• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.113-123
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• 2007

Through so that accident of semiconductor industry deduces unsafe factor of the person center on unsafe behaviour that incident history and questionnaire and I made starting point that extract very important factor. It served as a momentum that make up base that analyzes factors that happen based on factor that extract factor cause classification for the first factor, the second factor and the third factor and presents model of human error. Factor for whole defines factor component for human factor and to cause analysis 1 stage in human factor and step that wish to do access of problem and it do analysis cause of data of 1 step. Also, see significant difference that analyzes interrelation between leading persons about human mistake in semiconductor industry and connect interrelation of mistake by this. Continuously, dictionary road map to human error theoretical background to basis traditional accidental cause model and modern accident cause model and leading persons. I wish to present model and new model in semiconductor industry by backbone that leading persons of existing scholars who present model of existent human error deduce relation. Finally, I wish to deduce backbone of model of pre-suppression about accident leading person of the person center.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.111-115
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• 2002

The objective of this work is to develop improved slip factor model and correction method to predict flow through impeller in forward-curved centrifugal fan by investigating the validity of various slip factor models. Both steady and unsteady three-dimensional CFD analyses were performed with a commercial code tn validate the slip factor model and the correction method. The results show that the improved slip factor model presented in this paper could provide more accurate predictions for forward-curved centrifugal impeller than the other slip factor models since the presented model takes into account the effect of blade curvature. The comparison with CFD results also shows that the improved slip factor model coupled with the present correction method provides accurate predictions for mass-averaged absolute circumferential velocity at the exit of impeller near and above the flow rate of peaktotal pressure coefficient.

• Health Policy and Management
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• v.4 no.2
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• pp.58-76
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• 1994

In order to study factors affecting the use of the ambulatory physician services. Andersen's model for health utilization was modified by adding the health behavior component and examined with three different approaches. Three different approaches were the multiople regression model, logistic regression model, and LISREL model. For multiple regression, dependent variable was reported illness-related visits to a physician during past one year and independent variables are variaous variables measuring predisposing factor, enabling factor, need factor and health behavior. For the logistic regression, dependent variable was visit or no-visit to a physician during past one year and independent variables were same as the multiple regression analysis. For the LISREL, five endogenous variables of health utiliztion, predisposing factor, enabling factor, need factor, and health behavior and 20 exogeneous variables which measures five endogenous variables were used. According to the multiple regression analysis, chronic illness, health status, perceived health status of the need factor; residence, sex, age, marital status, education of the predisposing factor ; health insurance, usual source for medical care of enabling factor were the siginificant exploratory variables for the health utilization. Out of the logistic regression analysis, health status, chronic illness, residence, marital status, education, drinking, use of health aid were found to be significant exploratory variables. From LISREL, need factor affect utilization most following by predisposing factor, enabling factor and health behavior. For LISREL model, age, education, and residence for predisposing factor; health status, chronic illess, and perceived health status for need factor; medical insurance for enabling factor; and doing any kind of health behavior for the health behavior were found as the significant observed variables for each theoretical variables.

• Research in Community and Public Health Nursing
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• v.12 no.3
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• pp.557-569
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• 2001

The purpose of the study was to test the Pender's New Health Promotion Model in order to explain and predict female workers' health promotion behavior at manufacturing plants by using latent variable structural equation model. The data were collected from 280 female workers at 8 electronic factories located at Seoul. Kyunggi. and Incheon using a structured questionnaire through interview and self-report. LISREL was used to test the model. The results are as follows: 8 out of 15 paths of the modified one from the hypothetical model of Health Promotion were statistically significant and the total variance was 40%. The relationship between the previous health behavior and the cognitive emotional factor, and the interpersonal factor. and the situational factor each. and the relationship between perceived health status and interpersonal factor, and health promotion behavior each among gamma paths were unidirectional. On the beta paths. the relationship between the interpersonal factor and the cognitive emotional factor was bi-directional: the relationships amongst the interpersonal factor and the commitment to action, and the health promotion behavior were unidirectional. But the commitment to action was not a significant mediating factor to the health promotion behavior. Pender's New Model is considered good to explain and predict the female workers' health promotion behavior. The interpersonal factor should be considered in occupational nursing practice. But the concepts of situation and commitment to action should be further validated and measured.

• Journal of Mechanical Science and Technology
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• v.18 no.2
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• pp.302-312
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• 2004

This work developed improved slip factor model and correction method to predict flow through impeller in forward-curved centrifugal fan. Both steady and unsteady three-dimensional CFD analyses were performed to validate the slip factor model and the correction method. The results show that the improved slip factor model presented in this paper could provide more accurate predictions for forward-curved centrifugal impeller than the other slip factor models since the present model takes into account the effect of blade curvature. The correction method is provided to predict mass-averaged absolute circumferential velocity at the exit of impeller by taking account of blockage effects induced by the large-scale backflow near the front plate and flow separation within blade passage. The comparison with CFD results also shows that the improved slip factor model coupled with the present correction method provides accurate predictions for mass-averaged absolute circumferential velocity at the exit of impeller near and above the flow rate of peak total pressure coefficient.

• Journal of The Korean Association For Science Education
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• v.17 no.4
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• pp.481-492
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• 1997

The purpose of this study is to construct validity of Tripartite model of "Attitudes towards Science" using Exploratory and Confirmatory Factor Analyses. Exploratory and confirmatory factor analyses are two major approaches to factor analysis. The primary goal of factor analysis is to explain the covariances or correlations between many observed variables by means of relatively few underlying latent variables. In exploratory factor analysis, the number of latent variables is not determined before the analysis, all latent variables typically influence all observed variables, the measurement errors(${\delta}$) are not allowed to correlate, and unidentification of parameters is common. Confirmatory factor analysis requires a detailed and identified initial model. Confirmatory factor analysis techniques allow relations between latent and observed variables that are not possible with traditional, exploratory factor analysis techniques. As a result of exploratory factor analysis, tripartite model of "Attitudes towards Science" being composed of affection, behavioral intention and cognition is empirically identified. But attitude of science career being composed of affection and behavioral intention is identified. In validity test using confirmatory factor analysis, measurement structure of Tripartite model of "Attitudes towards Science" is not correspondent to data set. Because it is concluded that the object of attitudes are not specific.

• Korean Parent-Child Health Journal
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• v.17 no.1
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• pp.37-45
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• 2014

Purpose: This study aimed to review measurements of environmental health behavior and assess the construct validity of Environmental Health Engagement Profile (EHEP) through confirmatory factor analysis. Methods: The literature review was performed for selection of measurements. Confirmatory factor analysis with AMOS 19.0 was used for validation of EHEP. Results: The model fitness was not appropriate in the one-factor model; $x^2=91.11$ (df=5, p<.001), Comparative Fit Index (CFI)=8.19, Non Normed Fit Index (NNFI)=6.39, and Root Mean Square Error of Approximation (RMSEA)=0.20. The model fitness was appropriate in the two-factor model; $x^2=3.19$ (df=1, p=.074), CFI=9.95, NNFI= 9.71, RMSEA=0.07. A modification of scale was found to be the most suitable for use in the investigation of environmental health behavior. Conclusion: This study confirms that a two-factor model underlies the concept of environmental health behavior. The review of measurements can help nurses and researchers to assess the environmental health behaviors.

• Journal of Industrial Convergence
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• v.2 no.2
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• pp.127-147
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• 2004

This paper examines the time-series relations among expected return, risk, and book-to-market(B/M) at the portfolio level. The time-series analysis is a natural alternative to cross-sectional regressions. An alternative feature of the time-series regressions is that they focus on changes in expected returns, not on average returns. Using the time-series analysis, we can directly test whether the three-factor model explains time-varying expected returns better than the characteristic-based model. These results should help distinguish between the risk and mispricing stories. We find that B/M is strongly associated with changes in risk, as measured by the Fama and French(1993) three-factor model. After controlling for changes in risk, B/M contains little additional information about expected returns. The evidence suggests that the three-factor model explains time-varying expected returns better than the characteristic-based model.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.32-35
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• 1996

In this paper, it is shown that the dominant errors of baro-altimeters can be characterized by bias and scale factor errors. Also an optimal filter for estimating both bias and scale factor is derived based on the concept of model transition. The optimal filter is, however, not realizable because the model transition hypotheses increase exponentially. Therefore a realizable suboptimal filter using the interacting multiple model(IMM) technique is proposed. Computer simulation results show that the estimation errors of the proposed filter are smaller than those of the conventional least squares algorithm with a forgetting factor when both the bias and the scale factor are varying.

• The Journal of Korean Academic Society of Nursing Education
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• v.8 no.1
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• pp.61-71
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• 2002

purpose : The purpose of this study was to find out the influencing factors of smoking-cessation behavior of patients with coronary heart disease and to suggest the model of smoking-cessation behavior which was based on the relationship between influencing factors and then to test its fitness empirically. method : This study was based on the Theory of Reasoned Action and a hypothetical model was constructed with fifteen paths in consideration of main predictive factors of smoking-cessation behavior such as biological factor, disease-related characteristics, self-efficacy, supportive factor, environmental factor, disease-related perception factor, intention-to-quit, and psychological factor. The validity of a smoking- cessation model was tested to 264 patients with coronary heart disease by using SPSS 8.0 and Window LISREL 8.12a. results : 1. Seven of the 15 paths of smoking-cessation behavior proved to be significant. 2. The final model excluded three paths in the hypothetical model was demonstrated to be improved by $x^2$=44.31 (df=38, p=.22), Goodness of Fit Index (GFI)=.98, Adjusted Goodness of Fit Index (AGFI)=.96, Non-Normed Fit Index(NNFI)=1.00, Normed Fit Index(NFI)=1.00, and Root Mean Square Residual(RMR)=.24. 3.The smoking-cessation behavior was influenced directly by biological factor, self-efficacy, supportive factor, environmental factor, intention-to-quit, and psychological factor. The smoking-cessation behavior was accounted for 82% of variance by these factors. conclusion : although the adolescents' smoking behavior can be predicted by only smoking intention, it is hard to predict the adults' smoking-cessation behavior by only this factor. Therefore, intention-to-quit, self-efficacy, supportive factor should be improved because these are promotive factors for smoking-cessation behavior. Biological factor, environmental factor, and psychological factor are inhibitive factors, so nicotine replacement therapy is helpful to the high nicotine-dependents, and ex-smokers avoid other smokers in their environment and also patients should learn and practice the stress coping-skills.