• Title/Summary/Keyword: Network mapping

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System Level Network Simulation of Adaptive Array with Dynamic Handoff and Power Control (동적 핸드오프와 전력제어를 고려한 적응배열 시스템의 네트워크 시뮬레이션)

  • Yeong-Jee Chung;Jeffrey H. Reed
    • Journal of the Korea Society for Simulation
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    • v.8 no.4
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    • pp.33-51
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    • 1999
  • In this study, the system level network simulation is considered with adaptive array antenna in CDMA mobile communication system. A network simulation framework is implemented based on IS-95A/B system to consider dynamic handoff, system level network behavior, and deploying strategy into the overall CDMA mobile communication network under adaptive array algorithm. Its simulation model, such as vector channel model, adaptive beam forming antenna model, handoff model, and power control model, are described in detail with simulation block. In order to maximize SINR of received signal at antenna, Maximin algorithm is particularly considered, and it is computed at each simulation snap shot with SINR based power control and handoff algorithm. Graphic user interface in this system level network simulator is also implemented to define the simulation environments and to represent simulation results on real mapping system. This paper also shows some features of simulation framework and simulation results.

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Human Face Recognition used Improved Back-Propagation (BP) Neural Network

  • Zhang, Ru-Yang;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.21 no.4
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    • pp.471-477
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    • 2018
  • As an important key technology using on electronic devices, face recognition has become one of the hottest technology recently. The traditional BP Neural network has a strong ability of self-learning, adaptive and powerful non-linear mapping but it also has disadvantages such as slow convergence speed, easy to be traversed in the training process and easy to fall into local minimum points. So we come up with an algorithm based on BP neural network but also combined with the PCA algorithm and other methods such as the elastic gradient descent method which can improve the original network to try to improve the whole recognition efficiency and has the advantages of both PCA algorithm and BP neural network.

An ARP-disabled network system for neutralizing ARP-based attack

  • Battulga, Davaadorj;Jang, Rhong-Ho;Nyang, Dae-Hun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2016.10a
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    • pp.234-237
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    • 2016
  • Address Resolution Protocol (ARP) is used for mapping a network address to physical address in many network technologies. However, since ARP protocol has no security feature, it always abused by attackers for performing ARP-based attacks. Researchers presented many technologies to improve ARP protocol, but most of them require a high implementation cost or scarify the network performance for using ARP protocol securely. In this paper, we present an ARP-disabled network system to neutralize the ARP-based attacks. "ARP-disabled" means suppress the ARP messages like request, response and broadcast messages, but not the ARP table. In our system, ARP tables are used for managing static ARP entries without prior knowledge (e.g. IP, MAC list of client devices). This is possible because the MAC address was designed to be derived from IP address. In general, our system is safe from the ARP-based attacks even the attacker has a strong power. Moreover, we saved network bandwidth by disabling the ARP messages.

Network Coding Scheme using Orthogonality for Two-Way Relay Channel (양방향 중계 채널에서의 직교성을 이용한 네트워크 부호화 기법)

  • Ok, Jun-Ho;Lim, Jin-Soo;Shin, Dong-Joon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.3C
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    • pp.170-174
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    • 2011
  • We introduce the network coding which cooperative communication for two-way relay channel. We propose a new network coding scheme using orthogonality for cooperative communication system. The proposed network coding scheme via orthogonal mapping shows better BER performance because proposed scheme weakens error propagation which is disadvantage of DF scheme. And proposed scheme maintains same throughput compared to conventional scheme.

A Study on Rainfall Prediction by Neural Network (神經網理論에 의한 降雨豫測에 관한 硏究)

  • 오남선;선우중호
    • Water for future
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    • v.29 no.4
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    • pp.109-118
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    • 1996
  • The neural network is a mathematical model of theorized brain activity which attempts to exploit the parallel local processing and distributed storage properties. The neural metwork is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. A multi-layer neural network is constructed to predict rainfall. The network learns continuourvalued input and output data. Application of neural network to 1-hour real data in Seoul metropolitan area and the Soyang River basin shows slightly good predictions. Therefore, when good data is available, the neural network is expected to predict the complicated rainfall successfully.

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Fuzzy TAM Network Model Using SOM (SOM을 이용한 퍼지 TAM 네트워크 모델)

  • Hong, Jung-Pyo;Hwang, Seung-Gook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.642-646
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    • 2006
  • The fuzzy TAM(Topographical Attentive Mapping) network is a supervised method of pattern analysis which is composed of input layer, category layer, and output layer. But if we don't know the target value of the pattern, the network can not be trained. In this case, the target value can be replaced by a result induced by using an unsupervised neural network as the SOM (Self-organizing Map). In this paper, we apply the results of SOM to fuzzy TAM network and show its usefulness through the case study.

Comparison of Convolutional Neural Network Models for Image Super Resolution

  • Jian, Chen;Yu, Songhyun;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2018.06a
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    • pp.63-66
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    • 2018
  • Recently, a convolutional neural network (CNN) models at single image super-resolution have been very successful. Residual learning improves training stability and network performance in CNN. In this paper, we compare four convolutional neural network models for super-resolution (SR) to learn nonlinear mapping from low-resolution (LR) input image to high-resolution (HR) target image. Four models include general CNN model, global residual learning CNN model, local residual learning CNN model, and the CNN model with global and local residual learning. Experiment results show that the results are greatly affected by how skip connections are connected at the basic CNN network, and network trained with only global residual learning generates highest performance among four models at objective and subjective evaluations.

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Digital Collaborative Network Architecture Model Supported by Knowledge Engineering in Heritage Sites

  • Marcio Crescencio;Alexandre Augusto Biz;Jose Leomar Todesco
    • Journal of Smart Tourism
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    • v.4 no.1
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    • pp.19-29
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    • 2024
  • The objective of this article is to create a model of integrated management from the framework modeling of a digital collaborative network supported by knowledge engineering to make heritage site in the Brazil more effective. It is an exploratory and qualitative research with thematic analysis as technique of data analysis from the collaborative network, digital platform, world heritage, and tourism themes. The snowballing approach was chosen, and the mapping and classification of relevant studies was developed with the use of the spreadsheet tool and the Mendeley® software. The results show that the collaborative network model oriented towards strategic objectives should be supported by a digital platform that provides a technological environment that adds functionalities and digital platform services with the integration of knowledge engineering techniques and tools, enabling the discovery and sharing of knowledge in the collaborative network.

Implementation of a Framework for Location-aware Dynamic Network Provisioning (위치인지 능동 네트워크 제공을 위한 프레임워크 구현)

  • Nguyen, Huu-Duy;Nguyen, Van-Quyet;Nguyen, Giang-Truong;Kwon, Taeyong;Yeom, Sungwoong;Kim, Kyungbaek
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.133-135
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    • 2018
  • In these days, providing flexible and personalized network services subject to customers' requirements becomes an interesting issue for network service providers. Moreover, because each network service provider own finite network resources and infrastructure, dynamic network provisioning is essential to leverage the limited network resources efficiently and effectively for supporting personalized network services. Recently, as the population of mobile devices increases, the location-awareness becomes as important as the QoS-awareness to provision a network service dynamically. In this paper, we propose a framework for providing location-aware dynamic network services. This framework includes the web user interface for obtaining customers' requirements such as locations and QoS, the network generator for mapping the requested locations and network infrastructure, the network path calculator for selecting routes to meet the requested QoS and the network controller for deploying a prepared network services into SDN(Software-Defined Networking) enabled network infrastructure.

Design of the Automotive Gateway Based on a Mapping Table (매핑 테이블 기반의 자동차용 게이트웨이 설계)

  • Oh, Se-Chun;Kim, Eui-Ryong;Kim, Young-Gon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.12
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    • pp.1959-1968
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    • 2016
  • The recent automobiles, a number of ECU inside the vehicle has been used. Also, each ECU is connected to different types of networks in accordance with the characteristics. Therefore, efficient data exchange between discrete network has emerged as a very important element. The gateway is responsible for the ability to exchange data between discrete network. In this study, we propose the new gateway algorithm to provide the structure of the mapping table to improve the efficiency of data exchange between discrete network. Also it provides a structure of a new gateway algorithm with a function of adjusting the priority of the data to be transmitted to another network arbitrarily. Moreover, the proposed gateway structure may simultaneously convert the transmission data input from a particular network to multiple networks. Another advantage is easy to change the entire data structure only if we change the table structure in the gateway.