• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.51-69
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• 2014

Times to multiple events (TMEs) are a major data type in large-scale business and medical data. Despite its importance, the analysis of TME data has not been well studied because of the analysis difficulty from censoring of observation. To address this difficulty, we have developed a Bayesian-based multivariate survival analysis method, which can successfully estimate the joint probability density of survival times. In this work, we extended this method for the analysis of precedence, dependency and causality among multiple events. We applied this method to the electronic health records of 2,111 patients in a children's hospital in the US and the proposed analysis successfully shows the relation between times to two types of hospital visits for different medical issues. The overall result implies the usefulness of the multivariate survival analysis method in large-scale big data in a variety of areas including marketing, human resources, and e-commerce. Lastly, we suggest our future research directions based multivariate survival analysis method.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.2
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• pp.70-79
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• 2020

The offshore installation units may be subjected to various accidental loads such as collision from supply vessels, impact from dropped objects, blast load from gas explosion and thermal load from fire. This paper deals with the design and strength evaluation method of the stiffened plate structures in response to a blast load caused by a gas explosion accident. It is a comprehensive review of various items used in actual project such as the size and type of the explosive loads, general design procedure/concept and analysis method. The structural analyses using simple analysis methods based on SDOF model and nonlinear finite element analysis are applied to the particular FPSO project. Also validation studies on the design guidance given by simple analysis method based on SDOF model have also considered several items such as backpressure effects, material behavior and duration time of the overpressure. A good correlation between the prediction made by simple analysis method based on SDOF model and nonlinear finite element analysis can be generally obtained up to the elastic limit.

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.220-232
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• 2007

Current geometric modeling and analysis are commonly based on B-Rep modeling and a finite elements method respectively. Furthermore, it is difficult to represent an object whose material property is heterogeneous using the B-Rep method because the B-Rep is basically used for homogeneous models. In addition, meshes are required to analyze a property of a model when the finite elements method is applied. However, the process of generating meshes from B-Rep is cumbersome and sometimes difficult especially when the model is deformed as time goes by because the topology of deforming meshes are changed. To overcome those problems in modeling and analysis including homogeneous and heterogeneous materials, we suggest a unified modeling and analysis method based on implicit representation of the model using R-function which is suggested by Rvachev. For implicit modeling of an object a distance field is approximated and blended for a complex object. Using the implicit function mesh-free analysis is possible where meshes are not necessary. Generally mesh-free analysis requires heavy computational cost compared to a finite elements method. To improve the computing time of function evaluation, we utilize GPU programming. Finally, we give an example of a simple pipe design problem and show modeling and analysis process using our unified modeling and analysis method.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.164-172
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• 2023

The grain size distribution of sand provides crucial information for understanding coastal erosion and sediment deposition. The commonly used sieve analysis for grain size distribution analysis has limitations such as time-consuming processes and the inability to obtain information about individual particle shapes and colors. In this study, we propose a grain size distribution analysis method using smartphone digital images, which is simpler and more efficient than the sieve analysis method. During the image analysis process, we effectively detect particles from relatively low-resolution smartphone digital images by extracting particle boundaries through image gradient calculation. Using samples collected from four beaches in Gyeongsangbuk-do, we compare and validate the proposed boundary extraction image analysis method with the analysis method that does not extract boundaries, against sieve analysis results. The proposed method shows an average error rate of 8.21% at D₅₀, exhibiting a 65% lower error compared to the method without boundary extraction. Therefore, grain size distribution analysis using smartphone digital images is convenient, efficient, and demonstrated accuracy comparable to sieve analysis.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.73-84
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• 1994

Output analysis is one of the most important fields of simulation to achieve the accurate simulation results. This study shows how to analyze simulation output data in the steady state using Procrustes analysis technique which has not been used in the field of simulation yet. In this paper Procrustes analysis method is used to perform the analysis of simulation output efficiently and effectively by applying the improved version of the method. The experiments are conducted using M/M/1 queueing simulation model. The results obtained by Procrustes analysis method show better estimates for average waiting times and average queue lengths which are closer to true values and narrower confidence intervals than when replication-deletion method is used. Also it requires the smaller number of simulation runs.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.6
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• pp.172-182
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• 2003

In this study, the back analysis was performed by means of stereo-net, plane failure and block failure method to collapsed fields among the rock slopes designed by standardized criterion, and the internal frictions from the back analysis were compared with those used to reinforcement design. It was concluded that in the result of the analysis by means of stereo net, plain failure and block failure methods, the internal frictions used to re-design of collapsed slope underestimated 10$^{\circ}$, 5$^{\circ}$ and 10$^{\circ}$ in average. At present, the internal friction on the design is used the experience value according to the state of weathering, but internal friction angle by the back analysis on collapsed slope with various methods were more reliable values than those from the present method. And it was concluded that re-design was made extravagantly because the internal friction used to re-design for reinforcement of the collapsed slope was less than back analysis.

• Journal of the Korean Society for Railway
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• v.7 no.4
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• pp.319-325
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• 2004

In this study, analysis and design programs of bending of RC beams strengthened with fiber sheets are developed by using Visual Basic Language. The program consists two groups, ultimate strength method and nonlinear flexural analysis method. Ultimate strength method regards concrete compressive stress as a rectangular stress block and do not consider tensile stress of concrete and load-deflection curves. On the other hand, nonlinear flexural analysis considers tensile stress of concrete, load-deflection curves, state of stress distribution and failure strain of strengthening material. Also, the analysis method used in this study regards nonlinear flexural stress as compressive stress of concrete. This program can be a good tool for determining the bending strength of strengthened RC beams and estimating the amount of fiber sheets for practical use.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1364-1369
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• 2009

The building construction projects include a variety of risk factors due to uncertainties. To succeed in the projects, it is important how risks are managed. Risk management is composed of identification, analysis and response. Especially, the risk analysis is important to objectively calculate significance of risk factors. This paper evaluates a method to find priorities of risks using the AHP(Analytic Hierarchy Process). The method has some defects; (1) the consistency becomes weak as the number of pair-wise compared risks is large, and (2) the input and output procedures are complex when risks are added to or removed from a risk database. Thus the paper adopt the PROMETHEE(Preference Ranking Organization METHod Enrichment Evaluations) analysis process which is able to overcome the limitation of the AHP restricted to 9 risk factors. The PROMETHEE method makes the procedure of risk analysis simple, when the risk factors pull out and put in the risk database. The purpose of this study is to prove the possibility of the PROMETHEE analysis process by being compared with AHP.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.720-725
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• 2000

This paper persents the characteristic analysis method of slotless-type Permanent Magnet Synchronous Motor using the analytical method. The results of analysis are compered with FEM to verify the validity of the proposed method.

• Advances in Computational Design
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• v.4 no.1
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• pp.15-32
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• 2019

One of the efficient and useful tools to achieve the optimal design of structures is employing the sensitivity analysis in the finite element model. In the numerical optimization process, often the semi-analytical method is used for estimation of derivatives of the objective function with respect to design variables. Numerical methods for calculation of sensitivities are susceptible to the step size in design parameters perturbation and this is one of the great disadvantages of these methods. This article uses complex variables method to calculate the sensitivity analysis and combine it with discrete sensitivity analysis. Finally, it provides a new method to obtain the sensitivity analysis for linear structures. The use of complex variables method for sensitivity analysis has several advantages compared to other numerical methods. Implementing the finite element to calculate first derivatives of sensitivity using this method has no complexity and only requires the change in finite element meshing in the imaginary axis. This means that the real value of coordinates does not change. Second, this method has the lower dependency on the step size. In this research, the process of sensitivity analysis calculation using a finite element model based on complex variables is explained for linear problems, and some examples that have known analytical solution are solved. Results obtained by using the presented method in comparison with exact solution and also finite difference method indicate the excellent efficiency of the proposed method, and it can predict the sustainable and accurate results with the several different step sizes, despite low dependence on step size.