• Journal of Digital Convergence
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• v.11 no.3
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• pp.371-380
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• 2013

The purpose of this study was to develop the equation of $\dot{V}O_{2max}$ by $sub_{max}imal$ PACER method for obese middle school boys. For this, $_{max}$imal test using Bruce protocol in lab was performed and then PACER $_{max}imal$ test with portable $\dot{V}O_{2max}$ equipment. To decide the level of submaximal test, during PACER with portable equipment, we found the section in which target hreat rate(over 75%$HR_{max}$) and then per section(75%,80%,85%,90%,95%) metabolic responses were recorded, with which we analyzed multiple regression by stepwise method. Model 1(at 90%$HR_{max}$): $\dot{V}O_{2max}$(ml/kg/min) = 142.721-0.275(repetition)-0.48(HR)+0.177(weight)-1.536(age)[%error 3.90ml/kg/min; performance until 2 stage(13 repetition)]. Model 2(at 95%$HR_{max}$): $\dot{V}O_{2max}$(ml/kg/min) = 182.851-0.103(repetition)-0.744(HR)+0.186(weight)-0.324(age)[%error 4.51ml/kg/min; performance until 3 stage(25 repetitions)]. estimated $\dot{V}O_{2max}$ from Model 1 was different about $3.25{\pm}6.32ml/kg/min$(%error=6.84%), otherwise model 2 was $3.16{\pm}4.54ml/kg/min$(%error=5.75%). considering %HRmax, as the submaximal test model 1 might be fit more than model 2 for obese middle school boys.

• Korean Journal of Biological Psychiatry
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• v.27 no.2
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• pp.94-100
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• 2020

Objectives Amyloid β positron emission tomography (Aβ PET) is widely used as a diagnostic tool in patients who have symptoms of cognitive impairment, however, this diagnostic examination is too expensive. Thus, predicting the positivity of Aβ PET before patients undergo the examination is essential. We aimed to analyze clinical predictors of patients who underwent Aβ PET retrospectively, and to develop a predicting model of Aβ PET positivity. Methods 468 patients who underwent Aβ PET with cognitive impairment were recruited and their clinical indicators were analyzed retrospectively. We specified the primary outcome as Aβ PET positivity, and included variables such as age, sex, body mass index, diastolic blood pressure, systolic blood pressure, education, dementia family history, Mini Mental Status Examination (MMSE), Clinical Dementia Rating (CDR), Clinical Dementia Rating-Sum of Box (CDR-SB), hypertension (HTN), diabetes mellitus (DM) and presence of apolipoprotein E (ApoE) E4 as potential predictors. We developed three final models of amyloid positivity prediction for total subjects, mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia using a multivariate stepwise logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was performed and the area under curve (AUC) value was calculated for the ROC curve. Results Aβ PET negative patients were 49.6% (n = 232), and Aβ PET positive patients were 50.4% (n = 236). In the final model of all subjects, older age, female sex, presence of ApoE E4 and lower MMSE are associated with Aβ PET positivity. The AUC value was 0.296. In the final model of MCI subjects (n = 244), older age and presence of ApoE E4 are associated with Aβ PET positivity. The AUC value was 0.725. In the final model of AD subjects (n = 173), lower MMSE scores, the presence of ApoE E4 and history of HTN are associated with Aβ PET positivity. The AUC value was 0.681. Conclusions The cerebral amyloid positivity model, which was based on commonly available clinical indicators, can be useful for prediction of amyloid PET positivity in MCI or AD patients.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.1
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• pp.24-31
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• 2007

Purpose: This study was designed to analyze effects of learning organization on organizational commitment based on the MBTI personality type. Methods: The participants were 521 nurses working in the 4 general hospitals located in Seoul, Incheon and Kyunggido. The data were collected by self-reporting questionnaires. The data were analyzed using SAS program for descriptive and Stepwise multiple regression analysis. Results: The most frequent identified personality type was ISTJ and the least identified personal types was ENFJ. It is differ to recognize the learning organization according to personality type. In an aspect of organizational commitment, the statistically significant learning organizational factors according to nurse's MBTI personality type is revealed slightly different. In other word, Shared Vision is a statistically significant factor in ISTJ, ISTP, ISFP, ESTJ and ESFJ. System Thinking is a statistically significant factor in ISFJ. Team learning is a statistically significant factor in ESTP and ISTP. Mental Model is a statistically significant factor in ISTP. Conclusion: As our results, the effects of learning organization on organizational commitment were different according to the nurse's MBTI personality type. So these results will be used to develop the more effective strategies to enhance nurse's organizational commitment using construction of learning organization.

• Journal of Gifted/Talented Education
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• v.27 no.1
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• pp.1-16
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• 2017

This study aimed to analyze the relationships between Big five personality (openness to experience, conscientiousness, extraversion, agreeableness, neuroticism), self-regulation learning, and achievement in children in a gifted education program. 95 students in a gifted education program participated in this study. A hypothetical model proposed openness to experience, conscientiousness, extraversion, agreeableness, neuroticism as independent variables, and self-regulation learning and achievement with gifted education as dependent variables. Stepwise regression analysis indicated that openness to experience, conscientiousness, and agreeableness significantly predicted self-regulation learning. Also, neuroticism, selfregulation learning, and extraversion significantly impacted achievement with gifted education. openness to experience, conscientiousness, and agreeableness showed that complete mediating effects through self-regulation learning to achievement. A foundation for improving learning strategies in a successful gifted education program can be constructed on the basis of the results of this study.

• Journal of Korean Public Health Nursing
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• v.13 no.2
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• pp.183-201
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• 1999

This descriptive correlational study was conducted to identify the variables related to health promoting lifestyle of girls in High school students. 156 high school students and 88 vocational high school students who lives in Taegu city were selected by a convenience sampling method. The data were collected by self-reported questionnaires from August 24 to September 4. 1998. Pender and others' Health Promoting Lifestyle Profile. Shere et al's. Self-Efficacy scale. Wallston et al.' s Internal Health Locus of Control scale. Wares' Health self rating scale and Cohen & Hoberman's Social support scale were used. The data were analyzed by using descriptive statistics, Pearson correlation coefficient. t-test. MANOVA. ANOVA. Tukey verification and Stepwise multiple regression with SAS progrom. The results of this study were as follows : 1. The average score of health promoting lifestyle performance was 2.34(SD=.36)points by the 4 point scale. 2. The combination of self-efficacy. internal health locus of control. mather's educational level and type of school explained $41.31\%$ of the variance of health promoting lifestyle. 3. Health promoting lifestyle showed significant positive correlations with self efficacy(r=.5173. p=.001), perceived health status(r=.254, p=.001) and internal health locus of control(r=.321. p=.001). On the basis of the above findings, self-efficacy in cognitive factors. and social support in modifying factors were identified as the variables which explained the most part of the Pender's health-promotion model. Nursing strategies enhancing self-efficacy which has the most significant effect on health promoting lifestyle should be developed. Further research is required to find out the factors influencing health pormoting lifestyle of high school students.

• Imaging Science in Dentistry
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• v.35 no.3
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• pp.167-173
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• 2005

Purpose : To investigate the relationship between three-dimensional (3D) bone imaging parameters and trabecular strength in the mandible. Materials and Methods : Bone specimens were obtained from the mandibles of five male pigs weighing around 110 kg each. Of those, 43 samples were selected for 3D analysis and measured by micro-computed tomography. The five morphometric parameters were trabecular thickness (Tb.Th), bone specific surface (BS/BV), percent bone volume (BV/TV), structure model index (SMI) and degree of anisotropy (DA). Through destructive mechanical testing, strength parameters were obtained. Results : BV/TV, SMI, BS/BV, and Tb.Th showed significant correlations with strength parameters. DA did not show any correlation with the other parameters. In multiple linear regression analysis, BV/TV alone explained $43\%$ of the variance in Young's modulus. By stepwise inclusion of SMI, the variance in the Young's modulus was better explained up to $52\%$. Conclusions : Predicting trabecular strength in the mandible through architectural analysis would be possible. Further study is needed to establish the tendency and variety of trabecular architecture and strength according to the locations within the mandible.

• The Journal of Korean Academic Society of Nursing Education
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• v.22 no.1
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• pp.72-82
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• 2016

Purpose: The purpose of this study was to identify the effects of health status and health management on activities of daily living (ADL) in older, urban-dwelling Koreans. Methods: A total of 206 subjects were recruited from one senior welfare center, six senior citizen centers, and subjects' home in two cities. Data was collected with self-reported questionnaires in order to measure health management, health status, and ADL. Data was analyzed by t-test, ANOVA, and stepwise multiple linear regression using SPSS/WIN 22.0. Results: ADL in this subject were different depending on their age, education, marital status, type of family, and average monthly living expenses. Multivariate analysis showed that age (${\beta}=-0.35$, p<.001), exercise ability (${\beta}=0.20$, p<.001), diabetes (${\beta}=-0.17$, p<.001), osteoarthritis (${\beta}=-0.15$, p<.001), caregiver (${\beta}=0.14$, p=.005), frequency of health management (${\beta}=-0.13$, p=.006), smoking (${\beta}=-0.11$, p=.019), hypertension (${\beta}=-0.10$, p=.027), and type of family (${\beta}=-0.10$, p=.036) were significantly associated with ADL. Overall, approximately 60.2% of total variability in ADL could be explained by the 11 variables in this model ($R^2=0.602$, F=32.06, p<.001). Conclusion: This study suggests that individualized health care should be continued for older, community-dwelling Koreans in order to improve their ADL. Moreover, we need to develop self-care programs and encourage them to participate in those programs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.860-877
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• 2013

Cloud computing has become one of the most important technologies for reducing cost and increasing productivity by efficiently using IT resources in various companies. The cloud computing system has mainly been built for private enterprise, but public institutions, such as governments and national institutes, also plans to introduce the system in Korea. Various researches have pointed to security problems as a critical factor to impede the vitalization of cloud computing services, but they only focus on the security threats and their correspondents for addressing the problems. There are no studies that analyze major security issues with regard to introducing the cloud computing system. Accordingly, it is necessary to research the security factors in the cloud computing given to public institutions when adopting cloud computing. This research focuses on the priority of security solutions for the stepwise adoption of cloud computing services in enterprise environments. The cloud computing security area is classified into managerial, physical and technical area in the research, and then derives the detailed factors in each security area. The research derives the influence of security priorities in each area on the importance of security issues according to the identification of workers in private enterprise and public institutions. Ordered probit models are used to analyze the influences and marginal effects of awareness for security importance in each area on the scale of security priority. The results show workers in public institutions regard the technical security as the highest importance, while physical and managerial security are considered as the critical security factors in private enterprise. In addition, the results show workers in public institutions and private enterprise have remarkable differences of awareness for cloud computing security. This research compared the difference in recognition for the security priority in three areas between workers in private enterprise, which use cloud computing services, and workers in public institutions that have never used the services. It contributes to the establishment of strategies, with respect to security, by providing guidelines to enterprise or institutions that want to introduce cloud computing systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2664-2671
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• 2012

This study aimed to investigate the relationship between physical characteristics and walking ability in the elderly population. Subjects were 77 elderly (38 men and 39 women) who are capable of walking independently with and without walking aids. Correlation and stepwise multiple linear regression analyses were used to analyze the relationship between physical characteristics (age, gender, height, weight, body mass index, muscle mass, waist/hip ratio, heart rate, vital capacity, flexibility, maximum oxygen consumption, one-leg standing time, and strength of knee flexor and extensor) and walking velocity of subjects. Age, height, vital capacity, one-leg standing time, and strength of knee flexor and extensor showed significant correlations with walking velocity of subjects (p<.05). Further, the strength of knee flexor explained 27% of the variance, and up to 32% of the walking velocity could be explained when the strength of knee extensor were added to the model. The findings suggest that walking velocity of elderly depends on the strength of lower limb's strength and a variety of physical characteristics.

• Journal of Korean Public Health Nursing
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• v.12 no.2
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• pp.89-106
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• 1998

The Health Promotion Model by Pender(l987) was used as the conceptual framework for analyzing the health promotion behaviors. The purposes of this study were to describe health promoting life style behaviors in 245 women between the ages of 35 and 59 living in Seoul and other cities and to find their predictive factors. Data were collected from 1st to 23th. June. 1998. The tool used for this study was structured questionnaire with consisted of 8 items on general characteristics. 5 items on health related characteristics. 43 items on health promoting life style. 28 items on menopausal symptoms. 5 items on family support. and 28 items on self-efficacy. The collected data were analyzed using the SAS. yielding descriptive statistics. ANOVA. Pearson's Correlation. stepwise multiple regression. The findings of this study are as follows. 1) The mean score of health promotion behavior(3.25) is not high. The mean scores of this self actualization (3.73). interpersonal support (3.68). and nutrition (3.57). regulation of stress (3.22) in domains are higher than health responsibility (2.90). exercise (2.63). 2) The results of the comparison between the health promotion behaviors and general variables showed a statistically significant difference in education (P=.0061), domestic economy status(P=.0001). perception of health status(P=.0001) but. age. state of menstruation. perception of weight is not significant difference. 3) The correlation between health promoting life style and self-efficacy(P=.0001). family support(P=.0001) is significant. But. there is no correlation between health promoting life style and age. number of family. perception of weight. 4) In the cognitive-perceptual factors. self-efficacy (P=.0001) is very significant predictor (accounted for $39.7\%$) and in the modifying factors. family support(P=.0001) is very significant (accounted for $9.0\%$). It is same to other research results.