• Journal of the Korean Data and Information Science Society
• /
• v.23 no.3
• /
• pp.467-474
• /
• 2012

Human diseases and livestock economic traits are not typically the result of variation of a single genetic locus, but are rather the result of interplay between interactions among multiple genes and a variety of environmental exposures. We have used linear regression model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. Of course, we use 5 SNPs (single uncleotide polymorphism) which were studied recently by Oh et al. (2011). We apply the MDR (multifactor demensionality reduction) method on the identify major interaction effects of single nucleotide polymorphisms responsible for economic traits in a Korean cattle population.

• The Korean Journal of Applied Statistics
• /
• v.22 no.6
• /
• pp.1239-1247
• /
• 2009

Study the gene about economical characteristic of human disease or domestic animal is a matter of grave interest, preserve and elevation of gene of Korea cattle is key subject. Studies have been done on the gene of Korea cattle using EST based SNP map, but it is based on statistical model, therefore there are difference between real position and statistical position. These problems are solved using both EST_based SNP map and Gene on sequence by Lee et al. (2009b). We have used multifactor dimensionality reduction(MDR) method to study interaction effect of statistical model in general. But MDR method cannot be applied in all cases. It can be applied to the only case-control data. So, method is suggested E-MDR method using CART algorithm. Also we identified interaction effects of single nucleotide polymorphisms(SNPs) responsible for average daily gain(ADG) and marbling score(MS) using E-MDR method.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.3
• /
• pp.677-685
• /
• 2015

Disease of human and economic traits of livestocks are affected a lot by gene combination effect rather than a single gene effect. In this study, we used SNPHarvester method that supplement existing method in order to investigate the interaction of these genes. The used genes are SREBPs (g.3270+10274 C>T, g.13544 T>C) and FABP4 (g.2634+1018 A>T, g.2988 A>G, g.3690 G>A, g.3710 G>C, g.3977-325 T>C, g.4221 A>G) that are closely related to the fatty acid composition affecting the meatiness of Korean cattle. The economic traits which are used are oleic acid (C18:1), monounsaturated fatty acid (MUFA), marbling score (MS). First, we have utilized the SNPHarvester method in order to find excellent gene combination, and then used the multifactor dimensionality reduction method in order to identify excellent genotype in gene combination.

• Journal of KIISE
• /
• v.41 no.9
• /
• pp.666-673
• /
• 2014

This paper proposes a scalable face recognition method for unconstrained face databases, and shows a simple experimental result. Existing face recognition research usually has focused on improving the recognition rate in a constrained environment where illumination, face alignment, facial expression, and background is controlled. Therefore, it cannot be applied in unconstrained face databases. The proposed system is face feature extraction algorithm for unconstrained face recognition. First of all, we extract the area that represent the important features(landmarks) in the face, like the eyes, nose, and mouth. Each landmark is represented by a high-dimensional LBP(Local Binary Pattern) histogram feature vector. The multi-scale LBP histogram vector corresponding to a single landmark, becomes a low-dimensional face feature vector through the feature reduction process, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis). We use the Rank acquisition method and Precision at k(p@k) performance verification method for verifying the face recognition performance of the low-dimensional face feature by the proposed algorithm. To generate the experimental results of face recognition we used the FERET, LFW and PubFig83 database. The face recognition system using the proposed algorithm showed a better classification performance over the existing methods.

• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.6
• /
• pp.511-520
• /
• 2009

In this paper, we present a new iso-density surface reconstruction scheme based on a hierarchy on the input volume data and the output mesh data. From the input volume data, we construct a hierarchy of volumes, called a volume pyramid, based on a 3D dilation filter. After constructing the volume pyramid, we extract a coarse base mesh from the coarsest resolution of the pyramid with the Cell-boundary representation scheme. We iteratively fit this mesh to the iso-points extracted from the volume data under O(3)-adjacency constraint. For the surface fitting, the shrinking process and the smoothing process are adopted as in the SWIS (Shrink-wrapped isosurface) algorithm[6], and we subdivide the mesh to be able to reconstruct fine detail of the isosurface. The advantage of our method is that it generates a mesh which can be utilized by several multiresolution algorithms such as compression and progressive transmission.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
• /
• v.11 no.3
• /
• pp.11-21
• /
• 2000

을 합하여 얻을 수 있다. 이와 같은 광선 추적법을 적용한 해석적 방법은 디지털 방송의 수신 영역을 결정하는 중요한 두 요소인 수신 전계강도 및 다중 경로 간섭을 비교적 정확히 예측할 수 있다. 개발된 모델을 이용하여 디지털 방송 환경에서 동일채널 중계기로 인한 방송 수신 영역의 확대 또는 축소를 예측할 수 있으며, 중계기의 최적화 위치를 찾는 데 활용할 수 있다.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.6
• /
• pp.1331-1339
• /
• 2013

The lipoprotein lipase (LPL) gene can be considered a functional candidate gene that regulates fatty acid composition. Oh etc (2013) investigated the relationship between unsaturated fatty acids and five novel SNPs, and had confirmed that three polymorphic SNPs (c.322G>A, c.329A>T and c.1591G>A) were associated with fatty acid composition. We have used generalized linear model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. We applied the MDR method on the identify major interaction effects of exonic single nucleotide polymorphisms (SNPs) in the LPL gene for economic traits in Korean cattles population.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.11a
• /
• pp.10-13
• /
• 2022

최근 인공지능 기술을 바탕으로 지능형 분석을 수행하는 기계를 위한 비디오 부호화 기술의 필요성이 요구되면서, MPEG 에서는 VCM(Video Coding for Machines) 표준화를 시작하였다. VCM 에서는 기계를 위한 비디오/이미지 압축 또는 비디오/이미지 특징 압축을 위한 다양한 방법이 제시되고 있다. 본 논문에서는 객체추적(object tracking)을 위한 머신비전(machine vision) 네트워크에서 추출되는 다중스케일(multi-scale) 특징의 효율적인 압축 기법을 제시한다. 제안기법은 다중스케일 특징을 단일스케일(single-scale) 특징으로 차원을 축소하여 형성된 특징 시퀀스를 최신 비디오 코덱 표준인 VVC(Versatile Video Coding)를 사용하여 압축한다. 제안기법은 VCM 에서 제시하는 기준(anchor) 대비 89.65%의 BD-rate 부호화 성능향상을 보인다.

• Communications for Statistical Applications and Methods
• /
• v.16 no.4
• /
• pp.579-586
• /
• 2009

We have used multifactor dimensionality reduction(MDR) method to study interaction effect of statistical model in general. But MDR method cannot be applied in all cases. It can be applied to the only case-control data. So, two methods are suggested E-MDR and D-MDR method using regression tree algorithm and dummy variables. We applied the methods on the identify interaction effects of single nucleotide polymorphisms(SNPs) responsible for longissimus mulcle dorsi area(LMA), carcass cold weight(CWT) and average daily gain(ADG) in a Hanwoo beef cattle population. Finally, we compare the results using permutation test.

• The Korean Journal of Applied Statistics
• /
• v.28 no.5
• /
• pp.859-870
• /
• 2015

Economic-traits of livestock are affected by environmental and genetic factors. We are interested in genetic factors that influence the economic-traits of Korean cattle. It is necessary to adjust environmental factors in order to enhance the accuracy of the genetic effect analysis. In this paper, we propose a statistical model of Korean cattle that exclude environmental breeding farm and age factors. We formulated an adjusted economic-trait value, and applied multifactor dimensionality reduction (MDR) method to data of before-and-after adjustment to identify major FABP4 genes. We were able to increase the accuracy of the analysis after adjustment and identify superior FABP4 genes that influence grade and fatty acid.