• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2828-2836
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• 2015

Evaluation items were deducted by based on literature materials to supplement the evaluation system of rock cut-slope in national road. Delphi survey of experts were conducted to review the final evaluation items. As a result of reviewing the significance through stepwise multiple linear regression, all of deducted items were statistically significant because these had lower P-value than 0.05. And It was confirmed that the items were selected appropriately as they had relatively similar levels of the weight. In consideration of CVR and reliability both suggested items and existing items, the exclusible items was selected and new items can complement existing evaluation system were added. Finally 18 rock cut-slope evaluation items was deducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.510-516
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• 2020

This study investigated the characteristics and factors affecting inpatient infants, children, and adolescents who experienced falling, using NHDIS data from 2008 through 2017, The study analyzed data of 116 patients who were under 18 and who experienced injuries (KSCD, S00-S99) by falling (KSCD, W00-W19). Frequency analysis, cross-tabulations, and multiple regression analysis were conducted, using SPSS 23. There were more boys than girls, and most of the falls occurred at the ages of over one to under six years old. Most of the children had respiratory diseases, and most had open wounds or bruises due to falling. Also, most of the falls were related to the bed. In the factor analysis, age (β=.318), the main diagnosis (β=.231), and injury (β=.169) except gender affected falling. This suggests that it is necessary to conduct fall prevention education for children, considering the developmental stage characteristics and age group. It is necessary to screen the risk group such as children with a disease with relatively less restriction of activities or with a hyperactive disorder, and to develop a related manual. Hopefully, the results will be used as the basic data for fall prevention education and creating a fall prevention manual according to the characteristics of children's developmental stage for patients who need hospitalization, their caregivers, and the relevant medical team.

• Journal of Hospice and Palliative Care
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• v.7 no.2
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• pp.179-188
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• 2004

Purpose: The purpose of this study was to investigate the degree of fatigue and its related factors in cancer patients during chemotherapy. Methods: The subjects of this study consisted of 90 patients over 20 years old who were receiving chemotherapy at the injection room of the o.p.d. and ward admission care unit in a University hospital located in Gwang-ju city and data were collected from August 8th to October 2nd, 2002. Collected data were analysed using SPSS v 10.0. to obtain summary statistics for the descriptive analysis, t-test, ANOVA, pearson correlation, and multiple regression. Results: 1. Fatigue of the subjects was significantly correlated with physical distress score. and 6 items of subscale those were nausea, vomiting, anorexia, pain, and immobility, showed statistically significant correlation. 2. Fatigue of the subjects showed statistically significant differences according to a nap satisfaction. Fatigue of the subjects was significantly correlated with mood state, Also, all 5 items of subscale, which are those were anxiety, confusion, depression, energy, and anger showed statistically significant correlations. 3. Fatigue of the subjects showed statistically significant differences according to metastasis, chemotherapy cycle, post operation existence, post radiation therapy existence. There were significant negative correlation between fatigue and hematocrit and fatigue and weight change. There was no significant correlation between fatigue and spiritual well-being state. With the result to multiple regression, Immobility, Anorexia, Anger explained fatigue by, pain, and immobility showed statistically significant correlation.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.53-66
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• 2008

This research is to the establishment of a conceptual framework that supports road characteristic classification from a new point of view in order to complement of the existing road functional classification and examine of traffic pattern. The road characteristic classification(RCC) is expected to use important performance criteria that produced a policy guidelines for transportation planning and operational management. For this study, the traffic data used the permanent traffic counters(PTCs) located within the national highway between 2002 and 2006. The research has described for a systematic review and assessment of how exploratory factor analysis should be applied from 12 explanatory variables. The optimal number of components and clusters are determined by interpretation of the factor analysis results. As a result, the scenario including all 12 explanatory variables is better than other scenarios. The four components is produced the optimal number of factors. This research made contributions to the understanding of the exploratory factor analysis for the road characteristic classification, further applying the objective input data for various analysis method, such as cluster analysis, regression analysis and discriminant analysis.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.369-377
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• 2013

The purpose of this study was to explore which factors mostly influenced players' tour results employing tour skill factors provided by LPGA. For this study, Top 10 LPGA players' stats during 9 years (2004 2012) were used. As matter of fact, 10 variables were used like average score, top 10 finish, average putt, average birdies, average eagles, driving distance, driving accuracy, greens in regulation, sand saves, putts per GIR. and prize money earning. Stepwise multiple regression was conducted using SPSS win 20.0. Results indicated that the most influential tour skill factor to 9 seasons' results was average score, second influential factor was average putt, and the third factor was driving distance, and then top 10 finish was the fourth. Also on a year on year basis, 2004 was average score, 2005 was GIR., 2006 was average eagles, 2007 was top 10 finish, 2008 was average score, 2009 was average putt, 2010 were average score, GIR. and putt per GIR, 2011 was average birdies and 2012 was putt per GIR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.236-244
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• 2016

The purpose of this study was to investigate the relationship amongst emotional labor, communication competence, resilience, and clinical nursing performance of university hospital nurses, and to identify the influencing factors on job performance of clinical nurses who work at two university hospitals. The data was collected using questionnaires from 216 nurses in February 2016. Data was analyzed using one-way ANOVA, Pearson correlation, and stepwise multiple regression using IBM SPSS 22. There were differences in communication competence (F=3.679, p=.003), resilience (F=7.909, p<.003), and nursing performance (F=2.331, p=.044) correlates with the frequency of leisure activity. The significant relationships were found among age (r=.242, p<.001), years of service (r=.278, p<.001), emotional labor (r=.211, p=.002), communication competence (r=.585, p<.001), and resilience (r=.431, p<.001) with nursing performance in university hospital nurses. The result of the stepwise multiple regression indicates that communication competence and years of service predict 40.9% (F=75.356, p<.001) in nursing performance of university hospital nurses. The most powerful predictor was communication competence (${\beta}=.581$, p<.001), followed by years of service (${\beta}=.268$, p<.001). In conclusion, to enhance nursing performance for university hospital nurses, it is necessary to develop and utilize educational programs that enhance the communication competence and to develop strategies to support leisure activities for university hospital nurses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.208-218
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• 2017

Objective: This study examined the caregiver burden, depressive symptoms, and mental-related quality of life of 226 caregivers of stroke patients, who had been hospitalized in 7 general hospitals located in Cheongju and Daejeon Metropolitan city. Methods: Data were collected from August 5, 2014 to October 5, 2014 and a structured self-administered questionnaire was used. The results were analyzed using a t-test, ANOVA for different comparisons of the mental related quality of life in the sociodemographic characteristics, care-related characteristics, health-related behavioral characteristics, caregiver burden, and depressive symptoms. Hierarchical multiple regression was conducted to determine the explanatory power of the independent variables on the dependent variables, with the variables showing significant differences in univariate analysis as independent variables. Results: According to the results of hierarchical multiple regression analysis, the relevant factors that influenced the mental-related quality of life were the relationship with a patient, burden by 'care', burden by sacrifice of 'personal life', and depressive symptoms. Conclusion: To enhance health-related quality of life, not only is a systematic complement on such factors needed, but the development and implementation of an intervention program to the caregiver burden and depressive symptoms is also urgently required.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.315-323
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• 2020

This study was conducted to narrow the view on this by analyzing the difference between dental hygienists and patients' cognition and oral health education of scaling. The study was total 202 people were finally analyzed. The method of analysis compared the cognition of scaling and oral health education, and a hierarchical regression analysis was conducted to check the effect of cognition and oral health education on dental selection by stages. As a result, there were significant differences in all but one of the nine items of cognition for scaling (p<0.01) and significant differences appeared in all but seven of the 19 categories of oral health education for scaling (p<0.01). Therefore, dental hygienists will have to seek ways to reduce these differences and continue to study how to explain them in scaling so that they can have a positive impact on patients' dental clinic choices.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of radiological science and technology
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• v.39 no.1
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• pp.59-69
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• 2016

The objective of this study was to analyze the factors influencing integrated bolus peak timing in contrast-enhanced computed tomographic angiography (CTA) and to determine a method of calculating personal peak time. The optimal time was calculated by performing multiple linear regression analysis, after finding the influence factors through correlation analysis between integrated peak time of contrast medium and personal measured value by monitoring CTA scans. The radiation exposure dose in CTA was $716.53mGy{\cdot}cm$ and the radiation exposure dose in monitoring scan was 15.52 mGy (2 - 34 mGy). The results were statistically significant (p < .01). Regression analysis revealed, a -0.160 times decrease with a one-step increase in heart rate in male, and -0.004, -0.174, and 0.006 times decrease with one-step in DBP, heart rate, and blood sugar, respectively, in female. In a consistency test of peak time by calculating measured peak time and peak time by using the regression equation, the consistency was determined to be very high for male and female. This study could prevent unnecessary dose exposure by encouraging in clinic calculation of personal integrated peak time of contrast medium prior to examination.