• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.1-14
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• 2002

Traditional SPC techniques are looking out variation of process by fixed sampling interval and fixed sample size about every hour, the process of in-control or out-of-control couldn't be detected actually when the sample points are plotted near control limits, and it takes no notice of expense concerned with such sample points. In this paper, to overcome that, consider VSI(variable sampling interval) EWMA control charts which VSI method is applied. The VSI control charts use a short sampling internal if previous sample points are plotted near control limits, then the process has high probability of out-of-control. But it uses a long sampling interval if they are plotted near centerline of the control chart, since process has high possibility of in-control. And then a comparison and analysis between FSI(fixed sampling interval) and VSI EWMA in the statistical aspect and economic aspect is studied. Finally, we show that VSI EWMA control chart is more efficient than FSI EWMA control chart in the both aspects.

• Computers and Concrete
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• v.25 no.1
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• pp.83-94
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• 2020

The use of fly ash in modern-day concrete technology aiming sustainable constructions is on rapid rise. Fly ash, a spinoff from coal calcined thermal power plants with pozzolanic properties is used for cement replacement in concrete. Fly ash concrete is cost effective, which modifies and improves the fresh and hardened properties of concrete and additionally addresses the disposal and storage issues of fly ash. Soft computing techniques have gained attention in the civil engineering field which addresses the drawbacks of classical experimental and computational methods of determining the concrete compressive strength with varying percentages of fly ash. In this study, models based on soft computing techniques employed for the prediction of the compressive strengths of fly ash concrete are collected from literature. They are classified in a categorical way of concrete strengths such as control concrete, high strength concrete, high performance concrete, self-compacting concrete, and other concretes pertaining to the soft computing techniques usage. The performance of models in terms of statistical measures such as mean square error, root mean square error, coefficient of correlation, etc. has shown that soft computing techniques have potential applications for predicting the fly ash concrete compressive strengths.

• PNF and Movement
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• v.19 no.1
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• pp.105-113
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• 2021

Purpose: The purpose of this study was to investigate the effect of trunk-stabilization training using stabilizing reversal and rhythmic stabilization techniques of PNF on trunk muscle strength and respiratory function in elderly stroke patients. Methods: There were 26 stroke patients included in the study. Patients were divided into two groups, and all patients performed exercise 30 min five times per week for six weeks. The experimental group performed trunk stability exercise using stabilizing reversal and rhythmic stabilization techniques of PNF, and the control group performed flexibility and strength training. Trunk muscle strength, forced vital capacity, maximum inspiratory pressure, and maximum expiration pressure were measured to determine the changes after the intervention. For statistical processing, a paired t-test was performed within the group, and the value after intervention was performed as an independent t-test to find out the difference between the two groups. Results: In the experimental group, all of the trunk muscle strength, forced vital capacity, maximum inspiratory pressure, and maximum expiration pressure showed significant differences according to the intervention. In the control group, there were statistically significant differences in trunk muscle strength and forced vital capacity, but the maximum inspiratory pressure and the maximum expiration pressure did not show any statistical change. Conclusion: From these results, it can be seen that the trunk stability exercises that use the proprioceptive neuromuscular promotion method of stable reversal and rhythm stabilization can be a good intervention for the respiratory function of stroke patients.

• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.587-600
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• 2016

Purpose: This paper evaluates the performance of the pre-control(PC), an alternative to statistical process control techniques and compares with a control chart considering the tolerance of process. Methods: The previous studies for PC have drawbacks that PC with two linked stages, qualification and running, are discussed separately and independently. Hence this paper analyzes the performance of PC by integrating two stages. Results: Average outgoing quality limits to grasp the outcome of PC are provided by computational results for two process capability indexes, $C_p$ and $C_{pk}$ and the usefulness of PC from comparative experiments with modified control charts is commented. Conclusion: Helpful guidelines for quality managers to apply PC in practice and areas of process for PC to be more benefit are presented.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.139-147
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• 2009

Control charts are used to distinguish between chance and assignable causes in the variability of quality characteristics. When a control chart signals that an assignable cause is present, process engineers must initiate a search for the assignable cause of the process disturbance. Identifying the time of a process change could lead to simplifying the search for the assignable cause and less process down time, as well as help to reduce the probability of incorrectly identifying the assignable cause. The change point estimation by likelihood theory and the built-in change point estimation in a control chart have been discussed until now. In this article, we discuss two kinds of process change point estimation when the CUSUM ($\bar{x}$, s) control chart for monitoring process mean and variance simultaneously is operated. Throughout some numerical experiments about the performance of the change point estimation, the change point estimation techniques in the CUSUM ($\bar{x}$, s) control chart are considered.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.127-136
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• 2011

Multiplicative noise model is the one of popular method for masking continuous variables. In this paper, we propose the transformation on the variable to which random noise was multiplied. An advantage of the masking method using proposed transformation is that the masking data users can obtain the unbiased values of mean and variance of original (unmasked) data. We also consider the data utility and correlation structure of variables when we apply the proposed multiplicative noise scheme. To investigate the properties of the method of masking based on multiplicative noise, a simulation study has been conducted using the 2008 Householder Income and Expenditure Survey data.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.261-269
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• 2015

Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of logarithmic hazard learning effects property.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.179-184
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• 2004

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This article considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process disturbance model under consideration is an IMA(1,1) model with a location shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied by compensating the predicted deviation from target. For detecting special causes the two kinds of exponentially weighted moving average (EWMA) control chart are applied to the observed deviations: One for detecting location shift and the other for detecting increment of variability. It was assumed that the adjustment of the process under the presence of a special cause may change any of the process parameters as well as the system gain. The effectiveness of the IPC scheme is evaluated in the context of the average cost per unit time (ACU) during the operation of the scheme. One major objective of this article is to investigate the effects of the process parameters to the ACU. Another major objective is to give a practical guide for the efficient selection of the parameters of the two EWMA control charts.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.529-536
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• 2016

The purpose of this research is to evaluate the quality of Differential Police Response strategy. Although it has been approximately three years since these new police response systems were introduced, there is no research to evaluate them empirically. Using two types of statistical quality control techniques, Xbar-R control charts for variables data and P charts for attributes data, this study analyzes approximately 3,000 calls reported throughout the year 2012 to the 112 Integrated Dispatch Center in Ik-san police station. The Xbar-R control charts revealed that the police did not consistently respond to an emergency call for service (i.e., code one case) within 3 minutes. The P control chart also identified that there was a significant variation in the portion/number of defective calls where police failed to respond to non-emergency calls for service within 5 minutes. The results from this study suggest the police may need to review the target response time for code 1 and code 2 respectively.