• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.863-874
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• 2018

The purpose of this study is to evaluate the future climate change impact on stream aquatic ecology health of Han River watershed ($34,148km^2$) using SWAT (Soil and Water Assessment Tool) and random forest. The 8 years (2008~2015) spring (April to June) Aquatic ecology Health Indices (AHI) such as Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI) and Fish Assessment Index (FAI) scored (0~100) and graded (A~E) by NIER (National Institute of Environmental Research) were used. The 8 years NIER indices with the water quality (T-N, $NH_4$, $NO_3$, T-P, $PO_4$) showed that the deviation of AHI score is large when the concentration of water quality is low, and AHI score had negative correlation when the concentration is high. By using random forest, one of the Machine Learning techniques for classification analysis, the classification results for the 3 indices grade showed that all of precision, recall, and f1-score were above 0.81. The future SWAT hydrology and water quality results under HadGEM3-RA RCP 4.5 and 8.5 scenarios of Korea Meteorological Administration (KMA) showed that the future nitrogen-related water quality in watershed average increased up to 43.2% by the baseflow increase effect and the phosphorus-related water quality decreased up to 18.9% by the surface runoff decrease effect. The future FAI and BMI showed a little better Index grade while the future TDI showed a little worse index grade. We can infer that the future TDI is more sensitive to nitrogen-related water quality and the future FAI and BMI are responded to phosphorus-related water quality.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.3
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• pp.229-234
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• 2001

The EDXRF(Energy Dispersive X-ray Fluorescence Spectrometer) technique was applied to the determination of heavy metals in welding fume. The EDXRF method designed in this study was a non-destructive analysis method. Samples were analyzed directly by EDXRF without any pre-treatment such as digestion and dilution. The samples used to evaluate this method were laboratory samples exposed in a chamber connected with a welding fume generator. The samples were first analyzed using a non-destructive EDXRF method. The samples subsequently were analyzed using AAS method to verify accuray of the EDXRF method. The purpose of this study was to evaluate the possibility of the non-destructive analysis of heavy metals in welding fume by EDXRF. The results of this study were as follow: 1.When the samples were collected under the open-face sampling condition, a surface distribution of welding fume particles on sample filters was uniform, which made non-destructive analysis possible. 2. The method was statistically evaluated according to the NIOSH(National Institute for Occupational Safety and Health) and HSE(Health and Safety Executive) method. 3. The overall precision of the EDXRF method Was calculated at 3.45 % for Cr, 2.57 % for Fe and 3.78 % for Mn as relative standard deviation(RSD), respectively. The limits of detection were calculated at $0.46{\mu}g$/sample for Cr, $0.20{\mu}g$/sample for Fe and $1.14{\mu}g$/sample for Mn, respectively. 4. A comparison between the results of Cr, Fe, Mn analyzed by EDXRF and AAS was made in order to assess the accuracy of EDXRF method. The correlation coefficient between the results of EDXRF and AAS was 0.9985 for Cr, 0.9995 for Fe and 0.9982 for Mn, respectively. The overall uncertainty was determined to be ${\pm}12.31%$, 8.64 % and 11.91 % for Cr, Fe and Mn, respectively. In conclusion, this study showed that Cr, Fe, Mn in welding fume were successfully analyzed by the EDXRF without any sample pre-treatment such as digestion and dilution and a good correlation between the results of EDXRF and AAS was obtained. It was thus possible to use the EDXRF technique as an analysis method of working environment samples. The EDXRF method was an efficient method in a non-destructive analysis of heavy metals in welding fume.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1691-1707
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• 2022

Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.5-24
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• 2022

The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4107-4107
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• 2001

Previous works have shown the viability of NIRS technology for the prediction of fatty acids in Iberian pig fat, but although the resulting equations showed high precision, in the predictions of new samples important fluctuations were detected, greater with the time passed from calibration development to NIRS analysis. This fact makes the use of NIRS calibrations in routine analysis difficult. Moreover, this problem only appears in products like fat, that show spectrums with very defined absorption peaks at some wavelengths. This circumstance causes a high sensibility to small changes of the instrument, which are not perceived with the normal checks. To avoid these inconveniences, the software WinISI 1.04 has a mathematic algorithm that consist of create a “Repeatability File”. This file is used during calibration development to minimize the variation sources that can affect the NIRS predictions. The objective of the current work is the evaluation of the use of a repeatability file in quantitative NIRS analysis of Iberian pig fat. A total of 188 samples of Iberian pig fat, produced by COVAP, were used. NIR data were recorded using a FOSS NIRSystems 6500 I spectrophotometer equipped with a spinning module. Samples were analysed by folded transmission, using two sample cells of 0.1mm pathlength and gold surface. High accuracy calibration equations were obtained, without and with repeatability file, to determine the content of six fatty acids: miristic (SECV$\sub$without/=0.07% r$^2$$\sub$without/=0.76 and SECV$\sub$with/=0.08% r$^2$$\sub$with/=0.65), Palmitic (SECV$\sub$without/=0.28 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.24% r$^2$$\sub$with/=0.98), palmitoleic (SECV$\sub$without/=0.08 r$^2$$\sub$without/=0.94 and SECV$\sub$with/=0.09% r$^2$$\sub$with/=0.92), Stearic (SECV$\sub$without/=0.27 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.29% r$^2$$\sub$with/=0.96), oleic (SECV$\sub$without/=0.20 r$^2$$\sub$without/=0.99 and SECV$\sub$with/=0.20% r$^2$$\sub$with/=0.99) and linoleic (SECV$\sub$without/=0.16 r$^2$$\sub$without/=0.98 and SECV$\sub$with/=0.16% r$^2$$\sub$with/=0.98). The use of a repeatability file like a tool to reduce the variation sources that can disturbed the prediction accuracy was very effective. Although in calibration results the differences are negligible, the effect caused by the repeatability file is appreciated mainly when are predicted new samples that are not in the calibration set and whose spectrum were recorded a long time after the equation development. In this case, bias values corresponding to fatty acids predictions were lower when the repeatability file was used: miristic (bias$\sub$without/=-0.05 and bias$\sub$with/=-0.04), Palmitic (bias$\sub$without/=-0.42 and bias$\sub$with/=-0.11), Palmitoleic (bias$\sub$without/=-0.03 and bias$\sub$with/=0.03), Stearic (bias$\sub$without/=0.47 and bias$\sub$with/=0.28), oleic (bias$\sub$without/=0.14 and bias$\sub$with/=-0.04) and linoleic (bias$\sub$without/=0.25 and bias$\sub$with/=-0.20).

• Journal of the Korean Wood Science and Technology
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• v.2 no.2
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• pp.8-12
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• 1974

1. If one unity is given to the prongs whose ends touch each other for estimating the internal stresses occuring in it, the internal stresses which are developed in the open prongs can be evaluated by the ratio to the unity. In accordance with the above statement, an equation was derived as follows. For employing this equation, the prongs should be made as shown in Fig. I, and be measured A and B' as indicated in Fig. l. A more precise value will result as the angle (J becomes smaller. $CH=\frac{(A-B') (4W+A) (4W-A)}{2A[(2W+(A-B')][2W-(A-B')]}{\times}100%$ where A is thickness of the prong, B' is the distance between the two prongs shown in Fig. 1 and CH is the value of internal stress expressed by percentage. It precision is not required, the equation can be simplified as follows. $CH=\frac{A-B'}{A}{\times}200%$ 2. Under scheduled drying condition III the kiln, when the weight of a sample board is constant, the moisture content of the shell of a sample board in the case of a normal casehardening is lower than that of the equilibrium moisture content which is indicated by the Forest Products Laboratory, U. S. Department of Agriculture. This result is usually true, especially in a thin sample board. A thick unseasoned or reverse casehardened sample does not follow in the above statement. 3. The results in the comparison of drying rate with five different kinds of wood given in Table 1 show that the these drying rates, i.e., the quantity of water evaporated from the surface area of I centimeter square per hour, are graded by the order of their magnitude as follows. (1) Ginkgo biloba Linne (2) Diospyros Kaki Thumberg. (3) Pinus densiflora Sieb. et Zucc. (4) Larix kaempheri Sargent (5) Castanea crenata Sieb. et Zucc. It is shown, for example, that at the moisture content of 20 percent the highest value revealed by the Ginkgo biloba is in the order of 3.8 times as great as that for Castanea crenata Sieb. & Zucc. which has the lowest value. Especially below the moisture content of 26 percent, the drying rate, i.e., the function of moisture content in percentage, is represented by the linear equation. All of these linear equations are highly significant in testing the confficient of X i. e., moisture content in percentage. In the Table 2, the symbols are expressed as follows; Y is the quantity of water evaporated from the surface area of 1 centimeter square per hour, and X is the moisture content of the percentage. The drying rate is plotted against the moisture content of the percentage as in Fig. 2. 4. One hundred times the ratio(P%) of the number of samples occuring in the CH 4 class (from 76 to 100% of CH ratio) within the total number of saplmes tested to those of the total which underlie the given SR ratio is measured in Table 3. (The 9% indicated above is assumed as the danger probability in percentage). In summarizing above results, the conclusion is in Table 4. NOTE: In Table 4, the column numbers such as 1. 2 and 3 imply as follows, respectively. 1) The minimum SR ratio which does not reveal the CH 4, class is indicated as in the column 1. 2) The extent of SR ratio which is confined in the safety allowance of 30 percent is shown in the column 2. 3) The lowest limitation of SR ratio which gives the most danger probability of 100 percent is shown in column 3. In analyzing above results, it is clear that chestnut and larch easly form internal stress in comparison with persimmon and pine. However, in considering the fact that the revers, casehardening occured in fir and ginkgo, under the same drying condition with the others, it is deduced that fir and ginkgo form normal casehardening with difficulty in comparison with the other species tested. 5. All kinds of drying defects except casehardening are developed when the internal stresses are in excess of the ultimate strength of material in the case of long-lime loading. Under the drying condition at temperature of $170^{\circ}F$ and the lower humidity. the drying defects are not so severe. However, under the same conditions at $200^{\circ}F$, the lower humidity and not end coated, all sample boards develop severe drying defects. Especially the chestnut was very prone to form the drying defects such as casehardening and splitting.

• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.1
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• pp.1-8
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• 2015

To evaluate accuracy and precision of determination of total alkalinity ($Alk_T$) and carbon dioxide ($TCO_2$) derived from present study, experiment was applied with $CO_2$ CRM (Batch 132, Scripps Institution of Oceanography; $Alk_T=2229.24{\pm}0.39{\mu}mol/kg$, $TCO_2=2032.65{\pm}0.45{\mu}mol/kg$). As the result, average concentration of $Alk_T$ and $TCO_2$ was $2354.09{\mu}mol/kg$ (~5.6% difference with $CO_2$ CRM) and $2089.60{\mu}mol/kg$ (~2.3% difference with $CO_2$ CRM), respectively. For previous method (Gran Titration) by addition $NaHCO_3$ to deionized water($Alk_T$ $2023.33{\mu}mol/kg$), average concentration was $2193.39{\mu}mol/kg$ (sd=57.15, n=7). Whereas, average concentration was $2017.02{\mu}mol/kg$ (sd=10.98, n=7) for the present study. Recovery yield experiments of total alkalinity in deionized water and seawater were implemented by addition of $NaHCO_3$. The recovery yield of deionized water in the range 0 to $4952.39{\mu}mol/kg$ was 100.8% ($R^2$=0.999), and seawater in the range 0 to $2041.32{\mu}mol/kg$ was 102.3% ($R^2$=0.999). Comparison of $pCO_2$ sensor (PSI $CO_2-Pro^{TM}$) with present method showed very meaningful correlation coefficient ($R^2$=0.977) in the range of 427 to $705{\mu}atm$ and 9.16 to $15.24{\mu}mol/kg$ throught elapsed time for two weeks. Field experiment of diurnal variation of total carbon dioxide was accomplished at Sachon harbor in the coastal waters of East Sea of Korea. Concentration of $Alk_T$ and $TCO_2$ was increased during night, and decreased during daylight hours. The results showed mirror type between $TCO_2$ and dissolved oxygen, which was attributable to photosynthesis and respiration of phytoplankton. Also, open ocean field study was performed to obtain vertical profile of $Alk_T$ and $TCO_2$ in C-C zone (Clarion-Clipperton Fracture Zone), Northeastern Pacific. Average concentrations of $Alk_T$ in the surface mixed layer (0~60 m) and deeper layer below 200 m were $2422.38{\mu}mol/kg$ (sd=78.73, n=20) and $2465.87{\mu}mol/kg$ (sd=57.68, n=103), respectively. And average concentrations of $TCO_2$ were $2134.47{\mu}mol/kg$ (sd=65.4, n=20) and $2431.87{\mu}mol/kg$ (sd=65.02, n=103) in the same depth ranges such as $Alk_T$. Vertical distributions of $Alk_T$ and $TCO_2$ concentrations tended to increase with depth, and analyzed concentrations showed slightly higher than those of previous studies in this area.