• Proceedings of the Korea Society of Design Studies Conference
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• 2003.11a
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• pp.30-31
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• 2003

• Korean Journal of Agricultural Science
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• v.45 no.3
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• pp.447-454
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• 2018

Zearalenone (ZEN), a mycotoxin produced by Fusarium in food and feed, causes serious damage to the health of humans and livestock. Therefore, we compared the metabolomic profiles in the liver, serum, and urine of piglets fed a ZEN-contaminated diet using proton nuclear magnetic resonance ($^1H-NMR$) spectroscopy. The spectra from the three different samples, treated with ZEN concentrations of 0.8 mg/kg for 4 weeks, were aligned and identified using MATLAB. The aligned data were subjected to discriminating analysis using multivariate statistical analysis and a web server for metabolite set enrichment analysis. The ZEN-exposed groups were almost separated in the three different samples. Metabolic analysis showed that 28, 29, and 20 metabolites were profiled in the liver, serum, and urine, respectively. The discriminating analysis showed that the alanine, arginine, choline, and glucose concentrations were increased in the liver. Phenylalanine and tyrosine metabolites showed high concentrations in serum, whereas valine showed a low concentration. In addition, the formate levels were increased in the ZEN-treated urine. For the integrated analysis, glucose, lactate, taurine, glycine, alanine, glutamate, glutamine, and creatine from orthogonal partial least squares discriminant analysis (OPLS-DA) were potential compounds for the discriminating analysis. In conclusion, our findings suggest that potential biomarker compounds can provide a better understanding on how ZEN contaminated feed in swine affects the liver, serum, and urine.

• Journal of the Korean Home Economics Association
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• v.35 no.1
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• pp.263-276
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• 1997

The objectives of this study were to examine the differences in brand selection motives according to the domestic and foreign brand selection with shirts and jeans and to disclose the relationships between the brand selection and consumers' charcteristics; like their demographic variables sociability and superiority. Samples were 262 college women in Seoul Korea. The data were analyzed using t-test paired t-test χ2-test and discriminant analysis. The results of the study were the followings. 1. Purchasers of foreign brand were influenced by 'quality' 'wearing of others', 'reputation of brand', 'possibility of credit card use' more than those of domestic while purchasers of domestic brand were influenced by price. 2. Purchasers of foreign brand had more tendency to decide which brand to buy in advance than those of domestic. 3. 6 brand selection motives consumers' income and sociability contributed to discriminating the group of domestic and foreign brand purchase with shirts. The accuracy of the predicting the groups by the 8 variables was 75.95% Consumers high in sociability and income belonged to the group of foreign brand purchase. 4,6 brand selection motives consumers' age and superiority contributed to discriminating the group of domestic and foreign brand purchase with jeans. The accuracy of the predicting the groups by the 8 variables was 72.52% Consumers high in sociability and income belonged to the group of foreign brand purchase. 4. 6 brand selection motives consumer's age and superiority contributed to discriminating the group of domestic and foreign brand purchase with jeans. The accuracy of the predicting the groups by the 8 variables was 72.52% Consumers high in superiority and youngers belonged to the group of foreign brand purchase.

• Physical Therapy Korea
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• v.21 no.2
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• pp.37-47
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• 2014

Falls are common after stroke and most frequently related to loss of balance while walking. Consequently, preventing falls is one of the goals of acute, rehabilitative, and chronic stroke care. The purpose of this study was to investigate the incidence and risk factors of falls and to determine how well the Falls Efficacy Scale (FES), Timed Up and Go test (TUG), and Berg Balance Scale (BBS) could distinguish between fallers and non-fallers among stroke patients during inpatient rehabilitation. One hundred and fifteen participants with at least 3 months post-stroke and able to walk at least 3 m with or without a mono cane participated in this study. Fifty-four (47%) participants reported falling, and 15 (27.8%) had a recurrent fall. Logistic regression analysis for predicting falls showed that left hemiplegia [odds ratio (OR)=4.68] and fear of falling (OR=5.99) were strong risk factors for falls. Fallers performed worse than non-fallers on the FES, TUG, and BBS (p<.05, p<.01, respectively). In the receiver operator characteristic curve analysis, the TUG demonstrated the best discriminating ability among the three assessment tools. The cut-off score was 22 seconds on the TUG for discriminating fallers from non-fallers (sensitivity=88.9%, specificity=45.9%) and 27 seconds for discriminating recurrent fallers from single fallers and non-fallers (sensitivity=71.4%, specificity=40.2%). Results suggest that there is a need for providing fall prevention and injury minimization programs for stroke patients who record over 22 seconds on the TUG.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.154-154
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• 2017

In accordance with the opening of the Korean rice market, this study was focused on establishment of database for discriminating the Korean rice varieties and imported brand rices using DNA markers. In this study, the SNP markers were developed using single nucleotide polymorphisms between the reference sequences of japonica and them of 40 brand rices which collected in Australia, China, Thailand, United States and Vietnam. The developed SNP markers were screened to a total of 360 rices including 320 Korean rice varieties and 40 imported brand rices. We selected polymorphic markers among Korean bred rive varieties and imported brand rices. The selected markers were classified into 3 grades. The markers of A grade produced DNA band in 360 rices of 30~40%, B grades produced in 40~60%, and C grades produced bands over 60% rices. First, we tried to set-up the discriminating system using the minimum SNP markers of A grade. Especially, a set of sixteen SNP markers could identify among Korean bred rice varieties and imported brand rices. Additionally, some SNP markers like NSb for Pib gene, JJ80-T for Pi5 and YL155/YL87 for Pita which linked to resistance genes to blast were used to fingerprinting system. These markers were set-up as multiplex set for enhancing the identification efficiency among rice varieties. Finally, the selected SNP markers would be used to the fluidigm assay to construct the database for elaborate discrimination of rice varieties.

• Food Science of Animal Resources
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• v.34 no.6
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• pp.763-768
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• 2014

The identity of 45 Hanwo and 47 imported beef (non-Hanwoo) samples from USA and Australia were verified using the microsatellite (MS) marker and single nucleotide polymorphism (SNP) methods. Samples were collected from 19 supermarkets located in the city of Seoul and Gyeonggi province, South Korea, from 2009 to 2011. As a result, we obtained a 100% concordance rate between the MS and SNP methods for identifying Hanwoo and non-Hanwoo beef. The MS method presented a 95% higher individual discriminating value for Hanwoo (97.8%) than for non-Hanwoo (61.7%) beef. For further comparison of the MS and SNP methods, blood samples were collected and tested from 54 Hanwoo ${\times}$ Holstein crossbred cattle (first, second, and third generations). By using the SNP and MS methods, we correctly identified all of the first-generation crossbred cattle as non-Hanwoo; in addition, among the second and third generation crossbreds, the ratio identified as Hanwoo was 20% and 10%, respectively. The MS method used in our study provides more information, but requires sophisticated techniques during each experimental process. By contrast, the SNP method is simple and has a lower error rate. Our results suggest that the MS and SNP methods are useful for discriminating Hanwoo from non-Hanwoo breeds.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.387-400
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• 2021

The increase in number of streaming platforms and contents thereof, owing to an advancement of cloud environment, has triggered the rapid proliferation of illegally replicated contents as well as legal contents. This necessitates the development of technology capable of discriminating the copyright infringement of various contents. The Korea Copyright Protection Agency operates a video content demonstration system using AI, but it has limitations on distortions such as resolution changes. In this paper, we propose the powerful mechanism using skeleton, which is resistant against distorted video contents and capable of discriminating copyright infringement of platforms streaming illegal video contents. The proposed mechanism exploits the calculation of Hamming distance to the original video by converting collected data into binary ones for the efficient calculation. As a result of the experiment, the proposed mechanism have demonstrated the discrimination of illegally replicated video contents with an accuracy of 94.79% and average magnitude of 215KB.

• The Korea Journal of Herbology
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• v.35 no.1
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• pp.9-18
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• 2020

Objectives : We tried to establish standards for genuine by discriminating 3 kinds of pollen and spore herbs that are highly to be mixed with each other. Using an scanning electron microscope, we prepare a standard for discriminating external morphological characters of minute herbs, thereby contributing to the stable supply of genuine herbal medicines. Methods : Standard samples were confirmed by literature review on external morphological characteristics of original plants and herbal medicines, and collection and identification of original plants. The herbal medicines on the market were purchased and classified with using naked eye observation and magnifier. Finally, micromorphological identifications were conducted using an scanning electron microscope. Results : 1. Pini Pollen was clearly distinguished by its relatively medium size and a pollen grain with two swollen reticulate sacci at both ends. The verrucate ornamentation on the exine surface of the corpus and a sunken leptoma germ pore may be used as a discrimination criteria. 2. Typhae Pollen was distinguished by its relatively small size and a saccus on the end of a pollen grain. Reticulate ornamentation of exine surface of the corpus, and a slightly clear ulcerate germ pore can be used as a discrimination criteria. 3. Lygodii Spora was distinguished by its relatively large triangular-ovate shape and trichotomous fissure. Verrucate-tuberculate ornamentation of exine surface and trilete aperture could be used as a discrimination criteria. Conclusion : These results indicate that the use of electron microscopy is very effective for discriminating the external morphology of minute herbal medicines.

• Animal Bioscience
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• v.37 no.5
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• pp.918-928
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• 2024

Objective: The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. Methods: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. Results: The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R² >0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). Conclusion: A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.415-424
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• 2021

Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). Materials and Methods: We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power. Results: The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively. Conclusion: NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.