• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.243-251
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• 2006

This paper is to propose various quality and reliability sampling inspection methods to perform the competitive global outsourcing strategy while purchasing and subcontracting. The study also represents implementation strategy which can be efficiently and effectively used in the enterprise. Quality sampling inspection schemes extend reliability inspection techniques with a little change.

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.141-148
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• 2020

To find food, homes, and mates, some animals have adapted special sensing capabilities. Rather than using a passive method, they discharge a signal and then extract the necessary information from the response. More importantly, they use the slope of the detected signal to find the destination of an object. In this paper, similar strategy is mathematically formulated. A perturbation and correlation-based gradient estimation method is developed and used as a sensing strategy. This method allows us to adaptively sense an object in a given environment effectively. The proposed strategy is based on the use of gradient values; rather than instantaneous measurements. Considering the gradient value, the sampling frequency is planned adaptively, i.e., sparse sampling is performed in slowly varying regions, while dense sampling is conducted in rapidly changing regions. Using a temperature sensor, the proposed strategy is verified and its effectiveness is demonstrated.

• Korean Journal of Veterinary Research
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• v.47 no.1
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• pp.51-57
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• 2007

To establish a statistically reliable sampling strategy for serological surveillance of classical swinefever (CSF) in Korea, antibody test data from CSF surveillance conducted during year 2005 were analyzed.The most appropriate sampling method was determined to be stratified multi-stage random sampling strategy,in which the primary sampling unit is a pig farm and the secondary are the pigs by the strata of breedersand finishers in the selected farm. The optimum sample size was 5 to 19 including 1 to 2 breeders accordingto the number of pigs in the farm. The optimum sampling strategy demonstrated in this study was veryFindings of our study provide practical guidelines for surveillance of herd immunity level to CSF in Korea.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.443-450
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• 2008

This paper is to present design principle and operation strategy of acceptance control chart by the use of OC-Based sampling inspection for continuous data. The unified control limits for acceptance control chart when considering both APL(Acceptable Process Level) and RPL(Rejectable Process Level) are proposed. The control limits can be also extended to the acceptance control chart with unknown process standard deviation.

• 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.

• Structural Engineering and Mechanics
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• v.82 no.3
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• pp.271-282
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• 2022

The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.151-157
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• 2005

For the treatment of regulatory clearance of the soils, a procedure for the radionuclides and radioactivity concentration analysis is under development. A strategy for soil sampling including random sampling after homogenization and standardization was set up. Statistical representativeness is considered for not only sampling strategy but also sample size. In this study, designed sample size was designed with confidence interval and error bound of soil using the pilot samples which were taken following the sampling strategy.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.65-67
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• 2008

An adaptive response surface method with Latin Hypercube sampling strategy is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and ($1+{\lambda}$) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite element method to set a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6MW BLDC motor.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.701-702
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• 2008

An adaptive response surface method with Latin Hypercube sampling strategy is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and (1+${\lambda}$) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite element method to get a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6 MW BLDC motor, and the cogging torque is reduced to 19% of the initial one.

• Journal of Power Electronics
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• v.16 no.1
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• pp.227-237
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• 2016

A novel digital current control strategy for digitally controlled DC-DC switching converters, referred to as Adjacent Cycle Sampling (ACS), is proposed in this paper. For the ACS current control strategy, the available time interval from sampling the current to updating the duty ratio, is approximately one switching cycle. In addition, it is independent of the duty ratio. As a result, the contradiction between the processing speed of the hardware and the transient response speed can be effectively relaxed by using the ACS current control strategy. For digitally controlled buck DC-DC switching converters with trailing-edge modulation, digital current control algorithms with the ACS control strategy are derived for three different control objectives. These objectives are the valley, average, and peak inductor currents. In addition, the sub-harmonic oscillations of the above current control algorithms are analyzed and eliminated by using the digital slope compensation (DSC) method. Experimental results based on a FPGA are given, which verify the theoretical analysis results very well. It can be concluded that the ACS control has a faster transient response speed than the time delay control, and that its requirements for hardware processing speed can be reduced when compared with the deadbeat control. Therefore, it promises to be one of the key technologies for high-frequency DC-DC switching converters.