• Clinical and Experimental Pediatrics
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• v.64 no.1
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• pp.31-36
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• 2021

Background: The diagnosis of esophageal varices (EV) is based on the findings of esophagogastroduodenoscopy (EGD), biopsy, and serum markers. Thus, noninvasive cost-effective tests through which high-risk EV children can be diagnosed are needed. Purpose: This cross-sectional study aimed to identify the noninvasive markers for EV in children with liver cirrhosis. Methods: A total of 98 children with liver cirrhosis were evaluated in this study. The spleen size, platelet count, serum albumin, liver function test results, and risk scores were evaluated prior to endoscopy. The endoscopic investigations aimed to identify the presence of EV and red signs, and determine varices sizes. Results: Endoscopy revealed varices in 43 subjects (43.9%). The spleen size, platelet count, international normalized ratio, aspartate aminotransferase to platelet ratio index (APRI), platelet count to spleen size ratio, and risk score differed significantly between patients with and without EV on univariate analysis; however, the logistic regression analysis showed no differences, indicating that none of these parameters were independently associated with the presence of EV. Conclusion: Platelet count, risk score, platelet count to spleen size, and APRI can be useful tools for the identification of high-risk patients with EV and might reduce the need for invasive methods like EGD.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.301-309
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• 2021

Pulse count method is the classical reaction wheel speed detection method. In this study, we represent the pulse count method as mathematical equations. Instead of rotation speed, we model the reaction wheel rotation through rotation angle during sampling periods. We verified the effectiveness of the proposed model by comparing the pulse counts variation and averaging method effects from the model and previous research results. Then, we add tacho pulse non-uniformity to this verified model, and examine the errors of pulse count method. We express the measurement error increasement due to non-uniformity as mathematical equations, and also shows the requirement of moving average numbers to offset the measurement errors.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.227-234
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• 2002

In this paper, we consider hierarchical Bayes generalized linear models for the analysis of longitudinal count data. Specifically we introduce the hierarchical Bayes random effects models. We discuss implementation of the Bayes procedures via Markov chain Monte Carlo (MCMC) integration techniques. The hierarchical Baye method is illustrated with a real dataset and is compared with other statistical methods.

• 전기의세계
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• v.29 no.7
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• pp.455-459
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• 1980

The gain change of the photomultiplier which occurs as the count rate increased was examined. and simple feedback resistor series was introduced between 7th and 9th dynode for compensating the gain change. The effect of the feedback resistor series was considerably good to reduce the gain change. With the feedback resistor, the gain change was only 1.9%, when count rate was increased from 514 CPS (counts per second) to 1250 CPS. Without the feedback resister, the gain change was 6.9%, when the count rate was increased from 530 CPS to 1250 CPS.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.761-770
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• 2012

We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.93-107
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• 2002

Random effects generalised linear models are useful for analysing clustered count data in which responses are usually correlated. We propose a Bayesian approach to parameter estimation and variable selection in random effects generalised linear models for count data. A simple Gibbs sampling algorithm for parameter estimation is presented and a simple and efficient variable selection is done by using the Gibbs outputs. An illustrative example is provided.

• Journal of Environmental Health Sciences
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• v.2 no.1
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• pp.21-24
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• 1975

During April and May, 1973 rain water samples were collected five different times in nine selected areas of Seoul city. The pH factor and bacteria counts were measured. The following results were obtained. 1. The lowest pH was 6.18 at Moon Rae Dong and the highest was 6.30 at Jong Am Dong. This difference is not significant at the 0. 05 level. 2. The pH factor did not vary significantly with the time of sample collection. 3. Dae Bang Dong had the highest Total Plate Count of $1.9\times 10^3/ml$, Bo Moon Dong and An Kook Dong had the lowest Total Plate Count at $4.1\times 10^2/ml$. 4. The total plate count varied greatly according to the time of sample collection. This result can be used to remove are pollutants. 5. The Total plate Count is nearly inversely proportional to the length of time during which the sample is collected.

• Journal of Dairy Science and Biotechnology
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• v.22 no.1
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• pp.27-35
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• 2004

The shelf lift of market milk should be determined based on the flavor which is influenced by environmental and sanitary conditions of dairy farm, milk processing plant, and storage and transportation facility as well as compositional quality, such as protein and fat, of the milk itself. The legal shelf life of market milk is often limited by microbiological quality, e.g. total bacterial count, coliform count, and food poisoning bacteria. The bacteria involved with milk spoilage and poisoning are originated from bacteria contaminating milk after pasteurization or spores surviving the heat treatment of pasteurization. The important factors which influence the shelf life of market milk are microbiological quality of raw milk, pasteurization condition, post-pasteurization contamination, and temperature during storage and transportation. The organoleptic quality and shelf life of market milk should be further improved by satisfying the consumer's taste, which depends on somatic cell count and bacterial count of milk, feed quality, foreign substance in milk, and physical treatment during processing and transportation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.112-118
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• 1997

Characteristics of AE(Acoustic Emission) signal is related to cutting conditions, tool materials, and tool geometry in metal cutting. Relation between AE signal and tool wear was investigated experimentally. Experiment is carried out by interrupted cutting for SCM420 workpiece with TiN coating tool on HSS material. AE RMS voltage and count per event were increased according to tool wear. The major results are as follows : 1) AE RMS value is nearly constant as cutting speed changes, but is rapidly increase as feed rate increases. 2) AE RMS value and Count per Event increase as tool wear increases. 3) It is more effective to monitor tool wear by Incremental rate of AE RMS value than by Incremental rate of count per event.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.265-272
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• 2002

An Integer-valued autoregressive integrated (INARI) model is introduced to eliminate stochastic trend and seasonality from time series of count data. This INARI extends the previous integer-valued ARMA model. We show that it is stationary and ergodic to establish asymptotic normality for conditional least squares estimator. Optimal estimating equations are used to reflect categorical and serial correlations arising from panel count data and variations arising from three random processes for obtaining observation into estimation. Under regularity conditions for martingale sequence, we show asymptotic normality for estimators from the estimating equations. Using cancer mortality data provided by the U.S. National Center for Health Statistics (NCHS), we apply our results to estimate the probability of cells classified by 4 causes of death and 6 age groups and to forecast death count of each cell. We also investigate impact of three random processes on estimation.