• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.12
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• pp.2110-2117
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• 2003

A physics-based material removal model in various scales is described and a feature scale simulation for a chemical mechanical polishing (CMP) process is performed in this work. Three different scales are considered in this model, i.e., abrasive particle scale, asperity scale and wafer scale. The abrasive particle and the asperity scales are combined together and then homogenized to result in force balance conditions to be satisfied in the wafer scale using an extended Greenwood-Williamson and Whitehouse-Archard statistical model that takes into consideration the joint distribution of asperity heights and asperity tip radii. The final computation is made to evaluate the material removal rate in wafer scale and a computer simulation is performed for detailed surface profile variations on a representative feature. The results show the dependence of the material removal rate on the joint distribution, applied external pressure, relative velocity, and other operating conditions and design parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4098-4116
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• 2020

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.34.1-34.1
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• 2011

Combining a detailed non-grey radiative transfer computation with the three dimensional hydrodynamics, we investigate a reliable numerical scheme for turbulent convection in the solar surface. The solar photosphere is the extremely turbulent region composed of partly ionized compressible gases in high temperature. Especially, the super adiabatic layer (SAL) near the solar photosphere is the shallow transition region where the energy transport varies steeply from convection to radiation. In order to describe physical processes accurately, a detailed treatment of radiative transfer should be considered as well as the high resolution computation of fluid dynamics. For a direct computation of radiation fields, the Accelerated Lambda Iteration (ALI) methods have been applied to hydrodynamical medium, incorporating the Opacity Distribution Function (ODF) as a realistic schemes for non-grey problems. Computational domain is the rectangular box of dimensions $42{\times}3Mn$ with the resolution of $1202{\times}190$ meshed grids, which covers several granules horizontally and 8 ~ 9 pressure scale heights vertically. During several convective turn-over times, the 3-D snapshots have been compiled with a second order accuracy. In addition, our radiation-hydrodynamical computation has been compared with the classical approximations such as grey atmospheres and Eddington approximation.

• Structural Engineering and Mechanics
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• v.64 no.6
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• pp.695-701
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• 2017

This paper investigates some general properties in the degenerate scale problem of antiplane elasticity or Laplace equation. For a given configuration, the degenerate scale problem is solved by using conformal mapping technique, or by using the null field BIE (boundary integral equation) numerically. After solving the problem, we can define and evaluate the degenerate area which is defined by the area enclosed by the contour in the degenerate configuration. It is found that the degenerate area is an important parameter in the problem. After using the conformal mapping, the degenerate area can be easily evaluated. The degenerate area for many configurations, from triangle, quadrilles and N-gon configuration are evaluated numerically. Most properties studied can only be found by numerical computation. The investigated properties provide a deeper understanding for the degenerate scale problem.

• International journal of advanced smart convergence
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• v.7 no.2
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• pp.95-100
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• 2018

In this paper, we propose a binarized multi-scale module to accelerate the speed of the pose estimating deep neural network. Recently, deep learning is also used for fine-tuned tasks such as pose estimation. One of the best performing pose estimation methods is based on the usage of two neural networks where one computes the heat maps of the body parts and the other computes the part affinity fields between the body parts. However, the convolution filtering with a large kernel filter takes much time in this model. To accelerate the speed in this model, we propose to change the large kernel filters with binarized multi-scale modules. The large receptive field is captured by the multi-scale structure which also prevents the dropdown of the accuracy in the binarized module. The computation cost and number of parameters becomes small which results in increased speed performance.

• Particle and aerosol research
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• v.5 no.2
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• pp.45-52
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• 2009

Black carbon, which is a by-product of combustion of fossil fuel and biomass burning, is the component that imposes the largest uncertainty on quantifying aerosol climate effect. The direct, indirect and semi-direct climate effects of black carbon depend on its state of the mixing with other water-soluble aerosol components. The process that transforms hydrophobic externally mixed black carbon particles into hygroscopic internally mixed ones is called "aging". In most climate models, simple parameterizations for the aging time scale are used instead of solving detailed dynamics equations on the aging process due to the computation cost. In this study, a new parameterization for the black carbon aging time scale due to condensation and coagulation is presented as a function of the concentration of hygroscopic atmospheric components and the black carbon particle size. It is shown that the black carbon aging time scale due to condensation of sulfuric acid vapors varies to a large extent depending on the sulfuric acid concentration and the black carbon particle size. This result indicates that the constant aging time scale values suggested in the literature cannot be directly applied to a global scale modeling. The aging time scale due to coagulation with internally mixed aerosol particles shows an even stronger dependency on particle size, which implies that the use of a particle-size-independent aging time scale may lead to a large error when the aging is dominated by coagulation.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.455-460
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• 2006

This paper presents the convergency property of the Auxiliary Problem Principle when it is applied to large-scale Optimal Power Flow problems with Distributed or Parallel computation features. The key features and factors affecting the convergence ratio and solution stability of APP are also analyzed.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.117-126
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• 2003

GA(genetic algorithm) has a powerful searching ability and is comparatively easy to use and to apply as well. By that reason, GA is in the spotlight these days as an optimization skill for mechanical systems.$^1$However, GA has a low efficiency caused by a huge amount of repetitive computation and an inefficiency that GA meanders near the optimum. It also can be shown a phenomenon such as genetic drifting which converges to a wrong solution.$^{8}$ These defects are the reasons why GA is not widdy applied to real world problems. However, the low efficiency problem and the meandering problem of GA can be overcomed by introducing parallel computation$^{7}$ and gray code$^4$, respectively. Standard GA(SGA)$^{9}$ works fine on small to medium scale problems. However, SGA done not work well for large-scale problems. Large-scale problems with more than 500-bit of sere's have never been tested and published in papers. In the result of using the SGA, the powerful searching ability of SGA doesn't have no effect on optimizing the problem that has 96 design valuables and 1536 bits of gene's length. So it converges to a solution which is not considered as a global optimum. Therefore, this study proposes ExpGA(experience GA) which is a new genetic algorithm made by applying a new probability parameter called by the experience value. Furthermore, this study finds the solution throughout the whole field searching, with applying ExpGA which is a optimization technique for the structure having genetic drifting by the standard GA and not making a optimization close to the best fitted value. In addition to them, this study also makes a research about the possibility of GA as a optimization technique of large-scale design variable problems.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2359-2364
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• 2017

This paper proposes a scale factor based range estimation method using a sum of squares (SOS) method. Many previous studies measured distance by using a camera, which usually required two cameras and a long computation time for image processing. To overcome these disadvantages, we propose a range estimation method for an object using a single moving camera. A SOS-based Luenberger observer is proposed to estimate the range on the basis of the Euclidean geometry of the object. By using a scale factor, the proposed method can realize a faster operation speed compared with the previous methods. The validity of the proposed method is verified through simulation results.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.276-278
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• 1992

This paper presents a method of hierachical optimal control for time invariant large scale systems via Single Term Walsh Series. It is well known that the optimal control of a large scale system with quadratic performance criteria often involves the determination of time varying feedback gain matrix by solving the matrix Riccati differential equation, which is usually quite difficult. Therefore, in order to solve the problem, this paper is introduced to Single Term Walsh Series. The advantages of proposed method are simple and attractive for the control of large scale system in computation.