• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.427-733
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• 2003

Adiabatic shear bands have been observed in the serrated chip during high strain rate metal cutting process of medium carbon steel and titanium alloy. The recent microscopic observations have shown that dynamic recrystallization occurs in the narrow adiabatic shear bands. However the conventional flow stress models such as the Zerilli-Armstrong model and the Johnson-Cook model, in general, do not predict the occurrence of dynamic recrystallization (DRX) in the shear bands and the thermal softening effects accompanied by DRX. In the present study, a strain hardening and thermal softening model is proposed to predict the adiabatic shear localized chip formation. The finite element analysis (FEA) with this proposed flow stress model shows that the temperature of the shear band during cutting process rises above 0.5T$\sub$m/. The simulation shows that temperature rises to initiate dynamic recrystallization, dynamic recrystallization lowers the flow stress, and that adiabatic shear localized band and the serrated chip are formed. FEA is also used to predict and compare chip formations of two flow stress models in orthogonal metal cutting with AISI 1045. The predictions of the FEA agreed well with the experimental measurements.

• Transactions of Materials Processing
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• v.12 no.4
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• pp.358-363
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• 2003

Adiabatic shear bands have been observed in the serrated chip during high strain rate metal cutting process of medium carbon steel and titanium alloy The recent microscopic observations have shown that dynamic recrystallization occurs in the narrow adiabatic shear bands. However the conventional flow stress models such as the Zerilli-Armstrong model and the Johnson-Cook model, in general, do not predict the occurrence of dynamic recrystallization (DRX) in the shear bands and the thermal softening effects accompanied by DRX. In the present study, a strain hardening and thermal softening model is proposed to predict the adiabatic shear localized chip formation. The finite element analysis (FEA) with this proposed flow stress model shows that the temperature of the shear band during cutting process rises above 0.5Τ$_{m}$. The simulation shows that temperature rises to initiate dynamic recrystallization, dynamic recrystallization lowers the flow stress, and that adiabatic shear localized band and the serrated chip are formed. FEA is also used to predict and compare chip formations of two flow stress models in orthogonal metal cutting with AISI 1045. The predictions of the FEA agreed well with the experimental measurements.s.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.10
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• pp.1-11
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• 1993

A narrow-band dual TE$_{111}$ mode circular waveguide filter for Ku-Band satellite transponder was designed and manufactured based on a new model of the filter. We calculated the cavity size, pin polarizer depth and diameter, iris length and width, and used Bethe's Small Diffraction Theory and Chon's Correction Formular in order to obtain exact Result for each cavity. The designed dual model waveguide filter was manufactured with invar in order to maintain the thermal stability, and the filter performance was improved through the thermal test and vibration test to endure in the cosmic environment.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.88-95
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• 2015

For the frequency-domain spectral fatigue analysis, the probability density function of stress range needs to be estimated based on the stress spectrum only, which is a frequency domain representation of the response. The probability distribution of the stress range of the narrow-band spectrum is known to follow the Rayleigh distribution, however the PDF of wide-band spectrum is difficult to define with clarity due to the complicated fluctuation pattern of spectrum. In this paper, efforts have been made to figure out the links between the probability density function of stress range to the structural response of wide-band Gaussian random process. An artificial neural network scheme, known as one of the most powerful system identification methods, was used to identify the multivariate functional relationship between the idealized wide-band spectrums and resulting probability density functions. To achieve this, the spectrums were idealized as a superposition of two triangles with arbitrary location, height and width, targeting to comprise wide-band spectrum, and the probability density functions were represented by the linear combination of equally spaced Gaussian basis functions. To train the network under supervision, varieties of different wide-band spectrums were assumed and the converged probability density function of the stress range was derived using the rainflow counting method and all these data sets were fed into the three layer perceptron model. This nonlinear least square problem was solved using Levenberg-Marquardt algorithm with regularization term included. It was proven that the network trained using the given data set could reproduce the probability density function of arbitrary wide-band spectrum of two triangles with great success.

• Journal of the Korean Society of Combustion
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• v.10 no.2
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• pp.9-17
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• 2005

WSGGM with gray gas regrouping is successfully applied to study the flame structure of opposed flow flames including effect of radiative transfer. The statistical narrow band model is used to obtain the benchmark solutions. Results obtained by using the optically thin model are shown to overestimate the emission and to predict the flame structures inadequately especially for optically thick and low stretch rate flames. Computed results by using the WSGGM with 10 gray gases and SNB model show reasonable agreements with each other, and the required calculation time for the WSGGM is acceptable for engineering applications.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1437-1440
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• 2007

Many hydroclimatic time series are marked by interannual and longer quasi-period features that are associated with narrow band oscillatory climate modes. A time series modeling approach that directly considers such structures is developed and presented. The essence of the approach is to first develop a wavelet decomposition of the time series that retains only the statistically significant wavelet components, and to then model each such component and the residual time series as univariate autoregressive processes. The efficacy of this approach is demonstrated through the simulation of observed and paleo reconstructions of climate indices related to ENSO and AMO, tree ring and rainfall time series. Long ensemble simulations that preserve the spectral attributes of the time series in each ensemble member can be generated. The usual low order statistics are preserved by the proposed model, and its long memory performance is superior to the direction application of an autoregressive model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1900-1907
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• 2010

In this paper, a recurrent cerebellar modulation articulation control with praticle swarm optimization (PSO) method has been investigated for improvement of noise attenuation performance in active noise control system. For narrow band noise, FXLMS and RCMAC has a partial satisfactory noise attenuation. However, noise attenuation performance is poor for broad band noise and nonlinear path since it has linear filter structure. To improve this problem, a RCMAC with PSO is proposed and it is shown that satisfactory noise attenuation performance is obtained by some simulations in duct system using harmonic motor noise and KTX cabin noise as a noise source.

• Investigative Magnetic Resonance Imaging
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• v.20 no.1
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• pp.53-60
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• 2016

Purpose: To develop a technique for quantifying the $^{13}C$-metabolites by performing frequency-selective hyperpolarized $^{13}C$ magnetic resonance spectroscopy (MRS) in vitro which combines simple spectrally-selective excitation with spectrally interleaved acquisition. Methods: Numerical simulations were performed with varying noise level and $K_p$ values to compare the quantification accuracies of the proposed and the conventional methods. For in vitro experiments, a spectrally-selective excitation scheme was enabled by narrow-band radiofrequency (RF) excitation pulse implemented into a free-induction decay chemical shift imaging (FIDCSI) sequence. Experiments with LDH / NADH enzyme mixture were performed to validate the effectiveness of the proposed acquisition method. Also, a modified two-site exchange model was formulated for metabolism kinetics quantification with the proposed method. Results: From the simulation results, significant increase of the lactate peak signal to noise ratio (PSNR) was observed. Also, the quantified $K_p$ value from the dynamic curves were more accurate in the case of the proposed acquisition method compared to the conventional non-selective excitation scheme. In vitro experiment results were in good agreement with the simulation results, also displaying increased PSNR for lactate. Fitting results using the modified two-site exchange model also showed expected results in agreement with the simulations. Conclusion: A method for accurate quantification of hyperpolarized pyruvate and the downstream product focused on in vitro experiment was described. By using a narrow-band RF excitation pulse with alternating acquisition, different resonances were selectively excited with a different flip angle for increased PSNR while the hyperpolarized magnetization of the substrate can be minimally perturbed with a low flip angle. Baseline signals from neighboring resonances can be effectively suppressed to accurately quantify the metabolism kinetics.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.139-142
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• 2020

NB-IoT(Narrow Band Internet of Things) is an emerging LPWAN(Low Power Wide Area Network) radio technology. NB-IoT has many advantages like low power, low cost, and high coverage. However low bandwidth and low sampling rates also lead to poor positioning accuracy. This paper proposed a solution to optimize positioning accuracy under the OTDOA(Observed Time Difference of Arrival) approach by utilizing MLR(Multiple Linear Regression) models. Through the MLR model to predict the influence degree of weather(temperature, humidity, light intensity and air pressure) on the arrival time of signal transmission to improve the measurement accuracy. The improvement of measurement accuracy can greatly improve IoT applications based on NB-IoT.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2002.11a
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• pp.347-351
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• 2002

본 논문에서는, 위성 중계기 Engineering Model(EM)급 Ka 대역 입력 Demultiplexer (IMUX)의 진폭 및 군지연 등화된 채널 협대역 여파기의 개발/결과가 제시된다. 여파기는 큰 선택성(selectivity)과 작은 대역내 손실로써 동작하기 위해, 8차의 타원적분형 응답특성의 이중모드 결합구조의 특성을 가진다. 그리고 여파기 출력이 가지는 급한 변화의 군지연과 대역내 진폭은 2극(Pole) 등화기에 의해 평탄하게 된다. 튜닝 및 측정 결과는 요구규격사항을 잘 만족함을 보여준다.