Korean Journal of Agricultural and Forest Meteorology
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v.23
no.4
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pp.268-279
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2021
The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.
An, Phil-Gyun;Eom, Seong-Jun;Kim, Yong-Gyun;Cho, Han-Sol;Kim, Sang-Bum
Journal of Korean Society of Rural Planning
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v.27
no.4
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pp.55-70
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2021
In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.22
no.5
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pp.7-15
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2022
Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.
Kil, Sue Yeon;Shin, Hae Min;Choi, Joo Hyun;Kim, Yoo Sun
Journal of the Korean Society of Floral Art and Design
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no.45
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pp.31-46
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2021
With the advent of the post-COVID19 era, people must maintain social distancing to quarantine. However, this rule deprives people of freedom. Therefore, this study proposes a new normal plan for urban park design using drive-thru to recreate space for people to maintain and enjoy their previous lives while complying with quarantine rules. Olympic Park has a large floating population, and is one of the places where drive-thru is available. Therefore, the study designed this place to be the only cafe that could be operated if other cafes were shut down due to social distancing. The cafes in the park were designed into five spaces based on Olympic Park's flag motifs. The results were as follows. The cafe's name is CUPPY (Cup+Coffee), while each logo letter is expressed using the colors of the Olympic flag: blue, yellow, black, green, and red. The cafe spaces were divided into five continents (Europe, Asia, Africa, Oceania, and America), as symbolized by the Olympic flag, with the driving route shaped like the Olympic logo to match the five spaces. Human beings need change and adaptation in various fields to live in a post-COVID19 era that they have never experienced before. Just as the New Normal changes with time, and should, research is essential for presenting a New Normal in urban park design that reflects this disaster situation following the COVID-19 crisis. On this very point, we expect that this research will serve as a reference for urban park design. Additionally, it is believed that continuous suggestions and research will be necessary to apply the model to more diverse environments.
This study examined the patterns of coping strategies among Koreans during the early stage of the COVID-19 pandemic, explored the influence of demographic information (gender, age, economic level, household type), along with the unusual experiences due to COVID-19 (fear, stress of COVID, constraints of routine, income risk) on the classification of subclasses, and analyzed the latent profile differences in psychological wellbeing (life satisfaction, depression, and anxiety). An online survey was conducted among Korean Adults(n=600) between April 13, 2020 and 21, when WHO declared COVID-19 a global pandemic and Daegu as well as Gyeongsangbuk-do was nominated as a special disaster zone. First, Latent Profile Analysis (LPA) was used to identify subclasses of coping strategies and results suggested that the 4-class model had the best fit. Second, Class memberships were predicted by gender, age, economic level, as well as fear, stress, constraints of routine, and income risk, among the unusual experiences due to COVID-19. Finally, there are differences in psychological wellbeing among latent profiles. 'High level of adaptive coping group 3' showed the highest level of life satisfaction, 'Adaptive-maladaptive coping group 4' showed the highest level of depression, anxiety. Implications and suggestions are discussed based on the study results.
Journal of The Korean Society of Agricultural Engineers
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v.64
no.3
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pp.9-24
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2022
Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.
Journal of Korean Tunnelling and Underground Space Association
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v.23
no.6
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pp.605-612
/
2021
Amid growing global damage due to abnormal weather caused by global warming, the introduction of eco-friendly cars is accelerating to reduce greenhouse gas emissions from internal combustion engines. Accordingly, many studies are being conducted in each country to prepare for the explosion of hydrogen fuel in semi-closed spaces such as tunnels and underground parking lots to ensure the safety of hydrogen-electric vehicles. As a result of predicting the explosion pressure of the hydrogen tank using the equivalent TNT model, it was found to be about 1.12 times and 2.30 times higher at a height of 1.5 meters, respectively, based on the case of 52 liters of hydrogen capacity. A review of the impact on the human body and buildings by converting the predicted maximum explosive pressure into the amount of impact predicted that all predicted values would result in lung damage or severe partial destruction. The predicted degree of damage was applied only by converting the amount of impact caused by the explosion, and considering the additional damage caused by the explosion, it is believed that the actual damage will increase further and safety and disaster prevention measures should be taken.
Chan-hwi, Shin;Gyeong-jo, Min;Gyeong-Gyu, Kim;PuReun, Jeon;Hoon, Park;Sang-Ho, Cho
Explosives and Blasting
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v.40
no.4
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pp.15-26
/
2022
With the recent increase in old and dangerous buildings, the demand for technology in the field of structure demolition is rapidly increasing. In particular, in the case of structures with severe deformation of damage, there is a risk of deterioration in stability and disaster due to changes in the load distribution characteristics in the structure, so rapid structure demolition technology that can be efficiently dismantled in a short period of time is drawing attention. However, structural deformation such as unauthorized extension or illegal remodeling occurs frequently in many old structures, which is not reflected in structural information such as building drawings, and acts as an obstacle in the demolition design process. In this study, as an effective way to overcome the discrepancy between the structural information of old structures and the actual structure, access to actual structures through 3D modeling was considered. 3D point cloud data inside and outside the building were obtained through LiDAR and drone photography for buildings scheduled to be blasting demolition, and precision matching between the two spatial data groups was performed using an open-source based spatial information construction system. The 3D structure model was completed by importing point cloud data matched with 3D modeling software to create structural drawings for each layer and forming each member along the structure slab, pillar, beam, and ceiling boundary. In addition, the modeling technique proposed in this study was verified by comparing it with the actual measurement value for selected structure member.
Se-Hyeok Lee;Changuk Mun;Sangki Park;Jeong-Rae Cho;Junho Song
Journal of the Computational Structural Engineering Institute of Korea
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v.36
no.4
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pp.273-282
/
2023
Probabilistic safety assessment (PSA) has been widely used to evaluate the seismic risk of nuclear power plants (NPPs). However, studies on seismic PSA for process plants, such as gas plants, oil refineries, and chemical plants, have been scarce. This is because the major disasters to which these process plants are vulnerable include explosions, fires, and release (or dispersion) of toxic chemicals. However, seismic PSA is essential for the plants located in regions with significant earthquake risks. Seismic PSA entails probabilistic seismic hazard analysis (PSHA), event tree analysis (ETA), fault tree analysis (FTA), and fragility analysis for the structures and essential equipment items. Among those analyses, ETA can depict the accident sequence for core damage, which is the worst disaster and top event concerning NPPs. However, there is no general top event with regard to process plants. Therefore, PSA cannot be directly applied to process plants. Moreover, there is a paucity of studies on developing fragility curves for various equipment. This paper introduces PSA for gas plants based on FTA, which is then transformed into Bayesian network, that is, a probabilistic graph model that can aid risk-informed decision-making. Finally, the proposed method is applied to a gas plant, and several decision-making cases are demonstrated.
Min-Seop SIM;Jeong-Min Lee;Do-Yean KIM;Yul-Seong Kim
Journal of Navigation and Port Research
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v.47
no.1
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pp.37-48
/
2023
Recently, the increase of international trade volume is leading to risk exposure and safety accidents in the port terminal industry. In addition, as Serious Disaster Punishment Act came into effect on January, 2021, various guidelines and laws to protect safety and life in port terminals are being enacted. However, despite these efforts, medium-to-large safety accidents in the port terminal industry have occurred. According to the Korea Occupational Safety and Health Agency, from 2016 to 2019, the number of casualties in the port handling industry increased by 4.2%. To build some effective follow-up management of port accidents and preparation of related safety laws/systems, a risk analysis in consideration of causes and damage of accidents should be conducted. Therefore, in this study, major risk factors and preventive measures were derived by conducting risk assessment based on 1,039 cases of port terminal accidents collected by the Korea Occupational Safety and Health Agency for five years. Priorities for preventive measures were then determined through IPA analysis, Borich needs analysis, and The Locus For Focus analysis.
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