• Journal of the Korean association of regional geographers
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• v.21 no.2
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• pp.379-393
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• 2015

The fire damage has been increased as the frequency of fire incidence decreases with increasing in death and economic loss. Local governments are dependent on the activities of fire-fighters with crude preparedness and prevention for fire incidence. Most of researches on fire safety have focused on descriptive statistics which show general trends in fire incidence and condition. Here we tried to make a mutual causal model for fire damage, to make three big hypotheses with laying three small hypotheses under each big hypothesis. Five years statistics from public domains in the form of hardcopy or softcopy were collected and fifteen independent variables were selected to explain the number of death, the number of fire incidence and the amount of economic loss from fire incidence. The significances of statistics are different among the regional characteristics. The hypotheses were partially rejected and the meanings of rejected factors will refresh the tentative prejudice. It is necessary to revise the principle that the number of population and size of area are regarded as the most important criteria to allocate resources for fire control and to have the criteria flexible with results of our research such as the number of the weak to fire disaster.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.4
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• pp.10-17
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• 2020

The recent earthquake in Korea caused large and small damages to many school building. School building is an important building that is used as a shelter in the event of disaster. Among the seismic retrofit methods, the internal steel braced frame type method is used for its relatively easy construction and excellent performance. In this study, the maximum shear force and displacement were compared and examined by applying the brace frame to existing concrete school buildings. As a result, we verified the adequacy of the analytical model and compared and examined the effect of brace-height ratio on the span of the existing school buildings. The adequacy of the maximum shear force and displacement relationship can be confirmed in the model with a length of 0.3. In addition, seismic frame was applied to the actual non-seismic reinforced concrete school building, and the seismic performance was evaluated by nonlinear static analysis(Push-over analysis) according to the ratio of brace-height. As a result, the increase of the brace-height according to the brace-height ratio has the effect of increasing the maximum shear force and maximum load at the performance point. But the collapse of the braced frame due to the increase in the lateral stiffness occurred, indicating that seismic retrofit according to the proper brace-height is necessary. Therefore, in the seismic retrofit design of brace frame of existing school building, it is necessary to select the proper brace-height after retrofit analysis according to the brace-height ratio.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.811-819
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• 2013

This study aims to analyze determinants of mountainous and coastal area's housing value caused by the characteristics of the natural environment. As the current issue of housing value is throwing the spotlight on the climate change recently, environmental features are significantly important than before. There were a lot of studies on the influence of environmental characteristics to the housing price but these studies were mostly dealing with the housing price in especially apartments nearby Han-river in Seoul, South Korea. To have differences with existing studies, environmental characteristics estimating housing value are classified as 8 elements including the view, the wind speed, and the humidity. The result of this study is in following; there were few significant environmental variables in mountainous housing value growth model. This means people living in mountainous area recognize on environmental factors more such as housing or complex characteristics. People living in coastal area are much more sensitive environment variables in their residence value than mountainous area. Especially, the view for the ocean is the most important variable in housing value, and wind speed is second positively significant. Humidity and safety of disaster are negatively significant variables.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1965-1974
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• 2021

Satellite remote sensing approach can be actively used for forest monitoring. Especially, it is much meaningful to utilize Korea multi-purpose satellites, an independently operated satellite in Korea, for forest monitoring of Korea, Recently, several studies have been performed to exploit meaningful information from satellite remote sensed data via machine learning approaches. The forest information produced through machine learning approaches can be used to support the efficiency of traditional forest monitoring methods, such as in-situ survey or qualitative analysis of aerial image. The performance of machine learning approaches is greatly depending on the characteristics of study area and data. Thus, it is very important to survey the best model among the various machine learning models. In this study, the performance of deep neural network to classify artificial or natural forests was analyzed in Samcheok, Korea. As a result, the pixel accuracy was about 0.857. F1 scores for natural and artificial forests were about 0.917 and 0.433 respectively. The F1 score of artificial forest was low. However, we can find that the artificial and natural forest classification performance improvement of about 0.06 and 0.10 in F1 scores, compared to the results from single layered sigmoid artificial neural network. Based on these results, it is necessary to find a more appropriate model for the forest type classification by applying additional models based on a convolutional neural network.

• Journal of the Korea Institute of Building Construction
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• v.18 no.6
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• pp.611-619
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• 2018

The researches have only conducted regarding construction safety management and risk on interior construction site(workers) and is insufficient about the exterior construction site(third party). As a result, ordinary people who were near construction sites have injured and hold a negative view when they think about the construction industry because construction industry have been exposed to them having a high accidents rate through media. In addition, the importance of industrial disaster prevention is emphasized at this point in time, the overall safety management system should be constructed with considering construction site external(third human) for improving the negative image of the construction industry among ordinary people. Therefore, the objective of this study is to develop the quantification model of human accident utilizing the insurance claim payout occurred construction site exterior(third party). In the future, it can be used as a reference for developing the safety management checklist in construction site interior exterior and development for forecasting control system of human accident.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.305-312
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• 2018

The crops cultivated and consumed in Korea require specific climate conditions corresponding to their own growth characteristics. This study aims to analyze the relationship between climate change and agricultural productivity. According to growing concern about climate change internationally, many agricultural studies are developing technology to prevent damage from climate change. Before developing technology, we should figure out what kind of crop gets huge damage and how much caused by climate change. In the context of agricultural economics, we can define the reduction of agricultural product yield as a decline in productivity. As a result, this study analyzes the effects of climate change on agricultural productivity using Stochastic Frontier Analysis model. There are several kinds of climate change phenomena that increase the inefficiency of production. In other words, there are several kinds of crops that get negative influence by climate change. The result of this study can be used as basic guideline for producers to prepare for changing weather prior to developing disaster tolerance technology coping actively with special weather report.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.93-113
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• 2019

The behavior of the 3 hinged precast arch structure was investigated by comparing field measurements with numerical analyses performed for precast lining arch structures, which are widely used for the open-cut tunnel. According to the field measurements, the maximum vertical displacement occurred at the crown with upward displacements during the backfilling up to the crown of the arch and downward displacements at the backfill height above the crown. The final crown displacement was 19 mm upward from the original position. The horizontal displacement at the sidewall, which had a maximum horizontal displacement, occurred inward of the arch when compacting the backfill up to the crown and returned to the original position after completing the backfill construction. According to the analysis of displacement measurements, economical design is expected to be possible for precast arch structures compared to rigid concrete structures due to ground-structure interactions. Duncan model gave good results for the estimation of displacements and deformed shape of the tunnel according to the numerical analyses comparing with field measurements. The earth pressure coefficients calculated from the numerical analyses were 0.4 and 0.7 for the left and the right side of the tunnel respectively, which are agreed well with the eccentric load acting on the tunnel due to topographical condition and actual field measurements.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.707-721
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• 2022

In this study, a state-of-the-art review on urban inundation simulation technology was presented summarizing major achievements and limitations, and future research recommendations and challenges. More than 160 papers published in major domestic academic journals since the 2000s were analyzed. After analyzing the core themes and contents of the papers, the status of technological development was reviewed according to simulation methodologies such as physically-based and data-driven approaches. In addition, research trends for application purposes and advances in overseas and related fields were analyzed. Since more than 60% of urban inundation research used Storm Water Management Model (SWMM), developing new modeling techniques for detailed physical processes of dual drainage was encouraged. Data-based approaches have become a new status quo in urban inundation modeling. However, given that hydrological extreme data is rare, balanced research development of data and physically-based approaches was recommended. Urban inundation analysis technology, actively combined with new technologies in other fields such as artificial intelligence, IoT, and metaverse, would require continuous support from society and holistic approaches to solve challenges from climate risk and reduce disaster damage.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1167-1181
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• 2021

In relation to the algae bloom, four types of blue-green algae that emit toxic substances are designated and managed as harmful Cyanobacteria, and prediction information using a physical model is being also published. However, as algae are living organisms, it is difficult to predict according to physical dynamics, and not easy to consider the effects of numerous factors such as weather, hydraulic, hydrology, and water quality. Therefore, a lot of researches on algal bloom prediction using machine learning have been recently conducted. In this study, the characteristic importance of water quality factors affecting the occurrence of Cyanobacteria harmful algal blooms (CyanoHABs) were analyzed using the random forest (RF) model for Bohyeonsan Dam and Yeongcheon Dam located in Yeongcheon-si, Gyeongsangbuk-do and also predicted the occurrence of harmful blue-green algae using the machine learning and deep learning models and evaluated their accuracy. The water temperature and total nitrogen (T-N) were found to be high in common, and the occurrence prediction of CyanoHABs using artificial neural network (ANN) also predicted the actual values closely, confirming that it can be used for the reservoirs that require the prediction of harmful cyanobacteria for algal management in the future.