• Journal of Korean Library and Information Science Society
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• v.45 no.3
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• pp.271-295
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• 2014

The purpose of this study is to analyze factors that influence adolescents' reading effectiveness and to structuralize the relationship between those factors. In consequence, reading attitude is the greatest factor that influences reading effectiveness, followed by library positivity and the reading role model. According to ANOVA, there is a difference in average between personality types, but PLS(Partial Least Squares) shows that personality types do not affect reading attitudes and reading effectiveness.

• Journal of Korean Society of Transportation
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• v.15 no.3
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• pp.25-37
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• 1997

접든성통제는 고속도로에 있어서 교통사고 감소의 가장 효과적인 수단들 중의 하나로 인식되어져왔다. 이러한 접근통제의 새로운 적용으로서 접근성관리는 과도한 투자 없이 일반도로상에서 교통사고를 감소시키는데 활용되고 있다. 이 연구의 목적은 도시간선도로상에 있어서 접근성관리와 교통사고와의 관계를 교통사고비용의 측면에서 분석하는 것이다. 이를 위해, 이 연구는 미국 텍사스주 대도시 지역내 중앙분리간선도로의 교통사고자료를 다중회귀모형을 이용하여 분석하였다. 이 연구는 자료분석의 결과 다음과 같은 사실을 발견할 수 있었다. 첫째, 접근성관리는 도시간선도로의 교통사고비용과 밀접한 관계를 가지고 있었다. 둘째, 이러한 접근성관리와 교통사고비용과의 관계는 도로의 교통상황과 도로변 토지이용상태에 따라 다양하게 나타났다. 셋째, 대체로 접근성관리와 관련된 요인이 교통상황 및 토지이용상태에 관련된 요인보다 더 교통사고비용과 밀접한 관계를 보였다. 마지막으로, 교통사고비용을 설명하는데 있어 가장 중용한 접근성 관리 요인은 외부접근로의 간격으로 나타났다.

• Journal of the Korea Society of Computer and Information
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• v.4 no.3
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• pp.121-129
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• 1999

The purpose of this study is to examine the effects of Critical Factors in the use of Personal Computer, Office Automation Information Technology. The author presents a therortical model related Office Automation Information Technology by end-users and suggests how this model should be conceptualized. A model was estimated with data from 98 end-users. The results revealed that degree of organizational support. demographic charateristic, and useful to the task was positively related to usage of Office Automation Information Technology.

• Journal of the Korean Home Economics Association
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• v.47 no.5
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• pp.67-77
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• 2009

This study examined risk factors and protective factors in high school students’ suicidal ideation. Participants were 2000 adolescents from the KEEP(Korean Education and Employment Panel). Data mining decision tree model revealed that: (1) Irrespective of sex, the most important predictor was father-adolescent relationship. (2) Positive mother-adolescent relationship was predicted as protective factor in condition of negative father-adolescent relationship. (3) Family activities was predicted as risk factor in condition of negative mother-adolescent relationship under the circumstances with negative father-adolescent relationship. (4) Low self-evaluation was predicted as risk factor in condition of serious agony about personality under the circumstances with positive father-adolescent relationship.

• Journal of International Area Studies (JIAS)
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• v.14 no.1
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• pp.3-30
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• 2010

The focus of this paper is the determines of asymmetric cooperation between the European Union(and EC) and the Democratic People's Republic of Korea(DPRK). By analyzing the varying degree of cooperation and conflict by the EU and the DPRK, it argues that the outcomes of the asymmetric cooperation and conflict can be fully explained by the domestic and international variables.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.26-36
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• 2021

In this study, a deep learning model for predicting the queue length was developed using the information collected from the image detector. Then, a multiple regression analysis model, a statistical technique, was derived and compared using two indices of mean absolute error(MAE) and root mean square error(RMSE). From the results of multiple regression analysis, time, day of the week, occupancy, and bus traffic were found to be statistically significant variables. Occupancy showed the most strong impact on the queue length among the variables. For the optimal deep learning model, 4 hidden layers and 6 lookback were determined, and MAE and RMSE were 6.34 and 8.99. As a result of evaluating the two models, the MAE of the multiple regression model and the deep learning model were 13.65 and 6.44, respectively, and the RMSE were 19.10 and 9.11, respectively. The deep learning model reduced the MAE by 52.8% and the RMSE by 52.3% compared to the multiple regression model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.540-548
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• 2018

The purpose of this study was to test the validity and reliability of the Satisfaction with Simulation Experience (SSE) scale for evaluating high-fidelity simulation education for nursing students. Participants were 174 nursing students, seniors enrolled in two colleges in two different regions. Collected data were analyzed using SPSS / WIN 22.0 and tested for construct validity (factor analysis, group comparison test) and reliability (internal consistency). Factor analysis revealed 17 items and 3 factors explaining 71.581% of the variance. Group comparisons showed that satisfaction with simulation training differed significantly across satisfaction to a college life and school record. Internal consistency reliability for all items was .945. For each sub-domain, the reliability coefficient was .929 for 'Debrief', .908 for 'Clinical learning and reflection', and .860 for 'Clinical reasoning'. Nursing students' mean satisfaction with simulation using the high-fidelity simulator was 3.92. Results of this study are expected to be used for evaluating the satisfaction of nursing college students receiving high-fidelity simulation education, and to serve as groundwork for the development and application of nursing simulation education.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.759-766
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• 2008

Road classification system is the first step for determining the road function and design standards. Currently, roads are classified by various indices such as road location and function. In this study, we classify road using various traffic indices as well as to identify traffic characteristics for each type of road. To accomplish the objectives, mixture model was applied for classifying road and analyzing traffic characteristics using traffic data that observed at permanent traffic count stations. A total of 8 variables were applied: annual average daily traffic(AADT), $K_{30}$ coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and coefficient of variation(COV). A total of 350 permanent traffic count points were categorized into three groups : Group I (Urban road), Group II (Rural road), and Group III (Recreational road). AADT were 30,000 for urban, 16,000 for rural, and 5,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.

• Child Health Nursing Research
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• v.19 no.1
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• pp.59-68
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• 2013

Purpose: This study was conducted to identify current health care management and barriers in health care management according to ecological systems, and to develop an ecological model for enhancing health care in child care centers. Methods: Focus group interviews were conducted with directors and teachers of child care centers, and with parents of children enrolled in child care. Data were analyzed by the latent content analysis method. Results: Twelve categories of health care management were identified. Barriers to child health care included knowledge deficit and lack of competence in health care by teachers, lack of useful health care manuals, non-existence of professional child health care personnel in child care centers, lack of mutual information sharing and disagreement on child health conditions between child care personnel and parents, lack of specific health related child care inspection criteria and time flexible child care centers with a lack of policy on collaboration with health care facilities. The ecological model developed included specific strategies to improve health care management in child care. Conclusion: The proposed ecological model to improve child health care management should be useful to plan future health care program considering both the immediate and indirect social environment surrounding children in child care.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.11-28
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• 2015

Due to the mobil-centered lifestyle following the wider use of Smartphones, Mobile services, including mobile banking and mobile shopping business have increased rapidly. Also with the emergence of "Fintech", which finance combined with technology, IT based financial market is going to be highly promising. In this trend, interests mobile credit cards are increasing. But diffusion of the mobile credit card services is still in the low level. In this situation, to identify factors that influencing satisfaction and continuous usage intention on mobile credit card, this study applied innovation diffusion theory (IDT) and post acceptance model (PAM). To conducting this research, survey data were collected, and we used SmartPLS to analyze survey data. As a result of the study, perceived easy of use, image, compatibility and facilitation positively affect user's satisfaction in mobile credit cards and that such satisfaction have a positive impact on continuous intention to use. The facilitation influences user satisfaction more strongly for those who use mobile credit cards more than plastic credit cards. Also, perceived of use and image influence user satisfaction more strongly for those who use plastic credit cards more than mobile credit cards. It is expected that this study can be a guideline for credit card service providers and policy makers to invigorate mobile credit card business. Also it worths as a early-stage research on Fintech-related studies.