• Clinical and Experimental Pediatrics
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• v.62 no.11
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• pp.416-421
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• 2019

Background: The seropositivity rate of hepatitis B surface antigen (anti-HBs) antibodies is known to be ≥95% after hepatitis B virus vaccination during infancy. However, a low level or absence of anti-HBs in healthy children is discovered in many cases. Recent studies in adults reported that a reduced anti-HBs production rate is related to obesity. Purpose: To investigate whether body mass index (BMI) affects anti-HBs levels in healthy children following 3 serial dose vaccinations in infancy. Methods: We recruited 1,200 healthy volunteers aged 3, 5, 7, or 10 years from 4-day care centers and 4 elementary schools. All subjects completed a questionnaire including body weight, height, and vaccine type received. Levels of serum hepatitis B surface antigen (HBsAg) and anti-HBs in all subjects were analyzed using electrochemiluminescence immunoassay. The standardized scores (z score) for each sex and age were obtained using the lambda-mu-sigma method in the 2017 Korean National Growth Charts for children and adolescents. Results: Our subjects (n=1,200) comprised 750 males (62.5%) and 450 females (37.5%). The overall anti-HBs seropositivity rate was 57.9% (695 of 1,200). We identified significant differences in mean BMI values between seronegative and seropositive groups (17.45 vs. 16.62, respectively; P<0.001). The anti-HBs titer was significantly decreased as the BMI z score increased adjusting for age and sex (B=-15.725; standard error=5.494; P=0.004). The probability of anti-HBs seropositivity based on BMI z score was decreased to an OR of 0.820 after the control for confounding variables (95% confidence interval, 0.728-0.923; P=0.001). Conclusion: There was a significant association between anti-HBs titer and BMI z score after adjustment for age and sex. Our results indicate that BMI is a potential factor affecting anti-HBs titer in healthy children.

• Journal of Korea Water Resources Association
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• v.49 no.10
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• pp.877-885
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• 2016

In this study, the Standard Precipitation Index(SPI), meteorological drought index, was used to evaluate the temporal and spatial assessment of drought forecasting results for all cross Korea. For the drought forecasting, the Multi Layer Perceptron-Artificial Neural Network (MLP-ANN) was selected and the drought forecasting was performed according to different forecasting lead time for SPI (3) and SPI (6). The precipitation data observed in 59 gaging stations of Korea Meteorological Adminstration (KMA) from 1976~2015. For the performance evaluation of the drought forecasting, the binary classification confusion matrix, such as evaluating the status of drought occurrence based on threshold, was constituted. Then Receiver Operating Characteristics (ROC) score and F score according to conditional probability are computed. As a result of ROC analysis on forecasting performance, drought forecasting performance, of applying the MLP-ANN model, shows satisfactory forecasting results. Consequently, two-month and five-month leading forecasts were possible for SPI (3) and SPI (6), respectively.

• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.151-164
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• 2013

A key input for the assessment of Human Error Probabilities (HEPs) with Human Reliability Analysis (HRA) methods is the evaluation of the factors influencing the human performance (often referred to as Performance Shaping Factors, PSFs). In general, the definition of these factors and the supporting guidance are such that their evaluation involves significant subjectivity. This affects the repeatability of HRA results as well as the collection of HRA data for model construction and verification. In this context, the present paper considers the TAsk COMplexity (TACOM) measure, developed by one of the authors to quantify the complexity of procedure-guided tasks (by the operating crew of nuclear power plants in emergency situations), and evaluates its use to represent (objectively and quantitatively) task complexity issues relevant to HRA methods. In particular, TACOM scores are calculated for five Human Failure Events (HFEs) for which empirical evidence on the HEPs (albeit with large uncertainty) and influencing factors are available - from the International HRA Empirical Study. The empirical evaluation has shown promising results. The TACOM score increases as the empirical HEP of the selected HFEs increases. Except for one case, TACOM scores are well distinguished if related to different difficulty categories (e.g., "easy" vs. "somewhat difficult"), while values corresponding to tasks within the same category are very close. Despite some important limitations related to the small number of HFEs investigated and the large uncertainty in their HEPs, this paper presents one of few attempts to empirically study the effect of a performance shaping factor on the human error probability. This type of study is important to enhance the empirical basis of HRA methods, to make sure that 1) the definitions of the PSFs cover the influences important for HRA (i.e., influencing the error probability), and 2) the quantitative relationships among PSFs and error probability are adequately represented.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.13-28
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• 2010

Assuming a mixture distribution for credit evaluation studies, we discuss estimating threshold methods to minimize errors that default borrowers are predicted as non defaults or non defaults are regarded as defaults. A method by using statistical hypotheses tests, the most powerful test and generalized likelihood ratio test, for the probability density functions which are defined with the score random variable and the parameter space consisted of only two elements such as the default and non default states is proposed to estimate a threshold. And anther optimal thresholds to maximize classification accuracy measures of the accuracy and the true rate for ROC and CAP curves are estimated as equations related with these probability density functions. Three kinds of optimal thresholds in terms of the hypotheses testing, the accuracy and the true rate are obtained from normal random samples with various means and variances. The sums of the type I and type II errors corresponding to each optimal threshold are obtained and compared. Finally we discuss about their efficiency and derive conclusions.

• Atmosphere
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• v.25 no.1
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• pp.67-83
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• 2015

Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1471-1479
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• 2008

In this paper, we propose a technique to improve Out-Of-Vocabulary(OOV) rejection algorithms in variable vocabulary recognition system which is much used in ASR(Automatic Speech Recognition). The rejection system can be classified into two categories by their implementation method, keyword spotting method and utterance verification method. The utterance verification method uses the likelihood ratio of each phoneme Viterbi score relative to anti-phoneme score for deciding OOV. In this paper, we add speaker verification system before utterance verification and calculate an speaker verification probability. The obtained speaker verification probability is applied for determining the proposed variable-confidence threshold. Using the proposed method, we achieve the significant performance improvement; CA(Correctly Accepted for keyword) 94.23%, CR(Correctly Rejected for out-of-vocabulary) 95.11% in office environment, and CA 91.14%, CR 92.74% in noisy environment.

• Korean Journal of Adult Nursing
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• v.17 no.3
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• pp.464-473
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• 2005

Purpose: The purpose of this study was to evaluate and compare the predictive ability of three mortality scoring systems; Acute Physiology and Chronic Health Evaluation(APACHE) III, Simplified Acute Physiology Score(SAPS) II, and Mortality Probability Model(MPM) II in discriminating in-hospital mortality for intensive care unit(ICU) patients with spontaneous intracerebral hemorrhage. Methods: Eighty-nine patients admitted to the ICU at a university hospital in Daejeon Korea were recruited for this study. Medical records of the subject were reviewed by a researcher from January 1, 2003 to March 31, 2004, retrospectively. Data were analyzed using SAS 8.1. General characteristic of the subjects were analyzed for frequency and percentage. Results: The results of this study were summarized as follows. The values of the Hosmer-Lemeshow's goodness-of-fit test for the APACHE III, the SAPS II and the MPM II were chi-square H=4.3849 p=0.7345, chi-square H=15.4491 p=0.0307, and chi-square H=0.3356 p=0.8455, respectively. Thus, The calibration of the MPM II found to be the best scoring system, followed by APACHE III. For ROC curve analysis, the areas under the curves of APACHE III, SAPS II, and MPM II were 0.934, 0.918 and 0.813, respectively. Thus, the discrimination of three scoring systems were satisfactory. For two-by-two decision matrices with a decision criterion of 0.5, the correct classification of three scoring systems were good. Conclusion: Both the APACHE III and the MPM II had an excellent power of mortality prediction and discrimination for spontaneous intracerebral hemorrhage patients in ICU.

• Journal of the Korean Society of Earth Science Education
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• v.1 no.1
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• pp.63-71
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• 2008

The purpose for this study is to check if research activities can make positive effects on inquiry instruction utilizing materials when compared to traditional instruction utilizing the textbook. The effects of the class should be measured both in cognitive domain and in affective domain. The cognitive domain was measured by the change in achievements in learning science, and the affective domain was measured by the change in learning attitudes of science. The assumptions to be verified in this study were as follows. First, achievements in learning science are higher in the learner oriented inquiry instruction utilizing materials than in the learner oriented traditional instruction utilizing the textbook. Second, learning attitudes of science are higher in the learner oriented inquiry instruction utilizing materials than in the learner oriented traditional instruction utilizing the textbook.The results of the research are as follows. In the cognitive domain, achievements in learning science showed significant change(p=.045) measured by verifying the score for the difference among the averages for each sub-scale, in 5% of meaningful probability, and were higher in the inquiry instruction utilizing materials study. In the affective domain, learning attitudes of science showed significant change(p=.019) measured by verifying the score for the difference among the averages for each sub-scale, in 5% of meaningful probability, and were higher in the inquiry instruction utilizing materials study. In learning attitudes of science, 2 items(self-conception of science, attitudes of learning science) out of 3 items(self-conception of science, attitudes of learning science, learning habits of science) showed significant changes (p=.045, p=.001). But the difference(learning-habits of science) was not significant(p=.914).

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.294-297
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• 2007

Steam and advection fogs are frequently observed in the Yellow Sea located between Korea and China during the periods of March-April and June-July respectively. This study uses the remote sensing (RS) data for monitoring sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided an informative synopsis for the occurrence of steam and advection fogs through a ground truth. The RS data used in this study was GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and near-IR channel of GOES-9 and MTSAT-1R satellites was applied to estimate the extension of the sea fog. For the days examined, it was found that not only the DCD but also the texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind is used to provide a weak wind area less than threshold under stable condition of the surface wind around a fog event. The Laplacian computation for a measurement of the homogeneity was designed. A new combined method of DCD, QuikSCAT wind speed and Laplacian was applied in the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and Laplacian are -2.0 K, 8 m $s^{-1}$ and 0.1, respectively. The validation methods such as Heidke skill score, probability of detection, probability of false detection, true skill score and odds ratio show that the new combined method improves the detection of sea fog rather than DCD method.

• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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• pp.366-372
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• 2004

Objectives : This study was conducted to propose a new transmission/disequilibrium test(TDT) to test the linkage between genetic markers and disease-susceptibility genes based on haplotypes. Simulation studies were performed to compare the proposed method with that of Zhao et al. in terms of type I error probability and powers. Methods : We estimated the haplotype frequencies using the expectation-maximization(EM) algorithm with parents genotypes taken from a trio dataset, and then constructed a two-way contingency table containing estimated frequencies to all possible pairs of parents haplotypes. We proposed a score test based on differences between column marginals and their corresponding row marginals. The test also involved a covariance structure of marginal differences and their variances. In simulation, we considered a coalescent model with three genetic markers of biallele to investigate the performance of the proposed test under six different configurations. Results : The haplotype-based TDT statistics, our test and Zhao et al.'s test satisfied a type I error probability, but the TDT test based on single locus showed a conservative trend. As expected, the tests based on haplotypes also had better powers than those based on single locus. Our test and that of Zhao et al. were comparable in powers. Conclusion : We proposed a TDT statistic based on haplotypes and showed through simulations that our test was more powerful than the single locus-based test. We will extend our method to multiplex data with affected and/or unaffected sibling(s) or simplex data having only one parent s genotype.