• FLOWER RESEARCH JOURNAL
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• v.19 no.4
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• pp.219-224
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• 2011

Phalaenopsis (P.) has various species, and some of them have strong fragrance. There are fragrant species such as P. bellina, P. violacea, P. schilleriana and used in breeding program for fragrant Phalaenopsis. This study was performed for establishment of fragrance analysis system using GC-MS and electronic nose in eight P. resources. We analyzed fragrant compound using the tissue of sepal, petal, column, and lip of P. '3010'. The percentage of the major compound was high in the petal and lip tissues. The main compound emitted from P. bellina was linalool (21.21%). It was possible that fragrance pattern could be analyzed among the resources using the electronic nose. Discriminant function analysis (DFA) was more useful than the principal component analysis (PCA) in statistics program. We utilized GC-MS method for the major compounds of flower from our breeding materials. This study would be useful to the fragrant analysis system for the fragrant orchid breeding in the future.

• 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.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• Journal of Nutrition and Health
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• v.54 no.3
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• pp.247-261
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• 2021

Purpose: This study was conducted to identify the association between insulin resistance and the major dietary patterns of Korean adults. Methods: This study used data from the 2015 Korea National Health and Nutrition Examination Survey. The subjects were 2,276 adults aged 19 to 64 years old. Based on the food frequency questionnaire data, 112 food items were reclassified into 30 food groups. The principal component analysis method was applied to identify major dietary patterns. We used homeostatic model assessment of insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) value as indicators of insulin resistance. The association between major dietary patterns and insulin resistance was investigated using logistic regression analysis. Results: Three major dietary patterns were identified and assigned descriptive names based on the food items with high loadings: 'healthy Korean meal pattern', 'western meal pattern', and 'white rice, alcohol, meat pattern'. As the 'white rice, alcohol, meat pattern' score increased, significant increasing trends for fasting glucose concentration and HOMA-IR and a significant decreasing trend for QUICKI were observed after adjusting for age and sex. The odds ratio of insulin resistance according to the 'healthy Korean meal pattern' and the 'western meal pattern' were not statistically significant. the 'white rice, alcohol, meat pattern' showed a significant positive association with the risk of insulin resistance after adjusting for covariates. Conclusion: These results suggest that the 'white rice, alcohol, meat pattern' is positively associated with the risk of insulin resistance. The white rice, alcohol, meat pattern was related to the high consumption of alcohol together with rice or meat. This pattern was also associated with the high intake of sodium and low intakes of vitamin C, calcium, potassium, and dietary fiber. To confirm the association, further longitudinal studies are required.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1519-1529
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• 2018

The volcanic ash can spread out over hundreds of kilometers in case of large volcanic eruption. The deposition of volcanic ash may induce damages in urban area and transportation facilities. In order to respond volcanic hazard, it is necessary to estimate efficiently the diffusion area of volcanic ash. The purpose of this study is to compare in-situ volcanic deposition and satellite images of the volcanic eruption case. In this study, we used Near-Infrared (NIR) channels 7 and 8 of Geostationary Ocean Color Imager (GOCI) images for Mt. Aso eruption in 16:40 (UTC) on October 7, 2016. To estimate deposit area clearly, we applied Principal Component Analysis (PCA) and a series of morphology filtering (Eroded, Opening, Dilation, and Closing), respectively. In addition, we compared the field data from the Japan Meteorological Agency (JMA) report about Aso volcano eruption in 2016. From the results, we could extract volcanic ash deposition area of about $380km^2$. In the traditional method, ash deposition area was estimated by human activity such as direct measurement and hearsay evidence, which are inefficient and time consuming effort. Our results inferred that satellite imagery is one of the powerful tools for surface change mapping in case of large volcanic eruption.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.208-213
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• 2021

There is a lack of studies comparing the internal quality of fruit with its external quality. However, issues of internal quality of fruit such as internal browning are important. We propose a method of classifying normal apples and internally browned apples using a near-infrared (NIR) non-destructive system. Specifically, we found the optimal wavelength and characteristics of the spectra for determining the internal browning of Fuji apples. The NIR spectra of apples were obtained in the wavelength range of 470-1150 nm. A group of normal apples and a group of internally browned apples were identified using principal component analysis (PCA), and a partial least squares regression (PLSR) analysis was performed to develop and evaluate the discriminant model. The PCA analysis revealed a clear difference between the normal and internally browned apples. From the PLSR, the correlation coefficient of the predictive model without pretreatment was determined to be 0.902 with an RMSE value of 0.157. The correlation coefficient of the predictive model with pretreatment was 0.906 with an RMSE value of 0.154. The results show that this model is suitable for classifying normal and internally browned apples and that it can be applied for the sorting and evaluation of agricultural products for internal and external defects.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.540-547
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• 2011

This study was conducted to compare classification accuracy by tree species using QuickBird imagery for pixel- and segment-based classifications that have been mostly applied to classify land covers. A total of 398 points was used as training and reference data. Based on this points, the points were classified into fourteen land cover classes: four coniferous and seven deciduous tree species in forest classes, and three non-forested classes. In pixel-based classification, three images obtained by using raw spectral values, three tasseled indices, and three components from principal component analysis were produced. For the both classification processes, the maximum likelihood method was applied. In the pixel-based classification, it was resulted that the classification accuracy with raw spectral values was better than those by the other band combinations. As resulted that, the segment-based classification with a scale factor of 50% provided the most accurate classification (overall accuracy:76% and ${\hat{k}}$ value:0.74) compared to the other scale factors and pixel-based classification.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1605-1613
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• 2020

The tidal channel is a coastal sedimentary terrain that plays the most important role in the formation and development of tidal flats, and is considered a very important index for understanding and distribution of tidal flat sedimentation/erosion terrain. The purpose of this study is to understand the changes in tidal channels by a period after the opening of the floodgate of the seawall in the reclaimed land of Sihwa Lake using KOMPSAT high-resolution multispectral satellite image data and to evaluate the applicability and efficiency of high-resolution satellite images. KOMPSAT 2 and 3 images were used for extraction of the tidal channels' lineaments in 2009, 2014, and 2019 and were applied to supervised classification method based on Principal Component Analysis (PCA), Artificial Neural Net (ANN), Matched Filtering (MF), and Spectral Angle Mapper (SAM) and band ratio techniques using Normalized Difference Water Index (NDWI) and MF/SAM. For verification, a numerical map of the National Geographic Information Service and Landsat 7 ETM+ image data were utilized. As a result, KOMPSAT data showed great agreement with the verification data compared to the Landsat 7 images for detecting a direction and distribution pattern of the tidal channels. However, it has been confirmed that there will be limitations in identifying the distribution of tidal channels' density and providing meaningful information related to the development of the sedimentary process. This research is expected to present the possibility of utilizing KOMPSAT image-based high-resolution remote exploration as a way of responding to domestic intertidal environmental issues, and to be used as basic research for providing multi-platform-image-based convergent thematic maps and topics.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.33-33
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• 2020

Watermelon (Citrullus lanatus) is a non-seasonal, economically important, cucurbit cultivated throughout the world with Asia as a continent contributing the most. As part of the effort in diversifying watermelon genetic resources in the already cultivated group, this study was devoted to providing baseline data on morphological quality traits and health-beneficial phytonutrients of watermelon germplasm collections, thereby promoting watermelon research and cultivation programs. To this end, we reported morphological traits, citrulline, and arginine levels of watermelon genetic resources obtained from the gene bank of Agrobiodiversity Center, Republic of Korea, and discussed the relationship between each other. Diverse characteristics were observed among many of the traits. But, most of the genetic resources (>90%) were either red or pink-fleshed. Korean origin fruits contained intermediate levels of soluble solid content (SSC) while The USA, Russian, Tajikistan, Turkmenistan, Taiwan, and Uruguay originated had generally the highest levels of soluble solids. The citrulline and arginine contents using HPLC method were ranged from 6.9 to 52.1 mg/g (average, 27.3 mg/g) and 1.8 to 21.3 mg/g (average, 9.8 mg/g), respectively. The citrulline content determined using Citrulline Assay Kit was ranged from 6.5 to 42.8 mg/g (average, 27.0 mg/g). Resources with high citrulline and arginine levels contained low SSC. Whereas, red- and pink-colored flesh samples had less citrulline compared to yellow and orange. In addition to the profiling of morphological characters and phytonutrients, molecular marker characterization and identification of sources of resistance to diseases and pests are recommended for a more complete diversity analysis of watermelon genetic resources.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.69-90
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• 2023

The purpose of this study is to evaluate the service attributes and consumer reactions of telemedicine apps in South Korea and visualize their differentiation by constructing positioning maps. We crawled 23,219 user reviews of 6 major telemedicine apps in Korea from the Google Play store. Topics were derived by BERTopic modeling, and sentiment scores for each topic were calculated through KoBERT sentiment analysis. As a result, five service characteristics in the application attribute category and three in the medical service category were derived. Based on this, a two-dimensional positioning map was constructed through principal component analysis. This study proposes an objective service evaluation method based on text mining, which has implications. In sum, this study combines empirical statistical methods and text mining techniques based on user review texts of telemedicine apps. It presents a system of service attribute elicitation, sentiment analysis, and product positioning. This can serve as an effective way to objectively diagnose the service quality and consumer responses of telemedicine applications.