• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.515-520
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• 2022

Metaverse is at the center of heated debates in many areas recently. Coupled with real world, metaverse is extending its domain into social and cultural activities in addition to economic value creation as untact activities increase. Global companies are investing in R&D for metaverse. The reason is that metaverse is supposed to create new value by converging virtual and real worlds thanks to technology advancement such as AI, big data, 3D graphic, 5G, cloud computing, etc. Thus, innovative changes are expected in the economic, social and cultural areas. However, there are many problems to be solved yet for connecting virtual world and real one. Also, epoch-making development of products and services should be done for realistic experience and profit creation using virtual space in various industries beyond untact social activities against pandemic situation. The essence, present condition, development and its application areas of metaverse will be analyzed, and expected problems researched so that the strategy and methodology for securing global competitiveness will be addressed in coming metaverse era.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.9
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• pp.27-35
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• 2016

Today, with the advance of Information and communication technology, 'Smart, connected' toys, which apply technologies related to IoT (Internet of Things) to traditional toys, are emerging and rapidly growing. This research aims to analyze the tendencies and limitations of smart, connected toys through exploring the representative cases of smart, connected toys based on characteristics of ICBM (Internet of Things, Cloud, Big-data, and Mobile) technology. For this study, we begin by understanding literature research about smart, connected toys and ICBM technology. Then, we extracted the characteristics of ICBM technology for connecting physical and digital environments through investigating cases to which ICBM technologies are applied. Based on the extracted characteristics, the case studies of smart, connected toys were conducted. In this research, we explore the level of ICBM technology application and limitation to smart, connected toys. We expect this research will contribute to providing guidelines for developing smart, connected toys based on the characteristics of the latest technology.

• Convergence Security Journal
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• v.22 no.2
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• pp.27-42
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• 2022

In the era of the Fourth Industrial Revolution, digital transformation to increase the effectiveness of industry is becoming more important to achieving the goal of industrial innovation. The digital new deal and smart defense are required for digital transformation and utilize artificial intelligence, big data analysis technology, and the Internet of Things. These changes can innovate the industrial fields of national defense, society, and health with new intelligent services by continuously expanding cyberspace. As a result, work productivity, efficiency, convenience, and industrial safety will be strengthened. However, the threat of cyber-attack will also continue to increase due to expansion of the new domain of digital transformation. This paper presents the risk scenarios of cyber-attack threats in the Fourth Industrial Revolution. Further, we propose a preemptive intrusion response model to bolster the complex security environment of the future, which is one of the fundamental alternatives to solving problems relating to cyber-attack. The proposed model can be used as prior research on cyber security strategy and technology development for preemptive response to cyber threats in the future society.

• Journal of Korean Society of Disaster and Security
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• v.17 no.1
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• pp.17-25
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• 2024

Recent climate change has led to an increase in the probability of forest disasters (forest fires, landslides). However, disaster systems providing information for forest disaster response lack unified information provision. Therefore, this study aims to provide essential disaster information from a unified system for swift disaster response. To achieve this goal, we conducted a fundamental study on the necessary components for designing a forest disaster platform, explored methods for visualizing platforms enabling swift response and information provision during forest disasters through case studies, and presented the findings. Our results indicate that both domestic and international forest disaster response platforms commonly utilize spatial information to provide location-specific information. Key components identified for designing a response platform for forest disasters include constructing forest disaster big data, including climate information for target areas, developing technology for integrated diagnosis of forest disasters at each stage, and designing tailored safety care services for disaster areas.

• Journal of Industrial Convergence
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• v.22 no.3
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• pp.13-25
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• 2024

This study explores research topics related to dance performances published in Korea based on big data and examines research trends that change according to the trend of the times. The results derived from topic modeling analysis are as follows. (1) Six major topics were derived: a study on marketing strategies and development plans for dance performances, (2) a study on the re-watching factors of dance performance space and performance satisfaction, (3) a study on the popularity and contribution of dance performances in the stage environment, (4) a study on the current status of dance performances and the convergence of dance group operations, (5) a study on the definition of dance performances using various social media, and (6) a study on the direction and development of technology-applied dance performance contents. Accordingly, research trends and topics related to dance, including dance performances, social changes, key keywords of researchers' change interests were extracted, and keywords were compared and analyzed to present academic changes and countermeasures. Accordingly, the need for research to apply new technologies was emphasized as it diversified and fused.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.4
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• pp.299-307
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• 2024

Fishing villages, which are the focus of this study, are interested in fishing tourism for creating a new income base and sustaining fishing communities. This is because the extraordinary nature of the fishing village space creates new values in line with the function of tourism, however, the related policies are less than adequate compared to the importance of fishing village tourism. Therefore, this study aims to analyze the interest of Korean society in fishing village tourism the manner in which this issue has changed over time. Using the news analysis system, BigKinds, we systematically collected and analyzed articles related to fishing village tourism reported in the domestic media. The results showed that social interest in fishing village tourism and government policy support had increased over time, suggesting that fishing village tourism was an important strategy that could revitalize local economies and prevent the disappearance of fishing villages.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.4
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• pp.158-166
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• 2024

In a numerical method for the study of the circulation model, various vertical coordinate systems are used to simulate the physical response of the ocean and atmosphere to the increasing greenhouse gas emission. In this study, four types of vertical coordinate systems frequently used in oceanic and atmospheric circulation numerical models, i.e., height, general, pressure, and normalized vertical coordinate systems, respectively are introduced. Finally, the hydrostatic pressure equation, vertical velocity, equation of horizontal motion, and continuity equation expressed in a vertical coordinate system were introduced, and the pros and cons of the vertical coordinate system were summarized to promote the accuracy of numerical model development.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.157-171
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• 2021

The purpose of this study is to assess the smart city for major cities in Korea. The assessment indicators are based on the STIM structure (Service, Technology, Infrastructure, and Management Layer Architecture) of the Multi-Layered Smart City Model. Assessment indicators are established through smart city concepts, case analysis, big data analysis, as well as weighted through expert AHP survey. For the assessment, seven major metropolitan cities are selected, including Seoul, and their data such as KOSIS, KISDISTAT from 2017 to 2019 is utilized for the smart city level assessment. The smart city level results show that the service, technology, infrastructure, and management levels were relatively high in Seoul and Incheon, which are metropolitan areas. Whereas, Busan, Daegu, and Ulsan, the Gyeongsang provinces are relatively moderate, while Daejeon and Gwangju, the South Chungcheong region and the Jeolla provinces, were relatively low. The overall STIM ranking shows a similar pattern, as the Seoul metropolitan area smart city level outperforms the rest of the analyzed areas with a large difference. Accordingly, balanced development strategies are needed to reduce gaps in the level of smart cities in South Korea, and respective smart city plans are needed considering the characteristics of each region. This paper will follow the literature review, assessment index establishment, weight analysis of assessment index, major cities assessment and result in analysis, and conclusion.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.90-102
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• 2022

In recent years, as interest in healing increases, outdoor spaces with the concept of healing have been created. For more professional and in-depth planning and design, the perception and characteristics of outdoor healing places through social media posts were analyzed using NER. Text mining was conducted using 88,155 blog posts, and frequency analysis and clique cohesion analysis were conducted. Six elements were derived through a literature review, and two elements were added to analyze the perception and the characteristics of healing places. As a result, visitors considered place elements, date and time, social elements, and activity elements more important than personnel, psychological elements, plants and color, and form and shape when visiting healing places. The analysis allowed the derivation of perceptions and characteristics of healing places through keywords. From the results of the Clique, keywords, such as places, date and time, and relationship, were clustered, so it was possible to know where, when, what time, and with whom people were visiting places for healing. Through the study, the perception and characteristics of healing places were derived by analyzing large-scale data written by visitors. It was confirmed that specific elements could be used in planning and marketing.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.915-936
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• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.