• 제목/요약/키워드: Boolean network

검색결과 54건 처리시간 0.025초

부울대수산법에 의한 회로망신뢰도의 계산법 (A Boolean Algebra Method for Calculation of Network Reliability)

  • 고경식;오영환
    • 대한전자공학회논문지
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    • 제13권6호
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    • pp.20-23
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    • 1976
  • 본논문에서는 통신회로망의 신뢰도를 계산하는데 부울대수를 이용하는 방법을 제시하였다. 한 회로의 두 접합점사이의 모든 단순통로가 주어지면 병렬연산이라고 명명되는 부울대수산법에 의하여 두 단점사이의 신뢰도가 기호적으로 계산된다. 이 방법은 회로가 방향성이거나 비방향성이거나 다 효과적이다. A boolean algebra method for computing the reliability in a communication network is prosented. Given the set of all simple paths between two nodes in a network, the terminal reliability can be symbolically computed by the Boolean operation which is named parallel operation. The method seems to be promising for both oriented and nonoriented network.

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Semi-Tensor Product 연산을 이용한 불리언 네트워크의 정적 제어 (Static Control of Boolean Networks Using Semi-Tensor Product Operation)

  • 박지숙;양정민
    • 전기학회논문지
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    • 제66권1호
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    • pp.137-143
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    • 2017
  • In this paper, we investigate static control of Boolean networks described in the framework of semi-tensor product (STP) operation. The control objective is to determine control input nodes and their logical values so as to stabilize the considered Boolean network to a desired fixed point or cycle. Using topology of Boolean networks such as incidence matrix and hub nodes, a set of appropriate control input nodes is selected, and based on STP operations, we assign constant control inputs so that the controlled network can converge to a prescribed fixed point or cycle. To validate applicability of the proposed scheme, we conduct a numerical study on the problem of determining control input nodes for a Boolean network representing hierarchical differentiation of myeloid progenitors.

다변수 출력 함수에서 공통 논리식 추출 (A Boolean Logic Extraction for Multiple-level Logic Optimization)

  • 권오형
    • 한국컴퓨터산업학회논문지
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    • 제7권5호
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    • pp.473-480
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    • 2006
  • 본 논문에서는 여러 개의 출력단을 갖는 논리회로에서 공통식을 찾는 방법을 제안하였다. 각각의 출력단위로 2개의 큐브로 구성된 몫을 찾고, 이 몫들 간의 쌍을 이용해서 부울 공통식을 찾는 방법을 보였다. 실험 결과로 2개의 큐브만을 이용한 공통식 산출만으로 전체 논리회로의 크기를 줄이는 데 효과가 있음을 SIS1.2 결과와 비교하여 보였다.

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Parameter identifiability of Boolean networks with application to fault diagnosis of nuclear plants

  • Dong, Zhe;Pan, Yifei;Huang, Xiaojin
    • Nuclear Engineering and Technology
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    • 제50권4호
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    • pp.599-605
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    • 2018
  • Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

Inference of Gene Regulatory Networks via Boolean Networks Using Regression Coefficients

  • Kim, Ha-Seong;Choi, Ho-Sik;Lee, Jae-K.;Park, Tae-Sung
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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    • pp.339-343
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    • 2005
  • Boolean networks(BN) construction is one of the commonly used methods for building gene networks from time series microarray data. However, BN has two major drawbacks. First, it requires heavy computing times. Second, the binary transformation of the microarray data may cause a loss of information. This paper propose two methods using liner regression to construct gene regulatory networks. The first proposed method uses regression based BN variable selection method, which reduces the computing time significantly in the BN construction. The second method is the regression based network method that can flexibly incorporate the interaction of the genes using continuous gene expression data. We construct the network structure from the simulated data to compare the computing times between Boolean networks and the proposed method. The regression based network method is evaluated using a microarray data of cell cycle in Caulobacter crescentus.

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논리회로 기능검사를 위한 입력신호 산출 (Test pattern Generation for the Functional Test of Logic Networks)

  • 조연완;홍원모
    • 대한전자공학회논문지
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    • 제13권3호
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    • pp.1-6
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    • 1976
  • 이 논문에서는 Boolean difference를 이용하여 combinational 및 sequential 논리회로에서 발생하는 기능적인 고장에 대한 test pattern을 얻는 방법을 연구하였다. 이 방법은 test pattern을 얻고자 하는 회로의 Boolean 함수의 Boolean difference를 계산하므로써 체계적으로 test pattern을 얻는 절차를 보여주고 있다. 컴퓨터에 의한 실험결과에 의하며 이 방법은 combinational 회로 및 asynchronous sequential 회로에 적합하며, clock이 있는 flip flop을 적당히 모형화함으로서 이 방법을 synchronous sequential회로에도 적용할 수 있음이 입증되었다. In this paper, a method of test pattern generation for the functional failure in both combinational and sequentlal logic networks by using exterded Boole an difference is proposed. The proposed technique provides a systematic approach for the test pattern generation procedure by computing Boolean difference of the Boolean function that represents the Logic network for which the test patterns are to be generated. The computer experimental results show that the proposed method is suitable for both combinational and asynchronous sequential logic networks. Suitable models of clocked flip flops may make it possible for one to extend this method to synchronous sequential logic networks.

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Reverse Engineering of a Gene Regulatory Network from Time-Series Data Using Mutual Information

  • Barman, Shohag;Kwon, Yung-Keun
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2014년도 추계학술발표대회
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    • pp.849-852
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    • 2014
  • Reverse engineering of gene regulatory network is a challenging task in computational biology. To detect a regulatory relationship among genes from time series data is called reverse engineering. Reverse engineering helps to discover the architecture of the underlying gene regulatory network. Besides, it insights into the disease process, biological process and drug discovery. There are many statistical approaches available for reverse engineering of gene regulatory network. In our paper, we propose pairwise mutual information for the reverse engineering of a gene regulatory network from time series data. Firstly, we create random boolean networks by the well-known $Erd{\ddot{o}}s-R{\acute{e}}nyi$ model. Secondly, we generate artificial time series data from that network. Then, we calculate pairwise mutual information for predicting the network. We implement of our system on java platform. To visualize the random boolean network graphically we use cytoscape plugins 2.8.0.

랜덤 불리언 네트워크 모델을 이용한 되먹임 루프가 네트워크 강건성에 미치는 영향 (The Effects of Feedback Loops on the Network Robustness by using a Random Boolean Network Model)

  • 권영근
    • 한국정보과학회논문지:시스템및이론
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    • 제37권3호
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    • pp.138-146
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    • 2010
  • 생체네트워크는 여러 종류의 환경 변화에 매우 강건하다고 알려져 있지만 그 메커니즘은 아직 밝혀지지 않고 있다. 본 논문에서는 랜덤 네트워크에 비해 생체네트워크에 되먹임 루프가 매우 많이 존재한다는 구조적 특징을 발견하고 그것이 네트워크의 강건성에 어떤 영향을 미치는지를 살펴보았다. 이를 위해 불리언 네트워크 모델을 이용하여 네트워크 강건성을 적절하게 측정하는 방법을 정의하고 많은 불리언 네트워크에 대해서 시뮬레이션하였다. 그 결과, 불리언 네트워크에서 되먹임 루프의 개수가 증가하면 고정점 끌개의 개수는 거의 변화가 없지만 유한순환 끌개의 개수는 크게 줄어든다는 사실을 밝혔다. 또한, 되먹임 루프의 개수가 증가함에 따라 고정점 끌개로 수렴하는 거대한 끌개 영역이 생성됨을 보였다. 이러한 사실들은 매우 많은 수의 되먹임 루프가 네트워크의 강건성을 높이는 데 중요한 요인임을 설명한다.

Feature-Based Multi-Resolution Modeling of Solids Using History-Based Boolean Operations - Part I : Theory of History-Based Boolean Operations -

  • Lee Sang Hun;Lee Kyu-Yeul;Woo Yoonwhan;Lee Kang-Soo
    • Journal of Mechanical Science and Technology
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    • 제19권2호
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    • pp.549-557
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    • 2005
  • The requirements of multi-resolution models of feature-based solids, which represent an object at many levels of feature detail, are increasing for engineering purposes, such as analysis, network-based collaborative design, virtual prototyping and manufacturing. To provide multi-resolution models for various applications, it is essential to generate adequate solid models at varying levels of detail (LOD) after feature rearrangement, based on the LOD criteria. However, the non-commutative property of the union and subtraction Boolean operations is a severe obstacle to arbitrary feature rearrangement. To solve this problem we propose history-based Boolean operations that satisfy the commutative law between union and subtraction operations by considering the history of the Boolean operations. Because these operations guarantee the same resulting shape as the original and reasonable shapes at the intermediate LODs for an arbitrary rearrangement of its features, various LOD criteria can be applied for multi-resolution modeling in different applications.

IMAGE ENCRYPTION THROUGH THE BIT PLANE DECOMPOSITION

  • Kim, Tae-Sik
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제11권1호
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    • pp.1-14
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    • 2004
  • Due to the development of computer network and mobile communications, the security in image data and other related source are very important as in saving or transferring the commercial documents, medical data, and every private picture. Nonetheless, the conventional encryption algorithms are usually focusing on the word message. These methods are too complicated or complex in the respect of image data because they have much more amounts of information to represent. In this sense, we proposed an efficient secret symmetric stream type encryption algorithm which is based on Boolean matrix operation and the characteristic of image data.

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