• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.4
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• pp.28-36
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• 2002

The main purpose of this study was to estimate a new regression model to explain the relationship between urban forest and air temperature in summer, 2001. This study consists of two parts: correlation coefficient analysis and regression analysis. According to correlation coefficient analysis, thermal infra-red radiations of the major land use categories found significant difference in each category. However there were no significant relationship between the data (thermal infra-red radiation and NDVI) derived from Landsat-7 ETM+ image and air temperature at Automatic Weather Stations(AWSs). After estimating various regression models for summer air temperature, the final models were chosen. The final regression models consisted of two variables such as forest m and traffic facilities area. The regression models explained over 78% of the variability in air temperatures. The regression models with variables of forest area and traffic facilities area showed that the coefficient of the first variable was even more significant than the second one. However, the negative impact of the traffic facilities area was slightly greater than the positive impact of the forest area. Consequently, the effects of forest area and traffic facilities area were apparent to explain summer air temperature in Seoul. Therefore two policies have the most important implications to mitigate the summer air temperature in Seoul: to expand and to conserve the urban forest; and to change the Oafnc facilities'characteristics. The results from this study are expected to be useful not merely in informing the public that urban forest mitigates summer air temperahne, but in urging the necessity of budgets for trees and managing urban forests. It is recommended that field swey of summer air temperature be Performed for the vadidation of the models. The main purpose of this study was to estimate a new regression model to explain the relationship between urban forest and air temperature in summer, 2001. This study consists of two parts: correlation coefficient analysis and regression analysis. According to correlation coefficient analysis, thermal infra-red radiations of the major land use categories found significant difference in each category. However there were no significant relationship between the data (thermal infra-red radiation and NDVI) derived from Landsat-7 ETM+ image and air temperature at Automatic Weather Stations(AWSs). After estimating various regression models for summer air temperature, the final models were chosen. The final regression models consisted of two variables such as forest m and traffic facilities area. The regression models explained over 78% of the variability in air temperatures. The regression models with variables of forest area and traffic facilities area showed that the coefficient of the first variable was even more significant than the second one. However, the negative impact of the traffic facilities area was slightly greater than the positive impact of the forest area. Consequently, the effects of forest area and traffic facilities area were apparent to explain summer air temperature in Seoul. Therefore two policies have the most important implications to mitigate the summer air temperature in Seoul: to expand and to conserve the urban forest; and to change the traffic facilities'characteristics. The results from this study are expected to be useful not merely in informing the public that urban forest mitigates summer air temperature, but in urging the necessity of budgets for trees and managing urban forests. It is recommended that field survey of summer air temperature be Performed for the vadidation of the models.

• Journal of Environmental Health Sciences
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• v.44 no.4
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• pp.330-339
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• 2018

Objectives: The occurrence characteristics of BTEXS and phytoncides were investigated by type of urban forest. Methods: Four types of urban green space (Hongneung Forest, Mt. Chunjang, residential park, and traffic island) and Gwangneung Forest were selected. Monitoring of phytoncides and BTEXS was conducted considering the activity times of urban residents (five times per day) using a Tenax TA tube and suction pump in June 2017 (one day). Results: Phytoncide concentrations were ranked as Gwangneung Forest>Hongneung Forest>Mt. Cheonjang>traffic island>residential park. Relatively high concentrations of phytoncides were also identified in the urban forest. There was no significant difference between Gwangneung Forest and the urban forest. BTEXS concentrations were ranked as traffic island>residential park>Hongneung Forest>Gwangneung Forest>Mt. Cheonjang. Traffic island and residential park showed high levels of BTEXS depending on the inflow of vehicles. The difference in concentration by time was significant for the traffic island in particular. Pollutant levels in Hongneung Forest were as low as in Gwangneung Forest. Conclusion: The concentrations of phytoncides and BTEXS were different by types of urban green space, and the potential for health and hygiene of urban forests were able to be investigated. This study is expected to provide as basic data for the creation of urban forest spaces in the future.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.569-575
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• 2021

This study analyzed the effect of forests on reducing particulate matter by investigating the particulate matter concentration and influencing factors between urban forest and traffic forest. The concentrations of particulate matter in Hongreung Experimental Forest (urban forest) and a forest (traffic forest) formed at the intersection of Cheongryangri Station in Dongdaemun-gu, Seoul were measured with the light scattering method instrument from January to November 2018. During the study period, the average PM₁₀ concentrations in the urban forest and the traffic forest were 12.5㎍/m³ and 15.7 ㎍/m³, respectively, and the average PM_2.5 concentrations were 16.6㎍/m³and 6.9 ㎍/m³, respectively. Comparing the concentration by the urban atmospheric measurement network of the Ministry of Environment and the concentration in urban forests showed that the reduction rate of PM₁₀ was 66.9±28.6% in urbanforest and 58.6±44.1% in traffic forest and that of PM_2.5 was 71.3±23.0% and 64.9±31.3%. The difference in the reduction rate of particulate matter is likely related to the size and structure of the urban forest, and the wind velocity is considered the reduction factor.

• Korean Journal of Environmental Agriculture
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• v.42 no.2
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• pp.121-130
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• 2023

The RGB (red, green, and blue) imagery analysis is an important remote sensing tool, which estimates the effect of environmental stress on turfgrass growth and physiology. Therefore, this study investigated the effect of continuous wear stress treatment on Zoysia japonica through RGB imagery analysis. The results of the growth measurement showed that the plant height substantially decreased, after nine hours of treatment with no considerable difference thereafter. Dry weight measurement showed a substantial difference in the morphological growth characteristics of the aerial part of the turfgrass, but none in the stolon and root zone. This could be attributed to the short period of compaction treatment. The ROS (reactive oxygen species) analysis showed that ROS rapidly increased due to wear stress treatment. The MDA content increased during the traffic process, whereas the green pixels increased and decreased repeatedly; however, overall, the trend declined but the overall trend decreased. Thus, this study confirmed that MDA was effective in reflecting the wear stress of turfgrass; however, it could through RGB image analysis.

• Journal of the Korean housing association
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• v.19 no.1
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• pp.1-8
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• 2008

This study is an attempt to understand the floor-specific characteristics of facade road traffic noise in apartment buildings. For this purpose, it sampled a total of seven roadside apartment building complexes: three with no soundproof bar barrier installed at roadside, one with a forest buffer zone, one with a sound-absorbing hill, and two with soundproof barriers. The measured noise level was highest on the 5th floor of apartment buildings with no soundproof barrier, and the upper stories from the 5th floor showed lower-noise measurements in order. For apartment buildings with soundproof barriers, however, the noise level was lower on the 10th floor than the 5th floor. Two apartment building groups--one with a sound-absorbing hill and the other with no soundproof barrier--showed similar measurement results in the floor-specific characteristics of facade road traffic noise. This suggests that such installations have little sound insulation effect. In the apartment building complex with a forest buffer zone around it, a slight sound insulation effect was measured on the lower floors of the buildings.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.156-168
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• 2024

Purpose: The trend of highway traffic accidents shows a repeating pattern of increase and decrease, with the fatality rate being highest on highways among all road types. Therefore, there is a need to establish improvement measures that reflect the situation within the country. Method: We conducted accident severity analysis using Random Forest on data from accidents occurring on 10 specific routes with high accident rates among national highways from 2019 to 2021. Factors influencing accident severity were identified. Result: The analysis, conducted using the SHAP package to determine the top 10 variable importance, revealed that among highway traffic accidents, the variables with a significant impact on accident severity are the age of the perpetrator being between 20 and less than 39 years, the time period being daytime (06:00-18:00), occurrence on weekends (Sat-Sun), seasons being summer and winter, violation of traffic regulations (failure to comply with safe driving), road type being a tunnel, geometric structure having a high number of lanes and a high speed limit. We identified a total of 10 independent variables that showed a positive correlation with highway traffic accident severity. Conclusion: As accidents on highways occur due to the complex interaction of various factors, predicting accidents poses significant challenges. However, utilizing the results obtained from this study, there is a need for in-depth analysis of the factors influencing the severity of highway traffic accidents. Efforts should be made to establish efficient and rational response measures based on the findings of this research.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.1-8
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• 2015

Security has become an issue due to the rapid increases in internet traffic data network. Especially P2P traffic data poses a great challenge to network systems administrators. Preemptive measures are necessary for network quality of service(QoS) and efficient resource management like blocking suspicious traffic data. Deep packet inspection(DPI) is the most exact way to detect an intrusion but it may pose a private security problem that requires time. We used several machine learning methods to compare the performance in classifying network traffic data accurately over time. The Random Forest method shows an excellent performance in both accuracy and time.

• Geophysics and Geophysical Exploration
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• v.23 no.4
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• pp.230-242
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• 2020

We performed a magnetotelluric (MT) survey to delineate the geological structures below the depth of 20 km in the Gyeongju area where an earthquake with a magnitude of 5.8 occurred in September 2016. The measured MT data were severely distorted by electrical noise caused by subways, power lines, factories, houses, and farmlands, and by vehicle noise from passing trains and large trucks. Using machine-learning methods, we classified the MT time series data obtained near the railway and highway into two groups according to the inclusion of traffic noise. We applied three schemes, stochastic gradient descent, support vector machine, and random forest, to the time series data for the highspeed train noise. We formulated three datasets, Hx, Hy, and Hx & Hy, for the time series data of the large truck noise and applied the random forest method to each dataset. To evaluate the effect of removing the traffic noise, we compared the time series data, amplitude spectra, and apparent resistivity curves before and after removing the traffic noise from the time series data. We also examined the frequency range affected by traffic noise and whether artifact noise occurred during the traffic noise removal process as a result of the residual difference.

• Korean Journal of Agricultural Science
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• v.32 no.1
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• pp.1-8
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• 2005

This study was carried out to examine the effect of heavy traffic on chemical properties of soil in roadside trees of Daejeon city. Soil samples at 0~10cm and 10~30cm depths were collected from soil of the roadside trees, Platanus occidentalis, and Ginko biloba, Soil pH in heavy traffic regions were around 7.0 at 0~10cm and 10~30cm soil depths because of spraying of calcium chloride for snow moving. The concentrations of Fe, Cd, Cu, Zn, and Pb in soil were higher in heavy traffic regions(Daejeon Station and Daehwa Industrial Complex) than in light traffic region (Chungnam National University). The result could be from rubbing and wear of car tire and metals when they travel.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.435-446
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• 2022

Identifying ship types is an important process to prevent illegal activities on territorial waters and assess marine traffic of Vessel Traffic Services Officer (VTSO). However, the Terrestrial Automatic Identification System (T-AIS) collected at the ground station has over 50% of vessels that do not contain the ship type information. Therefore, this study proposes a method of identifying ship types through the Random Forest Classifier (RFC) from dynamic and static data of AIS and V-Pass for one year and the Ulsan waters. With the hypothesis that six features, the speed, course, length, breadth, time, and location, enable to estimate of the ship type, four classification models were generated depending on length or breadth information since 81.9% of ships fully contain the two information. The accuracy were average 96.4% and 77.4% in the presence and absence of size information. The result shows that the proposed method is adaptable to identifying ship types.