• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.306-313
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• 2011

The damage tolerance analysis is required to guarantee the structural safety and the reliability for aircraft components. The damage tolerance method, which evaluate the life considering the initial crack, considers a fatigue design model of the aircraft main structure. The fatigue crack growth life should be calculated in damage tolerance analysis and the inspection time to define the replacement cycle. In this paper, the damage tolerance analysis is performed for a turbine wheel which has complex geometry. The equation of the stress intensity factor for complex geometry is hard to know, so that they are usually processed by finite element analysis which takes long time. To solve this problem, the stress intensity factors at specified crack are obtained by the FEA and the crack growth life is evaluated using the surrogate model which is generated by the regression analysis of the FEA data. From the results, the efficiency of the crack growth life calculation and the damage tolerance analysis could be increased by taking the surrogate model.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.35-46
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• 2008

The purposes of this study are to analyze the characteristics and to develop the models of traffic accidents. In pursuing the above, this study gives particular attentions to developing the models(multiple linear, poisson and negative binomial regression) using the data of Cheongju and Cheongwon signalized intersections. The main results analyzed are as follows. First, the accident characteristics of rural area were defined by factor. Second, 4 accident models which are all statistically significant were developed. Finally, such the variables as $X_2$ and $X_{11}$ were evaluated to be specific variables which reflect the characteristics of rural area.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.11
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• pp.831-836
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• 2010

In this paper, Plasma Enhanced Chemical Vapor Deposition (PECVD) $SiO_2$ film properties are modeled using statistical analysis and neural networks. For systemic analysis, Box-Behnken's 3 factor design of experiments (DOE) with response surface method are used. For characterization, deposited film thickness and film stress are considered as film properties and three process input factors including plasma RF power, flow rate of $N_2O$ gas, and flow rate of 5% $SiH_4$ gas contained at $N_2$ gas are considered for modeling. For film thickness characterization, regression based model showed only 0.71% of root mean squared (RMS) error. Also, for film stress model case, both regression model and neural prediction model showed acceptable RMS error. For sensitivity analysis, compare to conventional fixed mid point based analysis, proposed sensitivity analysis for entire range of interest support more process information to optimize process recipes to satisfy specific film characteristic requirements.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.125-130
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• 2017

In this study, the influence of various factors on surface roughness was investigated using the Taguchi experimental method through high-speed machining processing. Feed rate, pitch, tool diameter, and depth of cut are widely applied to high-speed machining conditions for mold production. Each of these factors was implemented and classified into three levels; then, after high speed machining, surface roughness was measured, the S/N ratio was analyzed, and the influence on the surface roughness of control factors was analyzed quantitatively by ANOVA. Using this information, a mathematical model for predicting surface roughness was derived from multiple regression analysis. This mathematical model enables the surface roughness value after high-speed machining to be predicted at the production stage, before machining, for a wide range of machining conditions.

• YAKHAK HOEJI
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• v.47 no.3
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• pp.148-153
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• 2003

Skin moisture is an important factor in skin health. Measurement of moisture content can provide diagnostic information on the condition of skin. In this study, a portable near-infrared (NIR) system was newly integrated with a photo diode array detector that has no moving parts, and this system has been successfully applied for the evaluation of human skin moisture. Diffuse reflectance spectra were collected and transformed to absorbance using 1 nm step size over the wavelength range of 1100 nm to 2200 nm. Partial least squares regression (PLSR) was applied to develop a calibration model. For practical use for the evaluation of human skin moisture, the PLS model for human skin moisture was developed in vivo using the portable NIR system on the basis of the relative water content values of stratum corneum from the conventional capacitance method. The PLS model showed a good correlation. The calibration with the use of PLS model predicted human moisture with a standard error of prediction (SEP) of 3.5 at 1120∼1730 nm range. This study showed the possibility of skin moisture measurement using portable NIR system.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.84-92
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• 2021

Care services are a significant asset in human life. Care in its overall nature focuses on human needs and covers several aspects such as health care, homes, personal care, and education. In fact, care deals with many dimensions: physical, psychological, and social interconnections. Very little information is available on estimating the cost of care services that provided to orphans and abandoned children. Prediction of the cost of the care system delivered by governmental or non-governmental organizations to support orphans and abandoned children is increasingly needed. The purpose of this study is to analyze the care cost for orphanage organizations in Saudi Arabia to forecast the cost as well as explore the most influence factor on the cost. By using business analytic process that applied statistical and machine learning techniques, we proposed a model includes simple linear regression, Naive Bayes classifier, and Random Forest algorithms. The finding of our predictive model shows that Naive Bayes has addressed the highest accuracy equals to 87% in predicting the total care cost. Our model offers predictive approach in the perspective of business analytics.

• Health Policy and Management
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• v.17 no.2
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• pp.68-90
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• 2007

Nurse staffing level is an important factor that influences the quality of health service and patient outcomes. This study was carried out to examine the current state of acute hospital nurse staffing and find out factors that affect the nurse staffing level. Nurse staffing of individual hospitals was measured using the number of registered nurses per 100 beds. Descriptive and multiple regression analyses were conducted using 592 acute care hospitals' data. Regression model included structure factors such as referral level, ownership, medical and general staffing, and financial outcome factors such as occupancy rate, inpatient and outpatient revenues. Market characteristics included strength of competition, supply of nurses, and income and health status level of consumers. The average number of nurses per 100 beds was 28 and showed a great variation according to the referral level. Regression model explained this variation as much as 76.87%. Hospital structure variables which affecting the hospital nurse staffing level positively were ICU bed ratio, the staffing level of specialist, training doctor and employees except doctor and nursing personnel, while the negative factor was nurse aid staffing level. General hospitals employed more nurses than hospitals. Among outcome characteristics, occupancy rate and the amount of health insurance inpatient revenue affected positively on the hospital nurse staffing level. The more supply of the new nurse and the higher consumer income and health status in the medical service markets, the more nurses were employed by the medical institutes. According to the study result, hospitals employed more nurses when they had more financial incentive by increasing nurses. This means appropriate hospital incentive policy and regulation policy, which hospital violate nurse staffing level have to pay penality, should be needed. Clarifying job description between nurses and nurse aids and the reentry program for unemployed experienced nurses will be helpful to increase nurse staffing level.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.48-60
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• 1995

A flood - flow forecasting system model of river basins has been developed in this study. The system model consists of the data management system(the observation and telemetering system, the rainfall forecasting and data-bank system), the flood runoff simulation system, the reservoir operation simulation system, the flood forecasting simulation system, the flood warning system and the user's menu system. The Multivariate Rainfall Forecasting model, Meteorological factor regression model and Zone expected rainfall model for rainfall forecasting and the Streamflow synthesis and reservoir regulation(SSARR) model for flood runoff simulation have been adopted for the development of a new system model for flood - flow forecasting. These models are calibrated to determine the optimal parameters on the basis of observed rainfall, 7 streamfiow and other hydrological data during the past flood periods.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.115-125
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• 2015

This study is to analyze the preference of experiential activities and behavioral intention on rural tourism, with special focus on parents group of elementary students. The result can be utilized as basic data for demanding aspect of rural experiencing tourism. Two-step questionnaire survey was conducted, during May to July, 2915. Sample group was selected at 4 elementary school in Daegu city. 347 valid responses were analyzed with SPSS. Major results are as follows. Firstly, suggested model for 23 experiential activities in 7 types, were verified as valid by verifying factor analysis. Factor 1 was verified and named as 'Rual Life Experience', Factor 2 was verified and named as 'Health/Healing Experience', Factor 3, as 'Agricultural Product Experience', Factor 4, as 'Eco-Cultural Experience', Factor 5, as 'Leisure/Sports Experience', Factor 6, as 'Traditional Wellbeing Food Experience', and Factor 7, as 'Traditional Culture Experience'. All 7 factors explained 75.39% of total variance. Secondly, mean score of preference by each activity showed high in 'Health-care experience', 'Traditional food experience' and comparatively low in 'Collecting experience', 'Agricultural experience'. Thirdly, all 7 types(factors) of experience showed significant affecting relation to satisfaction, intention to participation and recommendation. Specially, 'Eco-Cultural Experience' and 'Rural Life Experience' showed high affecting relation. This could be the characteristics of parents group of elementary students.

• Journal of Korean society of Dental Hygiene
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• v.16 no.6
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• pp.931-941
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• 2016

Objectives: The purpose of this study was to examine the association between depression and poor oral health in Korean elderly using Korean version of the Patient Health Questionnaire-9 (PHQ-9) for assessment of depressive symptoms. Methods: This study used the data from Korean National Health and Nutrition Examination Survey (KNHANES VI-2). The study included 1,454 elderly Korean aged over 65. Variables included demographic characteristics (gender, age), socioeconomic factor (income, education), systemic diseases, oral health related factor (tooth brush, dental products), health related factor (alcohol drinking, smoking), and depression. Logistic regression analysis was used as sequential models. Effects were quantified as odds ratios (OR) and 95% confidence intervals (CI). Results: From frequency analysis, being female, primary school or less, non-alcohol drinking, poor oral health were significantly related to depression. In the multiple logistic regression model, depression was significantly associated with poor oral health (OR=1.96, CI=1.15-3.53) after adjustment for other covariates including demographic characteristics, socioeconomic factor, systemic diseases, oral health related factor, and health related factor (OR=1.91, CI=1.13-3.27). Conclusions: Depression had an influence on the poor oral health after adjustment as confounding variable in the elderly. It should be focused on the health promotion for the elderly vulnerable to depression and poor oral health. The development of the mental health and oral health should be established.