• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.246-251
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• 1998

This paper proposes a new building segmentation method from 1m resolution imagery using an Active Contour Model, known as "Balloons". The original balloons, which was designed by Cohen(Cohen, 1991) to extract features from medical images, are modified for building segmentation. The proposed method consists of two phases. Firstly, building boundaries are extracted by balloons with a given position on buildings from an operator. Since balloons actively adjust their shapes according to the boundaries, there is no more shape limitations on detecting buildings. Secondly, buildings are segmented by connecting the corners detected from the building boundaries, because most buildings, which are man-made objects, are effectively described by polygons. The test results show that most buildings are segmented efficiently and easily. The proposed method is new and timely as 1m resolution spaceborne imagery will be available in the very near future. The proposed method can be used fur operational building segmentation from such imagery.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2990-3002
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• 2021

The mechanical interaction between the fuel pellet and the cladding tube of a nuclear fuel rod is a very important for safety studies as this phenomenon could lead to fuel failure and release of radioactivity. To investigate the ductility of cladding tubes used in WWER type nuclear power plants, several mandrel tests were performed in the Centre for Energy Research (EK). This modified mandrel test was used to model the mechanical interaction between the fuel pellet and the cladding using a segmented tool. The tests were conducted at room temperature and at 300 ℃ with inactive as-received and hydrogenated cladding ring samples. The results show a gradual decrease in ductility as the hydrogen content increases, the ductile-brittle transition was seen above 1500 ppm hydrogen absorbed.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.468-475
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• 2020

In this paper, we proposed a three-dimensional visualization system for medical images in augmented reality based on deep learning. In the proposed system, the artificial neural network model performed fully automatic segmentation of the region of lung and pulmonary nodule from chest CT images. After applying the three-dimensional volume rendering method to the segmented images, it was visualized in augmented reality devices. As a result of the experiment, when nodules were present in the region of lung, it could be easily distinguished with the naked eye. Also, the location and shape of the lesions were intuitively confirmed. The evaluation was accomplished by comparing automated segmentation results of the test dataset to the manual segmented image. Through the evaluation of the segmentation model, we obtained the region of lung DSC (Dice Similarity Coefficient) of 98.77%, precision of 98.45%, recall of 99.10%. And the region of pulmonary nodule DSC of 91.88%, precision of 93.05%, recall of 90.94%. If this proposed system will be applied in medical fields such as medical practice and medical education, it is expected that it can contribute to custom organ modeling, lesion analysis, and surgical education and training of patients.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.333-342
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• 2022

In this paper, we perform a direct comparison study of real experimental data for domain rearrangement and the Cahn-Hilliard (CH) equation on the dynamics of morphological evolution. To validate a mathematical model for physical phenomena, we take initial conditions from experimental images by using an image segmentation technique. The image segmentation algorithm is based on the Mumford-Shah functional and the Allen-Cahn (AC) equation. The segmented phase-field profile is similar to the solution of the CH equation, that is, it has hyperbolic tangent profile across interfacial transition region. We use unconditionally stable schemes to solve the governing equations. As a test problem, we take domain rearrangement of lipid bilayers. Numerical results demonstrate that comparison of the evolutions with experimental data is a good benchmark test for validating a mathematical model.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.3
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• pp.19-32
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• 2020

Recently, the luxury brand market has expanded from the 5060 market to the 2030 market segment due to diversification of distribution channels, an increase in income, and changes in consumption values. This change is attributed to the increase in sales of fashion accessory products, such as bags and wallets, thereby confirming the importance of the luxury brand fashion accessories market. However, there are few studies of the luxury brand fashion accessories market or brand loyalty for fashion accessories, which accounts for a large proportion of the overall luxury brand market. The purpose of this study was to develop and empirically test a theoretical framework that captures and compares the difference of impact of service quality, product attributes, and consumer satisfaction on luxury brand loyalty between the 20-30 market and the 5060 market of the fashion accessories market. Data was collected from 598 customers who purchased luxury brand fashion accessories by objective sampling. Structural equation modelling was used to test the hypotheses developed for the study. Results found evident effects of consumer satisfaction on luxury brand loyalty through the perception of service quality by consumers. Additionally, in the 2030 market, the fashion accessory attributes had little impact on consumer satisfaction and luxury brand loyalty, whereas in the 5060 market, it had a significant impact only on consumer satisfaction, but not on luxury brand loyalty. This is the first study to examine a structural equation model of luxury brand loyalty to compare the difference of the model between segmented markets, such as the 2030 market and the 5060 market of the luxury brand fashion accessories market. These results will contribute to a better understanding of the mechanism that underlie the operation of an effective luxury branding strategy for fashion accessories.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.157-167
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• 2020

Fingerprinting method is useful when estimating the location of a requestor based on LTE signals in an urban area. To do this, it is necessary to acquire location-based signals everywhere in the service area for fingerprint DB generation in advance. However, there may be signal uncollected area within a wide service area, which may cause a problem that the positioning accuracy of the requestor is low. In order to solve this problem, in this paper, signal propagation modeling is performed based on the obtained measurements, and based on this model, the signal information in the non-acquisition region is estimated. To this end, techniques for modeling signal propagation according to a method using measurements are proposed. The performance of the proposed techniques is verified based on the measurements obtained on a test bed selected as Seocho-gu, Seoul. As a result, it can be seen that signal propagation modeling performed based on multidivision segmented measurements has the most performance improvement.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.519-521
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• 2003

Within the paper an approach for the automatic extraction and reconstruction of buildings in urban built-up areas base on fusion of high-resolution satellite image and LIDAR data is presented. The presented data fusion scheme is essentially motivated by the fact that image and range data are quite complementary. Raised urban objects are first segmented from the terrain surface in the LIDAR data by making use of the spectral signature derived from satellite image, afterwards building potential regions are initially detected in a hierarchical scheme. A novel 3D building reconstruction model is also presented based on the assumption that most buildings can be approximately decomposed into polyhedral patches. With the constraints of presented building model, 3D edges are used to generate the hypothesis and follow the verification processes and a subsequent logical processing of the primitive geometric patches leads to 3D reconstruction of buildings with good details of shape. The approach is applied on the test sites and shows a good performance, an evaluation is described as well in the paper.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.11
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• pp.1605-1614
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• 2002

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.5
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• pp.305-311
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• 2020

This study presents a probabilistic time series forecast of ship structural response using Bayesian inference combined with Volterra linear model. The structural response of a ship exposed to irregular wave excitation was represented by a linear Volterra model and unknown uncertainties were taken care by probability distribution of time series. To achieve the goal, Volterra series of first order was expanded to a linear combination of Laguerre functions and the probability distribution of Laguerre coefficients is estimated using the prepared data by treating Laguerre coefficients as random variables. In order to check the validity of the proposed methodology, it was applied to a linear oscillator model containing damping uncertainties, and also applied to model test data obtained by segmented hull model of 400,000 DWT VLOC as a practical problem.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.4
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• pp.217-223
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• 2013

This paper presents the wet damping estimation of the segmented hull model using the random decrement technique together with the continuous wavelet transform. The tested 16 sea states are grouped together based on the speed of the ship in order to figure out the possible influence of the ship speed on the damping ratio. The measured time histories of vertical bending moment for each tested sea state were processed with random decrement technique to derive the free decay signal, from which the damping ratios are estimated. Also, the autocorrelation functions of the filtered signal were calculated and comparison was made with the free decay signal obtained from the random decrement technique. Then the wet damping ratios for each sea state group, as well as precise wet natural frequencies, are estimated by using continuous wavelet transform. It turned out that the wet natural frequencies derived from the measured signal did not show any significant discrepancy compared with those obtained by wet hammering test, whereas the damping ratio did. It was considered that the discrepancy of the damping ratio between in calm and moving water may be attributed to the viscous effects caused by dramatically different flow pattern and relative velocity between the vibrating structure and surrounding fluid particles.