• Title/Summary/Keyword: simulated network

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A Study on Multiple Target Tracking Using Self-Organizing Neural Network (자기조직화 신경망을 이용한 다중 표적 추적에 관한 연구)

  • 서창진;김광백
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.6
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    • pp.1304-1311
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    • 2003
  • Target tracking in a real world situation is difficult problem because of continuous variations in images, huge amounts of data, and high processing speed demands. The problem becomes even harder in the case of sea background. This paper presents an initial study of neural network based method for target detection and tracking in cluttering environment. The approach uses a combination of differential motion analysis, Kohonen self-organizing network and region growing method. The network is capable of detecting the mass-centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment showed promising results.

A Study on Performance Evaluation of Efficient Vehicular Ad-Hoc Network in Road Traffic (도로 사정에 따른 효율적인 자동차 애드 혹망의 성능평가에 관한 연구)

  • Cho, Ok-Lae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.3
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    • pp.593-600
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    • 2007
  • In this paper, we composed several road network and evaluated the network for the performance of the network with protocols. The protocols we applied were the MANET routing protocols such as AODV(Ad-hoc On-Demand Distance Vector) and DSR(Dynamic Source Routing) protocols. Generally, the AODV performs better than the DSR. However, in my ad-hoc vehicular network, the performance of the DSR is the better than the AODV when there are more vehicles in the road environment than there are the less vehicles. For the simulation, we composed 4-lane road with vehicles and simulated in the OPNET.

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A Study on the Development of Robust control Algorithm for Stable Robot Locomotion (안정된 로봇걸음걸이를 위한 견실한 제어알고리즘 개발에 관한 연구)

  • Hwang, Won-Jun;Yoon, Dae-Sik;Koo, Young-Mok
    • Journal of the Korean Society of Industry Convergence
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    • v.18 no.4
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    • pp.259-266
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    • 2015
  • This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.

Performance Evaluation of Transmitting Brainwave Signals in Ad-Hoc Network at Medical Center (의료센터의 애드혹망에서 뇌파전송 성능평가)

  • Jo, Jun-Mo
    • The Journal of the Korea Contents Association
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    • v.10 no.12
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    • pp.216-222
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    • 2010
  • To improve the quality of life, wireless ad-hoc network technologies are considered as one of the key research areas in computer science and healthcare application industries. The ubiquitous healthcare systems also provide alerting mechanisms against ill conditions in real time. This minimizes the need for care-givers and helps the chronically ill and elderly to survive. For the application of the system, supporting the efficient and proper network system is essential. So in this paper, I suggest some hospital network environments including patient mobile nodes continuously sending brainwaves to the server of the hospital area. Finally, the network systems are simulated by OPnet simulator and evaluate the performance among various mobility of the mobile nodes and topologies of the network for the efficient system.

Modeling of in Silico Microbe System based on the Combination of a Hierarchical Regulatory Network with Metabolic Network (계층적 유전자 조절 네트워크와 대사 네트워크를 통합한 가상 미생물 시스템의 모델링)

  • Lee, Sung-Gun;Han, Sang-Il;Kim, Kyung-Hoon;Kim, Young-Han;Hwang, Kyu-Suk
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.10
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    • pp.843-850
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    • 2005
  • FBA(flux balance analysis) with Boolean rules for representing regulatory events has correctly predicted cellular behaviors, such as optimal flux distribution, maximal growth rate, metabolic by-product, and substrate concentration changes, with various environmental conditions. However, until now, since FBA has not taken into account a hierarchical regulatory network, it has limited the representation of the whole transcriptional regulation mechanism and interactions between specific regulatory proteins and genes. In this paper, in order to solve these problems, we describe the construction of hierarchical regulatory network with defined symbols and the introduction of a weight for representing interactions between symbols. Finally, the whole cellular behaviors with time were simulated through the linkage of a hierarchical regulatory network module and dynamic simulation module including FBA. The central metabolic network of E. coli was chosen as the basic model to identify our suggested modeling method.

A Study on Multiple Target Tracking Using Adaptive Neural Network and Mosaic Background Extraction (모자이크 배경이미지 추출과 적응적 신경망을 이용한 다중 보행자 추적 시스템에 관한 연구)

  • 서창진;양황규
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.8
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    • pp.1802-1808
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    • 2003
  • In this paper, we propose a method about the extraction of the pedestrian tracking trajectory in the road and we used the method of mosaic background extraction and adaptive neural network for automatic pedestrian tracking system. We used mosaic background extraction to overcome ghost phenomenon. And we detected pedestrian using differential image analysis. We used adaptive neural network for multiple pedestrian tracking that non­rigid form moving. The ART2 network is capable of detecting the mass­centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment show promising results.

Quality-Enhancement Technique on Video telephony over WCDMA Network (WCDMA망상에서 영상통화의 품질향상 기법)

  • Kim, Yo-Han;Kwak, Hyong-Won;Shin, Ji-Tae
    • Journal of Broadcast Engineering
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    • v.13 no.1
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    • pp.25-33
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    • 2008
  • Video telephony is a representative service in 3G mobile network. And there have been efforts to improve quality of video telephony service in different fields. In Korea, the leading mobile service provider SKTelecom and KTF service the WCDMA network as 3G mobile network. Now, more than a million people is using the network. In this paper, we study about video telephony over WCDMA network. and propose error minimizing algorithm using cross-layer adaptation between physical layer and video codec. We simulated 3G-324M protocol with MPEG-4 video codec, and simulation results show suggested algorithm improve packet transmission rate for improving quality of video telephony service.

Eager Data Transfer Mechanism for Reducing Communication Latency in User-Level Network Protocols

  • Won, Chul-Ho;Lee, Ben;Park, Kyoung;Kim, Myung-Joon
    • Journal of Information Processing Systems
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    • v.4 no.4
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    • pp.133-144
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    • 2008
  • Clusters have become a popular alternative for building high-performance parallel computing systems. Today's high-performance system area network (SAN) protocols such as VIA and IBA significantly reduce user-to-user communication latency by implementing protocol stacks outside of operating system kernel. However, emerging parallel applications require a significant improvement in communication latency. Since the time required for transferring data between host memory and network interface (NI) make up a large portion of overall communication latency, the reduction of data transfer time is crucial for achieving low-latency communication. In this paper, Eager Data Transfer (EDT) mechanism is proposed to reduce the time for data transfers between the host and network interface. The EDT employs cache coherence interface hardware to directly transfer data between the host and NI. An EDT-based network interface was modeled and simulated on the Linux-based, complete system simulation environment, Linux/SimOS. Our simulation results show that the EDT approach significantly reduces the data transfer time compared to DMA-based approaches. The EDTbased NI attains 17% to 38% reduction in user-to-user message time compared to the cache-coherent DMA-based NIs for a range of message sizes (64 bytes${\sim}$4 Kbytes) in a SAN environment.

GRID BASED ENERGY EFFICIENT AND SECURED DATA TRANSACTION FOR CLOUD ASSISTED WSN-IOT

  • L. SASIREGA;C. SHANTHI
    • Journal of applied mathematics & informatics
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    • v.41 no.1
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    • pp.95-105
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    • 2023
  • To make the network energy efficient and to protect the network from malignant user's energy efficient grid based secret key sharing scheme is proposed. The cost function is evaluated to select the optimal nodes for carrying out the data transaction process. The network is split into equal number of grids and each grid is placed with certain number of nodes. The node cost function is estimated for all the nodes present in the network. Once the optimal energy proficient nodes are selected then the data transaction process is carried out in a secured way using malicious nodes filtration process. Therefore, the message is transmitted in a secret sharing method to the end user and this process makes the network more efficient. The proposed work is evaluated in network simulated and the performance of the work are analysed in terms of energy, delay, packet delivery ratio, and false detection ratio. From the result, we observed that the work outperforms the other works and achieves better energy and reduced packet rate.

Exploiting cognitive wireless nodes for priority-based data communication in terrestrial sensor networks

  • Bayrakdar, Muhammed Enes
    • ETRI Journal
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    • v.42 no.1
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    • pp.36-45
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    • 2020
  • A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.