• Journal of Korean Society for Geospatial Information Science
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• v.22 no.2
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• pp.17-24
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• 2014

This paper proposes an automatic extraction method of control point based on Geospatial Web Service. The proposed method consists of 3 steps. 1) The first step is to acquires reference data using the Geospatial Web Service. 2) The second step is to finds candidate control points in reference data and the target image by SURF algorithm. 3) By using RANSAC algorithm, the final step is to filters the correct matching points of candidate control points as final control points. By using the Geospatial Web Service, the proposed method increases operation convenience, and has the more extensible because of following the OGC Standard. The proposed method has been tested for SPOT-1, SPOT-5, IKONOS satellite images and has been used military standard data as reference data. The proposed method yielded a uniform accuracy under RMSE 5 pixel. The experimental results proved the capabilities of continuous improvement in accuracy depending on the resolution of target image, and showed the full potential of the proposed method for military purpose.

• Journal of Distribution Science
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• v.14 no.4
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• pp.5-11
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• 2016

Purpose - The Education Ministry has plans to select top 10 percent academic journals among the domestic registration journals in NRF(National Research Foundation of Korea), and designate them as outstanding academic journals. To reflect this trend, KODISA has set its sights on paper publication rate and citation index with pushing forward globalism. First, this study will arrange the process of globalism and the current state of paper submission, and propose the direction of improvement in academic journals through understanding the characteristics of each major field. Research design, data, and methodology - KODISA has preceeded in examining and publishing research papers related to distribution field through indirectly or stimulating academic advancement. KODISA covers the whole fields in social science as well as in business administration and economics that associated with distribution field not limiting only within the range of distribution field. That is, the new subject that contributes to the progress in distribution field with original research can be a priority criteria in KODISA journal publication. Results - The major fields in papers published in KODISA can be categorized broadly as distribution field with economic and business administration point of view. Therefore, the distribution field with economic point of view includes the issues such as regulations, system, industry, market environment, distribution system, trade, and macroeconomics, etc. The business administration point of view in distribution includes distribution strategy, distribution organization, and distribution channel from the perspectives of the firm, etc. Conclusions - The aim of KODISA in 2020 is to be a global academic journal as SCI level of each journal in KODISA, JDS(Registration journal), IJIDB(Registration candidate), EAJBM(Registration candidate), JAFEB(Cabell's Registration journal). The KODISA journals have already settled as the largest academic society and journals of Korea in 2016 currently from humanities and social sciences area by the most gross in publication circulation, volumes, and types. Hereafter, KODISA will focus on the improvement for the objective indicators such as Impact Factor and Centrality index as qualitative growth as well as quantitative expansion. By doing so, KODISA will be a forum for developmental academic debate with attracting the world's greatest scholars' papers. Furthermore, they will be recognized journals and grow as the first-rate academic journals inside and outside of Korea.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.135-142
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• 2020

In this paper, we describe the iris localization method in RGB images. Most of the iris localization methods are developed for infrared images, thus an iris localization method in RGB images is required for various applications. The proposed method consists of four stages: i) detection of the candidate irises using circular Hough transform (CHT) from an input image, ii) detection of a pupil center based on deep learning, iii) determine the iris using the pupil center, and iv) correction of the iris region. The candidate irises are detected in the order of the number of intersections of the center point candidates after generating the Hough space, and the iris in the candidates is determined based on the detected pupil center. Also, the error due to distortion of the iris shape is corrected by finding a new boundary point based on the detected iris center. In experiments, the proposed method has an improved accuracy about 27.4% compared to the CHT method.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.1-9
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• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.330-343
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• 2007

In this paper, we present a new surface content completion system that can effectively repair both shape and appearance from scanned, incomplete point set inputs. First, geometric holes can be robustly identified from noisy and defective data sets without the need for any normal or orientation information. The geometry and texture information of the holes can then be determined either automatically from the models' context, or manually from users' selection. After identifying the patch that most resembles each hole region, the geometry and texture information can be completed by warping the candidate region and gluing it onto the hole area. The displacement vector field for the exact alignment process is computed by solving a Poisson equation with boundary conditions. Out experiments show that the unified framework, founded upon the techniques of deformable models and PDE modeling, can provide a robust and elegant solution for content completion of defective, complex point surfaces.

• Journal of Power Electronics
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• v.14 no.4
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• pp.796-805
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• 2014

A digital controller with a low-power approach for point-of-load synchronous buck converters is discussed and compared with its analog counterpart to confirm its feasibility for system integration. The tri-mode digital controller IC in $0.35{\mu}m$ CMOS process is presented to demonstrate solutions that include a PID, quarter PID, and robust RST compensators. These compensators address the steady-state, stand-by, and transient modes according to the system operating point. An idle-tone free condition for ${\Sigma}-{\Delta}$ DPWM reduces the inherent tone noise under DC-excitation. Compared with that of the traditional approach, this condition generates a quasi-pure modulation signal. Experimental results verify the closed-loop performances and confirm the power-saving mechanism of the proposed controller.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.67.4-67.4
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• 2019

We present preliminary results of our long-term (2009-2017) observing campaign using the NASA IRTF at Mauna Kea, to obtain $2-5{\mu}m$ spectroscopy of ~200 red point sources in the line of sight to the Galactic center. Point sources in our sample were selected from the mid-infrared images of the Spitzer Space telescope, and include candidate massive young stellar objects, which have previously been identified from our Spitzer/IRS spectroscopy. We show high foreground extinction of these sources from deep $3.1{\mu}m$ H2O ice and aliphatic hydrocarbon absorption features, suggesting that they are likely located in the central 300 pc region of the Galactic center. While many sources reveal photospheric $2.3{\mu}m$ gas CO absorption, few of them clearly indicate $3.54{\mu}m$ CH3OH ice absorption, possibly indicating a large dust column density intrinsic to a massive young stellar object.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.209-220
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• 2012

In this paper, we propose an adaptive pavement region detection method that is robust to changes of structural patterns in a natural scene. In order to segment out a pavement reliably, we propose two step approaches. We first detect the borderline of a pavement and separate out the candidate region of a pavement using VRays. The VRays are straight lines starting from a vanishing point. They split out the candidate region that includes the pavement in a radial shape. Once the candidate region is found, we next employ the adaptive multi-seed region growing(A-MSRG) method within the candidate region. The A-MSRG method segments out the pavement region very accurately by growing seed regions. The number of seed regions are to be determined adaptively depending on the encountered situation. We prove the effectiveness of our approach by comparing its performance against the performances of seed region growing(SRG) approach and multi-seed region growing(MSRG) approach in terms of the false detection rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.657-667
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• 2012

In the MPR selection algorithm of Optimized Link State Routing (OLSR), each node selects own MPRs independently, so most of nodes are selected to MPR at least once. To cope with this problem, the MPR candidate selection algorithm was proposed. The MPR candidate selection algorithm can reduce the number of MPRs, but the efficiencies of route and connectivity decline due to decreased number of MPRs. So, in this paper, we propose the Significant Multi-Point Relay (S-MPR) selection algorithm which can enhance the performance of ad hoc network by improving the MPR selection algorithm of OLSR. In proposed S-MPR selection algorithm, each node selects the most important node to S-MPR to guarantee the connectivity then selects remaining MPRs in MPR candidates. So proposed S-MPR selection algorithm can reduce the overhead of many MPRs without decline of routing performance. To show the performance gain of proposed S-MPR selection algorithm, we simulate the proposed S-MPR selection algorithm by using OPNET.

• Journal of Animal Science and Technology
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• v.56 no.7
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• pp.23.1-23.7
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• 2014

Background: Scanning of the genome for selection signatures between breeds may play important role in understanding the underlie causes for observable phenotypic variations. The discovery of high density single nucleotide polymorphisms (SNPs) provide a useful starting point to perform genome-wide scan in pig populations in order to identify loci/candidate genes underlie phenotypic variation in pig breeds and facilitate genetic improvement programs. However, prior to this study genomic region under selection in commercially selected Berkshire and Korean native pig breeds has never been detected using high density SNP markers. To this end, we have genotyped 45 animals using Porcine SNP60 chip to detect selection signatures in the genome of the two breeds by using the $F_{ST}$ approach. Results: In the comparison of Berkshire and KNP breeds using the FDIST approach, a total of 1108 outlier loci (3.48%) were significantly different from zero at 99% confidence level with 870 of the outlier SNPs displaying high level of genetic differentiation ($F_{ST}{\geq}0.490$). The identified candidate genes were involved in a wide array of biological processes and molecular functions. Results revealed that 19 candidate genes were enriched in phosphate metabolism (GO: 0006796; ADCK1, ACYP1, CAMK2D, CDK13, CDK13, ERN1, GALK2, INPP1; MAK, MAP2K5, MAP3K1, MAPK14, P14KB, PIK3C3, PRKC1, PTPRK, RNASEL, THBS1, BRAF, VRK1). We have identified a set of candidate genes under selection and have known to be involved in growth, size and pork quality (CART, AGL, CF7L2, MAP2K5, DLK1, GLI3, CA3 and MC3R), ear morphology and size (HMGA2 and SOX5) stress response (ATF2, MSRB3, TMTC3 and SCAF8) and immune response (HCST and RYR1). Conclusions: Some of the genes may be used to facilitate genetic improvement programs. Our results also provide insights for better understanding of the process and influence of breed development on the pattern of genetic variations.