• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.8
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• pp.60-66
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• 2013

The wind-speeds among geographically close wind-farms have high correlations seasonally. This paper presents a novel wind-speed sampling method which sincerely reflects the correlation among wind-speeds of different wind-farms. In the proposed method, the wind-speed samples are generated through the statistical data analysis of the measured past wind-speed data and are adequate to be applied to generation adequacy assessment based on random sampling. In the proposed method, the specific probability distribution need not to be assumed and sufficiently accurate wind-speed samples can be generated based only on the measured past data. The proposed method is applied to the two wind-farm problem to show its applicability.

• Proceedings of the KWS Conference
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• 2002.05a
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• pp.49-52
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• 2002

A vision sensor measure range data using laser light source, This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which needs faster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.584-587
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• 2002

A vision sensor measure range data using laser light source. This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which needs laster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.73-85
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• 2001

The spatial population existing in a plane ares, such as an animal or aerial population, have certain relationships among regions which are located within a fixed distance from one selected region. We consider with the adaptive searching estimation in spatial sampling for a spatial population. The adaptive searching estimation depends on values of sample points during the survey and on the nature of the surfaces under investigation. In this paper we study the estimation by the adaptive searching in a spatial sampling for the purpose of estimating the area possessing a particular characteristic in a spatial population. From the viewpoint of adaptive searching, we empirically compare systematic sampling with stratified sampling in spatial sampling through the simulation data.

• 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.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.162-164
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• 2007

This paper presents a "window-zoom-out" optimization strategy with relatively fewer sampling data. In this method, an optimal Latin hypercube sampling experiment based on multi-objective Pareto optimization is developed to obtain the sampling data. The response surface method with multiquadric radial basis function combined with (1+$\lambda$) evolution strategy is used to find the global optimal point. The proposed method is verified with numerical experiments.

• Journal of Korea Technology Innovation Society
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• v.5 no.2
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• pp.228-244
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• 2002

The survey of research and development (R&D) in science and technology (S&T) covers the current status of R&D activities in S&T in Korea, and provides a basis for decision making regarding S&T policy. Continuous improvement of the survey is widely needed to present reliable national basic statistics. Therefore, the purpose of the study is two-fold: to introduce sampling survey method in industrial sector and to make statistical technique to deal with non-response data from industrial sector. To these ends, first, case studies of the United States and Japan are illustrated. A new sampling design for the R&D survey is proposed and implementing stratified random sampling scheme is suggested. Moreover, statistical analysis of the non-response data is dealt with. Based on several screening criteria, we develop a new imputation method suitable for the R&D survey and also provide more detailed implementation plan. Various solutions to a problem arising from non-response item are also presented. Finally, some implications of the results are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.305-310
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• 1991

In industrial multivariable plants, it is often the case that the plant outputs are detected in a similar components not simultaneously but serially. In this paper, the problem of estimating the state vector of the plant based on the data obtained from such a detecting scheme is considered, and a special type of observer (referred to as a "multiple serial-sampling" type observer) which renews its internal states whenever a new group of data is obtained is proposed. It is proved that such an observer can be constructed for almost every sampling period if the plant is observable as a continuous-time multivariable system, and that the poles of the closed-loop system using the serial-sampling type observer consist of the poles of the observer and those of the state feedback system. The behaviors of the observer and the closed-loop system are studied by simulation. The results of simulation indicate that a multiple serial-sampling type observer can estimate the state of the plant more accurately than the ordinary type observers and improve the closed-loop performance, especially, in the existence of dectecting noise.ing noise.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.867-877
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• 2004

The sequential sampling inspection method is an extension of the multiple-sampling methods, and its theory is based on the sequential probability ratio test (SPRT) of Wald. In this paper, the characteristics of SPRT for testing the number of defects are approximated by using the estimated excess over the boundaries. The use of the estimated excess shows good performances in estimating the operating characteristic function and the average sample number of SPRT compared to the method by neglecting the excess. It also makes it possible to determine the boundary values which satisfy the desired error probabilities.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.544-549
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• 1990

In industrial multivariable plants, it is often the case that the plant outputs are detected not simultaneously but serially. In this paper, the problem of estimating the state vector of the plant based on the data obtained from such a detecting scheme is considered, and a special type of observer (referred to as a "serial-sampling' type observer) which renews its internal states whenever a new data is obtained is proposed. It is proved that such an observer can be constructed for almost every sampling period if the plant is observable as a continuous-time multivariable system, and that the poles of the closed-loop system using the serial-sampling type observer consist of the poles of the observer and those of the state feedback system. The behaviors of the observer and the closed-loop system are studied by simulation. The results of simulation indicate that a serial-sampling type observer can estimate the state of the plant more accurately than the ordinary type observers and improve the closed-loop performance.ance.