• 제목/요약/키워드: Multifactor

검색결과 73건 처리시간 0.036초

MULTIFACTOR MODELLING IN CONSTRUCTION MANAGEMENT

  • Leszek Janusz;Oleg Kaplinski
    • 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.

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Multifactor-Dimensionality Reduction in the Presence of Missing Observations

  • Chung, Yu-Jin;Lee, Seung-Yeoun;Park, Tae-Sung
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.31-36
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    • 2005
  • An identification and characterization of susceptibility genes for common complex multifactorial diseases is a challengeable task, in which the effect of single genetic variation will be likely dependent on other genetic variations(gene-gene interaction) and environmental factors (gene-environment interaction). To address is issue, the multifactor dimensionality reduction (MDR) has been proposed and implemented by Ritchie et al. (2001), Moore et al. (2002), Hahn et al.(2003) and Ritchie et al. (2003). With MDR, multilocus genotypes effectively reduce the dimension of genotype predictors from n to one, which improves the identification of polymorphism combinations associated with disease risk. However, MDR cannot handle missing observations appropriately, in which missing observation is treated as an additional genotype category. This approach may suffer from a sparseness problem since when high-order interactions are considered, an additional missing category would make the contingency table cells more sparse. We propose a new MDR approach with minimum loss of sample sizes by considering missing data over all possible multifactor classes. We evaluate the proposed MDR by using the prediction errors and cross validation consistency.

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MULTIFACTOR DIMENSIONALITY REDUCTION(MDR)을 이용한 한우 도체중에서의 주요 SNP 규명 (Main SNP Identification of Hanwoo Carcass Weight with Multifactor Dimensionality Reduction(MDR) Method)

  • 이제영;김동철
    • 응용통계연구
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    • 제21권1호
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    • pp.53-63
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    • 2008
  • 일반적으로 인간의 질병과 가축의 경제적인 특성은 하나의 유전자가 아닌 여러 유전자의 상호작용으로 일어난다고 믿고 있다. 따라서 본 연구에서는 세대를 거듭할수록 대립유전자의 유전이 안정적으로 발생되어지고 개체의 기능적인 유전적 가치를 직접적으로 추정할 수 있는 single nucleotide polymorphism(SNP)을 한우의 경제적 특성인도체중(carcass cold weight)에 대하여 모수적인 방법인 ANOVA와 비모수적인 방법인 multifactor dimensionality reduction(MDR)을 이용하여 하나의 유전자의 효과와 두 개의 유전자의 상호작용 효과를 비교하였다. ANOVA에서는 하나의 유전자 SNP1이 도체중에 유의한 효과가 있었고 상호작용 효과에서는 도체중에 유의한 효과는 없었다. MDR에서는 하나의 유전자의 효과인 SNP1과 두 개의 유전자의 상호작용인 SNP1*SNP2의 효과가 컸으며 SNP1과 SNP1*SNP2를 비교했을 시에는 SNP1*SNP2의 효과가 더 크게 나타났다. 이는 개별 SNP유전자 보다 복합 SNP유전자의 상호작용이 경제적인 특성인 도체증에 더 영향을 준다는 것을 알 수 있었다.

가계대출을 조건변수로 사용하는 소비 준거 자본자산 가격결정모형 (Can Bank Credit for Household be a Conditional Variable for Consumption CAPM?)

  • 권지호
    • 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.

Boosting Multifactor Dimensionality Reduction Using Pre-evaluation

  • Hong, Yingfu;Lee, Sangbum;Oh, Sejong
    • ETRI Journal
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    • 제38권1호
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    • pp.206-215
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    • 2016
  • The detection of gene-gene interactions during genetic studies of common human diseases is important, and the technique of multifactor dimensionality reduction (MDR) has been widely applied to this end. However, this technique is not free from the "curse of dimensionality" -that is, it works well for two- or three-way interactions but requires a long execution time and extensive computing resources to detect, for example, a 10-way interaction. Here, we propose a boosting method to reduce MDR execution time. With the use of pre-evaluation measurements, gene sets with low levels of interaction can be removed prior to the application of MDR. Thus, the problem space is decreased and considerable time can be saved in the execution of MDR.

Behavioral Analysis Zero-Trust Architecture Relying on Adaptive Multifactor and Threat Determination

  • Chit-Jie Chew;Po-Yao Wang;Jung-San Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권9호
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    • pp.2529-2549
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    • 2023
  • For effectively lowering down the risk of cyber threating, the zero-trust architecture (ZTA) has been gradually deployed to the fields of smart city, Internet of Things, and cloud computing. The main concept of ZTA is to maintain a distrustful attitude towards all devices, identities, and communication requests, which only offering the minimum access and validity. Unfortunately, adopting the most secure and complex multifactor authentication has brought enterprise and employee a troublesome and unfriendly burden. Thus, authors aim to incorporate machine learning technology to build an employee behavior analysis ZTA. The new framework is characterized by the ability of adjusting the difficulty of identity verification through the user behavioral patterns and the risk degree of the resource. In particular, three key factors, including one-time password, face feature, and authorization code, have been applied to design the adaptive multifactor continuous authentication system. Simulations have demonstrated that the new work can eliminate the necessity of maintaining a heavy authentication and ensure an employee-friendly experience.

유방암과 CCND1, ESR1, CDK7 유전자 다형성의 상호작용; 로지스틱 회귀분석과 multifactor dimensionality reduction(MDR)의 분석 비교 (Gene-gene interaction of CCND1, ESR1 and CDK7 on the risk of breast cancer detected by multifactor dimensionality reduction and logistic regression)

  • 최지엽;;;이경무;노동영;유근영;;강대희
    • 대한예방의학회:학술대회논문집
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    • 대한예방의학회 2004년도 제56차 추계 학술대회 연제집
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    • pp.40.1-40.1
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    • 2004
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국내 7대 특·광역시 노동시장의 고용성장 요인분해 - 네 변인 다요인분해분석의 적용 - (Decomposition of Employment Growth in Korean Metropolitan Labor Markets: An Application of a Four-way Multifactor Partitioning)

  • 박지한;김동현
    • 지역연구
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    • 제39권4호
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    • pp.53-71
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    • 2023
  • 본 연구는 국내 7대 특·광역시를 대상으로 지난 20년(1996~2016년)간의 고용성장에 대한 요인별 기여도를 파악하는 것이 목적이다. 이를 위해 통계청에서 제공하는 사업체 조사 자료를 바탕으로 다요인분해(multifactor partitioning, MFP)분석을 수행하였다. 분석의 주요 결과는 다음과 같다. 첫째, 장기간에 걸친 대도시권의 고용성장에서는 전반적으로 지역효과가 지배적인 영향력을 보이고 있으며, 산업구조효과가 이를 뒤따르고 있다. 동태적 다요인분해분석 결과는 향후 지역 간 고용 격차가 산업구조에 의해 설명될 가능성이 크다는 것을 보여준다. 둘째, 성별과 양질의 일자리구성효과는 지역별 고용성장에 큰 기여를 보이지 않는다. 단, 실질적인 개별 인자들의 기여를 보면 남성-상용근로자의 고용감소와 여성-비상용근로자의 고용성장 패턴을 유추할 수 있다. 이러한 결과는 각 지역 산업의 구조적 전환과 고용안정성이 동반된 질적성장을 도모할 수 있는 고용정책의 중요성과 필요성을 의미한다.

Identification of epistasis in ischemic stroke using multifactor dimensionality reduction and entropy decomposition

  • Park, Jung-Dae;Kim, Youn-Young;Lee, Chae-Young
    • 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.

Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method

  • Lee, Seungyeoun;Son, Donghee;Yu, Wenbao;Park, Taesung
    • 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.