• Proceedings of the KSR Conference
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• 2003.10b
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• pp.326-333
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• 2003

Railway system is consisted of resources such as rail-line, signalling system, and railcars. It is necessary to efficiently utilize these limited and expensive resources as much as possible up to given line capacity. So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. In this paper, we present systematic line capacity analysis model. The proposed model has three main components; TPS(tain performance simulator), PES(parameter evaluation simulator), LCS(line capacity simulator).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.698-701
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• 1996

A novel neural network control scheme is proposed to identify the inverse dynamic model of robot manipulator and to compensate for uncertainties in robot dynamics. The proposed controller is called reference compensation technique(RCT) by compensating at reference input trajectory. The proposed RCT scheme has many benefits due to the differences in compensating position and learning algorithm. Since the compensation is done outside the plant it can be applied to many control systems without modifying the inside controller. It performs well with low controller gain because the operating range of input values is small and the output of the neural network controller is amplified through the controller gain. The back-propagation algorithm is used to train and simulations of three link robot manipulator are carried out to prove the proposed controller's performances.

• 시스템엔지니어링워크숍
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• s.1
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• pp.9-14
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• 2003

The paper aims at presenting a systematic approach process and a method of requirement validation and system verification. Validation is applied during concept development to ensure conceptual validity, requirements validity, and design validity. Verification work is applied subsequent to the design work on test articles and early production items to produce evidence that the design solutions do, in fact, satisfy th requirements. In this paper, we present a requirements validation model and a system verification model. This models are applied to the development of TTX(Tilting Train Express)system with systems engineering tool, CORE.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.442-448
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• 2000

The conventional control of dynamic systems needs accurate mathematical modeling of control systems. But the modeling of dynamic systems require very complex computation process due to complex state equation and many control parameters. Accordingly this paper proposes a state space identification model of the dynamic system using neural networks. The Gauss-Newton method is used to train the proposed neural network and the effectiveness of proposed method is verified through the computer simulation of the Seesaw system identification problem.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1231-1238
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• 1999

This paper presents an approach for the optimal heating load Identification using Diagonal Recurrent Neural Networks(DRNN). In this paper, the DRNN captures the dynamic nature of a system and since it is not fully connected, training is much faster than a fully connected recurrent neural network. The architecture of DRNN is a modified model of the fully connected recurrent neural network with one hidden layer. The hidden layer is comprised of self-recurrent neurons, each feeding its output only into itself. In this study, A dynamic backpropagation (DBP) with delta-bar-delta learning method is used to train an optimal heating load identifier. Delta-bar-delta learning method is an empirical method to adapt the learning rate gradually during the training period in order to improve accuracy in a short time. The simulation results based on experimental data show that the proposed model is superior to the other methods in most cases, in regard of not only learning speed but also identification accuracy.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.971-972
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• 2008

In this paper, we present a novel method for classifying pornography images using adaptive skin detection. From an input image, we detect initial skin regions and construct an adaptive skin probability density model using color information for the detected skin regions. From the skin probability density model, we extract feature vectors and train the images using Support Vector Machine to classify pornography images.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.746-751
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• 1991

Deafs train articulation by observing mouth of a tutor. sensing tactually the notions of the vocal organs, or using speech training aids. Present speech training aids for deafs can measure only single speech ter, or display only frequency spectra in histogrm or pseudo-color. In this study, a speech training aids that can display subject's articulation in the form of a cross section of the vocal organs and other speech parameters together in a single system Is aimed to develop and this system makes a subject to know where to correct. For our objective, first, speech production mechanism is assumed to be AR model in order to estimate articulatory notions of the vocal tract from speech signal. Next, a vocal tract profile mode using LPC analysis is made up. And using this model, articulatory notions for Korean vowels are estimated and displayed in the vocal tract profile graphics.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.2
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• pp.69-77
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• 1993

Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.78-83
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• 2009

In this study, computer applied engineering (CAE) techniques are fully used to conduct structural and dynamic analyses of a whole huge wind turbine system including composite blades, tower and nacelle. For this study, computational fluid dynamics (CFD) is used to predict aerodynamic loads of the rotating wind-turbine blade model. Multi-body dynamic structural analyses are conducted based on the non-linear finite element method (FEM) by using super-element method for composite laminates blade. Three-dimensional finite element model of a wind turbine system is constructed including power train(main shaft, gear box, coupling, generator), bedplate and tower. The results for multi-body dynamic simulations on the wind turbine's critical operating conditions are presented in detail.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.4
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• pp.47-56
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• 1995

In this paper the model of the MQE-IMD-based neural trigger circuit is improved, where MQW-IMD is a new semiconductor device proposed and experimentally demonstrated by the author for the hardware implementation of the neural networks. The electron energy of AlXGa1-XAsbarrier is calculated by Ensemble Monte Carlo simulation according to the variation of Al mole fraction x and the applied electric field, whtich had been roughly estimated in the previous paper because of the difficulty to get the data. And in the consideration of the tunneling of the confined electrons within the quantum well the accuracy of the impact ionization rate is enhaned. Finally, the dependance of the frequency of pulse-train on the number of quantum wells can be calculated by modelling the effect of the distance of the induced positive charge from the cathode on the electric field at the cathode.