• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.709-716
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• 2005

As a way to build more efficient and intelligent container cranes for todays hub ports, communication networks are used to interconnect numerous sensors, actuators, controllers, and operator switches and consoles that are spatially distributed over a crane. Various signals such as sensor values and operator's commands are digitized and broadcast on the network instead of using separate wiring cables. This not only makes the design and manufacturing of a crane more efficient, but also easier implementation of intelligent control algorithms. This paper presents the performance evaluation of CAN(Controller Area Network), TTP(Time Triggered Protocol) and Byteflight that can be used for cranes. Through discrete event simulation, several important quantitative performance factors such as the probability of a transmission failure, average system delay (data latency) and maximum system delay have been evaluated.

• Proceedings of the KSR Conference
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• 2003.10c
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• pp.659-665
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• 2003

This paper presents a Train Communication Network simulator (TCNS) that can be used to evaluate the performance of TCN. TCN was accepted as the standard of the protocol for the communication network in trains. We carry out some simulation tests using the TCNS to show practical uses of the simulator. Results of some simulation tests are also reported. This paper presents a Train Communication Network simulator(TCNS) that can be used to evaluate the performance of TCN. TCN was accepted as the standard of the protocol for the communication network in trains. TCN of fieldbus was adopted as international standardization IEC 61375 in 1999. It has been operating on G7 train in korea. This paper developed TCNS(Train Communication Network simulator) as a simulator for performance evaluation. We can verify TCNS for preventing many kinds of occurring problems between the devices in data-communication. This study was developed TCNS as a simulator for the performance evaluation. We analyzed correlation between token, transmission data per paket and transmission speed of bus, through the TCNS, also analyzed result according to error rate of TCN. We carry out some simulation tests using the TCNS to show practical uses of the simulator. Results of some simulation tests are also reported.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.179-185
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• 2015

In this paper, we research the IPTV that is the convergence technique of TV and network technique and performed the performance evaluation of picture quality of IPTV in the situation of increasing the network traffic in the Internet environment. To do this, we constructed the mock Internet network similar to the real Internet environment and measured the quality of received video using V-Factor model according to the increase of network traffic, and analyzed the result of the experiment. Making use of the result of this paper for the threshold value of V-Factor, the measured factor of network performance, the measured factor of video performance in the watchable IPTV video quality.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.816-819
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• 1996

This paper focuses on development of simulation model for SAE J1850 and performance evaluation of a J1850 network. The simulation model has been developed by using discrete event simulation language. SAE J1850 is one of Class B network protocol for general data sharing applications. Through numerous simulation experiments, several important performance factors such as the probability of a successful transmission, average queue delay, and throughput have been evaluated.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.105-108
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• 2002

This paper analytical models of a centralized approach based on SNMP Protocol, distributed approach based on mobile agent, and mixed model which is tile existing mobile agent model in order to overcome large communication numbers of SNMP and accumulated data of mobile agent. And then, we compare and analyze these analytical models. Performance evaluation results show that performance of mobile agent and the mixed model is less sensitive to the network traffic and more profitable for complex network environment than that of SNMP.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.271-279
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• 2011

This paper draws performance results through comparing WMNs' methods when the WMNs are used in tunnel construction sites. There are many advantages of WMNs : lower cost, easy to network maintenance, robustness and reliability within RF-ranges. As a result, using the WMNs would be suitable to employ as a network infrastructure for the construction sites. This paper evaluates the performance of WMNs which we have installed in a tunnel construction. Through the performance results, we conclude the performance of data throughputs gets lower when we perform the network in tunnel environments. We make attempts WMNs' two major methods which are SISC(Single Interface with Single Channel) and MIMC(Multi Interface with Multi Channel) to figure out which method will be better for the construction sites. Through the experiments, the WMN based on the MIMC method was comparatively suitable in network performance aspect for the tunnel Sites.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.203-206
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• 2004

Recently home network has been developed in the field of Information Technology. And there are many protocols for smart home, such as Lonworks, Echonet, KNX, LnCP etc. However, the performance evaluation has not been nearly known between the protocols. Hence, this paper evaluates the performance of KNX by Konnex Association and LnCP(Living network Control Protocol) by LG Electronics. We developed simulation model using flowchart of KNX and LnCP and simulation scenario through analysis of message to be generated in the home network. Furthermore, we evaluate simulation performance, such as mean transmission delay, maximum transmission delay, and collision rate of both protocols.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1241-1248
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• 2006

In high reliability systems for industrial network such as railway signal system, fieldbus protocols have been known to satisfy the real-time and fault tolerant requirements. But, the application of fieldbus has been limited due to the high cost of hardware and software, and the difficulty in interfacing with multi-vendor products. Therefore, as an alternative to fieldbus, the computer network technology, especially Ethernet(IEEE 802.3), is being adapted to the industrial network. In this paper, we propose a switched Ethernet based railway signal system because of its very promising prospect for industrial application due to the elimination of uncertainties in the network operation. In addition, we propose the redundancy architecture for the reliability of network components. More specifically, this paper presents an analytical performance evaluation of switched Ethernet for railway signal system, and shows experimental evaluation of redundancy architecture.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.120-128
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• 1993

In this paper, an implementation of high-speed parallel processing system for neural network design on the multicomputer network is presented. Linear speedup expandability is increased by reducing the synchronization penalty and the communication overhead. Also, we presented the parallel processing models and their performance evaluation models for each of the parallization methods of the neural network. The results of the experiments for the character recognition of the neural network bases on the proposed system show that the proposed approach has the higher linear speedup expandability than the other systems. The proposed parallel processing models and the performance evaluation models could be used effectively for the design and the performance estimation of the neural network on the multicomputer network.

• The Journal of the Acoustical Society of Korea
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• v.41 no.1
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• pp.30-37
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• 2022

This paper compares and evaluates model performance from two perspectives according to the learning target and network structure for training Deep Neural Network (DNN)-based speech enhancement models in the frequency domain. In this case, spectrum mapping and Time-Frequency (T-F) masking techniques were used as learning targets, and a real network and a complex network were used for the network structure. The performance of the speech enhancement model was evaluated through two objective evaluation metrics: Perceptual Evaluation of Speech Quality (PESQ) and Short-Time Objective Intelligibility (STOI) depending on the scale of the dataset. Test results show the appropriate size of the training data differs depending on the type of networks and the type of dataset. In addition, they show that, in some cases, using a real network may be a more realistic solution if the number of total parameters is considered because the real network shows relatively higher performance than the complex network depending on the size of the data and the learning target.