• Journal of Korean Tunnelling and Underground Space Association
• /
• v.11 no.2
• /
• pp.199-211
• /
• 2009

Development of underground space is actively performed globally for better life in the surface, and the scale of the space is increasing. Extreme care should be taken in the construction of the underground space in urban areas in order to avoid damage of adjacent structures and interference with existing underground space. In case of shallow tunnels, reinforcement of ground and structures is necessary to minimize the damage to structures due to excavation but any standard for optimum range of the reinforcement has not been established yet. In this paper, a series of numerical analyses have been performed for a 20 m diameter tunnel excavated underneath a structure to investigate the degree of damage of the structure according to vertical and horizontal spacing between the tunnel and structure. In addition to that, optimum range of reinforcement is presented for each case where reinforcement is required. It has been observed that the reinforcement is necessary for the ground condition adapted in the analyses as follows: (1) if horizontal spacing ($S_{H}$) approaches to 0D (D: equivalent diameter of tunnel) for vertical spacing (Sv) of 0.5D, and (2) if tunnel exists underneath the structure for vertical spacing (Sv) of 0.75D. The reinforcement is not necessary for Sv of 10 regardless of $S_{H}$. It also has been obtained that the optimum ranges of the reinforcement around structure foundation are 7 m in depth and whole width of the structure and 5 m beyond tunnel sidewall. These reinforcememt ranges have been confirmed to be enough for stability of the structure if types of reinforcement method is appropriately selected.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.2D
• /
• pp.275-286
• /
• 2009

As a government building transferred to the outskirts of a city, it's easy to foresee a doughnut effect from advancement process of the city. In the case of Busan city comparing different cities a doughnut effect is being advanced seriously. To the access method for a city center activation the possibility which there will be a various branch, but in this research we analyzed factors of the stagnation in the public Government building neighboring area. And then made a proposal for the city activation plan by transferring the public Government building, analyze influence to surrounding areas using factor analysis. Hence, the object of this paper is to propose a plan for the activation of existig city and evaluates it which is presented consequently. In the case of Dongrae government office, a problem of the neighboring area and condition of present were surveyed and causes of the stagnation in existing city analyzed. Consequently the important five factors were extracted as follows; 1) historical and the cultural factor, 2) factor of creating the special street, 3) urban planning factor, 4) factor of transferring government office.

• Journal of Korea Entertainment Industry Association
• /
• v.13 no.8
• /
• pp.1-12
• /
• 2019

The purpose of this study is to explore ways to promote the stay type tourism in Ulsan. To achieve this, IPA analysis techniques were applied to survey the importance and performance of experts, tourists, and hotel users, and measures were developed for activation of common points among the groups. Most studies analyze the survey results of a group, but this study compared and analyzed the results among three groups of experts, tourists, and hotel users, resulting in areas requiring activation. According to the results of each group, 'cultural facilities' were selected as the attraction factor, and 'night tours' were chosen as the basic factor to improve. On the other hand, tourist attractions, clean environment and urban parks have been selected as implementation factors, which correspond to the "ecological tourism," one of Ulsan's five-color themes. According to the ranking, the three groups of experts, tourists, and hotel users were able to look at the results of priority items that were selected up to the third place, although there were no exact matching factors. The items selected by both groups were diversification of night viewing, traffic accessibility in tourist sites, and improvement of night scenery, operation of night experience programs, extension of night opening hours, and revitalization of night markets respectively.

• Korean Journal of Remote Sensing
• /
• v.40 no.1
• /
• pp.71-80
• /
• 2024

In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.

• Journal of Internet Computing and Services
• /
• v.24 no.6
• /
• pp.119-125
• /
• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_3
• /
• pp.1721-1730
• /
• 2023

As awareness of the problem of global warming emerges around the world, the role of carbon sinks in settlement is increasingly emphasized to achieve carbon neutrality in urban areas. In order to manage carbon sinks in settlement, it is necessary to identify the current status of carbon sinks. Identifying the status of carbon sinks requires a lot of manpower and time and a corresponding budget. Therefore, in this study, a map predicting the location of trees was created using already established tree location information and Sentinel-2 satellite images targeting Seoul. To this end, after constructing a tree presence/absence dataset, structured data was generated using 16 types of vegetation indices information constructed from satellite images. After learning this by applying the Extreme Gradient Boosting (XGBoost) model, a tree prediction map was created. Afterward, the correlation between independent and dependent variables was investigated in model learning using the Shapely value of Shapley Additive exPlanations(SHAP). A comparative analysis was performed between maps produced for local parts of Seoul and sub-categorized land cover maps. In the case of the tree prediction model produced in this study, it was confirmed that even hard-to-detect street trees around the main street were predicted as trees.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_4
• /
• pp.1165-1172
• /
• 2023

Recently, Korea has declared carbon neutrality by 2050. The Korea Forest Service is promoting the precision and high technology of forest resource surveys. As such, the demand for forest resource management is increasing, and the need to build a digital twin of forest space is increasing. However, to date, digital twin has only built and provided virtual city services, which are city and nationwide digital twin environments. Three-dimensional digital twin services targeting forest space are not operated and provided. Therefore, in this study, we aimed to implement a forest digital twin environment to provide 3D forest spatial information services corresponding to vertical information such as tree-level height and thorax diameter. By lightweighting realistic 3D tree models and applying 3D Tiles, we confirmed the feasibility of implementing a forest digital twin environment for 3D forest spatial information services. Through continuous research, we plan to implement a forest digital twin that can deploy and service 3D tree models for trees nationwide, including street trees in urban areas. This is expected to enable the development of forest digital twin services for forest resource management.

• Korean Journal of Environmental Biology
• /
• v.41 no.3
• /
• pp.247-255
• /
• 2023

The occurrence of sudden strike pest events in urban areas is increasing as global warming intensifies, consequently, re causing harmful impacts. Studies on these incidents are fewer in number and insufficient compared to research on other nuisances such as mosquitoes and flies. Therefore, we conducted a study on the development of a selective collection method, using a filter layer to establish a monitoring system for Ephemera orientalis (Ephemeroptera: Ephemeridae), a species frequently identified as a sudden strike pest. Three sampling points were selected along the Hangang River in Namyangju, where E. orientalis outbreaks occur. Prototypes, consisting of four layers and with a light source attached to attract insects, were installed at each sampling point. Sampling was performed every 30 minutes between 19:00 and 22:30 in the month of June. The filter interval of each layer was adjusted so that the collected mayflies were distributed into specific layers. To evaluate the collection efficiency in line with the materials and the filter intervals, the optimal collection efficiency was investigated by combining two types of layer materials (stainless and acrylic) and filter intervals (1-5 mm). The optimal conditions were as follows: The selective collection efficiency was found to be highest at 96.5% when the interval of the selective target filter was 2.0 mm and there was one upper filter.

• Korean Journal of Environment and Ecology
• /
• v.38 no.2
• /
• pp.127-142
• /
• 2024

This study aimed to understand the interrelationships between tree species in plant communities through Plant Social Network (PSN) analysis using a large amount of vegetation data surveyed in an island area belonging to a warm-temperate boreal forest. The Machilus thunbergii, Castanopsis sieboldii, and Ligustrum japonicum, which belong to the canopy layer, Pittosporum tobira and Ardisia japonica, which belong to the shrub layer and Trachelospermum asiaticum and Stauntonia hexaphylla, which belong to the vines, appearing in evergreen broad-leaved climax forest community, showed strong positive association(+) with each other. These tree species had a negative association or no friendly relationship with deciduous broad-leaved species due to the large difference in location environments. Divided into 4 group modularizations in the PSN sociogram, evergreen broad-leaved tree species in Group I and deciduous broad-leaved tree species in Group II showed high centrality and connectivity. It was analyzed that the arrangement of tree species (nodes) and the degree of connection (grouping) of the sociogram can indirectly estimate environmental factors and characteristics of plant communities like DCA. Tree species with high centrality and influence in the PSN included T. asiaticum, Eurya japonica, Lindera obtusiloba, and Styrax japonicus. These tree species are common with a wide range of ecological niches and appear to have the characteristics and survival strategies of opportunistic species that commonly appear in forest gaps and damaged areas. They will play a major role in inter-species interactions and structural and functional changes in plant communities. In the future, long-term research and in-depth discussions are needed to determine how these species actually influence plant community changes through interactions

• Journal of the Korean GEO-environmental Society
• /
• v.25 no.1
• /
• pp.5-11
• /
• 2024

Ground subsidence mainly occurs in urban areas with high population density, so it is necessary to clearly identify the cause of occurrence and prepare in advance. The main cause of ground subsidence is reported to be the creation of cavities in the ground due to damage to underground pipes, but the property information and influencing factors of underground pipes to predict and prepare for ground subsidence are not properly established. Therefore, in this study, factors showing a significant correlation with the occurrence of ground subsidence were selected among the underground facility property information and a regression equation was proposed through logistic regression analysis. For this purpose, data on underground structures and ground subsidence history information in the target area were collected, and the target area was divided into girds of 100m x 100m in size using QGIS. The underground facility attribute information and ground subsidence history information contained within the gird were extracted. Then, preprocessing was performed to construct a dataset and correlation analysis was performed. As a result, factors excluding the year of sewer pipes and communication pipes and the average depth of communication pipes, heat pipes, and gas pipes were found to have a significant correlation with ground subsidence. In addition, a regression equation for whether ground subsidence occurred in the target area is proposed through logistic regression analysis.