• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.419-437
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• 1995

Given the specific mean shift outlier model, several standard approaches to obtaining test statistic for outliers are discussed. Each of these is developed in detail for the nonlinear regression model, and each leads to an equivalent distribution. The geometric interpretations of the statistics and accuracy of linear approximation are also presented.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.201-208
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• 1993

Given the specific mean shift outlier model, the score test for multiple outliers in nonlinear regression is discussed as an alternative to the likelihood ratio test. The geometric interpretation of the score statistic is also presented.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.143-152
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• 1999

In Shewhart control chart, the average run length(ARL) is calculated using the mean of a conventional geometric distribution(CGD) assuming a sequence of identical and independent Bernoulli trials. In this, the success probability of CGB is the probability that any point exceeds the control limits. When the process is in-control state, there is no problem in the above assumption since the probability that any point exceeds the control limits does not change if the in-control state continues. However, if the out-of-control state begins and continues during the process, the probability of exceeding the control limits may take two forms. First, once the out-of-control state begins with exceeding probability p, it continues with the same exceeding probability p. Second, after the out-of-control state begins, the exceeding probabilities may very according to some pattern. In the first case, ARL is the mean of CGD with success probability p as usual. But in the second case, the assumption of a sequence of identical and independent Bernoulli trials is invalid and we can not use the mean of CGD as ARL. This paper concentrate on that point. By adopting one generalized binomial distribution(GBD) model that allows correlated Bernoulli trials, generalized geometric distribution(GGD) is defined and its mean is derived to find an alternative ARL when the process is in out-of-control state and the exceeding probabilities take the second form mentioned in the above. Small-scale simulation is performed to show how an alternative ARL works.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.5
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• pp.197-212
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• 1997

The performance of a torque converter can be expressed by the performance parameters such as flow radius and flow angle, on the mean flow path. The geometric analysis of the torque converter is required to determine these parameters for the modeling of the torque converter. In general, the blade shape is depicted by three dimensional data at the mid-surface of blade or those of the pressure and suction side. To generate three dimensional model of the blade using the data mentioned above, a consistent data format and a shape generation algorithm are required. This paper presents a useful consistent data format of the blades and an algorithm for the geometrical shape generation. By the geometric analysis program to which the shape generation algorithm is embedded, the variation of blade angles in rotating element analyzed. Then finally, the analyzed results of geometric profile of a blade are compared with those of the blade design principle, so called forced vortex theorem.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.49-60
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• 2011

The geometric process (GP) has been widely used for modeling failure and repair time sequences of repairable systems. The GP is mathematically tractable but restrictive in reliability applications since it actually assumes that the mean function of inter-failure times sequence asymptotically decreases to zero; and the mean function of successive repair times sequence asymptotically increases to infinity. This is generally unrealistic from an engineering perspective. This paper presents three extended GP models for modeling reliability deterioration and improvement (or growth) process. The extensions maintain the advantage of mathematical tractability of GP model. Their usefulness and appropriateness are illustrated with three real-world examples.

• Earthquakes and Structures
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• v.25 no.6
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• Spatial Information Research
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• v.20 no.2
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• pp.117-127
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• 2012

The purpose of this study is to develop the auto-building algorithm of the Geometric Network Model(GNM), a topology model including geometric information because of the need to reflect the features' geometric characteristic into the topology model, which is for development of indoor 3D virtual model enabling queries. As the critical algorithm, the Straight Medial Axis Transformation(SMAT) algorithm is proposed in order to automatically extract the medial axis of features. The SMAT algorithm is generalized from the existing S-MAT algorithm and a range of target features where applicable is extended from simple polygons to weakly simple polygons which mean the polygons containing the inner ring inside. The GNM built automatically is finally printed out as the .csv file for easy access and w ide application in other systems. This auto-building algorithm of the GNM is available for plenty of cases such as finding a shortest path, guiding a route in emergency situation, and semantic analysis.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.131-140
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• 1998

The objective of this study is to propose a new procedure to synthesize the multi-experts priorities in AHP. If multi-experts with different expertise are involved in a AHP decision, we need some way to aggregate their opinions. AHP model used to do numerical aggregation by taking only the geometric mean or the weighting geometric mean in past. To aggregate the multi-experts priorities, In this paper. we suggest a way which Decision Maker can exclude outlier matrix from group using the concept of the Compatibility and we Introduce Delphi method to use Compatibility in AHP. A numerical example is shown to illustrate the procedure.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.447-460
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• 2006

This paper develops a multiple comparison method for finding an optimal ordering of K geometric means of exponential parameters. This is based on the paired comparison experimental arrangement whose results can naturally be represented by a completely oriented graph. Introducing posterior preference probabilities and stochastic transitivity conditions to the graph, we obtain a new graphical model that yields criteria for the optimal ordering in the multiple comparison. Necessary theories involved in the method and some computational aspects are provided. Some numerical examples are given to illustrate the efficiency of the suggested method.

• Current Optics and Photonics
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• v.6 no.2
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• pp.161-170
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• 2022

Three-dimensional (3D) geometric models are introduced to correct vignetting, and a downhill simplex search is applied to determine the coefficients of a 3D model used in digital microscopy. Vignetting is nonuniform illuminance with a geometric regularity on a two-dimensional (2D) image plane, which allows the illuminance distribution to be estimated using 3D models. The 3D models are defined using generalized polynomials and arbitrary coefficients. Because the 3D models are nonlinear, their coefficients are determined using a simplex search. The cost function of the simplex search is defined to minimize the error between the 3D model and the reference image of a standard white board. The conventional and proposed methods for correcting the vignetting are used in experiments on four inspection systems based on machine vision and microscopy. The methods are investigated using various performance indices, including the coefficient of determination, the mean absolute error, and the uniformity after correction. The proposed method is intuitive and shows performance similar to the conventional approach, using a smaller number of coefficients.