• Journal of Korean Society for Quality Management
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• v.35 no.1
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• pp.24-34
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• 2007

This paper investigates the average run length (ARL) of a selectively moving average (S-MA) control chart. The S-U chart is designed to detect shifts in the process mean. The basic idea of the S-MA chart is to accumulate previous samples selectively in order to increase the sensitivity. The ARL of the S-MA chart was shown to be monotone decreasing with respect to the decision length in a previous research [3]. This paper derives the steady-state ARL in a closed-form and shows that the monotone property is resulted from head-start assumption. The steady-state ARL is shown to be a sum of head-start ARL and an additional term. The statistical design procedure for the S-MA chart is revised according to this result. Sensitivity study shorts that the steady-state ARL performance is still better than the CUSUM chart or the Exponentially Weighted Moving Average (EWMA) chart.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.243-251
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• 1995

본 연구에서는 자동상관인 공정의 변화를 빠르게 탐지할 수 있는 Special-Cause CUSUM 관리도를 사용하여 다섯가지 시계열 모델에 대해 다음과 같은 연구를 수행한다. 첫째 ACF와 PACF로 파라미터에 따른 ARL의 변화를 쉽게 해석할 수 있는 방법과 둘째로 독립인 관측값에 적용하는 Hawkins(1992)의 ARL 간략계산법을 자동상관인 공정에서도 사용할 수 있는 기법을 제시하여 기존의 시뮬레이션을 이용한 ARL 계산법에 비해 빠르고도 정확한 값을 구한다. 끝으로 두가지 유형의 평균이동에 대한 ARL 변화를 각각 계산해 보아 그 효과를 비교분석 한다.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.143-152
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• 1999

In Shewhart control chart, the average run length(ARL) is calculated using the mean of a conventional geometric distribution(CGD) assuming a sequence of identical and independent Bernoulli trials. In this, the success probability of CGB is the probability that any point exceeds the control limits. When the process is in-control state, there is no problem in the above assumption since the probability that any point exceeds the control limits does not change if the in-control state continues. However, if the out-of-control state begins and continues during the process, the probability of exceeding the control limits may take two forms. First, once the out-of-control state begins with exceeding probability p, it continues with the same exceeding probability p. Second, after the out-of-control state begins, the exceeding probabilities may very according to some pattern. In the first case, ARL is the mean of CGD with success probability p as usual. But in the second case, the assumption of a sequence of identical and independent Bernoulli trials is invalid and we can not use the mean of CGD as ARL. This paper concentrate on that point. By adopting one generalized binomial distribution(GBD) model that allows correlated Bernoulli trials, generalized geometric distribution(GGD) is defined and its mean is derived to find an alternative ARL when the process is in out-of-control state and the exceeding probabilities take the second form mentioned in the above. Small-scale simulation is performed to show how an alternative ARL works.

• Animal cells and systems
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• v.11 no.2
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• pp.175-182
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• 2007

The lysozyme II gene of cabbage butterfly Artogeia rapae was cloned from fat body of the larvae injected with E. coli and its nucleotide sequence was determined by the RACE-PCR. It has an open reading frame of 414 bp nucleotides corresponding to 138 amino acids including a signal sequence of 18 amino acids. The estimated molecular weight and the isoelectric point of the lysozyme II without the signal peptide were 13,649.38 Da and 9.11, respectively. The A. rapae lysozyme II (ARL II) showed the highest identity (81%) in the amino acid sequence to Manduca sexta lysozyme among other lepidopteran species. The two catalytic residues ($Glu^{32}$ and $Asp^{50}$) and the eight Cys residue motifs, which are highly conserved among other c-type lysozymes in invertebrates and vertebrates, are also completely conserved. A phylogenetic analysis based on amino acid sequences indicated that the ARL II was more closely related to M. sexta, Hyphantria cunea, Heliothis virescens, and Trichoplusia ni lysozymes. The ARL II gene was expressed in Spodoptera frugiperda 21 insect cells and the recombinant ARL II (rARL II) was purified from cell-conditioned media by cation exchange column chromatography and reverse phase FPLC. The purified rARL II was able to form a clear zone in lysoplate assay against Micrococcus luteus. The lytic activity was estimated to be 511.41 U/mg, 1.53 times higher than that of the chicken lysozyme. The optimum temperature for the lytic activity of the rARL II was $50^{\circ}C$, the temperature dependency of the absolute lytic activity of rARL II was higher than that of the chicken lysozyme at low temperatures under $65^{\circ}C$.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.141-143
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• 2010

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.269-281
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• 2008

This paper evaluated the collection development of the Korean collection at the A university over the several decade. Compared against the ACRL standard Formula A, the result demonstrated that the Korean library collection is still needed to increase Korean collection to support Korean-related program and Korean community in the area. When we share western language materials in the library as the same area studies resources, we can evaluate Korean studies collection as Level B. Comparison with similar institutions (ARL comparisons) shows that the collection is the middle among 15 universities which provide Korean programs. The situation for Korean resources at the A university is needed to get more support from Korean institutes and Korean societies to keep up with the Korean collection for academics and regional community users as well.

• 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.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.97-103
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• 2003

Shewhart-type control charts have historically been used for attribute data, though they have ARL biased property and even are unable to detect the improvement of a process with some process parameters. So far most efforts have been made to improve the performance of attribute control charts in terms of faster detection of special causes without increasing the rates of false alarm. In this paper, control limits are proposed that yield an ARL (nearly) unbiased chart for attributes. Optimal design is also proposed for attribute control charts under a natural sense of criterion.

• Journal of East-West Nursing Research
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• v.20 no.1
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• pp.57-62
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• 2014

Purpose: The purpose of this study was to evaluate the effect of a mixture of ARL oils, Agastache rugosa, Rosemarinu officinalis, and Lavandula angustifolia on atopic dermatitis (AD) model on NC/Nga mice. Methods: Twenty-four, 6 week-NC/Nga mice were assigned to a control group (C, n=8), an AD-induced group (E, n=8), and an ARL oil-treated group (E, n=8) that had two treatments per day for 6 days. Epidermis thickness, total amount of collagen and expression of TGF-${\beta}$ in the AD induced mice were measured. Results: The ARL oil-treated group showed a significantly decreased epidermis thickness, and a greater amount of collagen and expression of TGF-${\beta}$ compared with the AD-induced group. Conclusison: ARL oil may be a putative resources for care or treatment of AD in the view of nursing intervention.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.485-495
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• 2018

The CCC-r chart is more effective than traditional attribute control charts for monitoring high-quality processes. In-control process parameters are typically unknown and should be estimated when implementing a CCC-r chart. Phase II control chart performance can deteriorate due to the effect of the estimation error. In this paper, we used the standard deviation of average run length (ARL) as well as the average of ARL to quantify the between-practitioner variability in the CCC-r chart performance. The results indicate that the CCC-r chart requires larger Phase I data than previously recommended in the literature in order to have consistent chart in-control performance among practitioners.