• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.395-402
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• 2006

In analyzing the nano-scale phenomena or behaviors of nano devices or materials, it is often desirable to deal with more atoms than can be treated only with a full atomistic simulation. However, even now, it is advisable to apply the atomistic simulation to the narrow region where the deformation field changes rapidly but to apply the conventional continuum model to the region far from that region. This equivalent continuum model can be formulated by applying the Cauchy-Born rule to the exact atomistic potential as in the quasicontinuum method. To couple the atomistic model with the equivalent continuum model, continuum displacements are conformed to the molecular displacements at the discrete positions of the atoms within the bridging domain. To satisfy the coupling constraints, we apply the Lagrange multiplier method. The continuum model in the bridging model should be applied on the region where the deformation field changes gradually. Then we can make the nodal spacing in the continuum model be much larger than the atomic spacing. In the first step, we generate the atomic-resolution mesh with the nodal spacing equal to the atomic spacing, and then we eliminate the nodal degrees of freedom adaptively using the node deactivation techniques. We eliminate more DOFs as the regions are more far from the atomistic region. Computing time and computational resources can be greatly reduced by the present node deactivation technique in multi scale analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.768-774
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• 2010

Reconstruction of implicit surfaces from scattered point data sets have been developed in various engineering and scientific studies. In this paper, we represent a method to construct functions of 2D point data using multi-scale kernels and show it can be applied to graphics applications needed to access data in real-time. Our approach is similar to previous work in that a set of coefficients of the functions are calculated and stored in the preprocessing stage and function values at arbitrary positions are evaluated for real-time applications, however, it is different from others in that users can choose detail levels freely in real-time processing stage. The reason why the functions implicitly supports multi-resolution results from the mathematical properties of multi-scale kernels, and proposed method can be expanded to represent multi-resolution functions of n-dimensional data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.335-343
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• 2001

The conventional wavelet-based fractal image coding has the disadvantage that the encoding takes a long time, since each range block finds the best domain in the image. In this Paper, we propose wavelet-based fractal image coding using SAS(Self Affine System) method and multi-scale factor. It consists of the range and domain blocks in DWT(discrete wavelet transform) region. Using SAS method, the proposed method is that the searching process of the domain block is not required, and the range block selects the domain which is relatively located the same position in the upper level. The proposed method can perform a fast encoding by reducing the computational complexity in the encoding process. In order to improve the disadvantage of SAS method which is reduced image qualify, the proposed method is improved image qualify using the different scale factors for each level. As a result, there is not influence on an image quality, the proposed method is enhanced the encoding time and compression ratio, and it is able to the progressive transmission.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.231-238
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• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.293-304
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• 2007

In this paper, we present a Krylov subspace based projection method for reduced-order modeling of large scale bilinear multi-input multi-output (MIMO) systems. The reduced-order bilinear system is constructed in such a way that it can match a desired number of moments of multi-variable transfer functions corresponding to the kernels of Volterra series representation of the original system. Numerical examples report the effectiveness of this method.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.4
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• pp.1-9
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• 2013

We propose a heuristic algorithm for war-game model that is appropriate for warfare in which the maneuver of the attacker is relatively certain. Our model is based on a multi-weapon extention of the Lanchester's square law. However, instead of dealing with the differential equations, we use a multi-period linear approximation which not only facilitates a solution method but also reflects discrete natures of warfare. Then our game model turns out to be a continuous game known to have an ${\varepsilon}$-Nash equilibrium for all ${\varepsilon}{\geq}0$. Therefore, our model approximates an optimal warfare strategies for both players as well as an efficient reinforcement of area defense system that guarantees a peaceful equilibrium. Finally, we report the performance of a practical best-response type heuristic for finding an ${\varepsilon}$-Nash equilibrium for a real-scale problem.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.281-286
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• 2024

This paper describes the solution method of Team AIRLAB used to participate in the League of Robot Runners Competition which tackles the problem of Lifelong Multi-agent Pathfinding (MAPF). In lifelong MAPF, multiple agents are tasked to navigate to their respective goal locations where new goals are consecutively revealed once they reach initial goals. The agents need to avoid collisions and deadlock situations while they navigate to perform tasks. Our method consists of (i) Puzzle Heuristics, (ii) MAPF-LNS2, and (iii) RHCR. The Puzzle Heuristics is our own algorithm that generates a compact heuristic table contributing to reduce memory consumption and computation time. MAPF-LNS2 and RHCR are state-of-the-art algorithms for MAPF. By combining these three algorithms, our method can improve the efficiency of paths for all agents significantly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.47-52
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• 2009

Many techniques to realize e-paper is proposed, but full requirement of e-paper is still not satisfied. In this paper, driven condition and gray scale representation method of e-paper is proposed. As a result of this study, multi-channel drive for allowing gray scale representation by cell is developed. And also drive circuit design for liquid powder display panel is developed.

• Computers and Concrete
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• v.29 no.6
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• pp.393-405
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• 2022

Lightweight concrete is a superior material due to its light weight and high strength. There however remain significant lacunae in engineering knowledge with regards to shear failure of lightweight fiber reinforced concrete beams. The main aim of the present study is to investigate the optimum usage of steel fibers in lightweight fiber reinforced concrete (LWFRC). Multi-scale finite element model calibrated with experimental results is developed to study the effect of steel fibers on the mechanical properties of LWFRC beams. To decrease the amount of steel fibers, it is preferred to reinforce only the middle section of the LWFRC beams, where the flexural stresses are higher. For numerical simulation, a multi-scale finite element model was developed. The cement matrix was modeled as homogeneous and uniform material and both steel fibers and lightweight coarse aggregates were randomly distributed within the matrix. Considering more realistic assumptions, the bonding between fibers and cement matrix was considered with the Cohesive Zone Model (CZM) and its parameters were determined using the model update method. Furthermore, conformity of Load-Crack Mouth Opening Displacement (CMOD) curves obtained from numerical modeling and experimental test results of notched beams under center-point loading tests were investigated. Validating the finite element model results with experimental tests, the effects of fibers' volume fraction, and the length of the reinforced middle section, on flexural and residual strengths of LWFRC, were studied. Results indicate that using steel fibers in a specified length of the concrete beam with high flexural stresses, and considerable savings can be achieved in using steel fibers. Reducing the length of the reinforced middle section from 50 to 30 cm in specimens containing 10 kg/m3 of steel fibers, resulting in a considerable decrease of the used steel fibers by four times, whereas only a 7% reduction in bearing capacity was observed. Therefore, determining an appropriate length of the reinforced middle section is an essential parameter in reducing fibers, usage leading to more affordable construction costs.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1212-1223
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• 2022

Skin lesions are common diseases that range from skin rashes to skin cancer, which can lead to death. Note that early diagnosis of skin diseases can be important because early diagnosis of skin diseases considerably can reduce the course of treatment and the harmful effect of the disease. Recently, the development of computer-aided diagnosis (CAD) systems based on artificial intelligence has been actively made for the early diagnosis of skin diseases. In a typical CAD system, the accurate classification of skin lesion types is of great importance for improving the diagnosis performance. Motivated by this, we propose a novel deep ensemble classification with multi-scale attention networks. The proposed deep ensemble networks are jointly trained using a single loss function in an end-to-end manner. In addition, the proposed deep ensemble network is equipped with a multi-scale attention mechanism and segmentation information of the original skin input image, which improves the classification performance. To demonstrate our method, the publicly available human skin disease dataset (HAM 10000) and the private animal skin lesion dataset were used for the evaluation. Experiment results showed that the proposed methods can achieve 97.8% and 81% accuracy on each HAM10000 and animal skin lesion dataset. This research work would be useful for developing a more reliable CAD system which helps doctors early diagnose skin diseases.