• Journal of the Korean Professional Engineers Association
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• v.24 no.2
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• pp.127-136
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• 1991

The communication transmission engineering plays the most important role in electrical communications engineering. Recently, it has been making remarkable progress as an infrastructure supporting informationaged society. Specially, the start of television conference and service of high speed digital transmission can be said it is announcing a raising curtain of high speed broad band age. Together with high speed broad band service needs a capacity as much as several or several hundred times of telephone with one circuit, various kinds of service forms are anticipated to emerge, it is anticipated to give a big impact to the way of future communications network. At present, telecommunication network is transforming telephone voice information by analog technology into a flexible higher system disposable of a variety of information such as pictures or data other than telephone by the introduction of digital technology. Consequently, the development of the hereafter for the following respective technologies is desired.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.99-104
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• 1994

This paper proposes the method to process many pattern data 2-dimensionally at high speed in designing the physical of LSI. And this study shows that the switching network,which transmits pattern data between memory and processing elements at high speed on bidirection,has been designed using the barrel shifter and simulated with VHDL design system.

• Smart Structures and Systems
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• v.34 no.1
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• pp.17-23
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• 2024

Non-destructive methods are extensively utilized for assessing the integrity of rock bolts, with longitudinal wave speed being a crucial property for evaluating rock bolt quality. This research aims to propose a method for predicting reliable longitudinal wave velocities by leveraging various properties of the rock surrounding the rock bolt. The prediction algorithm employed is the Multilayer Neural Network (MNN), and the input properties includes elastic modulus, shear wave speed, compressive strength, compressional wave speed, mass density, porosity, and Poisson's ratio, totaling seven. The implementation of the MNN demonstrates high reliability, achieving a coefficient of determination of 0.996. To assess the impact of each input property on longitudinal wave speed, an importance score is derived using the random forest algorithm, with the elastic modulus identified as having the most significant influence. When the elastic modulus is the sole input parameter, the coefficient of determination for predicting the longitudinal wave speed is observed to be 0.967. The findings of this study underscore the reliability of selecting specific properties for predicting longitudinal wave speed and suggest that these insights can assist in identifying relevant input properties for rock bolt integrity assessments in future construction site experiments.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.429-435
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• 2018

In radar systems, FFT (fast Fourier transform) operation is necessary to obtain the range and velocity of target, and the design of an FFT processor which operates at high speed is required for real-time implementation. The perfect shuffle network is suitable for high-speed FFT processor. In particular, twice perfect shuffle network based on radix-4 is preferred for very high-speed FFT processor. Moreover, radar systems that requires various velocity resolution should support scalable FFT points. In this paper, we propose a 8~1024-point scalable FFT processor based on twice perfect shuffle network algorithm and present hardware design and implementation results. The proposed FFT processor was designed using hardware description language (HDL) and synthesized to gate-level circuits using $0.65{\mu}m$ CMOS process. It is confirmed that the proposed processor includes logic gates of 3,293K.

• Proceedings of the KSR Conference
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• 2009.05b
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• pp.527-532
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• 2009

Recently, Interior Permanent Magnet Machine(IPM) is widely used for traction motor in the high speed train. Due to the high efficiency and high power density of the IPM, it has lots of heat sources such as iron loss and copper loss. These heat sources can cause the demagnetization of permanent magnet, losses in output power and even irreversible defect of the IPM. To prevent the power loss caused by heat sources, the accurate thermal analysis has to be carried out. For the thermal analysis of the IPM, the thermal network is designed for this traction motor. The thermal analysis has executed at rated speed operation. The result of thermal network analysis can be used for the IPM design process.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.958-959
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• 2008

This paper is proposed a high performance speed control of the Interior Permanent Magnet Synchronous Motor through the Neural Network SV-PWM. SV-PWM is controlled using Neural Network control. SV-PWM can be maximum used maximum dc link voltage and is excellent control method due to characteristic to reducing harmonic more than others. Neural Network control has a advantage which can be robustly controlled. Simulation results are presented to show the validity of the proposed algorithm.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2021-2026
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• 2008

Recently, a high speed rail consists of many train coaches and power cars. For keeping the reliable train communication system with train coaches and power cars, train uses the OSI model(Open Systems Interconnection Basic Reference Model) and KTX(Korea Train eXpress) only uses the Physical to Transport layer of OSI model. This paper describes the analysis of CLNP(Connectionless Network Protocol) and ES-IS(End System to Intermediate System) protocols used in KTX for the network layer. CLNP is used to send data to other system and ES-IS protocol is used to route and send information between end systems and intermediate systems. Also this paper presents the protocol parsing program and implementation of Network layer.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.233-236
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• 2005

Our country compares with advanced nations by supply of super high speed network and information communication infra construction has gone well very. Many people by extension of on-line transaction and various internet services can exchange, or get information easily in this environment. But, virus or poisonous information used to Cyber terror such as hacking was included within such a lot of information and such poisonous information are threatening national security as well as individual's private life. There were always security and speed among a lot of items to consider networks equipment from these circumstance to now when develop and install in trade-off relation. In this paper, we present a high speed VPN Acceleration Board(VPN-AB) that balances both speed and security requirements of high speed network environment. Our VPN-AB supports two VPN protocols, IPsec and SSL. The protocols have a many cryptographic algorithms, DES, 3DES, AES, MD5, and SHA-1, etc.. The acceleration board process data packets into the system with In-line mode. So it is possible that VPN-AB processes inbound and outbound packets by 10Gbps. We use Nitrox-II CN2560 security processor VPN-AB is designed using that supports many hardware security modules and two SPI-4.2 interfaces to design VPN-AB.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.249-256
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control (FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, FLC and ANN controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.