• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4228-4237
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• 2023

The Improved Deterministic Truncation of Monte Carlo (iDTMC) is a powerful acceleration and variance reduction scheme in the Monte Carlo analysis. The concept of the iDTMC method and correlated sampling-based real variance estimation are briefly introduced. Moreover, the application of the iterative scheme to the correlated sampling is discussed. The iDTMC method is utilized in a 3-dimensional small modular reactor (SMR) model problem. The real variances of burnup-dependent criticality and power distribution are evaluated and compared with the ones obtained from 30 independent iDTMC calculations. The impact of the inactive cycles on the correlated sampling is also evaluated to investigate the consistency of the correlated sample scheme. In addition, numerical performances and sensitivity analysis on the real variance estimation are performed in view of the figure of merit of the iDTMC method. The numerical results show that the correlated sampling accurately estimates the real variances with high computational efficiencies.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.44-50
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• 2024

This paper offers an overview of matrix formation and calculation techniques within the framework of General Linear Models (GLMs). It takes a sequential approach, beginning with a detailed exploration of matrix formation and calculation methods in regression analysis and univariate analysis of variance (ANOVA). Subsequently, it extends the discussion to cover multivariate analysis of variance (MANOVA). The primary objective of this study was to provide a clear and accessible explanation of the underlying matrices that play a crucial role in GLMs. Through linking, essentially different statistical methods, by fundamental principles and algebraic foundations that underpin the GLM estimation. Insights presented here aim to assist researchers, statisticians, and data analysts in enhancing their understanding of GLMs and their practical implementation in diverse research domains. This paper contributes to a better comprehension of the matrix-based techniques that can be extended to GLMs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.97-100
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• 2004

We propose some properties of fuzzy multivariate analysis of variance by fuzzy vector operation with agreement index. We deals fuzzy null hypotheses and fuzzy alternative hypothesis and define the agreement index for the grades of the judgements that the hypothesis is rejection or acceptance. Finally, we provide an example to evaluate the judgements.

• Bulletin of the Korean Mathematical Society
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• v.51 no.3
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• pp.701-716
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• 2014

The limiting distribution for the linear placement statistics under the null hypotheses has been provided by Orban and Wolfe [9] and Kim [5] when one of the sample sizes goes to infinity, and by Kim, Lee and Wang [6] when the sample sizes of each group go to infinity simultaneously. In this paper we establish the generalized Kruskal-Wallis one-way analysis of variance for the linear placement statistics.

• KIEAE Journal
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• v.16 no.2
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• pp.17-22
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• 2016

Purpose: Sensitivity analysis offers a good guideline for designing energy conscious buildings, which is fitted to a specific building configuration. Sensitivity analysis is, however, still too expensive to be a part of regular design process. The One-at-a-time (OAT) is the most common and simplest sensitivity analysis method. This study aims to propose a reasonable ground that the OAT can be an alternative method for the variance-based method in some early design scenarios, while the variance-based method is known adequate for dealing with nonlinear response and the effect of interactions between input variables, which are most cases in building energy simulations. Method: A test model representing the early design phase is built in the DOE2 energy simulations. Then sensitivity ranks between the OAT and the Variance-based methods are compared at three U.S. sites. Result: Parameters in the upper rank by the OAT do not much differ from those by the Main effect index. Considering design practices that designers would chose the most energy saving design option first, this rank similarity between two methods seems to be acceptable in the early design phase.

• Journal of the Korea Society for Simulation
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• v.10 no.4
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• pp.41-50
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• 2001

When optimizing a complex system by determining the optimum condition of the system parameters of interest, we often employ the process of estimating the unknown objective function, which is assumed to be a second order spline function. In doing so, we normally use common random numbers for different set of the controllable factors resulting in more accurate parameter estimation for the objective function. In this paper, we will show some mathematical result for the analysis of variance when using common random numbers in terms of the regression error, the residual error and the pure error terms. In fact, if we can realize the special structure of the covariance matrix of the error terms, we can use the result of analysis of variance for the uncorrelated experiments only by applying minor changes.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.103-108
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• 2002

We consider an estimation of discontinuous variance function in nonparametric heteroscedastic random design regression model. We first propose estimators of a change point and jump size in variance function and then construct an estimator of entire variance function. We examine the rates of convergence of these estimators and give results on their asymptotics. Numerical work reveals that the effectiveness of change point analysis in variance function estimation is quite significant.

• Korean Journal of Clinical Laboratory Science
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• v.45 no.2
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• pp.60-65
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• 2013

Data from repeated measurements are accomplished through repeatedly processing the same subject under different conditions and different points of view. The power of testing enhances the choice of pertinent analysis methods that agrees with the characteristics of data concerned and the situation involved. Along with the clinical example, this paper compares the analysis of the variance on ex-post tests, gain score analysis, analysis by mixed design and analysis of covariance employable for repeating measure. Comparing the analysis of variance on ex post test, and gain score analysis on correlations, leads to the fact that the latter enhances the power of the test and diminishes the variance of error terms. The concluded probability, identified that the gain score analysis and the mixed design on interaction between "between subjects factor" and "within subjects factor", are identical. The analysis of covariance, demonstrated better power of the test and smaller error terms than the gain score analysis. Research on four analysis method found that the analysis of covariance is the most appropriate in clinical data than two repeated test with high correlation and ex ante affects ex post.

• Journal of Korean Academy of Nursing Administration
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• v.10 no.1
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• pp.141-159
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• 2004

Purpose: The purpose of this study was to investigate the degree of information technology application, and to identify the effect of information technology application en knowledge management process in clinical nurses. Method: Participants were 629 regular clinical nurses who had worked for over 1 year in general units of 9 tertiary medical hospitals including 2 national university hospitals, 5 university hospitals, and 2 hospitals founded by business enterprises. Data were collected from March to May 2003 through questionnaires. Thee structured instruments were used to collect the data: Information Technology Application scale, Knowledge Management Process Scale(Jeong, Lee, Lee, & Kim, 2003), and one for general characteristics. The data were analyzed using reliability analysis, descriptive analysis, one-way ANOVA, $Scheff{\acute{e}$ test, correlation analysis, partial correlation analysis, and multiple regression analysis with the SPSS for Windows 10,0 program. Result: 1) The HIS application degree, IT application ability, and IT application frequency were significantly correlated with the degree of knowledge management process activation and 4 elements of knowledge management process, Knowledge Creation, Knowledge Storage, Knowledge Sharing, and Knowledge Utilization(p=.000). 2) The 3 variables, HIS application degree, IT application ability, and IT application frequency explained 47.2% of the total variance of the degree of knowledge management process activation, and 352% of me total variance of Knowledge Storage. And 2 variables, HIS application degree and IT application frequency explained 17.6% of the total variance of Knowledge Creation, 39.9% of the total variance of Knowledge sharing, and 33.8% of the total variance of Knowledge utilization(p=.000). 3) As a result of multiple regression analysis, the key determinant of the degree of knowledge management process activation for nurses was HIS application degree The HIS application degree, IT application frequency, position, IT application ability, and continuous total numbers of years working at the present hospital explained 51.1% of the total variance of the degree of knowledge management process activation(p=.000). Conclusions: These results suggest that the information technology application positively affects the nurses' knowledge management process. From the above findings, information technology application is empirically verified as a useful and effective method to activate knowledge management process, and knowledge management.

• Atmosphere
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• v.16 no.4
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• pp.359-370
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• 2006

Terrain height variance spectra for the Korean mountain region are calculated in order to determine an adequate grid size required to resolve terrain forcing on mesoscale model simulation. One-dimensional spectral analysis is applied to specifically the central-eastern part of the Korean mountain region, where topographical-scale forcing has an important effect on mesoscale atmospheric flow. It is found that the terrain height variance spectra in this mountain region has a wavelength dependence with the power law exponents of 1.5 at the wavelength near 30 km, but this dependence is steeply changed to 2.5 at the wavelength less than 30 km. For the adequate horizontal grid size selection on mesoscale simulation two-dimensional terrain height spectral analysis is also performed. There is no directionality within 50% of spectral energy region, so one-dimensional spectral analysis can be reasonably applied to the Korea Peninsula. According to the spectral analysis of terrain height variance, the finer grid size which is higher than 6 km is required to resolve a 90% of terrain variance in this region. Numerical simulation using WRF (Weather Research and Forecasting Model) was performed to evaluate the effect of different terrain resolution in accordance with the result of spectral analysis. The simulated results were quantitatively compared to observations and there was a significant improvement in the wind prediction across the mountain region as the grid space decreased from 18 km to 2 km. The results will provide useful guidance of grid size selection on mesoscale topographical simulation over the Korean mountain region.