• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.513-524
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• 2022

Recently, detecting damages of civil infrastructures from digital images using deep learning technology became a very popular research topic. In order to adapt those methodologies to the field, it is essential to explain robustness of deep learning models. Our research points out that the existing pixel-based deep learning model evaluation metrics are not sufficient for detecting cracks since cracks have linear appearance, and proposes a new evaluation methodology to explain crack segmentation deep learning model more rationally. Specifically, we design, implement and validate a methodology to generate tolerance buffer alongside skeletonized ground truth data and prediction results to consider overall similarity of topology of the ground truth and the prediction rather than pixel-wise accuracy. We could overcome over-estimation or under-estimation problem of crack segmentation model evaluation through using our methodology, and we expect that our methodology can explain crack segmentation deep learning models better.

• Tunnel and Underground Space
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• v.13 no.6
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• pp.486-494
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• 2003

When the orientations of joints are measured on a rock exposure, there are frequent cases that are difficult to approach by the surveyor to the target joints or to set up scanlines on the slope. In this study, to complement such limit and weak points, a new algorithm was developed to interpret joint orientation from analyzing the images of rock slope. As a method of arranging the multiple images of a rock slope, the multistage convergent photographing system was introduced to overcome the limitation of photographing direction which existing method such as parallel stereophotogrammetric system has and to cover the range of image measurement, which is the overlapping area between the image pair, to a maximum extent. To determine camera parameters in the perspective projection equation that are the main elements of the analysis method, a new method was developed introducing three ground control points and single ground guide point. This method could be considered to be very simple compared with other existing methods using a number of ground control points and complicated analysis process. So the global coordinates of a specific point on a rock slope could be analyzed with this new method. The orientation of a joint could be calculated using the normal vector of the joint surface which can be derived from the global coordinates of several points on the joint surface analyzed from the images.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.46-55
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• 2015

A water tube with detonating cord was devised to control the blast dust. Water diffusion experiments with different detonating cord positions were conducted during the series of experiments to optimize the design parameters of the tube. Images from high speed camera were analyzed to evaluate the results. AUTODYN program was adopted to simulate the diffusion process of water and compared with the images. Diffusion of water shows cross flow in case of external charge while the internal case shows radial flow. A bubble ring was formed during the numerical analysis of internal charge case as occurred in underwater blast. An additional bubble ring was formed by the reflection pressure from the ground. And the Weber number was determined as sufficient for spray atomization performance of the water tube.

• Tunnel and Underground Space
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• v.24 no.1
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• pp.55-66
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• 2014

In this study, a joint survey system was developed to efficiently analyze geometrical characteristics of joint structures in rock mass using photogrammetric technique. The system includes both hardware and software. The hardware consists of a high resolution image camera for photographing image of a surface of rock body, a direction controlling system for adjusting the attitude of camera, and a digital compass for measuring the rotation angle of camera. The software was also developed in order to analyze the orientation, density, mean length of joints revealed on the images of rock surfaces. The software developed in this study was named as JointeXtractor. As applying this system into several field measurements, the orientation, density, mean length of joints could be quantitatively measured through analyzing the images of rock surfaces, in which the case of a difficult-to-access area was especially included for the test of the system.

• Tunnel and Underground Space
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• v.25 no.6
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• pp.527-533
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• 2015

This study performed an on-site demonstration of the topographic surveying technique at a large-scale open-pit limestone mine in Korea using a fixed-wing unmanned aerial vehicle (UAV, Drone, SenseFly eBee). 288 sheets of aerial photos were taken by an automatic flight for 30 minutes under conditions of 300 m altitude and 12 m/s speed. Except for 37 aerial photos in which no keypoint was detected, 251 aerial photos were utilized for data processing including correction and matching, then an orthomosaic image and digital surface model with 7 cm grid spacing could be generated. A comparison of the X, Y, Z-coordinates of 4 ground control points measured by differential global positioning system and those determined by fixed-wing UAV photogrammetry revealed that the root mean squared errors were around 15 cm. Because the fixed-wing UAV has relatively longer flight time and larger coverage area than rotary-wing UAVs, it can be effectively utilized in large-scale open-pit mines as a topographic surveying tool.

• Journal of the Korean Geotechnical Society
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• v.34 no.12
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• pp.145-154
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• 2018

The damage investigation and inspection methods performed in concrete facilities such as bridges, tunnels, retaining walls and so on, are usually visually examined by the inspector using the surveying tool in the field. These methods highly depend on the subjectivity of the inspector, which may reduce the objectivity and reliability of the record. Therefore, the new image processing techniques are necessary in order to automatically detect the cracks and objectively analyze the characteristics of cracks. In this study, deep learning and image processing technique were developed to detect cracks and analyze characteristics in images for concrete facilities. Two-stage image processing pipeline was proposed to obtain crack segmentation and its characteristics. The performance of the method was tested using various crack images with a label and the results showed over 90% of accuracy on crack classification and segmentation. Finally, the crack characteristics (length and thickness) of the crack image pictured from the field were analyzed, and the performance of the developed technique was verified by comparing the actual measured values and errors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.67-77
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• 2022

An automatic freeway bus-only lane enforcement system was developed and assessed in a real-world environment. Observation of a bus-only lane on the Youngdong freeway, South Korea, revealed that approximately 99% of the vehicles violated the high-occupancy vehicle (HOV) lane regulation. However, the current enforcement by the police not only exhibits a low enforcement rate, but also induces unnecessary safety and delay concerns. Since vehicles with six passengers or higher are permitted to enter freeway bus-only lanes, identifying the number of passengers in a vehicle is a core technology required for a freeway bus-only lane enforcement system. To that end, infrared cameras and the You Only Look Once (YOLOv5) deep learning algorithm were utilized. For assessment of the performance of the developed system, two environments, including a controlled test-bed and a real-world freeway, were used. As a result, the performances under the test-bed and the real-world environments exhibited 7% and 8% errors, respectively, indicating satisfactory outcomes. The developed system would contribute to an efficient freeway bus-only lane operations as well as eliminate safety and delay concerns caused by the current manual enforcement procedures.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.7-17
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• 2011

We have developed an inversion code for three-dimensional (3D) resistivity tomography including the anisotropy effect. The algorithm is based on the finite element approximations for the forward modelling and Active Constraint Balancing method is adopted to enhance the resolving power of the smoothness constraint least-squares inversion. Using numerical experiments, we have shown that anisotropic inversion is viable to get an accurate image of the subsurface when the subsurface shows strong electrical anisotropy. Moreover, anisotropy can be used as additional information in the interpretation of subsurface. This algorithm was also applied to the field dataset acquired in the abandoned old mine area, where a high-rise apartment block has been built up over a mining tunnel. The main purpose of the investigation was to evaluate the safety analysis of the building due to old mining activities. Strong electrical anisotropy has been observed and it was proven to be caused by geological setting of the site. To handle the anisotropy problem, field data were inverted by a 3D anisotropic tomography algorithm and we could obtain 3D subsurface images, which matches well with geology mapping observations. The inversion results have been used to provide the subsurface model for the safety analysis in rock engineering and we could assure the residents that the apartment has no problem in its safety after the completion of investigation works.

• Journal of computational fluids engineering
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• v.15 no.3
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• pp.39-45
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• 2010

The turbulent flows in a tunnel mock-up($10L{\times}0.5W{\times}0.25H$ m3 : scale reduction 1/20) with rectangular cross section were investigated. The instantaneous velocity fields of Re = 49,029, 89,571 were measured by the 2-D PIV system which is consisted of double pulsed Nd:Yag laser and the tracer particles in the straight-duct mock-up where the flows were fully developed. The mean velocity profiles were taken from the ensemble averages of 1,000 instantaneous velocity fields. Simultaneously, numerical simulations(RANS) were performed to compare with experimental data using STREAM code. Non-linear eddy viscosity model (NLEVM : Abe-Jang-Leschziner Eddy Viscosity Model) was employed to resolve the turbulent flows in the duct. The calculated mean velocity profiles were well compared with PIV results. In the log-law profiles, the experimental data were in good agreement with numerical simulations all the way to the wake region except the viscous sub-layer (near wall region).

• Annals of Clinical Neurophysiology
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• v.13 no.2
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• pp.87-92
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• 2011

Background: Tarsal tunnel syndrome (TTS) is an entrapment neuropathy that occurs in the ankle. Previous studies reported that this disease was due to physiologic factors and structural lesions in the ankle or foot. The authors investigated the causative factors of TTS and their frequency via operative findings. The diagnostic value of MRI was also evaluated based on the concordance between the operative findings and the MRI findings. Methods: This study was performed in retrospective by using medical record of the patients who underwent operations with TTS from August 2003 to May 2010. Physical examination, nerve conduction study, and MRI were conducted on patients who visited department of neurology or orthopedic surgery due to pain and sensory abnormality of their ankle and foot. Results: 34 patients underwent the operation. Ganglion accounted for the largest portion of the operative findings. In addition, varicose veins, intrinsic foot muscle hypertrophy, tenosynovitis, and fascia thickening were mainly observed. Of the 34 patients, 33 patients underwent pre-operative MRI, of whom 18 patients showed MRI findings consistent with the operative findings. Conclusions: Space-occupying lesions accounted for the majority of the causative factors in TTS patients who underwent the surgical treatment. In this study, the MRI appeared useful for identifying causes of TTS.