• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• Journal of the Korean Regional Science Association
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• v.37 no.1
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• pp.29-44
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• 2021

Particulate matter(PM) is one of the leading causes of lung cancer. Recognizing its considerable risk to human health, people change their behaviors when a concentration level of PM is high. The impact of particulate matter on urban activities may vary depending on the lasting days of PM and PM matter alerts. In addition, the level of averting behavior may vary depending on the types and physical characteristics of urban activities and the degree of vulnerability to PM among people. Although the way people respond to PM may vary depending on these various factors, previous research evidence on this is very insufficient. Therefore, this study multilaterally analyzed the impact of PM on the urban activities in Jongno-gu, one of the CBD areas of Seoul. For this, we linked SKT's mobile phone signal data to land use data to extract the daily number of active people by urban activity types and ages. According to multiple regression analysis, the averting behavior varies depending on the type of urban activity, the physical characteristics of the place of activity(inside and outdoor), the lasting days of PM, PM alerts and the age of people. The results of this study can be used as basic data to policy makers who establish policies for adapting to air pollution policies by providing various effects of PM on the urban activities.

• Land and Housing Review
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• v.13 no.1
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• pp.23-38
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• 2022

As city tourism has recently been evaluated as a major indicator of urban competitiveness, strengthening the role of cities as tourist destinations has received more attention. However, industrialization and urbanization of many cities lead to population decline, extinction of traditional industries, and deterioration of living environments, weakening urban functions and competitiveness. Thus, it is essential for declining cities to build a measure to restore urban competitiveness by enhancing urban functions. Accordingly, this study focused on socio-cultural urban regeneration by exploring physical spaces for tourism destinations in declining cities. Different from general tourist destinations, tourism destinations of urban regeneration have a temporal perspective covering the past, present, and future. How does the temporal perspective of urban regeneration tourist destinations affect tourists' satisfaction and behavioral intention? In order to address these questions, this study conducts an empirical analysis based on structural equation modeling (SEM) using the sample of tourists who have visited urban regeneration tourism destinations. With SEM, this paper investigates structural relationships across variables by testing the hypothesis established in the proposed research model. The results show that precious memories of the past are the most important factor for tourists to visit urban regeneration tourist destinations. The empirical findings of this study will contribute to the research areas of urban tourism, urban regeneration tourism, and urban regeneration tourism destinations. In addition, this study can provide practical implications to develop socio-cultural contents of urban regeneration areas as tourism resources to establish plans for urban regeneration projects and achieve sustainable development strategies.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Korean Journal of Heritage: History & Science
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• v.55 no.3
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• pp.60-72
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• 2022

A number of wooden built heritage remain in Korea, and most have been damaged by various biological factors including termite. Owing to the irreversible damage caused by termites, wooden built heritage are losing their authenticity and structural stability. In this study, Area-Wide Integrated Termite Management(AW-ITM) was proposed to prevent termite damage. First, to understand the locational characteristics of these sites, the distance from adjacent forests and surrounding forest areas was analyzed for 182 national designated wooden built heritage(national treasures, treasures) using the Geographic Information System(GIS). By analyzing existing pest control projects(2003-2020) and the components of the ITM, the characteristics of termite control for cultural heritages were determined. Based on these results, the cultural heritage sites and their surrounding spaces were divided into three areas, and the types of cultural properties were divided into six types according to the location and number of buildings. Along with this, termite control measures were proposed for each area and type. The concept of AW-ITM has been partially applied to the "Comprehensive Control of Termites in wooden built heritages Sites" by the Cultural Heritage Administration. Caution must be taken with regard to the establishment of a cultural heritage management policy; AW-ITM should be applied on a trial basis with the results then being carefully analyzed and reflected in the establishment of policies pertaining to the conservation management of cultural heritage.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.855-863
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• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.302-311
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• 2022

Sound barrier walls are one of the most effective alternatives for reducing environmental noise on roads and railways in the city center. The insertion loss of the sound barrier against road traffic noise is the sum of the sound transmission loss, sound absorption loss, and sound energy reduction due to the diffraction attenuation of the sound barrier. The sound transmission loss of the sound barrier is one of the important factors that determine the insertion loss of the sound barrier and is a basic indicator that determines the performance of the sound barrier. Nevertheless, there is not a separate standard in Korea for measuring the acoustic transmission loss of sound barrier panels. There are only a few conditions in KS F 4770 series that stipulates on the general material of sound barrier panels. This thesis examines the necessity of the acoustic transmission loss measurement and evaluation standards of sound barrier walls, and seeks a measurement method in a free sound field (anechoic chamber) sound receiving room considering the characteristics of sound barrier walls installed in external spaces, unlike indoor building materials. In addition, a single number evaluation method using a reference spectrum was proposed so that the sound insulation effect according to various installation places such as roadside or railroad side can be easily displayed.

• Explosives and Blasting
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• v.41 no.1
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• pp.1-18
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• 2023

Stemming is a process applied to blast holes to prevent gases from escaping during detonation. A stemming material helps confine the explosive energy for longer and increases rock fragmentation. This study developed a stemming material based on a shear-thickening fluid (STF) that reacts to dynamic shock. Two blasting experiments were conducted to Field-verify the performance of the STF-based stemming material. In the first experiment, the pressure inside the blast hole was directly measured based on applying the stemming material. In the second field verification, tunnel blasting was performed, and the blasting results of sand stemming and, that of the STF-based stemming case were compared. The measurement results of the pressure in the blast hole showed that when the STF-based stemming material was applied, the pressure at the top of the blast hole was lower than in the sand stemming case, and the stemming ejection was also lower. The results of the field application verify that the excavation performance of the STF-based stemming case in the tunnel blasting was superior to that of the sand stemming case.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.85-97
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• 2023

Seoul Boramae Park was opened on May 5, 1986, after the Republic of Korea Air Force Academy relocated to Cheongju City in 1985. This study aims to examine the birth and evolution of Seoul Boramae Park and diagnose the park's value being transformed from the former site of the Air Force Academy. Policy reports and newspaper data were analyzed as a research method, focusing on Seoul public records. The study results are as follows. First, Seoul Boramae Park is a large-scale park created before the policy for parks on relocated sites we enacted. Second, Seoul Boramae Park has historical value as an urban park where memories and traces of the Air Force Academy overlap. Third, Seou Boramae Park contributed to regional change by promoting the public value of parks created on the relocated sites with an urban planning method. Seoul Boramae Park has implications for Korean landscape history as a case of securing large green areas in Seoul and presenting its function and roles as a park created on a relocated site.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.