• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.81-95
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• 1996

In this paper, we propose a motio estiamtion algorithm using low-resolution quantization to reduce the computation of the full search algorithm. The proposed algorithm consists of the low-resolution search which determins the candidate motion vectors by comparing the low-resolution image and the full-resolution search which determines the motion vector by comparing the full-resolution image on the positions of the candidate motion vectors. The low-resolution image is generated by subtracting each pixel value in the reference block or the search window by the mean of the reference block, and by quantizing it is 2-bit resolution. The candidate motion vectors are determined by counting the number of pixels in the reference block whose quantized codes are unmatched to those in the search window. Simulation results show that the required computational cost of the proposed algorithm is reduced to 1/12 of the full search algorithm while its performance degradation is 0.03~0.12 dB.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.156-161
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• 1997

Zernike moments have been one of the most commonly used feature vectors for recognizing rotated patterns due to its rotation invariant characteristics. In order to reduce its expensive computational cost, several methods have been proposed to lower the complexity. One of the methods proposed by mukundan and K. R. Ramakrishnan[1], however, is not rotation invariant. In this paper, we propose another method that not only reduces the computational cost but preserves the rotation invariant characteristics. In the experiment, we compare our method with others, in terms of computing time and the accuracy of moment feature at different rotational angle of an object in image.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.307-314
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• 2000

A parallel condensation algorithm for efficient dynamic analysis of three-dimensional large-scale structures is presented. The algorithm is developed for a user-friendly and cost effective high-performance computing system on a collection of Pentium processors connected via a 100 Mb/s Ethernet LAN. To harness the parallelism in the computing system effectively, a large-scale structure is partitioned into a number of substructures equal to the number of computers in the computing system Then, for reduction in the size of an eigenvalue problem the computations required for static condensation of each substructure is processed concurrently on each slave computer. The performance of th proposed parallel algorithm is demonstrated by applying to dynamic analysis of a three dimensional structure. The results show that how the parallel algorithm facilitates the efficient use of a small number of low-cost personal computers for dynamic analysis of large-scale structures.

• Korean Journal of Computational Design and Engineering
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• v.22 no.2
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• pp.129-140
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• 2017

This paper presents a systematic approach for design of timely and proper layouts of a manufacturing system facilitating reconfigurability, referred to as a reconfigurable manufacturing system. A proper methodology for design of a system layout is required for reconfiguration planning - adding or removing machines for supplying the exact capacity needed to fulfill market demands, as well as minimizing the cost of adding new machines. In this paper, theory of constraints is used to make reconfiguration manufacturing systems more cost-effective and efficiency. The proposed approach is validated by using a real industrial case. This paper suggests that the proposed study should be performed concurrently with the design of a new manufacturing system.

• Structural Engineering and Mechanics
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• v.14 no.1
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• pp.57-70
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• 2002

This work presents an iterative mesh partitioning approach to improve the efficiency of parallel substructure finite element computations. The proposed approach employs an iterative strategy with a set of empirical rules derived from the results of numerical experiments on a number of different finite element meshes. The proposed approach also utilizes state-of-the-art partitioning techniques in its iterative partitioning kernel, a cost function to estimate the computational cost of each submesh, and a mechanism that adjusts element weights to redistribute elements among submeshes during iterative partitioning to partition a mesh into submeshes (or substructures) with balanced computational workloads. In addition, actual parallel finite element structural analyses on several test examples are presented to demonstrate the effectiveness of the approach proposed herein. The results show that the proposed approach can effectively improve the efficiency of parallel substructure finite element computations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1123-1129
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• 2012

This paper presents the fast steady state analysis using time-stepping finite element method for a high power three-phase transformer. The high power transformer spends huge computational cost of the time-stepping finite element method. It is because that the high power transformer requires a lot of time to reach steady state by its large inductance component. In order to reduce computational cost, in this paper, the adaptive time-step control algorithm combined with the embedded 2nd 4th singly diagonally implicit Runge-Kutta method and the analysis strategy using variation of the winding resistance are studied, and their numerical results are compared with those from the typical time-stepping finite element method.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.50-60
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• 2002

A new co-evolutionary algorithm, of which the convergence speed is accelerated by neural networks, is proposed and verified in this paper. To reduce computational load required for co-evolutionary optimization processes, the cost function and constraint information is stored in the neural networks, and the extra offspring group, whose cost is computed by the neural networks, is generated. It increases the offspring population size without overloading computational effort; therefore, the convergence speed is accelerated. The proposed algorithm is applied to attitude control design of flexible satellites, and it is verified by computer simulations and experiments using a torque-free air bearing system.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.2
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• pp.86-95
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• 2016

We propose a new approach to the stochastic version of Lanchester model. Commonly used approach to stochastic Lanchester model is through the Markov-chain method. The Markov-chain approach, however, is not appropriate to high dimensional heterogeneous force case because of large computational cost. In this paper, we propose an approximation method of stochastic Lanchester model. By matching the first and the second moments, the distribution of each unit strength can be approximated with multivariate normal distribution. We evaluate an approximation of discrete Markov-chain model by measuring Kullback-Leibler divergence. We confirmed high accuracy of approximation method, and also the accuracy and low computational cost are maintained under high dimensional heterogeneous force case.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.215-218
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• 2003

In this paper we apply PMC (parallel model combination) to speech recognition system online. As a representative of model based noise compensation techniques, PMC compensates environmental mismatch by combining pretrained clean speech models and real-time estimated noise information. This is very effective approach for compensating extreme environmental mismatch but is inadequate to use in on-line system for heavy computational cost. To reduce the computational cost and to apply PMC online, we use a noise masking effect - the energy in a frequency band is dominated either by clean speech energy or by noise energy - in the process of model compensation. Experiments on artificially produced noisy speech data confirm that the proposed technique is fast and effective for the on-line model compensation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1266-1272
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• 2001

This paper discusses the multi-level optimization method in dynamic optimization problems, through stiffened plate of ship structures. In structural optimization, the computational cost increases rapidly as the number of design variables increases. And we need a great amount of calculation and time on problems of modified dynamic characteristics of large and complicated structures. In this paper, the multi-level optimization is proposed, which decreases computational time and cost. The dynamic optimum designs of stiffened plate that control the natural frequency and minimize weight subjected to constraints condition are derived. It is shown that the results are effective in the optimum modification for dynamic characteristics of the stiffened plate.