• Journal of Applied Biological Chemistry
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• v.58 no.4
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• pp.345-348
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• 2015

Dried Rehmannia Radix Preparat, produced in different geographic origins of Korea and China, were investigated for the trace element contents using X-ray fluorescence spectrometry. When the estimated data for 35 kind of elements including K, P, S, Cl, Si, Al, Fe, Sn, etc on 143 samples were analyzed by canonical discrimination technique, the average classification correct rate was 92.3% and the significance was less than 0.0001. In case of reducing the number of elements for statistic analysis from 35 to 8 and to 3, the correct rates were also reduced to 88.1% and to 84.6%. The correct rate for Chinese samples ranged from 94.6-96.0%, while those for Korean ranged from 72.5-89.9%.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.576-593
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• 2021

In this study, in order to investigate the factors that affect the percentage of correct answers and the degree of discrimination of the TOEIC test, a regression analysis was performed using corpus indicators that influence correct answer rate and the degree of discrimination for each part derived from the item analysis. The basic calculation word_length, consistency index LSA_overlap_adjacent_sentences, lexical diversity MTLD_VOCD, conjunction All_logical_causal_connectives_incidence, situational model casual_particles_causal_verbs_Ratio, syntactic complexity Left_embeddedness, and syntactic pattern density Infinitive_density were found to have negative effects. These factors that lower the correct answer rate can be utilized when setting learning goals. Vocabulary diversity index MTLD_VOCD, conjunction Additive_connectives_incidence, syntactic pattern density Infinitive_density, and lexical information person1_2_pronoun_incidence were found to have a positive effect. Factors influencing the increase in discrimination may provide important information for developing a learning program.

• Food Science of Animal Resources
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• v.30 no.6
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• pp.918-922
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• 2010

Due to the large amount of beef imported from the USA to Korea, Korean consumers have become increasingly interested in the country of origin since it can affect market prices. Previously, Bos indicus and Bos taurus-specific markers were developed for the purpose of cattle breed identification, specifically discrimination of Australian beef. In this study, six SNP markers derived from Illumina 50K bovine SNP chip data were used for the discrimination between Korean cattle (Hanwoo) and imported beef from USA. PCR-RFLP genotyping methods were also developed, which indicates that these markers can be applied relatively easily compared to other markers. Taking into account a discrimination rate of 55% based on MC1R marker between Hanwoo and imported beef from USA, two additional markers, SNPs 23803 and 34776, were ideal and resulted in probability of identification of 0.942 and probability of misjudgment of 0.03. Therefore, the markers developed in this study can greatly contribute to the correct discrimination between beef from USA and Hanwoo beef.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1045-1046
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• 2015

When using the Support Vector Machine in the online signature verification, SVM kernel function should be chosen to use non-linear SVM and the constant parameters in the kernel functions should be adjusted to appropriate values to reduce the error rate of signature verification. Non-linear SVM which is built on a strong mathematical basis shows better performance of classification with the higher discrimination power. However, choosing the kernel function and adjusting constant parameter values depend on the heuristics of the problem domain. In the signature verification, this paper deals with the problems of selecting the correct kernel function and constant parameters' values, and shows the kernel function and coefficient parameter's values with the minimum error rate. As a result of this research, we expect the average error rate to be less than 1%.

• Journal of Korean Biological Nursing Science
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• v.20 no.1
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• pp.11-19
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• 2018

Purpose: The purposes of this study were to perform items analysis using the classical test theory (CTT) and the item response theory (IRT), and to establish the validity and reliability of the Korean version of pressure ulcer prevention knowledge. Methods: The 26-item pressure ulcer prevention knowledge instrument was translated into Korean, and the item analysis of the 22 items having an adequate content validity index (CVI), was conducted. A total of 240 registered nurses in 2 university hospitals completed the questionnaire. Each item was analyzed applying CTT and IRT according to 2-parameter logistic model. Response alternatives quality, item difficulty and item discrimination were evaluated. For testing validity and reliability, Pearson correlation coefficient and Kuder Richardson-20 (KR-20) were used. Results: Scale CVI was .90 (Item-CVI range= .75-1.00). The total correct answer rate for this study population was relatively low as 52.5%. The quality of response alternatives was found to be relatively good (range= .02-.83). The item difficulty of the questions ranged form .10 to .86 according to CTT and -12.19 to 29.92 according to the IRT. This instrument had 12-low, 2-medium and 8-high item difficulty applying IRT. The values for the item discrimination ranged .04-.57 applying CTT and .00-1.47 applying IRT. And overall internal consistency (KR-20) was .62 and stability (test-retest) was .82. Conclusion: The instrument had relatively weak construct validity, item discrimination according to the IRT. Therefore, the cautious usage of a Korean version of this instrument would be recommended for discrimination because there are so many attractive response alternatives and low internal consistency.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1729-1740
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• 2017

This paper describes a vision-based method that effectively recognize a traffic light. The method consists of two steps of traffic light detection and discrimination. Many related studies have used color information to detect traffic light, but color information is not robust to the varying illumination environment. This paper proposes a new method of traffic light detection based on intensity and saturation. When a traffic light is turned on, the light region usually shows values with high saturation and high intensity. However, when the light region is oversaturated, the region shows values of low saturation and high intensity. So this study proposes a method to be able to detect a traffic light under these conditions. After detecting a traffic light, it estimates the size of the body region including the traffic light and extracts the body region. The body region is compared with five models which represent specific traffic signals, then the region is discriminated as one of the five models or rejected as none of them. Experimental results show the performance of traffic light detection reporting the precision of 97.2%, the recall of 95.8%, and correct recognition rate of 94.3%. These results shows that the proposed method is effective.

• Journal of Korean Society of Forest Science
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• v.88 no.2
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• pp.240-248
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• 1999

On the basis of data obtained from five forest roads collapsed due to a heavy rainfall of 1995 in Chunchon, Kangwon-do, this study was carried out to evaluate and predict the fill slope failure of forest roads with four factors of forest road structure and those of location condition by using Quantification theory(II). The results were summarized as follows ; In the structure factors of forest road, the fill slope failure was mainly occurred in longitudinal gradients less than $2^{\circ}$ or more than $4^{\circ}$, distance of surface-flow longer than 80m, fill slope length greater than 6m, and fill slope gradients steeper than $35^{\circ}$. In the factors of location condition, the failure was mainly occurred in ridge portion of road position, weathered rock and soft rock of constituent material, slope gradients in the range from $35^{\circ}$ to $45^{\circ}$, and concave and convex of longitudinal slope forms. The priority order for factors influencing on fill slope failure was ranked by fill slope length, constituent material, road position, and so on. And the rate of correct discrimination by analysis of fill slope failure was estimated at the high prediction of 86.5%.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.235-245
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• 2012

Logistic discrimination is an useful statistical technique for quantitative analysis of financial service industry. Especially it is not only easy to be implemented, but also has good classification rate. Generalized additive model is useful for credit scoring since it has the same advantages of logistic discrimination as well as accounting ability for the nonlinear effects of the explanatory variables. It may, however, need too many additive terms in the model when the number of explanatory variables is very large and there may exist dependencies among the variables. Mixtures of factor analyzers can be used for dimension reduction of high-dimensional feature. This study proposes to use the low-dimensional factor scores of mixtures of factor analyzers as the new features in the generalized additive model. Its application is demonstrated in the classification of some real credit scoring data. The comparison of correct classification rates of competing techniques shows the superiority of the generalized additive model using factor scores.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.595-602
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• 2007

This paper proposes a method that discriminates signal peptide and predicts the cleavage site of the secretory proteins cleaved by the signal peptidase I. The preprocessing stage uses hydrophobicity scales of amino acids in order to predict the presence of signal sequence and the cleavage site. The preprocessing enhances the performance of the prediction method by eliminating the non-secretory proteins in the early stage of prediction. for the effective use of support vector machine for the signal sequence prediction, the biologically relevant distance between the amino acid sequences is defined by using the hydrophobicity and substitution matrix; the hydrophobicity can be used to Predict the location of amino acid in a cell and the substitution matrix represents the evolutionary relationships of amino acids. The proposed method showed 98.9% discrimination rates from signal sequences and 88% correct rate of the cleavage site prediction on Swiss-Prot release 50 protein database using the 5-fold-cross-validation. In the comparison tests, the proposed method has performed significantly better than other prediction methods.

• Journal of Preventive Medicine and Public Health
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• v.38 no.3
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• pp.276-282
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• 2005

Objectives : To evaluate the predictive validity of three scoring systems; the acute physiology and chronic health evaluation(APACHE) III, simplified acute physiology score(SAPS) II, and mortality probability model(MPM) II systems in critically ill patients. Methods : A concurrent and retrospective study conducted by collecting data on consecutive patients admitted to the intensive care unit(ICU) including surgical, medical and coronary care unit between January 1, 2004, and March 31, 2004. Data were collected on 348 patients consecutively admitted to the ICU(aged 16 years or older, no transfer, ICU stay at least 8 hours). Three models were analyzed using logistic regression. Discrimination was assessed using receiver operating characteristic(ROC) curves, sensitivity, specificity, and correct classification rate. Calibration was assessed using the Lemeshow-Hosmer goodness of fit H-statistic. Results : For the APACHE III, SAPS II and MPM II systems, the area under the receiver operating characterist ic(ROC) curves were 0.981, 0.978, and 0.941 respectively. With a predicted risk of 0.5, the sensitivities for the APACHE III, SAPS II, and MPM II systems were 81.1, 79.2 and 71.7%, the specificities 98.3, 98.6, and 98.3%, and the correct classification rates 95.7, 95.7, and 94.3%, respectively. The SAPS II and APACHE III systems showed good calibrations(chi-squared H=2.5838 p=0.9577 for SAPS II, and chi-squared H=4.3761 p=0.8217 for APACHE III). Conclusions : The APACHE III and SAPS II systems have excellent powers of mortality prediction, and calibration, and can be useful tools for the quality assessment of intensive care units(ICUs).