• Journal of the Korean Society of Marine Environment & Safety
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• 제15권4호
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• pp.315-328
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• 2009

Long-term trends and distribution patterns of water quality were investigated in the Garolim coastal areas of Yellow Sea, Korea from 1998 to 2007. Water samples were collected at 3 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 were not clear among stations but the seasonal variations were distinct except pH and ammonia. The trend analysis by principal component analysis(PCA) during twenty years revealed the significant variations in water quality in the study area. Annual water qualities were clearly classified into 4 clusters by PCA; year cluster 1997, 1998 and 2000-2002, 1999 and 2003-2006/2008. By this multi-variate analysis the annual trends were summarized as follows; In recent years, salinity increased, whereas dissolved inorganic nitrogen, nitrate nitrogen and COD decreased and water quality generally continued to be in good condition in Gsrolim coastal areas without inflow of freshwater from land. Garolim coastal areas are required to be conserved continuously as important coastal areas for fisheries.

• Journal of Conservation Science
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• 제25권3호
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• pp.335-345
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• 2009

This paper presents investigations on 60 glass beads excavated from floorless tombs of Eunpyeong Newtown site to figure out composition and lead isotope ratio by SEM-EDS and TIMS, which show the difference between their compositions and Pb provenance of lead glass. The results of the composition analysis are that excavated glass are mainly divided into Potash glass($K_2O$-CaO-$SiO_2$) and Potash-lead glass($K_2O$-PbO-$SiO_2$) and the samples excavated from III-3 floorless tombs No.1005 are presumed not glass but Quartz. The transparent 9 lead glasses excavated from II-3 floorless tomb No.101 and III-3 floorless tomb No.908 seem to be manufactured by the same raw material at same site because the concentration of their compositions are well accorded with each other and deviations of them are very limited. As a result of principal component analysis(PCA), glass beads excavated are largely assort to two groups, Potash glass and Potash lead glass as well. That is, glass beads excavated from Eunpyeoung Newtown sites are quite different two types of main composition. In addition, the results of Pb provenance analysis used in lead glass confirm that most lead glass are significantly correlated with galena of northern China.

• Korean Journal of Fisheries and Aquatic Sciences
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• 제35권4호
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• pp.431-437
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• 2002

In order to understand the spatiotemporal variation of water quality, an investigation on variation characteristics of water quality was conducted at 13 stations in Yongil bay from 1990 to 1998. The salinity in summer was relatively lower than that in other seasons and it have increased from inner bay to outside of the bay gradually. However, nitrate concentration in summer was relatively higher than that in other seasons, and it was the highest, up to $65.40\%$, among dissolved inorganic nitrogens, Nitrate concentration indicates the possibility of affecting by freshwater discharges to Yongil bay. Correlation analysis showed that salinity had a significantly good correlation with nitrate. This result suggested that inflow of river had an influence on increase of nitrate. The result of Principal Component Analysis (PCA) indicated that nitrate was major factor to influence the water quality in Yongil Bay.

• Journal of Digital Convergence
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• 제12권8호
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• pp.139-146
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• 2014

We investigated the relative efficiency and statistical analysis of Kimchi-related manufactures in Jeollabuk-do for their management efficiency and improvement plans. We used data enveloped analysis (DEA) for the relative efficiency, and principal component analysis (PCA) and t-test for the statistical analysis. We analyzed 34 DMUs among 67 DMUs located in Jeollabuk-do. The results were as follows; the statistical efficiency, pure statistical efficiency, scale efficiency for 34 DMUs were 0.653, 0.761, and 0.863, respectively. The correlated component regression (CCR) showed that DMUs above efficiency 1 were 61.5% among -si (urban area), and 23.8% among -gun (rural area), respectively. However, there were not the significant differences of and BCC, CCR, and scale efficiency between urban area and rural area. This study will be useful for local industry's promotion by providing the information on Kimchi-related manufactures.

• Korean Journal of Remote Sensing
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• 제30권2호
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• pp.275-292
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• 2014

The objective of this study is to determine Tasseled Cap Transformation (TCT) coefficients for the Geostationary Ocean Color Imager (GOCI). TCT is traditional method of analyzing the characteristics of the land area from multi spectral sensor data. TCT coefficients for a new sensor must be estimated individually because of different sensor characteristics of each sensor. Although the primary objective of the GOCI is for ocean color study, one half of the scene covers land area with typical land observing channels in Visible-Near InfraRed (VNIR). The GOCI has a unique capability to acquire eight scenes per day. This advantage of high temporal resolution can be utilized for detecting daily variation of land surface. The GOCI TCT offers a great potential for application in near-real time analysis and interpretation of land cover characteristics. TCT generally represents information of "Brightness", "Greenness" and "Wetness". However, in the case of the GOCI is not able to provide "Wetness" due to lack of ShortWave InfraRed (SWIR) band. To maximize the utilization of high temporal resolution, "Wetness" should be provided. In order to obtain "Wetness", the linear regression method was used to align the GOCI Principal Component Analysis (PCA) space with the MODIS TCT space. The GOCI TCT coefficients obtained by this method have different values according to observation time due to the characteristics of geostationary earth orbit. To examine these differences, the correlation between the GOCI TCT and the MODIS TCT were compared. As a result, while the GOCI TCT coefficients of "Brightness" and "Greenness" were selected at 4h, the GOCI TCT coefficient of "Wetness" was selected at 2h. To assess the adequacy of the resulting GOCI TCT coefficients, the GOCI TCT data were compared to the MODIS TCT image and several land parameters. The land cover classification of the GOCI TCT image was expressed more precisely than the MODIS TCT image. The distribution of land cover classification of the GOCI TCT space showed meaningful results. Also, "Brightness", "Greenness", and "Wetness" of the GOCI TCT data showed a relatively high correlation with Albedo ($R^2$ = 0.75), Normalized Difference Vegetation Index (NDVI) ($R^2$ = 0.97), and Normalized Difference Moisture Index (NDMI) ($R^2$ = 0.77), respectively. These results indicate the suitability of the GOCI TCT coefficients.

• Korean Journal of Remote Sensing
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• 제29권5호
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• pp.569-579
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• 2013

In this study, land-cover classification was implemented using features extracted from multi-temporal SAR data through 3D wavelet transform and the applicability of the 3D wavelet transform as a feature extraction approach was evaluated. The feature extraction stage based on 3D wavelet transform was first carried out before the classification and the extracted features were used as input for land-cover classification. For a comparison purpose, original image data without the feature extraction stage and Principal Component Analysis (PCA) based features were also classified. Multi-temporal Radarsat-1 data acquired at Dangjin, Korea was used for this experiment and five land-cover classes including paddy fields, dry fields, forest, water, and built up areas were considered for classification. According to the discrimination capability analysis, the characteristics of dry field and forest were similar, so it was very difficult to distinguish these two classes. When using wavelet-based features, classification accuracy was generally improved except built-up class. Especially the improvement of accuracy for dry field and forest classes was achieved. This improvement may be attributed to the wavelet transform procedure decomposing multi-temporal data not only temporally but also spatially. This experiment result shows that 3D wavelet transform would be an effective tool for feature extraction from multi-temporal data although this procedure should be tested to other sensors or other areas through extensive experiments.

• Journal of Soil and Groundwater Environment
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• 제12권2호
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• pp.20-26
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• 2007

The microbial community properties of groundwater samples contaminated with landfill leachates were examined using Ecoplate including 31 sole carbon sources. The samples were KSG1-12 (leachate), KSG1-16 (treated leachate), KSG1-07 (contaminated groundwater), KSG1-08 (contaminated groundwater), and KSG1-13 (uncontaminated groundwater). Among the carbon sources used as substrates, 2-hydroxy benzoic acid, D,L-$\alpha$-glycerol phosphate, and D-malic acid were not utilized in any sample, while D-xylose, D-galacturonic acid, L-aspargine, tween 80, and L-serine were utilized in all 5 samples. The rest of substrates showed very different patterns among the samples. Average well color development (AWCD) analysis demonstrated that the potential activity on 31 substrates was in the order of KSG1-16 > KSG1-12 > KSG1-07 > KSG-08 > KSG1-13, which generally agrees with the degree of pollution, except KSG1-16. Principal component analysis (PCA) on similarity between samples showed two groups (KSG1-12, -07 and -08 vs KSG1-16 and -13), coinciding with contaminated and uncontaminated groups. Shannon index showed that the microbial diversities were similar among the samples.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제21권8호
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• pp.579-592
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• 2020

This study was designed to assess the water quality and phytoplankton community including chlorophyll a in blood cockle (Tegillarca granosa) farms in May, August and November of 2017 in the northwestern Yeoja Bay, Korea. As a result, the seasonal characteristics of water types by water temperature and salinity were clear. Nutrients were abundant in silicate throughout the season, but phosphate was scarce in spring and summer, and nitrogen sources were scarce in autumn. The species composition of phytoplankton community was a very simple distribution, and the standing crop was also very low. The annual dominant species is dominated by the diatoms, with Skeletonema costatum-ls, Nitzschia longissima in spring, Pleurrosigma normanii, Coscinodiscus gigas in summer, and N. longissima, Pseudonitschia pungens, Chaetoceros curvisetus, Eucampia zodiacus in autumn. In summer the results were different from other coastal waters of Korea. The principal component analysis(PCA) and correlation analysis showed that the characteristics of water quality and biological environments differed according to the season. Furthermore, it was determined by the supply of materials through fresh water on land, seawater congestion caused by the refueling of surface sediments with lower depth, and the balance of biological production and mineralization of organic matters in blood cockle farms.

• Current Optics and Photonics
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• 제4권1호
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• pp.31-43
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• 2020

The feasibility of the application of terahertz electromagnetic waves in the diagnosis of prostate cancer was examined. Four samples of incomplete cancerous prostatic paraffin-embedded tissues were examined using terahertz spectral imaging (TPI) system and the results obtained by comparing the absorption coefficient and refractive index of prostate tumor, normal prostate tissue and smooth muscle from one of the paraffin tissue masses examined were reported. Three hundred and sixty cases of absorption coefficients from one of the paraffin tissues examined were used as raw data to classify these three tissues using the Principal Component Analysis (PCA) and Least Squares Support Vector Machine (LS-SVM). An excellent classification with an accuracy of 92.22% in the prediction set was achieved. Using the distribution information of THz reflection signal intensity from sample surface and absorption coefficient of the sample, an attempt was made to use the TPI system to identify the boundaries of the different tissues involved (prostate tumors, normal and smooth muscles). The location of three identified regions in the terahertz images (frequency domain slice absorption coefficient imaging, 1.2 THz) were compared with those obtained from the histopathologic examination. The tissue tumor region had a distinctively visible color and could well be distinguished from other tissue regions in terahertz images. Results indicate that a THz spectroscopy imaging system can be efficiently used in conjunction with the proposed advanced computer-based mathematical analysis method to identify tumor regions in the paraffin tissue mass of prostate cancer.

• Journal of the Korean Institute of Intelligent Systems
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• 제26권5호
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• pp.416-422
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• 2016

Lots of plastics are widely used in a variety of industrial field. And the amount of plastic waste is massively produced. In the study of waste recycling, it is emerged as an important issue to prevent the waste of potentially useful resource materials as well as to reduce ecological damage. So, the recycling of plastic waste has been currently paid attention to from the view point of reuse. Existing automatic sorting system consist of near infrared ray (NIR) sensors to classify the types of plastics. But the classification of black plastics still remains a challenge. Black plastics which contains carbon black are not almost classified by NIR because of the characteristic of the light absorption of black plastics. This study is focused on handling how to identify black plastics instead of NIR. Raman spectroscopy is used to get qualitative as well as quantitative analysis of black plastics. In order to improve the performance of identification, Support Vector Machine(SVM) classifier and Principal Component Analysis(PCA) are exploited to more preferably classify some kinds of the black plastics, and to analyze the characteristic of each data.