Purpose: As the connection between physical and non-physical structures in cities is expanding and becoming more complex, the risk of complex disaster which causes damage in a complex way is increasing. Preparing for these complex disasters, it is important to preemptively identify and manage disasters that can develop into complex disasters. Therefore, this study analyzes the disaster types studied as complex disasters by analyzing the trends of domestic and international studies related to complex disasters, and presents the direction of complex disaster management in the future. Method: We first established co-occurrence networks between disaster types based on 993 articles related to complex disasters published in disaster-related journals for the last 20 years (2002-2021). Then, through network analysis, domestic and international complex disaster research trends were compared and analyzed. Result: Research on complex disasters related to storm and flood damage, infrastructure failure and fire was high in domestic studies, and it was analyzed that research on complex disasters related to earthquakes and landslides has recently increased. However, in international studies, the proportion of studies on infrastructure failure along with storm and flood damage and earthquake was high, and various types of disasters such as tsunami and drought appeared. Conclusion: The results of this study are expected to increase the understanding of the trends in complex disaster research and provide suggestions of domestic complex disaster research in the future.
This study conducted a descriptive research to compare the degree of patient safety culture awareness among general hospitals and long-term care hospital nurses. The subjects of this study were 150 nurses who worked for more than 6 months at 2 general hospitals and 4 long-term care hospitals located in 3 cities, the data has collected from October to December 2021. To Measure patient safety culture, the patient safety culture measurement tool developed by Soon Gyo Lee was used. Data were analyzed by 𝑥2-test, ANOVA, and t-test using SPSS 20.0 program. As a result of the study, the variables with high patient safety culture were the nurse's age(F=44.17, p=.000), clinical career(F=62.86, p=.000), and current workplace career(F=26.27, p=.000). Among the subdomains of patient safety culture, leadership(t=2.07, p= .040) and patient safety priorities(t=2.18, p=.031) were found to be higher in long-term care hospital nurses than general hospital nurses. Based on this result, we expected that it can be used as data in developing programs to raise the level of patient safety culture in hospitals and long-term care hospitals.
Park Yoonkyung;Yun Sang-Lean;Yoon Younghan;Kim Reeho;Nishimura Fumitake;Sturat L. Simpson;Kim Ilho
Journal of Korean Society on Water Environment
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v.39
no.3
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pp.231-239
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2023
Public sewage treatment facilities are a necessary infrastructure for public health that treat sewage generated in cities and basin living areas and discharge it into rivers or seas. Recently, the role of public sewage treatment is receiving attention as a place of use of wastewater-based epidemiology (WBE), which analyzes human specific metabolic emissions or biomarkers present in sewage to investigate the environment to which the population is exposed in the water drain. WBE is mainly applied to investigate legal and water-law drug use or to predict and analyze the lifestyle of local residents. WBE has also been applied to predict and analyze the degree of infectious diseases that are prevalent worldwide, such as COVID-19. Since sewage flowing into public sewage treatment facilities includes living information of the population living in the drainage area, it is easy to collect basic data to predict the confirmation and spread of infectious diseases. Therefore, it is necessary to establish a new role of public sewage treatment facilities as an infrastructure necessary for WBE that can obtain information on the confirmation and spread of infectious diseases other than the traditional role of public sewage treatment. In South Korea, the sewerage supply rate is about 95.5% and the number of public sewage treatment facility is 4,209. This means that the infrastructure of sewerage is fully established. However, to successfully drive for WBE , research on monitoring and big-data analysis is needed.
Arguably many studies point out that regional innovation capabilities are accepted as a major source of growth for the sustainable regional economy. Recently, a smart specialisation strategy that should reflect regional characteristics in the policy implementation process of the regional innovation system has been proposed, but empirical studies have only presented limited results. This study attempts to overcome limitations by approaching smart specialisation as a supplementary strategy for existing regional innovation research. To this end, smart specialisation was not an alternative strategy for the regional innovation system, but rather the institutional elements of regional innovation capabilities, and the relationship between regional innovation capabilities and the local economy was analyzed to identify the impact of smart specialisation on the local economy. A study was conducted through a panel model consisting of 16 cities and provinces in Korea and 10 years from 2009-2018, and the FGLS model was finally used through the process of searching for an appropriate panel model. As a result of the study, smart specialisation consisting of industry related variety and non-related variety had a positive effect on the local economy. In addition, other regional innovation capabilities measured by dividing them into base and facilitating factors also had a positive effect on the local economy, reaffirming the results of positive research between existing regional innovation and the local economy. This study is meaningful in that smart specialisation lacking in domestic research was viewed as an institutional element of regional innovation capabilities, and it was measured through regional industry-related variety and non-related variety.
Journal of the Korean Society for Library and Information Science
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v.57
no.3
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pp.231-248
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2023
The purpose of this study is to trigger a discussion on the educational gap between regions in school library resources. To this end, differences and correlations between other resources invested in the school library and output results were analyzed according to manpower allocation. There was a positive correlation between the number of books, the budget, the number of seats, the number of borrowed materials, and the number of students. It was analyzed that manpower allocation had a negative correlation with the number of subjects in which the ratio of students, the lowest grade in the achievement evaluation, was more than 1/2. As a result of examining the staffing according to the 「School Library Promotion Act」 by regional characteristics, it was found that the allocation rate was statistically significantly higher in the order of metropolitan area, and provincial unit. Depending on the regional characteristics, there were differences in net asset per household as well as differences in school library manpower assignment rates. In contrast, the large cities with relatively affluent school library manpower assignment rates were found to be higher. Therefore, based on the survey contents of this study, it was emphasized that the manpower stipulated in the 「School Library Promotion Act」 should be deployed as soon as possible even in relatively poor areas to bridge the educational gap between regions.
A relative important analysis was conducted to determine what factors are required for port selection in Mokpo New Port and what needs to be addressed first in order to expand automobile and steel cargo handling. The port selection factors of Mokpo New Port were classified into 4 major and 13 intermediate categories, and AHP analysis was used. As a result, items such as 'port facilities', 'accessibility to international ports', 'port facility usage fees', and 'connectivity with neighboring cities/ports' were evaluated as important. The respondent groups were divided into shipowner and shipper, port operator and stevedore, and public official, and an analysis of variance (ANOVA) was conducted to verify if there was a difference in perception between the groups. As a result, shipowner and shipper, port operator and stevedore were similar, but there was a difference from public official group. Shipowner and shipper, port operator and stevedore with similar response characteristics were classified into the 'port practitioner' group, and public official were classified into the 'port policy maker' group, and the difference in perception between the group was tested. Therefore, there were differences in some major category items, and even in the intermediate category items such as 'possession of adjacent hinterland industrial complex', 'cargo equipment', '24-hour port operation', 'inland transportation cost', 'accessibility to international ports', 'marketing and incentives' with statistical. In other words, the 'port practitioner' group evaluated items that can increase cargo creation and handling productivity as important whereas the 'port policy maker' group considers port development and policies such as port infrastructure, connectivity with other ports, and incentive support items are more important.
Journal of the Korean Association of Geographic Information Studies
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v.26
no.3
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pp.65-84
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2023
In order to establish a balanced development plan at the local government level, it is necessary to understand the current urban spatial structure. In particular, since the central area is a key element of balanced development, it is necessary to accurately identify its location and size. Therefore, the purpose of this study was to identify the central area system for Busan and to derive underprivileged areas that were alienated from the service areas where the functions of the central area could be used. To identify the central area system, four indicators(De facto Population, Land Price, Commercial Buildings, Credit Card Consumption) were used to calculate the central area index, and Getis-Ord Gi* and DBSCAN analysis were performed. Next, the hierarchy of the central areas were classified and the service areas were derived through network analysis by using it. As a result of the analysis, a total of 12 central areas were found in Seomyeon, Jungang, Yeonsan, Jangsan, Haeundae, Deokcheon, Dongnae, Daeyeon, Sasang, Pusan National University, Busan Station, and Sajik. Most of the underprivileged areas affected by the central area appeared in the Eastern area of Busan and the Western area of Busan, and were derived from old industrial areas, residential areas, and some new cities. Based on the results of the study, we can find three meanings. First, we have made a new attempt to apply a machine learning methodology that has not been covered in previous studies. Second, our data show the difference between the actual data and the existing planned central areas. Third, we not only found the location of the central areas, but also identified the underprivileged areas.
Despite the growing importance of video-based social media content, such as vlogs, as a marketing tool in the travel industry, there is limited research on the characteristics that enhance engagement among potential travelers. This study explores the influence of emotional valence in YouTube travel content on viewer engagement, specifically likes and comments. We analyzed 4,619 travel-related YouTube videos from eight popular tourist cities. Using negative binomial regression analysis, we found that both positive and negative emotions significantly influence the number of likes received. Videos with higher positive emotions as well as negative emotions receive more likes. However, when it comes to the number of comments, only negative emotions showed a significant positive influence, while positive emotions had no significant impact. These findings offer valuable insights for marketers seeking to optimize engagement strategies on YouTube, considering the unique nature of travel products. Further research into the effects of specific emotions on engagement is warranted to improve marketing strategies. This study highlights the powerful impact of emotions on viewer engagement in the context of social media, particularly on YouTube.
Proceedings of the Korea Water Resources Association Conference
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2023.05a
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pp.32-32
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2023
Incidences of urban flood and extreme heat waves (due to the urban heat island effect) are expected to increase in New Zealand under future climate change (IPCC 2022; MfE 2020). Increasingly, the mitigation of such events will depend on the resilience of a range Nature-Based Solutions (NBS) used in Sustainable Urban Drainage Schemes (SUDS), or Water Sensitive Urban Design (WSUD) (Jamei and Tapper 2019; Johnson et al 2021). Understanding the impact of changing precipitation and temperature regimes due climate change is therefore critical to the long-term resilience of such urban infrastructure and design. Cuthbert et al (2022) have assessed the trade-offs between the water retention and cooling benefits of different urban greening methods (such as WSUD) relative to global location and climate. Using the Budyko water-energy balance framework (Budyko 1974), they demonstrated that the potential for water infiltration and storage (thus flood mitigation) was greater where potential evaporation is high relative to precipitation. Similarly, they found that the potential for mitigation of drought conditions was greater in cooler environments. Subsequently, Jaramillo et al. (2022) have illustrated the locations worldwide that will deviate from their current Budyko curve characteristic under climate change scenarios, as the relationship between actual evapotranspiration (AET) and potential evapotranspiration (PET) changes relative to precipitation. Using the above approach we assess the impact of future climate change on the urban water-energy balance in three contrasting New Zealand cities (Auckland, Wellington, Christchurch and Invercargill). The variation in Budyko curve characteristics is then used to describe expected changes in water storage and cooling potential in each urban area as a result of climate change. The implications of the results are then considered with respect to existing WSUD guidelines according to both the current and future climate in each location. It was concluded that calculation of Budyko curve deviation due to climate change could be calculated for any location and land-use type combination in New Zealand and could therefore be used to advance the general understanding of climate change impacts. Moreover, the approach could be used to better define the concept of urban infrastructure resilience and contribute to a better understanding of Budyko curve dynamics under climate change (questions raised by Berghuijs et al 2020)). Whilst this knowledge will assist in implementation of national climate change adaptation (MfE, 2022; UNEP, 2022) and improve climate resilience in urban areas in New Zealand, the approach could be repeated for any global location for which present and future mean precipitation and temperature conditions are known.
KIPS Transactions on Software and Data Engineering
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v.12
no.9
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pp.387-398
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2023
The COVID-19 outbreak has significantly impacted human lifestyles and patterns. It was recommended to avoid face-to-face contact and over-crowded indoor places as much as possible as COVID-19 spreads through air, as well as through droplets or aerosols. Therefore, if a person who has contacted a COVID-19 patient or was at the place where the COVID-19 patient occurred is concerned that he/she may have been infected with COVID-19, it can be fully expected that he/she will search for COVID-19 symptoms on Google. In this study, an exploratory data analysis using deep learning models(DNN & LSTM) was conducted to see if we could predict the number of confirmed COVID-19 cases by summoning Google Trends, which played a major role in surveillance and management of influenza, again and combining it with data on the number of confirmed COVID-19 cases. In particular, search term frequency data used in this study are available publicly and do not invade privacy. When the deep neural network model was applied, Seoul (9.6 million) with the largest population in South Korea and Busan (3.4 million) with the second largest population recorded lower error rates when forecasting including search term frequency data. These analysis results demonstrate that search term frequency data plays an important role in cities with a population above a certain size. We also hope that these predictions can be used as evidentiary materials to decide policies, such as the deregulation or implementation of stronger preventive measures.
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