Journal of Korean Society of Environmental Engineers
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v.29
no.5
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pp.521-527
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2007
To investigate the relationship between PCB sources and concentration level in soil, PCBs concentration of 8 soil samples around Shiwa industrial complex were measured. The concentration of PCBs in soil samples were ranged from 2.43 to 274 ng/g dry (0.116 to 60.5 pg WHO-TEQ/g dry) md off-gas were ranged from 48.6 to $2872ng/m^3(0.00150\sim15.2ng\;WHO-TEQ/m^3)$; these are similar levels with results of previous study in Korea. The homologue patterns in soil samples were varied from sample to sample, but isomer patterns were very similar with each other. The two principal components were extracted by Principal Component Analysis(PCA) of 8 soil samples and cumulative factor loading was 95.7%. As the result of PCA, it could be expected that PCBs in soil samples of this study were more affected by PCB products than combustion process and mostly affected by already-known sources.
This study was conducted in order to determine changes in the growth responses of Quercus serrata and Q. aliena which are potential natural vegetation of riverine in Korea under four light gradients within ambient and elevated $CO_2$ concentration and temperature levels. As a result, growth responses of two species were affected by light factor. Aboveground, belowground, plant biomass and root:shoot ratio of two species grown under the control and treatment were increased in the highest light level. Plant biomass and root:shoot ratio of two oak species were not significantly affected by elevated $CO_2$ and temperature, while aboveground biomass of them was lower in the treatment than control. Belowground biomass of Q. serrata was lower in the treatment than control under the gradients that are more than 70% of light level. As light intensity increases, elevated $CO_2$ and temperature promoted root growth of two oak species but had a negative effect on aboveground growth. According to the principal component analysis(PCA), two oak species were discriminatively arranged based on factor 1 and 2. Also, the reactions towards the ambient and elevated $CO_2$ and temperature were slightly different. It is clearly visible that all features relied on axis 1 and axis II are highly correlated with most variables except for stem and shoot length.
Journal of the Institute of Electronics Engineers of Korea SP
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v.42
no.1
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pp.17-23
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2005
In this paper, we propose face recognition method using embedded data in super states segmentalized that is specification region exist to face region, hair, forehead, eyes, ears, nose, mouth, and chin. Proposed method defines super states that is specification area in normalized size (92×112), and embedded data that is extract internal factor in super states segmentalized achieve face recognition by PCA algorithm. Proposed method can receive specification data that is less in proposed image's size (92×112) because do orignal image to learn embedded data not to do all loaming. And Showed face recognition rate in image of 92×112 size averagely 99.05%, step 1 99.05%, step 2 98.93%, step 3 98.54%, step 4 97.85%. Therefore, method that is proposed through an experiment showed that the processing speed improves as well as reduce existing face image's information.
This study was carried out to investigate aroma patterns of Hanwoo (Korean cattle) beef using electronic nose during refrigerated storage, and to compare these results with chemical quality (pH, TBARS). The M. longissimus muscle from Hanwoo carcasses after 24 hrs postmortem was obtained and stored at 5${\pm}$1$^{\circ}C$ for 7 days. Sensitivity (dR/RO) values among electronic nose data were changed differently during refrigerated storage, and showed significant difference on the 7th day of storage (p<0.01). The dR/RO from SY/G, SY/AA, SY/Gh, SY/gCTl, SY/gCT decreased but those from SY/LG, T30/1, P10/1, P10/2, P40/1, T70/2, PA2 increased during storage for 7 days. Mapping these data using PCA (principal component analysis) showed that the 1st day data were present in the middle of the right side, the 3rd day data were present in bottom part of this area and the 7th day data spread out more widely on the left side. In case of DFA (discriminant factor analysis), the flock clustered round and located in different side clearly comparing with PCA plot. In analysis of correlation coefficients among electronic nose data and chemical quality data, there was significant correlation among sensor data (p<0.001). But pH and TBARS were not significantly correlated with electronic nose data. Consequently, PCA and DFA plot by electronic nose data showed difference during refrigerated storage and there were significant correlations among sensors. Therefore it will be possible to detect separate aroma patterns of Hanwoo beef using electronic nose.
Jung, Kang-Young;Ahn, Jung-Min;Lee, Kyung-Lak;Kim, Shin;Yu, Jae-Jeong;Cheon, Se-Uk;Lee, In Jung
Journal of Environmental Science International
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v.24
no.6
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pp.743-753
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2015
In this study, it is an object to develop a regression model for the estimation of TOC (total organic carbon) concentration using investigated data for three years from 2010 to 2012 in the Gam Stream unit watershed, and applied in 2009 to verify the applicability of the regression model. TOC and $COD_{Mn}$ (chemical oxygen demand) were appeared to be derived the highest correlation. TOC was significantly correlated with 5 variables including BOD (biological oxygen demand), discharge, SS (suspended solids), Chl-a (chlorophyll a) and TP (total phosphorus) of p<0.01. As a result of PCA (principal component analysis) and FA (factor analysis), COD, TOC, SS, discharge, BOD and TP have been classified as a first factor. TOCe concentration was estimated using the model developed as an independent variable $BOD_5$ and $COD_{Mn}$. R squared value between TOC and measurement TOC is 0.745 and 0.822, respectively. The independent variable were added step by step while removing lower importance variable. Based on the developed optimal model, R squared value between measurement value and estimation value for TOC was 0.852. It was found that multiple independent variables might be a better the estimation of TOC concentration using the regression model equation(in a given sites).
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.3112-3112
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2001
Near-Infrared Spectroscopy (NIRS) was investigated aiming at the identification of falsified drugs. The identification is based on comparison of the NIR spectrum of a sample with a typical spectra of an authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Two spectrophotometers (Brimrose - Luminar 2000 and 2030), based on acoustic-optical filter (AOTF) technology, sharing the same controlling computer, software (Brimrose - Snap 2.03) and the data acquisition electronics, were employed. The Luminar 2000 scans the range 850 1800 nm and was employed for transmitance/absorbance measurements of liquids with a transflectance optical bundle probe with total optical path of 5 mm and a circular area of 0.5 $\textrm{cm}^2$. Model 2030 scans the rage 1100 2400 nm and was employed for reflectance measurement of solids drugs. 300 spectra, acquired in about 20 s, were averaged for each sample. Chemometric treatment of the spectral data, modelling and classification were performed by using the Unscrambler 7.5 software (CAMO Norway). This package provides the Principal Component Analysis (PCA) and SIMCA algorithms, used for modelling and classification, respectively. Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to accomplish the diversity of physico-chemical characteristics found among commercial products. Parameters which could affect the spectra of a given drug (especially if presented as solid tablets) were investigated and the results showed that the first derivative can minimize spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The effect of ambient humidity and temperature were also investigated. The first factor needs to be controlled for model construction because the ambient humidity can cause spectral alterations that should cause the wrong classification of a real drug if the factor is not considered by the model.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
/
pp.1281-1281
/
2001
Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.
Park, Jeonghyeon;Yang, Jiwon;Choi, Wonei;Kim, Serin;Lee, Hanlim
Korean Journal of Remote Sensing
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v.38
no.2
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pp.189-198
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2022
In this present study, we investigated the effect of the offset correction factor calculation method on the sulfur dioxide (SO2) column density in the SO2 retrieval algorithm of the Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020. The GEMS operational SO2 retrieval algorithm is the Differential Optical Absorption Spectroscopy (DOAS) - Principal Component Analysis (PCA) Hybrid algorithm. In the GEMS Hybrid algorithm, the offset correction process is essential to correct the absorption effect of ozone appearing in the SO2 slant column density (SCD) obtained after spectral fitting using DOAS. Since the SO2 column density may depend on the conditions for calculating the offset correction factor, it is necessary to apply an appropriate offset correction value. In this present study, the offset correction values were calculated for days with many cloud pixels and few cloud pixels, respectively. And a comparison of the SO2 column density retrieved by applying each offset correction factor to the GEMS operational SO2 retrieval algorithm was performed. When the offset correction value was calculated using radiance data of GEMS on a day with many cloud pixels was used, the standard deviation of the SO2 column density around India and the Korean Peninsula, which are the edges of the GEMS observation area, was 1.27 DU, and 0.58 DU, respectively. And around Hong Kong, where there were many cloud pixels, the SO2 standard deviation was 0.77 DU. On the other hand, when the offset correction value calculated using the GEMS data on the day with few cloud pixels was used, the standard deviation of the SO2 column density slightly decreased around India (0.72 DU), Korean Peninsula (0.38 DU), and Hong Kong (0.44 DU). We found that the SO2 retrieval was relatively stable compared to the SO2 retrieval case using the offset correction value on the day with many cloud pixels. Accordingly, to minimize the uncertainty of the GEMS SO2 retrieval algorithm and to obtain a stable retrieval, it is necessary to calculate the offset correction factor under appropriate conditions.
Background: The aim of this work was the comparison between the carcass and the meat ewes of the regional Traditional market and the Islamic religious (Halal) market. Methods: Thirty and 20 at the end of career traditional market and Halal market ewes were slaughtered following the EC (European Council, 2009) animal welfare guidelines. Live weight of ewes was taken and dressing percentage of carcasses was calculated. On every carcass zoometric measurement and the evaluation trough the EU grid rules were performed. On the Musculus longissimus thoracis of 12 Traditional market carcasses and 11 Halal market carcasses the physical-chemical and nutritional analysis were performed. Consumer tests for liking meat ewe were performed in order to find consumer's preference level for Traditional and Halal markets ewe meat. Considering as fixed factor the ewe meat market (Traditional and Halal), results were submitted to oneway Analysis of Variance (ANOVA) and to Principal Component Analysis (PCA). Results: The Halal market ewes have shown lower dressing percentages ($42.91{\pm}0.82$ vs $46.42{\pm}0.69$) and lower conformation score ($4.5{\pm}0.5$ vs $7.8{\pm}0.4$). The Halal market meat showed higher cooking loss in oven ($37.83{\pm}1.20$ vs $32.03{\pm}1.15%$), lesser Chroma value ($18.63{\pm}0.70$ vs $21.84{\pm}0.67$), and lesser Hue angle value ($0.26{\pm}0.02$ vs $0.34{\pm}0.02$). This product had also lower fat percentage ($4.2{\pm}0.4$ vs $7.09{\pm}0.4$). The traditional market meat had higher percentage in monounsatured fatty acids (MUFA) ($43.84{\pm}1.05$ vs $38.22{\pm}1.10$), while the Halal market meat had higher percentage in ${\omega}3$ poliunsatured fatty acids (PUFA) ($5.04{\pm}0.42$ vs $3.60{\pm}0.40$). The consumer test showed as the ewe meat was appreciate by the consumers. Conclusions: Both meat typologies have shown good nutritional characteristics. The traditional market meat had higher MUFA composition, and a better MUFA/satured fatty acids (SFA) ratio, while the Halal market meat had higher PUFA composition. These results were also supported by the PCA. The consumers preferred the traditional market meat.
In order to investigate effects of elevated $CO_2$ concentration and temperature on the ecological niche of Quercus serrata in Korea. We divided experimental condition in the greenhouse that are control (ambient condition) and treatment with elevated $CO_2$ (approximately 1.6 above than control) and increased air temperature (approximately $2.2^{\circ}C$ above than control). We measured twenty kind characters of seedlings and calculated the ecological niche breadth. As a result, the ecological niche breadth, treatment was widened in the light gradient than the control, was narrowed in the moisture and nutrient gradient. This is may be predicted when the global warming progress, Q. serrata is increases resistance to light environment, and decrease resistance to moisture and nutrient environment. According to the principal component analysis (PCA), control and treatment were arranged based on factor 1 and 2 in each environment gradients. Ecological response is involved variety characters. Among them, indicating that Characters of production is involved in many a parts.
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