• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.299-310
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• 2009

In this paper, we proposed a new method to correct the zoom lens distortion for the video sequence captured by the zoom lens. First, we defined the nonlinear zoom lens distortion model which is represented by the focal length and the lens distortion using the characteristic that lens distortion parameters are nonlinearly and monotonically changed while the focal length is increased. Then, we chose some sample images from the video sequence and estimated a focal length and a lens distortion parameter for each sample image. Using these estimated parameters, we were able to optimize the zoom lens distortion model. Once the zoom lens distortion model was obtained, lens distortion parameters of other images were able to be computed as their focal lengths were input. The proposed method has been made experiments with many real images and videos. As a result, accurate distortion parameters were estimated from the zoom lens distortion model and distorted images were well corrected without any visual artifacts.

• Journal of the Korea Computer Graphics Society
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• v.23 no.5
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• pp.67-73
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• 2017

We propose several techniques which can be employed in a 3D fitness program for monitoring and correcting user's posture. To implement a 3D fitness program, improved reference motion generating techniques and visualizing techniques are necessary. First, in order to understand the difference between the user and the reference movement of a professional, a retargeting method between two different body shapes are studied. Second, the problem of self-occlusion, which occurs when using a low-cost depth sensor to represent complex motions, is solved by using a sample database and time consistency. The system proposed in this paper evaluates the user's posture considering the physical characteristics of the user, and then provides feedback to the user.

• Korean Journal of Applied Biomechanics
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• v.19 no.3
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• pp.567-580
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• 2009

The purpose of this study was to find out how the combined exercise program has an influence on the physical recovery of the patients suffering from work-related back problems. Research objects consist of 43 patients suffering from back problems due to workplace accidents. The result of the study shows that the combined exercise program increased muscular strength and endurance significantly and worked positively in lumbar recovery of the patients. It also increased the lowered flexibility caused by back pain to the level of normal state. In addition, the program was effective on the correction of the bad pose of body and scoliosis. Moreover, it helped improve on lifting, social life and reduce in the duration and the frequency of outbreak of pain. Finally, according to the result of this study, the combined exercise program was shown to be effective and appropriate for the patients suffering from work-related back problems.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.194-202
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• 2021

Ionosphere, one of the largest error sources, can pose potentially harmful threat to single-frequency GNSS (global navigation satellite system) user even after applying ionospheric corrections to their GNSS measurements. To quantitatively assess ionospheric impacts on the satellite navigation-based applications using simulation, the standard deviation of residual ionospheric errors is needed. Thus, in this paper, we determine conservative statistical quantity that covers typical residual ionospheric errors for nominal days. Extensive data-processing computes TEC (total electron content) estimates from GNSS measurements collected from the Korean reference station networks. We use Klobuchar model as a correction to calculate residual ionospheric errors from TEC (total electron content) estimate. Finally, an exponential delay model for residual ionospheric errors is presented as a function of local time and satellite elevation angle.

• Journal of Chest Surgery
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• v.57 no.4
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• pp.413-417
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• 2024

A 70-year-old man with dilated cardiomyopathy underwent left ventricular assist device (LVAD) implantation, using a HeartWare ventricular assist device, as a bridge to candidacy. After 26 months, computed tomography (CT) angiography indicated stenosis in the LVAD outflow graft; however, the patient was asymptomatic, prompting a decision to manage his condition with close monitoring. Ten months later, the patient presented with dizziness and low-flow alerts. Subsequent CT angiography revealed a critical obstruction involving the entire LVAD outflow graft. The patient underwent emergency surgery, during which an organized seroma causing the graft obstruction was found between a wrapped expanded polytetrafluoroethylene (ePTFE) graft and a Dacron outflow graft. The covering of the outflow graft was removed, along with the organized seroma. Following removal of the ePTFE wrap and decompression of the outflow graft, normal LVAD flow was reestablished. The practice of wrapping the outflow graft with synthetic material, commonly done to facilitate later redo sternotomy, may pose a risk for outflow graft obstruction.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.