• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.613-621
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• 2021

This study conducted a network analysis to determine how COVID-19 vaccine-related issue spread on Twitter during the introduction stage of the COVID-19. Issue diffusion tendency is analyzed according to the time period: phase 1 (initiation of vaccine introduction: March 7 - April 3, 2021), phase 2 (stagnant period of vaccination: April 4 - April 22, 2021), and phase 3 (increase of vaccination: April 23 - May 5, 2021). NodeXL was used for data collection and analysis. Daily Twitter network data were collected by entering search terms highly related to the COVID-19 vaccine. This study found that side effects-related opinions were repeatedly formed throughout the analysis period. As the vaccination rate increased and death cases were reported on media, death-related issues also emerged on Twitter. On the other hand, vaccine safety did not receive much attention on Twitter. The results of this study highlight the role of social media as a channel of issue diffusion when a national disaster strikes. We emphasize the need for the government to monitor public opinions on social media and reflect them in crisis communication strategies.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.85-94
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• 2022

Construction industry is facing difficult challenges in terms of productivity, manpower, and industrial accidents. Currently, along with the 4th Industrial Revolution, various high-tech technologies are emerging, and efforts are being made to solve the problem by applying the technologies related to the 4th Industrial Revolution to the construction industry. As part of these efforts, research is being conducted to develop a construction equipment control system to increase productivity and safety at earthworks sites where many and various types of construction equipment are involved, and the system needs a function to increase productivity by optimizing the moving path of construction equipment. In the case of trucks, the location of the temporary road must be optimized in order to optimize the path of movement in the construction site. However, only matters related to the quality standard of temporary roads have been suggested so far, and there is no standardized process for efficiently determining the location of temporary roads. In this paper, the factors and its importance related to the location of the temporary road were identified through field surveys and interviews with experts, and a method for determining the location of the temporary road was presented. It was confirmed that the suggested method through a case study could improve the productivity of earthwork.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.407-416
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• 2018

The development of modern technology has rapidly grown the field of wearable devices. Wearable equipments should satisfy low power consumption and small/lightweight because of characteristics of body wearing. In this paper, an overview of wearable equipments is explained, and wearable device market is investigated. In addition, we investigate developed technology of wearable components, which is divided into component and communication technology. Meanwhile, a smart HSE system is required to meet the demand of the society for the serious industrial accident. To address this issue, we propose an interactive method between the wearable component and the HSE system, which are expected to be effective in safety management. As a detailed case study, a risk scenario is made with risk factors in welding workshop, and then we propose an interactive method between a wearable component and an HSE system that can reduce the risk. This proposed method is useful to achieve high level of worker's safety.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.307-322
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• 2023

Rock-mass grouting plays a crucial role in the construction of dams and deep caverns, effectively preventing seepage in the foundations, enhancing stability, and mitigating hazards. Most rock grouting is affected by hydrogeological and rock engineering indices such as rock quality designation (RQD), rock mass quality (Q-value), geological strength index (GSI), joint spacing (Js), joint aperture (Ap), lugeon value (Lu), secondary permeability index (SPI), and coefficient of permeability (K). Therefore, accurate geological analysis of basic rock properties and guidelines for grouting construction are essential for ensuring safe and effective grouting design and construction. Such analysis has been applied in dam construction sites, with a particular focus on the geological characteristics of bedrock and the development of prediction methods for grout take. In South Korea, many studies have focused on grout injection materials and construction management techniques. However, there is a notable lack of research on the analysis of hydrogeological and rock engineering information for rock masses, which are essential for the development of appropriate rock grouting plans. This paper reviews the current state of research into the correlation between the grout take with important hydrogeological and rock engineering indices. Based on these findings, future directions for the development of rock grouting research in South Korea are discussed.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.743-754
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• 2023

The global occurrence of myriad natural disasters and incidents, catalyzed by climate change and extreme meteorological conditions, has engendered substantial human and material losses. International organizations such as the International Charter have established an enduring collaborative framework for real-time coordination to provide high-resolution satellite imagery and geospatial information. These resources are instrumental in the management of large-scale disaster scenarios and the expeditious execution of recovery operations. At the national level, the operational deployment of advanced National Earth Observation Satellites, controlled by National Geographic Information Institute, has not only catalyzed the advancement of geospatial data but has also contributed to the provisioning of damage analysis data for significant domestic and international disaster events. This special edition of the National Disaster Management Research Institute delineates the contemporary landscape of major disaster incidents in the year 2023 and elucidates the strategic blueprint of the government's national disaster safety system reform. Additionally, it encapsulates the most recent research accomplishments in the domains of artificial satellite systems, information and communication technology, and spatial information utilization, which are paramount in the institution's disaster situation management and analysis efforts. Furthermore, the publication encompasses the most recent research findings relevant to data collection, processing, and analysis pertaining to disaster cause and damage extent. These findings are especially pertinent to the institute's on-site investigation initiatives and are informed by cutting-edge technologies, including drone-based mapping and LiDAR observation, as evidenced by a case study involving the 2023 landslide damage resulting from concentrated heavy rainfall.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.641-653
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• 2023

As climate change and urbanization are causing unprecedented natural disasters in urban areas, it is crucial to have urban flood predictions with high fidelity and accuracy. However, conventional physically- and deep learning-based urban flood modeling methods have limitations that require a lot of computer resources or data for high-resolution flooding analysis. In this study, we propose and implement a method for improving the spatial resolution of urban flood analysis using a deep learning based super-resolution technique. The proposed approach converts low-resolution flood maps by physically based modeling into the high-resolution using a super-resolution deep learning model trained by high-resolution modeling data. When applied to two cases of retrospective flood analysis at part of City of Portland, Oregon, U.S., the results of the 4-m resolution physical simulation were successfully converted into 1-m resolution flood maps through super-resolution. High structural similarity between the super-solution image and the high-resolution original was found. The results show promising image quality loss within an acceptable limit of 22.80 dB (PSNR) and 0.73 (SSIM). The proposed super-resolution method can provide efficient model training with a limited number of flood scenarios, significantly reducing data acquisition efforts and computational costs.

• Journal of the Korean Geotechnical Society
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• v.39 no.12
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• pp.47-60
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• 2023

At present, in South Korea, there is a growing concern regarding solar power facilities installed on slopes because they are prone to damage caused by natural disasters, such as heavy rainfall and typhoons. Each year, these solar power facilities experience soil erosion due to heavy rainfall and foundation damage or detachment caused by strong wind loads. Despite these challenges, the interaction between the ground and structures is not adequately considered. Current analyses primarily focus on the structural stability under external loads; the overall facility site's stability-excluding the solar structures-in relation to its surrounding slopes is neglected. Therefore, in this study, we use finite-difference method analysis to simulate the behavior of the foundation and piles to assess changes in lateral displacement and bending stress in piles, as well as the safety factor of sloped terrains, in response to various influencing factors, such as pile diameter, spacing between piles, pile-embedding depth, wind loads, and dry and wet conditions. The analysis results indicate that pile spacing and wind loads significantly influence lateral displacement and bending stress in piles, whereas pile-embedding depth strongly influences the safety factor of sloped terrains. Moreover, we found that under certain conditions, the design criteria in domestic standards may not be met.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.845-853
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• 2023

Recently, along with the increase in chemical accidents, the number of accidents-related disasters has been increasing continuously since 2012, and when looking at the hydrogen fluoride incident which is a representative example of domestic chemical incidents, there is insufficient technology applicable to the incident site. The result was that the damage spread. Therefore, in this paper, we will adapt the water pollution accident response system to a location-based approach, and introduce a measurement method for alternative index tracking using a GPS electronic floater of a location-based index measurement method for real-time response in the water environment when a chemical incident occurs. The research target area is Gumi City, which is the area where the hydrogen fluoride incident occurred, and Gamcheon is selected, and alternative tracking using GPS electronic floater is conducted in the corresponding target area through water quality and flow measurement. As a result, it is possible to measure water quality and flow at the same time in tracker experiments using GPS electronic floater based on the research results, it is believed that using GPS electronic floater will be of great help in disaster response systems for spill incidents in the river.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.321-332
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• 2024

Understanding the status of surface cover in riparian zones is essential for river management and flood disaster prevention. Traditional survey methods rely on expert interpretation of vegetation through vegetation mapping or indices. However, these methods are limited by their ability to accurately reflect dynamically changing river environments. Against this backdrop, this study utilized satellite imagery to apply the Random Forest method to assess the distribution of vegetation in rivers over multiple years, focusing on the Naeseong Stream as a case study. Remote sensing data from Sentinel-2 imagery were combined with ground truth data from the Naeseong Stream surface cover in 2016. The Random Forest machine learning algorithm was used to extract and train 1,000 samples per surface cover from ten predetermined sampling areas, followed by validation. A sensitivity analysis, annual surface cover analysis, and accuracy assessment were conducted to evaluate their applicability. The results showed an accuracy of 85.1% based on the validation data. Sensitivity analysis indicated the highest efficiency in 30 trees, 800 samples, and the downstream river section. Surface cover analysis accurately reflects the actual river environment. The accuracy analysis identified 14.9% boundary and internal errors, with high accuracy observed in six categories, excluding scattered and herbaceous vegetation. Although this study focused on a single river, applying the surface cover classification method to multiple rivers is necessary to obtain more accurate and comprehensive data.