• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.135-154
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• 2021

This paper compares and analyzes the domestic OTT services to access their success factors, strategies and examine the domestic OTT leader's wavve's unique differentiation strategy. It is a comparative study of the top five market share services based on the operator and content's key success factors criteria, revenue structure, personalization, interactive media and cooperation. As a result, the common success factors were contents that reflected the characteristics of the operators, hybrid VOD, hybrid filtering, real-time participation interaction, alliances between the same and heterogeneous industries, and utilization of existing business areas. In addition, the study confirmed that it expanded the scope of the project and operated the contents efficiently by introducing one or more business strategies. wavve has been widely validated with its content, while B2C has long-term benefits and overseas use services, and B2B has a systematic use system, differentiating itself from other services. This paper can be the foundation for identifying the strengths and differences of each service on 2021, entering the domestic OTT industry, and establishing competitive strategies.

• Science of Emotion and Sensibility
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• v.11 no.2
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• pp.193-206
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• 2008

This paper describes to experiments on the estimation of tourist images in Busan. Preliminary tasks were performed to find out the condition of tourism souvenir and products proper to ocean city with situation in Busan. This survey analyzed by factor analysis taken in local residents, foreigners and other city. Result of factor analysis shows that the local residents and others think of Busan as similar image both. Outsider recognized Busan to tourist attractions of seaside environment and tourist facilities, and have good image of sightseeing and shopping in city. The local people remind Busan as progressive, feels sweet, activity, friendly image beside that foreign tourist remind as clean, modern, abundant, and others think as stable, changing, novelty, friendly. To abstract 8 factors among the images, take out of relevance to condition of tourist and image factors. Important factors for development of tourist industry in Busan are a feeling safe, clean, novelty in priority. And find way that enhancing image to abundant, friendly, activity were proper to tourist industry.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.44-55
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• 2002

This paper tried to analyse the factors influencing consumer trust and the relationships between cause variables and results in Internet Shopping Mall. In order to do so, this paper tried to analyse the trust factors in TV Home Shopping as well as Internet Shopping Mall in terms of cyber markets both. There found six factors ： perceived factor before purchasing, perceived factor after purchasing, perceived and emotional factors in the course of purchasing, positive and negative emotional factors after purchasing. These factors are correlated with Internet shopping variables and we can measure how Internet shopping variables can affect trust to the shopping mall. We can compare the trust factors of TV home shopping with those of Internet shopping mall and then we can activate Internet Shopping Mall. More implications of this study and further researches should be discussed in the future research.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.11a
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• pp.44-55
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• 2002

This paper tried to analyse the factors influencing consumer trust and the relationships between cause variables and results in Internet Shopping Mall. In order to do so, this paper tried to analyse the trust factors in TV Home Shopping as well as Internet Shopping Mall in terms of cyber markets both. There found six factors: perceived factor before purchasing, perceived factor after purchasing, perceived and emotional factors in the course of purchasing, posit ive and negative emotional factors after purchasing. These factors are correlated with internet shopping variables and we can measure how Internet shopping variables can affect trust to the shopping mall. We can compare the trust factors of TV home shopping with those of Internet shopping Mall. and then we can activate Internet Shopping Mall. More implications of this study and further researches should be discussed in the future research.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.269-277
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• 2021

The purpose of the study is to explore the effect of university's managing and system support in online classes on learning participation mediated by learning presence and to examine the structural relationship between the factors. In order to achieve the purpose of the study, 135 students who take online "College English 2" classes were analyzed for the fitness of the research model and the path and structural analysis through a confirmative factor of the structural equation model. As a result of the study, first, the university's managing support for online class showed a positive effect to learning presence. Second, the university's managing support for online classes completely mediated learning presence and had a positive effect on learning participation. This study can clarify the structural relationship between environmental factors which are online class support and learners' characteristics in university online class, learning presence, and learning participation and can broaden the understanding of learning participation in online classes. It gives the implications that should be considered in teaching and learning design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.423-432
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• 2021

This study developed a scale to measure college students' perceived stress levels for adverse life events that may occur in their daily lives and confirmed its validity and reliability. The scale was developed in accordance with DeVellis' scale development guidelines. Data were collected from 1,242 students of a local university in 2020. The collected samples were randomly separated into two groups (A, B). Group A (N=620) was tested for an initial examination of the performance, exploratory factor analysis, multitrait-multimethod matrix, criterion-related validity, and reliability of each item; and verified with group B (N=622) for confirmatory factor analysis and reliability re-test. As a result, the final scale of 33 items and eight factors were developed. The KMO values were 0.92, and Bartlett's spherical test was significant (χ²=12532.42, p<.001); the number of factors with initial eigenvalues of 1.0 or higher was eight; the cumulative factor loadings of 71.5% and the commonality of each item was 0.56 or higher. The reliability of the scale was Cronbach's alpha 0.94; sub-factors' Cronbach's alpha was 0.78 to 0.90. Therefore, these findings suggest that the scale developed in this study would be useful for measuring the stress levels of daily life for college students.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.11
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• pp.641-649
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• 2017

In the study, the water quality of the Imjin River basin with pollutants of changing characteristics it was determined through statistical analysis, correlation analysis, principle component and factor analysis, and cluster analysis. Among all analyzed data points, the average water quality concentration at the Sincheon 3 site shows high levels of BOD 13.4 mg/L, COD 19.9 mg/L, T-N 11.145 mg/L, T-P 0.336 mg/L, TOC 14.2 mg/L, indicating that Sincheon basin requires intersive water quality management out of the entire drainage basin. The correlational analysis of comprehensive water quality data shows statistically significant correlation between COD, TOC, BOD, T-N water quality factors, as well as finding of high correlation between organic and nutrients. The principal component analysis show that 2 main components being extracted at 81.221% from the measuring station's entire data, while seasonal data show 3 main components being extracted at 96.241%. Factor analysis of the entire data set and the seasonal data identify BOD, COD, T-N, T-P, TOC as the common factors influencing water quality. The spatial and temporal cluster analysis showed 4 groups and 3 groups, respectively, according to seasonal characteristics and land use. By analysing the water quality factors for the Imjin River basins over an 8 year period, with consideration to the spatial and temporal characteristics, this study will become the fundamental analytic data that will help understand the future changes of water quality in the Imjin River basin.

• Journal of vocational education research
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• v.37 no.5
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• pp.25-53
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• 2018

The purpose of this study is to find out the improvement plan through the satisfaction survey of the trainees involved in vocational training fraud preventive education. In order to do this, we conducted a satisfaction survey(4,263 persons) of 5,939 people who participated in the prevention education conducted by group education or e-learning in 2017. Finally we collected 4,237 effective responses data. Descriptive statistics and the regression analysis were conducted. The finding of the study were as follows. First, the education service quality(4.42), satisfaction level(4.44), understanding level(4.44) and help level(4.45) were significantly higher than those of participants in the preventive education 4 and above. Second, e-learning participants' perceived level of education service quality, satisfaction, comprehension, and help was higher in all variables than collective education's. Third, all of the sub-factors of preventive education service quality influenced satisfaction, understanding, and help in collective education and e-learning, respectively. In the collective education, the contents of education had the greatest influence, and in e-learning, the data composition had the greatest influence. Fourth, desirable education contents were cases of fraud training(70.7%), disposition regulations(47.9%), NCS course operation instructions(32.8%) and training management best practices(32.4%). Additional requirements also included the establishment of an in-depth course, the provision of anti-fraud education content for trainees, and screen switching and system stability that can be focused on e-learning. Therefore, this study suggests that first, it is necessary to activate e-learning for prevention education more, reflecting satisfaction of e-learning is higher than that of collective education. Second, it is necessary to diversify the content of preventive education and to provide it more abundantly, because it has the biggest influence in common with the satisfaction, understanding and help level of the preventive education. Third, education content next, the factors that have a relatively big influence on satisfaction are shown as delivery method and education place in the collective education. Therefore, it is necessary to prepare education place considering the assignment of instructor and convenience. Fourth, constructing data next, the factor that have a relatively great influence on understanding and help are found to be operator support, and more active operator support activities are required in e-learning. Fifth, it is required to delivery prevention activity for trainees participating in vocational training. Sixth, it is necessary to analyze the educational need to construct the contents of preventive education more systematically.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.351-361
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• 2021

The seriousness of fire is rising because fire causes enormous damage to property and human life. Therefore, this study aims to predict various risk factors affecting fire by fire type. The predictive analysis of fire factors was carried out targeting Gyeonggi-do, which has the highest number of fires in the country. For the analysis, using machine learning methods SVM (Support Vector Machine), RF (Random Forest), GBRT (Gradient Boosted Regression Tree) the accuracy of each model was presented with a high fit model through MAE (Mean Absolute Error) and RMSE (Root Mean Squared Error), and based on this, predictive analysis of fire factors in Gyeonggi-do was conducted. In addition, using machine learning methods such as SVM (Support Vector Machine), RF (Random Forest), and GBRT (Gradient Boosted Regression Tree), the accuracy of each model was presented with a high-fit model through MAE and RMSE. Predictive analysis of occurrence factors was achieved. Based on this, as a result of comparative analysis of three machine learning methods, the RF method showed a MAE = 1.765 and RMSE = 1.876, as well as the MAE and RMSE verification and test data were very similar with a difference between MAE = 0.046 and RMSE = 0.04 showing the best predictive results. The results of this study are expected to be used as useful data for fire safety management allowing decision makers to identify the sequence of dangers related to the factors affecting the occurrence of fire.

• Land and Housing Review
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• v.15 no.3
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• pp.25-43
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• 2024

Using the 2021 Korea Housing Survey Data, this study compared and analyzed the factors influencing the residential mobility of residents in public and private rental housing by population and social characteristics, economic characteristics, and housing characteristics. The analysis results are as follows. As a result of descriptive statistics analysis, it was found that private rental households were young and economically active. While the proportion of apartment residents and new housing, and the level of housing satisfaction were low, the level of housing insecurity was high. Through logistic regression analysis, significant factors influencing the residential mobility of private and public leases were analyzed. In terms of demographic and social characteristics, private leases were affected by marital status, the number of household members, the age of the household head, and the residential area, while public leases were affected by marital status and the age of the household head. In terms of economic characteristics, private leases were affected by assets, debt, and housing management costs, while public leases were affected only by debt. In terms of residential characteristics, private leases were affected by periods of homelessness, housing satisfaction, housing insecurity, and a sense of homeownership, while public leases were affected by housing type, years of construction, housing satisfaction, housing insecurity, and a sense of homeownership.