• The korean journal of orthodontics
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• v.34 no.5 s.106
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• pp.371-379
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• 2004

The purpose of this study was to investigate the changes and types of statistical methods used in the Korean Journal of Orthodontics (KJO) and the American Journal of Orthodontics and Dentofacial Orthopedics (AJODO) from )999 to 2003. The frequency of use, transitions, assumption check of statistical methods and types of advanced statistical methods were examined from each journal. The study consisted of 247 articles published in the KJO and randomly chosen 50 articles per year which were original articles and used statistical methods T-test, analysis of variance(ANOVA), correlation analysis, nonparametric analysis. regression analysis chi-square test. factor analysis, were the order of statistical methods most frequently used in the KJO, while t-test. ANOVA, nonparametric analysis, correlation analysis, regression analysis, chi-square test. factor analysis. were the order of statistical methods used in the AJODO The changes of statistical methods observed in the KJO were not significant $(X^2=17.4\;p=0.5881)$ but the changes observed in the AJODO was seen to be significant $(x^2=42.4,\;p=0.0397)$ Some of the studies examined had overlooked the assumptions of the statistical methods employed. Data investigation such as outlier should be performed before analysis and alternative statistical approaches are applied for a small sample size. Types of advanced statistical methods were factor analysis and discriminant analysis in the KJO and Intention-To-Treat (ITT) analysis in clinical trials through multi-center, survival analysis and Generalized Estimating Equations (GEE) in the AJODO. Appropriate analysis approaches and interpretations should be applied for the correlated and repeated measurements of the orthodontic data set.

• Culinary science and hospitality research
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• v.21 no.6
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• pp.49-62
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• 2015

Give that statistical analysis is an essential component of foodservice-related research, the purpose of this review is to analyse research trends of statistical methods applied to foodservice-related research. To achieve these objective, this study carried out a content analysis on a total of 251 out of 415 research articles published in The Korean Journal of Culinary Research(TKJCR) from January 2010 to December 2013. Of the total 164 research articles focussing on natural science research, qualitative research, articles written in English were excluded from the scope of this study. The results of this study are as follows. First, it turned out that 269 research articles applied quantitative research methods, and only 10 articles applied qualitative research methods among the 279 research articles based on social science research methods. Second, 20 article (8.0%) among the 251 did not specify the statistical methods or computer programs that were used for statistical analysis. Third, it was found that 228 articles (90.8%) used the SPSS program for data analysis. Fourth, in terms of frequency of use, it was revealed frequency analysis was most used, followed in order by reliability analysis, exploratory factor analysis, correlation analysis, regression analysis, structural equation modeling, confirmatory factor analysis, t-test, variance analysis, and cross tabs analysis, However, 3 out of 56 research articles that used a t-test did not suggest a t-value. 10 out of 64 articles that used ANOVA and demonstrated a significant difference in between-group mean did not conducted post-hoc test. Therefore, the researchers with interest in foodservice fields need to keep in mind that choosing and applying the correct statistical technique both determine the value and the success or failure of a study. To enhance the value and success of a study, it is necessary to use the proper statistical technique in an efficient way in order to prevent statistical errors.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.1000-1011
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• 2005

This paper presents a system for medical statistical analysis that helps medical professionals analyze clinical data more easily and accurately. It is able to recommend proper methods according to the distribution of sample data, and provides guide maps composed of icons for the understanding of the process of analysis. Besides general statistical analysis, it includes commonly-used statistical methods for medical fields, such as survival analysis and methods for repetitive measurements. The results of analysis are interactively displayed by 3D glyph-based visualization with uncertainty.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.217-222
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• 2005

We come to know that recent seismic design is used in the railway bridge design by several analysis methods. The result of the analysis in each method is very different from each other, so very weak structures or very exaggerated structures are designed for earthquake. In this paper, by conducting seismic analysis of 25m PSC beam bridge mainly used in railway bridge, we compared and analyzed the difference of the result of the analysis methods. As a result, we could find that moment varies from $53\%\;to\;151\%$ depending on geometrical shape of bridge or seismic analysis method.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.95-106
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• 2005

Complete-case analysis is easy to carry out and it may be fine with small amount of missing data. However, this method is not recommended in general because the estimates are usually biased and not efficient. There are numerous alternatives to complete-case analysis. A natural alternative procedure is available-case analysis. Available-case analysis uses all cases that contain the variables required for a specific task. The EM algorithm is a general approach for computing maximum likelihood estimates of parameters from incomplete data. These methods and multiple imputation(MI) are reviewed and the performances are compared by simulation studies in monotone missing pattern.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.5
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• pp.513-525
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• 2016

To propose an effective ensemble methods in predicting $PM_{10}$ concentration, six experiments were designed by different ensemble average methods (e.g., non-weighted, single weighted, and cluster weighted methods). The single weighted method was calculated the weighted value using both multiple regression analysis and singular value decomposition and the cluster weighted method was estimated the weighted value based on temperature, relative humidity, and wind component using multiple regression analysis. The effects of ensemble average methods were significantly better in weighted average than non-weight. The results of ensemble experiments using weighted average methods were distinguished according to methods calculating the weighted value. The single weighted average method using multiple regression analysis showed the highest accuracy for hourly $PM_{10}$ concentration, and the cluster weighted average method based on relative humidity showed the highest accuracy for daily mean $PM_{10}$ concentration. However, the result of ensemble spread analysis showed better reliability in the single weighted average method than the cluster weighted average method based on relative humidity. Thus, the single weighted average method was the most effective method in this study case.

• KIEAE Journal
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• v.16 no.1
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• pp.81-87
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• 2016

Purpose: Heat transfers phenomena are described by the second order partial differential equation and its boundary conditions. In a three-dimensional structure of a building, the heat transfer phenomena generally include more than one material, and thus, become complicate. The analytic solutions are useful to understand heat transfer phenomena, but they can hardly be applied in engineering or design problems. Engineers and designers have generally been forced to use numerical methods providing reliable results. Finite volume methods with the unstructured grid system is only the suitable means of the analysis for the complex and arbitrary domains. Method: To obtain an numerical solution, a discretization method, which approximates the differential equations, and the interpolation methods for temperature and heat flux between two or more materials are required. The discretization methods are applied to small domains in space and time, and these numerical solutions form the descretized equations provide approximated solutions in both space and time. The accuracy of numerical solutions is dependent on the quality of discretizations and size of cells used. The higher accuracy, the higher numerical resources are required. The balance between the accuracy and difficulty of the numerical methods is critical for the success of the numerical analysis. A simple and easy interpolation methods among multiple materials are developed. The linear equations are solved with the BiCGSTAB being a effective matrix solver. Result: This study provides an overview of discretization methods, boundary interface, and matrix solver for the 3-dimensional numerical heat transfer including two materials.

• Computational Structural Engineering
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• v.7 no.1
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• pp.109-116
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• 1994

In this paper, various reliability analysis methods for calculating a probability of failure are investigated for their accuracy and efficiency. Crude Monte Carlo method is used as a basis for the comparison of various numerical results. For the sampling methods, Importance Sampling method and Directional Simulation method are considered for overcoming a drawback of Crude Monte Carlo method. For the approximate methods, conventional Rackwitz-Fiessler method. 3-parameter Chen-Lind method, and Rosenblatt transformation method are compared on the basis of First order reliability method. As a Second-order reliability method, Curvature-Fitting paraboloid method, Point-fitting paraboloid method, and Log-likelihood function method are explored in order to verify the accuracy of the reliability calculation results. These methods mentioned above would have some difficulty unless the limit state equation is expressed explicitly in terms of random design variables. Thus, there is a need to develop some general reliability methods for the case where an implicit limit state equation is given. For this purpose, Response surface method is used where the limit state equation is approximated by regression analysis of the response surface outcomes resulted from the structural analysis. From the application of these various reliability methods to three examples, it is found that Directional Simulation method and Response Surface method are very efficient and recommendable for the general reliability analysis problem cases.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.113-124
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• 2024

Background: The increasing need to minimize animal testing has sparked interest in alternative methods with more humane, cost-effective, and time-saving attributes. In particular, in silico-based computational toxicology is gaining prominence. Adverse outcome pathway (AOP) is a biological map depicting toxicological mechanisms, composed of molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). To understand toxicological mechanisms, predictive models are essential for AOP components in computational toxicology, including molecular structures. Objectives: This study reviewed the literature and investigated previous research cases related to AOP and in silico methodologies. We describe the results obtained from the analysis, including predictive techniques and approaches that can be used for future in silico-based alternative methods to animal testing using AOP. Methods: We analyzed in silico methods and databases used in the literature to identify trends in research on in silico prediction models. Results: We reviewed 26 studies related to AOP and in silico methodologies. The ToxCast/Tox21 database was commonly used for toxicity studies, and MIE was the most frequently used predictive factor among the AOP components. Machine learning was most widely used among prediction techniques, and various in silico methods, such as deep learning, molecular docking, and molecular dynamics, were also utilized. Conclusions: We analyzed the current research trends regarding in silico-based alternative methods for animal testing using AOPs. Developing predictive techniques that reflect toxicological mechanisms will be essential to replace animal testing with in silico methods. In the future, since the applicability of various predictive techniques is increasing, it will be necessary to continue monitoring the trend of predictive techniques and in silico-based approaches.

• Nuclear Engineering and Technology
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• v.11 no.3
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• pp.219-229
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• 1979

The current status of the computational methods and computer codes for the analysis of reactor kinetics is reviewed. Computational methods which have been developed for space-dependent transient analyses are presented and recent progress in the development of methods is discussed.