• 한국통신학회논문지
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• 제24권7A호
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• pp.1036-1045
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• 1999

본 논문에서는 임의의 프로세스가 여러 그룹에 속하는 중첩된 프로세스 그룹 환경에 효율적으로 적용할 수 있는 인과관계 순서화 알고리즘을 제시하였다. 본 알고리즘은 네트워크 구성 형태에 따라 선택할 수 있도록 제안하였다. 즉, 브로드캐스트 네트워크에서는 수신자 선택 알고리즘을 제안하였으며, 점대점 네트워크에서는 송신자 선택 알고리즘을 제안하였다. 각 알고리즘은 순서화에 요구되는 메시지 오버해드를 줄이기 위해 그룹별로 불필요한 벡터 타임스탬프를 제거하였으며, 메시지 오버해드를 최소화하기 위해 국부적으로 유지하고 있는 다른 프로세스와 다른 그룹의 정보를 이용하여 압축하도록 하였다. 각각의 새로운 인과관계 순서화 알고리즘을 논리적으로 증명하였고, 시뮬레이션을 통해 기존의 인과관계 순서화 알고리즘과의 성능을 비교하였다.

• 대한한의학회지
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• 제35권3호
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• pp.49-59
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• 2014

Background: Eight positions for new formulations in Jingyuequanshu is a unique classifying system and each position can be presented as a network. Network analysis is an effective method of visualizing the relationship of textual information. Purpose: This study aimed to analyze the structure of the eight positions for new formulations in Jingyuequanshu, and to acquire information about composing materia medica. Methods: We constructed an initial database and binary matrix of eight positions for new formulation in Jingyuequanshu, including its herbs and formulations. With this data, we carried out frequency and network analysis. Results: We analyzed each of the eight positions for new formulation, entire positions, and five positions after removing 'causal/cold/hot' positions. We found that the formulas of the causal position are distributed throughout the new formulation, and those of the cold and hot positions are also distributed similarly but the two groups are exclusive to each other. The other 5 positions are distributed exclusively to one another. Conclusions: Eight positions for new formulation of Jingyuequanshu were classified into three axes by exploratory network analysis. One is an axis of causal position, another is an axis of cold/hot positions, and the last is an axis of the other five positions.

• 한국지반공학회논문집
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• 제28권10호
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• pp.89-96
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• 2012

본 연구에서는 사면위험도의 합리적인 평가 가중치를 도출하기 위하여 국내의 대표적인 평가방법에 대해 동일한 영향성을 주는 것으로 간주되는 항목들을 그룹화하여 그 영향성을 분석하고 이를 국립방재연구소(NIDP) 평가법과 비교, 사면붕괴 주요인자 선별의 적정성과 배점비율을 검토하였다. 또한, 붕괴가 발생된 28개소 사면을 대상으로 ANN(Artificial Neural Network) 기법을 적용하여 사면붕괴 유발인자 가중치에 대한 합리적 배점이 이루어졌는지에 대해 고찰하였다. ANN기법에 의해 평가비중을 재조정하여 분석한 결과, 국립방재연구소 평가법의 평가비중 오차가 큰 예상피해도, 인장균열, 계곡부 항목의 가중치를 조정하여야 보다 정확한 평가가 가능할 것으로 분석되었다.

• Genomics & Informatics
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• 제9권4호
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• pp.143-151
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• 2011

In this study, we propose a novel, intuitive method of constructing an expression quantitative trait (eQT) network that is related to the metabolic syndrome using LOD scores and peak loci for selected eQTs, based on the concept of gene-gene interactions. We selected 49 eQTs that were related to insulin resistance. A variance component linkage analysis was performed to explore the expression loci of each of the eQTs. The linkage peak loci were investigated, and the "support zone" was defined within boundaries of an LOD score of 0.5 from the peak. If one gene was located within the "support zone" of the peak loci for the eQT of another gene, the relationship was considered as a potential "directed causal pathway" from the former to the latter gene. SNP markers under the linkage peaks or within the support zone were searched for in the database to identify the genes at the loci. Two groups of gene networks were formed separately around the genes IRS2 and UGCGL2. The findings indicated evidence of networks between genes that were related to the metabolic syndrome. The use of linkage analysis enabled the construction of directed causal networks. This methodology showed that characterizing and locating eQTs can provide an effective means of constructing a genetic network.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.373-378
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• 2005

The diagrammatic language for pathways is widely used for representing systems knowledge as a network of causal relations. Biologists infer and hypothesize with pathways to design experiments and verify models, and to identify potential drug targets. Although there have been many approaches to formalize pathways to simulate a system, reasoning with incomplete and high level knowledge has not been possible. We present a qualitative formalization of a pathway language with incomplete causal descriptions and its translation into propositional temporal logic to automate the reasoning process. Such automation accelerates the identification of drug targets in pathways.

• Transactions on Control, Automation and Systems Engineering
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• 제1권1호
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• pp.54-61
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

• 한국시스템다이내믹스연구
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• 제12권1호
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• pp.89-114
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• 2011

With steady increase in the demand for door-to-door delivery services, courier service providers are facing a constant pressure to reduce delivery price in order to secure quantity order and to improve the efficiency and reliability for customer service. The objective of this research is to explain the structure of the door-to-door delivery including door-to-door delivery service demand, sorting capacity in the hub-terminal, and the system performance measures such as service reliability networks using causal loop diagram(CLD). Based on causal relation, this research describes a comprehensive approach to examine how capacity reliability contributes to the renewal of the firm's competences through its reciprocal relationship with travel time reliability and connectivity reliability. Also, this research suggests the policy alternatives to improve effectiveness and efficiency of door-to-door delivery network in response to increase customer satisfaction and profit maximization of the courier service providers: operational, tactical, and strategic levels.

• 디지털융복합연구
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• 제12권1호
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• pp.127-139
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• 2014

본 연구의 목적은 스마트폰 운영체제의 지배적 디자인을 결정하는 주요 요인이 무엇인지 제시하고 제시된 요인들과 사용만족 간의 논리적 인과관계를 검증하는데 있다. 이를 위해 지배적 디자인을 결정하는 스마트폰 운영체제의 주요 결정요인을 OS호환성, OS향상성, 사용자기반, 그리고 네트워크 효과 등으로 제시했다. 그리고 사용만족과의 논리적 인과관계를 실증분석했다. 연구결과, 스마트폰 운영체제의 OS호환성과 OS향상성은 사용기반 확대에 긍정적인 영향을 미치는 것으로 나타났다. 특히 OS향상성은 사용기반을 확대 시킬 뿐만 아니라 네트워크 효과를 강화시키는 원인으로 나타났다. 그리고 직접적으로 사용만족에도 긍정적인 영향을 미치는 것으로 나타났다. 연구결과는 그동안 실증연구가 이루어지지 않았던 운영체제의 지배적 디자인 결정과정에 대해 논리적 인과관계를 제시하여 학문적으로 뿐만 아니라 실무적으로도 크게 기여했다고 판단된다.

• 한국정보전자통신기술학회논문지
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• 제11권2호
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• pp.169-174
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• 2018

일반적으로 자료의 효과 연속형인 경우 분산분석과 이산형인 경우 분할표 카이제곱 검정을 통계적 분석방법으로 사용한다. 다차원의 자료에서는 계층적 구조의 분석이 요구되어지며 자료간의 인과관계를 나타내기 위해 통계적 선형모형을 채택하여 분석한다. 선형모형의 구조에서는 자료의 정규성이 요구되어지며 일부 자료에서는 비 선형모형을 채택할 수도 있다. 특히, 설문조사 자료 구조는 문항의 특성상 이산형 자료의 형태가 많아 모형의 조건에 만족하지 않는 경우가 종종 발생한다. 자료구조의 차원이 높아질수록 인과관계, 교호작용, 연관성분석 등에 다차원 범주형 자료 분석 방법을 사용한다. 본 논문에서는 확률분포의 계산을 이용한 베이지안 네트워크 모형이 범주형 자료 분석에서 분석절차를 줄이고 교호작용 및 인과관계를 분석할 수 있다는 것을 제시하였다.

• 한국시스템다이내믹스연구
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• 제16권2호
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• pp.33-52
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• 2015

This study aims to comprehensively understand the dynamics of the community network of Community Child Centers and further find out the measures to activate its community network based on the Systems Thinking. The contents of the study are as follows. Firstly, it examines the existing studies on the community network of Community Child Centers and presents the major variables to understand the situation of its community network. Secondly, it analyzes the structure of its causation in order to understand the dynamics of its community network. Lastly, it concludes with the suggestions to activate its community network based on its feedback structure presented in the causal loop diagrams. This study is expected to make a useful and basic material as the first research to dynamically understand the community network issue of the Community Child Centers.