• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.446-454
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• 2010

According to the original chart parsing algorithm, a sentence is parsed in a strict left-to-right order. The modified chart parsing algorithm proposed in this paper breaks the strictness. With the proposed algorithm, a sentence is parsed in a random order. Conventional left-to-right parsing is also possible, since left-to-right parsing is a special case of random-order parsing. The proposed parsing algorithm is an extension of chart parsing algorithm and its control structure is very simple, so that it is easy to implement the algorithm.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1353-1366
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• 2015

These days Shewhart control chart for evaluating stability of the process is widely used in various field. But it must follow strict assumption of distribution. In real-life problems, this assumption is often violated when many quality characteristics follow non-normal distribution. Moreover, it is more serious in multivariate quality characteristics. To overcome this problem, many researchers have studied the non-parametric control charts. Recently, SVDD (Support Vector Data Description) control chart based on RBF (Radial Basis Function) Kernel, which is called K-chart, determines description of data region on in-control process and is used in various field. But it is important to select kernel parameter or etc. in order to apply the K-chart and they must be predetermined. For this, many researchers use grid search for optimizing parameters. But it has some problems such as selecting search range, calculating cost and time, etc. In this paper, we research the efficiency of selecting parameter regions as data structure vary via simulation study and propose a new method for determining parameters so that it can be easily used and discuss a robust choice of parameters for various data structures. In addition, we apply it on the real example and evaluate its performance.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.497-515
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• 2016

Modern processes often monitor more than one quality characteristic that are referred to as multivariate statistical process control (MSPC) procedures. The MSPC is the most rapidly developing sector of statistical process control and increases interest in the simultaneous inspection of several related quality characteristics. Most multivariate detection procedures based on a multi-normality assumptions are independent, but there are many processes that assume non-normality and correlation. Many multivariate control charts have a lack of related joint distribution. Copulas are tool to construct multivariate modelling and formalizing the dependence structure between random variables and applied in several fields. From copula literature review, there are a few copula to apply in MSPC that have multivariate control charts, and represent a successful tool to identify an out-of-control process. This paper presents various types of copulas modelling for the multivariate control chart. The performance measures of the control chart are the average run length (ARL) and the average number of observations to signal (ANOS). Furthermore, a Monte Carlo simulation is shown when the observations were from an exponential distribution.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.787-796
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• 2014

Situations where sample size is not constant are common when monitoring a process with Poisson count data. In this paper, we propose a generalized likelihood ratio(GLR) control chart to detect shifts in the Poisson rate when the sample size varies. The performance of the proposed GLR chart is compared with the performance of several cumulative sum(CUSUM) type charts. It is shown that the overall performance of the GLR chart is comparable with CUSUM type charts and is significantly better in cases where the actual value of the shift is different from the pre-specified value in CUSUM type charts.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.359-364
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• 2002

In case of pn control chart often used in mass production system of plant industry and so on, we could evaluate it's performance by the approximation to normal distribution. It has many differences according to sample sizes and defective fraction, and have disadvantage that needs much samples to use the normal distribution approximation. Existent control charts can not detect the cause of process something wrong because it is taking the sampling intervals of fixed length about all times from the process. Therefore, to overcome this shortcoming we use VSI(variable sampling intervals) techniques in this paper. This technique takes a long sampling interval to have the next sampling point if the sample point is in stable state, and if the sample point is near control lines, it takes short sampling interval because the probability to escape control limit is high. To analyze performance of pn control charts that have existent fixed sampling intervals(FSI) and that use VSI technique, we compare ATS of two charts, and analyze the performance of each control chart by the sample sizes, process fraction defective and control limits that Ryan and Schwertman had proposed.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.99-107
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• 2019

The "Risk management" and "Security monitoring" activities for cyber security are deeply correlated in that they prepare for future security threats and minimize security incidents. In addition, it is effective to apply a pattern model that visually demonstrates to an administrator the threat to that information asset in both the risk management and the security system areas. Validated pattern models have long-standing "control chart" models in the traditional quality control sector, but lack the use of information systems in cyber risk management and security systems. In this paper, a cyber Security Risk Monitoring (SRM) system that integrates risk management and a security system was designed. The SRM presents a strategy for applying 'security control' using the pattern of 'control charts'. The security measures were integrated with the existing set of standardized security measures, ISMS, NIST SP 800-53 and CC. Using this information, we analyzed the warning trends of the cyber crisis in Korea for four years from 2014 to 2018 and this enables us to establish more flexible security measures in the future.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.149-153
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• 2008

$C_p$ and other process capability indices are used extensively in industry, However, They are inadequate and widely misused. In a practical application, process average ${\mu}$ is almost always drifted by various assignable causes in process. And control charts will not detect these shifts in process average. In this study, incorporating these undetected shifts, a new capability analysis method is introduced.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.365-370
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• 2002

In this study, according to MARMA(1,0) model which was suggested by Seppala, in case of existing autocorrelation in X control chart and EWMA control chart, the standard method and the non-parametric bootstrap method were compared and analysed using the bootstrap method which use the resampling prediction residual.

• Journal of Korean Society for Quality Management
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• v.26 no.2
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• pp.51-60
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• 1998

Exponetially weighted moving average(EWMA) control chart to simultaneously monitor correlation coefficients of several correlated quality variables under multivariate normal process are proposed. Performances of the proposed control charts are measured in terms of average run length(ARL) by simulation. Numerical results show that smaller values of smoothing constant are more efficient in terms of ARL.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.217-234
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• 2000

Approximately normalized control charts, called Q charts, have been given Quesenberry(1991) for charting in process of short-run, job-shop, etc. We consider a Q chart with inspection error for job-shop floor under geometric distribution, which can be used for processes when a fraction nonconforming is very small. Our results would be applied for designing other control charts with inspection error.