• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.167-177
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• 2022

In order to obtain satellite image products using the image transmitted to the ground station after capturing the satellite images, many image pre/post-processing steps are involved. During the pre/post-processing, when converting from level 1R images to level 1G images, geometric correction is essential. An interpolation method necessary for geometric correction is inevitably used, and the quality of the level 1G images is determined according to the accuracy of the interpolation method. Also, it is crucial to speed up the interpolation algorithm by the level processor. In this paper, we proposed a lightweight CNN-based interpolation method required for geometric correction when converting from level 1R to level 1G. The proposed method doubles the resolution of satellite images and constructs a deep learning network with a lightweight deep convolutional neural network for fast processing speed. In addition, a feature map fusion method capable of improving the image quality of multispectral (MS) bands using panchromatic (PAN) band information was proposed. The images obtained through the proposed interpolation method improved by about 0.4 dB for the PAN image and about 4.9 dB for the MS image in the quantitative peak signal-to-noise ratio (PSNR) index compared to the existing deep learning-based interpolation methods. In addition, it was confirmed that the time required to acquire an image that is twice the resolution of the 36,500×36,500 input image based on the PAN image size is improved by about 1.6 times compared to the existing deep learning-based interpolation method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.31-52
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• 2024

Considering the significant relationship between a tree's branch structure and physiology, understanding the detailed branch structure is crucial for fields such as species classification, and 3D tree modelling. Recently, terrestrial laser scanning (TLS) and quantitative structure model (QSM) have enhanced the understanding of branch structures by capturing the radius, length, and branching angle of branches. Previous studies examining branch structure with TL S and QSM often relied on mean or median of branch structure parameters, such as the radius ratio and length ratio in parent-child relationships, as representative values. Additionally, these studies have typically focused on the relationship between trunk and the first order branches. This study aims to explore the distribution of branch structure parameters up to the third order in Aesculus hippocastanum, Ginkgo biloba, and Prunus yedoensis. The gamma distribution best represented the distributions of branch structure parameters, as evidenced by the average of Kolmogorov-Smirnov statistics (radius = 0.048; length = 0.061; angle = 0.050). Comparisons of the mode, mean, and median were conducted to determine the most representative measure indicating the central tendency of branch structure parameters. The estimated distributions showed differences between the mode and mean (average of normalized differences for radius ratio = 11.2%; length ratio = 17.0%; branching angle = 8.2%), and between the mode and median (radius ratio = 7.5%; length ratio = 11.5%; branching angle = 5.5%). Comparisons of the estimated distributions across branch orders and species were conducted, showing variations across branch orders and species. This study suggests that examining the estimated distribution of the branch structure parameter offers a more detailed description of branch structure, capturing the central tendencies of branch structure parameters. We also emphasize the importance of examining higher branch orders to gain a comprehensive understanding of branch structure, highlighting the differences across branch orders.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.113-120
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• 2020

The multi-view video is a collection of multiple videos capturing the same scene at different viewpoints. Thus, there is an advantage of providing for user oriented view pointed video. This paper is suggested that the compression performance of layered depth image structure expression has improved by using more improved method. We confirm the data size of layer depth image by encoding H.264 technology and the each performances of reconstructed images. The H.264/AVC technology has easily extended for H.264 technology of video contents. In this paper, we suggested that layered depth structure can be applied for an efficient new image contents. We show that the huge data size of multi-view video image is decreased, and the higher performance of image is provided, and there is an advantage of for stressing error restoring.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.1-13
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• 2008

An efficient segregated algorithm for the coupling of velocity and pressure of incompressible fluid flow, called IDEAL Inner Doubly-Iterative Efficient Algorithm for Linked-Equations), has been proposed by the present authors. In the algorithm there exist double inner iterative processes for pressure equation at each iteration level, which almost completely overcome two approximations in SIMPLE algorithm. Thus the coupling between velocity and pressure is fully guaranteed, greatly enhancing the convergence rate and stability of solution process. The performance of the IDEAL algorithm for three-dimensional incompressible fluid flow and heat transfer problems is analyzed and a systemic comparison is made between the algorithm and three other most widely-used algorithms (SIMPLER, SIMPLEC and PISO). It is found that the IDEAL algorithm is the most robust and the most efficient one among the four algorithms compared. This new algorithm is used for the velocity prediction of a new interface capturing method. VOSET, also proposed by the present author. It is found that the combination of VOSET and IDEAL can appreciably enhance both the interface capture accuracy and convergence rate of computations.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.1-13
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• 2008

An efficient segregated algorithm for the coupling of velocity and pressure of incompressible fluid flow, called IDEAL (Inner Doubly-Iterative Efficient Algorithm for Linked-Equations), has been proposed by the present authors. In the algorithm there exist double inner iterative processes for pressure equation at each iteration level, which almost completely overcome two approximations in SIMPLE algorithm. Thus the coupling between velocity and pressure is fully guaranteed, greatly enhancing the convergence rate and stability of solution process. The performance of the IDEAL algorithm for three-dimensional incompressible fluid flow and heat transfer problems is analyzed and a systemic comparison is made between the algorithm and three other most widely-used algorithms (SIMPLER, SIMPLEC and PISO). It is found that the IDEAL algorithm is the most robust and the most efficient one among the four algorithms compared. This new algorithm is used for the velocity prediction of a new interface capturing method -VOSET, also proposed by the present author. It is found that the combination of VOSET and IDEAL can appreciably enhance both the interface capture accuracy and convergence rate of computations.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1029-1035
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• 2013

This paper proposes a real time lane detection algorithm using LRF (Laser Range Finder) for autonomous navigation of a mobile robot. There are many technologies for safety of the vehicles such as airbags, ABS, EPS etc. The real time lane detection is a fundamental requirement for an automobile system that utilizes outside information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. By the vision-based system, recognition of environment for three dimensional space becomes excellent only in good conditions for capturing images. However there are so many unexpected barriers such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement. In this paper, we introduce a three dimensional lane detection algorithm using LRF, which is very robust against the illumination. For the three dimensional lane detections, the laser reflection difference between the asphalt and lane according to the color and distance has been utilized with the extraction of feature points. Also a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been verified through the real experiments.

• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.125-145
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• 2011

Pushover analysis has gained significant popularity as an analytical tool for realistic determination of the inelastic behaviour of RC structures. Though significant work has been done to evaluate the demands realistically, the evaluation of capacity and realistic failure modes has taken a back seat. In order to throw light on the inelastic behaviour and capacity evaluation for the RC framed structures, a 3D Reinforced concrete frame structure was tested under monotonically increasing lateral pushover loads, in a parabolic pattern, till failure. The structure consisted of three storeys and had 2 bays along the two orthogonal directions. The structure was gradually pushed in small increments of load and the corresponding displacements were monitored continuously, leading to a pushover curve for the structure as a result of the test along with other relevant information such as strains on reinforcement bars at critical locations, failure modes etc. The major failure modes were observed as flexural failure of beams and columns, torsional failure of transverse beams and joint shear failure. The analysis of the structure was by considering all these failure modes. In order to have a comparison, the analysis was performed as three different cases. In one case, only the flexural hinges were modelled for critical locations in beams and columns; in second the torsional hinges for transverse beams were included in the analysis and in the third case, joint shear hinges were also included in the analysis. It is shown that modelling and capturing all the failure modes is practically possible and such an analysis can provide the realistic insight into the behaviour of the structure.

• Applied Microscopy
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• v.39 no.1
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• pp.57-64
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• 2009

The trapping leaves of Drosera capture insects by secreting sticky mucilage from numerous glandular trichomes (GTs) that are developed on the leaf epidermis. The present study examines and compares the structural features of those trichomes in Drosera binata and D. pygmy with the use of light and electron microscopy. The study focuses primarily on the development and differentiation pattern of the GTs during growth. Upon examination, the upper and lower epidermis were readily distinguishable by the features of GTs in developing leaves. In particular, the GTs were dense in the upper epidermis and along the leaf margin. In D. binata, the capitate GTs with elongated stalk and sessile peltate GTs were found most commonly, whereas only capitate GTs with varying degrees of the stalk length were observed in D. pygmy. Up to ca. $2.2{\sim}3.4\;mm$ long capitate GTs were seen in the leaf margins of D. binata and ca. $3.7{\sim}4.2\;mm$ long GTs having racket-like head with adaxial hemispheric structures, otherwise known as tentacles, were noted in the leaf margin of D. pygmy. The peltate GTs were found to be distributed in the lower epidermis of D. binata. In both species, head cells were dense with cytoplasm containing high numbers of Golgi bodies, ER, mitochondria and small vesicles. Secretory materials accumulated within numerous small vacuoles, then fused together to form a single large vacuole, which serves as a secretory cavity. Flection movement of the marginal GTs and leaf blade GTs, and increased mucilage secretion from the head cells upon contact with prey during the capturing process are considered to be major factors in their active insectivorous mechanism. The findings of this study will be useful in comparisons to similar findings in other species that form adhesive trapping leaves, such as Drosophyllum or Pinguicula., further contributing a better understanding of the function and structure of the trapping leaves of carnivorous plants.

• Journal of the HCI Society of Korea
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• v.13 no.4
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• pp.5-14
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• 2018

The Empathy for Dementia using Virtual Reality (EDuVR) system, developed by the Jeju Provincial Dementia Center, is a 3D video system capturing the experience of dementia in a first-person perspective using 360 degree vritual reality (VR) technology. It was developed to create a greater understanding of dementia and to help people empathize with individuals with dementia through an immersive VR experience. The EDuVR shows how a dementia patient has impairments in memory, orientation, language, judgment and problem solving, as well as problems with activities of daily living. The present study reported the effectiveness of the EDuVR experience in changing public awareness of, and attitude toward, dementia. Sixty-six participants were assigned to the EDuVR (n = 34) or the conventional education (n = 32) groups, and two types of questionnaires - attitude and awareness questionnaires - were administered to the subjects before and after the EDuVR experience or education. The simulator sickness and presence questionnaires were administered to the EDuVR group to assess cybersickness and presence of the VR experience. As a results, the attitude and awareness toward dementia patients changed positively in both the EDuVR and the conventional education groups, and these changes did not differ between two groups. Only one person reported a significant level of cybersicness after experiencing the EDuVR system. These results suggest that the EDuVR enhances the level of understanding and empathy for dementia and would be a useful tool for improving awareness in the general public.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.12
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• pp.1690-1695
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• 2001

Wheat straw was treated on laboratory scale with 4% urea at a moisture level of 50% along with different amounts of acetic acid (AA) to fix various levels of ammonia nitrogen (15, 30, 45 and 60%) evolved from urea and stored for 4 weeks. Chemical composition of the treated samples revealed a significant (p<0.01) increase in N content of the samples where AA was added. The N content of the ammoniated straw was only 1.21% which increased to 2.58 with the addition of AA to trap 30% $NH_3-N$. The concentration of free $NH_3-N$ in the straw was significantly (p<0.01) less when more than 15% $NH_3-N$ was trapped with AA. There was significant increase (p<0.01) in N disappearance and depression in NDF and hemicellulose disappearance, when AA was used to trap 30% $NH_3-N$. Large scale treatment of wheat straw with 4% urea at a moisture level of 50% along with AA (to trap 30% $NH_3-N$) increased the N content, but not as much as in laboratory scale treatment. In vivo experiment conducted on nine adult male buffaloes divided into three groups revealed no difference in the intake of DM, OM, NDF, ADF, cellulose and hemicellulose among group I (ammoniated straw), group II (AA treated ammoniated straw) and group III (AA treated ammoniated straw +1 kg barley grain), but the intake was significantly (p<0.05) more in groups where AA treated straw was fed as compared to only ammoniated straw fed group. However EE digestibility was depressed in group II. The digestibility of cellulose and hemicellulose both depressed significantly (p<0.05) in group II and III as compared to group I. Animals in all the 3 groups showed positive nitrogen balance and it was significantly more in group II and III as compared to group I. DCP intake was significantly (p<0.05) more in group II and III as compared to group I, but there was no significant difference among the three groups in TDN intake. It can be concluded that AA (to trap 30% $NH_3-N$) is effective in capturing the excess ammonia released during urea ammoniation of straw and improving its nutritive value, as well as animal performance.