• Title/Summary/Keyword: block graph

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Controlling a Traversal Strategy of Abstract Reachability Graph-based Software Model Checking (추상 도달가능성 그래프 기반 소프트웨어 모델체킹에서의 탐색전략 고려방법)

  • Lee, Nakwon;Baik, Jongmoon
    • Journal of KIISE
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    • v.44 no.10
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    • pp.1034-1044
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    • 2017
  • Although traversal strategies are important for the performance of model checking, many studies have ignored the impact of traversal strategies in model checking with a block-encoded abstract reachability graph. Studies have considered traversal strategies only for an abstract reachability graph without block-encoding. Block encoding plays a crucial role in the model checking performance. This paper therefore describes Dual-traversal strategy, a simple and novel technique to control traversal strategies in a block-encoded abstract reachability graph. This method uses two traversal strategies for a model checking, one for effective block-encoding, and the other for traversal in an encoded abstract reachability graph. Dual-traversal strategy is very simple and can be implemented without overhead compared to the existing single-traversal strategy. We implemented the Dual-traversal strategy in an open source model checking tool and compare the performances of different traversal strategies. The results show that the model checking performance varies from the traversal strategies for the encoded abstract reachability graph.

Dynamic Block Reassignment for Load Balancing of Block Centric Graph Processing Systems (블록 중심 그래프 처리 시스템의 부하 분산을 위한 동적 블록 재배치 기법)

  • Kim, Yewon;Bae, Minho;Oh, Sangyoon
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.5
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    • pp.177-188
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    • 2018
  • The scale of graph data has been increased rapidly because of the growth of mobile Internet applications and the proliferation of social network services. This brings upon the imminent necessity of efficient distributed and parallel graph processing approach since the size of these large-scale graphs are easily over a capacity of a single machine. Currently, there are two popular parallel graph processing approaches, vertex-centric graph processing and block centric processing. While a vertex-centric graph processing approach can easily be applied to the parallel processing system, a block-centric graph processing approach is proposed to compensate the drawbacks of the vertex-centric approach. In these systems, the initial quality of graph partition affects to the overall performance significantly. However, it is a very difficult problem to divide the graph into optimal states at the initial phase. Thus, several dynamic load balancing techniques have been studied that suggest the progressive partitioning during the graph processing time. In this paper, we present a load balancing algorithms for the block-centric graph processing approach where most of dynamic load balancing techniques are focused on vertex-centric systems. Our proposed algorithm focus on an improvement of the graph partition quality by dynamically reassigning blocks in runtime, and suggests block split strategy for escaping local optimum solution.

NORDHAUS-GADDUM TYPE RESULTS FOR CONNECTED DOMINATION NUMBER OF GRAPHS

  • E. Murugan;J. Paulraj Joseph
    • Korean Journal of Mathematics
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    • v.31 no.4
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    • pp.505-519
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    • 2023
  • Let G = (V, E) be a graph. A subset S of V is called a dominating set of G if every vertex not in S is adjacent to some vertex in S. The domination number γ(G) of G is the minimum cardinality taken over all dominating sets of G. A dominating set S is called a connected dominating set if the subgraph induced by S is connected. The minimum cardinality taken over all connected dominating sets of G is called the connected domination number of G, and is denoted by γc(G). In this paper, we investigate the Nordhaus-Gaddum type results for the connected domination number and its derived graphs like line graph, subdivision graph, power graph, block graph and total graph, and characterize the extremal graphs.

A Reliability Computational Algorithm for Reliability Block Diagram Using Factoring Method (팩토링 기법을 이용한 신뢰성 구조도의 신뢰도 계산 알고리즘)

  • Lie, Chang-Hoon;Kim, Myung-Gyu;Lee, Sang-Cheon
    • Journal of Korean Institute of Industrial Engineers
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    • v.20 no.3
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    • pp.3-14
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    • 1994
  • In this study, two reliability computational algorithms which respectively utilize a factoring method are proposed for a system represented by reliability block diagram. First, vertex factoring algorithm is proposed. In this algorithm, a reliability block diagram is considered as a network graph with vertex reliabilities. Second algorithm is mainly concerned with conversion of a reliabilities block diagram into a network graph with edge reliabilities. In this algorithm, the independence of edges is preserved by eliminating replicated edges, and in computing the reliability of a converted network graph, existing edge factoring algorithm is applied. The efficiency of two algorithms are compared for example systems with respect to computing times. The results shows that the second algorithm is shown to be more efficient than the first algorithm.

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A Study on the Induction Method of Transfer Function of Bond Graph using Mason's Rule (메이슨의 공식을 이용한 본드그래프의 전달함수 유도법에 관한 연구)

  • 한창수;오재응
    • Transactions of the Korean Society of Automotive Engineers
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    • v.6 no.4
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    • pp.66-75
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    • 1998
  • In many case of optimal design and sensitivity analysis, obtaining of transfer function between input and output variables is a difficult and time-consuming problem. The bond graph modeling is a method that is used for making it easy to analyze complex systems composed of mechanical and electrical parts. It gives us a simple and systematic tool to get state-space equations easily. And we can obtain the transfer function graphically using bond graph and Mason's rule. This paper shows how bond graphs are converted to block diagram and how Mason's rule is applied. And the simple direct method to obtain transfer function from bond graph is introduced. As a example, induction of transfer function of electric power steering composed of mechanical and electrical parts will be done.

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Ship block assembly modeling based on the graph theory (그래프 이론을 기반으로 한 선박의 블록 어셈블리 모델링)

  • Hag-Jong Jo;Kyu-Yeul Lee
    • Journal of the Society of Naval Architects of Korea
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    • v.38 no.2
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    • pp.79-86
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    • 2001
  • This study shows an attempt to generate an assembly sequence and its model for a ship block assembly using the graph theory and graph algorithms. To generate the ship block assembly, we propose four levels of the ship block assembly model such as "geometry mode1", "relational model", "sequential mode1", and "hierarchical model". To obtain the relational model, we used surface and surface intersection algorithm. The sequential model that represents a possible assembly sequence is made by using several graph algorithms from the relational model. The hierarchical model will be constructed from the sequential model in order to represent the block assembly tree and so forth. The purpose of the hierarchical model is to define an assembly tree and to generate the Bill Of Material(BOM). Lastly, the validity of the method proposed in this study is examined with application to ship block assembly models of a single type and double type according to four models mentioned above.

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Graph Convolutional - Network Architecture Search : Network architecture search Using Graph Convolution Neural Networks (그래프 합성곱-신경망 구조 탐색 : 그래프 합성곱 신경망을 이용한 신경망 구조 탐색)

  • Su-Youn Choi;Jong-Youel Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.649-654
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    • 2023
  • This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

EFFICIENT ALGORITHMS TO COMPUTE ALL ARTICULATION POINTS OF A PERMUTATION GRAPH

  • Pal, Madhumangal
    • Journal of applied mathematics & informatics
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    • v.5 no.1
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    • pp.141-152
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    • 1998
  • Based on the geometric representation an efficient al-gorithm is designed to find all articulation points of a permutation graph. The proposed algorithm takes only O(n log n) time and O(n) space where n represents the number of vertices. The proposed se-quential algorithm can easily be implemented in parallel which takes O(log n) time and O(n) processors on an EREW PRAM. These are the first known algorithms for the problem on this class of graph.

ONE-SIDED FATTENING OF THE GRAPH IN THE REAL PROJECTIVE PLANE

  • Choy, Jaeyoo;Chu, Hahng-Yun
    • Bulletin of the Korean Mathematical Society
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    • v.59 no.1
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    • pp.27-43
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    • 2022
  • The one-sided fattenings (called semi-ribbon graph in this paper) of the graph embedded in the real projective plane ℝℙ2 are completely classified up to topological equivalence. A planar graph (i.e., embedded in the plane), admitting the one-sided fattening, is known to be a cactus boundary. For the graphs embedded in ℝℙ2 admitting the one-sided fattening, unlike the planar graphs, a new building block appears: a bracelet along the Möbius band, which is not a connected summand of the oriented surfaces.

Crack detection in concrete slabs by graph-based anomalies calculation

  • Sun, Weifang;Zhou, Yuqing;Xiang, Jiawei;Chen, Binqiang;Feng, Wei
    • Smart Structures and Systems
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    • v.29 no.3
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    • pp.421-431
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    • 2022
  • Concrete slab cracks monitoring of modern high-speed railway is important for safety and reliability of train operation, to prevent catastrophic failure, and to reduce maintenance costs. This paper proposes a curvature filtering improved crack detection method in concrete slabs of high-speed railway via graph-based anomalies calculation. Firstly, large curvature information contained in the images is extracted for the crack identification based on an improved curvature filtering method. Secondly, a graph-based model is developed for the image sub-blocks anomalies calculation where the baseline of the sub-blocks is acquired by crack-free samples. Once the anomaly is large than the acquired baseline, the sub-block is considered as crack-contained block. The experimental results indicate that the proposed method performs better than convolutional neural network method even under different curvature structures and illumination conditions. This work therefore provides a useful tool for concrete slabs crack detection and is broadly applicable to variety of infrastructure systems.