• 대한산업공학회지
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• 제23권4호
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• pp.793-802
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• 1997

A sampling plan is presented for situations where sampling inspection is based on the quality characteristic of interest and items in rejected lots are screened based on a correlated variable. A cost model is constructed which involves the costs of misclassification errors, sampling and screening inspections. A method of finding optimal values of sample size, acceptance number and cutoff value on the correlated variable is presented, and numerical studies are given.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• 산경연구논집
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• 제8권4호
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• pp.15-21
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• 2017

Purpose - In this work, we examined the causal relationship between credit loans from households (CLH), loan collateralized with housing (LCH) and an interest of certificate of deposit (ICD) among others in South Korea. Furthermore, the optimal forecasts on the underlying model will be obtained and have the potential for applications in the economic field. Research design, data, and methodology - A total of 31 realizations sampled from the 4th quarter in 2008 to the 4th quarter in 2016 was chosen for this research. To achieve the purpose of this study, a regression model with correlated errors was exploited. Furthermore, goodness-of-fit measures was used as tools of optimal model-construction. Results - We found that by applying the regression model with errors component ARMA(1,5) to CLH, the steep and lasting rise can be expected over the next year, with moderate increase of LCH and ICD. Conclusions - Based on 2017-2018 forecasts for CLH, the precipitous and lasting increase can be expected over the next two years, with gradual rise of two major explanatory variables. By affording the assumption that the feedback among variables can exist, we can, in the future, consider more generalized models such as vector autoregressive model and structural equation model, to name a few.

• Journal of information and communication convergence engineering
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• 제2권4호
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• pp.214-218
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• 2004

In this paper, we have analyzed TCP performance over wireless correlated fading links with and without Snoop protocol. For a given value of the packet error rate, TCP performance without Snoop protocol is degraded as the fading is getting fast (i.e. the user moves fast). When Snoop protocol is introduced in the base station, TCP performance is enhanced in most wireless environments. Especially the performance enhancement derived from using Snoop protocol is large in fast fading channel. This is because packet errors become random and sporadic in fast fading channel and these random packet errors (mostly single packet errors) can be compensated efficiently by Snoop protocol's local packet retransmissions. But Snoop protocol can't give a large performance improvement in slow fading environments where long bursts of packet errors occur. Concerning to packet error rate, Snoop protocol results in the highest performance enhancement in the channel with mid-high values of packet error rate. This means Snoop protocol cannot fully fulfill its ability under too low or too high packet error rate environments.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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• pp.171-179
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• 2006

For the problem of variable selection in linear models, we consider the errors are correlated with V covariance matrix. Hocking's theorems on the effects of the overfitting and the underfitting in linear model are extended to the less than full rank and correlated error model, and to the ANCOVA model.

• Journal of the Korean Statistical Society
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• 제29권2호
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• pp.231-245
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• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.187-192
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• 2005

For the problem of variable selection in linear models, we consider the errors are correlated with V covariance matrix. Hocking's theorems on the effects of the overfitting and the undefitting in linear model are extended to the less than full rank and correlated error model, and to the ANCOVA model

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.557-578
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• 2007

In Response Surface Methodology (RSM), rotatability is a natural and highly desirable property. For second order general correlated regression model, the concept of robust rotatability was introduced by Das (1997). In this paper a new measure of robust rotatability for second order response surface designs with correlated errors is developed and illustrated with an example. A comparison is made between the newly developed measure with the previously suggested measure by Das (1999).

• Journal of the Korean Data and Information Science Society
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• 제27권2호
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• pp.559-564
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• 2016

The Durbin-Watson (DW) test in regression model and the Ljung-Box (LB) test in ARMA (autoregressive moving average) model are typical examples of correlated error tests. The DW test is used for detecting autocorrelation of errors using the residuals from a regression analysis. The LB test is used for specifying the correct ARMA model using the first some sample autocorrelations based on the residuals of a tted ARMA model. In this article, simulations with four data generating processes have been carried out to evaluate their performances as correlated error tests. Our simulations show that the DW test is severely dependent on the assumed AR(1) model but isn't sensitive enough to reject the misspecified model and that the LB test reports lackluster performance in general.

• 대한약침학회지
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• 제27권3호
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• pp.253-263
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• 2024

Objectives: Nurses face mental health issues like emotional labor, stress, and depression, increasing the risk of medical errors. This study assesses the mental health and medical errors among nurses in Korean medicine clinics in South Korea. Methods: The cross-sectional analysis involved 83 nurses, examining relationships between emotional labor, stress, depression, cognitive failure, Hwa-byung (HB) (a syndrome of suppressed anger in Korean culture), and medical errors. It identified factors associated with HB and medical errors using multiple regression analysis, presenting their odds ratios (ORs) with 95% confidence intervals (CIs). Results: The findings revealed a current HB prevalence of 19.28% and a 6-month medical error prevalence of 16.87% among participants. The regression analysis showed that higher levels of depression (OR = 1.368, 95% CI = 1.098 to 1.703, p = 0.005), cognitive failure (OR = 1.072, 95% CI = 1.011 to 1.136, p = 0.020), and HB trait (OR = 1.136, 95% CI = 1.005 to 1.284, p = 0.041) significantly correlated with HB presence. Conclusion: This groundbreaking study on this previously under-researched nurse workforce highlights the critical need for comprehensive mental health care, with the objective of significantly enhancing their mental well-being and improving their overall work environment.