• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.6
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• pp.55-64
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• 2001

Industrial machines are sometimes exposed to the danger of earthquake. In the design of a mechanical system, this factor should be accounted for from the viewpoint of reliability to analyze a complex nonlinear structure system under random excitation is proposed. First, the actual random excitation, such as earthquake, is approximated to the corresponding Gaussian process for the statistical analysis. The modal equations of overall system are expanded sequentially. Then, the perturbed equations are synthesized into the overall system and solved in probabilistic way. Several statistical properties of a random process that are of interest in random vibration are evaluated in each substructure. Comparing with the results of the numerical simulation proved the efficiency of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.40-48
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• 2007

This paper presents a novel texture segmentation method using multilayer perceptron (MLP) networks and Markov random fields in multiscale Bayesian framework. Multiscale wavelet coefficients are used as input for the neural networks. The output of the neural network is modeled as a posterior probability. Texture classification at each scale is performed by the posterior probabilities from MLP networks and MAP (maximum a posterior) classification. Then, in order to obtain the more improved segmentation result at the finest scale, our proposed method fuses the multiscale MAP classifications sequentially from coarse to fine scales. This process is done by computing the MAP classification given the classification at one scale and a priori knowledge regarding contextual information which is extracted from the adjacent coarser scale classification. In this fusion process, the MRF (Markov random field) prior distribution and Gibbs sampler are used, where the MRF model serves as the smoothness constraint and the Gibbs sampler acts as the MAP classifier. The proposed segmentation method shows better performance than texture segmentation using the HMT (Hidden Markov trees) model and HMTseg.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.305-312
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• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.5
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• pp.1105-1111
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• 2005

In order to investigate the meanings and bases of transforming theories of diseases(病傳論), several relevant theories were collected from medical books since . The outside-to-inside changing process(pyoree jeon) was the fundamental pattern in febrile diseases regardless of slang han and wen bing after Han dynasty. But in case of numb disease the three exogenous pathogenic factors of wind, cold and dampness got into each viscera through five tissues like skin, vessesl, flesh, tendons, bones respectively. It was called corresponding changing process(sanghap jeon) here. The pathogenic changing process(byungsa jeon) had complicated details to explain pathologic processes, but could give useful informations on evaluating relative strength of pathogens and tendency ahead. The changing process of diseases of internal injuries were explained in case of emotional distress which is outbroken abruptly didn't follow regular order of viscera-emotion relations. So it was named random changing process(bulcha jeon) after 's usage. And marasmus and asthenic disease followed top-to-down or down-to-top changing process(sangha jeon) based on . There are many types of changing process of diseases between viscera and viscera or viscera and bowels like generation changing process, restriction changing process, changing process between couple, changing process of mutual transmission based on attributions of each element by the theory of 5 phases(五行論). And changing process to a neighbor doesn't have any special relations within two organs but has anatomical contiguity and physiological continuity between them. The transforming theories of diseases bring forth useful understanding on comings and goings of pathogenic factors and tendency and prognosis of disease, so they are needed to be taught in the course of pathology class.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2002.09a
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• pp.25.2-25
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• 2002

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.859-870
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• 2011

The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

• Transactions of Materials Processing
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• v.29 no.4
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.271-276
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• 2011

The working conditions of construction equipments such as excavators, wheel loaders and haulers are very tough and severe in fact. To design main components of construction equipment under the severe environment, it's important for engineers to consider design for vibration durability point of view at the early stage of product development process. Radiator as a cooling unit of construction equipment is one of critical components to apply design for vibration. We present a design for vibration process and methodology on the radiator system in construction equipment industries. From the natural frequency and the random vibration analysis based on field vibration test data, we could find current status of radiator layout design to develop and made best layout specification of radiator design to decide for product development process at the early stage.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1384-1385
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• 2006

Platinum is a candidate of top and bottom electrode in ferroelectric random access memory and dynamic random access memory. High dielectric materials and ferroelectric materials were generally patterned by plasma etching, however, the low etch rate and low etching profile were repoted. We proposed the damascene process of high dielectric materials and ferroelectric materials for patterning process through the chemical mechanical polishing process. At this time, platinum as a top electrode was used for the stopper for the end-point detection as Igarashi model. Therefore, the control of removal rate in platinum chemical mechanical polishing process was required. In this study, an addition of $H_{2}O_{2}$ oxidizer to alumina slurry could control the removal rate of platinum. The removal rate of platinum rapidly increased with an addition of 10wt% $H_{2}O_{2}$ oxidizer from 24.81nm/min to 113.59nm/min. Within-wafer non-uniformity of platinum after chemical mechanical polishing process was 9.93% with an addition of 5wt% $H_{2}O_{2}$ oxidizer.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.20-27
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• 2010

This paper proposes a saturation compensating method by embedding pseudo-random code information in wavelet packet based colorization algorithm. In the color-to-gray process, an input RGB image is converted into YCbCr images, and a 2-level wavelet packet transform is applied to the Y image. And then, color components of CbCr are embedded into two sub-bands including minimum amount of energy on the Y image. At this time, in order to compensate the color saturations of the recovered color image during the printing and scanning process, the maximum and minimum values of CbCr components of an original image are also embedded into the diagonal-diagonal sub-band by a form of pseudo-random code. This pseudo-random code has the maximum and minimum values of an original CbCr components, and is expressed by the number of white pixels. In the gray-to-color process, saturations of the recovered color image are compensated using the ratio of the original CbCr values to the extracted CbCr values. Through the experiments, we can confirm that the proposed method improves color saturations in the recovered color images by the comparison of color difference and PSNR values.