• Economic and Environmental Geology
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• v.41 no.1
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• pp.15-32
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• 2008

The hydrochemical and isotopic (stable isotopes and noble gas isotopes) analyses for hot spring waters, cold groundwaters and surface water samples from the Seokmodo hot spring area of the Ganghwa province were carried out to characterize the hydrogeochemical characteristics of thermal waters and to interpret the source of thermal water and noble gases and the geochemical evolution of hot spring waters in the Seokmodo geothermal system. The hot spring waters and groundwaters show a weakly acidic condition with the pH values ranging from 6.42 to 6.77 and 6.01 to 7.71 respectively. The outflow temperature of the Seokmodo hot spring waters ranges from $43.3^{\circ}C\;to\;68.6^{\circ}C$. Relatively high values of the electrical conductivities which fall between 60,200 and $84,300{\mu}S/cm$ indicate that the hot spring waters were mixed with seawater in the subsurface geothermal system. The chemical compositions of the Seokmodo hot spring waters are characterized by Na-Ca-Cl water type. On the other hand, cold groundwaters and surface waters can be grouped into three types such as the Na(Ca)-$HCO_3$, Na(Ca)-$SO_4$ and Ca-$HCO_3$ types. The ${\delta}^{18}O\;and\;{\delta}D$ values of hot spring waters vary from -4.41 to -4.47%o and -32.0 to -33.5%o, respectively. Cold groundwaters range from -7.07 to -8.55%o in ${\delta}^{18}O$ and from -50.24 to -59.6%o in ${\delta}D$. The oxygen and hydrogen isotopic data indicate that the hot spring waters were originated from the local meteoric water source. The enrichments of heavy isotopes ($^{18}O\;and\;^2H$) in the Seokmodo hot spring waters imply that the thermal water was derived from the diffusion Bone between fresh and salt waters. The ${\delta}^{34}S$ values ranging from 23.1 to 23.5%o of dissolved sulfate are very close to the value of sea water sulfate of ${\delta}^{34}$S=20.2%o in this area, indicating the origin of sulfate in hot springs from sea water. The $^3H/^4He$ ratio of hot spring waters varies from $1.243{\times}10^{-6}\;to\;1.299{\times}10^{-6}cm^3STP/g$, which suggests that He gas in hot spring waters was partly originated from a mantle source. Argon isotopic ratio $(^{40}Ar/^{36}Ar=298{\times}10^{-6}cm^3STP/g)$ in hot spring waters corresponds to the atmospheric value.

• Journal of Life Science
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• v.25 no.2
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• pp.237-242
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• 2015

The use of calcite-forming bacteria (CFB) in crack remediation and durability improvements in construction materials creates a permanent and environmentally-friendly material. Therefore, research into this type of application is stimulating interdisciplinary studies between microbiology and architectural engineering. However, the mechanisms giving rise to these materials are dependent on calcite precipitation by the metabolism of the CFB, which raises concerns about possible hazards to cement-based construction due to microbial metabolic acid production. The aim of this study was to determine target microorganisms that possibly can have bio-corrosive effects on cement mortar and to assess multi-functional CFBs for their safe application to cement structures. The chalky test was first used to evaluate the $CaCO_3$ solubilization feature of construction sites by fungi, yeast, bacterial strains. Not all bacterial strains are able to solubilize $CaCO_3$, but C. sphaerospermum KNUC253 or P. prolifica KNUC263 showed $CaCO_3$ solubilization activity. Therefore, these two strains were identified as target microorganisms that require control in cement structures. The registered patented strains Bacillus aryabhatti KNUC205, Arthrobacter nicotianae KNUC2100, B. thuringiensis KNUC2103 and Stenotrophomonas maltophilia KNUC2106, reported as multifunctional CFB (fungal growth inhibition, crack remediation, and water permeability reduction of cement surfaces) and isolated from Dokdo or construction site were unable to solubilize $CaCO_3$. Notably, B. aryabhatti KNUC205 and A. nicotianae KNUC2100 could not hydrolyze cellulose or protein, which can be the major constituent macromolecules of internal materials for buildings. These results show that several reported multi-functional CFB can be applied to cement structures or diverse building environments without corrosive or bio-deteriorative risks.

• Korean Journal of Food Science and Technology
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• v.37 no.5
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• pp.768-775
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• 2005

Lentinus edodes powder was added at 1-3%(w/w) to improve functional properties of jocheong. Content of crude protein, ash, crude lipids, total mineral, free sugar and reducing sugar increased with increasing amount of L. edodes powder, while viscosity and solid and carbohydrate contents decreased. Through amino acid analysis, 17 amino acids were identified and quantified, glutamic acid being the major amino acid. No significant differences were observed in fatty acid composition and pH between control and L. edodes powder-added jocheong. Addition of mushroom powder in jocheong decreased lightness, yellowness and redness in Hunter's color value. Sensor score of jucheong containing 1% of L. edodes powder was similar to that of control. Results showed jocheong containing less than 2% L. edodes powder gave highest scores in quality characteristics and sensory evaluation.

• Korean Journal of Food Science and Technology
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• v.7 no.4
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• pp.200-207
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• 1975

This experiment was carried out to investigate the chemical composition and microflora of soy sauce during storage under the different temperature. The results obtained are as follows. (1) Total nitrogen, color density, specific gravity and sodium chloride concentration of soy sauce showed a increasing tendency in the progress of storage period. Open-storage state at $30^{\circ}C\;and\;15^{\circ}C$ were responsible to the increase of components as compare with close-storage state at $5^{\circ}C$. (2) pH and buffer action were not almost changed during the storage. (3) Alcohol and sugar contents of soy sauce showed a decreasing tendency in the process of storage period, especially in the case of open state alcohol being almost disappeared within 11 months in all groups. (4) The number of common bacteria in one ml of soy sauce were counted as $96{\times}10^4$ before pasteurization and $10^3$ after pasteurization. The osmophilic bacteria was counted as $38{\times}10^4$, $10^2$ after pasteurization. (5) The spore number of mold in one ml of soy sauce were counted $32{\times}10^7$ before pasteurization, 58 after pasteurization and 10 to $10^2$ in the progress of storage period. (6) The bacteria number of soy sauce were somewhat decreased with the passing, of the time. The group of high temperature and open state were more notable than low temperature and close state.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.242-249
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• 2008

Recently, AVO analysis has been widely used in oil exploration with seismic subsurface section as a direct indicator of the existence of the gas. In the case of the deep reservoirs like the gas reservoirs in the East-sea, it is often difficult to observe AVO responses in CMP gathers even though the bright spots are shown in the stacked section. Because the reservoir becomes more consolidated as its depth deepens, P-wave velocity does not decrease significantly when the pore fluid is replaced by the gas. Thus the difference in Poisson's ratio, which is a key factor for AVO response, between the reservoir and the layer above it does not increase significantly. In this study, we analyzed the effects of Poisson's ratio difference on AVO response with a variety of Poisson's ratios for the upper and lower layers. The results show that, as the difference in Poisson's ratio between the upper and lower layers decreases, the change in the reflection amplitude with incidence angle decreases and AVO responses become insignificant. To consider the limitation of AVO responses shown in the gas reservoir in East-sea, the velocity model was made by simulation Gorae V structure with seismic data and well logs. The results of comparing AVO responses observed from the synthetic data with theoretical AVO responses calculated by using material properties show that the amount of the change in reflection amplitude with increasing incident angle is very small when the difference in Poisson's ratio between the upper and lower layers is small. In addition, the characteristics of AVO responses were concealed by noise or amplitude distortion arisen during preprocessing. To overcome such limitations of AVO analysis of the data from deep reservoirs, we need to acquire precisely reflection amplltudes In data acquisition stage and use processing tools which preserve reflection amplitude in data processing stage.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• The Journal of Engineering Geology
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• v.15 no.2 s.42
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• pp.213-227
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• 2005

This study aims to assess the problems with investigation method and to suggest the complementary solutions by comparing the predicted data from surface investigation with the outcome data from underground cavern. In the study area, one(NE-1) of 6 fracture zones predicted during the surface investigation was only confirmed in underground caverns. Therefore, it is necessary to improve the confidence level for prediction. In this study, the fracture classification criteria was quantitatively suggested on the basis of the BHTV images of NE-1 fracture zone. The major orientation of background fractures in rock mass was changed at the depth of the storage cavern, the length and intensity were decreased. These characteristics result in the deviation of predieted predicted fracture properties and generate the investigation bias depending on the bore hole directions and investigated scales. The evaluation of hydraulic connectivity in the surface investigation stage needs to be analyze by the groundwater pressures and hydrochemical properties from the monitoring bore hole(s) equipped with a double completion or multi-packer system during the test bore hole is pumping or injecting. The hydraulic conductivities in geometric mean measured in the underground caverns are 2-3 times lower than those from the surface and furthermore the horizontal hydraulic conductivity in geometric mean is six times lower than the vertical one. To improve confidence level of the hydraulic conductivity, the orientation of test hole should be considered during the analysis of the hydraulic conductivity and the methodology of hydro-testing and interpretation should be based on the characteristics of rock mass and investigation purposes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.4
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• pp.338-346
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• 2017

Natural seaweed beds and habitat environments were investigated using quantitative and qualitative methods from May to December 2015 at 3 sites in Gangneung, Uljin, and Busan along the eastern coast of Korea. In total, 9 green, 23 brown, and 64 red algal taxa were identified. The biomass of the seaweed at Gangneung was 173.2 to $613.8wet\;wt.g/m^2$ of Dictyota divaricata, 360.8 to $520.4wet\;wt.g/m^2$ of Symphyocladia linearis, and 25.9 to $470.8wet\;wt.g/m^2$ of Undaria pinnatifida. At Uljin, these numbers were 5.5 to $256.2wet\;wt.g/m^2$ of Plocamium telfarirae and 46.8 to $241.5wet\;wt.g/m^2$ of Agarum clathratum. The biomass of Sargassum coreanum and Ecklonia cava were 388.1 to $6,972.4wet\;wt.g/m^2$ and 194.9 to $958.5wet\;wt.g/m^2$, respectively, at Busan. S. coreanum and E. cava showed higher biomass compared to other seaweed at Busan. The biomass rate represented an average of 19.2 percent of the total population, ranging from 0.0 to 55.5 percent in Gangneung. In Uljin, the average was calculated as 63.8 percent, and this figure was 48.5 percent in Busan. The percentage of barren ground averaged 46.7 percent in Gangneung and 91.1 percent in Uljin. Uljin showed the highest percentage of barren ground compared to other regions. Sea urchin density appeared to be $6.0ind./m^2$ in Gangneung, $7.0ind./m^2$ in Uljin, and $2.0ind./m^2$ in Busan, with the lowest sea urchin density being that of Busan. In conclusion, the composition of species, appearance ratio, and abundance of vegetation found were similar to previous studies, but it is thought that continuous monitoring is needed due to concerns about physical and chemical pollution caused by global warming, climate change, and coastal development.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.9
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• pp.1136-1141
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• 2008

This study was to investigate antiwrinkle effect of mugwort (Artemisia vulgaris) methanol extract in hairless mouse skin induced by UVB-irradiation. Hairless mouse were topically treated with the basic lotion alone (control), ascorbic acid (AA-0.5%, AA-1.0%, AA-2.0%, and AA-5.0%) and mugwort extract (ME-0.5%, ME-1.0%, ME-2.0%, and ME-5.0%) dissolved in a basic lotion. After topical treatment of 30 minutes, the animals were irradiated with increasing doses of UVB radiation ($60{\sim}100\;mJ/cm^2$) for 4 weeks. In our experimental condition, skin thickness of hairless mouse was significantly decreased ($12.5{\sim}21.4%$) in all ME groups compared with control group. Ra value, that is surface roughness parameter induced by skin wrinkling, was significantly decreased ($23.7{\sim}31.1%$) in ME-1.0%, 2.0% and 5.0% group compared with control group. Furthermore, Rq, Rz and Rt value were significantly decreased to $11.2{\sim}21.2%$, $19.8%{\sim}24.5%$, and $14.2%{\sim}22.7%$, respectively. Wrinkle formation of ascorbic acid treatment group as reference group was inhibited, but its effect was less than ME treatment. Matrix metalloproteinase-1 activity was significantly inhibited ($19.7{\sim}22.6%$) compared with control group and collagen content was significantly increased (about 10%) when compared with control group. These results indicate that ME could protect skin aging and wrinkle formation in hairless mouse from photo-irradiation.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.