• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.457-461
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• 1988

In this study an one-board micom controlled precision temperature control system has been developed. The digital temperature control system is consisted of an one-board micom as digital controller, a 12-bit A/D and D/A converter, a power amplifier, a NTC thermister, a preamplfier and a heat chamber. An operating control program for the control system was written in Z80 machine language. A Dual-PID predictor control algorithm was proposed. Experments were conducted with different sampling time and limitted error value. As a result, the temperature in a heat chamber can be well controlled within +- 0.2 .deg.C when the sampling time was applied to 10 sec and the limitted error value +- 0.5 .deg.C under the dual-PID predictor control algorithm. By means of one-board micom overall system has been reduced in size and volume, thus the system becomes compact and less expensive.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.85-91
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• 2015

The press-fit shaft is an important part used in automobiles, vessels, and trains. This study proposes an optimized design method to reduce damage that may occur in the press-fitted shaft by modifying the shape of the boss step of the press-fitted shaft. To reduce the time and cost of running the optimized design method, an approximate design optimization is applied and an optimized algorithm is generated using a genetic algorithm that is widely used in engineering fields and an approximate model using a response surface method. The planned experiments for the data that are needed to generate the approximate model use a central composite design (CCD) and Latin hypercube sampling (LHS), and the results of the approximate optimization using the above two design of experiments are to be compared.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.94-100
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• 2003

This paper presents the experiments on the approximation of a hydraulic servo system using a real time recurrent neural networks (RTRN) with time varying weights. In order to verify the effectiveness of the RTRN algorithm in hydraulic servo system, we design the experimental hydraulic system and implemented the real time approximation of system output. Experimental results show that approximated output of the RTRN well follows the position trajectory of the electro-hydraulic servo system. And also it is verified that the 2-D RNN can be implemented in sampling time even though high sampling frequency experimentally.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.31-36
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• 2020

Most of the background subtraction algorithms show good performance in static scenes. In the case of dynamic scenes, they frequently cause false alarm to "temporal clutter", a repetitive motion within a certain area. In this paper, we propose a robust technique for the multiple interval pixel sampling (MIS) algorithm to handle highly dynamic scenes. An adaptive threshold scheme is used to suppress false alarms in low-confidence regions. We also utilize multiple background models in the foreground segmentation process to handle repetitive background movements. Experimental results revealed that our approach works well in handling various temporal clutters.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.999-1008
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• 2012

A Bayesian multiple change-point model for small data is proposed for multivariate means and is an extension of the univariate case of Cheon and Yu (2012). The proposed model requires data from a multivariate noncentral $t$-distribution and conjugate priors for the distributional parameters. We apply the Metropolis-Hastings-within-Gibbs Sampling algorithm to the proposed model to detecte multiple change-points. The performance of our proposed algorithm has been investigated on simulated and real dataset, Hanwoo fat content bivariate data.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.95-126
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• 2009

The present contribution addresses the parallelization of advanced simulation methods for structural reliability analysis, which have recently been developed for large-scale structures with a high number of uncertain parameters. In particular, the Line Sampling method and the Subset Simulation method are considered. The proposed parallel algorithms exploit the parallelism associated with the possibility to simultaneously perform independent FE analyses. For the Line Sampling method a parallelization scheme is proposed both for the actual sampling process, and for the statistical gradient estimation method used to identify the so-called important direction of the Line Sampling scheme. Two parallelization strategies are investigated for the Subset Simulation method: the first one consists in the embarrassingly parallel advancement of distinct Markov chains; in this case the speedup is bounded by the number of chains advanced simultaneously. The second parallel Subset Simulation algorithm utilizes the concept of speculative computing. Speedup measurements in context with the FE model of a multistory building (24,000 DOFs) show the reduction of the wall-clock time to a very viable amount (<10 minutes for Line Sampling and ${\approx}$ 1 hour for Subset Simulation). The measurements, conducted on clusters of multi-core nodes, also indicate a strong sensitivity of the parallel performance to the load level of the nodes, in terms of the number of simultaneously used cores. This performance degradation is related to memory bottlenecks during the modal analysis required during each FE analysis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.10
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• pp.811-816
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• 2018

When applying the MLFMM algorithm to a large scattering problem, the accuracy of the calculation of the transfer function has a crucial effect on the final simulation results. The numerical accuracy for the double integral on the unit sphere is strongly dependent on the sampling number. With an increasing the sampling points, the overall required memory and running time of the MLFMM simulation also increases. Hence, an optimal over-sampling rate for the number of the sampling points is numerically obtained, which is verified for a real large scattering problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6063-6079
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• 2019

When the length of sampling data sequence is too large, the method of gesture recognition based on traditional Dynamic Time Warping (DTW) algorithm will lead to too long calculation time, and the accuracy of recognition result is not high.Support vector machine (SVM) has some shortcomings in precision, Edit Distance on Real Sequences(EDR) algorithm does not guarantee that noise suppression will not suppress effective data.A new method based on Improved Interpolation Dynamic Time Warping (IIDTW)algorithm is proposed to improve the efficiency of gesture recognition and the accuracy of gesture recognition. The results show that the computational efficiency of IIDTW algorithm is more than twice that of SVM-DTW algorithm, the error acceptance rate is FAR reduced by 0.01%, and the error rejection rate FRR is reduced by 0.5%.Gesture recognition based on IIDTW algorithm can achieve better recognition status. If it is applied to unlock mobile phone, it is expected to become a new generation of unlock mode.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.1-11
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• 2021

Estimation of distribution algorithm (EDA) is a popular stochastic metaheuristic algorithm. EDA has been widely utilized in various optimization problems. However, it has been shown that the diversity of the population gradually decreases during the iterations, which makes EDA easily lead to premature convergence. This article introduces a hybrid estimation of distribution algorithm (EDA) with differential evolution (DE) based on self-adaptive strategy, namely HEDADE-SA. Firstly, an alternative probability model is used in sampling to improve population diversity. Secondly, the proposed algorithm is combined with DE, and a self-adaptive strategy is adopted to improve the convergence speed of the algorithm. Finally, twenty-five benchmark problems are conducted to verify the performance of HEDADE-SA. Experimental results indicate that HEDADE-SA is a feasible and effective algorithm.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.4
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• pp.305-312
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• 2005

In this thesis, Lohmann's algorithm and FFT (fast Fourier transform) are used to synthesize binary-phase holograms. FFT computing is carried out for the calculation of complex wavefronts of $128{\times}128$ sampling points of an object that is numerically specified. Then using the Lohmann's algorithm, the amplitude and the phase of complex wavefronts are encoded in binary holograms on each sampling points. PC (personal computer) and laser printer are used to plot binary-phase holograms and CGH (computer generated holograms) films are obtained from this plot by photographic reduction. Holographic images of numerically specified objects are reconstructed from the He-Ne laser and the inverse Fourier optics system. We estimate the quality of holographic images according to the sampling number, application of random phase, amplitude clipping and bleaching the CGH film. We derive optimized conditions to reconstruct better holographic images and to reduce the speckle noise. FFT and Lohmann's algorithm are implemented with MS Visual BASIC 6.0 for the programming of binary-phase hologram.