• Nuclear Engineering and Technology
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• v.33 no.5
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• pp.483-497
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• 2001

In this work, a neuro-fuzzy inference system combined with the wavelet denoising, PCA (principal component analysis) and SPRT (sequential probability ratio test) methods is developed to detect the relevant sensor failure using other sensor signals. The wavelet denoising technique is applied to remove noise components in input signals into the neuro-fuzzy system The PCA is used to reduce the dimension of an input space without losing a significant amount of information. The PCA makes easy the selection of the input signals into the neuro-fuzzy system. Also, a lower dimensional input space usually reduces the time necessary to train a neuro-fuzzy system. The parameters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The residuals between the estimated signals and the measured signals are used to detect whether the sensors are failed or not. The SPRT is used in this failure detection algorithm. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level and the hot-leg flowrate sensors in pressurized water reactors.

• Korean journal of applied entomology
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• v.48 no.1
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• pp.45-51
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• 2009

This paper presents sequential sampling plans for evaluating the pest density based on complete counts from probe in a rice storage warehouse. Both maize weevil and Indian meal moth population showed negative binomial dispersion patterns in brown rice storage. For cost-effective monitoring and action decision making system, sequential sampling plans by using the sequential probability ratio test (SPRT) were developed for the maize weevil and Indian meal moth in warehouses with 0.8 M/T storage bags. The action threshold for the two insect pests was estimated to 5 insects per kg, which was projected by a matrix model. The results show that, using SPRT methods, managers can make decisions using only 20 probe with a minimum risk of incorrect assessment.

• The Korean Journal of Applied Statistics
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• v.3 no.1
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• pp.105-120
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• 1990

In this paper, a sequential test procedure is defined by using cumulative sum (CUSUM) of statistics. The properties as well as the efficiency of the CUSUM test are studied in comparison with the sequential probability ratio test (SPRT). It was shown that, the operating characteristic function and the average sample numbrer can be derived by Wald and Wiener process approximations. Also it was shown that the statistics used in the CUSUM test is determined to provide asymtotically equivalent efficiency compared to the SPRT. The efficiency of the CUSUM test and the SPRT are cpmpared by an example for some limited number of cases in the exponential distribution.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2594-2599
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• 2003

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.1-13
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• 1996

The sequential sampling inspection method is an extension of the double-sampling and multiple-sampling methods and its theory is based on the sequential probability ratio test(SPRT). In this paper, the characteristics of SPRT for testing the propotion of defectives 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.

• 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.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.4
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• pp.1160-1171
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• 2015

The purpose of this study is to design and develop a computer based learning and test system, which supports not only testing learner's ability but also learning contents with giving feedback and hint. In order to design and develop a computer based learning and test system, Visual Basic dot Net software is used. The system works in three stages: sequential problem solving stage, randomized problem solving stage, and the challenge stage of pass/fail. The results of this study are as follows: (a) We propose the context of design for the computer based learning and test system. (b) We design and develop items display function with sequential and random algorithm in this system. (c) We design and develop pass/fail function by applying SPRT(Sequential Probability Ratio Testing) algorithm in the computer based learning and test system.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.31-45
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• 1998

This paper proposes a method of designing one-sided cumulative scored control charts to control the process mean with a normally distributed quality characteristic. The average run length(ARL) is obtained from the average sample number of sequential probability ratio test(SPRT) on trinomial distribution. Using the analogy between cumulative scored control chart and SPRT for trinomial observations, a procedure is presented to determine three control chart parameters; lower and u, pp.r scoring boundaries and action limit. The parameters are determined by minimizing the ARL when the process is out of control with prespecified ARL when the process is in control.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.29-37
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• 2009

This paper proposes a curtailed-sequential probability ratio test (SPRT) control chart. For using the conventional SPRT control chart, the number of items inspected in a sampling point should have no restriction since items in a sampling point are inspected one by one until an SPRT Is terminated. The number of observations taken in a sampling point, however, has an upper bound since sampling and testing of an item is time-consuming or expensive. When the sample size reaches the upper bound without evidence of an in-control or out-of-control state of a process, the proposed chart makes a decision using the sample mean of all observations taken in a sampling point. The properties of the Proposed chart are obtained by a Markov chain approach and the performance of the chart is compared with fixed sample size (FSS) and variable sample size (VSS) control charts. A comparative study shows that the proposed chart performs better than VSS control charts as well as conventional FSS control charts.

• Journal of the Korean Operations Research and Management Science Society
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• v.9 no.2
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• pp.23-27
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• 1984

We Observe a sequence of i. i. d random variables with density f or g. Only if g is true we should stop the process. Hence. the testing problem is completely described by a stopping time. Among all stopping times with error probability of first kind not exceeding a given bound, the one-sided sequential probability ratio test has smallest expected sample size if g is true. Moreover, the generalized one-sided SPRT has smallest expected sample size for g in the class of stopping times with expected sample size under f not falling below a given bound.