Objective: This study examined the change of informal labeling self-respect, depression/anxiety, and aggression of adolescents over time and relationship between the intercept and the growth of the variables. Method: 4-year longitudinal panel data(n=2,699), Korea Youth Panel Survey (KYPS), were analyzed to verify the influence of informal labeling on self-respect, depression/anxiety, and aggression of adolescents. Through latent growth modeling, temporal change of the variables was examined. Results: Analytic results are as follow. First, the initial status of informal labeling had a negative impact on the initial status of self-respect. The slope of informal labeling also had a negative impact on the slope of self-respect. In contrast, the initial status of informal labeling did not have an significant impact on the slope of self-respect. Second, the initial status of informal labeling had a positive impact on the initial status of aggression. The slope of informal labeling had a negative impact on the slope of aggression. In contrast, the initial status of informal labeling did not have an significant impact on the slope of aggression. Third, the initial status of informal labeling had a positive impact on the initial status of depression/anxiety and a negative impact on the slope of depression/anxiety. The slope of informal labeling had a positive impact on the slope of self-respect. Conclusions: The results suggest the importance of informal labeling on self-respect, depression/anxiety, and aggression of adolescents.
This study verified the influence of supervision on job burnout and mediating effect of self-efficacy of workers in leisure welfare centers for the elderly. A survey of 275 employees of 15 facilities of Daejeon and Chungnam area was conducted. Main analysis methods are confirmatory factor analysis and structural equation model analysis. The analysis result is that supervision influences job burnout and mediating effect of self-efficacy is proved. Considering the analysis result, some countermeasures can be proposed to alleviate the job burnout. For improving the supervision of workers, the strengthening of educational and evaluational supervision, the provision of education and training for supervisors and individualized supervision, and the inclusion of supervision in facility evaluation are necessary. To improve employees' self-efficacy, it is necessary to provide capacity-building programs and emotional support services, education and administrative support for improving ethical awareness, and self-leadership.
Kim, Wonsu;Jang, Dongmin;Park, Sung Won;Yang, MyungSeok
Journal of Information Science Theory and Practice
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v.10
no.spc
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pp.135-142
/
2022
Recently, with the development of data processing technology and the increase of computational power, methods to solving social problems using Artificial Intelligence (AI) are in the spotlight, and AI technologies are replacing and supplementing existing traditional methods in various fields. Meanwhile in Korea, heavy rain is one of the representative factors of natural disasters that cause enormous economic damage and casualties every year. Accurate prediction of heavy rainfall over the Korean peninsula is very difficult due to its geographical features, located between the Eurasian continent and the Pacific Ocean at mid-latitude, and the influence of the summer monsoon. In order to deal with such problems, the Korea Meteorological Administration operates various state-of-the-art observation equipment and a newly developed global atmospheric model system. Nevertheless, for precipitation nowcasting, the use of a separate system based on the extrapolation method is required due to the intrinsic characteristics associated with the operation of numerical weather prediction models. The predictability of existing precipitation nowcasting is reliable in the early stage of forecasting but decreases sharply as forecast lead time increases. At this point, AI technologies to deal with spatio-temporal features of data are expected to greatly contribute to overcoming the limitations of existing precipitation nowcasting systems. Thus, in this project the dataset required to develop, train, and verify deep learning-based precipitation nowcasting models has been constructed in a regularized form. The dataset not only provides various variables obtained from multiple sources, but also coincides with each other in spatio-temporal specifications.
Journal of the Korean Society of Clothing and Textiles
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v.46
no.1
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pp.182-198
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2022
Bullying at school results in a variety of psychological and social issues. Even after victims reach adulthood, these issues do not resolve and can have detrimental effects. The purpose of this study is to explore the effect of school bullying victimization on body appreciation in adulthood. Considerations include multi-mediating effects of physical attractiveness comparison and ambivalent emotions toward beauty. A research model comprised of six hypotheses was derived applying the A (adversity)-B (belief)-C (consequence) theory. A survey with 583 South Korean women in their twenties to forties was conducted to collect data. Confirmatory factor analysis, structural equation modeling, and multi-mediation analysis were applied, and all hypotheses were accepted. School bullying victimization had a negative influence on body appreciation in adulthood. Additionally, physical attractiveness comparison and ambivalent emotions toward beauty mediated this causal relationship. Also, the mediating effect of physical attractiveness comparison on the relationship between school bullying victimization and body appreciation was the greatest among the three mediating effects. This study demonstrated that bullying victimization at school continues into adulthood, which hurts body appreciation of adulthood. The findings would contribute to the development of therapy programs for school bullying victims.
Purpose - This empirical study, aims to identify the determinants of adoption and acceptance of mobile payment as to understand why it is successful in some countries in Sub-Saharan Africa but failing in others. A comparative study of a successful mobile payment service and a purported failed one was done as to have some insights to the factors affecting acceptance of the technology. Design/methodology/approach - The strength of three notable theories: theory of diffusion of innovation (DOI), the extended unified theory of user acceptance of information technology (UTAUT2) and self-efficacy theory were use. The self-efficacy of government support inclusion as, a moderating variable in the form of infrastructure, securing transaction and price value revealed the relevance of government in the success of mobile payment service. By means of a field survey of 705 subjects in two separate regions of Africa (East and West), the data was collected and use to test the research model. Findings - The study result shows the importance of the moderating factor of government support to the success of mobile payment of any nation. The result also shows the importance of the perception of relative advantage, compatibility, complexity, social influence as already revealed by other studies. Research implications or Originality - Mobile payment success in some part of Sub-Saharan Africa is well known but also suggested to fail in some Sub-Saharan African countries. Buttressing the need for understanding of the factors affecting mobile payment acceptance. This article empirically examined the factors influencing the success of mobile payment, and we implicated that if the implementation of mobile payment is to be successful for mobile commerce in any nation, adoption, acceptance and use by its citizen is imperative.
This study verified the influence of distributive justice on burnout and inspected the mediating effect of empowerment of personnel in rehabilitation facilities. We surveyed 321 personnel in facilities of Daejeon and Chungnam areas. The main methods are structural equation model analysis and confirmatory factor analysis. The important analysis result is that distributive justice influenced burnout negatively and mdiating effect of empowerment was identified. According to analysis results, some measurements were proposed to reduce personnels' burnout. For increasing distribution fairness, compensation by objective evaluation of ability and workload, establishment of transparent compensation system, improvement of working conditions of irregular workers are required. In order to improve empowerment, leadership education for managers and operation of related programs, voluntary participation of employees in programs, provision of supervision and education of empowerment are needed.
The Journal of Asian Finance, Economics and Business
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v.9
no.1
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pp.291-298
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2022
COVID-19 has spread across the world in the last two years, confining people to their homes and shutting down businesses and markets. The world is currently experiencing a catastrophic economic and social crisis. To benefit people and to protect them, industries invented new products. These products were made by small and medium-sized businesses across the globe. In South Asia, there was also a rigorous lockdown, people were laid off, and SMEs adopted E-commerce to assist clients and customers. Therefore, the study aims to analyze the impact of the COVID-19 pandemic on E-commerce adoption through open innovation strategies in South Asian countries. 500 respondents were selected through an online questionnaire to collect data from different countries of South Asia. The prominent countries are; India, Pakistan, and Bangladesh. The results of the study show that perceived compatibility and complexity have a positive influence on E-commerce adoption. In normal circumstances, however, the open innovation model is feasible. Knowledge and experience sharing and management attitude have a moderate impact on E-commerce adoption. These results are beneficial for researchers and SME managers in South Asia to overcome the challenges of the COVID-19 pandemic and increase the number of skilled people employed. This study suggests that SMEs should hire skilled workers to upgrade their systems.
This study utilized minimum number of demographic variables and first-semester GPA of students to predict the final academic status of students at a vocational college in Seoul. The results from XGBoost and LightGBM models revealed that these variables significantly impacted the prediction of students' dismissal. This suggests that early academic performance could be an important indicator of potential academic dropout. Additionally, the possibility that academic years required to award an associate degree at the vocational college could influence the final academic status was confirmed, indicating that the duration of study is a crucial factor in students' decisions to discontinue their studies. The study attempted to model without relying on psychological, social, or economic factors, focusing solely on academic achievement. This is expected to aid in the development of an early warning system for preventing academic dropout in the future.
International Journal of Internet, Broadcasting and Communication
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v.16
no.2
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pp.209-217
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2024
Recent years have seen a notable increase in fire incidents in university cafeterias, yet the social attention to these occurrences remains limited. Despite quick responses to these incidents preventing loss of life, the need for large-scale evacuation in such high foot traffic areas can cause significant disruptions, economic losses, and panic among students. The potential for stampedes and unpredictable damage during inadequate evacuations underscores the importance of fire safety and evacuation research in these settings. Previous studies have explored evacuation models in various university environments, emphasizing the influence of environmental conditions, personal characteristics, and behavioral patterns on evacuation efficiency. However, research specifically focusing on university cafeterias is scarce. This paper addresses this gap by employing Pathfinder software to analyze fire spread and evacuation safety in a university cafeteria. Pathfinder, an advanced emergency evacuation assessment system, offers realistic 3D simulations, crucial for intuitive and scientific evacuation analysis. The studied cafeteria, encompassing three floors and various functional areas, often exceeds a capacity of 1500 people, primarily students, during peak times. The study includes constructing a model of the cafeteria in Pathfinder and analyzing evacuation scenarios under different fire outbreak conditions on each floor. The paper sets standard safe evacuation criteria (ASET > RSET) and formulates three distinct evacuation scenarios, considering different fire outbreak locations and initial evacuation times on each floor. The simulation results reveal the impact of the fire's location and the evacuation preparation time on the overall evacuation process, highlighting that fires on higher floors or longer evacuation preparation times tend to reduce overall evacuation time.In conclusion, the study emphasizes a multifaceted approach to improve evacuation safety and efficiency in educational settings. Recommendations include expanding staircase widths, optimizing evacuation routes, conducting regular drills, strengthening command during evacuations, and upgrading emergency facilities. The use of information and communication technology for managing emergencies is also suggested. These measures collectively form a comprehensive framework for ensuring safety in educational institutions during fire emergencies.
The performance of recommender systems (RS) has been measured mainly in terms of accuracy. However, there are other aspects of performance that are difficult to understand in terms of accuracy, such as coverage, serendipity, and satisfaction with recommended results. Moreover, particularly with RSs that suggest multiple items at a time, such as YouTube, user satisfaction with recommended results may vary not only depending on their accuracy, but also on their configuration, content, and design displayed to the user. This is true when classifying an RS as a single RS with one recommended result and as a multiple RS with diverse results. No empirical analysis has been conducted on the influence of the content and distribution of recommendation items on user satisfaction. In this study, we propose a research model representing the content and distribution of recommended items and how they affect user satisfaction with the RS. We focus on RSs that recommend multiple items. We performed an empirical analysis involving 149 YouTube users. The results suggest that user satisfaction with recommended results is significantly affected according to the HHI (Herfindahl-Hirschman Index). In addition, satisfaction significantly increased when the recommended item on the top of the list was the same category in terms of content that users were currently watching. Particularly when the purpose of using RS is hedonic, not utilitarian, the results showed greater satisfaction when the number of views of the recommended items was evenly distributed. However, other characteristics of selected content, such as view count and playback time, had relatively less impact on satisfaction with recommended items. To the best of our knowledge, this study is the first to show that the category concentration of items impacts user satisfaction on websites recommending diverse items in different categories using a content-based filtering system, such as YouTube. In addition, our use of the HHI index, which has been extensively used in economics research, to show the distributional characteristics of recommended items, is also unique. The HHI for categories of recommended items was useful in explaining user satisfaction.
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