• Journal of Korean Society for Quality Management
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• v.28 no.4
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• pp.194-203
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• 2000

This paper is concerned with an economic selection of both the process mean and the lower limit for a continuous production process with the quadratic loss function. It is assumed that the quality characteristic is normally distributed with a known variability. A profit model is developed which involves selling price, production cost, reprocessing cost and the cost which is incurred by imperfect quality. Methods of finding optimum values of the process mean and the lower limit are presented, and a numerical example is given.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.758-762
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• 2011

In this paper an efficient algorithm is proposed to remove additive white Gaussian noise(AWGN) with edge preservation. A function is used to separate the filtering mask to two sets according to the direction information. Then, we calculate the mean and standard deviation of the pixels in each set. In order to preserve the details, we also compare standard deviations between the two sets to find out smaller one. Corrupted pixel is replaced by the mean of the filtering window's median value and the smaller set's mean value that the rate of change is faster than the other one. Experiment results show that the proposed algorithm outperforms with significant improvement in image quality than the conventional algorithms. The proposed method removes the Gaussian noise very effectively.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.444-447
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• 1995

The satellite in a circular orbit about a planet with disturbances and a three-degree-of-freedom (3DOF) structure under seismic excitations are modeled by the linear stochastic differential equations. Then the risk-sensitive optimal control method is applied to those equations. The mean and the variance of the cost function varies with respect to the risk-sensitivity parameter, .gamma.$_{RS}$ . For a particular risk-sensitivity parameter value, risk-sensitive control reduces to LQG control. Furthermore, the derivation of the mean square value of the state and control action are given for a finite-horizon full-state-feedback risk-sensitive control system. The risk-sensitive controller outperforms a classical LQG controller in the mean square sense of the state and the control action.

• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.905-917
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• 2022

This study was conducted to evaluate the use of the MAR function and the image quality of the image when examining with each radiation dose. A simple Periapical phantom was made to set up an implant, and images were obtained and analyzed according to the presence or absence of MAR function for each radiation dose using CBCT equipment. In this study, MEAN, SNR, and CNR values were obtained using the Image J program, and through statistical analysis, images were the most quantitative and suitable values when the Abutment of Implant was 100 kVp and 8 mA, and when the Center of Implant and Apex of Implant were 100 kVp and 9 mA. As a result, it was confirmed that if the radiation dose increased, the Pixel Value, SNR, and CNR values of the image rose up so that the quality of the image improved, and using the MAR function reduced artifacts.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1338-1348
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• 2017

In this study, a modified ripple correlation control (RCC) maximum-power point-tracking (MPPT) algorithm is proposed for a single-stage single-phase voltage source inverter (VSI) on a grid-connected photovoltaic system (GCPVS). Unlike classic RCC methods, the proposed algorithm does not require high-pass and low-pass filters or the increment of the AC component filter function in the voltage control loop. A simple arithmetic mean function is used to calculate the average value of the photovoltaic (PV) voltage, PV power, and PV voltage ripples for the MPPT of the RCC method. Furthermore, a high-accuracy and high-precision MPPT is achieved. The performance of the proposed algorithm for the single-stage single-phase VSI GCPVS is investigated through simulation and experimental results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.21-29
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• 2011

At existing skin detection methods using skin color information defined based on the prior knowldege, threshold value to be used at the stage of dividing the backround and the skin region was decided on a subjective point of view through experiments. Also, threshold value was selected in a passive manner according to their background and illumination environments in these existing methods. These existing methods displayed a drawback in that their performance was fully influenced by the threshold value estimated through repetitive experiments. To overcome the drawback of existing methods, this paper propose a skin region detection method using a histogram approximation based on the mean shift algorithm. The proposed method is to divide the background region and the skin region by using the mean shift method at the histogram of the skin-map of the input image generated by the comparison of the similarity with the standard skin color at the CbCr color space and actively finding the maximum value converged by brightness level. Since the histogram has a form of discontinuous function accumulated according to the brightness value of the pixel, it gets approximated as a Gaussian Mixture Model (GMM) using the Bezier Curve method. Thus, the proposed method detects the skin region by using the mean shift method and actively finding the maximum value which eventually becomes the dividing point, not by using the manually selected threshold value unlike other existing methods. This method detects the skin region high performance effectively through experiments.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• Journal of Korean Ophthalmic Optics Society
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• v.4 no.1
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• pp.63-68
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• 1999

It was made of a chart by new method to be measured the contrast sensitivity for a spatial frequency, and the mean luminance of a lattice frequency was made to three forms of 25, 50, 75% and let it to be ready a CS value from 0 to $10^3$. As a result of measuring of the CS value for a spatial frequency on a target of 12 year old students, CS value decreased of according to down the average luminance value and also the peak position shift to low spatial frequency. The low visioned person decreased the CS value in side of high frequency or in space of total frequency. By the lattice adaptation, a measured CS value was decreased in circumstance regions of adapted space frequency.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.87-95
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• 1999

We propose a simulation model of 3-dimensional MPEG data over Asynchronous transfer Mode(ATM) networks. The model is based on a slice level and is named to Projected Vector Autoregressive(PVAR) model. The PVAR model is modeled using the Autoregressive(AR) model in order to meet the autocorrelation condition and fit the histogram, and maps real data by a projection function. For the projection function, we use the Cumulative Distribution Probability Function (CDPF), and the procedure is performed at each slice level. Our proposed model shows good performance in meeting the autocorrelation condition and fitting the histogram, and is found important in analyzing the performance of networks. In addiotion, we apply a smoothing method by which a periodic mean value. In general. the Quality of Service(QoS) depends on the Cell Loss Rate(CLR), which is related to the cell loss and a maximum delay in a buffer. Hence the proposed smoothing method can be used to improve the QoS.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.203-209
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• 2015

Recently, the portion of electronic control in an engine system has been increasing with the aim of meeting the requirements of emissions and fuel efficiency of the engine system in the construction machinery industry. Correspondingly, the complexity of the engine management system (EMS) has increased. This study developed an engine HiLS system for reducing the cost and time required for function development for the EMS. The engine model for HiLS is composed of air, fuel, torque, and dynamometer models. Further, the mean value method is applied to the developed HiLS engine model. This model is validated by its application to a heavy-duty diesel engine equipped with an exhaust gas recirculation system and a turbocharger. Test results demonstrate that the model has accuracy greater than 90 and also verify the feasibility of the virtual calibration process.