• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.83-91
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• 1997

A reactor vibration monitoring has been performed using neutron noise obtained from excore detectors for the safety operation, Traditionally, the spectral estimator based on Fourier analysis has been widely used in the noise analysis of the reactor system. If the bias is too severe, the resolution would not be adequate for a given application. One major motivation for the current interests in the parametric approach to spectral estimation is the apparent higher resolution achievable with these modern techniques. In considering an unbias, a consistency, an efficency, and a minimum lower bound of the statictic estimation, an AR model is appropriate for noise spectral estimation with sharp peaks but not deep valley. In order to select an appropriate model order, the lag value of autocorrleaton function is applied. Burg method to trace the vibration mode of RPV internal is the most sucuessful.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.42-48
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• 1997

This paper has apparaised ability of speaker recognition and speech recognition using correlation dimension and Lyapunov dimension. In this method, speech was regarded the cahos that the random signal is appeared in determinisitic raising system. we deduced exact correlation dimension and Lyapunov dimension with searching important orbit from AR model power spectrum when reconstruct strange attractor using Taken's embedding theory. We considered a usefulness of speech recognition and speaker recognition using correlation dimension and Lyapunov dimension that characterized reconstruction attractor. As a result of consideration, which were of use more the speaker recognition than speech recognition, and in case of speaker recognition using Lyapunov dimension were much recognition rate more than speaker recognitions using correlation dimension.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.23-28
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• 2009

This study describes an emotion classification method using two different feature parameters of four-channel EEG signals. One of the parameters is linear prediction coefficients based on AR modelling. Another one is cross-correlation coefficients on frequencies of ${\theta}$, ${\alpha}$, ${\beta}$ bands of FFT spectra. Using the linear predictor coefficients and the cross-correlation coefficients of frequencies, the emotion classification test for four emotions, such as anger, sad, joy, and relaxation is performed with an artificial neural network. The results of the two parameters showed that the linear prediction coefficients have produced the better results for emotion classification than the cross-correlation coefficients of FFT spectra.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.47-54
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• 2010

Old archived film shows two major defects: line scratch and blobs. In this paper, we present a design and implementation of an automatic video restoration system for line scratches observed in archived film. We use autoregressive (AR) image model because we can make stochastic and specifically autoregressive image generation process with our PAST-PRESENT model and Sampling Pattern. We designed locality maximizing scanning pattern, which can generate nearly stationary time-like series of pixels, which is a strong requirement for a stochastic series to be autoregressive. The sampled pixel series undergoes filtering and model fitting using Durbin-Levinson algorithm before interpolation process. We designed three-stage film restoration system, which includes (1) film acquisition from VHS tapes, (2) simple line scratch detection and restoration, and (3) manual blob identification and sophisticated inpainting scheme. We implemented film acquisition and simple inpainting scheme on Texas Instruments DSP board TMS320DM642 EVM, and implemented our AR inpainting scheme on PC for sophisticated restoration. We experimented our scheme with two old Korean films: "Viva Freedom" and "Robot Tae-Kwon-V", and the experimental results show that our scheme improves Bertalmio's scheme for subjective quality (MOS), objective quality (PSNR), and especially restoration ratio (RR), which reflects how much similar to the manual inpainting results.

• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.9
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• pp.1593-1602
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• 2001

본 연구는 스포츠 아우터웨어용 나일론 직물의 소리에 대한 주관적 감각과 이에 관련된 객관적 측정치를 규명하기 위하여, 서로 다른 8종의 나일론 직물의 소리의 스펙트럼 파형을 고찰하였으며, 소리 파라미터로 총음압(level pressure of total sound, LPT),세 가지 AR (autoregressive)계수, Zwicker의 심리음향학적 모델에 따른 크기(Z)와 날카로움(Z)를 계산하였고, Kawabata Evaluation System(KES)으로 직물의 물리적 성질을 측정하였다. 주관적 감각 평가를 위하여 피험자에게 녹음된 각 직물소리를 들려주어 7개 소리 감각 (부드러움, 시끄러움, 날카로움, 맑음, 거 침, 높음, 유쾌함)을 의미분별척도로 답하게 한 후, 단계적 선형 회귀식을 이용하여 직물 소리의 주관적 감각에 대한 예측 모델을 제시하였다. 울트라스웨이드를 제외한 태피터 나일론 직물들은 스펙트럼 파형 에서 다른 조성 섬유의 직물들보다 음압 값이 높고, 총음압이 60dB 안팎의 값을 보여, 착용자에게 불쾌감을 줄 것으로 예상되었으며, 주관적 감각 평가에서도 소리의 부드러움과 맑음, 유쾌함에서 음의 점수를, 시끄러움과 날카로움, 거침, 높음에서 양의 점수를 얻었다. 주관적 감각의 예측모델에서 총음압은 시끄러움과 거침에 정적 영향을, 유쾌함에 부적 영향을 미쳐서 나일론 직물 소리의 총음압이 50dB 이하일 때 주관적으로 유쾌하게 느껴지는 것으로 나타났다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.54-59
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• 1999

In this paper, a generalized auto-regressive(AR) model is proposed for linear prediction based on adaptive spatio-temporal support region(ASTSR). The conventional AR model suffers from the drawback that the prediction error increases in the edge region because the rectangular support region of the edge does not satisfy the stationary assumption. Thus, the proposed approach puts an emphasis on the formulation of a spatio-temporally adaptive support region for the AR model, called ASTSR. The ASTSR consists of two parts: the adaptive spatial support region(ASSR) connected with edges and the adaptive temporal support region(ATSR) related to temporal discontinuities. The AR model based on ASTSR not only produces more accurate model parameters but also reduces the computational complexity in the motion picture restoration.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.89-94
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• 1995

A16061, SB41 and SM45C was used for developing tool wear monitoring system in face milling. First of all, Neural networks of which input are 8 $_{th}$ order AR morel parameters, frequency band energies, cutting conditions was used to monitor tool wear for each material. Finally, A unified neural network, which has tensile strengths of each material as an additional input, was constructed to consider the effect three materials on the features of tool wear. It was verified that tensile strength is the one of properties of workpiece materials.s.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06a
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• pp.131-134
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• 1998

본 논문에서는 시공간 적응적 기반영역 (Adaptive Spatio-Temporal Support Region : ASTSR)을 바탕으로 하는 일반화된 Auto-Regressive(AT)모델을 제안한다. 시공간 적응적 기반 영역은 영상 내 경계선의 특성과 동영상에서의 시간적 불연속 (temporal discontinuity) 개념을 이용하여 구성되어질 수 있다. 설정된 시공간 적응적 기반영역은 기존의 AR 모델에 적용되어지는 직사각형 형태의 기반영역에 비하여 보다 정상상태(stationarity)의 특성을 가지며 이로 인해 더 정확한 모델 파라미터들을 추출해 낼 수 있을 뿐 아니라 데이터의 처리량에서도 큰 이득을 얻을 수 있다. 제안된 방법은 손상된 동영상 데이터를 복원(motion picture restoration)하는 측면에 응용되어 실험되어졌으며 기존의 모델과 비교하여 우수한 성능을 보여주었다.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2018.06a
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• pp.49.2-49.2
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• 2018

스퍼터링에 의해 증착된 박막 내 기계적 응력 발생 현상을 규명하기 위하여 활발한 이론적, 실험적 접근이 있었으나, 복잡한 플라즈마 증착환경 내에서 다양한 증착 파라미터로 인해 정확한 응력 발생 메커니즘에 대해 아직도 완벽한 규명이 되지 않은 상황이다. 본 연구에서는 몰리브데늄 (Mo)과 텅스텐 (W) 박막을 마그네트론 스퍼터링법을 이용하여 증착 시 발생하는 잔류응력 발생 현상에 대해 논의하겠다. Mo 박막의 경우 증착압력을 2.5 mTorr와 4.1 mTorr로 고정시킨 채 기판 바이어스를 0-250 V 간격으로 변화시킨 결과, 2.5 mTorr에서는 기판바이어스가 증가할수록 압축응력이 증가하는 반면 4.1 mTorr에서는 기판바이어스가 증가할수록 인장응력이 증가하는 것이 확인되었다. 이러한 반대 경향의 잔류응력을 발생시키는 기판 바이어스 효과를 확인하기 위하여 증착 파라미터 변경에 따른 박막 성장 거동 모델을 제시한다. W 박막은 준안정상인 ${\beta}$-상이 증착 초기(2.5 nm)에 형성이 되고, 증착 과정에서 열역학적 안정상인 ${\alpha}$-상으로 상변태 하였다. 상변태에 의한 부피 변화에 따른 잔류응력 발생의 분석을 위하여 X-ray 회절피크의 비대칭성을 분석한 결과 압축응력과 인장응력이 공존하고 있는 것으로 확인되었다. 본 연구결과는 스퍼터링 공정 시 높은 에너지를 가지는 중성화된 Ar과 스퍼터된 원자가 기판과 충돌 시 atomic peening effect에 의해 압축응력이 발생한다는 일반적인 이론과 상충되는 결과로서, Mo 및 W 박막 내 잔류응력 제어를 위한 방안을 제시한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.716-726
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• 2010

In this research, design optimization of an aircraft wing has been performed using the fully automated Multidisciplinary Design Optimization (MDO) framework, which integrates aerodynamic and structural analysis considering nonlinear structural behavior. A computational fluid dynamics (CFD) mesh is generated automatically from parametric modeling using CATIA and Gambit, followed by an automatic flow analysis using FLUENT. A computational structure mechanics (CSM) mesh is generated automatically by the parametric method of the CATIA and visual basic script of NASTRAN-FX. The structure is analyzed by ABAQUS. Interaction between CFD and CSM is performed by a fully automated system. The Response Surface Method (RSM) is applied for optimization, helping to achieve the global optimum. The optimization design result demonstrates successful application of the fully automated MDO framework.