• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.151-161
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• 2021

The purpose of this study was to identify citizens' needs and what they perceive the health-related problems are so public opinion can be reflected in the Daegu Community Health Plan. A citizen participation group was organized, and two roundtable discussions were held in June and July 2018. The number of participants in the first and second round was 40 and 44, respectively. Customer itinerary guidance, DVDM (Definition, Value, Difficulty, and Method) Map, and Persona-based scenario method were used for the roundtable discussions. The measures to improve the health status proposed by the citizens included expanding access to health services, establishing health services centered on small-living areas, expanding mental health services, creating health-friendly environments, resolving environmental problems, and improving social health. In addition, enhancing communication and creating harmonized environments, improving access to healthcare, generating pleasant physical environments, and assigning socials roles for vulnerable individuals were brought up as the means to resolve health disparities. The strength of the present study lies in the fact that, unlike survey methods, the citizens' exact needs were identified by sharing their thoughts. Moreover, it was proven that practical measures would be needed to implement citizen participation in planning health-related projects.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.107-118
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• 2022

As connected and automated driving(CAD) technology is entering its commercialization stage, service platforms providing CAD-based mobility services have increased these days. However, CAD-baded mobility services with these platforms need more consideration for the demand for mobility services when determining target areas for CAD-based mobility services because current CAB-based mobility design focus on driving performance and driving stability. For a more efficient design of CAD-based mobility services, we analyzed the applicability for the introduction of CAD-based mobility services in terms of driving difficulty of CAD and demand patterns of current non-CAD based-mobility services, e.g., taxi, demand-responsive transit(DRT), and special transportation systems(STS). In addition, for the spatial analysis of the applicability of the CAD-based mobility service, we propose the Index for Autonomous Driving Applicability (IADA) and analyze the characteristics of the spatial distribution of IADA from the network perspective. The analysis results show that the applicability of CAD-based mobility services depends more on the demand patterns than the driving difficulty of CAV. In particular, the results show that the concentration pattern of demand in a specific road link is more important than the size of demand. As a result, STS service shows higher applicability compared to other mobility services, even though the size of demand for this mobility service is relatively small.

• Journal of the Korean GEO-environmental Society
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• v.22 no.12
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• pp.33-40
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• 2021

The deterioration of underground facilities, disturbance of the ground due to underground development activities, and changes in ground water can cause ground subsidence accidents in the urban areas. The investigation on the geotechnical and hydraulic factors affecting the ground subsidence accident is very significant to predict the ground subsidence risk in advance. In this study, an analysis DB was constructed through 3D ground modeling to utilize the currently operating geotechnical survey information DB and ground water behavior information for risk prediction. Additionally, using these results, the relationship between the actual ground subsidence occurrence history and ground conditions and ground water level changes was confirmed. Furthermore, the methodology used to visualize the risk of ground subsidence was presented by reconstructing the engineering characteristics of the soil presented according to the Unified Soil Classification System (USCS) in the existing geotechnical survey information into the internal erosion sensitivity of the soil, Based on the result, it was confirmed that the ground in the area where the ground subsidence occurred consists of more than 40% of sand (SM, SC, SP, SW) vulnerable to internal erosion. In addition, the effect of the occurrence frequency of ground subsidence due to the change in ground water level is also confirmed.

• Journal of the Korea Institute of Building Construction
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• v.22 no.1
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• pp.69-80
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• 2022

The proportion of buildings over 30 years old in Korea has increased, from 29.0% in 2005 to 37.8% in 2019. These old buildings were built during a time in which there was a lack of building-related safety standards in areas such as fire safety performance. Worse, during their years of use, many such old buildings have had illegal changes and extensions made, making them more vulnerable in terms of safety. Fire safety investigations are being conducted to prevent large-scale disasters in multi-use buildings, but no investigation has been conducted at the regional district level, where small-scale old buildings are concentrated. Therefore, to identify fire risk factors in the old building district where old buildings are concentrated, the composition characteristics of the buildings were first analyzed. To examine the spatial characteristics of old building districts in order to derive fire risk factors, the results of this analysis based on the structure, use, roof type, and year of approval for use are as follows. It was found through our analysis that as of the date of approval for the use of the building, the main structure of the building has the greatest impact.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.175-201
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• 2023

In the midst of going through a non-face-to-face society, most of human activities narrowed down to the platform, restrictions on external activities are bringing the internal scalability of digital technology. Metaverse is virtually shifting reality and increasing the possibility of utilization in various areas. However, researches linked to the educational effects of metaverse, especially students with disabilities, are still an unknown area that lacks exploration. This paper focuses on the fact that metaverse-education is widening educational fields that meets the various needs of disabled students to realize social good and inclusive education, and communication effects such as resolving barriers to interaction are prominent. As a research method, examining literature research papers linked to AR/VR, metaverse with communication skills, interviews, articles, and columns by experts, and policy suggestions and implications for the special education was conducted. Although the limitations of research are confirmed, significant results are found on inclusive education, which provides educational maximizing effects and realizing human rights through direct immersive experience reflecting the Cone of Experience Theory. Hopefully follow-up studies on meta-edu for disabled students will be carried out in the future, and various interdisciplinary discussions are needed to carefully observe inclusive policies and benefits so that the socially vulnerable are not excluded from technologies in ICT society.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korean Geosynthetics Society
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• v.22 no.2
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• pp.1-12
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• 2023

Research on the causes of landslides and prediction of vulnerable areas is being conducted globally. This study aims to predict the effective soil depth, a critical element in analyzing and forecasting landslide disasters, using topographic information. Topographic data from various institutions were collected and assigned as attribute information to a 100 m × 100 m grid, which was then reduced through data grading. The study predicted effective soil depth for two cases: three depths (shallow, normal, deep) and five depths (very shallow, shallow, normal, deep, very deep). Three classification models, including K-Nearest Neighbor, Random Forest, and Deep Artificial Neural Network, were used, and their performance was evaluated by calculating accuracy, precision, recall, and F1-score. Results showed that the performance was in the high 50% to early 70% range, with the accuracy of the three classification criteria being about 5% higher than the five criteria. Although the grading criteria and classification model's performance presented in this study are still insufficient, the application of the classification model is possible in predicting the effective soil depth. This study suggests the possibility of predicting more reliable values than the current effective soil depth, which assumes a large area uniformly.

• Journal of the Korean Geotechnical Society
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• v.39 no.7
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• pp.57-67
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• 2023

Slope failures during rainfall have been observed in mountainous areas of South Korea as a result of the presence of solar power facilities. The seepage behavior and pore pressure distribution differ from typical slopes due to the presence of impermeable solar panels, and the load imposed by the solar power structures also affects the slope behavior. This study aims to develop a method for evaluating the stability of slopes with solar power facilities and to analyze vulnerable points by considering the maximum slope displacement. To assess the slope stability and predict behavior while considering rainfall seepage, a combined seepage analysis and finite difference method numerical analysis were employed. For the selected site, various variables were assumed, including parameters related to the Soil Water Characteristic Curve, strength parameters that satisfy the Mohr-Coulomb failure criterion, soil properties, and topographic factors such as slope angle and bedrock depth. The factors with the most significant influence on the factor of safety (FOS) were identified. The presence of solar power facilities was found to affect the seepage distribution and FOS, resulting in a decreasing trend due to rainfall seepage. The maximum displacement points were concentrated near the upper (crest) and lower (toe) sections of the slope.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.53-60
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• 2023

Recently, along with the improvement of high-speed rail and road design speed, the proportion of tunnel construction work is increasing proportionally. In particular, the construction of long tunnels is rapidly increasing due to the mountainous terrain of our country. In this way, due to the trend of tunnels becoming longer, it is difficult to design and construct tunnels by avoiding fault zones. In the case of tunnel construction in mountainous areas, ground investigation is often difficult even during design due to the topographical conditions, making precise ground investigation difficult, and as a result, the upper part of the tunnel is damaged during tunnel construction. When fault zones, which are vulnerable to weathering, exist, the stability of the tunnel during excavation is directly affected by the fault zone distribution, strength characteristics, and groundwater distribution range. In particular, when a fault zone is distributed in the upper part of a tunnel, damage such as tunnel collapse and excessive displacement may occur, and in order to prevent this in advance, countermeasures must be established through analysis of similar cases. Therefore, in this study, when a large-scale fault zone exists in the upper part of a tunnel, the relationship and characteristics of damage to the tunnel structure were analyzed.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.