• Tuberculosis and Respiratory Diseases
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• v.70 no.6
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• pp.490-497
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• 2011

Background: It is difficult but important to differentiate between bacterial and viral infections, especially for respiratory infections. Hence, there is an ongoing need for sensitive and specific markers of bacterial infections. We investigated novel biomarkers for discriminating community acquired bacterial pneumonia from 2009 H1N1 influenza A infections. Methods: This was a prospective, observational study of patients with community acquired bacterial pneumonia, 2009 H1N1 Influenza A infection, and healthy controls. Serum samples were obtained on the initial visit to the hospital and stored at $-80^{\circ}C$. We evaluated CRP (C-reactive protein), PCT (procalcitonin), LBP (lipopolysaccharide-binding protein) and copeptin. These analytes were all evaluated retrospectively except CRP. Receiver operating characteristic curve (ROC) analyses were performed on the resulting data. Results: Enrolled patients included 27 with community acquired bacterial pneumonia, 20 with 2009 H1N1 Influenza A infection, and 26 who were healthy controls. In an ROC analysis for discriminating community acquired bacterial pneumonia from 2009 H1N1 influenza A infection, areas under the curve (AUCs) were 0.799 for CRP (95% Confidence interval [CI], 0.664~0.934), 0.753 for PCT (95% CI, 0.613~0.892) and 0.684 for LBP (95% CI, 0.531~0.837). Copeptin was not different among the three groups. Conclusion: These findings suggest that serum CRP, PCT and LBP can assist physicians in discriminating community acquired bacterial pneumonia from 2009 H1N1 influenza A infection.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.112-120
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• 2009

Face membership authentication is to decide whether an incoming person is an enrolled member or not using face recognition, and basically belongs to two-class classification where support vector machine (SVM) has been successfully applied. The previous SVMs used for face membership authentication have been trained and tested using image feature vectors extracted from member face images of each class (enrolled class and unenrolled class). The SVM so trained using image feature vectors extracted from members in the training set may not achieve robust performance in the testing environments where configuration and size of each class can change dynamically due to member's joining or withdrawal as well as where testing face images have different illumination, pose, or facial expression from those in the training set. In this paper, we propose an effective class discriminating feature vector-based SVM for robust face membership authentication. The adopted features for training and testing the proposed SVM are chosen so as to reflect the capability of discriminating well between the enrolled class and the unenrolled class. Thus, the proposed SVM trained by the adopted class discriminating feature vectors is less affected by the change in membership and variations in illumination, pose, and facial expression of face images. Through experiments, it is shown that the face membership authentication method based on the proposed SVM performs better than the conventional SVM-based authentication methods and is relatively robust to the change in the enrolled class configuration.

• Korean Journal of Culture and Social Issue
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• v.8 no.2
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• pp.191-208
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• 2002

This survey research examined the effectiveness, gender identity and the satisfaction of life of female leaders in government, in relation to the organizational culture regarding gender discrimination. The respondents were high -ranking (above 5th grade) male (N=154) and female (N=150) leaders in government and the supervisors (N= 139) of the female leaders. The results demonstrated that the effectiveness of female leaders was rated lower as she helped her junior females at work more as a mentor, while she was rated as being more effective as her leadership style became more relationship-oriented. The satisfaction of life of female leaders was higher as she engaged more in mentoring to the junior females and as she had more positive gender identity. However, life satisfaction became lower as the organizational culture became more discriminating toward females. The discriminating organizational culture was also correlated negatively with the interpersonal relationship between females(especially the relationship with the female seniors). These results are indicating that the behaviors, the effectiveness ratings and the satisfaction of life of female leaders in Government are restricted by the gender -discriminating organizational culture and the cultural stereotypes of the members in the organization.

• Fire Protection Technology
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• s.18
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• pp.5-16
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• 1995

The capacity commonly required sensors includes capability of quickly and properly catching the conditions of a fire and discriminating other factors such as noise, interference, etc. IR flame detector which react to the infra-red rays emitted from the flame. This study is aimed to know the characteristic repond to the specified fire plate. Experiment is acted by manufacture's technical data that is explained relation of detective range and sensitivity.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.89-92
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• 1987

In a template-matchig-based speech recognition syste, excessive weight given to perceptually unimportant spectral variations is undesirable for discriminating among acoustically similar words. By introducing a simple threshold-type nonlinearity applied to the distance metric, the word recognition performance can be improved for a vocabulary with similar sounding words, without modifying the system structure.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.357-358
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• 2005

• Bulletin of the Korean Chemical Society
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• v.32 no.10
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• pp.3775-3778
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• 2011

• Journal of Plant Biotechnology
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• v.49 no.1
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• pp.2-2
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• 2022

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.117-123
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• 2012

Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and disease-infected seed potatoes with the spectral range from 400 to 1100 nm. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and disease-infected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis/NIR reflectance method has good potential for non-destructive sorting for disease-infected seed potatoes.

• Journal of Korean Academy of Nursing
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• v.41 no.3
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• pp.423-431
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• 2011

Purpose: The study was designed to determine the discriminating ability of a Bayesian network (BN) for predicting risk for pressure ulcers. Methods: Analysis was done using a retrospective cohort, nursing records representing 21,114 hospital days, 3,348 patients at risk for ulcers, admitted to the intensive care unit of a tertiary teaching hospital between January 2004 and January 2007. A BN model and two logistic regression (LR) versions, model-I and .II, were compared, varying the nature, number and quality of input variables. Classification competence and case coverage of the models were tested and compared using a threefold cross validation method. Results: Average incidence of ulcers was 6.12%. Of the two LR models, model-I demonstrated better indexes of statistical model fits. The BN model had a sensitivity of 81.95%, specificity of 75.63%, positive and negative predictive values of 35.62% and 96.22% respectively. The area under the receiver operating characteristic (AUROC) was 85.01% implying moderate to good overall performance, which was similar to LR model-I. However, regarding case coverage, the BN model was 100% compared to 15.88% of LR. Conclusion: Discriminating ability of the BN model was found to be acceptable and case coverage proved to be excellent for clinical use.