• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.27-44
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• 2001

A fast Poisson solver on irregular domains, based on bound-ary methods, is presented. The harmonic polynomial approximation of the solution of the associated homogeneous problem provides a good practical boundary method which allows a trivial parallel processing for solution evaluation or straightfoward computations of the interface values for domain decomposition/embedding. AMS Mathematics Subject Classification : 65N35, 65N55, 65Y05.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.6
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• pp.70-77
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• 1984

This paper represents a fast computational algorithm for the discrete sine transform defined by Kekre and Solanki. Techniques are developed to factor the discrete sine trans form matrix into M=log2 2N matrices, where the number(N) of sampled data points is a power of two. Each factorial matrix contains not more than two non-zero real elem tints in any row or column. As a result of this method, the exact a배orithm for the fast discrete sine transform is accomplished. The algorithm is illustiated by a signal flow graph, which may be readily translated to hardware or software implementation.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2002.11a
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• pp.375-379
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• 2002

본 논문에서는 수 만개이상의 미지수를 필요로 하는 복잡한 3차원 구조에서의 정전용량 추출을 위한 고속화 알고리즘(Fast mutilpole method)과 결합한 효과적인 적응 삼각요소 분할법(Adaptive triangular mesh refinement algorithm)을 제안하였다. 요소세분화과정은 초기요소로 전하의 분포를 구하고, 전하밀도가 높은 영역에서의 요소세분화를 수행하여 이루어진다. 제안된 방법을 이용하여 많은 미지수를 필요로 하는 IC packaging 구조에서의 정전용량을 추출하였다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.6
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• pp.957-960
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• 1986

Two fast methods for a Sobel operator with four directional masks are proposed. They reduce the computation time more than 50% at the expense of a small extra storage locations. Comparisons of the original method and the proposed fast methods are included.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.6
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• pp.619-625
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• 2009

FastSLAM which uses the Rao-Blackwellized particle filter is one of the famous solutions to SLAM (Simultaneous Localization and Mapping) problem that estimates concurrently a robot's pose and surrounding environment. However, the particle depletion problem arises from the loss of the particle diversity in the resampling process of FastSLAM. Then, the performance of FastSLAM degenerates over the time. In this work, DIR (Density Information-based Resampling) technique is proposed to solve the particle depletion problem. First, the cluster is constructed based on the density of each particle, and the density of each cluster is computed. After that, the number of particles to be reserved in each cluster is determined using a linear method based on the distance between the highest density cluster and each cluster. Finally, the resampling process is performed by rejecting the particles which are not selected to be reserved in each cluster. The performance of the DIR proposed to solve the particle depletion problem in FastSLAM was verified in computer simulations, which significantly reduced both the RMS position error and the feature error.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.1
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• pp.27-32
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• 2003

This paper describes to extend the fast algorithm fur the capacitance extraction of large three-dimensional object. The triangular meshes are used and refined adaptively in the area where the heavy charges reside in each iterative solving. This technique is applied to the capacitance extraction of a 68-pin cerquad package. The results show fast convergence, and this adaptive technique coupled with the fast algorithm is efficient to reduce the number of elements and computing time with least additional computational efforts in large three dimensional problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.66-78
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• 2012

This paper proposes a computation model of the quantity supplied to optimize inventory costs for the fast fashion. The model is based on a forecasting, a store and production capacity, an assortment planning and quick response model for fast fashion retailers, respectively. It is critical to develop a standardized business process and mathematical model to respond market trends and customer requirements in the fast fashion industry. Thus, we define a product supply model that consists of forecasting, assortment plan, store capacity plan based on the visual merchandising, and production capacity plan considering quick response of the fast fashion retailers. For the forecasting, the decomposition method and multiple regression model are applied. In order to optimize inventory costs. A heuristic algorithm for the quantity supplied is designed based on the assortment plan, store capacity plan and production capacity plan. It is shown that the heuristic algorithm produces a feasible solution which outperforms the average inventory cost of a global fast fashion company.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.669-672
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• 1998

In this paper, w epropose a fast fractal coding method based on correlation coefficients of subblocks in input image. In the proposed method, domain pool is selected based on correlation analysis of input image and the isometry transform for each block is chosen based on the IFS method. To investigate the performance of the proposed method, we compared image quality and encoding time with full search PIFS method and jacquin's PIFS method. Experimental results show that proposed method yields nearly the same performance in PSNR, and its encoding time is reduced for images size of 512*512 compared with full search PIFS method and jacquin's PIFS method.

• Investigative Magnetic Resonance Imaging
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• v.4 no.1
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• pp.42-51
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• 2000

Purpose: Projection-type Fast Spin Echo (PFSE) imaging is robust to patient motion or flow related artifact compared to conventional Fast Spin Echo (FSE) imaging, however, it has difficulty in controlling $T_2$ contrast. In this paper, Tz contrast in the PFSE method is analyzed and compared with those of the FSE method with various effective echo times by computer simulation. The contrasts in the FSE and PFSE methods are also compared by experiments with volunteers. From the analysis and simulation, it is shown that ${T_2}-weighted$ images can well be obtained by the PFSE method proposed. Materials and methods: Pulse sequence for the PFSE method is implemented at a 1.0 Tesla whole body MRI system and $T_2$ contrasts in the PFSE and FSE methods are analyzed by computer simulation and experiment with volunteers. For the simulation, a mathematical phantom composed of various $T_2$ values is devised and $T_2$ contrast in the reconstructed image by the PFSE is compared to those by the FSE method with various effective echo times. Multi-slice ${T_2}-weighted$ head images of the volunteers obtained by the PFSE method are also shown in comparison with those by the FSE method at a 1.0 Tesla whole body MRI system. Results: From the analysis, $T_2$ contrast by the PFSE method appears similar to those by the FSE method with the effective echo time in a range of SO-lOOms. Using a mathematical phantom, contrast in the PFSE image appears close to that by the FSE method with the effective echo time of 96ms. From experiment with volunteers, multi-slice $T_2-weighted$ images are obtained by the PFSE method having contrast similar to that of the FSE method with the effective echo time of 96ms. Reconstructed images by the PFSE method show less motion related artifact compared to those by the FSE method. Conclusion: The projection-type FSE imaging acquires multiple radial lines with different angles in polar coordinate in k space using multiple spin echoes. The PFSE method is robust to patient motion or flow, however, it has difficulty in controlling $T_2$ contrast compared to the FSE method. In this paper, it is shown that the PFSE method provides good $T_2$ contrast (${T_2}-weighted$ images) similar to the FSE method by both computer simulation and experiments with volunteers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.38-42
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• 2002

A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.