot sulfuric acid. The dissolved Ti(IV) is reduced to the Ti(III) by adding aluminum metals. The reduced Ti(III) is titrated against a standard oxidizing agent, Fe(III) (ammonium iron(III) sulfate), with potassium thiocyanate as an indicator In order to test accuracy and applicability of the proposed method, we analyzed the amounts of titanium dioxide in four types of sunscreen cosmetics, such as cream, make-up base, foundation and powder, after adding known amounts of titanium dioxide $(1{\sim}25w/w%)$. The percent recoveries of the titanium dioxide in four types of formulations were in the range between 96 and 105%. We also analyzed 7 commercial cosmetic products labeled titanium dioxide as an ingredient and compared the results with those of obtained from ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry), one of the most powerful atomic analysis techniques. The results showed that the titrated amounts were well coincided with the analyzed amounts of titanium dioxide by ICP-AES. Although instrumental analytical methods, ICP-MS (Inductively Coupled Plasma-Mass Spectrometry) and ICP-AES, are the best for the analysis of titanium, it is hard to adopt because of their high prices for small cosmetic companies. It was found that the volumetric method presented here gat e quantitative and reliable results with routine lab-wares and chemicals.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.3
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• pp.375-388
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• 2019

Accurate evaluation of sea-to-air $CO_2$ flux and its variability is crucial information to the understanding of global carbon cycle and the prediction of atmospheric $CO_2$ concentration. $fCO_2$ observations are sparse in space and time in the East Sea. In this study, we derived high resolution time series of surface $fCO_2$ values in the southwest East Sea, by feeding sea surface temperature (SST), salinity (SSS), chlorophyll-a (CHL), and mixed layer depth (MLD) values, from either satellite-observations or numerical model outputs, to three machine learning models. The root mean square error of the best performing model, a Random Forest (RF) model, was $7.1{\mu}atm$. Important parameters in predicting $fCO_2$ in the RF model were SST and SSS along with time information; CHL and MLD were much less important than the other parameters. The net $CO_2$ flux in the southwest East Sea, calculated from the $fCO_2$ predicted by the RF model, was $-0.76{\pm}1.15mol\;m^{-2}yr^{-1}$, close to the lower bound of the previous estimates in the range of $-0.66{\sim}-2.47mol\;m^{-2}yr^{-1}$. The time series of $fCO_2$ predicted by the RF model showed a significant variation even in a short time interval of a week. For accurate evaluation of the $CO_2$ flux in the Ulleung Basin, it is necessary to conduct high resolution in situ observations in spring when $fCO_2$ changes rapidly.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

• Korean Journal of Optics and Photonics
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• v.33 no.4
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• pp.167-176
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• 2022

Adaptive optics (AO) systems compensate for atmospheric disturbance, especially phase distortion, by introducing counter-wavefront deformation calculated from real-time wavefront sensing or prediction. Because AO system implementations are time-consuming and costly, it is highly desirable to estimate the system's performance during the development of the AO system or its parts. Among several techniques, we mostly apply statistical analysis, computational simulation, and optical-bench tests. Statistical analysis estimates performance based on the sum of performance variances due to all design parameters, but ignores any correlation between them. Computational simulation models every part of an adaptive optics system, including atmospheric disturbance and a closed loop between wavefront sensor and deformable mirror, as close as possible to reality, but there are still some differences between simulation models and reality. The optical-bench test implements an almost identical AO system on an optical bench, to confirm the predictions of the previous methods. We are currently developing an AO system for a 1.6-m ground telescope using a deformable mirror that was recently developed in South Korea. This paper reports the results of the statistical analysis and computer simulation for the system's design and confirmation. For the analysis, we apply the Strehl ratio as the performance criterion, and the median seeing conditions at the Bohyun observatory in Korea. The statistical analysis predicts a Strehl ratio of 0.31. The simulation method similarly reports a slightly larger value of 0.32. During the study, the simulation method exhibits run-to-run variation due to the random nature of atmospheric disturbance, which converges when the simulation time is longer than 0.9 seconds, i.e., approximately 240 times the critical time constant of the applied atmospheric disturbance.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.181-196
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• 2023

Size, velocity, and time equivalence are mechanisms that allow us to perceive objects in three-dimensional space consistently, despite errors on the two-dimensional retinal image. These mechanisms work on common cues, suggesting that the perception of motion distance, motion speed, and motion time may share common processing. This can lead to the hypothesis that, despite the spatial nature of visual stimuli distorting temporal perception, the perception of motion speed and the perception of motion duration will tend to oppose each other, as observed for objects moving in the environment. To test this hypothesis, the present study measured perceived speed using Müller-Lyer illusion stimulus to determine the relationship between the time-perception consequences of motion stimuli observed in previous studies and the speed perception measured in the present study. Experiment 1 manipulated the perceived motion trajectory while controlling for the retinal motion trajectory, and Experiment 2 manipulated the retinal motion trajectory while controlling for the perceived motion trajectory. The result is that the speed of the inward stimulus, which is perceived to be shorter, is estimated to be higher than that of the outward stimulus, which is perceived to be longer than the actual distance traveled. Taken together with previous time perception findings, namely that time perception is expanded for outward stimuli and contracted for inward stimuli, this suggests that when the perceived trajectory of a stimulus manipulated by the Müller-Lyer illusion is controlled for, perceived speed decreases with increasing duration and increases with decreasing duration when the perceived distance of the stimulus is constant. This relationship suggests that the relationship between time and speed perceived by spatial cues corresponds to the properties of objects moving in the environment, i.e, an increase in time decreases speed and a decrease in time increases speed when distance remains the same.

• Journal of Korean Society of Forest Science
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• v.85 no.3
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• pp.453-461
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• 1996

Three Phyllostachys stands of P. pubescens, P. bambusoides and P. nigra var, henonis in Sunchon were studied to investigate biomass, net production and nutrient distribution. Five $10m{\times}10m$ quadrats were set up and 20 sample culms of 2 years and over were harvested for dimension analysis in each stand. One year old culms and subterranean parts were estimated by the harvested quadrat method. The largest mean DBH, height and basal area were shown in P. pubescens stand, and followed by P. nigra var. henonis stand and P. bambusoides stand. There was little difference in accuracy among three allometric biomass regression models of logWt=A+B1ogD, $logWt=A+BlogD^2H$ and logWt=A+BlogD+ClogH, where Wt, D and H were dry weight, DBH and height, respectively. Analysis of covariance showed that there were significant differences in intercept among the linear allometric biomass regressons of three Phyllostachys species. Biomass included subterranean parts was the largest in P. pubescens stand(103.621t/ha), and followed by P. nigra var. henonis stand(86.447t/ha) and P. bambusoides stand(36.767t/ha). Leaf biomass was 6.3% to 7.8% of total biomass in each stands. The ratio of aboveground biomass and subterranean biomass in each stand was 1.87 to 2.26. Net production included subterranean parts was the greatest in P. pubescens stand(6.115t/ha/yr), and followed by P. nigra var. henonis stand(5.609t/ha/yr) and P, bambusoides stand(3.252t/ha/yr). The highest net assimilation ratio was estimated in P. pubescens stand(2.979), and followed by P. nigra var. henonis stand(2.752) and P. bambusoides stand(2.187). Biomass accumulation ratio of each stand was 2.679 to 5.358. Concentrations of N, P and Mg were the highest in leaves, and followed by subterranean parts, and culms+branches in all three species. Concentration of Ca was the highest in leaves, and followed by culms+branches, and subterranean parts in all three species. The difference in biomass among three species stands was caused by their culm size, leaf biomass, net assimilation ratio, and efficiency of leaves to produce culms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.1
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• pp.39-47
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• 2009

The importance of securing water resources and their efficient management has attracted more attention recently due to water deficit. In water budget analysis, however, evapotranspiration(${\lambda}E$) has been approximated as the residual in the water balance equation or estimated from empirical equations and assumptions. To minimize the uncertainties in these estimates, it is necessary to directly measure ${\lambda}E$. In this study, using the eddy covariance technique, we have measured ${\lambda}E$ in a mixed forest in the Seolmacheon catchment in Korea from September 2007 to December 2008. During the growing season(May-July), ${\lambda}E$ in this mixed forest averaged about $2.2\;mm\;d^{-1}$, whereas it was on average $0.5\;mm\;d^{-1}$ during the non-growing season in winter. The annual total ${\lambda}E$ in 2008 was $581\;mm\;y^{-1}$, which is about 1/3 of the annual precipitation of 1997 mm. Despite the differences in the amount and frequency of precipitation, the accumulated ${\lambda}E$ during the overlapping period(i.e., September to December) for 2007 and 2008 was both ${\sim}110$ mm, showing virtually no difference. The omega factor, which is a measure of decoupling between forest and the atmosphere, was on average 0.5, indicating that the contributions of equilibrium ${\lambda}E$ and imposed ${\lambda}E$ to the total ${\lambda}E$ were about the same. The results suggest that ${\lambda}E$ in this mixed forest was controlled by various factors such as net radiation, vapor pressure deficit, and canopy conductance. In this study, based on the direct measurements of ${\lambda}E$, we have quantified the relative contribution of ${\lambda}E$ in the water balance of a mixed forest in the Seolmacheon catchment. In combination with runoff data, the information on ${\lambda}E$ would greatly enhance the reliability of water budget analysis in this catchment.