• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5771-5777
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• 2013

The need of continuous management for diseases came to the fore as a chronic disease has increased, however, research related to personalized food intake analysis are insufficient. In diabetes risk analysis model of this study, food preferences are calculated by Pearson correlation coefficient that is proven method to assess the similarity, and diabetes risk is computed as a Logistic regression that was used in prevalence studies. For the Significance evaluation of this model, it was verified through t-test at 0.05 level of 52 comparison subjects and 52 control subjects. Both groups were significantly independent (p=0.046 <0.05). This model is a new way to personalized health management, through the application to healthcare system based on web and mobile.

• Journal of Hospice and Palliative Care
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• v.16 no.4
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• pp.223-231
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• 2013

Purpose: This study was conducted to explore how nurses' attitude toward dignified death and moral sensitivity affect their end-of-life care performance. Methods: Study participants were 172 nurses who work at university hospitals in a metropolitan city in Korea. Data were collected from June 20 through August 13, 2012 using the Dignified Death Scale, Moral Sensitivity Scale, and End-of-Life Care Performance Scale. Data were analyzed using the SPSS/WIN 19.0 program. Results: Factors affecting nurses' end-of-life care performance included moral sensitivity, dignified death and education level. Conclusion: Moral sensitivity, dignified death and education level should be considered when developing an educational program for nurses' end-of-life care performance.

• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.23-33
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• 2007

The collaborative filtering has used the nearest neighborhood method based on the preference and the similarity using the Pearson correlation coefficient. Therefore, it does not reflect content of the items and has the problems of the sparsity and scalability as well. the item-based collaborative filtering has been practically used to improve these defects, but it still does not reflect attributes of the item. In this paper, we propose the user and item based collaborative filtering using the classification property and Naive Bayesian to supplement the defects in the existing recommendation system. The proposed method complexity refers to the item similarity based on explicit data and the user similarity based on implicit data for handing the sparse problem. It applies to the Naive Bayesian to the result of reference. Also, it can enhance the accuracy as computation of the item similarity reflects on the correlative rank among the classification property to reflect attributes.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.429-440
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• 2015

This study was to investigate factors influencing the school adjustment according to gender and body mass index (BMI) of middle school students who participated in the 2nd-wave Korea Children and Youth Panel Study (KCYPS). This study used a crosssectional design with secondary analysis with KCYPS. The variables were parental interest, behavioral problem, aggression, attention problem, somatic symptom, social withdrawal, depression, and academic achievement. The data were analyzed with descriptive statistics, Pearson's correlation coefficients, and multiple regressions. School adjustment was significantly associated with academic achievement high, explaining 11.3~19.1% of the variance in boys. School adjustment was significantly associated with attention problem, explaining 14.9~42.4% of the variance in girls. Factors influencing school adjustment were significantly different according to gender and BMI. To improve the school adjustment, it is necessary to develop gender-specific school adjustment promotion programs according to BMI.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.9-16
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• 2007

This paper describe methodology that is distributed on 2-dimensional plane to much high-dimensional facial motion datas using Isomap algorithm, and user interface techniques to control facial expressions by selecting expressions while user navigates this space in real-time. Isomap algorithm is processed of three steps as follow; first define an adjacency expression of each expression data, and second, calculate manifold distance between each expressions and composing expression spaces. These facial spaces are created by calculating of the shortest distance(manifold distance) between two random expressions. We have taken a Floyd algorithm for it. Third, materialize multi-dimensional expression spaces using Multidimensional Scaling, and project two dimensions plane. The smallest adjacency distance to define adjacency expressions uses Pearson Correlation Coefficient. Users can control facial expressions of 3-dimensional avatar by using user interface while they navigates two dimension spaces by real-time.

• Journal of Convergence for Information Technology
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• v.10 no.11
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• pp.232-239
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• 2020

The purpose of this study was to identify the factors affecting the motivation for blood donation participation of university students. The subjects of this study were 200 university students in one area, and a self-report questionnaire was used for data collection. The data analysis used frequency, percentage, mean, standard deviation, Independent T-test, One-way ANOVA, Pearson Correlation Coefficient, and Multiple Regression Analysis. As a result of the study, the factors influencing the subjects' motivation to participate in blood donation were significant in the order of attitude toward blood donation, future blood donation plan, perceived health status, altruism, and number of blood donation experiences. The results of this study can be used as basic data for the development of educational programs to increase the motivation for blood donation participation of university students. It also suggests that there is a need to develop strategies that can increase university students' attitudes toward blood donation, altruism, and health status.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.261-270
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• 2018

The purpose of this study is to investigate the effect of work-family conflict and social support on retention intention in married female nurses. Participants were nurses working in 5 general hospitals in C city and data were collected from September 1 to 15, 2017. Data were analyzed by t-test, one-way ANOVA, Pearson's correlation, multiple regression analysis using SPSS Win 23.0. Factors influencing retention intention were identified as following; time-based conflict, more than one child, charge nurse, support of a co-workers, managers' support, with 37.3% explanatory power. This study shows that time-based conflict has negative effect on retention intention, while support of co-workers and managers have positive effect. This result may be useful in developing new strategies for enhancing retention intention. Further research is needed to identify other factors affecting the retention intention of married female nurses.

• Journal of Convergence for Information Technology
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• v.8 no.2
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• pp.11-18
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• 2018

The purpose of this study was to analyze the effects of Socio-demographic Characteristics, perceived stress and depression of college students in Daegu and Kyungbuk provinces on problem drinking behavior. The subjects of the study were 295 college students who understood and agreed on the purpose of this study and conducted questionnaires using structured questionnaires. Data were analyzed with frequency, percentage, mean, standard deviation, t-test, ANOVA, Scheffe test, pearson correlation coefficient, and multiple regression analysis. The results showed that depression was the most influential factor in the problem drinking behavior of college students in Daegu and Kyungbuk provinces, followed by gender, academic performance, and residental type. Therefore, it is necessary to develop an intervention program that takes into account the social psychological approach to prevent depression of college students and the characteristics of gender, academic performance, and residental type in order to prevent problem drinking of college students.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.137-147
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• 2015

This study proposes an algorithm for predicting breast cancer prognosis based on genetic network. We identify prognosis-specific network using gene expression data and PPI(protein-protein interaction) data. To acquire the network, we calculate Pearson's correlation coefficient(PCC) between genes in all PPI pairs using gene expression data. We develop a prediction model for breast cancer patients with estrogen-receptor-negative using the network as a classifier. We compare classification performance of our algorithm with existing algorithms on independent data and shows our algorithm is improved. In addition, we make an functionality analysis on the genes in the prognosis-specific network using GO(Gene Ontology) enrichment validation.

• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.57-66
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• 2012

Recently, with a rapidly growing of the mobile content market, a variety of mobile-based applications are being launched. But mobile devices, compared to the average computer, take a lot of effort and time to get the final contents you want to use due to the restrictions such as screen size and input methods. To solve this inconvenience, a recommender system is required, which provides customized information that users prefer by filtering and forecasting the information.In this study, an tailored multi-information recommendation system utilizing a Personalized information recommendation system on smartphone is proposed. Filtering of information is to predict and recommend the information the individual would prefer to by using the user-based collaborative filtering. At this time, the degree of similarity used for the user-based collaborative filtering process is Euclidean distance method using the Pearson's correlation coefficient as weight value.As a real applying case to evaluate the performance of the recommender system, the scenarios showing the usefulness of recommendation service for the actual restaurant is shown. Through the comparison experiment the augmented reality based multi-recommendation services to the existing single recommendation service, the usefulness of the recommendation services in this study is verified.