• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.72-80
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• 2021

Based on the previous year's statistics, 37% of buildings in South Korea are aged over 30 years. As the number of the aging buildings increases, so does the need for maintenance. Building maintenance involves a significant number of works; the work of 'maintenance manager' accounting for the largest part. Currently, the maintenance history record is mostly in drawing or handwritten form which makes reviewing the data highly time consuming. Therefore, to improve the convenience of maintenance works and optimize historical data management, the existing maintenance process was analyzed. Problems were derived and a smart device-based automation model was established. In order to establish a smart device-based automation model, ① general flow of facility management process was analyzed and related articles were reviewed, ② current maintenance process was optimized, ③ functional block diagram of BIM Data, COBie Data, IoT, and AR-based automated maintenance management model was created, ④ a smart device-based automated maintenance management model was constructed, ⑤ finally, the above system was verified by testing the aforementioned model in the field site, evaluating the time required for the maintenance process and reviewing maintenance history data against the current one.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.413-419
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• 2022

As the development of the underground space becomes active, safety accidents related to the underground are frequently occurring in recent years. In this regard, the Ministry of Land, Infrastructure and Transport is enforcing the 『Special Act on Underground Safety Management』 (enforced on January 1, 2018, hereafter referred to as the Underground Safety Act). Among the core contents of the Underground Safety Act, underground facilities(water supply, sewage, gas, power, communication, heating) buried underground, underground structures(subway, underpass, underpass, underground parking lot, underground shopping mall, common area), ground (Drilling, wells, geology) of 15 types of underground information can be checked at a glance on a three-dimensional basis by constructing an integrated underground spatial map and using it. The purpose of this study is to develop a program that can quickly inspect the three-dimensional model after creating a three-dimensional underground structure data among the underground spatial integration maps. To this end, we first investigated and reviewed the domestic and foreign status of technology that generates and automatically inspects 3D underground structure data. A quality inspection program was developed. Through this study, it is judged that it will be meaningful as a basic research for improving the quality of underground structures on the integrated map of underground space by automating more than 98% of the 3D model inspection process, which is currently being conducted manually.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.161-173
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• 2020

In-depth interview in the field of hospitality industry services was conducted in COVID- 19. Introduction of kiosks for non-face-to-face services using untact technology, reservation, pay systems, self-service, service improvement using room service should be carried out. It is also necessary to implement Instagram, Facebook, YouTube, P-blogs, online broadcasting and live commerce through the establishment of m-channel system through untact marketing sales channels in the hospitality industry now that the product composition to solve the pro -blem of untact marketing is drawing attention due to diversification of online sales channe -ls. Now, the recognition of important elements of service education and a establishment of differentiated system of untact marketing, expansion of untact sale channel, implementation of non-face-to-face counseling service and introduction of pre-booking, telecommuting were recognized as urgent parts. In particular, a service differentiation and importance of human services, which were recognized free of charge, have re-recognized as premium, and quality service aspect of the hospitality industry in untact and the direction to diversify marketing channels are presented.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.2
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• pp.26-34
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• 2023

This study conducted interviews with former and current managers of Cheongwadae landscape architecture to provide basic information necessary to preserve, manage, and utilize Gyeongbokgung Palace's back garden, and the main conclusions summarized are as follows. First, the topography changed a lot with the construction of the main building and the official residence under President Roh Tae-woo. The water system was connected to Gyeongbokgung Palace in the past, but is now disconnected. Second, in the case of planting, the most important principles were the president's security and protocol, and accordingly, trees were placed or managed. Trees were planted by introducing excellent trees in various regions, and wildflowers and ground cover plants were frequently replaced according to the season. Third, facilities and roads were arranged for the president's protocol, hobbies, and workers' rest, and fire-fighting facilities were installed to prevent disaster in the forest area of Baegaksan Mountain. Fourth, the biggest inflection point of Gyeongbokgung Palace's back garden during Cheongwadae period was the change in topography due to the new construction of the main building and official residence during President Roh Tae-woo, the removal of A and B barbed wire fences that separated space during President Roh Moo-hyun, and the extensive landscaping carried out for the G20 Summit under President Lee Myung-bak. The area of Gyeongbokgung Palace's back garden is expected to face another inflection point due to the opening of Cheongwadae on May 10, 2022, and the work of evaluating the historical, academic, and landscape values of Gyeongbokgung Palace's back garden should be carried out while preserving the status.

• The Journal of Bigdata
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• v.6 no.2
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• pp.125-137
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• 2021

The number of CCTV installed in Korea is over 1.3 million, increasing by more than 15% annually. However, due to the limited budget compared to the installation demand, the infrastructure is composed of 500,000 pixel low-quality CCTV, and there is a limits on identification of objects in the video. Public CCTV has high utility in various fields such as crime prevention, traffic information collection (control), facility management, and fire prevention. Especially, since installed in high height, it works as its role in solving diverse crime and is in increasing trend. However, the current public CCTV field is operated with potential problems such as inability to identify due to environmental factors such as fog, snow, and rain, and the low-quality of collected images due to the installation of low-quality CCTV. Therefore, in this study, in order to remove the typical low-quality elements of public CCTV, the method of attenuating scattered light in the image caused by dust, water droplets, fog, etc and algorithm application method which uses deep-learning algorithm to improve input video into videos over quality over 4K are suggested.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.339-346
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• 2009

In this study, the flow characteristics of the sea region, where tidal current and shock waves are combined, are identified using a three-dimensional numerical model (Princeton Ocean Model, POM). The model is adopted and applied for simulating the flows of the sea region near the open sections during the seadike closure work of Sihwa Seadike which was closed in 1994. The simulation results show that the shock waves with high velocities propagate through the sections toward the inside and outside of the seadike during the periods of the spring and ebb tides, respectively. It is found that the phenomena of flow separation occur near the shock waves; as the shock waves extend to wider zones after passing the sections, their effects on the tidal current become weak. In addition, the longitudinal velocity profiles of the flows are revealed to be affected by the shock waves. For all the simulations, at the ebb tide, the drawdown of the water levels occurs in front of the open section, respectively, especially, hydraulic jump occurs when simulating the case of maximum difference in water level between the inside and outside of the seadike. As a result, it is thought that the flow characteristics of the sea region dominated by shock waves need to be identified employing three-dimensional analysis approach, which is expected to provide the information for ocean engineering works and facility management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.479-493
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• 2023

The need for safety management has arisen due to the increasing number of years of operated underground structures, such as tunnels and utility tunnels, and accidents caused by those aging infrastructures. However, in the case of privately managed underground utility ducts, there is a lack of detailed guidelines for facility safety and maintenance, resulting in inadequate safety management. Furthermore, the absence of basic design information and the limited space for safety assessments make applying currently used non-destructive testing methods challenging. Therefore, this study suggests non-destructive inspection methods using ultrasonic and impact-echo techniques to assess the quality of underground structures. Thickness, presence of rebars, depth of rebars, and the presence and depth of internal defects are assessed to provide fundamental data for the safety assessment of box-type general underground structures. To validate the proposed methodology, different conditions of concrete specimens are designed and cured to simulate actual field conditions. Applying ultrasonic and impact signals and collecting data through multi-channel accelerometers determine the thickness of the simulated specimens, the depth of embedded rebar, and the extent of defects. The predicted results are well agreed upon compared with actual measurements. The proposed methodology is expected to contribute to developing safety diagnostic methods applicable to general underground structures in practical field conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.5
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• pp.186-198
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• 2024

LiDAR is a key sensor used in autonomous vehicles, and its range of applications is expanding because it can generate 3D information and is relatively robust to various environmental factors. However, it is known that LiDAR performance is degraded to some extent due to signal attenuation and scattering by raindrops during rain, and thus the need for analysis of factors affecting rainfall in road environment detection and utilization using LiDAR has been confirmed. In this study, we analyze how signal attenuation and scattering, known as factors degrading LiDAR performance during rain, cause performance degradation based on real data. We acquire data using facilities that utilize high-luminosity retroreflective sheeting in indoor chamber where quantity of rainfall can be controlled, and quantitatively confirm the degradation of LiDAR performance during rain by interpreting it from the perspective of signal attenuation and scattering. According to the point cloud distribution and performance analysis results, LiDAR performance deteriorates due to signal attenuation and scattering caused by rain. Specifically, the quantitative performance analysis shows that LiDAR experiences a decrease in intensity primarily due to signal attenuation from rain, as well as a reduction in NPC and intensity due to signal scattering effects, along with an increase in measurement distance error.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.615-626
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• 2024

To accurately and efficiently monitor soil moisture (SM) across South Korea, this study developed a SM estimation model that integrates the cloud computing platform Google Earth Engine (GEE) and Automated Machine Learning (AutoML). Various spatial information was utilized based on Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and the global precipitation observation satellite GPM (Global Precipitation Measurement) to test optimal input data combinations. The results indicated that GPM-based accumulated dry-days, 5-day antecedent average precipitation, NDVI (Normalized Difference Vegetation Index), the sum of LST (Land Surface Temperature) acquired during nighttime and daytime, soil properties (sand and clay content, bulk density), terrain data (elevation and slope), and seasonal classification had high feature importance. After setting the objective function (Determination of coefficient, R² ; Root Mean Square Error, RMSE; Mean Absolute Percent Error, MAPE) using AutoML for the combination of the aforementioned data, a comparative evaluation of machine learning techniques was conducted. The results revealed that tree-based models exhibited high performance, with Random Forest demonstrating the best performance (R² : 0.72, RMSE: 2.70 vol%, MAPE: 0.14).