• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.908-921
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• 2022

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.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.97-105
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• 2023

Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.556-576
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• 2023

This study attempted to find a way to utilize idle spaces in rural areas as a way to respond to rural extinction. Based on the keywords "startup," "youth start-up," and "youth start-up+rural," start-up+rural," the study sought to identify the perception of idle facilities in rural areas through the keywords "Idle facilities" and "closed schools." The study presented basic data for policy direction and plan search by reviewing frequency analysis, major keyword analysis, network analysis, emotional analysis, and domestic and foreign cases. As a result of the analysis, first, it was found that idle facilities and school closures are acting importantly as factors for regional regeneration. Second, in the case of youth startups in rural areas, it was found that not only education on agriculture but also problems for residence should be solved together. Third, in the case of young people, it was confirmed that it was necessary to establish digital utilization for agriculture by actively starting a business using digital. Finally, in order to attract young people and revitalize the region through best practices at home and abroad, policy measures that can serve as various platforms such as culture and education as well as startups should be presented in connection with local residents. These results are significant in that they presented implications for youth start-ups in rural areas by reviewing start-up recognition for the influx of young people as one of the alternatives for the use of idle facilities and regional regeneration, and if additional solutions are presented through field surveys, they can be used to set policy goals that fit the reality.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.239-248
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• 2023

The purpose of this study is to analyze the factors for service contracts that affect the successful bid price rate, focusing on the case of the country market. In the study, ordering organizations and bidders differentiated themselves from existing studies by analyzing service contracts that affect the successful bid price rate in a wide range of country markets. Comparative analysis of the awarding price ratio for services, this work provides a comparable result to the existing results in the previous literature. The analytical model used five independent variables such as budget, contract method, the days of the public notice, the awarding method, and the lowest awarding ratio. In the survey and analysis, big data was collected using text mining for service bids for Nara Market over the past 18 years and data was analyzed in a multi-dimensional way. The results of the analysis are as follows, (1) if budget does not determine the awarding price ratio. This is not the case in small amounts. (2) The contract method affects the awarding price ratio. (3) The days of the public notice increase, the awarding price ratio decrease. (4) the awarding method affects the awarding price ratio. (5) The lowest awarding ratio determines the awarding price ratio. Based on the results of empirical analysis, policy implications were sought.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.31-59
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• 2024

In June 2016, the term "Fourth Industrial Revolution" was first used at the World Economic Forum in Davos, Switzerland, and it gained worldwide attention. Consequently, the importance of smart ports has increased as the shipping industry has been incorporating various Fourth Industrial Revolution technologies. Currently, major countries around the world are working to achieve digital transformation in the maritime and port industry by establishing comprehensive smart ports. However, the smartification of domestic ports in South Korea is currently limited to a few areas such as Busan, Incheon, and Gwangyang, focusing on port automation. In this context, this study performed keyword analysis to identify key components of smart ports and conducted Analytic Hierarchy Process (AHP) analysis among relevant stakeholders to determine the priorities for the Introduction of smart ports in South Korea. The analysis revealed that universities prioritized automation, intelligenceization, informatization and environmentalization in that order. Research institutes prioritized informatization, intelligenceization, automation and environmentalization. Government agencies prioritized informatization, automation, intelligenceization and environmentalization, while private sector enterprises prioritized automation, intelligenceization, informatization, and environmentalization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.319-327
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• 2016

Korea faces a wide range of problems in areas such as safety, environment, and traffic due to the rapid economic development and urbanization process. Despite the local governments’ efforts to deal with electronic civil complaints and solve urban problems, civil complaints have been on the increase year by year. In this study, we collected civil complaint data over the last six years from a small and medium-sized city, Jinju-si. In order to conduct a spatial distribution pattern analysis, we indicated the location data on the area through Geocoding after classifying the reasons for civil complaints and then extracted the location data of the civil complaint occurrence spots in order to analyze the correlation between electronic civil complaints and land use. Results demonstrated that electronic civil complaints in Jinju-si were clustered in residential, central commercial, and residential-industrial mixed-use areas—areas where land development had been completed within the city center. After analyzing the civil complaints according to the land use, results revealed that complaints about illegal parking were the highest. Regarding the analysis results of facility distribution within a 50m radius from the civil complaint areas, civil complaints occurred a lot in detached housing areas located within the commercial and residential-industrial mixed-use areas. In the case of residential areas(old downtown), civil complaints were condensed in the areas with many ordinary restaurants. This research explored civil complaints in terms of the urban space and can be expected to be effectively utilized in finding solutions to the civil complaints

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.253-263
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• 2016

We analyzed the social issue 'image of the elderly' using Big Data and Social Network Analysis. First, we analyzed the words extracted by the text mining technique by inputting the keyword 'elderly'. As a result of analysis, the image of the elderly viewed through media such as cafes, blogs, etc. Representing the trend of the public was using the word 'Senior' the most. The image of the elderly is expressed using the word having the highest frequency in the top 10, "The elderly are 'Senior' people who are respected by society, they are organized to earn money, to earn their qualifications, to health, and to 'Seniors' who desire to work healthy up to 100 years old". The purpose of this study is to differentiate from the existing analysis method by analyzing the macro-level image of the elderly including the social discourse by collecting vast amount of data and analyzing it with the social networking technique. When the image of the elderly that the public perceives is positively expressed as 'Senior', it can be said that the direction of the current elderly policy is evaluated as a desirable direction. On the other hand, it was able to feel the 'desire' of the public who wanted to be evaluated. Therefore, the policy direction of the elderly to be applied in the future should be the policy that enables the elderly to be perceived as 'Necessary existence' in society by taking on social roles. In addition, we proposed to implement the policy of the elderly that reflects priorities such as job creation, welfare, and alienation that can activity and maintain health.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.5
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• pp.1-11
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• 2016

There has been an increasingly high interest in gardens and garden design in Korea recently. However, the usage of the term 'garden' is extremely varied and complex, and there has been very little academic research made on the meaning of garden. Therefore, this research attempts to investigate the ideas of current gardens and to elucidate their changing patterns by means of extensive literature research and big data analysis. The notion of garden in the past was broad including not only private space such as Madang(마당) and Teul(뜰), but also even field and grass land as public outdoor space. Yet, the meaning has become smaller to merely private space due to the change of dwelling systems due to high industrial development of the 20th century. Furthermore, the introduction of urban parks as an interactive space between nature and humans, the similar spatial function of gardens, has blurred the boundary between garden and park, which created confusion in understanding the concept of a garden. After all, garden is a subject for humans. The meanings of garden need to be recognized from various points of view since garden itself is a creation by the sum of diverse fields such as natural and social sciences as well as culturology. This discussion on the meaning of garden in the present day will give a conceptual foundation for future research on gardens and garden design. Also, the big data analysis employed here as a research method can help other similar research topics, particularly semantics in landscape architecture.

• Journal of Environmental Impact Assessment
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• v.25 no.4
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• pp.296-306
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• 2016

There is a growing interest in establishing a regional climate change adaptation policy as the climate change impact in the region and local scale increases. This study focused on the analysis of 32 regions on its characteristics of local climate change adaptation plans. First, statistic program R was used for conducting cluster analysis based on the frequency and budgets of adaptation plan. Further, we analyzed damage frequency from newspapers regarding climate change impacts in eight categories which were caused by extreme weather events on 2,565 cases for 24 years. Lastly, the characteristics of climate change adaptation plan was compared with damage frequency patterns for evaluating the adequacy of climate change adaptation plan on each cluster. Four different clusters were created by cluster analysis. Most clusters clearly have their own characteristics on certain sectors. There was a high frequency of damage in 'disaster' and 'health' sectors. Climate change adaptation plan and budget also invested a lot on those sectors. However, when comparing the relative rate among regional governments, there was a difference between types of damage and climate change adaptation plan. We assumed that the difference could come from that each region established their adaptation plans based on not only the frequency of damage, but vulnerability assessment, and expert opinions as well. The result of study could contribute to policy making of climate change adaptation plan.