• Journal of the Society of Naval Architects of Korea
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• v.42 no.2 s.140
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• pp.159-164
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• 2005

Monostatic RCS analysis of complex structures has been done with a combined method of physical and geometric optics, commonly applied to high frequency electromagnetic backscattering problems. In the analysis, the complex structure is modeled as a number of flat surfaces and the RCS of whole structure is calculated by summing RCS of each surface, which can be obtained from an analytical solution of flat surface phase integral derived from physical optics. The reflected and hidden surfaces are searched by an object precision method based on adaptive triangular beam method, which can take account for effects of multiple reflections and polarizations of electromagnetic wave. The validity of the presented RCS analysis method has been verified by comparing with exact solutions and measured data for various structures.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.5
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• pp.27-38
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• 2021

The physical condition assessment criteria of fill dam safety inspection are now weakly regulated and inappropriate for small agricultural reservoirs since these criteria have fundamental backgrounds suitable for large-scale dams. This study proposes the degree (critical values) of defects for the quantitative condition assessment of the embankment in order to prepare the condition assessment criteria for a small reservoir with a storage capacity of less than one (1) million cubic meters. The critical values of defects were calculated by applying the method that considers the size ratios based on the dimensional data of reservoirs, and the method of statistical analysis on the measured values of the defect degree which extracted from comprehensive annual reports on reservoir safety inspection. In comparison with the current criteria, the newly proposed critical values for each condition assessment item of the reservoir embankment are presented in paragraphs 4 and 6 of the conclusion. In addition, this study presents a method of displaying geometric figures to clarify the rating classification for condition assessment items with the two defect indicators.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.801-810
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• 2018

Diffusion is a random process used to model financial and physical phenomena. When we construct statistical models for repeatedly observed diffusion processes, the idea of random effects needs to be considered. In this research, we introduce random parameters for an Ornstein-Uhlenbeck diffusion model and geometric Brownian motion diffusion model. In order to apply the maximum likelihood estimation method, we tried to build likelihoods in closed-forms, by assuming appropriate distributions for random effects. We applied the random effect models to data consisting of Dow Jones Industrial Average indices recorded daily over 27 years from 1991 to 2017.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.71-79
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• 2019

Geolocation accuracy is one of the important factors in utilizing all weather available SAR satellite imagery. In this study, an error budget analysis was performed on key variables affecting on geolocation accuracy by generating KOMPSAT-5 simulation data. To perform the analysis, a Range-Doppler model was applied as a geometric model of the SAR imagery. The results show that the geolocation errors in satellite position and velocity are linearly related to the biases in the azimuth and range direction. With 0.03cm/s satellite velocity biases, the simulated errors were up to 0.054 pixels and 0.0047 pixels in the azimuth and range direction, and it implies that the geolocation accuracy is sensitive in the azimuth direction. Moreover, while the clock drift causes a geolocation error in the azimuth direction, a signal delay causes in the range direction. Monte-Carlo simulation analysis was performed to analyze the influence of multiple geometric error sources, and the simulated error was up to 3.02 pixels in the azimuth direction.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.5
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• pp.825-839
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• 2021

This study aims to develop jacquard fashion masks using traditional patterns and investigates the preference and emotions of consumers for them. Nine patterns were designed with the motifs of plum flower, turtle, and geometric patterns using an Adobe Illustrator program. After that, 20 kinds of jacquard fabrics were developed using those patterns, and prototype masks were made. Furthermore, data were collected using a survey of 231 adult consumers to understand the emotional images evoked by jacquard fashion masks with traditional patterns. The results of the research show that the emotional dimension derived from jacquard fashion masks with traditional patterns consists of seven factors: luxurious image, frugal image, feminine image, oriental image, sporty image, geometrical image, generous image. We found that consumers preferred the M6 with the plum flower pattern as the motif as the most preferred design, while M13 with the geometric pattern as the motif was the lowest preferred.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.103-114
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• 2024

The escalating demands for high-resolution satellite imagery necessitate the dissemination of geospatial data with superior accuracy.Achieving precise positioning is imperative for mitigating geometric distortions inherent in high-resolution satellite imagery. However, maintaining sub-pixel level accuracy poses significant challenges within the current technological landscape. This research introduces an approach wherein upsampling is employed on both the satellite image and ground control points (GCPs) chip, facilitating the establishment of a high-resolution satellite image precision sensor orientation. The ensuing analysis entails a comprehensive comparison of matching performance. To evaluate the proposed methodology, the Compact Advanced Satellite 500-1 (CAS500-1), boasting a resolution of 0.5 m, serves as the high-resolution satellite image. Correspondingly, GCP chips with resolutions of 0.25 m and 0.5 m are utilized for the South Korean and North Korean regions, respectively. Results from the experiment reveal that concurrent upsampling of satellite imagery and GCP chips enhances matching performance by up to 50% in comparison to the original resolution. Furthermore, the position error only improved with 2x upsampling. However,with 3x upsampling, the position error tended to increase. This study affirms that meticulous upsampling of high-resolution satellite imagery and GCP chips can yield sub-pixel-level positioning accuracy, thereby advancing the state-of-the-art in the field.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.323-332
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• 2012

An airborne LiDAR system performs several observations on flight routes to collect data of targeted regions accompanying with discrepancies between the collected data strips of adjacent routes. This paper aims to present an automatic error correction technique using modified ICP as a way to remove relative errors from the observed data of strip data between flight routes and to make absolute correction to the control data. A control point data from the existing digital topographic map were created and the modified ICP algorithm was applied to perform the absolute automated correction on the relatively adjusted airborne LiDAR data. Through such process we were able to improve the absolute accuracy between strips within the average point distance of airborne LiDAR data and verified the possibility of automation in the geometric corrections using a large scale digital map.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.129-138
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• 2022

Collecting and labeling sufficient training data, which is essential to deep learning-based visual inspection, is difficult for manufacturers to perform because it is very expensive. This paper presents a steel plate surface defect detection system with industrial-grade detection performance by training a small amount of steel plate surface images consisting of labeled and non-labeled data. To overcome the problem of lack of training data, we propose two data augmentation techniques: program-based augmentation, which generates defect images in a geometric way, and generative model-based augmentation, which learns the distribution of labeled data. We also propose a 4-step semi-supervised learning using pseudo labels and consistency training with fixed-size augmentation in order to utilize unlabeled data for training. The proposed technique obtained about 99% defect detection performance for four defect types by using 100 real images including labeled and unlabeled data.

• Journal of KIBIM
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• v.3 no.3
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• pp.19-28
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• 2013

In Korea highway bridges, most piers are the type of one-column or multi-column ones. So, in this study, under an environment applying BIM so fast, to activate researches on two-column piers subjected to bidirectional seismic loading, a 3D parametric modeling method was selected when the model of two-column piers and one-column piers were formed. Also, interface module between input data in structural analysis and 3D model of RC pier was developed. The module can create the input data for non-linear structural analysis like material, geometric properties and additional coefficients.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1583-1596
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• 2003

A study of forced convection in a circular pipe with a partially filled porous medium was numerically investigated. The Brinkman-Forchheimer extension of the Darcy model was used to analyze the and temperature distribution in the porous medium. Our study includes two types of porous layer configurations: (1) a layer attached at the tube wall extending inward towards the centerline and (2) a layer at the centerline extending outward. The effect of several parameters, such as Darcy number, effective viscosity, effective thermal conductivity, and inertia parameter, as well as the effect of geometric parameters, were investigated.