• 한국음향학회지
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• 제33권2호
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• pp.146-151
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• 2014

본 논문은 기존의 가야금 안족 모델을 분석하고 안족의 위치에 따른 주파수 모델링을 개선하기 위한 방법에 대해서 기술한다. 기존의 모델은 안족의 위치별 기본 주파수의 변화를 지수 함수로 가정, 리키 적분기를 이용하여 이들 주파수를 적분한 후 선형 회귀 모델을 이용하여 주파수와 안족의 위치에 관한 수식의 파라미터를 구하였다. 이 모델은 평균적으로 2.5 Hz의 오차를 보였으나 낮은 주파수에 대해서는 최대 7.75 Hz의 오차를 보였다. 이에 제안하는 모델은 안족의 위치를 세부 구간으로 나누고 각 구간 내 누적 주파수에 대한 선형 회귀 모델을 적용하였고, 리키 적분기의 계수를 바꿔가며 안족 위치의 세부 구간 내 각 현의 기본 주파수와 계산된 주파수간 RMSE(Root Mean Square Error)가 최소가 되는 계수를 찾음으로써 최적의 파라미터를 구하였다. 이러한 과정을 통해 얻어진 모델은 기존의 오차를 최대 3배가량 줄일 수 있었다.

• 한국지능시스템학회논문지
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• 제14권3호
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• pp.285-289
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• 2004

최근 인터넷의 발전으로 디지털 오디오 및 비디오와 같은 멀티미디어 스트림에 대한 요구가 증가하고 있다. 이러한 멀티미디어 스트리밍을 UDP로 전송할 경우 TCP와 같은 혼잡제어를 수행하지 않기 때문에 동일한 전송경로의 TCP 트래픽 궁핍을 일으켜 혼잡붕괴 및 막대한 전송지연을 초래한다. 이러한 문제점으로 인하여 실시간 멀티미디어 스트림의 전송지연과 혼잡제어를 위한 새로운 전송기법과 프로토콜에 대한 다각적인 연구가 수행되고 있다. TCP 친화적 혼잡제어 기법은 크게 일반적인 혼잡윈도우 관리기능을 이용하는 윈도우 기반 혼잡제어와 TCP 모델링 방정식 등을 이용하여 전송율을 직접 조절하는 율 기반 혼잡제어로 나눌 수 있다. 본 논문은 윈도우 기반과 율 기반을 복합적으로 다룬 하이브리드형 TCP-friendly 혼잡제어 기법에서 Square-root 혼잡회피 알고리즘을 제안하였으며, NS를 사용하여 제안한 TEAR의 성능을 실험하였다. 실험을 통하여 제안한 기법의 적용으로 TEAR의 안정성을 개선할 수 있음을 보였다.

• 제어로봇시스템학회논문지
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• 제11권6호
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• pp.502-509
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• 2005

In this paper, a 4-wheel vehicle model including the effects of tire slip was considered, along with variable parameter sliding control, in order to improve the performance of the vehicle longitudinal response. The variable sliding parameter is made to be proportional to the square root of the pressure derivative at the wheel, in order to compensate for large pressure changes in the brake cylinder. A typical tire force-relative slip curve for dry road conditions was used to generate an analytical tire force-relative slip function, and an antilock sliding control process based on the analytical tire force-relative slip function was used. A retrofitted brake system, with the pushrod force as the end control parameter, was employed, and an average decay function was used to suppress the simulation oscillations. The simulation results indicate that the velocity and spacing errors were slightly larger than those obtained when the wheel slip effect was not considered, that the spacing errors of the lead and follower were insensitive to the adhesion coefficient up to the critical wheel slip value, and that the limit for the antilock control under non-constant adhesion road conditions was determined by the minimum value of the equivalent adhesion coefficient.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권1호
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• pp.31-38
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• 2013

Patients with heart disease need long-term monitoring of the electrocardiogram (ECG) signal using a portable electrocardiograph. This trend requires the miniaturization of data storage and faster transmission to medical doctors for diagnosis. The ECG signal needs to be utilized for efficient storage, processing and transmission, and its data must contain the important components for diagnosis, such as the P wave, QRS-complex, and T wave. In this study, we select the vertex which has a larger curvature value than the threshold value for compression. Then, we reconstruct the compressed signal using by radial basis function interpolation. This technique guarantees a lower percentage of root mean square difference with respect to the extracted sample points and preserves all the important features of the ECG signal. Its effectiveness has been demonstrated in the experiment using the Massachusetts Institute of Technology and Boston's Beth Israel Hospital arrhythmia database.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1994년도 춘계학술대회
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• pp.43-48
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• 1994

본 논문은 반복 수축 변환의 프랙탈(fractal) 이론에 근거한 심전도 데이터 압축에 관한 연구이다. 심전도 데이터에 반복 함수계(Iterated Function System : IFS) 모델을 적용하여 신호 자체의 자기 유사성(self-similarity)을 반복 수축 변환으로 표현하고, 그 매개변수만을 저장한다. 재구성시는 변환 매개변수를 반복 적용하여 원래의 신호에 근사되어지는 값을 얻게 된다. 심전도 데이타는 부분적으로 자기 유사성을 갖는다고 보고, 부분 자기-유사 프랙탈 모델(piecewise self-affine fractal model)로 표현될 수 있다. 이 모델은 신호를 특정 구간들로 나누어 각 구간들에 대해 최적 프랙탈 보간(fractal interpolation)을 구하고 그 중 오차가 가장 작은 매개변수만을 추출하여 저장한다. 이 방법을 심전도 데이타에 적용한 결과 특정 압축율에 대해 아주 적은 재생오차 (percent root-mean-square difference : PRD)를 얻을 수 있었다.

• Nuclear Engineering and Technology
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• 제52권8호
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• pp.1771-1776
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• 2020

Adverse effects in the measured gamma spectrum caused by radioactive statistical fluctuations, gamma ray scattering, and electronic noise can be reduced by energy spectrum denoising. Wavelet threshold denoising can be used to perform multi-scale and multi-resolution analysis on noisy signals with small root mean square errors and high signal-to-noise ratios. However, in traditional wavelet threshold denoising methods, there are signal oscillations in hard threshold denoising and constant deviations in soft threshold denoising. An improved wavelet threshold calculation method and threshold processing function are proposed in this paper. The improved threshold calculation method takes into account the influence of the number of wavelet decomposition layers and reduces the deviation caused by the inaccuracy of the threshold. The improved threshold processing function can be continuously guided, which solves the discontinuity of the traditional hard threshold function, avoids the constant deviation caused by the traditional soft threshold method. The examples show that the proposed method can accurately denoise and preserves the characteristic signals well in the gamma energy spectrum.

• Journal of Mechanical Science and Technology
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• 제20권11호
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• pp.1801-1812
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• 2006

In this paper, a 4-wheel vehicle model including the effects of tire slip was considered, along with variable parameter sliding control, pushrod force as the end control parameter, and an antilock sliding control, in order to improve the performance of the vehicle longitudinal response. The variable sliding parameter is made to be proportional to the square root of the pressure derivative at the wheel, in order to compensate for large pressure changes in the brake cylinder. A typical tire force-relative slip curve for dry road conditions was used to generate an analytical tire force-relative slip function, and an antilock sliding control process based on the analytical tire force-relative slip function was used. A retrofitted brake system, with the pushrod force as the end control parameter, was employed, and an average decay function was used to suppress the simulation oscillations. Simulation results indicate that the velocity and spacing errors were slightly larger than the results that without considering wheel slip effect, the spacing errors of the lead and follower were insensitive to the adhesion coefficient up to the critical wheel slip value, and the limit for the antilock control on non-constant adhesion road condition was determined by the minimum of the equivalent adhesion coefficient.

• 한국농공학회지
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• 제44권7호
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• pp.1-13
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• 2002

Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

• 방사성폐기물학회지
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• 제19권4호
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• pp.447-457
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• 2021

Graphite Isotope Ratio Method (GIRM) can be used to estimate plutonium production in a graphite-moderated reactor. This study presents verification results for the GIRM combined with a 3-D polynomial regression function to estimate cumulative plutonium production in a graphite-moderated reactor. Using the 3-D Monte-Carlo method, verification was done by comparing the cumulative plutonium production with the GIRM. The GIRM can estimate plutonium production for specific sampling points using a function that is based on an isotope ratio of impurity elements. In this study, the ¹⁰B/¹¹B isotope ratio was chosen and calculated for sampling points. Then, 3-D polynomial regression was used to derive a function that represents a whole core cumulative plutonium production map. To verify the accuracy of the GIRM with polynomial regression, the reference value of plutonium production was calculated using a Monte-Carlo code, MCS, up to 4250 days of depletion. Moreover, the amount of plutonium produced in certain axial layers and fuel pins at 1250, 2250, and 3250 days of depletion was obtained and used for additional verification. As a result, the difference in the total cumulative plutonium production based on the MCS and GIRM results was found below 3.1% with regard to the root mean square (RMS) error.

• Geomechanics and Engineering
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• 재33권6호
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• pp.567-581
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• 2023

The prediction and achievement of a proper rock fragmentation size is the main challenge of blasting operations in surface mines. This is because an optimum size distribution can optimize the overall mine/plant economics. To this end, this study attempts to develop four improved artificial intelligence models to predict rock fragmentation through cascaded forward neural network (CFNN) and radial basis function neural network (RBFNN) models. In this regards, the CFNN was trained by the Levenberg-Marquardt algorithm (LMA) and Conjugate gradient backpropagation (CGP). Further, the RBFNN was optimized by the Dragonfly Algorithm (DA) and teaching-learning-based optimization (TLBO). For developing the models, the database required was collected from the Midouk copper mine, Iran. After modeling, the statistical functions were computed to check the accuracy of the models, and the root mean square errors (RMSEs) of CFNN-LMA, CFNN-CGP, RBFNN-DA, and RBFNN-TLBO were obtained as 1.0656, 1.9698, 2.2235, and 1.6216, respectively. Accordingly, CFNN-LMA, with the lowest RMSE, was determined as the model with the best prediction results among the four examined in this study.