• Economic and Environmental Geology
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• v.53 no.5
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• pp.597-608
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• 2020

Even after the Gyeongju earthquake and the Pohang earthquake, hundreds of aftershocks and micro-earthquakes are still occurring in the southeastern part of the Korean Peninsula. These phenomena mean that the stress is constantly working, implying that another huge earthquake may occur in the future. Therefore, the gravity field interpretation method was used to analyze the deep geological structure of the Pohang-Ulsan region in the southeastern Korean Peninsula. First, a gravity survey was performed to collect the insufficient data and to calculate the detailed Bouguer gravity anomaly in the study area. Based on the gravity anomaly data, the location, direction, and maximum depth of deep fault lines were analyzed using the inversion methods "Curvature analysis" and "Euler deconvolution method". As a result, it is interpreted that at least six fault lines(C1~C6) exist in deep depth. The deep fault line C1 is well correlated to the Yeonil Tectonic Line(YTL), suggesting that YTL is extended up to about 4000m deep. The deep fault line C2 consists of several segment faults and well correlated to the fault lines on the surface. Inferred fault lines C3, C4, and C5 have an NW-SE direction, which is parallel to the Ulsan fault. The deep fault line C6 has the direction of NE-SW, and it is interpreted that the eastern boundary fault of Eoil Basin is extended to the deep. Comparing the inferred fault lines with the distribution of micro-earthquakes, the location of the deep fault line C1 is well correlated to the hypocenter of micro-earthquakes. This implies that faults in deep depth are related to the recent earthquakes in the southeastern Korean Peninsula.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.341-346
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• 2009

The motion data glove is a representative human-computer interaction tool that inputs human hand gestures to computers by measuring their motions. The motion data glove is essential equipment used for new computer technologiesincluding home automation, virtual reality, biometrics, motion capture. For its popular usage, this paper attempts to develop an inexpensive visual.type motion data glove that can be used without any special equipment. The proposed approach has the special feature; it can be developed as a low-cost one becauseof not using high-cost motion-sensing fibers that were used in the conventional approaches. That makes its easy production and popular use possible. This approach adopts a visual method that is obtained by improving conventional optic motion capture technology, instead of mechanical method using motion-sensing fibers. Compared to conventional visual methods, the proposed method has the following advantages and originalities Firstly, conventional visual methods use many cameras and equipments to reconstruct 3D pose with eliminating occlusions But the proposed method adopts a mono vision approachthat makes simple and low cost equipments possible. Secondly, conventional mono vision methods have difficulty in reconstructing 3D pose of occluded parts in images because they have weak points about occlusions. But the proposed approach can reconstruct occluded parts in images by using originally designed thin-bar-shaped optic indicators. Thirdly, many cases of conventional methods use nonlinear numerical computation image analysis algorithm, so they have inconvenience about their initialization and computation times. But the proposed method improves these inconveniences by using a closed-form image analysis algorithm that is obtained from original formulation. Fourthly, many cases of conventional closed-form algorithms use approximations in their formulations processes, so they have disadvantages of low accuracy and confined applications due to singularities. But the proposed method improves these disadvantages by original formulation techniques where a closed-form algorithm is derived by using exponential-form twist coordinates, instead of using approximations or local parameterizations such as Euler angels.