• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2511-2517
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• 2009

Recently, a FMCW radar is used for the various purposes in the short range detection and tracking of targets. The main advantages of a FMCWradar are the comparative simplicity of implementation and the low peak power transmission characterizing the very low probability of signal interception. Since it uses the frequency modulated continuous wave for transmission and demodulation, the received beat frequency represents the range and Doppler information of targets. Detection and extraction of useful information from targets are performed in this beat frequency domain. Therefore, the resolution and accuracy in the estimation of a beat spectrum are very important. However, using the conventional FFT estimation method, the high resolution spectrum estimation with a low sidelobe level is not possible if the acquisition time is very short in receiving target echoes. This kind of problems deteriorates the detection performance of adjacent targets having the large magnitude differences in return echoes and also degrades the reliability of the extracted information. Therefore, in this paper, the model parameter estimation methods such as autoregressive and eigenvector spectrum estimation are applied to mitigate these problems. Also, simulation results are compared and analyzed for further improvement.

• Journal of IKEEE
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• v.26 no.3
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• pp.355-363
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• 2022

Korea is pursuing a plan to switch and expand energy sources with a focus on renewable energy with the goal of becoming carbon neutral by 2050. As the instability of energy supply increases due to the intermittent nature of renewable energy, accurate prediction of the amount of renewable energy generation is becoming more important. Therefore, the government has opened a small-scale power brokerage market and is implementing a system that pays settlements according to the accuracy of renewable energy prediction. In this paper, a prediction model was implemented using a statistical model and an artificial intelligence model for the prediction of solar power generation. In addition, the results of prediction accuracy were compared and analyzed, and the revenue from the settlement amount of the renewable energy generation forecasting system was estimated.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.2
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• pp.32-45
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• 2000

This paper presents the analytic derivation of the SINR, when a linear array antenna is accommodated into the cellular CDMA basestation receiver, in relation to the two major performance effecting factors in beamforming(BF) applications, i. e., the direction selectivity, which refers to the narrowness of the mainbeam width, and the direction-of-arrival(DOA) estimation accuracy. The analytically derived results are compared with the operation simulation of the receiver realized with the several BF algorithms and their agreements are confirmed, consequently verifying the correctness of the analysis and the operation simulation. In order to investigate separately the effects of the errors occurring in the direction estimation and in the interference suppression, which are the two major functional components of general BF algorithms, both the algorithms of steering BF and the minimum- variance- distortionless-response(MVDR) BF are applied to the analysis. A signal model to reflect the spatially scattering phenomenon of the RF waves entering into the .:nay antenna, which directly affects on the accuracy of the BF algorithm's direction estimation, is also suggested in this paper and applied to the analysis and the operation simulation. It is confirmed from the results that the enhancement of the direction selectivity of the away antenna is not desirable in view of both the implementation economy and the BF algorithm's robustness to the erroneous factors. Such a trade-off characteristics is significant in the sense that it can be capitalized to obtain an economic means of BF implementation that does not severely deteriorate its performance while ensuring the robustness to the erroneous effects, consequently manifesting the significance of the analysis results of this paper that can be used as a design reference in developing BF algorithms to the cellular CDMA system.

• The Journal of Bigdata
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• v.8 no.2
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• pp.165-175
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• 2023

LNG is a representative imported cargo at Incheon Port and has a relatively high contribution to the increase/decrease in overall cargo volume at Incheon Port. In addition, in the view point of nationwide, LNG is the one of the most important key resource to supply the gas and generate electricity. Thus, it is very essential to identify the factors that have impact on the demand fluctuation and build the appropriate forecasting model, which present the basic information to make balance between supply and demand of LNG and establish the plan for power generation. In this study, different to previous research based on macroscopic annual data, the weekly demand of LNG is converted from the cargo volume unloaded by LNG carriers. We have identified the periodicity and correlations among internal and external factors of demand variability. We have identified the input factors for predicting the LNG demand such as seasonality of weekly cargo volume, the peak power demand, and the reserved capacity of power supply. In addition, in order to predict LNG demand, considering the characteristics of the data, time series prediction with weekly LNG cargo volume as a dependent variable and prediction through an artificial neural network model were made, the suitability of the predictions was verified, and the optimal model was established through error comparison between performance and estimates.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.4
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• pp.280-287
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• 2012

The sources of greenhouse gases (GHG) at Hanyang University Ansan campus, including direct sources, indirect sources, and others, were investigated in order to establish the GHG inventory. Emission of GHG was calculated with the energy use from each source from 2007 and 2009. The indirect emission (56.7%) due to the electricity significantly contributed to total GHG emission. The scenario for the GHG reduction was designed for both campus administration and members. The reduction potential of GHG was simulated from 2007 to 2020 using Long-range Energy Alternatives Planning (LEAP) model. In case of GHG reduction scenario by campus administration, the GHG can be reduced by 63.34 ton $CO_{2eq}/yr$ for stationary combustion in the direct source, by 221.1 ton $CO_{2eq}/yr$ for mobile combustion in the direct source, and by 4,637.34 ton $CO_{2eq}/yr$ for lighting in the indirect source, compared to 2020 Business As Usual (BAU). In case of GHG reduction action scenario by campus members, the reduction potential of GHG was 1293.76 ton $CO_{2eq}/yr$. Overall, the total GHG emissions in 2020 by the both scenarios can be decreased by 24% compared to 2020 BAU.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.483-494
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• 2023

Recently, gas turbine generators are widely used for frequency control of power systems. Although the inlet temperature of a gas turbine is a key factor related to the performance and lifespan of the device, the inlet temperature is not measured directly for reasons such as the turbine structure and operating environment. In particular, the inlet temperature of the reheating gas turbine is very important for stable operation management, but field workers are experiencing a lot of difficulties because the manufacturer does not provide information on the calculation formula. Therefore, in this study, we propose a method for estimating the inlet temperature of a gas turbine using a machine learning-based linear regression analysis method based on a polytropic process equation. In addition, by proposing an inlet temperature calculation algorithm through the usefulness analysis and verification of the inlet temperature calculation model obtained through linear regression analysis, it is intended to help to improve the level of reheat gas turbine combustion tuning technology.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.4
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• pp.333-340
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• 2001

This paper presents a calculating method for inductance of the Switched Reluctance Motor(SRM) for torque characteristics and driving by analytical model. The torque generating characteristics of the SRM depend on the phase current and the inductance variation features, but Its nonlinear magnetic characteristics make it difficult to calculating inductance. Recently, The approaches for calculating inductance have taken vary from detailed finite element method(FEM) and Fitting method in magnetization curves using complex nonlinear magnetic circuit models. But those methods have not satisfactory approach for machine performance calculations, because of having a long time and remodeling for analyses, therefore thus an alternative approach is required. So it is suggested simply calculating method of the inductance based on designed data of machinery by analytical model in unaligned and aligned rotor. In order to prove the calculating, there are compare with analytical FEM. direct measurement, this method, and simulation. The compared result is shown to obtain good accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.1
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• pp.69-82
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• 1993

본 논문에서는 디지틀 이동 통신 시스템의 열악한 페이딩 채널에 적합한 변복조 반식중의 하나인${\pi}$/4-shift QPSK 성능을 논하고, 그 성능 개선을 위한 새로운 TCM(trellis-coded modulation)을 적응하여 trellis-부호화된${\pi}$/8-shift 8SPSK 방식을 제안 한다. 기존의 ${\pi}$/4-shift QPSK변조 방식에 TCM의 도입은 요구된 대역폭과 송신 전력과 전송을 그대로 유지하면서 부호화와 변조를 일체화함으로서 부호화 이득(coding gain)을 얻을 수 있다. 이동 통신 채널에서 trellis-부호화된 ${\pi}$/8-shift 8PSK방식의 시스템 성능을 추정하기 위해서, 가산 백색 가우시안 잡음과 레일레이 페이딩 현상이 존재하는 채널에서, 차량속도 변화에 따른 도플러 효과에 의한 페이딩율이 10Hz와 30Hz인 두 경우에 대해 시스템을 모델링한다. Trellis-부호화된${\pi}$/8-shift 8PSK에 대한 부호화 이득은 비트 에러 확률을 적용하여 분석하고, 기본 시스템과 새롭게 모델링 되어진 시스템의 개선된 성능을 비교하기 위해, TCM의 상태수를 4,8,16으로 선정하여 비교 구현해 본 결과, 상태수가 커질수록 더 좋은 성능을 나타내고, 기존의 ${\pi}$/4-shift QPSK보다 trellis-부호된 ${\pi}$/8-shift 8PSK는 가산 백색 가우시안 잡음채널에서는 3~4dB의 부호화 이득을 얻고, 레일레이 페이티 채널하에서 3~16dB정도의 부호화 이득을 얻음을 알 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.172-180
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• 2013

In this paper, we propose an energy-efficient camera operating scheme to save energy which can be used for mass surveillance cameras. This technique determines how many cameras should be turned on in the consideration of the velocity vector of monitoring targets, which is acquired by DSRC object tracking, the model of the specification of installed cameras, and the road model of installed sites. Also, we address other techniques used to save energy for the surveillance system as well. Throughout performance evaluation, we demonstrate the excellence of our proposed scheme compared with previous approaches.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.96-99
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• 2018

최근 초고화질 영상뿐만 아니라 360 비디오 콘텐츠의 보급이 확산되고 있다. 이미 대중적으로 보급된 스마트폰을 통해 누구나 쉽게 이 360 비디오 콘텐츠를 접할 수 있는데, 스마트폰의 성능은 제한적일 수 밖에 없다. 따라서 본 논문은 모바일 VR 에서 360 비디오 병렬처리를 수행할 때 보다 적합한 최적화 방법 2 가지를 소개한다. 이를 위해 전력 소모를 줄이는 장점으로 인해 모바일 디바이스에 많이 사용되는 비대칭 멀티코어의 특징을 활용한다. 두 방법 모두 공통적으로 각 코어의 성능비와 할당되는 작업량을 비례하게 하여 디코딩 작업의 시간을 줄이는 방법들이다. 첫 번째 방법은 영상을 타일로 분할할 때 각 코어의 성능비와 비례하게 분할하는 방법이다. 해당 기법을 적용하기 위해서, 비디오 크기별 연산 복잡도 분석 모델을 활용하여 사용한다. 제안하는 기법을 사용한 실험 결과, 평균적으로 약 25%의 디코딩 시간 개선을 보였다. 두 번째 방법은 타일로 분할된 영상의 각 복잡도 정도를 PU 의 양으로 추정하여, 각 코어의 성능비와 비례하게 코어에 할당하는 방법이다. 해당 기법을 사용하기 위해서, PU 의 양과 연산 복잡도 정도의 상관관계를 회귀분석하여 이를 이용한다. 제안하는 기법을 사용한 실험 결과, 약 9~16%의 디코딩 시간 개선을 보였다.