• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.487-501
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• 2017

A machine vision system (MVS) is a computer system that utilizes one or more image-capturing devices to provide image data for analysis and interpretation. Recently there have been a number of industrial- and medical-device applications where control charts have been proposed for use with image data. The use of image-based control charting is somewhat different from traditional control charting applications, and these differences can be attributed to several factors, such as the type of data monitored and how the control charts are applied. In this paper, we investigate the adjustment effect of image size and region of interest (ROI) size, when we use control charts to monitor grayscale image data in industry.

• Journal of radiological science and technology
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• v.39 no.4
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• pp.527-534
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• 2016

Dual-energy X-ray absorptiometry (DEXA) is the most widely used technical instrument for evaluating bone mineral content (BMC) and density (BMD) in patients of all ages. In 2016, DEXA devices operating is 5617 in Korea. In this study we investigated the quality of management practices survey for DEXA equipment and we analyzed it. We got a survey response rate of 12.6%. Accurate bone densitometry test is used data for estimation a patient's risk of fracture. However, improper bone densitometry will increase the possibility of causing a false positive. Therefore. it is essential to use the proper aids accurate bone densitomenty to be performed, and the quality control of the device to reduce the error factor of the tester through the training to reduce error for the device and the attitude.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.436-437
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• 2012

Double patterning technology (DPT) has been suggested as a promising candidates of the next generation lithography technology in FLASH and DRAM manufacturing in sub-40nm technology node. DPT enables to overcome the physical limitation of optical lithography, and it is expected to be continued as long as e-beam lithography takes place in manufacturing. Several different processes for DPT are currently available in practice, and they are litho-litho-etch (LLE), litho-etch-litho-etch (LELE), litho-freeze-litho-etch (LFLE), and self-aligned double patterning (SADP) [1]. The self-aligned approach is regarded as more suitable for mass production, but it requires precise control of sidewall space etch profile for the exact definition of hard mask layer. In this paper, we propose etch end point detection (EPD) in spacer etching to precisely control sidewall profile in SADP. Conventional etch EPD notify the end point after or on-set of a layer being etched is removed, but the EPD in spacer etch should land-off exactly after surface removal while the spacer is still remained. Precise control of real-time in-situ EPD may help to control the size of spacer to realize desired pattern geometry. To demonstrate the capability of spacer-etch EPD, we fabricated metal line structure on silicon dioxide layer and spacer deposition layer with silicon nitride. While blanket etch of the spacer layer takes place in inductively coupled plasma-reactive ion etching (ICP-RIE), in-situ monitoring of plasma chemistry is performed using optical emission spectroscopy (OES), and the acquired data is stored in a local computer. Through offline analysis of the acquired OES data with respect to etch gas and by-product chemistry, a representative EPD time traces signal is derived. We found that the SE-EPD is useful for precise control of spacer etching in DPT, and we are continuously developing real-time SE-EPD methodology employing cumulative sum (CUSUM) control chart [2].

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.7
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• pp.983-994
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• 2004

The aim of this study is to provide fundamental data on the development of ready-to-wear clothes appropriate for the body types of elderly women. The study was conducted targeting 318 elderly women over 60 years of age whose fields of action were colleges for the elderly, sports centers, or business sites in Seoul and the neighboring districts. A total of 44 features in the upper body were used for the anthropometric measurement and analysis using anthropometry and photometry. The results of the study are as follows: 1. Somatotypes were classified into three types according to a cluster analysis using height and weight indices. Type 1 is the group with long and undersized upper body and straight body type since the face of the upper body is long relative to height and width, girth and depth are the smallest relative to weight, the breasts are somewhat fat, with a small extent of drooping and a straight back. Type 2 is the group that is considered fat relative to the body, has broad shoulders, drooping breasts with a wide space between them, and a back-bent upper body. Type 3 is the group that has a bent shape, the shortest upper body relative to height, and showing average obesity factors. 2. Indices of height and weight were used for factor analysis, cluster analysis, and discriminant analysis in order to classify upper body somatotype according to shape while excluding size factors of elderly women＇s upper body somatotype. The same method was used to compare and verify the result according to the absolute measurement and height index. Classification based on height and weight indices demonstrate that such somatotype classification minimizes the personal equation of body shape and it induces better classification based on shape as the results showed the highest cumulative sum of square(CUSUM) at 78.38% while six factors showed the smallest result and the hit rate for the classified three groups showed the highest result at 95.30%.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.83-91
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• 2021

Health is an outset of psychological, social, financial, and physical state. Several macroeconomic factors are entangled with health and mortality. Infant mortality and life expectancy are two keyguard on demographic research context on last few decades. On the other hand, foreign inflows play an unprecedent role for raising economic circulation and providing more opportunities to build a better society. The study aims to investigate the relationship between foreign direct investment (FDI), economic growth, and Bangladesh's health. This study employs time-series data from 1980 to 2018. Results show, with Auto-regressive Distribute Lag (ARDL) model, that there is significant cointegration among variables. Foreign investment and economic output relate significantly and positively to health. On the contrary, education is quasi-linked with a different sign-on different model. For model validation, pitfalls of time-series multicollinearity, heteroscedasiticy, and autocorrelation are not present. Also, CUSUM and CUSUMSQ tests are validating the model as stable and fit for future prediction. Medical assessment and education need more attention from the government as well as the private sector. FDI can play a catalyst role for improving the health sector, raising opportunity in educating and creating a better lifestyle. In order to optimize foreign investment, the government should implement necessary reforms and policies.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.1-9
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• 2023

Until now, the periods of river discharge management throughout a year are divided into flood and non-flood periods, and the ranges of discharges to be managed are broadly defined from drought discharge to flood discharge. In this study, using the long-term daily discharge data from 8 points of four major rivers, we propose a method of dividing the year into several periods with the homogeneous mean and dispersion of discharges. As a result of the study, the period of through a year was different depending on the point, but it could be divided into pre-flood period, flood period, and post-flood period. And the more subdivided the period, the more decreased the ratio of the maximum discharge to the minimum discharge. In addition, in order to ensure that the discharge for a year is more than the drought discharge and less than the flood discharge, to set the range of discharge management per period as the average flow ± standard deviation for each period is proposed.

• Management & Information Systems Review
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• v.34 no.3
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• pp.17-39
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• 2015

This study examined the structural changes and volatility in the global stock markets using a Markov Regime Switching ARCH model developed by the Hamilton and Susmel (1994). Firstly, the US, Italy and Ireland showed that variance in the high volatility regime was more than five times that in the low volatility, while Korea, Russia, India, and Greece exhibited that variance in the high volatility regime was increased more than eight times that in the low. On average, a jump from regime 1 to regime 2 implied roughly three times increased in risk, while the risk during regime 3 was up to almost thirteen times than during regime 1 over the study period. And Korea, the US, India, Italy showed ARCH(1) and ARCH(2) effects, leverage and asymmetric effects. Secondly, 278 days were estimated in the persistence of low volatility regime, indicating that the mean transition probability between volatilities exhibited the highest long-term persistence in Korea. Thirdly, the coefficients appeared to be unstable structural changes and volatility for the stock markets in Chow tests during the Asian, Global and European financial crisis. In addition, 1-Step prediction error tests showed that stock markets were unstable during the Asian crisis of 1997-1998 except for Russia, and the Global crisis of 2007-2008 except for Korea and the European crisis of 2010-2011 except for Korea, the US, Russia and India. N-Step tests exhibited that most of stock markets were unstable during the Asian and Global crisis. There was little change in the Asian crisis in CUSUM tests, while stock markets were stable until the late 2000s except for some countries. Also there were stable and unstable stock markets mixed across countries in CUSUMSQ test during the crises. Fourthly, I confirmed a close relevance of the volatility between Korea and other countries in the stock markets through the likelihood ratio tests. Accordingly, I have identified the episode or events that generated the high volatility in the stock markets for the financial crisis, and for all seven stock markets the significant switch between the volatility regimes implied a considerable change in the market risk. It appeared that the high stock market volatility was related with business recession at the beginning in 1990s. By closely examining the history of political and economical events in the global countries, I found that the results of Lamoureux and Lastrapes (1990) were consistent with those of this paper, indicating there were the structural changes and volatility during the crises and specificly every high volatility regime in SWARCH-L(3,2) student t-model was accompanied by some important policy changes or financial crises in countries or other critical events in the international economy. The sophisticated nonlinear models are needed to further analysis.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.907-920
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• 2015

Charts based on geometric distribution are effective to monitor the proportion of nonconforming items in high-quality processes where the in-control proportion nonconforming is low. The implementation of this chart is often based on the assumption that in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice for high-quality process where the proportion of nonconforming items is very small. An inaccurate estimate of the parameter can result in estimated control limits that cause unreliability in the monitoring process. The maximum likelihood estimator (MLE) is often used to estimate in-control proportion nonconforming. In this paper, we recommend a Bayes estimator for the in-control proportion nonconforming to incorporate practitioner knowledge and avoid estimation issues when no nonconforming items are observed in the Phase I sample. The effects of parameter estimation on the geometric chart and the geometric CUSUM chart are considered when the MLE and the Bayes estimator are used. The results show that chart performance with estimated control limits based on the Bayes estimator is generally better than that based on the MLE.