• Title/Summary/Keyword: Directed Graph

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TG Index, its Graphical Matrix Representation and Application on Polyenes

  • Gumus, Selcuk;Turker, Lemi
    • Bulletin of the Korean Chemical Society
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    • v.35 no.5
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    • pp.1413-1416
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    • 2014
  • A novel topological index (TG Index) has been introduced. The graphical matrix representation of the TG index includes the use of directed subgraphs for the first time in graph theory literature. The application of the TG index on certain properties of polyenes yielded very well correlation data.

Analysis of Web Customers Using Bayesian Belief Networks (베이지안 네트워크를 이용한 전자상거래 고객들의 성향 분석)

  • 양진산;장병탁
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.387-392
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    • 2000
  • 전자 상거래에서 고객의 성향을 이해하기 위해서는 일반적으로 판매 실무에서의 경험과 전문적인 지식을 필요로 하게 된다. 데이터 마이닝은 고객들에 대한 데이터의 분석을 통해서 이러한 성향들을 알아내는 것을 목표로 한다. 베이지안 네트워크는 DAG(Directed Acyclic Graph)를 이용하여 데이터의 구조를 시각적으로 표현하여 주는 확률모형으로 변수사이의 종속관계를 밝히고 데이터 마이닝의 기법으로 이용할 수 있다. 본 논문에서는 베이지안 네트워크를 사용하여 전자 상거래 고객들의 성향을 분석하기 위한 방법을 제시한다. 또한 고객성향에 대한 주요 요인을 분석하기 위해 Descriminant 모형을 이용하고 그 유용성을 다른 방법들과 비교하였다.

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Development of a Decision Support System Shell for Problem Structuring (문제구조화를 위한 의사결정지원시스템츠 쉘의 개발)

  • 이재식;박동진
    • Journal of the Korean Operations Research and Management Science Society
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    • v.19 no.3
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    • pp.15-40
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    • 1994
  • We designed a knowledge-based decision support system for structuring semi-or unstructured problems. Problem structuring involves extraction of the relevant factors from the identified problem, and model construction that represents the relationships among those factors. In this research, we employed a directed graph called Influence Deiagram as a tool for problem structuring. In particular, our proposed system is designed as a shell. Therefore, a decision maker can change the content of the knowledge base to suit his/her own interested domain.

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Fault-consequence digraph를 이용한 전문가 시스템의 지식베이스 구현

  • 윤병석;오전근;윤인섭
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.389-394
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    • 1989
  • 본 연구에서는 화학공정의 자동화와 관련된 실시간 나프타 분해로 이상진단 시스템의 한 부분을 구성하고 있는 지식기반의 구현을 위하여 공정변수 상호간의 관계를 나타낸 signed directed graph(SDG)를 기반으로 이상에서 파급되는 증상들을 순서대로 나타내는 fault-consequence digraph(FCD)를 지식모델로 사용했고, 이를 사고사례를 이용하여 검토해본 결과 초기에 정확한 이상원인 후보를 찾아내므로써 이상진단 전문가 시스템의 지식모델로 적합함을 알 수 있었다.

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Deadlock Detection and Resolution for Flexible Job Routing (유연 공정 라우팅에서의 고착 탐지 및 해결)

  • 임동순;우훈식
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.58
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    • pp.49-58
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    • 2000
  • In order to resolve a deadlock problem in manufacturing systems, three main methods have been proposed-prevention, avoidance, and recovery. The prevention and avoidance methods require predicting deadlocks in advance in order to prohibit them. In contrast, the recovery method allows a system to enter a deadlock state, then resolves it usually using a common buffer. In this paper, a deadlock recovery method considering the impact of flexible job routings is proposed. This method is based on capacity-designated directed graph (CDG) model representing current requesting and occupying relations between Jobs and resources in order to detect a deadlock and then recovers it.

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Analysis of Web Customers Using Bayesian Belief Networks (베이지안 네트워크를 이용한 전자상거래 고객들의 성향 분석)

  • 양진산;장병탁
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.1
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    • pp.16-21
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    • 2001
  • 전자 상거래에서 고객의 성향을 이해하기 위해서는 일반적으로 판매 실무에서의 경험과 전문적인 지식을 필요로 하게 된다. 데이터 마이닝은 고객들에 대한 데이터의 분석을 통해서 이러한 성향들을 알아내는 것을 목표로 한다. 베이지안 네트워크는 DAG(Directed Acyclic Graph)를 이용하여 데이터의 구조를 시각적으로 표현하여 주는 확률모형으로 변수사이의 종속관계를 밝히고 데이터 마이닝의 기법으로 이용할 수 있다. 본 논문에서는 베이지안 네트워크를 사용하여 전자 상거래 고객들의 성향을 분석하기 위한 방법을 제시한다. 또한 고객성향에 대한 주요 요인을 분석하기 위해 Discriminant 모형을 이용하고 그 유용성을 다른 방법들과 비교하였다.

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FUZZY METHOD FOR FINDING THE FAULT PROPAGATION WAY IN INDUSTRIAL SYSTEMS

  • Vachkov, Gancho;Hirota, Kaoru
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1114-1117
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    • 1993
  • The paper presents an effective method for finding the propagation structure of the real origin of a system malfunction. It uses a combined system model consisting of Structural Model (SM) in the form of Fuzzy Directed Graph and Behavior Model (BM) as a set of Fuzzy Relational Equations $A\;{\circ}\;R\;=\;B$. Here a specially proposed fuzzy inference technique is checked and investigated. Finally a test example for fault diagnosis of an industrial system is given and analyzed.

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STRONG COMPATIBILITY IN CERTAIN QUASIGROUP NONUNIFORM HOMOGENEOUS SPACES OF DEGREE 4

  • Im, Bokhee;Ryu, Ji-Young
    • Honam Mathematical Journal
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    • v.41 no.3
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    • pp.595-607
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    • 2019
  • We consider quasigroups $Q({\Gamma})$ obtained as certain double covers of the symmetric group $S_3$ of degree 3, for directed graphs ${\Gamma}$ on the vertex set $S_3$. We completely characterize the strong compatibility of elements of $Q({\Gamma})$ for any quasigroup nonuniform homogeneous space of degree 4. For such homogeneous spaces, we classify all the strong and weak compatibility graphs of $Q({\Gamma})$.

Improvement of Face Recognition Algorithm for Residential Area Surveillance System Based on Graph Convolution Network (그래프 컨벌루션 네트워크 기반 주거지역 감시시스템의 얼굴인식 알고리즘 개선)

  • Tan Heyi;Byung-Won Min
    • Journal of Internet of Things and Convergence
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    • v.10 no.2
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    • pp.1-15
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    • 2024
  • The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.