• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.22 no.4
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• pp.350-357
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• 2019

Purpose: This study aimed to evaluate a possible association between the anti-tissue transglutaminase antibody (anti-tTG) titer and stage of duodenal mucosal damage and assess a possible cut-off value of anti-tTG at which celiac disease (CD) may be diagnosed in children in conjunction with clinical judgment. Methods: This observational study was conducted at a gastroenterology clinic in a tertiary hospital from April 2012 to May 2013. Seventy children between 6-months and 18-years-old with suspected CD underwent celiac serology and duodenal biopsy. Statistical analyses were done using SPSS 16. Diagnostic test values were determined for comparing the anti-tTG titer with duodenal biopsy. An analysis of variance and Tukey-Kramer tests were performed for comparing the means between groups. A receiver operating characteristics curve was plotted to determine various cut-off values of anti-tTG. Results: The mean antibody titer increased with severity of Marsh staging (p<0.001). An immunoglobulin (Ig) A-tTG value at 115 AU/mL had 76% sensitivity and 100% specificity with a 100% positive predictive value (PPV) and 17% negative predictive value (NPV) for diagnosis of CD (p<0.001, 95% confidence interval [CI], 0.75-1). Conclusion: There is an association between the anti-tTG titer and stage of duodenal mucosal injury in children with CD. An anti-tTG value of 115 AU/mL (6.4 times the upper normal limit) had 76% sensitivity, 100% specificity, with a 100% PPV, and 17% NPV for diagnosing CD (95% CI, 0.75-1). This cut-off may be used in combination with clinical judgment to diagnose CD.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.134-143
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• 2011

The selection of meaningful clinical tests and its reference values from a high-dimensional clinical data with imbalanced class distribution, one class is represented by a large number of examples while the other is represented by only a few, is an important issue for differential diagnosis between similar diseases, but difficult. For this purpose, this study introduces methods based on the concepts of both discernibility matrix and function in rough set theory (RST) with two discretization approaches, equal width and frequency discretization. Here these discretization approaches are used to define the reference values for clinical tests, and the discernibility matrix and function are used to extract a subset of significant clinical tests from the translated nominal attribute values. To show its applicability in the differential diagnosis problem, we have applied it to extract the significant clinical tests and its reference values between normal (N = 351) and abnormal group (N = 101) with either cholecystitis or cholelithiasis disease. In addition, we investigated not only the selected significant clinical tests and the variations of its reference values, but also the average predictive accuracies on four evaluation criteria, i.e., accuracy, sensitivity, specificity, and geometric mean, during l0-fold cross validation. From the experimental results, we confirmed that two discretization approaches based rough set approximation methods with relative frequency give better results than those with absolute frequency, in the evaluation criteria (i.e., average geometric mean). Thus it shows that the prediction model using relative frequency can be used effectively in classification and prediction problems of the clinical data with imbalanced class distribution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.321-340
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• 2016

The Compressive Video Sensing (CVS) is a useful technology for wireless systems requiring simple encoders but handling more complex decoders, and its rate-distortion performance is highly affected by the quantization of measurements and reconstruction of video frame, which motivates us to presents the Space-Time Quantization (ST-Q) and Motion-Aligned Reconstruction (MA-R) in this paper to both improve the performance of CVS system. The ST-Q removes the space-time redundancy in the measurement vector to reduce the amount of bits required to encode the video frame, and it also guarantees a low quantization error due to the fact that the high frequency of small values close to zero in the predictive residuals limits the intensity of quantizing noise. The MA-R constructs the Multi-Hypothesis (MH) matrix by selecting the temporal neighbors along the motion trajectory of current to-be-reconstructed block to improve the accuracy of prediction, and besides it reduces the computational complexity of motion estimation by the extraction of static area and 3-D Recursive Search (3DRS). Extensive experiments validate that the significant improvements is achieved by ST-Q in the rate-distortion as compared with the existing quantization methods, and the MA-R improves both the objective and the subjective quality of the reconstructed video frame. Combined with ST-Q and MA-R, the CVS system obtains a significant rate-distortion performance gain when compared with the existing CS-based video codecs.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.71-84
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• 2017

Radon, which enters the interior environment from soil, rocks, and groundwater, is a radioactive gas that poses a serious risk to humans. Indoor radon concentrations are measured to investigate the risk of radon gas exposure and reliable radon concentration mapping is then performed for further analysis. In this study, we compared the predictive performance of various univariate kriging algorithms, including ordinary kriging and three nonlinear transform-based kriging algorithms (log-normal, multi-Gaussian, and indicator kriging), for mapping radon concentrations with an asymmetric distribution. To compare and analyze the predictive performance, we carried out jackknife-based validation and analyzed the errors according to the differences in the data intervals and sampling densities. From a case study in South Korea, the overall nonlinear transform-based kriging algorithms showed better predictive performance than ordinary kriging. Among the nonlinear transform-based kriging algorithms, log-normal kriging had the best performance, followed by multi-Gaussian kriging. Ordinary kriging was the best for predicting high values within the spatial pattern. The results from this study are expected to be useful in the selection of kriging algorithms for the spatial prediction of data with an asymmetric distribution.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• KIEAE Journal
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• v.16 no.3
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• pp.89-94
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• 2016

Purpose: This study aimed at developing an artificial neural network (ANN) model to predict the optimal start moment of the setback temperature during the normal occupied period of a building. Method: For achieving this objective, three major steps were conducted: the development of an initial ANN model, optimization of the initial model, and performance tests of the optimized model. The development and performance testing of the ANN model were conducted through numerical simulation methods using transient systems simulation (TRNSYS) and matrix laboratory (MATLAB) software. Result: The results analysis in the development and test processes revealed that the indoor temperature, outdoor temperature, and temperature difference from the setback temperature presented strong relationship with the optimal start moment of the setback temperature; thus, these variables were used as input neurons in the ANN model. The optimal values for the number of hidden layers, number of hidden neurons, learning rate, and moment were found to be 4, 9, 0.6, and 0.9, respectively, and these values were applied to the optimized ANN model. The optimized model proved its prediction accuracy with the very storing statistical correlation between the predicted values from the ANN model and the simulated values in the TRNSYS model. Thus, the optimized model showed its potential to be applied in the control algorithm.

• Journal of Veterinary Clinics
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• v.27 no.2
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• pp.142-146
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• 2010

The purpose of this study is to establish experimental canine skin barrier disruption model in dog. The study was designed to investigate the predictive properties of acetone damage using as effect parameters transepidermal water loss (TEWL) and stratum corneum (SC) hydration. To compare the structures of SC intercellular lipids in normal and acetone damaged skin, TEM observations were performed. Six clinically normal, male Beagles without dermatological problems were chosen for this study. Acetone damage was performed at 48hrs after clipping. Efficacy measurements for TEWL and skin hydration were performed before ($t_1$) and after ($t_2$) damage in a temperature- and humidity-controlled room ($2{0\sim}22^{\circ}C$, 50-60%). TEWL and SC hydration values were decreased in the acetone damaged model compared with non damaged skin. In TEM observation of acetone damaged sample, the intercellular lipid lamellae exhibit abnormal and incomplete structure compared with those of normal skin. It seems that acetone damage would be one of canine skin epidermal barrier disruption model for the study of canine atopic dermatitis (AD) as well as dry skin in veterinary dermatology research.

• Korean Journal of Community Nutrition
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• v.14 no.3
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• pp.340-353
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• 2009

It is very important to screen the elderly for nutritional risk, because nutritional status is a critical factor to maintain their health. Some nutrition checklists used in Korea for the elderly are from other countries. Reliability of those checklist in Korea is not studied enough. This survey was done for the elderly over 65-years-old who live in Hong-cheon, An-dong, Dam-yang and Yeon-gi in Korea (subject; summer: 146, winter: 145) to study the reliability of DETERMINE checklist which is adopted widely in Korea. Using the score of DETERMINE checklist, the elderly were divided as high, middle and low risk groups. For nutritional assessment for those elderly, dietary assessment using 24 recall, anthropometry, biochemical assessment and health condition were used. Results for the checklist showed that percentage below EAR for energy intake and protein intake in winter were higher in the high risk group than other groups. The intakes of phosphorus and iron and most vitamins were below the DRI. The percentage of subjects with intake below DRI was highest in the high risk group. Sensitivity, specificity, and positive predictive values using the DETERMINE were calculated using 6 point as a cut-off point. Subjects were divided into two groups by MAR (MAR < 0.75:undernutrition, MAR < 0.75 : normal). Sensitivity recorded 49.4% and 34.3%, specificity did 61.9% and 65.4 and Positive predictive value did 62.1% and 46.0% each for summer and winter. Results of screening using DETERMINE Checklist were not matched with dietary assessment but not with anthropometric and biochemical measurement. In conclusion DETERMINE 'Checklist' is shown be a good screening tool for finding out risk groups for dietary intake in the elderly, It needs to verify reliability and validity through large-scale survey.

• The Journal of Internal Korean Medicine
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• v.43 no.1
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• pp.53-67
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• 2022

Objectives: This study aimed to identify the characteristics of the heart rate variability (HRV) index in patients with burning mouth syndrome (BMS) and to evaluate the predictive value of HRV for Korean medical treatment responsiveness to tongue pain in BMS. Methods: Among BMS patients who visited the Oral Diseases Clinic of Kyung Hee University Korean Medicine Hospital from January 1, 2018, to May 31, 2021, we reviewed the clinical records of 217 women aged 50 years and over. HRV and unstimulated saliva flow rate (USFR) measurements were carried out, and all patients were asked to indicate their degree of tongue pain using the visual analog scale (VAS). The subjects were classified into subgroups according to the presence or absence of hyposalivation and VAS improvement, and each subgroup was compared using the HRV index. Logistic regression analysis was conducted to confirm whether cause-effect relationships were present between statistically significant values. Results: BMS patients had lower LF and HF than healthy people. Subgroup analysis demonstrated that there were some statistically significant differences in the HRV index according to salivation rate and degree of pain. In addition, as the LF/HF ratio increased, the pain improvement rate decreased after treatment. Conclusion: The autonomic nerve activity of BMS patients was lower than that of healthy people; however, autonomic balance was not impaired. In addition, tongue pain in BMS patients responded more favorably to Korean medical treatment when patients fell within a normal range of the LF/HF ratio, suggesting that autonomic imbalance could be used as one of the predictable factors in clinical practice.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.4 no.2
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• pp.351-358
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• 1997

Body temperature should be measured accurately to assess neonate's condition for proper care. Temperatures measured in rectal, axillary and tympanic site were compared in 129 normal neonates to find out proper nursing time for measuring temperature and the validity of fever detection. The results were as follows : 1. Mean temperatures of axillary and tympanic site($36.85^{\circ}C,\;37.12^{\circ}C$) were significantly lower than those of rectal site($37.19^{\circ}C$). 2. Mean nursing time for measuring body temperature was significantly higher and lower in axillary and tympanic temperatures(159.49 seconds, 11.07 seconds) than in rectal temperature(105.62 seconds). 3. Tympanic and axillary temperatures were significantly correlated with rectal temperature (r=0.85, r=0.78) and the significant correlation was demonstrated between tympanic and axillary temperatures(r=0.76). 4. Sensitivity, specificity, positive and negative predictive values were 0.87, 0.90, 0.72, 0.96 for detecting fever respectively. The above findings indicated that the tympanic thermometer offers a useful alternative to conventional methods.