• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.404-414
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• 2014

Yield prediction is important to manage semiconductor quality. Many researches with machine learning algorithms such as SVM (support vector machine) are conducted to predict yield precisely. However, yield prediction using SVM is hard because extremely imbalanced and big data are generated by final test procedure in semiconductor manufacturing process. Using SVM algorithm with imbalanced data sometimes cause unnecessary support vectors from major class because of unselected support vectors from minor class. So, decision boundary at target class can be overwhelmed by effect of observations in major class. For this reason, we propose a under-sampling method with minor class based SVM (MCSVM) which overcomes the limitations of ordinary SVM algorithm. MCSVM constructs the model that fixes some of data from minor class as support vectors, and they can be good samples representing the nature of target class. Several experimental studies with using the data sets from UCI and real manufacturing process represent that our proposed method performs better than existing sampling methods.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.385-390
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• 1993

It is the purpose of this paper to present a dialogical tuning method of the sampling period in fuzzy control systems. Last year, the authors gave a dialogical tuning technique of fuzzy control system under the fixed sampling period in this symposium. In the case where sampling period is chosen larger, the response of the control system is unsatisfactory, and in the case where the sampling period is smaller, ineffective control actions are repeated. The appropriate sampling period is chosen through the step response of the closed loop fuzzy control process. As the tuning technique depends on the controlled plant, it is necessary to estimate the rough characteristics of it. The authors propose a method to decide th appropriate sampling period, by inspecting the characteristics of the plant.

• International Journal of Reliability and Applications
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• v.15 no.2
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• pp.77-84
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• 2014

In this paper, a optimal designing methodology is proposed to determine the parameters for skip-lot sampling plan of type SkSP-2 plan with double sampling plan as reference plan, when the lifetime of the product follows generalized exponential distribution. The two points on the operating characteristic curve approach are used to find the optimal parameters for the proposed plan. The plan parameters are determined so as to minimize the average sample number subject to satisfying simultaneously both producer and consumer risks at the acceptable and limiting quality levels respectively.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.35-43
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• 1993

The principal objective of a sampling plan is to make efficient use of the budget allocated and to obtain as precise an estimate of a population parameter as possible. In order to estimate the proportion of defectives produced or to determine some measure of product Quality, it is necessary to select random samples which represent a population parameter of the process. In this case, the two stage sampling is more efficient and convenient than simple random sampling. Therefore this paper aims to propose the design procedures of two stage sampling plan to obtain a representative samples in considering the sampling precision under the restricted sampling unspection cost.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.1
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• pp.72-80
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• 2015

In distributed generation systems, a grid-connected inverter should operate with synchronization to grid voltage. Considering that synchronization requires the phase angle of grid voltage, a phase locked loop (PLL) scheme is often used. The synchronous reference frame phase locked loop (SRF-PLL) is generally known to provide reasonable performance under ideal grid voltage. However, this scheme indicates performance degradation under the harmonic distorted or unbalanced grid voltage condition. To overcome this limitation, this paper proposes a phase and harmonic detection method of grid voltage using fast Fourier transform (FFT). To reduce the calculation time of FFT algorithm, minimum sampling data is taken from the voltage measurement to determine the phase angle and the magnitude of harmonic components. An experimental test setup for a grid-connected inverter system has been constructed. By comparative simulations and experiments under various abnormal grid voltage conditions, the proposed scheme has been proven to effectively track the phase angle of the grid voltage.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1309-1317
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• 2006

The paper considers some Bayes estimators of the finite population mean with auxiliary information under priors which are scale mixtures of normal, and thus have tail heavier than that of the normal. The proposed estimators are quite robust in general. Numerical methods of finding Bayes estimators under these heavy tailed priors are given, and are illustrated with an actual example.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.637-644
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• 2001

We investigated two kinds of mean square error (MSE) estimator of homogeneous linear estimator (HLE) for the population total under stratified multi-stage sampling. One is studied when the second stage variance component is estimable and the other is found in cafe it is not estimable. The proposed estimators are necessary forms of non-negative unbiased MSE estimators of HLE.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.751-759
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• 2012

This paper proposes an alternative stratified randomized response model based on the model of Singh and Joarder (1997). It is shown numerically that the proposed stratified randomized response model is more efficient than Hong et al. (1994) (under proportional allocation) and Kim and Warde (2004) (under optimum allocation).

• Journal of Korean Society for Quality Management
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• v.11 no.1
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• pp.18-23
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• 1983

Continuous sampling plans CSP-1(i,f)'s with which AOQL is guaranteed, can be applied to the cases in need of effective sampling without stopping the process or dividing batches during production. But the plans that can guarantee the same AOQL value are too many. Therefore we have to select one plan among them. There may be a lot of ways to choose it. This paper connects with various sampling costs, the concept to try to detect the shift of process average under fractional inspection in CSP-1,to find a minimum cost sampling plan among several CSP-1 sampling plan alternatives (i, f)'s with the same AOQL value.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.255-266
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• 2007

A Bayesian estimation of the four-parameter gamma distribution is considered under the noninformative prior. The Bayesian estimators are obtained by the Gibbs sampling. The generation of the shape/power parameter and the power parameter in the Gibbs sampler is implemented using the adaptive rejection sampling algorithm of Gilks and Wild (1992). Also, the location parameter is generated using the adaptive rejection Metropolis sampling algorithm of Gilks, Best and Tan (1995). Finally, the simulation result is presented.