• Asian-Australasian Journal of Animal Sciences
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• 제26권11호
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• pp.1536-1544
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• 2013

A least squares regression interval mapping model was derived to detect quantitative trait loci (QTL) with a unique mode of genomic imprinting, polar overdominance (POD), under a breed cross design model in outbred mammals. Tests to differentiate POD QTL from Mendelian, paternal or maternal expression QTL were also developed. To evaluate the power of the POD models and to determine the ability to differentiate POD from non-POD QTL, phenotypic data, marker data and a biallelic QTL were simulated on 512 F2 offspring. When tests for Mendelian versus parent-of-origin expression were performed, most POD QTL were classified as partially imprinted QTL. The application of the series of POD tests showed that more than 90% and 80% of medium and small POD QTL were declared as POD type. However, when breed-origin alleles were segregating in the grand parental breeds, the proportion of declared POD QTL decreased, which was more pronounced in a mating design with a small number of parents ($F_0$ and $F_1$). Non-POD QTL, i.e. with Mendelian or parent-of-origin expression (complete imprinting) inheritance, were well classified (>90%) as non-POD QTL, except for QTL with small effects and paternal or maternal expression in the design with a small number of parents, for which spurious POD QTL were declared.

• Journal of Korean society of Dental Hygiene
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• 제22권2호
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• pp.107-115
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• 2022

Objectives: This study aimed to examine the effects of dietary protein intake and quality on periodontal disease in Korean adults. Methods: The data used for analysis were obtained from the 7th Korean National Health and Nutrition Examination Survey (2016-2018). Data were analyzed using chi-square and t-test. Additionally, multiple logistic regression analysis was performed to assess the association between dietary protein intake and quality and periodontal disease. Statistical significance level was set at <0.05. Results: Multiple logistic regression analysis of dietary protein intake and periodontal disease in the model adjusted for socioeconomic factors showed that were significantly related to the Q1 (odds ratio [OR]: 1.18, 95% confidence interval [CI]: 1.01-1.39). However, this correlation was not significant in the model in which all variables were corrected. Moreover, analysis of the dietary protein quality and periodontal disease in model 4, which was adjusted for socioeconomic variables, showed that were significantly related to the low score (OR: 1.13, 95% CI: 1.00-1.27). Conclusions: The results showed a significant association between periodontal disease and poor intake and quality of dietary protein in the Korean adult population.

• Communications for Statistical Applications and Methods
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• 제23권4호
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• pp.343-353
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• 2016

In doubly-censored data, an originating event time and a terminating event time are interval-censored. In certain analyses of such data, a researcher might be interested in the elapsed time between the originating and terminating events as well as regression modeling with risk factors. Therefore, in this study, we introduce a model evaluation method to measure the predictive ability of a model based on negative predictive values. We use a semiparametric estimate of the predictive accuracy to provide a simple and flexible method for model evaluation of doubly-censored survival outcomes. Additionally, we used simulation studies and tested data from a prostate cancer trial to illustrate the practical advantages of our approach. We believe that this method could be widely used to build prediction models or nomograms.

• The Korean Journal of Physiology and Pharmacology
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• 제28권2호
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• pp.121-127
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• 2024

Vancomycin is a frequently used antibiotic in intensive care units, and the patient's renal clearance affects the pharmacokinetic characteristics of vancomycin. Several advantages have been reported for vancomycin continuous intravenous infusion, but studies on continuous dosing regimens based on patients' renal clearance are insufficient. The aim of this study was to develop a vancomycin serum concentration prediction model by factoring in a patient's renal clearance. Children admitted to our institution between July 1, 2021, and July 31, 2022 with records of continuous infusion of vancomycin were included in the study. Sex, age, height, weight, vancomycin dose by weight, interval from the start of vancomycin administration to the time of therapeutic drug monitoring sampling, and vancomycin serum concentrations were analyzed with the linear regression analysis of the mixed effect model. Univariable regression analysis was performed using the vancomycin serum concentration as a dependent variable. It showed that vancomycin dose (p < 0.001) and serum creatinine (p = 0.007) were factors that had the most impact on vancomycin serum concentration. Vancomycin serum concentration was affected by vancomycin dose (p < 0.001) and serum creatinine (p = 0.001) with statistical significance, and a multivariable regression model was obtained as follows: Vancomycin serum concentration (mg/l) = -1.296 + 0.281 × vancomycin dose (mg/kg) + 20.458 × serum creatinine (mg/dl) (adjusted coefficient of determination, R² = 0.66). This prediction model is expected to contribute to establishing an optimal continuous infusion regimen for vancomycin.

• The Korean Journal of Applied Statistics
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• 제19권1호
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• pp.97-110
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• 2006

Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model. The weighted self-tuning estimator (WSTE) recently suggested by Lee (2004) has no more computational difficulty and it has the asymptotic normality and the high break-down point simultaneously. Although it has better properties than the other robust estimators, WSTE does not have full efficiency under the normal error model through the weighted least squares which is widely used. This paper introduces a new approach as called the reweighted WSTE (RWSTE), whose scale estimator is adaptively estimated by the self-tuning constant. A Monte Carlo study shows that new approach has better behavior than the general weighted least squares method under the normal model and the large data.

• The Korean Journal of Applied Statistics
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• 제22권6호
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• pp.1177-1190
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• 2009

The traffic operating speed is one of important information to measure a road capacity. When we supply the information of the road of high traffic by using navigation, offering the present traffic information and the forecasted future information are the outstanding functions to serve the more accurate expected times and intervals. In this study, we proposed the traffic speed forecasting model using the accumulated traffic speed data of the road and highway and forecasted the average speed for each the road and high interval and each time interval using Fourier transformation and time series regression model with trigonometrical function. We also propose the proper method of missing data imputation and treatment for the outliers to raise an accuracy of the traffic speed forecasting and the speed grouping method for which data have similar traffic speed pattern to increase an efficiency of analysis.

• Journal of Environmental Science International
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• 제32권9호
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• pp.659-669
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• 2023

The purpose of this study is to predict the pressure drop due to the installation of venturi under diverse operating conditions such as dust concentration, pulse interval and pressure, and filtration velocity using algebraic-linear regression model and use it as an economic data and efficient operating condition for a pulse air jet bag filter. A pilot scale bag filter with a filter a filter size(Ø140 × 850ℓ, 12) was used, and the filters used in the experiment were the polyester filters most commonly used in real industrial sites. The SAS 9.4 program (SAS Institute, USA) was used to predict and to determine the effects of inlet concentration (C_i), pulse interval (P_i) and pressure (P_p), filtration velocity (V_f), presence or absence of venturi, etc. The results are shown below. The variation in pressure drop with or without venturi installation was 38.8 mmAq when venturi is installed and 47.6 mmAq when venturi is not installed, indicating a difference in pressure drop of 8.8 mmAq depending on venturi installation. It is estimated that the efficiency can be improved by about 18.5% if the venturi is installed.

• Smart Structures and Systems
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• 제15권2호
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• pp.395-408
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• 2015

This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.

• Geomechanics and Engineering
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• 제29권5호
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• pp.523-533
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• 2022

Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R²≥0.79; whereas, a one-step prediction is R²≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R² and UPD is proposed. When UPD increases R² decreases exponentially; In particular, UPD at R²=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R² value targeted by an operator. Therefore, a calculation process for the equation between the R² and UPD is addressed.

• Nuclear Engineering and Technology
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• 제52권8호
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• pp.1807-1816
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• 2020

In this work, a Gaussian Process (Kriging) approach is proposed to provide efficient dose mapping for complex radiation fields using limited number of responses. Given a few response measurements (or simulation data points), the proposed approach can help the analyst in completing a map of the radiation dose field with a 95% confidence interval, efficiently. Two case studies are used to validate the proposed approach. The First case study is based on experimental dose measurements to build the dose map in a radiation field induced by a D-D neutron generator. The second, is a simulation case study where the proposed approach is used to mimic Monte Carlo dose predictions in the radiation field using a limited number of MCNP simulations. Given the low computational cost of constructing Gaussian Process (GP) models, results indicate that the GP model can reasonably map the dose in the radiation field given a limited number of data measurements. Both case studies are performed on the nuclear engineering radiation laboratories at the University of Sharjah.