• Asian-Australasian Journal of Animal Sciences
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• v.24 no.11
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• pp.1525-1528
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• 2011

The purpose of this study was to detect SNPs that were responsible for a carcass trait in Hanwoo populations. A non-parametric model applying a restricted partition method (RPM) was used, which exploited a partitioning algorithm considering statistical criteria for multiple comparison testing. Phenotypic and genotypic data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, in which the pedigree structure comprised 229 steers from 16 paternal half-sib proven sires that were born in Namwon or Daegwanryong livestock testing station between spring of 2002 and fall of 2003. A carcass trait, longissimus dorsi muscle area for each steer was measured after slaughter at approximately 722 days. Three SNPs (19_1, 18_4 and 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the quantitative trait loci (QTL) for meat quality were previously detected, were used in this study. The RPM analyses resulted in two significant interaction effects between SNPs (19_1 and 18_4) and (19_1 and 28_2) at ${\alpha}$ = 0.05 level. However, under a general linear (parametric) model no interaction effect between any pair of the three SNPs was detected, while only one main effect for SNP19_1 was found for the trait. Also, under another non-parametric model using a multifactor dimensionality reduction (MDR) method, only one interaction effect of the two SNPs (19_1 and 28_2) explained the trait significantly better than the parametric model with the main effect of SNP19_1. Our results suggest that RPM is a good alternative to model choices that can find associations of the interaction effects of multiple SNPs for quantitative traits in livestock species.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.79-85
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• 2006

This paper presents a strategy and tactic for robot soccer using furry logic mediator that determines robot action depending on the positions and the roles of adjacent two robots. Conventional Q-learning algorithm, where the number of states increases exponentially with the number of robots, is not suitable for a robot soccer system, because it needs so much calculation that processing cannot be accomplished in real time. A modular Q-teaming algorithm reduces a number of states by partitioning the concerned area, where mediator algorithm for cooperation of robots is used additionally. The proposed scheme implements the mediator algorithm among robots by fuzzy logic system, where simple fuzzy rules make the calculation easy and hence proper for robot soccer system. The simulation of MiroSot shows the feasibility of the proposed scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1458-1467
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• 2010

Recently, imitation and infringement rights of an intellectual property are being recognized as impediments to nation's industrial growth. To prevent the huge loss which comes from theses impediments, many researchers are studying protection and efficient management of an intellectual property in various ways. Especially, the prediction of patent registration is very important part to protect and assert intellectual property rights. In this study, we propose the patent document analysis method by using text mining to predict whether the patent is registered or rejected. In the first instance, the proposed method builds the database by using the word frequencies of the rejected patent documents. And comparing the builded database with another patent documents draws the similarity value between each patent document and the database. In this study, we used k-means which is partitioning clustering algorithm to select criteria value of patent rejection. In result, we found conclusion that some patent which similar to rejected patent have strong possibility of rejection. We used U.S.A patent documents about bluetooth technology, solar battery technology and display technology for experiment data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.8-16
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• 2016

This study presents the visualization of shape information based on Octree using 3D laser scanning. The process of visualization was established to construct the Octree structure from the 3D scan data. The scan data was converted to a 2D surface through the mesh technique and the surface was then converted to a 3D object through the Raster/Vector transformation. The 3D object was transmitted to the Octree Root Node and The shape information was constructed by the recursive partitioning of the Octree Root Node. The test-bed was selected as the steel bridge structure in Sungkyunkwan University. The shape information based on Octree was condensed into 89.3%. In addition, the Octree compressibility was confirmed to compare the shape information of the office building, a computer science campus in Germany and a New College in USA. The basis is created by the visualization of shape information for double-deck tunnel and it will be expected to improve the efficiency of structural health monitoring and maintenance.