• 품질경영학회지
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• 제30권2호
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• pp.99-117
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• 2002

Variable sampling interval(VSI) and variable sample size(VSS) control charts vary the sampling rate for the next sample depending on the current chart statistic. This paper develops EWMA charts with the VSI and VSS features, and investigates the effectiveness of these charts in context of an economic model. The economic properties of these charts are evaluated by using Markov chain methods. The model contains cost parameters which allow the specification of the costs associated with sampling, false alarms, and operating off target. This economic model can be used to quantify the cost saving that can be obtained by using control charts with the VSI and VSS features instead of with the fixed sampling rate(FSR) feature, and can also be used to gain insight into the way that control charts with the VSI and VSS features should be designed to achieve optimal economic performance. The economic performance of X charts with the VSI and VSS features is also considered.

• 산업경영시스템학회지
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• 제17권30호
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• pp.101-106
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• 1994

The basic of the VSI charts is that if the sample statistic computed after a sample is taken shows some indication of a process change than the sampling interval before the next sample should be short otherwise long. This paper was shown the VSS chart can be considerably more efficient than the FSS chart and the effectiveness of VSI R chart with S chart used for monitoring a process standard deviation.

• 대한산업공학회지
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• 제33권4호
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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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.560-570
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• 2006

This paper proposes a selectively cumulative sum (S-CUSUM) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI S-CUSUM chart is to adjust sampling intervals and to accumulate previous samples selectively in order to increase the sensitivity. The VSI S-CUSUM chart employs a threshold limit to determine whether to increase sampling rate as well as to accumulate previous samples or not. 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 S-CUSUM 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 number L is a decision variable and is called a 'control length'. A Markov chain model is employed to describe the VSI S-CUSUM sampling process. Some useful 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 S-CUSUM chart is proposed. Comparative studies show that the proposed VSI S-CUSUM chart is uniformly superior to the VSI CUSUM chart or to the Exponentially Weighted Moving Average (EWMA) chart with respect to the ATS performance.

• East Asian Economic Review
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• 제20권4호
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• pp.469-491
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• 2016

In this paper, we estimate the exchange rate exposure, indicating the effect of exchange rate movements on firm values, for a sample of 1,400 firms in seven East Asian countries. The exposure estimates based on various exchange rate variables, return horizons and a control variable are compared. A key result from our analysis is that the long term effect of exchange rate movements on firm values is greater than the short term effect. And we find very similar results from using other exchange rate variables such as the U.S. dollar exchange rate, etc. Second, we add exchange rate volatility as a control variable and find that the extent of exposure is not much changed. Third, we examine the changes in exposure to exchange rate volatility with an increase in return horizon. Consequently the ratio of firms with significant exposures increases with the return horizons. Interestingly, the increase of exposure with the return horizons is faster for exposure to volatility than for exposure to exchange rate itself. Taken as a whole, our findings suggest that the socalled "exposure puzzle" may be a matter of the methodology used to measure exposure.

• 대한간호학회지
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• 제11권2호
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• pp.105-123
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• 1981

This study was carried out during the month of September 1976 to analyse and compare the health complaints of two groups of the university women, those who lived at home and those who lived in the university dormitory. The purpose of the study was to provide basic data required by the university health program for planning related to the health need of women students. The study sample consisted of 434 students living in the dormitory and 381 students living at home enrolled for the fall semester 1976 in a womens university in Seoul. The instrument used for the collection of data was an abridged version of a modified Cornell Medical Index. The questionarre included 35 items related to physical health complaint and 22 items related to mental health complaints. The data was treated by a computer (SPSS) using one way analysis, the Fishers' ratio and Chi-Square test at the 5％ level were used for the test for statistical significance. The interpretation of this study is limited due to the sample which was restricted to one university and not randomly selected. To guide the direction of the study, it was hypothesized that the rate of expressed health problems of students living in the dormitory would be Venter than that of students living at home. The hypothesis was tested and rejected. The following is a summary of the findings; 1. Total health (physical and mental) complaints a. There was no statistically significant difference between the home and dormitory groups with regard to total health complaints expressed. b. The rate of total complaints expressed by the home group significantly higher than dormitory group only among third year students. c. There was no statistically significant between the home and dormitory groups in their satisfaction with their economic situation. d. The home group showed a significantly higher rate of complaints related to the Nervous System compared to that of the dormitory group. 2. Physical health complaints a. Students living at home showed a significantly higher rate of physical complaints than the dormitory group. b. When the year variable was controlled, the third year was the only group which showed a different rate between home and dormitory groups; the home group presented a higher rate. c. Since the year variable seemed to affect the physical complaints those data were further analysed to see whether the specific system areas were operating as variables in each year. The results were as follow: Among the home group, First year students showed a higher rate in Family History of Disease, while the third year students more Nervous System and Cardiovascular System complaints. Among the dormitory group, only fourth year students showed a higher rate in the Skeletal-Muscular System. This was the only area the dormitory group though only for the fourth year students supported the hypothesis. d. When the economic satisfaction variable was controlled, the satisfied group was the only group which showed a different rate between home and dormitory groups; the home group presented higher rate. e. Since the economic satisfaction variable seemed to affect the physical complaints those data were further analyzed to see whether the specific system areas were operating as variables in each economic satisfaction level, but there was no statistically significant difference between home and dormitory groups. 3. Mental health complaints a. There was no significantly difference between home and dormitory groups with regard to mental health complaints expressed. b. When the year variable was controlled the third year group was the only group which showed a different rate between home and dormitory groups; the home group presented a higher rate. c. Since the year variable seemed to affect the mental complaints, those data were further analyzed to see whether the specific system areas were operatings variables in each economic satisfaction level. The result were as follows: Among the home group, the third year students showed higher rates in Inadequacy and Anxiety. d. When the economic satisfaction variable was controlled, the very satisfied group was the only group which showed a different rate between home and dormitory groups: the home group presented a higher rate. Since the economic satisfaction variable seemed to affect the mental complaints, those data were further analysed to see whether the specific system areas were operating as variables in each economic satisfaction level, but there was no statistical significant difference between the home and dormitory groups. Although the social environment of dormitory life differs from family life, there was no difference in the rate of total health problem complaints between the home and dormitory groups but the home group showed a higher rate of physical health complaints than the dormitory group. Possible positive factors influencing dormitory life and negative factors influencing family life affecting health complaints must be explored in order to relate to the health needs of the university health program. This study could not define the causes for the fewer physical complaints of dormitory students living at home. Further study of such causal factors recommended in order to provide the data needed to contribute to a more effective health program.

• 수산경영론집
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• 제42권3호
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• pp.1-13
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• 2011

It is necessary to set up a standard of estimation for annual unit price of sale and cost, damage rate for calculating compensation against fishery damage objectively. Two items on the unit price and cost have regulations but the damage rate has not, so it may occurred some problems such as reasonability and balance because the estimation should be handling by an appraiser's knowledge and experience. This study has analyzed using Regression model and searched variable costs and fixed costs about each items appraisers to operate in the present. It is compare profit damage index is calculated by an estimated model and an appraised example. This analysis showed highly 23-30% estimated model more than appraised example. It means the overestimation for fishery damage. This difference has caused by limited data, lack of sample, much difference in the standard deviation, and has not classified each kind of business and weight of coastal fishery, the overestimation more than what expected. This study has analyzed that the applied rate of fixed and variable cost in relation to the compensation in the cost of coastal fishery is very valuable.

• 한국안전학회지
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• 제23권6호
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• pp.84-90
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• 2008

The mass loss rate and heat release rate of puzzle mats were analysed using variable external irradiation level. Five samples of puzzle mat were tested in this study : Type A, B, C, D and E. Type A, B and C are all general grades whereas Type D and E are both Flame retardant grades. Incident heat fluxs of $25kW/m^2$, $35kW/m^2$, $50kW/m^2$ and $70kW/m^2$ were selected for these experiments. All samples were tested in the horizontal orientation and were wrapped in a single layer of aluminum foil. Each sample was nominally 20mm thick and 100mm square. The combustion heat and mass loss rate were carried out from Oxygen bomb calorimeter and mass loss calorimeter according to ISO 5660-1 respectively. Heat release rates were calculated using the equation ${\dot{Q}}=A_f{\dot{m}}"_X{\Delta}H_c=0.75A_f{\dot{m}}"{\Delta}H_c$. where $A_f$ is the horizontal burning area of the sample, $\dot{m}"$ is mass loss rate per unit area, ${\Delta}H_c$ is complete heat of combustion and 0.75 is combustion efficiency.

• East Asian Economic Review
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• 제22권2호
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• pp.141-176
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• 2018

The paper analyzes and compares the effects of domestic monetary policy using DSGE, DSGE-VAR, and VAR based on a two-country open economy model of Korea and the U.S. According to impulse response analysis, a domestic interest rate hike raises won value in the case of DSGE and DSGE-VAR models, while in the case of the unrestricted VAR model, it lowers won value. In the marginal data density standard, DSGE-VAR (${\mu}=1$) is superior to DSGE or Bayesian VAR over the sample period. Conversely, in the in-sample RMSE criterion, especially for the won/dollar exchange rate, VARs are superior to DSGE or DSGE-VAR. It is necessary to study further if these differences are caused by model misspecification or omitted variable bias.

• 응용통계연구
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• 제32권4호
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• pp.631-642
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• 2019

다수의 항목무응답이 발생한 표본조사에서는 추정의 정확성이 떨어진다. 이를 해결하기 위한 많은 방법이 개발되었으나 응답률이 관심변수에 의해 영향을 받는 경우임에도 이를 고려하지 않고 랜덤으로 무응답이 발생한다는 가정 하에서 사용하는 무응답 처리 방법을 사용하게 되면 편향이 발생하는 것으로 알려져 있다. Chung과 Shin (2017)과 Min과 Shin (2018)은 응답률이 관심변수의 함수인 경우에서 발생된 편향을 적절히 처리하여 추정의 정확성을 향상시키는 방법을 제안하였다. 본 연구에서는 응답률 함수가 선형(linear)이면서 초모집단 모형의 오차가 정규분포를 따르는 경우를 살펴보았으며 층별 모집단 수가 편향 보정에 영향을 주는지도 살펴보았다. 모의실험을 통하여 제안된 추정량의 성능을 살펴보았으며 실제 자료 분석을 통해 이를 확인하였다.