• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.101-101
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• 2020

Soybean is known as to have a several healthy ingredients. Among them, isoflavones are effective in reducing obesity, menopausal symptom. Isoflavones consist of 12 isomers, including Aglycon, Glucoside, Malonyl glucoside, Acetyl glucoside, and are usually found in soybean seeds. The content is determined by the sum of 12 isomers, and the content value difference between the varieties is huge. In this study, we investigated the agronomic traits, 12 isomer of isoflavone content and composition for 49 soybean germplasms. This germplasms were selected from the 23,000 germplasms with the highest total content of isoflavones possessed by the National Agrobiodiversity Center. Seed samples were cultivated in experimental field located in Jeonju City on April 04, 2019. Matured seeds were harvested and portions of each seed samples were oven-dried, pulverized, and analyzed for their isoflavone compositions using HPLC-DAD. The soybean samples showed distinction in their agronomic traits, isoflavone compositions and contents. The days to flowering ranged between 38 and 69 days while the days to maturity ranged between 103 and 156 days. The seed coat color of soybean germplasms was 24 in black, 10 in yellow, 2 in green, 5 in yellowish green, 4 in green with black spot, 4 in pale yellow. The germplasm with the highest total content of isoflavones was the IT178054(1257.61±7.98 ㎍/g), but the germplasms containing the largest number of isoflavone isomers were IT274592, IT275005, both germplasms had 11 isoflavone isomers excluding Malonyl glycitin. The largest source of Aglycon, the most easily absorbed isoflavone form in the human body, was IT274592(DZ: 8.83±0.30 ㎍/g, GL: 11.14±0.81 ㎍/g, GE: 8.16±0.26 ㎍/g), while only IT274592, IT275005, IT308619 contained all three components of Aglycon. In Principal Component Analysis(PCA), the first two principal components showed more than 3.5 Eigen value and accounted for 58.2% of variability. The total content value had strong relationship with Malonyl genistin content value. Acetyl isomers had strong relationship, but Malonyl isomers were only related to isomers except Malonyl glycitin. These results will help in research on soybean varieties to enhance isoflavone ingredients.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.465-472
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• 2017

In the past, researchers mainly used the supervised learning technique of machine learning to analyze power data and investigated the identification of patterns through the data mining technique. Data analysis research, however, faces its limitations with the old data classification and analysis techniques today when the size of electric power data has increased with the possible real-time provision of data. This study thus set out to propose a clustering architecture to analyze large-sized electric power data. The clustering process proposed in the study supplements the K-means algorithm, an unsupervised learning technique, for its problems and is capable of automating the entire process from the collection of electric power data to their analysis. In the present study, power data were categorized and analyzed in total three levels, which include the row data level, clustering level, and user interface level. In addition, the investigator identified K, the ideal number of clusters, based on principal component analysis and normal distribution and proposed an altered K-means algorithm to reduce data that would be categorized as ideal points in order to increase the efficiency of clustering.

• Toxicological Research
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• v.23 no.1
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• pp.55-63
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• 2007

Diethylnitrosamine (DEN) is a nitrosamine compound that can induce a variety of liver lesions including hepatic carcinoma, forming DNA-carcinogen adducts. In the present study, microarray analyses were performed with Affymetrix Murine Genome 430A Array in order to identify the gene-expression profiles for DEN and to provide valuable information for the evaluation of potential hepatotoxicity. C57BL/6NCrj mice were orally administered once with DEN at doses of 0, 3, 7 and 20 mg/kg. Liver from each animal was removed 2, 4, 8 and 24 hrs after the administration. The histopathological analysis and serum biochemical analysis showed no significant difference in DEN-treated groups compared to control group. Conversely, the principal component analysis (PCA) profiles demonstrated that a specific normal gene expression profile in control groups differed clearly from the expression profiles of DEN-treated groups. Within groups, a little variance was found between individuals. Student's t-test on the results obtained from triplicate hybridizations was performed to identify those genes with statistically significant changes in the expression. Statistical analysis revealed that 11 genes were significantly downregulated and 28 genes were upregulated in all three animals after 2 h treatment at 20 mg/kg. The upregulated group included genes encoding Gdf15, JunD1, and Mdm2, while the genes including Sox6, Shmt2, and SIc6a6 were largely down regulated. Hierarchical clustering of gene expression also allowed the identification of functionally related clusters that encode proteins related to metabolism, and MAPK signaling pathway. Taken together, this study suggests that match with a toxicant signature can assign a putative mechanism of action to the test compound if is established a database containing response patterns to various toxic compounds.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1169-1175
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• 2011

The soil chemical properties, microbial community structures and biochemical properties of lettuce or cucumber-cultivated greenhouse soil samples were analyzed to assess soil health and characterize microbial distribution in 8 locations in Korea. Although most of chemical properties were within the soil management guidelines, the available phosphate, and the contents of exchangeable potassium and calcium were higher than those of recommended levels. In the culture-dependent analysis, 841 bacterial strains were isolated from the greenhouse soils and were identified at the genus level by 16S rRNA gene sequences analysis. The dominant bacterial genera were Bacillus (35.7%), Microbacterium (9.3%), Arthrobacter (5.7%) and Lysobacter (5.1%). The abundance of pseudomonads was highly variable depending on the soil samples. In the culture-independent analysis, soil microbial community was investigated by using phospholipid fatty acid (PLFA) method. Principal component analysis (PCA) showed that a specific grouping for microbial community structure in the greenhouse soils was not observed based on cultivated crops and investigated sites. The results revealed that the greenhouses soils examined are relatively sound managed in terms of soil chemical contents and microbial properties.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.177-198
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• 2021

Existing change detection researches have been focused on changes of land use and land cover (LULC), damaged areas, or large vegetated and water regions. On the other hands, increased temporal and spatial resolution of satellite images are strongly suggesting the feasibility of change detection of small objects such as vehicles and ships. In order to check the feasibility, this paper analyzes the performance of existing pixel-based change detection methods over small objects. We applied pixel differencing, PCA (principal component analysis) analysis, MAD (Multivariate Alteration Detection), and IR-MAD (Iteratively Reweighted-MAD) to Kompsat-3A and Google Map images taken within 10 days. We extracted ground references for changed and non-changed small objects from the images and used them for performance analysis of change detection results. Our analysis showed that MAD and IR-MAD, that are known to perform best over LULC and large areal changes, offered best performance over small object changes among the methods tested. It also showed that the spectral band with high reflectivity of the object of interest needs to be included for change analysis.

• Journal of Environmental Impact Assessment
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• v.28 no.3
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• pp.215-230
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• 2019

The objective of this research is to evaluate the water quality characteristics using the statistical analysis of major tributaries in the Han River and to provide water quality improvement plan by selecting tributaries that should be preferentially managed by river grade classification method. The major 15 tributaries in Han River watershed were monitored for discharge and water quality during January-December 2017. As a result of the correlation analysis, the river discharge has been not correlation with other water quality constituents (p>0.05) but COD and TOC were significantly correlated (r=0.957, p<0.01). The main cause of water quality fluctuation was organic pollutants and nutrients in the principal component analysis (PCA) method. The BOD, COD, TOC, TN, and TP were found to be significantly different (p<0.05) by seasonal in result of one-way ANOVA analysis. Result of river grade classification by quantitative indicators the tributaries requiring improvement of water quality were Gulpocheon, Anyangcheon, Wangsukcheon, and Tancheon which affected by wastewater treatment plant.In this research, we determined tributaries that need to improve the water quality of Han River watershed and it can be used as an important data for efficient water quality management.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.467-476
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• 2023

Schisandra chinensis (S. chinensis) is a deciduous broad-leaved cave plant belonging to the Schisandraceae family and is widely distributed in East Asia including Korea, Japan, China, and Taiwan. It has been reported that the main components contained in S. chinensis include lignan compounds and triterpenoid compounds. To distinguish the characteristics of S. chinensis by production region of Korea, a discriminant was established by performing metabolite profiling and principal component analysis, a multivariate statistical analysis technique. As a result, 16 types of triterpenoids, 9 types of lignan, and 1 type each of flavonoid, phenylpropanoid, and fatty acid were identified. In addition, through multivariate statistical analysis, it was confirmed that the four groups in Danyang, Moongyeong, Geochang, and Pyeongchang were divided, by applying the s-plot model of orthogonal partial least squares discriminant analysis. Biomarkers were identified: lanostane, cycloartane, schiartane triterpenoid, and dibenzocyclo-octadiene lignan were identified as chemical markers, respectively.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.425-435
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• 2023

Organoleptic parameters such as color, odor, and flavor influence consumer perception of drinking water quality. This study aims to evaluate the taste of the selected bottled and tap water samples using an electronic tongue (E-tongue) instead of a sensory test. Bottled and tap water's mineral components are related to the overall preference for water taste. Contrary to the sensory test, the potentiometric E-tongue method presented in this study distinguishes taste by measuring the mineral components in water, and the data obtained can be statistically analyzed. Eleven bottled water products from various brands and one tap water from I city in Korea were evaluated. The E-tongue data were statistically analyzed using multivariate statistical tools such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the E-tongue method can clearly distinguish taste discrimination in drinking water differing in water quality based on the ion-related water quality parameters. The water quality parameters that affect taste discrimination were found to be total dissolved solids (TDS), sodium (Na+), calcium (Ca²⁺), magnesium (Mg²⁺), sulfate (SO₄^2-), chloride (Cl^-), potassium (K⁺) and pH. The distance calculation of HCA was used to quantify the differences between 12 different types of drinking water. The proposed E-tongue method is a practical tool to quantitatively evaluate the differences between samples in water quality items related to the ionic components. It can be helpful in quality control of drinking water.

• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.4
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• pp.321-337
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• 2010

Long-term trends and distribution patterns of water quality were investigated in the Mokpo coastal areas of the Yellow Sea, Korea from 1979 to 2009. Water samples were collected at 5 stations and physicochemical parameters were analyzed including water temperature, salinity, suspended solids (SS), chemical oxygen demand (COD), dissolved oxygen (DO) and nutrients. Spatial distribution patterns of temperature, pH and DO were not clear among stations but the seasonal variations were distinct except ammonium. The trend analysis by principal component analysis (PCA) during 30 years revealed the significant variations in water quality in the study area. Spatial water qualities were discriminated into 3 clusters by PCA; station cluster 1, 2~4, and 5. Annual water qualities were clearly discriminated into 4 surface water clusters and 2 bottom water clusters by PCA. By this multi-variate analysis, the annual trends were summarized as the followings; water temperature, pH and COD tended to increase from late 1980's, salinity to decrease, phosphate to increase from 1994 and dissolved inorganic nitrogen to increase, due to the input of fresh water same as shown in Kyoungin coastal area, Asan coastal area, Choensoo bay and Gunsan coastal area.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.3
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• pp.203-218
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• 2011

Long-term trends and distribution patterns of water quality were investigated in the Yeoja Bay of South Sea, Korea from 1976 to 2010. Water samples were collected at 3 stations and physicochemical parameters were analyzed including water temperature, salinity, hydrogen ion concentration (pH), dissolved oxygen (DO), chemical oxygen demand (COD), suspended solids (SS) and nutrients. Spatial distribution patterns of temperature, pH and DO were not clear among stations but the seasonal variations were distinct except ammonium. The trend analysis by principal component analysis (PCA) during 31 years revealed the significant variations in water quality in the study area. Spatial water qualities were discriminated into 2 clusters by PCA; station cluster 1 and 2~3. Annual water qualities were clearly discriminated into 4 clusters by PCA. By this multi-variate analysis, the annual trends were summarized as the followings; water temperature, COD and SS tended to increase from late 1970's, decreased salinity, and increased phosphate from 1991 to 2001 and increased dissolved inorganic nitrogen. Water quality was showed by the input of fresh water same as those of Kyoungin coastal area, Asan coastal area, Choensoo bay, Gunsan coastal and Mokpo coastal area in the Yeoja Bay.