• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.499-505
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• 2004

A Propulsion System of the CRW(Canard Rotor Wing) type UAV(Unmanned Aerial Vehicle) was composed of the turbojet engine to generate the propulsive exhaust gas, and the duct system including straight bent ducts, tip-jet nozzles, a master valve and a variable main nozzle for three flight modes such as lift/landing mode, low speed transition flight mode and high speed forward flight mode. In this study, in order to operate safely the propulsion system, the dynamic Performance behavior of the system was modeled and simulated using the SIMULIN $K^{ }$, which is the user-friendly GUI type dynamic analysis tool provided by MATLA $B^{ }$. In the transient performance model, the inter-component volume model was used. The performance analysis using the developed models was performed at various flight condition, valve angle positions and fuel flow schedules, and these results could set the safe flight mode transition region to satisfy the inlet temperature overshoot limitation as well as the compressor surge margin. Performance analysis results using the SIMULIN $K^{ }$ performance program were compared with them using the commercial program GSP.m GSP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.33-42
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• 2013

This paper presents a multihop range-free localization algorithm to estimate the physical location of a normal node with local connectivity information in anisotropic sensor networks. In the proposed algorithm, a normal node captures the detour degree of the shortest path connecting an anchor pair and itself by comparing the measured hop count and the expected hop count, and the node estimates the distances to the anchors based on the detour degree. The normal node repeats this procedure with all anchor combinations and pinpoints its location using the obtained distance estimates. The proposed algorithm requires fewer anchors and less communication overhead compared to existing range-free algorithms. We showed the superiority of the proposed algorithm over existing range-free algorithms through MATLA simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1558-1563
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• 2007

In this paper, phase-locked loop (PLL) of a combinational architecture consisting of an adaptive bandwidth and fractional-N is presented to improve performances and reduce the order of ${\Delta}{\Sigma}$ modulator while maintaining equivalent or better performance with fast locking. The architecture of adaptive bandwidth PLL was simulated by HSPICE using 0.35m CMOS parameters. The behavioral simulation of the proposed adaptive bandwidth fractional-N PLL with a ${\Delta}{\Sigma}$ modulator was carried out by using MatLab to determine if the architecture could achieve the objectives. The HSPICE simulation showed that this type of PLL was able to fast locking, and reduce fractional spurs about 20dB.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.572-578
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• 2020

The stock market is affected by unexpected factors, such as politics, society, and natural disasters, as well as by corporate performance and economic conditions. In recent days, artificial intelligence has become popular, and many researchers have tried to conduct experiments with that. Our study proposes an experiment using not only stock-related data but also other various economic data. We acquired a year's worth of data on stock prices, the percentage of foreigners, interest rates, and exchange rates, and combined them in various ways. Thus, our input data became diversified, and we put the combined input data into a nonlinear autoregressive network with exogenous inputs (NARX) model. With the input data in the NARX model, we analyze and compare them to the original data. As a result, the model exhibits a root mean square error (RMSE) of 0.08 as being the most accurate when we set 10 neurons and two delays with a combination of stock prices and exchange rates from the U.S., China, Europe, and Japan. This study is meaningful in that the exchange rate has the greatest influence on stock prices, lowering the error from RMSE 0.589 when only closing data are used.