• Horticultural Science & Technology
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• v.32 no.1
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• pp.105-114
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• 2014

We established a high throughput screening system of African yam tuber lines which contain high contents of total carotenoids, flavonoids, and phenolic compounds using ultraviolet-visible (UV-VIS) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. The total carotenoids contents from 62 African yam tubers varied from 0.01 to $0.91{\mu}g{\cdot}g^{-1}$ dry weight (wt). The total flavonoids and phenolic compounds also varied from 12.9 to $229{\mu}g{\cdot}g^{-1}$ and from 0.29 to $5.2mg{\cdot}g^{-1}$dry wt. FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate the 62 African yam tuber lines into three separate clusters corresponding to their taxonomic relationship. The quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds from African yam tuber lines were established using partial least square regression algorithm from FT-IR spectra. The regression coefficients ($R^2$) between predicted values and estimated values of total carotenoids, flavonoids and phenolic compounds were 0.83, 0.86, and 0.72, respectively. These results showed that quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from FT-IR spectra of African yam tuber lines with higher accuracy. Therefore we suggested that quantitative prediction system established in this study could be applied as a rapid selection tool for high yielding African yam lines.

• Journal of Plant Biotechnology
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• v.45 no.3
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• pp.250-256
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• 2018

To determine whether metabolite fingerprinting for whole cell extracts based on Fourier transform infrared spectroscopy (FT-IR) can be used to discriminate and compare metabolic equivalence, standard medicinal parts of Cynanchum wilfordii (Maxim.) Hemsl. and their adventitious roots were subjected to FT-IR. The principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) from FT-IR spectral data showed that whole metabolic pattern from the adventitious root of Cynanchum wilfordii was highly similar to its standard medicinal parts. These results clearly showed that mass proliferation of adventitious roots could be applied for the novel supply of standard medicinal parts of medicinal plants. Furthermore, FT-IR spectroscopy combined with multivariate analysis established in this study could be applied as an alternative tool for discriminating of whole metabolic equivalence from standard medicinal parts. Thus, it is proposed that these metabolic discrimination systems from the adventitious root of Cynanchum wilfordii could be applied for metabolic standardization of in vitro grown Cynanchum wilfordii.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.81-89
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• 2004

In this paper, we compare face recognition rate by PCA algorithm using distance change and embedded data being input left side and right side image in stereo images. The proposed method detects face region from RGB color space to YCbCr color space. Also, The extracted face image's scale up/down according to distance change and extracts more robust face region. The proposed method through an experiment could establish standard distance (100cm) in distance about 30∼200cm, and get 99.05% (100cm) as an average recognition result by scale change. The definition of super state is specification region in normalized size (92${\times}$112), and the embedded data extracts the inner factor of defined super state, achieved face recognition through PCA algorithm. The orignal images can receive specification data in limited image's size (92${\times}$112) because embedded data to do learning not that do all learning, in image of 92${\times}$112 size averagely 99.05%, shows face recognition rate of test 1 99.05%, test 2 98.93%, test 3 98.54%, test 4 97.85%. Therefore, the proposed method through an experiment showed that if apply distance change rate could get high recognition rate, and the processing speed improved as well as reduce face information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.383-386
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• 2005

CCW(China Coastal Water) is different each year. It appears clearly from June to October in the neighboring sea of Jeju island. It appears in June, and it's strong most in August, after tat disappears in October. CCW appeared clearly at 1996 and 1999 during investigation period(1995 to 1999). SLA and SST appear annual variations(about 365day), semi-annual variations(about 180day) from power spectral density. After PCA(Principal component analysis), it's different. PCA of SLA shows 43day variations and PCA of SST shows 259day variations. SLA and SST appear annual variation, semi-annual variation and seasonal variation from power spectral density. SLA appeared that summer and fall of 1996 and 1999 is higher than other years. It seem to be being the relationship which is close with the severe rain strom. Temperature distribution of sea surface according to season is different, but clearly water temperature boundary divides this area into Yellow Sea and East China Sea. It considered that CCW follow according to boundary of temperature. The variation which it follows at time of SLA and SST is faster about one month to three month at Yangtz.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.56-68
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• 2022

In this paper, we propose a compression method for multi-resolution feature maps for VCM. The proposed compression method removes the redundancy between the channels and resolution levels of the multi-resolution feature map through PCA-based transformation. According to each characteristic, the basis vectors and mean vector used for transformation, and the transformation coefficient obtained through the transformation are compressed using a VVC-based coder and DeepCABAC. In order to evaluate performance of the proposed method, the object detection performance was measured for the OpenImageV6 and COCO 2017 validation set, and the BD-rate of MPEG-VCM anchor and feature map compression anchor proposed in this paper was compared using bpp and mAP. As a result of the experiment, the proposed method shows a 25.71% BD-rate performance improvement compared to feature map compression anchor in OpenImageV6. Furthermore, for large objects of the COCO 2017 validation set, the BD-rate performance is improved by up to 43.72% compared to the MPEG-VCM anchor.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.4
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• pp.297-313
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• 2009

Long-term trends and distribution patterns of water quality were investigated in the Gunsan coastal areas of Yellow Sea, Korea from 1972 to 2006. Water samples were collected at 6 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, DO and SS were not clear among stations but the seasonal variations were distinct except COD and SS. The trend analysis by principal component analysis(PCA) during 24 years revealed the significant variations in water quality in the study area. Spatial water qualities were clearly classified into 3 clusters by PCA; station cluster 1, 2~4, and 5~6. Annual water qualities were clearly classified into 4 surface water clusters and 5 bottom water clusters by PCA. By this multi-variate analysis. The annual trends were summarized as follows; Salinity, pH and DO tended to increase since late 1970's, COD to increase since 1987, and SS to decrease and nutrients to increase in Gunsan coastal waters due to the input of fresh water from land same as in Kyoungin coastal area, Asan coastal area and Choensoo bay.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.1
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• pp.47-52
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• 2010

Physical, chemical and biological properties of soils and cadmium(Cd) content of Artemisia princeps var. orientalis collected from 10 metalliferous mines were analysed. Cd contents of unplanted soils and rhizosphere soils were not significantly different(p < 0.05), and mean values were 5.92 and 5.91 mg/kg, respectively. In addition, Cd content of rhizosphere soils were correlated with Cd content of Artemisia princeps (p < 0.05, ${R^2}_{shoot}$ = 0.3120, ${R^2}_{root}$ = 0.4177). Minimum data set(MDS) of soil quality parameters for statistical assessment of Cd uptake was established by principal component analysis, and it was identified as organic matter(OM), dehydrogenase activity(DHA), pH, exchangeable Mg. According to multiple regression analysis using the MDS, coefficients of determination ($R^2$) for Cd uptake of shoot and root of Artemisia princeps were found to be 0.3418 and 0.5121, respectively. This suggests that statistical soil quality assessment using the MDS seems a useful tool to interpret heavy metal uptake of plant.

• Food Engineering Progress
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• v.23 no.1
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• pp.62-68
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• 2019

In this study, the physical and sensorial properties of the meat analog were studied for the purpose of improving sensory preference and mimicking animal meat. The meat analog was made with different types of liquid materials such as oil, water, lecithin, polysorbate 80, or the emulsion of these components. At the aspect of density, the sample mixed with oil was higher than the sample mixed with water. Cooking loss value was higher at the sample with water than the sample with oil and this was the result opposite to the liquid holding capacity analysis. Also, texture profile analysis result showed that the samples with medium chain triglycerides (MCT) oil only showed the highest values in all attributes except for adhesiveness. Principal component analysis was carried out to analyze sensorial properties and it showed that the overall acceptance was high when the juiciness and softness increased. This result was highly related with the addition of emulsion. Therefore, emulsion technology can be a good candidate for improving the quality of meat analog and for mimicking the taste of animal meat.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.562-569
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• 2019

Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.

• Economic and Environmental Geology
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• v.53 no.5
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• pp.619-629
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• 2020

The National Groundwater Monitoring Network (NGMN) in South Korea has been implemented in alluvial/ bedrock aquifers for efficient management of groundwater resources. In this study, aquifer types were reclassified with unconfined and confined aquifers based on water-level fluctuation and water quality characteristics. Principal component analysis (PCA) of water-level data from paired monitoring wells of alluvial/bedrock aquifers results in the principal components of both aquifers showing similar water-level fluctuation pattern. There was no significant difference in the rate of water-level rises responding to precipitations and in the NO₃-N concentrations between the alluvial and bedrock aquifers. In contrast, in the results classified with the hydrogeological type, the principal components of water level were different between unconfined and confined conditions. The water-level rises to precipitation events were estimated to be 4.6 (R²=0.8) in the unconfined and 2.1 (R²=0.4) in the confined aquifers, respectively, indicating less impact of precipitation recharge to the confined aquifer. The confined aquifers have the average NO₃-N concentration below 3 mg/L, implying the natural background level protected from the sources at surface. In summary, reclassification of aquifers into hydrogeological types clearly shows the differences between unconfined and confined aquifers in the water-level fluctuation pattern and NO₃-N concentrations. The hydrogeologic condition of aquifer could improve groundwater resource management by providing critical information on groundwater quantity through recharge estimation and quality for protection from potential contamination sources.