• Journal of The Korea Institute of Healthcare Architecture
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• v.23 no.1
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• pp.7-14
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• 2017

Purpose: Since the large hospitals are one of the most intensive energy users among building types in Korea, it is important to investigate and apply appropriate energy conservation measures. There are many researches on energy conservation measures for HVAC system in hospitals, but only few useful guidelines for envelope design variables were existed. The building envelope is one of the important factors to building energy consumption and patients' comfort. The purpose of this study is to suggest the most influential envelope design variables for each end-use energy demand. Methods: 100 samples were generated by LHS(Latin Hypercube Sampling) method. After energy performance simulation, global sensitivity analysis was performed by the regression method. DesignBuilder, Simlab 2.2 and JEPlus were used in this process. Results: The most influencing variables are SHGC, SHGC and VT for heating, cooling, and lighting, respectively. However, the most influencing variable for total energy demand is WWR(Window to Wall Ratio). The analysis was conducted based on the coefficient of variance results. Implications: The six envelop design variables were ranked according to the end-use energy demand.

• The Journal of Industrial Distribution & Business
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• v.11 no.7
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• pp.29-40
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• 2020

Purpose: In modern society, many urban problems are occurring, such as aging, hollowing out old city centers and polarization within cities. In this study, we intend to apply big data and machine learning methodologies to predict depression symptoms in the elderly population early on, thus contributing to solving the problem of elderly depression. Research design, data and methodology: Machine learning techniques used random forest and analyzed the correlation between CES-D10 and other variables, which are widely used worldwide, to estimate important variables. Dependent variables were set up as two variables that distinguish normal/depression from moderate/severe depression, and a total of 106 independent variables were included, including subjective health conditions, cognitive abilities, and daily life quality surveys, as well as the objective characteristics of the elderly as well as the subjective health, health, employment, household background, income, consumption, assets, subjective expectations, and quality of life surveys. Results: Studies have shown that satisfaction with residential areas and quality of life and cognitive ability scores have important effects in classifying elderly depression, satisfaction with living quality and economic conditions, and number of outpatient care in living areas and clinics have been important variables. In addition, the results of a random forest performance evaluation, the accuracy of classification model that classify whether elderly depression or not was 86.3%, the sensitivity 79.5%, and the specificity 93.3%. And the accuracy of classification model the degree of elderly depression was 86.1%, sensitivity 93.9% and specificity 74.7%. Conclusions: In this study, the important variables of the estimated predictive model were identified using the random forest technique and the study was conducted with a focus on the predictive performance itself. Although there are limitations in research, such as the lack of clear criteria for the classification of depression levels and the failure to reflect variables other than KLoSA data, it is expected that if additional variables are secured in the future and high-performance predictive models are estimated and utilized through various machine learning techniques, it will be able to consider ways to improve the quality of life of senior citizens through early detection of depression and thus help them make public policy decisions.

• Journal of the Korean Society of School Health
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• v.7 no.1
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• pp.29-36
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• 1994

The purpose of this study was to explain the performance pattern of health education and related factors in elementary school. The data were collected from school nurses who have been working elementary school. Sample of 77 were analyzed by percent distribution, ${\chi}^2$-test, discriminant analysis. The performance rates of health education was 74%, Only 19% of total carried out health education of 6 hours per week. Important variables that was showed significant association with health education level were as follows: Perception of importance about health education among personal characteristics of school nurses and size of school c1ass, cooperation level of school administrator, operation method of school health clinic, the difficulty of school health clinic among school organization characteristics. The canonical correlation between the health education (yes or no) and important independent variables was 0.52. Among them, operation method of school health clinic. perceiveness of health education, size of school class represented the significant contribution (canonical coefficient: 0.66, 0.54, 0.52) to school health education. These findings suggest that structure and management variables of school organization are more important than personal variables of school nurses related to activation of school health education. Therefore, it is expected that the quantity and quality improvement of school health education be able to accomplish through the systematic support of school organization and government demension.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.391-398
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• 2011

After a concrete is poured, reinforced concrete structures were distressed by physical and chemical factor over time. It is in need to define important variables related to structural behavior for effectively conducting seismic analysis of structures with age-related degradation. In this study, a sensibility analysis using the first-order second moment method was performed to analyze an important variables for the reinforced concrete shear wall with age-related degradation. Because the seismic capacity of aging structures without a concrete hardening effect can be underestimated, the sensibility of analysis variables was analyzed according to the concrete hardening. Important variables for RC shear wall with age-related degradation was presented by using the tornado diagram.

• Educational Technology International
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• v.25 no.1
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• pp.27-65
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• 2024

The purpose of this study was to identify differences in learning patterns according to content complexity in video-based learning environments and to derive variables that have an important effect on learning achievement within particular learning contexts. To achieve our aims, we observed and collected data on learners' cognitive processes through perceived affordances, using behavioral logs and eye movements as specific indicators. These two types of reaction data were collected from 67 male and female university students who watched two learning videos classified according to their task complexity through the video learning player. The results showed that when the content complexity level was low, learners tended to navigate using other learners' digital logs, but when it was high, students tended to control the learning process and directly generate their own logs. In addition, using derived prediction models according to the degree of content complexity level, we identified the important variables influencing learning achievement in the low content complexity group as those related to video playback and annotation. In comparison, in the high content complexity group, the important variables were related to active navigation of the learning video. This study tried not only to apply the novel variables in the field of educational technology, but also attempt to provide qualitative observations on the learning process based on a quantitative approach.

• Korean Journal of Applied Biomechanics
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• v.32 no.1
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• pp.1-8
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• 2022

Objective: This study proposes a methodology to analyze important variables that have a significant impact on the putting direction prediction using a machine learning-based putting direction prediction model trained with IMU sensor data. Method: Putting data were collected using an IMU sensor measuring 12 variables from 6 adult males in their 20s at K University who had no golf experience. The data was preprocessed so that it could be applied to machine learning, and a model was built using five machine learning algorithms. Finally, by comparing the performance of the built models, the model with the highest performance was selected as the proposed model, and then 12 variables of the IMU sensor were applied one by one to analyze important variables affecting the learning performance. Results: As a result of comparing the performance of five machine learning algorithms (K-NN, Naive Bayes, Decision Tree, Random Forest, and Light GBM), the prediction accuracy of the Light GBM-based prediction model was higher than that of other algorithms. Using the Light GBM algorithm, which had excellent performance, an experiment was performed to rank the importance of variables that affect the direction prediction of the model. Conclusion: Among the five machine learning algorithms, the algorithm that best predicts the putting direction was the Light GBM algorithm. When the model predicted the putting direction, the variable that had the greatest influence was the left-right inclination (Roll).

• Journal of Korean Academy of Nursing
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• v.10 no.2
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• pp.73-85
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• 1980

The purpose of this study was to investigate the compliance behavior of hypertensive patients in light of their health belief model that explains an individual's compliance with health maintenance or getting well. Although there are many effective regimens and treatments for hypertension nowadays. the most important point to be taken to consideration in their behavioral aspect is their compliance with regard to the control of body weight. eating habits as to salt and cholesterol intake. stresses. activity patterns and smoking as related to their life style. The important reasons for the failure in the control of hypertensive patients are the complexity of regimens to be complied to. irregular medication and the life long restrictions in their own life style. The compliance of patients to medical regimens and rocommendations or failure to do so is an essential factor. Accordingly. the degree of the patient's compliance is an important determinant as to the success or failure of hypertension control. The subjects for this study were 187 hypertensive patients selected from admitted and out patients of the medical department at seven University Hospitals in Seoul. Data was collected from Dec. 1, 1979 to Feb. 15, 1980 using the questionaire method and was analysed by the use of means. standard deviations, coefficient of correlations, analysis of variance and multiple regression analysis. The results obtained are as follows A. Of the seven independent variables in light of health belief model. benefit. barrier and severity are closely related to patient's compliance behavior. Therefore these variables could be used as determinants to predict and modify the hypertensive behavior. 1. Benefit is the most important and significant of the variables for explaining the dependent variables. It accounts for the highest variance of patient's compliance. (23.62%) 2. Then taking the former together with barrier. the variance of compliance showed on increase. (26.59%) 3. And with the addition of severity to the first two. the variance of compliance was also increased. (28.l2 %) B. Except for susceptibility all the independent variables such as severity. benefit, knowledge. motivation and barrier are correlated to dependent variable compliance. C. Sex. marital status and religion appeared to have significant influence on the dependent variables. Therefore one could conclude that the more the patients are aware that hypertension is a threat to health. the more they understand the benefit of taking actions to prevent such a threat. and the less they perceive any barrier when taking action. the more compliant they become in following medical regimens and recommendations. Age. marital status and religion played a significant influence to their compliance. Accordingly. the selected structural variables and demographic variables which have influenced sick role behavior of the hypertensive patient must be integrated to teaching and counselling programs for better hypertension control.

• The Research Journal of the Costume Culture
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• v.11 no.4
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• pp.591-605
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• 2003

The purpose of this study was to examine the comprehensive relationships among personal characteristics, shopping orientations, and attitude which impact department store patronage behavior of apparel shopping. The data were collected via questionnaires from convenient samples of 290 female college students. Statistical analysis of factor analysis and multiple regression analysis were performed in analysing the data. The shopping orientations seemed to be the most important variable in predicting both attitude toward and patronage behavior of department store for apparel shopping. In predicting shopping orientations, material value and income found to be the important variables.

• Journal of the Korean Society of Radiology
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• v.3 no.4
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• pp.5-12
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• 2009

Arterial blood from the heart chonggyeong passed directly to the cerebral arteries and the blood circulation is important, especially in arteries that prevent blood flow there are several variables. Among the variables the average flow velocity, pulse index, and blood flow resistance and which variables, double maekbakjisuna systolic and diastolic blood flow resistance index at the maximum rate and blood pressure associated with this because they are important variables, The change of variables such as speed noehyeolryu There are observations about the non-invasive ultrasound measurements using Doppler noehyeolryu uses. Up to 20 men in the exercise of noeroganeun hyeolryuin chonggyeong arteries to increase blood flow rates can be found.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.12
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• pp.1366-1370
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• 2007

For the purpose of finding how the annoyance response to aircraft noise is affected by non-noise variables, the questionnaire survey is conducted around the Gimpo International Airport in Seoul, Korea. The non-noise variables used in this research are divided into two categories; demographic and attitudinal variables. The result of the survey suggests that aircraft noise annoyance is not affected to an important extent by other noise sources(e.g., road traffic noise and community noise etc.) and the demographic variables (sex, age, education, occupation, dwelling type and length of residence). It has been found that it is affected to an important extent by the attitudinal variables such as complaints.