• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.53-61
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• 2022

Recent years have drawn a great attention to generation MZ and Metaverse, due to 4th industrial revolution and the development of digital environment that blurs the boundary between reality and virtual reality. Generation MZ approaches the information very differently from the existing generations and uses distinguished communication methods. In terms of learning, they have different motivations, types, skills and build relationships differently. Meanwhile, Metaverse is drawing a great attention as a teaching method that fits traits of gen MZ. Thus, the current research aimed to investigate how to increase the use of Metaverse in Educational Technology. Specifically, this research examined the antecedents of popularity of Gather Town, a platform of Metaverse. Big data of news articles have been collected and analyzed using the Bigkinds system provided by Korea Press Foundation. The analysis revealed, first, a rapid increasing trend of media exposure of Gather Town since July 2021. This suggests a greater utilization of Gather Town in the field of education after the COVID-19 pandemic. Second, Word Association Analysis and Word Cloud Analysis showed high weights on education related words such as 'remote', 'university', and 'freshman', while words like 'Metaverse', 'Metaverse platform', 'Covid19', and 'Avatar' were also emphasized. Third, Network Analysis extracted 'COVID19', 'Avatar', 'University student', 'career', 'YouTube' as keywords. The findings also suggest potential value of Gather Town as an educational tool under COVID19 pandemic. Therefore, this research will contribute to the application and utilization of Gather Town in the field of education.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.534-548
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• 2021

In this paper, the feasibility of generating solar power near an abandoned quarry is examined with the objectives of resolving the essential problems that quarries encounter, such as rockfalls and space usage issues. On an abandoned quarry site in Sadang, Seoul, Republic of Korea, two different PV installation methods were analyzed. The first is attaching PV directly on the quarry slope. Since there are no corresponding safety standards and precedents for installing solar panels directly on slopes, the power generation potential was calculated by using topographic data and reasonable assumptions. The surface area of cut slope section was extracted from the Digital Elevation Model(DEM) via ArcGIS and Python programming to calculate the tilt and power capacity of installable panels. The other approach is installing PV as a rockfall barrier, and the power generation potential was analyzed with the assumption that the panel is installed in the direction of facing solar irradiation. For the derivation of power generation, the renewable energy generation analysis program SAM(System Advisor Model) was used for both methods. According to the result, quarries that have terminated resource extraction and remain devastated have the potential to be transformed into renewable energy generation sites.

• Smart Media Journal
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• v.11 no.5
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• pp.75-81
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• 2022

In order to respond to carbon neutrality and climate change in agriculture, agricultural machinery, which has been developed centered on internal combustion engines, needs to be converted to an electric-based technology that does not emit greenhouse gases. In this study, simulations for electric UTV suspension design were performed to reduce vibration and shock of electric UTV for agricultural use and to improve driving stability and control performance of the vehicle. The simulation was performed by dividing the tolerance load of the vehicle body and the loaded load state. The range of motion of the suspension spring of UTV is within 30% of the range of motion under condition B under tolerance, the displacement of the UTV suspension with full load is reduced from 264mm to 121mm, and the damping speed is 260mm/s to 300mm/s that it can be seen that the range of motion is within 60%. Suspension design of electric UTV for multi-purpose agricultural work is a very important factor for maintaining agricultural work ability in towing work such as tillage as well as driving and terrain adaptation. The results of this study can be usefully used to determine the spring parameters with the appropriate damping range so that the electric UTV can be used for various agricultural tasks.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.728-737
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• 2022

Metaverse is gaining worldwide interest, and related industries are developing rapidly. In the field of education, students' interest in metaverse is increasing, and education on metaverse-related technologies and services is required. However, since metaverse classes in universities mainly consist of theoretical education and domestic/overseas case analysis education, practical education that can apply metaverse technology to the real world is also necessary. In the cultural field, event contents such as entrance ceremonies and exhibitions are mainly produced for metaverse contents, and it is also necessary to study metaverse contents that can be sustained for a long time by people visiting regularly. In this study, educational contents that can link cultural participation in the real world with cultural participation in the metaverse were studied using the local cultural space as a medium to produce sustainable metaverse contents. The 'Metaverse Moonshin Art Museum commemorating the 100th anniversary of Moonshin's birth' program reinterpreted the real world of Changwon Moonshin Art Museum into a virtual world by collaborating with students on the Roblox. The 'Expanded Reality Moonshin Art Museum' program created an expanded Metaverse art museum that transcends time by augmenting the deceased Moonshin artist in the museum's exhibition space using HoloLens. For students studying culture-related majors, an educational program that combines metaverse education and practical training was conducted, and it is planned to be supplemented and used as a teaching plan.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.711-721
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• 2022

Due to a long-term pandemic of COVID-19 since 2019, our society finally goes into 'un-tact (non-contact) era' in earnest by increasing an importance of non-contacted activities which are able to live without contacts among people. Un-tact era has influenced to generate a huge structural change with digitalization in our daily life as well as industrial society based on digital twin as an essential technology. As a technology representing real world in virtual digital world by integrating various technologies applied to 4^th industrial revolution, digital twin leads an innovation in industrial society with diverse industrial processes. But this technique isn't actively used across all industries due to structural limitations and environmental restrictions of digital twin. Especially, the field of construction and facility is necessary to use digital twin because it requires periodic managements of buildings in daily life and is directly connected with casualties in cases of disaster. But issues faced in reality are acting as an obstacle for applying digital twin. Therefore, this study suggests the necessity applying digital twin in facility safety response based on these issues and emphasizes active applications of digital twin by describing the expected effects being created. Furthermore, it connects to create demands of digital twin by overcoming current issues and suggesting high sustainable development.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• Membrane Journal
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• v.33 no.4
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• pp.149-157
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• 2023

Covalent organic frameworks (COFs) have shown promise in various applications, including molecular separation, dye separation, gas separation, filtration, and desalination. Integrating COFs into membranes enhances permeability, selectivity, and stability, improving separation processes. Combining COFs with single-walled carbon nanotubes (SWCNT) creates nanocomposite membranes with high permeability and stability, ideal for dye separation. Incorporating COFs into polyamide (PA) membranes improves permeability and selectivity through a synthetic interfacial strategy. Three-dimensional COF fillers in mixed-matrix membranes (MMMs) enhance CO₂/CH₄ separation, making them suitable for biogas upgrading. All-nanoporous composite (ANC) membranes, which combine COFs and metal-organic framework (MOF) membranes, overcome permeance-selectivity trade-offs, significantly improving gas permeance. Computational simulations using hypothetical COFs (hypoCOFs) demonstrate superior CO₂ selectivity and working capacity relevant for CO₂ separation and H₂ purification. COFs integrated into thin-film composite (TFC) and polysulfonamide (PSA) membranes enhance rejection performance for organic contaminants, salt contaminants, and heavy metal ions, improving separation capabilities. TpPa-SO₃H/PAN covalent organic framework membranes (COFMs) exhibited superior desalination performance compared to traditional polyamide membranes by utilizing charged groups to enable efficient desalination through electrostatic repulsion, suggesting their potential for ionic and molecular separations. These findings highlight COFs' potential in membrane technology for enhanced separation processes by improving permeability, selectivity, and stability. In this review, COF applied for the separation process is discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.93-106
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• 2010

In performing a series of in-situ thermal response tests, the effective thermal conductivities of six vertical closed-loop ground heat exchangers were experimentally evaluated and compared one another, which were constructed in a test bed in Wonju. To compare thermal efficiency of the ground heat exchangers in field, the six boreholes were constructed with different construction conditions: grouting materials (cement vs. bentonite), different additives (silica sand vs. graphite) and the shape of pipe-sections (general U-loop type vs. 3 pipe-type). From the test results, it can be concluded that cement grouting has a higher effective thermal conductivity than bentonite grouting, and the efficiency of graphite better performs than silica sand as a thermally-enhancing addictive. In addition, a new 3 pipe-type heat exchanger provides less thermal interference between the inlet and outlet pipe than the conventional U-loop type heat exchanger, which results in superior thermal performance. Based on the results from the in-situ thermal response tests, a series of economic analyses have been made to show the applicability of the new addictives and 3 pipe-type heat exchanger.