• 제목/요약/키워드: Network analysis method

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신경회로망과 경계요소법을 이용한 원공에서 파생하는 2차원 탄성균열의 응력세기계수 예측 모델링 (The Prediction Modelling on the Stress Intensity Factor of Two Dimensional Elastic Crack Emanating from the Hole Using Neural Network and Boundary element Method)

  • 윤인식;이원
    • 대한기계학회논문집A
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    • 제25권3호
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    • pp.353-361
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    • 2001
  • Recently the boundary element method has been developed swiftly. The boundary element method is an efficient and accurate means for analysis of two dimensional elastic crack problems. This paper is concerned with the evaluation and the prediction of the stress intensity factor(SIF) for the crack emanating from the circular hole using boundary element method-neural network. The SIF of the crack emanating from the hole was calculated by using boundary element method. Neural network is used to evaluate and to predict SIF from the results of boundary element method. The organized neural network system (structure of four processing element) was learned with the accuracy 99%. The learned neural network system could be evaluated and predicted with the accuracy of 83.3% and 71.4% (in cases of SIF and virtual SIF). Thus the proposed boundary element method-neural network is very useful to estimate the SIF.

HFC 가입자망 상향대역 신호분석에 관한 연구 (The Analysis on the Upsteam band Signal in the HFC Access Network)

  • 장문종;김선익;이진기
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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    • pp.142-144
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    • 2004
  • To provide more qualified data service on the HFC(Hybrid-Fiber Coaxial) access network, the channel characteristics of upstream transmission band should be carefully investigated and analysed. It will be easier to do network management if the monitoring system for noise measurement in the network is available, In this paper, noise analysis method and the frequency selection method in the upstream band for duplex transmission are suggested. And, Data aquisition device for the signal measurement Is implemented. With this network monitoring system, field test and the result from the collected data are described.

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연결망 분석도구를 이용한 크리스토퍼 알렉산더 패턴언어 활용 가능성에 관한 연구 (A Study on the Possibility to Use Christopher Alexander's Pattern Language by Using Network Analysis Tool)

  • 정성욱;김문덕
    • 한국실내디자인학회논문집
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    • 제25권3호
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    • pp.31-39
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    • 2016
  • This study is aimed to increase the possibility of using the Christopher Alexander's pattern language. The methodology of this study is (i) to analyze the pattern language by using the network analysis tool in order to understand the complicate network structure of the pattern language, and (ii) to apply the Alexander's method of using the pattern language by using the network analysis tool (Gephi) and to examine the feasibility of the network analysis tool as a tool for using the pattern language. Firstly, as a result of analysing the pattern language, (i) the pattern language classified by pattern number is distinguished by the patterns of towns, buildings and construction, among which the pattern of buildings plays a key function in the networks; (ii) the buildings functions a medium connecting between the towns and the construction; and (iii) the pattern language is divided into 6 sub-modules, through which the user can select a pattern. Secondly, the result of using the network analysis tool as a tool for using the pattern language (i) suggests the new method of using the pattern language by using the network analysis tool (Gephi); (ii) makes it possible to easily figure out the characteristics of the links between the patterns; and (iii) increases the completeness of the pattern language by making it easy to find out the sub-patterns in selecting a pattern.

A quantitative assessment method of network information security vulnerability detection risk based on the meta feature system of network security data

  • Lin, Weiwei;Yang, Chaofan;Zhang, Zeqing;Xue, Xingsi;Haga, Reiko
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권12호
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    • pp.4531-4544
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    • 2021
  • Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

SNS에서의 개선된 소셜 네트워크 분석 방법 (Improved Social Network Analysis Method in SNS)

  • 손종수;조수환;권경락;정인정
    • 지능정보연구
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    • 제18권4호
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    • pp.117-127
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    • 2012
  • 최근 온라인 소셜 네트워크 서비스(SNS)의 사용자가 크게 늘어나고 있으며 다양한 분야에서 SNS의 사용자 관계 구조 및 메시지를 분석하기 위한 연구를 진행하고 있다. 그러나 대부분의 소셜 네트워크 분석 방법들은 노드 사이의 최단 거리를 기초로 하고 있으므로 계산 시간이 오래 걸린다. 이는 점차 대형화 되어가는 SNS의 데이터를 여러 분야에서 활용하는데 걸림돌이 되고 있다. 이에 따라 본 논문에서는 SNS의 사용자 그래프에서 사용자간 최단거리를 빠르게 찾기 위한 휴리스틱 기반의 최단 경로 탐색 방법을 제안한다. 제안하는 방법은 1) 트리로 표현된 소셜 네트워크에서 시작 노드와 목표 노드를 설정한다. 그리고 2) 만약 목표 노드가 경사 트리의 단말에 있다면 경사 트리가 시작하는 노드를 임시 골 노드로 설정한다. 마지막으로 3) 연결의 차수를 평가값으로 하는 휴리스틱 기반 최단거리 탐색을 수행한다. 이렇게 최단거리를 탐색한 후 매개 중심성 분석(Betweenness Centrality) 및 근접 중심성(Closeness Centrality)를 계산한다. 제안하는 방법을 사용하면 소셜 네트워크 분석에서 가장 많은 시간이 필요한 최단거리 탐색을 빠르게 수행할 수 있으므로 소셜 네트워크 분석의 효율성을 기대할 수 있다. 본 논문에서 제안하는 방법을 검증하기 위하여 약 16만 명으로 구성된 SNS에서의 실제 데이터를 이용하여 매개 중심성 분석과 근접 중심성 분석을 수행하였다. 실험 결과, 제안하는 방법은 전통적 방식에 비하여 매개 중심성, 근접 중심성의 계산 시간이 각각 6.8배, 1.8배 더 빠른 결과를 보였다. 본 논문에서 제안한 방법은 소셜 네트워크 분석의 시간을 향상시켜 여러 분야에서 사회 현상 및 동향을 분석하는데 유용하게 활용될 수 있다.

Improved Characteristic Analysis of a 5-phase Hybrid Stepping Motor Using the Neural Network and Numerical Method

  • Lim, Ki-Chae;Hong, Jung-Pyo;Kim, Gyu-Tak;Im, Tae-Bin
    • KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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    • 제11B권2호
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    • pp.15-21
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    • 2001
  • This paper presents an improved characteristic analysis methodology for a 5-phase hybrid stepping motor. The basic approach is based on the use of equivalent magnetic circuit taking into account the localized saturation throughout the hybrid stepping motor. The finite element method(FEM) is used to generate the magnetic circuit parameters for the complex stator and rotor teeth and airgap considering the saturation effects in tooth and poles. In addition, the neural network is used to map a change of parameters and predicts their approximation. Therefore, the proposed method efficiently improves the accuracy of analysis by using the parameter characterizing localized saturation effects and reduces the computational time by using the neural network. An improved circuit model of 5-phase hybrid stepping motor is presented and its application is provided to demonstrate the effectiveness of the proposed method.

A semi-automatic cell type annotation method for single-cell RNA sequencing dataset

  • Kim, Wan;Yoon, Sung Min;Kim, Sangsoo
    • Genomics & Informatics
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    • 제18권3호
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    • pp.26.1-26.6
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    • 2020
  • Single-cell RNA sequencing (scRNA-seq) has been widely applied to provide insights into the cell-by-cell expression difference in a given bulk sample. Accordingly, numerous analysis methods have been developed. As it involves simultaneous analyses of many cell and genes, efficiency of the methods is crucial. The conventional cell type annotation method is laborious and subjective. Here we propose a semi-automatic method that calculates a normalized score for each cell type based on user-supplied cell type-specific marker gene list. The method was applied to a publicly available scRNA-seq data of mouse cardiac non-myocyte cell pool. Annotating the 35 t-stochastic neighbor embedding clusters into 12 cell types was straightforward, and its accuracy was evaluated by constructing co-expression network for each cell type. Gene Ontology analysis was congruent with the annotated cell type and the corollary regulatory network analysis showed upstream transcription factors that have well supported literature evidences. The source code is available as an R script upon request.

A Framework for implementing Knowledge Network using Social Network Analysis

  • Hwang, Hyun-Seok;Kim, Su-Yeon
    • 한국정보기술응용학회:학술대회논문집
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    • 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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    • pp.139-142
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    • 2005
  • Recently research interest in Knowledge Management (KM) has grown rapidly. Companies regard intellectual capital as important asset and strive to deploy KM in an organization to gain a competitive edge. Many organizations currently engage in knowledge management in order to leverage knowledge both within their organization and externally to their shareholders and customers. Most of the previous research related to KM are dedicated to investigate the role of information technology in extracting, capturing, sharing, coverting organizational knowledge. Knowledge workers, however, are paid less attention though they are the key players in KM activities such as knowledge creation, dissemination, capture and conversion. We regard knowledge workers as a major component of KM and starting point of understanding organizational knowledge activities. Therefore we adopt a method to understand and analyze knowldge workers' social relationships. In this paper we investigate Social Network Analysis (SNA) as a tool for analyzing knowledge network. We introduce the basic concept of SNA and suggest a framework for implementing knowledge network by explaining how SNA can be used for analyzing knowledge network. We also propose a numerical method for identifying knowledge workers using SNA after classifying knowledge workers. The suggested method is expected to help understanding key knowledge players within an organization.

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새로운 분할법에 의한 회로망해석 (Analysis of Large-Scale Network using a new Network Tearing Method)

  • 김준현;송현선
    • 한국통신학회논문지
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    • 제12권3호
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    • pp.267-275
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    • 1987
  • 회로망내에 존재하는 절점과 가지를 분할하여 몇 개의 부분회로망으로 나누고 분할절점에서의 전압 및 전류관계식으로부터 회로망방정식을 정식화하여 각 부분회로망 별로 독립적으로 처리함으로서 대형회로망을 효율적으로 해석할 수 있도록 하였다. 본 논문에서 제안한 분할회로망에 대한 방정식은 분할하기 전의 단일회로망에 대한 방정식과 비교할 때 절점의 순서만 재 배열한 결과가 되므로, 종래의 단일회로망에 대한 산법을 그대로 분할법에 적용할 수 있다. 또한, 어드미턴스행렬의 블록대각형구조를 이용한 병렬계산 알고리즘을 제시하였다.

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계통운영시스템 계통해석 프로그램 정확도 향상에 관한 연구 (A Study on the Enhancement of Accuracy of Network Analysis Applications in Energy Management Systems)

  • 조윤성
    • 조명전기설비학회논문지
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    • 제29권12호
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    • pp.88-96
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    • 2015
  • This paper describes a new method for enhancing the accuracy of network analysis applications in energy management systems. Topology processing, state estimation, power flow analysis, and contingency analysis play a key factor in the stable and reliable operation of power systems. In this respect, the aim of topology processing is to provide the electrical buses and the electrical islands with the actual state of the power system as input data. The results of topology processing is used to input of other applications. New method, which includes the topology error analysis based on inconsistency check, coherency check, bus mismatch check, and outaged device check is proposed to enhance the accuracy of network analysis. The proposed methodology is conducted by energy management systems and the Korean power systems have been utilized for the test systems.