• Journal of Nutrition and Health
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• v.29 no.9
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• pp.1021-1027
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• 1996

This study examined the patterns of nutrient intakes measured by 1-, 3-, 7-day recalls and records as well as food frequency questionnaire among 59 females volunteers enrolled in the university in Seoul, Korea. Over a 4 month period, a modified Willett food frequency questionnaire was administered once, and a 24-hour dietary recall was conducted 12 times and a weighted dietary record 14 times. From these 12 recalls and 14 records, 1-, 3-, 7-day data were randomly selected. For energy and 11 nutrients, group mean intakes derived from food frequency questionnaire were higher than from recalls and records. Group mean intakes from recalls and records showed little differences depending on days of dietary studies and dietary methods. Measures of agreement were calculated by weighted kappa and intraclass correlation coefficient values calculated for quintile categories while comparing to the results of 26 days recalls and records. Weighted kappa values ranged from 0.11 for riboflavin to 0.36 for vitamin C for and 1-day recall, and from 0.21 for iron to 0.31 for energy for the 1-day record. Weighted kappa values were increased as the number of days of dietary studies increased (0.34-0.57 for the 3-day recalls, 0.27-0.50 for the 3-day records, 0.50-0.68 for the 7-day recalls, and 0.50-0.65 for the 7-day records). Weighted kappa values for food frequency questionnaire were higher than the 1-day data, but lower than the 3-and-7day data(0.34 for energy, 0.31 for iron and 0.22 for vitamin C). Intraclass correlation coefficients ranged from 0.21 for vitamin A to 0.57 for calcium. The degrees of agreement by different methods and days of dietary study are lower in our study compared to agreement by different methods and days of dietary study are lower in our study compared to those in previously published studies for Western populations, partly due to the differences of data analysis methods as well as of dietary patterns between those samples and ours.

• Journal of dental hygiene science
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• v.15 no.3
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• pp.377-382
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• 2015

The purpose of this study was to evaluate the validity and reliability of plaque scoring system using new Qraycam (All in One Bio, Korea) device which enables plaque score without tooth disclosing. This study measured Quigley-Hein index and plaque control record by both Qraycam and disclosing agent on 64 elderly people and checked degree of congruence between the two methods. Reliability was evaluated with the mean of measured values, kappa index and intraclass correlation coefficient statistical analysis. The analysis of the plaque scores showed a high agreement between the measured values according to the method of measurement and the measured part. The mean of plaque index of anterior labial were not significantly different according to measurement method. The kappa index was higher by Qraycam and tooth disclosing method of plaque index. Therefore, it was verified that Qraycam has sufficient reliability as screening tool for plaque scoring system.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.999-1009
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• 2019

The importance of high-resolution sea ice maps of the Arctic Ocean is increasing due to the possibility of pioneering North Pole Routes and the necessity of precise climate prediction models. In this study,sea ice classification algorithms for two deep learning models were examined using Sentinel-1 A/B SAR data to generate high-resolution sea ice classification maps. Based on current ice charts, three classes (Open Water, First Year Ice, Multi Year Ice) of training data sets were generated by Arctic sea ice and remote sensing experts. Ten sea ice classification algorithms were generated by combing two deep learning models (i.e. Simple CNN and Resnet50) and five cases of input bands including incident angles and thermal noise corrected HV bands. For the ten algorithms, analyses were performed by comparing classification results with ground truth points. A confusion matrix and Cohen's kappa coefficient were produced for the case that showed best result. Furthermore, the classification result with the Maximum Likelihood Classifier that has been traditionally employed to classify sea ice. In conclusion, the Convolutional Neural Network case, which has two convolution layers and two max pooling layers, with HV and incident angle input bands shows classification accuracy of 96.66%, and Cohen's kappa coefficient of 0.9499. All deep learning cases shows better classification accuracy than the classification result of the Maximum Likelihood Classifier.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.115-127
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• 2024

This research aimed to construct models with various structures based on the Transformer module and to perform land cover classification, thereby examining the applicability of the Transformer module. For the classification of land cover, the Unet model, which has a CNN structure, was selected as the base model, and a total of four deep learning models were constructed by combining both the encoder and decoder parts with the Transformer module. During the training process of the deep learning models, the training was repeated 10 times under the same conditions to evaluate the generalization performance. The evaluation of the classification accuracy of the deep learning models showed that the Model D, which utilized the Transformer module in both the encoder and decoder structures, achieved the highest overall accuracy with an average of approximately 89.4% and a Kappa coefficient average of about 73.2%. In terms of training time, models based on CNN were the most efficient. however, the use of Transformer-based models resulted in an average improvement of 0.5% in classification accuracy based on the Kappa coefficient. It is considered necessary to refine the model by considering various variables such as adjusting hyperparameters and image patch sizes during the integration process with CNN models. A common issue identified in all models during the land cover classification process was the difficulty in detecting small-scale objects. To improve this misclassification phenomenon, it is deemed necessary to explore the use of high-resolution input data and integrate multidimensional data that includes terrain and texture information.

• Tuberculosis and Respiratory Diseases
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• v.79 no.4
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• pp.282-288
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• 2016

Background: Tuberculosis (TB) is a major health problem, and accurate and rapid diagnosis of multidrug-resistant (MDR) and extended drug-resistant (XDR) TB is important for appropriate treatment. In this study, performances of solid and liquid culture methods were compared with respect to MDR- and XDR-TB isolate recovery and drug susceptibility testing. Methods: Sputum specimens from 304 patients were stained with Ziehl-Neelsen method. Mycobacterium tuberculosis (Mtb) isolates were tested for recovery on $L{\ddot{o}wenstein$-Jensen (LJ) medium and the BacT Alert 3D system. For drug susceptibility testing of Mtb, isolates were evaluated on M-KIT plates and the BacT Alert 3D system. Results: The recovery rates were 94.9% (206/217) and 98.2% (213/217) for LJ medium and the BacT Alert 3D system, respectively (kappa coefficient, 0.884). The rate of drug resistance was 13.4% for at least one or more drugs, 6.0% for MDR-TB and 2.3% for XDR-TB. M-KIT plate and BacT 3D Alert 3D system were comparable in drug susceptibility testing for isoniazid (97.7%; kappa coefficient, 0.905) and rifampin (98.6%; kappa coefficient, 0.907). Antibiotic resistance was observed using M-KIT plates for 24 of the total 29 Mtb isolates (82.8%). Conclusion: The liquid culture system showed greater reduction in the culture period, as compared with LJ medium; however, drug susceptibility testing using M-KIT plates was advantageous for simultaneous testing against multiple drug targets.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.2168-2173
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• 2003

Pressure balancing valve is one of important control devices, which is fully automatic and no manual controls, regulating or adjustments are needed. It is typically used to maintain constant temperature of working fluid in power and chemical plants and domestic water supply systems. Pressure balancing valve is composed of body, cylinder and balancing piston. Therefore, the balancing piston shapes are important design parameters for a pressure balancing valve. In this study, numerical and experimental analyses are carried out with two different balancing piston shapes. Especially, the distribution of static pressure is investigated to calculate the flow coefficient($C_v$). The governing equations are derived from making using of three-dimensional Navier-Stokes equations with standard ${\kappa}-{\varepsilon}$ turbulence model and SIMPLE algorithm. Using commercial code, PHOEIC, the pressure and flow fields in pressure balancing valve are depicted.

• Imaging Science in Dentistry
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• v.47 no.1
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• pp.25-31
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• 2017

Purpose: The aim of this study was to compare the diagnostic accuracy of previously trained endodontists in the detection of artificially created periapical lesions using cone-beam computed tomography (CBCT) and digital periapical radiography (DPR). Materials and Methods: An ex vivo model using dry skulls was used, in which simulated apical lesions were created and then progressively enlarged using #1/2, #2, #4, and #6 round burs. A total of 11 teeth were included in the study, and 110 images were obtained with CBCT and with an intraoral digital periapical radiographic sensor (Instrumentarium dental, Tuusula, Finland) initially and after each bur was used. Specificity and sensitivity were calculated. All images were evaluated by 10 previously trained, certified endodontists. Agreement was calculated using the kappa coefficient. The accuracy of each method in detecting apical lesions was calculated using the chisquare test. Results: The kappa coefficient between examiners showed low agreement (range, 0.17-0.64). No statistical difference was found between CBCT and DPR in teeth without apical lesions (P=.15). The accuracy for CBCT was significantly higher than for DPR in all corresponding simulated lesions(P<.001). The correct diagnostic rate for CBCT ranged between 56.9% and 73.6%. The greatest difference between CBCT and DPR was seen in the maxillary teeth (CBCT, 71.4%; DPR, 28.6%; P<.01) and multi-rooted teeth (CBCT, 83.3%; DPR, 33.3%; P<.01). Conclusion: CBCT allowed higher accuracy than DPR in detecting simulated lesions for all simulated lesions tested. Endodontists need to be properly trained in interpreting CBCT scans to achieve higher diagnostic accuracy.

• Journal of Korean Society of Forest Science
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• v.81 no.4
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• pp.346-356
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• 1992

The extensive Snake River floodplain in Northwest United States has experienced major changes in water channels and vegetation types due to floodings. To detect the change of wetland cover-types for the period of 1985 and 1988, post-classification comparison and image differencing change detection techniques were evaluated using Landsat-5 TM digital data. Differenced infrared-band images indicated better accuracy indices than any visible-band images. A thresholding technique was applied to identify the change and no change categories from the transformed images produced by image differencing. The problems in using different accuracy indices, including the Kappa coefficient of agreement, overall accuracy, producer's accuracy, user's accuracy, and average accuracy(based on both the producer's and user's accuracy approaches) in determining an optimal threshold level, were examined.

• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.3
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• pp.171-177
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• 2018

The purpose of this study was to evaluate the reliability and the validity of Deficiency and Excess Pattern Identification Questionnaire. The number of subjects enrolled in this study was 248, from July 2015 to March. 2016. The surveys was conducted two times with 3 month interval. The Cronbach's ${\alpha}$ analysis for internal reliability, Pearson Correlation Coefficient analysis for test-retest reliability were conducted. Factor analysis with varimax rotation for construct validity was used. Kappa analysis for diagnostic reliability were used. The significant p-value was < .05. The Cronbach's ${\alpha}$ was .929 in Deficiency and .932 in Excess questionnaire. The reliabilities between test and retest Intra Correlation Coefficient (ICC) was .71-.762 in the Deficiency, and .58-.786 in Excess questionnaire, respectively. Deficiency was divided by five factors, and Excess four factors. The factor convergence was 72.54% in the Deficiency and 67.5% in Excess questionnaire. The test-retest agreement of four pattern was 68.5% and Kappa was .530. This study reveals that Deficiency and Excess Pattern Identification Questionnaire is a reliable and valid. However, further study to validate the questionnaire is needed.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.491-495
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• 2016

Background: Small B-cell non-Hodgkins lymphoma (NHL) is difficult to be distinguished from non-neoplastic reactive processes using conventional haematoxylin-eosin (HE) staining due to different interpretations among pathologists with diagnosis based on morphologic features. Ancillary examinations such as immunohistochemical (IHC) staining are essential. However, negative or doubtful results are still sometimes obtained due to unsatisfactory tissue processing or IHC technique. The polymerase chain reaction (PCR) as a molecular diagnostic technique is very sensitive and specific. Clonality detection of heavy chain immunoglobulin (IgH) gene rearrangement has been widely used to establish diagnosis of B-cell NHL. Aims: To elaborate interobserver variation in small B-cell NHL diagnosis based on morphologic features only and to confirm sensitivity and specificity of the PCR technique as an ancillary method. Materials and Methods: A toptal of 28 samples of small B cell NHL and suspicious lymphoma were interpreted by 3 pathologists in Sardjito General Hospital based on their morphology only. The reliability of assessment and the coefficient of interobserver agreement were calculated by Fleiss kappa statistics. Interpretation results were confirmed with IHC staining (CD20, CD3, Bcl2). PCR was performed to analyze the clonality of IgH gene rearrangement. Results: Interobserver agreement in morphologic evalution of small B cell NHL and chronic lymphadenitis revealed kappa coefficient 0.69 included in the substantial agreement category. The cases were divided into 3 groups based on morphology and IHC results; lymphoma, reactive process and undetermined group. PCR analysis showed 90% sensitivity and 60% specificity. Conclusions: The present study revealed a substantial agreement among pathologists in small B-cell NHL diagnosis. For difficult cases, PCR is useful as complementary method to morphologic and IHC examinations to establish definitive diagnosis.