• Journal of the Korean Society of Radiology
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• v.8 no.7
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• pp.435-441
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• 2014

This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the RGB image compression rate and image quality, such as gray-level images and showed good.

• Journal of the Korean Society of Radiology
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• v.10 no.4
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• pp.263-270
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• 2016

This paper suggests techniques to enhance coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, There applied to 24-bpp color image compression and image techniques. The result did not occur a loss in the image quality of the image when using the encoding method, such as almost to the color in the YIQ image compression rate and image quality, such as RGB images and showed good.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.413-423
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• 2022

The purpose of this study is to analyze the role of the job competency assessor who assess achievement of job performance ability based on NCS (educational training, qualifications, field experience, etc.) through competency assessment. For this purpose, job analysis including development and verification of the job model and selection of core task are conducted. As a result, main duties of the job competency assessor are to understand the NCS based assessment principle, establish an assessment plan, design and develop assessment tools, assess competence, provide feedback and re-assessment, record and manage assessment result, verify the internal assessment result, establish the RPL (recognition of prior learning) plan, implement the RPL and verify the RPL assessment result, and 48 task are derived. In addition, a total of 21 core tasks are derived based on the threshold value multiplied by the importance and difficulty of the task for each duty. Based on this, implications for job analysis of the job competency assessor are presented.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.104-113
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• 2014

The existing rough mode decision (RMD) algorithm, used in HEVC standard loses the coding efficiency and wastes encoding time when encoding using transform skip mode (TSM) because the RMD algorithm in HEVC uses a selection method that is designed for DCT, not for TSM. This paper proposes a new RMD algorithm for TSM in HEVC. Our proposed RMD algorithm enhances the coding efficiency by employing a new cost function to increase the probability of selecting the best intra prediction mode for TSM. In addition, it reduces the encoding time by skipping the encoding process of least feasible TSM based on a newly proposed threshold value. The experiment results show that the proposed method achieves coding gains of -0.3% for screen contents with a 10% reduction in encoding time compared to those of the HEVC standard.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.547-557
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• 2017

In this paper, a new spectral unmixing based target detection algorithm is proposed which adopted Iterative Error Analysis as a tool for extraction of background endmembers by using the target spectrum to be detected as initial endmember. In the presented method, the number of background endmembers is automatically decided during the IEA by stopping the iteration when the maximum change in abundance of the target is less than a given threshold value. The proposed algorithm does not have the dependence on the selection of image endmembers in the model-based approaches such as Orthogonal Subspace Projection and the target influence on the background statistics in the stochastic approaches such as Matched Filter. The experimental result with hyperspectral image data where various real and simulated targets are implanted shows that the proposed method is very effective for the detection of both rare and non-rare targets. It is expected that the proposed method can be effectively used for mineral detection and mapping as well as target object detection.

• The KIPS Transactions:PartC
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• v.17C no.5
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• pp.399-406
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• 2010

Many problems are arisen due to the weakness in the security and invasion to privacy by malicious attacker or internal users while various data services are available in ubiquitous network environment. The matter of controlling security for various contents and large capacity of data has appeared as an important issue to solve this problem. The allocation methods of Ito, Saito and Nishizeki based on traditional polynomial require all shares to restore the secret information shared. On the contrary, the secret information can be restored if the shares beyond the threshold value is collected. In addition, it has the effect of distributed DBMS operation which distributes and restores the data, especially the flexibility in realization by using parameters t,v,k in combinatorial design which has regularity in DB server and share selection. This paper discuss the construction of new share allocation method and data distribution/storage management with the application of matrix structure of t-(v,k,1) design for allocating share when using secret sharing in management scheme to solve the matter of allocating share.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.610-622
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• 2008

Moving object segmentation is an essential technique for various video surveillance applications. The result of moving object segmentation often contains shadow regions caused by the color difference of shadow pixels. Hence, moving object segmentation is usually followed by a shadow elimination process to remove the false detection results. The common assumption adopted in previous works is that, under the illumination variation, the value of chromaticity components are preserved while the value of intensity component is changed. Hence, color transforms which separates luminance component and chromaticity component are usually utilized to remove shadow pixels. In this paper, various color spaces (YCbCr, HSI, normalized rgb, Yxy, Lab, c1c2c3) are examined to find the most appropriate color space for shadow elimination. So far, there have been some research efforts to compare the influence of various color spaces for shadow elimination. However, previous efforts are somewhat insufficient to compare the color distortions under illumination change in diverse color spaces, since they used a specific shadow elimination scheme or different thresholds for different color spaces. In this paper, to relieve the limitations of previous works, (1) the amount of gradients in shadow boundaries drawn to uniform colored regions are examined only for chromaticity components to compare the color distortion under illumination change and (2) the accuracy of background subtraction are analyzed via RoC curves to compare different color spaces without the problem of threshold level selection. Through experiments on real video sequences, YCbCr and normalized rgb color spaces showed good results for shadow elimination among various color spaces used for the experiments.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.4
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• pp.223-237
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• 2011

The intermittent freshwater discharge has an critical influence upon the biophysical environments and the ecosystems of the Yeongsan Estuary where the estuary dam altered the continuous mixing of saltwater and freshwater. Though freshwater discharge is controlled by human, the extreme events are mainly driven by the heavy rainfall in the river basin, and provide various impacts, depending on its magnitude and frequency. This research aims to evaluate the magnitude and frequency of extreme freshwater discharges, and to establish the magnitude-frequency relationships between basin-wide rainfall and freshwater inflow. Daily discharge and daily basin-averaged rainfall from Jan 1, 1997 to Aug 31, 2010 were used to determine the relations between discharge and rainfall. Consecutive daily discharges were grouped into independent events using well-defined event-separation algorithm. Partial duration series were extracted to obtain the proper probability distribution function for extreme discharges and corresponding rainfall events. Extreme discharge events over the threshold 133,656,000 $m^3$ count up to 46 for 13.7y years, following the Weibull distribution with k=1.4. The 3-day accumulated rain-falls which occurred one day before peak discharges (1day-before-3day -sum rainfall), are determined as a control variable for discharge, because their magnitude is best correlated with that of the extreme discharge events. The minimum value of the corresponding 1day-before-3day-sum rainfall, 50.98mm is initially set to a threshold for the selection of discharge-inducing rainfall cases. The number of 1day-before-3day-sum rainfall groups after selection, however, exceeds that of the extreme discharge events. The canonical discriminant analysis indicates that water level over target level (-1.35 m EL.) can be useful to divide the 1day-before-3day-sum rainfall groups into discharge-induced and non-discharge ones. It also shows that the newly-set threshold, 104mm, can just separate these two cases without errors. The magnitude-frequency relationships between rainfall and discharge are established with the newly-selected lday-before-3day-sum rainfalls: $D=1.111{\times}10^8+1.677{\times}10^6{\overline{r_{3day}}$, (${\overline{r_{3day}}{\geqq}104$, $R^2=0.459$), $T_d=1.326T^{0.683}_{r3}$, $T_d=0.117{\exp}[0.0155{\overline{r_{3day}}]$, where D is the quantity of discharge, ${\overline{r_{3day}}$ the 1day-before-3day-sum rainfall, $T_{r3}$ and $T_d$, are respectively return periods of 1day-before-3day-sum rainfall and freshwater discharge. These relations provide the framework to evaluate the effect of freshwater discharge on estuarine flow structure, water quality, responses of ecosystems from the perspective of magnitude and frequency.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.4
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• pp.417-424
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• 2010

The purpose of this study was to detect significant SNPs for carcass quality traits using DNA chips of high SNP density in Hanwoo populations. Carcass data of two hundred and eighty nine steers sired by 30 Korean proven sires were collected from two regions; the Hanwoo Improvement Center of National Agricultural Cooperative Federation in Seosan, Chungnam province and the commercial farms in Gyeongbuk province. The steers in Seosan were born between spring and fall of 2006 and those in Gyeonbuk between falls of 2004 and 2005. The former steers were slaughtered at approximately 24 months, while the latter steers were fed six months longer before slaughter. Among the 55,074 SNPs in the Illumina bovine 50K chip, a total of 32,756 available SNPs were selected for whole genome association study. After adjusting for the effects of sire, region and slaughter age, phenotypes were regressed on each SNP using a simple linear regression model. For the significance threshold, 0.1% point-wise p value from F distribution was used for each SNP test. Among the significant SNPs for a trait, the best set of SNP markers were selected using a stepwise regression procedure, and inclusion and exclusion of each SNP out of the model was determined at the p<0.001 level. A total of 118 SNPs were detected; 15, 20, 22, 28, 20, and 13 SNPs for final weight before slaughter, carcass weight, backfat thickness, weight index, longissimus dorsi muscle area, and marbling score, respectively. Among the significant SNPs, the best set of 44 SNPs was determined by stepwise regression procedures with 7, 9, 6, 9, 7, and 6 SNPs for the respective traits. Each set of SNPs per trait explained 20-40% of phenotypic variance. The number of detected SNPs per trait was not great in whole genome association tests, suggesting additional phenotype and genotype data are required to get more power to detect the trait-related SNPs with high accuracy for estimation of the SNP effect. These SNP markers could be applied to commercial Hanwoo populations via marker-assisted selection to verify the SNP effects and to improve genetic potentials in successive generations of the Hanwoo populations.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1332-1344
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• 2004

Upon development of information super-highway and multimedia-related technoiogies in recent years, more efficient technologies to transmit, store and retrieve the multimedia data are required. Among such technologies, firstly, it is common that the semantic-based image retrieval is annotated separately in order to give certain meanings to the image data and the low-level property information that include information about color, texture, and shape Despite the fact that the semantic-based information retrieval has been made by utilizing such vocabulary dictionary as the key words that given, however it brings about a problem that has not yet freed from the limit of the existing keyword-based text information retrieval. The second problem is that it reveals a decreased retrieval performance in the content-based image retrieval system, and is difficult to separate the object from the image that has complex background, and also is difficult to extract an area due to excessive division of those regions. Further, it is difficult to separate the objects from the image that possesses multiple objects in complex scene. To solve the problems, in this paper, I established a content-based retrieval system that can be processed in 5 different steps. The most critical process of those 5 steps is that among RGB images, the one that has the largest and the smallest background are to be extracted. Particularly. I propose the method that extracts the subject as well as the background by using an Image, which has the largest background. Also, to solve the second problem, I propose the method in which multiple objects are separated using RGB channel selection techniques having optimized the excessive division of area by utilizing Watermerge's threshold value with the object separation using the method of RGB channels separation. The tests proved that the methods proposed by me were superior to the existing methods in terms of retrieval performances insomuch as to replace those methods that developed for the purpose of retrieving those complex objects that used to be difficult to retrieve up until now.