• Title/Summary/Keyword: network diagram

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Current Source Disposition of Large-scale Network with Loop-reduction Drawing Technique (망축소작도법에 의한 대형회로망 전류원 처리)

  • Hwang, Jae-Ho
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • 제49권5호
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    • pp.278-286
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    • 2000
  • A new large-scale network geometric analysis is introduced. For a large-scale circuit, it must be analyzed with a geometric diagram and figure. So many equations are induced from a geometric loop-node diagram. The results are arranged into a simple matrix, of course. In case of constructing a network diagram, it is not easy to handle voltage and current sources together. Geometric loop analysis is related to voltage sources, and node analysis is to current sources. The reciprocal transfer is possible only to have series or parallel impedance. If not having this impedance, in order to obtain equivalent circuit, many equations must be derived. In this paper a loop-reduction method is proposed. With this method current source branch is included into the other branch, and disappears in circuit diagram. So the number of independent circuit equations are reduced as much as that of current sources. The number is not (b-n+1), but (b-n+1-p). Where p is the number of current sources. The reduction procedure is verified with a geometric principle and circuit theory. A resultant matrix can be constructed directly from this diagram structure, not deriving circuit equations. We will obtain the last results with the help of a computer.

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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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    • 제20권3호
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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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Writing ADM Network Diagram of Frame Work for the Precast Concrete Public Apartment Building Construction Management (보-기둥구조 PC공동주택 시공관리를 위한 골조공사 ADM공정표 작성)

  • Kim, Ki-Ho;Kim, MIn-Jun;Kim, Jin-Won;Lee, Dong-Gun;Sohn, Jeong-Rak;Lee, Bum-Sik
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 한국건축시공학회 2022년도 가을 학술논문 발표대회
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    • pp.221-222
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    • 2022
  • In this study, the work flow of the construction process was analyzed based on construction monitoring for a building of the middle size beam-column system Precast Concrete(PC) apartment building supplied by LH, and the Arrow Daigram Method(ADM) network diagram of its construction was written. The results of this study are judged to be able to improve productivity by using the PC structure apartment building construction plan to calculate a reasonable construction period and prepare a process management method for the PC structure frame construction.

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Relationship Analysis of Field Work in Beam-Column System Frame Work of the Precast Concrete Public Apartment Building (보-기둥구조 PC공동주택 골조공사 작업관계 분석)

  • Kim, Ki-Ho;Kim, Jin-Won;Kim, MIn-Jun;Lee, Dong-Gun;Sohn, Jeong-Rak;Lee, Bum-Sik
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 한국건축시공학회 2022년도 가을 학술논문 발표대회
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    • pp.41-42
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    • 2022
  • This study analyzed the process related to the linkage between on-site work targeting the middle size Precast Concrete(PC) public apartment building with beam-column system and prepared on-site works flow relationship diagram in which the wet process consists of core Critical Path(CP) to prepare a network diagram of the Precedence Diagram Method(PDM). Through this study, it is expected that it will be possible to maximize the project management capability by suggesting a method to minimize risk factors and the optimized process management of the beam-column system PC public apartment building.

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A Study on 'Digital Diagram' for Creating Architectural Forms (건축 형태생성을 위한 디지털 다이어그램에 관한 연구)

  • Kang Hoon
    • Korean Institute of Interior Design Journal
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    • 제15권4호
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    • pp.147-155
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    • 2006
  • Recently, because of the rapid remarkable development of the digital media, contemporary society is continuously extending and changing over the limitation of the human recognition. But in the field of architectural form creation, a diagram used in the design process of the past is not enough to reflect a complication, contingent and multiple quality of these contemporary society. So, to reveal the rhizomorphous and non-hierarchial qualify of the contemporary digital network society, architecture became necessary to use the diagram with digital media which have various possibilities to present architect's abstract images that the diagram of the past couldn't do. Therefore, this study proposes that the process for creating architectural form with the digital diagram be a alternative to conquest the limits of contemporary architecture, so it present the complicate and contingent quality of contemporary society. Furthermore, it examines the quality and possibility of the diagram by understanding the creation and transformation of the digital diagram, and how to apply to the actual architecture process of the creating form.

Anti-air Unit Learning Model Based on Multi-agent System Using Neural Network (신경망을 이용한 멀티 에이전트 기반 대공방어 단위 학습모형)

  • Choi, Myung-Jin;Lee, Sang-Heon
    • Journal of the Korea Institute of Military Science and Technology
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    • 제11권5호
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    • pp.49-57
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    • 2008
  • In this paper, we suggested a methodology that can be used by an agent to learn models of other agents in a multi-agent system. To construct these model, we used influence diagram as a modeling tool. We present a method for learning models of the other agents at the decision nodes, value nodes, and chance nodes in influence diagram. We concentrated on learning of the other agents at the value node by using neural network learning technique. Furthermore, we treated anti-air units in anti-air defense domain as agents in multi. agent system.

k-NN Query Processing Algorithm based on the Matrix of Shortest Distances between Border-point of Voronoi Diagram (보로노이 다이어그램의 경계지점 최소거리 행렬 기반 k-최근접점 탐색 알고리즘)

  • Um, Jung-Ho;Chang, Jae-Woo
    • Journal of Korea Spatial Information System Society
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    • 제11권1호
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    • pp.105-114
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    • 2009
  • Recently, location-based services which provides k nearest POIs, e.g., gas stations, restaurants and banks, are essential such applications as telematics, ITS(Intelligent Transport Systems) and kiosk. For this, the Voronoi Diagram k-NN(Nearest Neighbor) search algorithm has been proposed. It retrieves k-NNs by using a file storing pre-computed network distances of POIs in Voronoi diagram. However, this algorithm causes the cost problem when expanding a Voronoi diagram. Therefore, in this paper, we propose an algorithm which generates a matrix of the shortest distance between border points of a Voronoi diagram. The shortest distance is measured each border point to all of the rest border points of a Voronoi Diagram. To retrieve desired k nearest POIs, we also propose a k-NN search algorithm using the matrix of the shortest distance. The proposed algorithms can m inim ize the cost of expanding the Voronoi diagram by accessing the pre-computed matrix of the shortest distances between border points. In addition, we show that the proposed algorithm has better performance in terms of retrieval time, compared with existing works.

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TMUML: A Singular TM Model with UML Use Cases and Classes

  • Al-Fedaghi, Sabah
    • International Journal of Computer Science & Network Security
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    • 제21권6호
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    • pp.127-136
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    • 2021
  • In the systems and software modeling field, a conceptual model involves modeling with concepts to support development and design. An example of a conceptual model is a description developed using the Unified Modeling Language (UML). UML uses a model multiplicity formulation approach, wherein a number of models are used to represent alternative views. By contrast, a model singularity approach uses only a single integrated model. Each of these styles of modeling has its strengths and weaknesses. This paper introduces a partial solution to the issue of multiplicity vs. singularity in modeling by adopting UML use cases and class models into the conceptual thinging machine (TM) model. To apply use cases, we adopt the observation that a use-case diagram is a description that shows the internal structure of the part of the system represented by the use case in addition to being useful to people outside of the system. Additionally, the UML class diagram is recast in TM representation. Accordingly, we develop a TMUML model that embraces the TM specification of the UML class diagram and the internal structure extracted from the UML use case. TMUML modeling introduces some of the advantages that have made UML a popular modeling language to TM modeling. At the same time, this approach supplies UML with partial model singularity. The paper details experimentation with TMUML using examples from the literature. Our results indicate that mixing UML with other models could be a viable approach.

A Study on the Neural Network Diagnostic System for Rotating Machinery Failure Diagnosis (신경망을 이용한 회전축의 이상상태 진단에 관한 연구)

  • 유송민;박상신
    • Tribology and Lubricants
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    • 제16권6호
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    • pp.461-468
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    • 2000
  • In this study, a neural network based diagnostic system of a rotating spindle system supported by ball bearings was introduced. In order to create actual failure situations, two exemplary abnormal status were made. Out of several possible data source locations, ten measurement spots were chosen. In order to discriminate multiple abnormal status, a neural network system was introduced using back propagation algorithm updating connecting weight between each nodes. In order to find the optimal structure of the neural network system reducing the information sources, magnitude of the weight of the network was referred. Hinton diagram was used to visually inspect the least sensitive weight connecting between input and hidden layers. Number of input node was reduced from 10 to 7 and prediction rate was increased to 100%.