• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Economic and Environmental Geology
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• v.48 no.2
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• pp.147-160
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• 2015

In 2014, on 31 August and 1 September, the emissions of $CH_4$, $CO_2$, and $O_2$ gases were measured six times using the closed chamber method from exposed tidal flat sediments in the same position relative to the low point of the tidal cycle in the Eoeun-ri, Taean-gun, on the Mid-western Coast of Korea. The concentrations of $CH_4$ in the air sample collected in the chamber were measured using gas chromatography with an EG analyzer, model GS-23, within 6 hours of collection, and the other gases were measured in real time using a multi-gas monitor. The gas emission fluxes (source (+), and sink (-)) were calculated from a simple linear regression analysis of the changes in the concentrations over time. In order to see the surrounding parameters (water content, temperature, total organic carbon, average mean size of sediments, and the temperature of the inner chamber) were measured at the study site. On the first day, across three measurements during 5 hours 20 minutes, the observed $CO_2$ flux absorption was -137.00 to $-81.73mg/m^2/hr$, and the $O_2$ absorption, measured simultaneously, was -0.03 to $0.00mg/m^2/hr$. On the second day using an identical number of measurements, the $CO_2$ absorption was -20.43 to $-2.11mg/m^2/hr$, and the $O_2$ absorption -0.18 to $-0.14mg/m^2/hr$. The $CH_4$ absorption before low tide was $-0.02mg/m^2/hr$ (first day, Pearson correlation coefficient using the SPSS statistical analysis is -0.555(n=5, p=0.332, pronounced negative linear relationship)), and $-0.15mg/m^2/hr$ (second day, -0.915(n=5, p=0.030, strong negative linear relationship)) on both measurement days. The emitted flux after low tide on both measurement days reached a minimum of $+0.00mg/m^2/hr$ (+0.713(n=5, p=0.176, linear relationship which can be almost ignored)), and a maximum of $+0.03mg/m^2/hr$ (+0.194(n=5, p=0.754, weak positive linear relationship)) after low tide. However, the absolute values of the $CH_4$ fluxes were analyzed at different times. These results suggest that rate for $CH_4$ fluxes, even the same time and area, were influenced by changes in the tidal cycle characteristics of surface sediments for understanding their correlation with these gas emissions, and surrounding parameters such as physiochemical sediments conditions.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2003.10a
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• pp.134-135
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• 2003

The dental implant materials required good mechanical properties, such as fatigue strength, combined with a high resistance to corrosion. For increasing fatigue resistance and delaying onset of stress corrosion cracking, shot peening has been used for > 50 years to extend service life of metal components. However, there is no information on the electrochemical behavior of shot peened and hydroxyapatite(HA) coated Ti-6Al-4V alloys. To increase fatigue strength, good corrosion resistance, and biocompatibility, the electrochemical characteristics of Ti/TiN/HA coated and shot peened Ti-6Al-4V alloys by electron beam physical vapor deposition(EB-PVD) have been researched by various electrochemical method in 0.9%NaCl. Ti-6Al-4V alloys were prepared under the condition of hydrogen and vacuum arc furnace. The produced materials were quenched at 1000$^{\circ}C$ under high purity dried Ar atmosphere and were hold at 500$^{\circ}C$ for 2 hrs to achieve the fatigue strength(1140㎫) of materials. Ti-6Al-4V alloys were prepared under the condition of hydrogen and vacuum arc furnace. Shot peening(SP) and sand blasting treatment was carried out for 1, 5, and 10min. On the surface of Ti-6Al-4V alloys using the steel balls of 0.5mm and alumina sand of 40$\mu\textrm{m}$ size. Ti/TiN/HA multilayer coatings were carried out by using electron-beam deposition method(EB-PVD) as shown Fig. 1. Bulk Ti, powder TiN and hydroxyapatite were used as the source of the deposition materials. Electrons were accelerated by high voltage of 4.2kV with 80 - 120mA on the deposition materials at 350$^{\circ}C$ in 2.0 X 10-6 torr vacuum. Ti/TiN/HA multilayer coated surfaces and layers were investigated by SEM and XRD. A saturated calomel electrode as a reference electrode, and high density carbon electrode as a counter electrode, were set according to ASTM GS-87. The potentials were controlled at a scan rate of 100 mV/min. by a potentiostat (EG&G Co.273A) connected to a computer system. Electrochemical tests were used to investigate the electrochemical characteristics of Ti/TiN/HA coated and shot peened materials in 0.9% NaCl solution at 36.5$^{\circ}C$. After each electrochemical measurement, the corrosion surface of each sample was investigated by SEM.