• Communications for Statistical Applications and Methods
• /
• 제3권1호
• /
• pp.73-85
• /
• 1996

In this paper, we consider the distribution-free confidence intervals for the reliability of the stress-strength model when the stress X and strength Y depend linearly on some explanatory variables z and w, respectively. We apply these confidence intervals to the Rocket-Motor data and compare the results to those of Guttman et al. (1988). Some simulation results show that the distribution-free confidence intervals have better performance for nonnormal errors compared to those of Guttman et al. (1988), which are designed for normal random variables in respect that the former yield the coverage levels closer to the nominal coverage level than the latter.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 1998년도 가을 학술발표대회 논문집(III)
• /
• pp.946-951
• /
• 1998

In order to calculate the thermal stresses of massive concrete structures in non-steady state conditions the thermal properties of the materials have to be well known. Structural materials such as concrete, rock and soil are heterogeneous, damp and porous so that measurements of their thermal properties by conventional methods would result in large errors. In this study, thermal conductivity was measured by the device, QTM-D3 which is usually used in Japan. Variables are chosen as age, water content, temperature, aggregate content, S/A ratio and type of cementitious materials. Finally a model for thermal conductivity was proposed.

• 간호행정학회지
• /
• 제4권1호
• /
• pp.193-214
• /
• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein. 1967: Fishbein & Ajzen. 1975). the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances. continuing education opportunity. rigidity of the administration. paticipative decision making, latitude, group support, role conflict, work load, need for achievement. experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however. that path analysis can not count measurment errors: measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%), pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment, the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support, role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention, The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment', 'Rigidity of the administration' and latitude were also found to have important roles in predictingr the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• 간호행정학회지
• /
• 제4권1호
• /
• pp.183-214
• /
• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein, 1967;Fishbein & Ajzen. 1975), the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances, continuing education opportunity, rigidity of the administration, paticipative decision making, latitude, group support, role conflict, work load, need for achievement, experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however, that path analysis can not count measurement errors; measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%). pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment. the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support. role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention. The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment'. 'Rigidity of the administration' and latitude were also found to have important roles in predictor for the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• 운동영양학회지
• /
• 제25권1호
• /
• pp.35-41
• /
• 2021

[Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R²) and 85.9% (adjusted R²), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R²) and 82.6% (adjusted R²), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R²) and 91.0% (adjusted R²), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

• 응용통계연구
• /
• 제34권4호
• /
• pp.623-632
• /
• 2021

본 연구에서는 여러가지 시계열 모형 중 평활법(가법계절지수, 승법계절지수), 계절 ARIMA 모형, ARARCH 그리고 AR-GARCH 회귀모형을 이용하여 최대 전력수요를 예측하는 방법을 연구하였다. 이 때 가중 평균모형으로 추세를 갖는 시계열 모형과 온도에 대한 회귀 모형을 적절한 가중치로 예측 정확도를 높이는 방법도 연구하였다. 결과적으로 AR-GARCH 회귀모형으로 예측하는 것이 가중 우수함을 보였다.

• 한국항공운항학회지
• /
• 제23권2호
• /
• pp.63-68
• /
• 2015

This paper presents the algorithm for envelope protection of helicopters. The algorithm consists of two feedback control loops: inner loop and outer loop. As an inner loop control, model following control is designed to meet the ADS-33 handling qualities specification by minimizing the tracking errors between the responses of the actual model and those of the command filter. In order to implement envelope protection, saturation limiter is imposed to command channels in command filter, whose limits are computed corresponding to the envelope limit. Fast model predictive control is designed as an outer loop control to deal with saturation constraints generated by the inner loop envelope protection and also imposed by outer loop envelope protection variables. Simulation results show that the proposed algorithm yields good envelope protection performance.

• 한국측량학회지
• /
• 제37권2호
• /
• pp.71-79
• /
• 2019

Geolocation accuracy is one of the important factors in utilizing all weather available SAR satellite imagery. In this study, an error budget analysis was performed on key variables affecting on geolocation accuracy by generating KOMPSAT-5 simulation data. To perform the analysis, a Range-Doppler model was applied as a geometric model of the SAR imagery. The results show that the geolocation errors in satellite position and velocity are linearly related to the biases in the azimuth and range direction. With 0.03cm/s satellite velocity biases, the simulated errors were up to 0.054 pixels and 0.0047 pixels in the azimuth and range direction, and it implies that the geolocation accuracy is sensitive in the azimuth direction. Moreover, while the clock drift causes a geolocation error in the azimuth direction, a signal delay causes in the range direction. Monte-Carlo simulation analysis was performed to analyze the influence of multiple geometric error sources, and the simulated error was up to 3.02 pixels in the azimuth direction.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
• /
• pp.43-46
• /
• 2005

[1] There are systematical errors associated with ionospheric influence in retrieving key atmospheric parameters from radio occultation (RO) soundings. In order to obtain better-quality retrievals, we develop a new method, hereafter called National Central University Radio Occultation (NCURO) scheme, to reduce the ionospheric influence. The excess phase is divided into two parts, namely geometric excess length and path excess length (excess length along ray path due to refractivity effect). An excess phase equation is presented and implemented in the NCURO scheme Whose performance is evaluated through comparisons with model simulation and experimental data. The model simulation is based on the use of the ionospheric model 002001 and atmospheric model NRLMSISE-OO. Results show that the NCURO scheme significantly reduces the ionospheric influence at altitudes above 70 km as does the scheme presented in the literature, and provides better corrections for the atmospheric profile. INDEX TERMS: 2400 Ionosphere: Ionosphere; 6964 Radio Science: Radio wave propagation; 6969 Radio Science: Remote sensing.

• Asian-Australasian Journal of Animal Sciences
• /
• 제33권10호
• /
• pp.1633-1641
• /
• 2020

Objective: The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. Methods: Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. Results: The R² values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R² values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. Conclusion: The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.