• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.633-637
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• 2005

The paper presents a multifactor modelling of construction processes. There are three phases of the proposed extended procedure. Tools for these phases from chronometric test to verifying of the assumed model are indicated. Apart from the classic verification activities the method of artificial neural networks has been successfully applied. The paper presents the usage of these tools to model the process of assembly of structural corrugated steel plate structures.

• Genomics & Informatics
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• 제14권4호
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• pp.166-172
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• 2016

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

• BMB Reports
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• 제42권9호
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• pp.617-622
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• 2009

We investigated the genetic associations of ischemic stroke by identifying epistasis of its heterogeneous subtypes such as small vessel occlusion (SVO) and large artery atherosclerosis (LAA). Epistasis was analyzed with 24 genes in 207 controls and 271 patients (SVO = 110, LAA = 95) using multifactor dimensionality reduction and entropy decomposition. The multifactor dimensionality reduction analysis with any of 1- to 4-locus models showed no significant association with LAA (P > 0.05). The analysis of SVO, however, revealed a significant association in the best 3-locus model with P10L of TGF-$\beta{1}$, C1013T of SPP1, and R485K of F5 (testing balanced accuracy = 63.17%, P < 0.05). Subsequent entropy analysis also revealed that such heterogeneity was present and quite a large entropy was estimated among the 3 loci for SVO (5.43%), but only a relatively small entropy was estimated for LAA (1.81%). This suggests that the synergistic epistasis model might contribute specifically to the pathogenetsis of SVO, which implies a different etiopathogenesis of the ischemic stroke subtypes.

• 아태비즈니스연구
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• 제11권3호
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• pp.199-215
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• 2020

Purpose - This article tries to test if the conditional consumption capital asset pricing model (CCAPM) with bank credit for household as a conditional variable can explain the cross-sectional variation of stock returns in Korea. The performance of conditional CCAPM is compared to that of multifactor asset pricing models based on Arbitrage Pricing Theory. Design/methodology/approach - This paper extends the simple CCAPM to the conditional version of CCAPM by using bank credit for household as conditioning information. By employing KOSPI and KOSDAQ stocks as test assets from the second quarter of 2003 to the first quarter of 2018, this paper estimates risk premiums of conditional CCAPM and a variety of multifactor linear models such as Fama-French three and five-factor models. The significance of risk factors and the adjusted coefficient of determination are the basis for the comparison in models' performances. Findings - First, the paper finds that conditional CCAPM with bank credit performs as well as the multifactor linear models from Arbitrage Pricing theory on 25 test assets sorted by size and book-to-market. When using long-term consumption growth, the conditional CCAPM explains the cross-sectional variation of stock returns far better than multifactor models. Not only that, although the performances of multifactor models decrease on 75 test assets, conditional CCAPM's performance is well maintained. Research implications or Originality - This paper proposes bank credit for household as a conditional variable for CCAPM. This enables CCAPM, one of the most famous economic asset pricing models, to conform with the empirical data. In light of this, we can now explain the cross-sectional variation of stock returns from an economic perspective: Asset's riskiness is determined by its correlation with consumption growth conditional on bank credit for household.

• Communications for Statistical Applications and Methods
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• 제15권2호
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• pp.265-271
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• 2008

It is commonly believed that diseases of human or economic traits of livestock are caused not by single genes acting alone, but multiple genes interacting with one another. This issue is difficult due to the limitations of parametric-statistic methods of gene effects. So we introduce multifactor-dimensionality reduction(MDR) as a methods for reducing the dimensionality of multilocus information. The MDR method is nonparametric (i. e., no hypothesis about the value of a statistical parameter is made), model free (i. e., it assumes no particular inheritance model) and is directly applicable to case-control studies. Application of the MDR method revealed the best model with an interaction effect between the SNPs, SNP1 and SNP3, while only one main effect of SNP1 was statistically significant for LMA (p < 0.01) under a general linear mixed model.

• Asian-Australasian Journal of Animal Sciences
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• 제21권6호
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• pp.784-788
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• 2008

Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models. A non-parametric, model-free approach using the 'expanded multifactor-dimensionality reduction (MDR) method' considering high dimensionalities of interaction effects between multiple single nucleotide polymorphisms (SNPs), was applied to identify interaction effects of SNPs responsible for carcass traits in a Hanwoo beef cattle population. Data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, and comprised 299 steers from 16 paternal half-sib proven sires that were delivered in Namwon or Daegwanryong livestock testing stations between spring of 2002 and fall of 2003. For each steer at approximately 722 days of age, the Longssimus dorsi muscle area (LMA) was measured after slaughter. Three functional SNPs (19_1, 18_4, 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the QTL for meat quality were previously detected, were assessed. Application of the expanded MDR method revealed the best model with an interaction effect between the SNPs 19_1 and 28_2, while only one main effect of SNP19_1 was statistically significant for LMA (p<0.01) under a general linear mixed model. Our results suggest that the expanded MDR method better identifies interaction effects between multiple genes that are related to polygenic traits, and that the method is an alternative to the current model choices to find associations of multiple functional SNPs and/or their interaction effects with economic traits in livestock populations.

• Genomics & Informatics
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• 제18권4호
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• pp.38.1-38.9
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• 2020

Chronotype is an important moderator of psychiatric illnesses, which seems to be controlled in some part by genetic factors. Clock genes are the most relevant genes for chronotype. In addition to the roles of individual genes, gene-gene interactions of clock genes substantially contribute to chronotype. We investigated genetic associations and gene-gene interactions of the clock genes BHLHB2, CLOCK, CSNK1E, NR1D1, PER1, PER2, PER3, and TIMELESS for chronotype in 1,293 healthy Korean individuals. Regression analysis was conducted to find associations between single nucleotide polymorphism (SNP) and chronotype. For gene-gene interaction analyses, the quantitative multifactor dimensionality reduction (QMDR) method, a nonparametric model-free method for quantitative phenotypes, were performed. No individual SNP or haplotype showed a significant association with chronotype by both regression analysis and single-locus model of QMDR. QMDR analysis identified NR1D1 rs2314339 and TIMELESS rs4630333 as the best SNP pairs among two-locus interaction models associated with chronotype (cross-validation consistency [CVC] = 8/10, p = 0.041). For the three-locus interaction model, the SNP combination of NR1D1 rs2314339, TIMELESS rs4630333, and PER3 rs228669 showed the best results (CVC = 4/10, p < 0.001). However, because the mean differences between genotype combinations were minor, the clinical roles of clock gene interactions are unlikely to be critical.

• Journal of the Korean Data and Information Science Society
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• 제23권3호
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• pp.467-474
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• 2012

인간의 질병과 가축의 경제적인 특성은 하나의 유전자가 아닌 여러 유전자의 상호작용의 영향을 더 많이 받는다고 알려져 있다. 본 논문에서는 유전적인 효과만을 밝혀내기 위해 선형회귀모형을 활용하여 환경적인 요인을 보정하고, 최근 한우의 맛과 육질에 영향을 준다고 밝혀진 단일염기다형성 5개 (Oh 등, 2011)를 이용해 한우의 경제형질에 영향을 주는 우수 유전자 조합을 선별하고 우수 유전자형을 밝힌다. 이때, 많은 유전자들 중에서 우수한 유전자를 찾기 위한 비모수적인 방법인 다중인자 차원 축소 방법을 이용하여 단일 유전자의 효과보다 상호작용의 효과가 한우의 경제형질에 더 많은 영향을 준다는 사실을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1057-1067
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• 2014

인간게놈 프로젝트 이후 질병과 연관된 변이유전자를 탐색하기 위해 유전형질의 차이에 영향을 주는 단일 유전자를 중심으로 전장유전체 연관성 연구가 활발하게 진행되어왔다. 그러나 전장유전체 연관성 연구에서 접근한 단일유전자 분석방법에 한계점이 발견되면서 최근에는 다중유전자 분석방법이나 유전자-유전자간의 상호작용에 대한 연구들이 활발하게 진행 중이다. 이 중 다중차원축소방법은 유전자-유전자간의 상호작용의 연관성을 찾아내기 위하여 고차원을 일차원으로 축소하는 방법으로 이진형 반응변수를 기반으로 크게 활용되고 있다. 본 논문에서는 이 방법을 생존시간으로 확장하여 생존시간과 연관된 유전자-유전자간의 상호작용을 찾아내는 방법을 제안하고자 한다. 구체적으로 가속화 고장시간 회귀모형 하에서 표준화잔차 스코어를 분류기준으로 사용하여 다중차원축소방법을 적용하는 방법으로 AFT-MDR이라고 지칭하였다. 시뮬레이션 연구를 통하여 기존에 제안된 Surv-MDR과 Cox-MDR과의 검정력을 비교하였으며 국내의 백혈병환자 자료분석에 적용하였다. 시뮬레이션 결과로부터 AFT-MDR은 유전율이 높을수록 검정력이 커지며 회귀모형에 기반하여 공변량의 효과를 고려할 수 있다는 장점이 있으나 센서링 비율이 높아지면서 검정력이 매우 떨어진다는 단점이 발견되었다. 따라서 이를 보완하기 위한 추후연구의 필요성이 요구된다.

• 국제지역연구
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• 제15권2호
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• pp.125-150
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• 2011

경제가 선진화 되면서 나타나는 경제의 서비스화는 일반적으로 생산성 저하 현상을 야기할 것이라는 우려가 있다. 그러나 선진국의 경우 경제의 서비스화 현상이 진행되면서 생산성이 오히려 상승하는 Baumol의 역설 현상이 발생하였다. Oulton(1999, 2001)은 이러한 현상의 이유로 하나의 산업에서의 생산이 타 산업으로부터 중간재를 공급받아 생산되는 연쇄과정인 전후방연관효과에서 찾고 있다. 따라서 본 연구에서는 Oulton(1999, 2001)의 이론을 실증적으로 검증해 볼 필요성이 있다고 판단하였다. 또한 더미변수를 이용하여 소비자 서비스와 생산자 서비스의 중간 투입 간의 영향력 차이를 파악하고자 하였다. 위의 연구 목적을 달성하기 위해 한국은행에서 발간되는 산업연관표(1990, 1995, 2000, 2005)의 자료로 멀티레벨모형(Multi-level Model)을 활용하여 이론 검증을 실시하였다. 연구 결과, Oulton(1999, 2001)의 이론과 같이 한국의 경우에 중간재 생산자 서비스의 투입 비중이 상승하면 다요소생산성(Multifactor Productivity)이 상승하였다. 또한 중간재 생산자 서비스의 비중 변화와 달리 중간재 소비자 서비스의 비중 변화는 다요소생산성에 유의한 영향을 유발하지 않았다. 주요 산업(서비스업, 제조업, 그 외 산업)별로 중간재 생산자 서비스의 비중 변화의 효과 차이를 검증한 결과 제조업이 서비스업과 그 외의 기타산업에 비해 중간재 생산자 서비스의 비중 변화의 효과가 더 작았다.