• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.8
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• pp.53-61
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• 1998

Dynamic characteristics of widely tunable SGDBR/SSGDBR laser diodes integrated with an electroabsorption modulator is inestigated using an improved large-signal timef-domain model. First, wide tunning properties of a SGDBR laser diode and a SSGDBR laser diode are analyzed respectively and compared with each other. And, intensity-modulation characteristics of a SGDBR laser diode incorprating an electroabsorption modulator are investigated. It is shown that an external modulation has the lower frequency chirp by 1/20 for almost same extinction ratios than a direct modulation, and a nearly transform-limited pulse train can be generated using the optical gating of an electroabsorption modulator.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.05a
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• pp.997-1002
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• 2002

Traditional prediction models have been developed with a fixed equation form based on the limited number of data and parameters. If new data is quite different from original data, then the model should update not only its coefficients but also its equation form. However, artificial neural network (ANN) does not need a specific equation form. Instead of that, it needs enough input-output data. Also, it can continuously re-train the new data, so that it can conveniently adapt to new data. Therefore, the purpose of this paper is to develop the I-PreConS (Intelligent system for PREdiction of CONcrete Strength using ANN) that provides in-place strength information of the concrete to facilitate concrete form removal and scheduling for construction.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.446-449
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• 2004

Traditional prediction models have been developed with a fixed equation from based on the limited number of data and parameters. If new data is quite different from original data, then the model should update not only its coefficients but also its equation form. However, artificial neural network dose not need a specific equation form. Instead of that, it needs enough input-output data. Also, it can continuously re-train the new data, so that it can conveniently adapt to new data. Therefore, the purpose of this study is to verify faith and application of prediction system of concrete strength using artificial neural networks through mock-up test.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.771-772
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• 2006

Recently, Interior Permanent Magnet Synchronous Motor(IPMSM) is widely used in the industry applications such as power train for hybrid vehicles and compressor motors of air-conditioner due to its high power density and wide speed range. In designing motors, pole slot combination should be chosen properly according to the use of the motor and driving method in the initial design stage, accordingly there have been many researches about pole slot combination. As a part of the studies, this paper presents a comparison of characteristics of concentrated winding IPMSM, such as back-emf, Total Harmonic Distortion(THD) and core losses for each pole slot combination. By comparing the characteristics of each model, this paper can be a guide or reference in determining pole slot combination in the initial design stage.

• Journal of the Korean Society of Safety
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• v.33 no.2
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• pp.145-151
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• 2018

In this study, the track-bridge interaction analysis was performed using an analytical model considering the track structure, thereby taking into account the linear conditions (R=650 m, cant variation $160{\pm}60mm$) and the dynamic characteristics of the bridge. As a result of the study, the allowable speed on the example bridge considered was calculated at 200 km/h based on vertical deflection, vertical acceleration, and irregularity in longitudinal level, but was also evaluated at 170km/h based on the coefficient of derailment, wheel load reduction, and lateral displacement of the rail head. It is considered desirable to set the speed 170km/h to the speed limit in order to secure the safety of both the bridge and the track. It is judged that there will be no problems with ensuring rail protection and train stability in the speed band.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.197-208
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• 2016

In this paper, we propose a method based on a convolutional neural network which is one of the deep neural network. So, we convert a malware code to malware image and train the convolutional neural network. In experiment with classify 9-families, the proposed method records a 96.2%, 98.7% of top-1, 2 error rate. And our model can classify 27 families with 82.9%, 89% of top-1,2 error rate.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2169-2170
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• 2011

This paper presents about the analysis on cost factor reduction using the life cycle cost model for motor block in the KTX-1. Until now, most life cycle cost of the system as a whole that has been studied. but in case of railway industry part, LCC studies are needed on the subsystem like a propulsion control system because subsystems are developed continuously localization. Therefore, In this paper presents cost breakdown structure for life cycle cost (LCC) estimation for localization development of propulsion control system (Motor Block) in high speed railway vehicle (KTX-1). Also to analysis LCC on motor block, it was analyzed physical breakdown structure (PBS) and preventive cost on propulsion control system in view of maintenance cost. Based on this, we describe life cycle cost on motor block of KTX-1.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.11
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• pp.2817-2824
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• 1994

A torque split type multi-pass CVT(MPC) system consiting of CVT and planetary gear train with 4 clutches was suggested to overcome the inherent inferior acceleration performance of CVT. Also, a shifting algorithm of MPC was suggested for the two driving modes : (1) power mode and (2) economy mode. By using the shifting algorithm and the MPC vehicle dynamic model, numerical simulations were performed to estimate the performance of the MPC vehicle. Simulation results showed that comparing the performance of the conventional 4-speed automatic transmission, an improvement in acceleration can be obtained by MPC for the power mode and 31% improvement in fuel economy for the economy mode.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.328-333
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• 2002

When vehicle travelling along the track which has irregularity such as vertical profile, dynamic forces arise at the Wheel/Rail contact patch by wheel/rail interaction. In particular short wavelength irregularities on dipped joint and small stiffness of connecting rail bring about intense wheel/rail dynamic effects at higher speed. In the paper, a new model for dipped joint rail is developed to study dynamic behavior of track. A cusp behavior on dipped joint was defined by its amplitude and decay factor, which was presented by FRA track classes. The result of case study are presented, which show wheel rail contact force in each track classes, train operation speed and bending flexible rigidity ratio of fishplates which are connecting the rail.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.385-390
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• 2009

This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).