• Title, Summary, Keyword: Network structure

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The Access Network Architecture for BcN Adapted (BcN 적합형 액세스네트워크 구조)

  • Lee, Sang-Moon
    • 한국정보통신설비학회:학술대회논문집
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    • pp.121-124
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    • 2007
  • This article describes a function and structure of access network equipment under BcN environment. Access network until now have constructed separately to offer voice, data service. However, simplifies network structure, function that can do traffic concentration, subscriber certification, individual charging, QoS according to service and routing is required in BcN. In this paper, compare method offering by separate system with existing access network and method that offer integrating function inside system for structure of suitable access network to BcN and search structure of access network equipment for desirable access network of hereafter. Composition of this paper is as following. In Chapter 2, establishment history and structure of access network until present. In Chaprte 3, define suitable requirement and functions to BcN. And compare structure for access net work that is new with present. Last Chapter 4, suggests direction of structure of BcN access network and concludes conclusion.

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A Method to Analyze the Structure of Interpersonal Trust Network in SNS (SNS 구성원 간 신뢰망 구조 분석방법)

  • Song, Hee Seok
    • Journal of Information Technology Applications and Management
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    • v.23 no.2
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    • pp.97-112
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    • 2016
  • Many studies have pointed out that trust is the most important component of social capital. Although there have been lots of attempts to measure level of trust between members of community, it is hard to find studies which examine trust from the standpoint of structural aspects. Because of the recent rapid growth of SNS and openness trend on members and their friendship information, it became possible to understand the structure of trust relationships among users in SNS. This study aims to facilitate interpersonal trust by comparing the structure of the trust network among social network users. For this purpose, it proposes a method to explore the structure of trust network and strategies to evolve toward more open structure. In experiments to distinguish structure of trust network with three social network communities, it is discovered that ADVOGATO has characteristics of open and collective network together whereas EPINION and FILMTRUST have collective and open characteristics respectively.

Study of Virtual Goods Purchase Model Applying Dynamic Social Network Structure Variables (동적 소셜네트워크 구조 변수를 적용한 가상 재화 구매 모형 연구)

  • Lee, Hee-Tae;Bae, Jungho
    • Journal of Distribution Science
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    • v.17 no.3
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    • pp.85-95
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    • 2019
  • Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

The Activation Plan of Chain Information Network And Efficent NDB Design (효율적인 NDB 설계 및 유통 정보 NETWORK 활성화 방안)

  • 남태희
    • KSCI Review
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    • v.1 no.2
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    • pp.73-94
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    • 1995
  • In this paper, design of efficient NDB(Network Data Base) for the activation plan of chain information network. The DB structure build up, logical structure, store structure, physical structure, the data express for one's record, and the express using linked in the releation of data. Also express as hierarchical model on the DSD(Data Structure Diagram) from the database with logical structure. Each node has express on record type, the linked in course of connective this type, the infuence have efficent of access or search of data, in the design for connection mutually a device of physical, design for database, and construction a form of store for logical. Also activation of chain information network of efficent, using POS(Point Of Sale) system in OSI(Open Systems Interconnection) environment for network standardization, and build up network a design for system.

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Analysis of Indeterminate Truss Structures by Element-Focused Network Approach (요소 중심의 네트워크 접근법을 이용한 부정정 트러스 구조 해석)

  • Han, Yicheol
    • Journal of The Korean Society of Agricultural Engineers
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    • v.58 no.3
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    • pp.13-19
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    • 2016
  • Element-focused network analysis method for truss structure is proposed. The propagation process of loads from external loads to connected other elements is similar to that of connections between nodes in accordance with attachment rule in a network. Here nodes indicate elements in a truss structure and edges represent propagated loads. Therefore, the flows of loads in a truss structure can be calculated using the network analysis method, and consequently the structure can also be analyzed. As a first step to analyze a truss structure as a network, we propose a local load transfer rule in accordance with the topology of elements, and then analyze the loads of the truss elements. Application of this method reveal that the internal loads and reactions caused by external loads can be accurately estimated. Consequently, truss structures can be considered as networks and network analysis method can be applied to further complex truss structures.

Nonlinear System Modelling Using Neural Network and Genetic Algorithm

  • Kim, Hong-Bok;Kim, Jung-Keun;Hwang, Seung-Wook;Ha, Yun-Su;Jin, Gang-Gyoo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.71.2-71
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    • 2001
  • This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...

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The Effect of Interpenetrating Polymer Network upon Tracking Resistance of Epoxy Composite Materials (에폭시 복합재료의 내트래킹성에 미치는 상호침입망목의 효과)

  • 김탁용;이덕진;손인환;김명호;김경환;김재환
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • pp.225-229
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    • 1996
  • In this study, in order to develop outdoor insulating materials, SIN(simultaneous interpenetrating polymer network) was introduced to Epoxy resin and the environment resistance was investigated. The single network structure specimen(E series) formed of Epoxy resin alone and simultaneous interpenetrating polymer network specimen (EM series) in which epoxy resin was taken as the first network and methyl methacrylate resin as the second network were manufactured. Ten kinds of specimens were manufacture by filler (SiO$_2$) content. SEM were utilized in order to confirm their network structure changes, and AC voltage dielectric strength was measured. Also, UV-test and tracking test were carried out investigate the environment resistance characteristic. Therefore the variations of network structure were happened as a result of SEM test, and it was confirmed that simultaneous interpenetrating polymer network specimens were more excellent than single network structure specimens.

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Uplinks Analysis and Optimization of Hybrid Vehicular Networks

  • Li, Shikuan;Li, Zipeng;Ge, Xiaohu;Li, Yonghui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.473-493
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    • 2019
  • 5G vehicular communication is one of key enablers in next generation intelligent transportation system (ITS), that require ultra-reliable and low latency communication (URLLC). To meet this requirement, a new hybrid vehicular network structure which supports both centralized network structure and distributed structure is proposed in this paper. Based on the proposed network structure, a new vehicular network utility model considering the latency and reliability in vehicular networks is developed based on Euclidean norm theory. Building on the Pareto improvement theory in economics, a vehicular network uplink optimization algorithm is proposed to optimize the uplink utility of vehicles on the roads. Simulation results show that the proposed scheme can significantly improve the uplink vehicular network utility in vehicular networks to meet the URLLC requirements.

The Modeling of Chaotic Nonlinear System Using Wavelet Based Fuzzy Neural Network

  • Oh, Joon-Seop;You, Sung-Jin;Park, Jin-Bae;Choi, Yoon-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • pp.635-639
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    • 2004
  • In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the modeling of chaotic nonlinear systems. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the modeling performance for chaotic nonlinear systems and compare it with those of the FNN and the WFM.

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Path Tracking Control Using a Wavelet Based Fuzzy Neural Network for Mobile Robots

  • Oh, Joon-Seop;Park, Yoon-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.1
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    • pp.111-118
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    • 2004
  • In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.