• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.1
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• pp.1-8
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• 2014

Using the level set and the meshfree methods, we develop a topological shape optimization method applied to linear elasticity problems. Design gradients are computed using an efficient adjoint design sensitivity analysis(DSA) method. The boundaries are represented by an implicit moving boundary(IMB) embedded in the level set function obtainable from the "Hamilton-Jacobi type" equation with the "Up-wind scheme". Then, using the implicit function, explicit boundaries are generated to obtain the response and sensitivity of the structures. Global nodal shape function derived on a basis of the reproducing kernel(RK) method is employed to discretize the displacement field in the governing continuum equation. Thus, the material points can be located everywhere in the continuum domain, which enables to generate the explicit boundaries and leads to a precise design result. The developed method defines a Lagrangian functional for the constrained optimization. It minimizes the compliance, satisfying the constraint of allowable volume through the variations of boundary. During the optimization, the velocity to integrate the Hamilton-Jacobi equation is obtained from the optimality condition for the Lagrangian functional. Compared with the conventional shape optimization method, the developed one can easily represent the topological shape variations.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.125-131
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• 2021

The problem of determining the maintenance point which minimizes the process-related total cost is called the 'process mean shift problem'. By expanding and integrating the existing maintenance models that have been partially progressed, we present a expanded and integrated maintenance model which reflects the production site where various situations occur. To implement this, we set both the upper and lower limits of the product specification, and adopted the quality loss function for conforming items. Also, we set the process variance of the wear level as a function rather than a constant. In this study, we developed two general functions to the wear level. One is about the production volume and the other is maintenance cost. As a result, this study is expected to be a maintenance model that can be applied to various processes. In the future, this study can be developed as a profit maximization model by adding profit items from product sales, and expansion to a maintenance model that introduces failure to the model of this study can be considered.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.235-247
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• 1993

The predictive density function of a potential future observation and its first four moments are obtained in this paper to study the effects of a non-normal prior of the unknown mean of a normal population. The derived predictive density function is modified to study changes in utility curves, used to choose the optimum treatment from a given set of treatments, at a given level of stimulus due to slight deviations from normality of the prior distribution. Numerical illustrations are provided to exhibit some effectsl.

• Proceedings of the Korea Association of Information Systems Conference
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• 1996.11a
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• pp.211-216
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• 1996

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, an architecture o fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so 솜 t the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1996.10a
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• pp.211-216
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• 1996

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, an architecture of fuzzy nerual networks with fuzzy weights and fuzzy biases is shown. Next a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value.A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.137-140
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• 2002

This paper presents a new variational framework for detecting and tracking moving objects in image sequence. Motion detection is performed using Level Set Model. The original frame is used to provide th moving object boundaries Then, the detection and the tracking problem are addressed in a common framework that employs a inward-outward curve evolution function. This function is minimized using a gradient decent method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6B
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• pp.379-385
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• 2012

Recent development of computing power and theoretical advances in computational fluid dynamics have made possible numerical simulations of water waves with full Navier-Stokes equations. In this study, an internal wave maker using the mass source function approach was combined with the level set finite element method for generation of waves. The model is first applied to the two-dimensional linear wave generation and propagation. Then, it is applied to the three-dimensional simulation of the same problem. To effectively utilize computational resources and enhance the speed of execution, parallel algorithms are developed and applied for the three-dimensional problem. The results of numerical simulations are compared with theoretical values and good agreements are observed.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.6 s.144
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• pp.583-592
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• 2005

The turbulent free surface flow around a self-propelled KRISO 138K LNG Carrier is numerically simulated using the finite volume based multi-block RANS code, WAVIS developed at HRISO. The realizable k-$\varepsilon$ turbulence model with a wail function is employed for the turbulence closure. The free surface is captured with the Level-Set method and body forces are used to model the effects of a propeller without resolving the detail blade flow. In order to obtain an accurate free surface solution and stable convergence, the computations are executed with a proper fine grid refinement around the free surface and with an adoption of implicit discretization scheme for the Level-Set formulation. The computed velocity vectors at the several stations and wave patterns show a good agreement with the experimental results measured at the KRISO towing tank.

• Steel and Composite Structures
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• v.44 no.5
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• pp.633-649
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• 2022

This paper is first implemented with the bending behavior of three-dimensional functionally graded (3DFG) plates in the framework of level set-based topology optimization (LS-based TO). Besides, due to the suitable properties of the current design domain, the thin-plate spline (TPS) is recognized as a RBF to construct the LS function. The overall mechanical properties of the 3DFG plate are assessed using a power-law distribution scheme via Mori-Tanaka micromechanical material model. The bending response is obtained using the first-order shear deformation theory (FSDT). The mixed interpolation of four elements of tensorial components (MITC4) is also implemented to overcome a well-known shear locking problem when the thickness becomes thinner. The Hamilton-Jacobi method is utilized in each iteration to enforce the necessary boundary conditions. The mathematical formulas are expressed in great detail for the LS-based TO using 3DFG materials. Several numerical examples are exhibited to verify the efficiency and reliability of the current methodology with the previously reported literature. Finally, the influences of FG materials in the optimized design are explained in detail to illustrate the behaviors of optimized structures.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.43-48
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• 2003

We consider a consumption and investment problem where an investor's investment opportunity gets enlarged when she becomes rich enough, i.e., when her wealth touches a critical level. We derive optimal consumption and investment rules assuming that the investor has a time-separable von Neumann-Morgenstern utility function. An interesting feature of optimal rules is that the investor consumes less and takes more risk in risky assets if the investor expects that she will have a better investment opportunity when her wealth reaches a critical level.