• International Journal of High-Rise Buildings
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• v.10 no.4
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• pp.335-344
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• 2021

In structural engineering practice, understanding the performance of composite columns under extreme loading conditions such as high-rise bulding, long span and heavy loads is essential to accuratly predicting of material responses under severe loads such as fires or earthquakes. Hitherto, the combined effect of partial axial loads and subsequent elevated temperatures on the performance of hollow steel column filled fly ash concrete have not been widely investigated. Comprehensive test was carried out to investigate the effect of elevated temperatures on partial axially loaded square hollow steel column filled fly ash concrete as reported in this paper. Four batches of hollow steel column filled fly ash concrete ( 30 percent replacement of fly ash), (HySC) and normal concrete (CFHS) were subjected to four different load levels, n_f of 20%, 30%, 40% and 50% based on ultimate column strength. Subsequently, all batches of the partially damage composite columns were exposed to transient elevated temperature up to 250℃, 450℃ and 650℃ for one hour. The overall stress - strain relationship for both types of composited columns with different concrete fillers were presented for each different partial load levels and elevated temperature exposure. Results show that CFHS column has better performance than HySC at ambient temperature with 1.03 relative difference. However, the residual ultimate compressive strength of HySC subjected to partial axial load and elevated temperature exposure present an improvement compared to CFHS column with percentage difference in range 1.9% to 18.3%. Most of HySC and CFHS column specimens failed due to local buckling at the top and middle section of the column caused by concrete crushing. The columns failed due to global buckling after prolong compression load. After the compression load was lengthened, the columns were found to fail due to global buckling except for HySC02.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.839-850
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• 2018

The flood damage in urban areas due to torrential rain is increasing with urbanization. For this reason, accurate and rapid flooding forecasting and expected inundation maps are needed. Predicting the extent of flooding for certain rainfalls is a very important issue in preparing flood in advance. Recently, government agencies are trying to provide expected inundation maps to the public. However, there is a lack of quantifying the extent of inundation caused by a particular rainfall scenario and the real-time prediction method for flood extent within a short time. Therefore the real-time prediction of flood extent is needed based on rainfall-runoff-inundation analysis. One/two dimensional model are continued to analyize drainage network, manhole overflow and inundation propagation by rainfall condition. By applying the various rainfall scenarios considering rainfall duration/distribution and return periods, the inundation volume and depth can be estimated and stored on a database. The Rainfall-Duration-Flooding Quantity (RDF) relationship curve based on the hydraulic analysis results and the Self-Organizing Map (SOM) that conducts unsupervised learning are applied to predict flooded area with particular rainfall condition. The validity of the proposed methodology was examined by comparing the results of the expected flood map with the 2-dimensional hydraulic model. Based on the result of the study, it is judged that this methodology will be useful to provide an unknown flood map according to medium-sized rainfall or frequency scenario. Furthermore, it will be used as a fundamental data for flood forecast by establishing the RDF curve which the relationship of rainfall-outflow-flood is considered and the database of expected inundation maps.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.313-320
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• 2018

In the spring of 2018, opened-flowers of fruit trees were frozen to death due to abnormal low temperature around Jeonbuk Province and southern Gyeonggi Province areas. In the 2000s, abnormal weather is observed all over the world very frequently. As a consequence, various sectors of the society suffer from economic damage and negative effects of the abnormal weather. Moreover, recent global climate change is believed to increase the incidence of extreme weathers, which are out of the normal range of the local climate. It is necessary to identify these abnormal weather phenomena accurately and analyze the effects of them on crops in order to understand the effects of them on crop yields. This study projected the trend of the low-temperature occurrence in the future by predicting the changes in future flowering dates and quantifying the temperature distribution after flowering using climate change scenarios. This study targeted areas actually producing a major portion of pear, peach, and apple in South Korea. The results of this study predicted that the flowering dates of these fruits will be approximately 20 days earlier than the current normal year in the future (2071-2100) for the study area. Moreover, it was found that the distribution of low temperature would vary by fruit type and region to some degree. The results of this study present only a portion of fruit trees cultivars grown in South Korea. It was expected that, when this approach is applied to various crops and fruit trees, it will be possible to contribute to preparing countermeasures for climate change in the agricultural sector.

• Journal of Korean Society of Rural Planning
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• v.24 no.4
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• pp.135-146
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• 2018

A Visual landscape planning and management system has been introduced and implemented by each ministry so as to solve the problems of visual landscape destruction due to recognition on the value of natural landscape of beautiful territory and various development projects. At present, this system emphasizes the importance of the visual and perceptual aspect of the landscape however, there is a lack of techniques required for comprehensively predicting, evaluating, and managing it. Furthermore, sustainable landscape management after the completion of development projects has been inadequately carried out, as the focus has been only on consultation in the planning process of the development project in institutional performance. To this end, we presented objective and standardized criteria to predict and judge the effects of development projects on landscapes before project implementation. During the implementation of the development project, the influence of the visual landscape becomes accumulated in the construction progress stage. There is a need to identify the main viewpoints and to examine the continuous changes in the landscape-influencing factors, owing to the remarkable influences on the landscape, such as the change in the topography and the change caused by the artificial structure. During the stage of managing the influence on the visual landscape after the completion of the project, the influence on landscape should be monitored by measuring the change in the continuous landscape-influencing factors and determining the extent to which the actual reduction plan has been implemented. These processes should be performed continuously to maintain the quality of the visual landscape. The change in the landscape caused by the development project is shown to cause relatively greater visual damage than other factors composing the landscape owing to the influence of the artificial factors including the structure or the building. This shows that not only detailed examination of the visual impact before the development project but also continuous management is required during and after the development project. For this purpose, we derived eight landscape-influencing factors including form/shape, line, color, texture, scale/volume, height, skyline, and landscape control point. The proposed considering to be of high utilization in that it has a clear target of the landscape influencing factors.

• Journal of the Korea Society for Simulation
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• v.28 no.3
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• pp.41-48
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• 2019

In modern-war campaign, precision-guided missiles are dominantly used to minimize the collateral damage. Imaging infrared seekers are widely applied for the precise guidance. Due to the high cost of the infrared detector, the cost for the one-shot weapon's test is a burden for the development. To reduce the test cost, a simulation method including imagery tracking is required, which is so-called integrated-flight simulation(IFS). The synthetic image generation(SIG)-based simulation method is typically used, which however cannot represent various environmental and target conditions. In this paper, a new IFS method is proposed using on-sight measured image to overcome the limitations of the SIG-based IFS(SIIFS). The target image acquired at the launching sight has been used only for checking the performance criteria of the image tracker and has not been tried for IFS since it has low resolution and little information. The study described in this paper, however, shows that the on-sight image-based IFS can predict the pre- and mid-course flight performance quite similarly and is very useful for the flight test analysis.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1584-1588
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• 2018

During hyperthermia therapy, cancer cells are heated to a temperature in the range of $40{\sim}45^{\circ}C$ for a defined time period to damage these cells while keeping healthy tissues at safe temperatures. Prior to hyperthermia therapy, the amount of heat energy transferred to the cancer cells must be predicted. Among various non-invasive methods, the thermal prediction method using the specific absorption rate (SAR) is the most widely used method. The existing methods predict the thermal distribution by using a single constant for the mass density in one organ through assignment. However, because the SAR and the bio heat equation (BHE) vary with the mass density, the mass density of each organ must be accurately considered. In this study, the mass density distribution was calculated using the relationship between the Hounsfield unit and the mass density of tissues in preceding research. The SAR distribution was found using a quasi-static approximation to Maxwell's equation and was used to calculate the potential distribution and the energy distributions for capacitive RF heating. The thermal distribution during exposure to RF waves was determined by solving the BHE with consideration given to the considering contributions of heat conduction and external heating. Compared with reference data for the mass density, our results was within 1%. When the reconstructed temperature distribution was compared to the measured temperature distribution, the difference was within 3%. In this study, the density distribution and the thermal distribution were reconstructed for the agar phantom. Based on these data, we developed an algorithm that could be applied to patients.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1805-1815
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• 2022

In 2022, wildfires broke out in Uljin-gun and Samcheok-si, which set the record for the longest forest fire in Korea, but there were no casualties. To protect local residents from wildfires, they must evacuate. Predicting the demand for evacuation in the event of wildfires is essential for the efficiency of disaster management. The purpose of this study is to analyze the human mobility patterns according to the occurrence of Uljin-gun and Samcheok-si wildfires. SKT floating population data was used in this study to analyze the human mobility patterns in Uljin-gun and Samcheok-si. The main findings are as follows. First, while the movement of the resident and visiting population decreased, the movement of the worker population was found to be similar to normal. Second, the resident population of Buk-myeon, Uljin-gun moved to the surrounding area to avoid the wildfires. Third, the region is an area judged to be safe from wildfires, and this mobility patterns are related to emergency disaster text messages. This study confirmed human mobility patterns of the population in the area where the wildfires through the floating population data, which is quantitative data. This suggests that it is important to guide residents to shelters through emergency text messages to minimize damage in the event of wildfires.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1195-1204
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• 2021

Recently, local torrential rain have become more frequent and severe due to abnormal climate conditions, causing a surge in human and properties damage including infrastructures along the river. In this study, water surface elevation prediction algorithm was developed using the LSTM (Long Short-term Memory) technique specialized for time series data among Machine Learning to estimate and prevent flooding of the facilities. The study area is Jamsu Bridge, the study period is 6 years (2015~2020) of June, July and August and the water surface elevation of the Jamsu Bridge after 3 hours was predicted. Input data set is composed of the water surface elevation of Jamsu Bridge (EL.m), the amount of discharge from Paldang Dam (m³/s), the tide level of Ganghwa Bridge (cm) and the number of tweets in Seoul. Complementary data were constructed by using not only structured data mainly used in precedent research but also unstructured data constructed through wordcloud, and the role of unstructured data was presented through comparison and analysis of whether or not unstructured data was used. When predicting the water surface elevation of the Jamsu Bridge, the accuracy of prediction was improved and realized that complementary data could be conservative alerts to reduce casualties. In this study, it was concluded that the use of complementary data was relatively effective in providing the user's safety and convenience of riverside infrastructure. In the future, more accurate water surface elevation prediction would be expected through the addition of types of unstructured data or detailed pre-processing of input data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.179-189
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• 2022

Ice and water droplets rise and fall above the freezing altitude under the effects of strong updrafts and downdrafts, grow into hail, and then fall to the ground in the form of balls or irregular lumps of ice. Although such hail, which occurs in a local area within a short period of time, causes great damage to the agricultural and forestry sector, there is a paucity of domestic research toward predicting hail. The objective of this study was to introduce Land-Atmosphere Modeling Package (LAMP) hail prediction and measure its performance for 50 hail events that occurred from January 2020 to July 2021. In the study period, the frequency of occurrence was high during the spring and during afternoon hours. The average duration of hail was 15 min, and the average diameter of the hail was 1 cm. The results showed that LAMP predicted hail events with a detection rate of 70%. The hail prediction performance of LAMP deteriorated as the hail prediction time increased. The radar reflectivity of actual cases of hail indicated that the average maximum reflectivity was greater than 40 dBZ regardless of altitude. Approximately 50% of the hail events occurred when the reflectivity ranged from 30~50 dBZ. These results can be used to improve the hail prediction performance of LAMP in the future. Improved hail prediction performance through LAMP should lead to reduced economic losses caused by hail in the agricultural and forestry sector through preemptive measures such as net coverings.

• Ecology and Resilient Infrastructure
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• v.10 no.1
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• pp.11-19
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• 2023

Alien species are known to threaten regional biodiversity globally, which has increased global interest regarding introduction of alien species. The Ministry of Environment of Korea designated species that have not yet been introduced into the country with potential threat as alert alien species to prevent damage to the ecosystem. In this study, potential habitats of Esox lucius and Maccullochella peelii, which are predatory and designated as alert alien fish, were predicted on a national basis. Habitat suitability was evaluated using EHSM (Ecological Habitat Suitability Model), and water temperature data were input to calculate Physiological Habitat Suitability (PHS). The prediction results have shown that PHS of the two fishes were mainly controlled by heat or cold stress, which resulted in biased habitat distribution. E. lucius was predicted to prefer the basins at high latitudes (Han and Geum River), while M. peelii preferred metropolitan areas. Through these differences, it was expected that the invasion pattern of each alien fish can be different due to thermal preference. Further studies are required to enhance the model's predictive power, and future predictions under climate change scenarios are required to aid establishing sustainable management plans.