• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.217-229
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• 2020

Recently, weather changes in Korea have intensified due to global warming, and the five major natural disasters that occur mostly include heavy rains, typhoons, storms, heavy snow, and earthquakes. Busan is vulnerable to snow disaster, given that the amount of natural disaster damage in Busan accounts for more than 50% of the total amount in the entire metropolitan cities in Korea, and that the Busan area includes many hilly mountains. In this study, we attempted to identify vulnerable areas for snowfall disasters in Busan areas using the geographic information system (GIS) with the data for both geographical and anthropogenic characteristics. We produced the maps of vulnerable areas for evaluating factors that include altitude, slope, land cover, road networks, and demographics, and overlapped those maps to rank the vulnerability to snowfall disasters as the 5th levels finally. To weight each evaluating factor, we used an entropy method. The riskiest areas are characterized by being located in mountainous areas with roads, including Sansung-ro in Geumjeong-gu, Mandeok tunnel in Buk-gu, Hwangnyeongsan-ro in Suyeong-gu, and others, where road restrictions were actually enforced due to snowfall events in the past. This method is simple and easy to be updated, and thus we think this methodology can be adapted to identify vulnerable areas for other environmental disasters.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.169-177
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• 2007

Existing wireless access (mobile) routers are based commonly on the network address and port translation (NAPT) technique which permits simultaneously sharing a subscriber's connection to the network with multiple users. However, the NAPT architecturally makes the users invisible on the network side, thus becoming a user-oriented connection technique. In this paper, we propose a novel service provider-oriented unlicensed nomadic access relay station (WiNNERS) for helping wireless broadband network service providers to make their business more lucrative by accommdating unlicensed band users as subscribers into their network. The WiNNERS offers service providers the capability to directly manage each of the unlicensed band users at the network side. This direct management allows the service providers to flexibly and simply handle QoS, access control, and billing for each user. In order to distinguish each of the unlicensed band users the WiNNERS constructs a virtual tunnel from each user's terminal to the network access router using connection identifiers which is defined for service flow management within the WiBro system, Consequently, our proposed service provider-oriented relay station can be included into the WiBro network system with minimum modifications.

• Tunnel and Underground Space
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• v.23 no.5
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• pp.353-361
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• 2013

Previous studies for analyzing optimal haulage routes of dump trucks in open pit mines mostly used raster data. However, the raster data has several problems in performing optimal route analyses: (1) the jagged appearance of haulage roads according the cell resolution often causes overestimation of the travel cost; (2) it difficult to trace the topological relationships among haulage roads. These problems can be eliminated by using vector network data, however a new method is required to reflect the performance characteristics of a dump truck according to terrain gradient changes. This study presents a new method to create vector network data with the consideration of terrain gradient for analyzing optimal haulage routes of dump trucks in open pit mines. It consists of four procedures: (a) creating digital elevation models, (b) digitizing haulage road networks, (c) calculating the terrain gradient of haulage roads, and (d) calculating the average speed and travel time of a dump truck along haulage roads. A simple case study at the Roto South pit in the Pasir open pit coal mine, Indonesia is also presented to provide proof that the proposed method is easily compatible to ArcGIS Network Analyst software and is effective in finding optimal haulage routes of dump trucks with considering terrain gradient in open pit mines.

• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.400-414
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• 2021

Under high-level radioactive waste repository conditions, bentonite as an engineered barrier material undergoes thermal, hydrological, mechanical, and chemical processes. We report the applications of X-ray Computed Tomography (CT) imaging technique on the characterization and analysis of bentonite over the past decade to provide a reference of the utilization of this technique and the recent research trends. This overview of the X-ray CT technique applications includes the characterization of the bentonite either in pellets or powder form. X-ray imaging has provided a means to extract grain information at the microscale and identify crack networks responsible for the pellets' heterogeneity. Regarding samples of pellets-powder mixtures under hydration, X-ray CT allowed the identification and monitoring of heterogeneous zones throughout the test. Some results showed how zones with pellets only swell faster compared to others composed of pellets and powder. Moreover, the behavior of fissures between grains and bentonite matrix was observed to change under drying and hydrating conditions, tending to close during the former and open during the latter. The development of specializing software has allowed obtaining strain fields from a sequence of images. In more recent works, X-ray CT technique has served to estimate the dry density, water content, and particle displacement at different testing times. Also, when temperature was added to the hydration process of a sample, CT technology offered a way to observe localized and global density changes over time.