• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2286-2288
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• 2001

In this paper, a drive system of induction motor with high performance is realized on the viewpoint of the design and experiment, using the DSP (TMS320F240). The speed controller for induction motor drive system is designed on the basis of a neuro-fuzzy network. The neuro-fuzzy controller acts as a feed-forward controller that provides the right control input for the plant and accomplishes error back-propagation algorithm through the network. The proposed network is used to achieve the high speedy calculation of the space vector PWM (Pulse Width Modulation) and to build the neuro-fuzzy control algorithm, for the real-time control. The proposed neuro-fuzzy algorithm on the basis of DSP shows that experimental results have good performance for the precise speed control of an induction motor drive system. It is confirmed that the proposed controller could provide more improved control performance than conventional v/f vector controllers through the experiment.

• Journal of Welding and Joining
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• v.25 no.6
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• pp.64-70
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• 2007

Recently, several models to control weld quality, productivity and weld properties in arc welding process have been developed and applied. Also, the applied model to make effective use of the robotic GMA(Gas Metal Arc) welding process should be given a high degree of confidence in predicting the bead dimensions to accomplish the desired mechanical properties of the weldment. In this study, a development of the on-line learning neural network models that investigate interrelationships between welding parameters and bead width as well as apply for the on-line quality control system for the robotic GMA welding process has been carried out. The developed models showed an excellent predicted results comparing with the predicted ability using off-line learning neural network. Also, the system will extend to other welding process and the rule-based expert system which can be incorporated with integration of an optimized system for the robotic welding system.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.2
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• pp.57-64
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• 2002

We implemented two fast PC clusters using fast PCs and high speed network. First. we built the first generation of 16 PC cluster and have used it for real-time operation at Cheju Regional Meteorological Office. Next, we built the second generation of 16PC with dual CUs cluster which was efficiently improved based on performance analysis of the first generation of cluster. In this research we also analyzed performance of two different clusters, which have different CPUs and communication devices using the parallel model MM5 which has been used for the real-time weather forecasting.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.55-60
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• 2006

The proposed method uses FFT(Fast Fourier Transform) and neural networks in order to extract texts in real time. In general, text areas are found in the higher frequency domain, thus, can be characterized using FFT. The neural network are learned by character region(high frequency) and non character region(low frequency). The candidate text areas can be thus found by applying the higher frequency characteristics to neural network. Therefore, the final text area is extracted by verifying the candidate areas. Experimental results show a perfect candidate extraction rate and about 95% text extraction rate. The strength of the proposed algorithm is its simplicity, real-time processing by not processing the entire image.

• ETRI Journal
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• v.45 no.4
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• pp.650-665
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• 2023

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time were obtained from 900 households of single apartments. To detect outliers and missing values in smart meter data, a deep learning model, the autoencoder, consisting of a graph convolutional network and bidirectional long short-term memory network, was applied to the smart metering technique. Power management based on the smart metering technique was executed by multi-objective optimization in the presence of a battery storage system and an electric vehicle. The results of the power management employing the proposed smart metering technique indicate a reduction in electricity cost and amount of power supplied by the grid compared to the results of power management without anomaly detection.

• Journal of Navigation and Port Research
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• v.48 no.2
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• pp.116-124
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• 2024

Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.424-434
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• 2017

In industrial wireless sensor networks, many applications require integrated QoS supporting. This paper proposes a reliable protocol for real-time monitoring in industrial wireless sensor networks. Retransmission is well-known to recover the transmission failure, however, this might cause the time delay to violate the real-time requirement. The proposed protocol exploits broadcasting feature of wireless networks and the temporal opportunity concept. The opportunities to relay the data packets are shared by the broadcasting feature and the temporal opportunity concept maximize the number of candidates in communication. Simulation results show that the proposed protocol is superior to the existing real-time protocols in term of real-time service and reliability.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.43-48
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• 2004

RTP that is proposed supplement of real-time services on internet environment, as Real-time Transport Protocol, is the protocol that for the purpose of sending data of stream type. RTP and RTCP(Real-time Transport Control Protocol) basically work at the same time, RTCP serves with state information of network at present. RTP has important properties of a transport protocol that runs on end-to-end systems and provides demultiplexing. It also offer reliability and protocol-defined flow／congestion control that transport protocol like TCP can not provides. In this paper, we look around concept and construction of Differentiated sen1ice tint run on RTP and by setting parameters of packet transfer method be used CBQ(Class-Based Queuing) for packet transfer on Differentiated service, each service queue controls properly through packet scheduling method, such as WRR(Weighted Round Robin) and PRR(Packet-by-packet Round Robin) all service classes do not experience the starvation and confirm the performance through computer simulation to achieve fairly scheduling.

• Journal of IKEEE
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• v.2 no.2 s.3
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• pp.270-277
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• 1998

As the network technologies advance, the control systems progress from a centralized architecture to a distributed one. However, these control systems were designed mostly based on the general-purpose operating systems(OS) and have many problems for assurance of a real-time property required for plant processing fields. Therefore, the control systems far a plant process upon real-time OS hare been increased gradually. In this paper, the real-time OS emphasizes on the realization of real-time processing capability, reliability of real-time response, and multi-processing functionality which are prerequisites for a distributed control system. And on the basis of this OS, the number of executable loop and logic, the functions of main plant processing, was analyzed and its validity was also evaluated. The system in this paper was designed not to effect on processing data while online, and the time spent on switching was measured.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.301-304
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• 2013

In this paper, to improve the fast boot and soft real-time for the responsiveness in Qplus with relative evaluation rather than an absolute evaluation using validated to perform the services actually used. Qplus is included soft real-time, fast booting, and file system technology. There is a development board that mounted on an embedded Linux and Qplus. AV (Audio / Video) group communications is ported on the development board for soft real-time multimedia streaming services and to evaluate the performance of communication. We performed three major evaluation such as booting time measurement experiment, own performance measurement experiments for soft real-time measurement experiment, and performance measurement experiments for via the network communication performance evaluation. They are a practical Qplus performance evaluation and analysis.