• Journal of the Korean Wood Science and Technology
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• 제13권3호
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• pp.3-26
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• 1985

The object of this study was to investigate the effects on physical and mechanical properties of wood particle and sawdust board combined with wire net. Conventional forming, press-lam, and veneer comply boards combining one to four wire net sheets were made from wood particle and sawdust with different spacings (8, 10, 12, and 18 Mok) and different wire diameters (0.35, 0.50, and 0.80mm) composing wire net. They were compared and analyzed statistically with specific gravity, thickness swelling, length swelling, bending properties (modulus of rupture, modulus of elasticity, work to proportional limit, and total work), internal bonding strength, and screw holding strength between wood particle and sawdust boards. The results obtained at this study as cording to the discussions might be concluded as follows; 1. In specific gravity, both particle and sawdust boards by press-lam method were higher than by conventional forming and veneer comply method, and the boards containing more wire net sheets also showed higher value. But the wire net spacings(Mok) had no influence on specific gravity. In general, particle board showed higher specific gravity than sawdust board. Veneer comply board showed lowest specific gravity values. 2. Both particle and sawdust boards by press-lam method was slightly lower than by conventional forming and veneer comply method in thickness swelling. The sawdust board containing 8, 12. and 18 Mok wire net showed lower thickness swelling than the corresponding particle board, but both sawdust and particle boards containing the T8 and 10 Mok wire net showed higher and similar thickness swelling. 3. Both particle and sawdust boards containing wire net showed no difference in MOR and MOE of bending. Comply board was the highest and particle board showed slightly higher than sawdust board in MOR and MOE values. 4. In work to proportional limit and total work in bending, both particle and sawdust boards containing thicker wire diameter and more wire net sheets showed higher value. From these facts, it is conceivable that boards with thicker wire diameter and more wire net sheets show increasing resistance against external force. But there was no significant difference between particle and sawdust borads. 5. In resistance against delamination (internal bonding strength), both sawdust and particle boards containing wire net showed lower value than control, and also showed decreasing tendency with more number of wire net sheet composed. Particle board showed higher resistance against delamination than sawdust board. 6. In screw holding strength, sawdust board containing thicker wire diameter and more wire net sheets showed higher value, but particle board by press-lam method was higher than by conventional forming and veneer comply method. Screw holding strength of particle board was higher than that of sawdust board.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1992년도 학술논문발표회 논문집 제11권 1호
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• pp.23-28
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• 1992

The purpose of this paper is to develop a new adaptive echo canceller improving convergence speed and near-end-talker detection performance of the conventional echo canceller. In a conventional adaptive echo canceller, an adaptive digital filter with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to cote the coefficients, and NET detector using energy comparison method prevents the adaptive digital filter to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF(Adaptive Digital Filter) output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yield more accurate detection of the start point of the NET signal.

• 디지털융복합연구
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• 제19권6호
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• pp.251-258
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• 2021

본 논문에서는 U-Net 기반의 semantic segmentation 방법에서 정확도를 향상시키기 위해 residual learning을 활용한 인코더-디코더 구조의 모델을 제안하였다. U-Net은 딥러닝 기반의 semantic segmentation 방법이며 자율주행 자동차, 의료 영상 분석과 같은 응용 분야에서 주로 사용된다. 기존 U-Net은 인코더의 얕은 구조로 인해 특징 압축 과정에서 손실이 발생한다. 특징 손실은 객체의 클래스 분류에 필요한 context 정보 부족을 초래하고 segmentation 정확도를 감소시키는 문제가 있다. 이를 개선하기 위해 제안하는 방법은 기존 U-Net에 특징 손실과 기울기 소실 문제를 방지하는데 효과적인 residual learning을 활용한 인코더를 통해 context 정보를 효율적으로 추출하였다. 또한, 인코더에서 down-sampling 연산을 줄여 특징맵에 포함된 공간 정보의 손실을 개선하였다. 제안하는 방법은 Cityscapes 데이터셋 실험에서 기존 U-Net 방법에 비해 segmentation 결과가 약 12% 향상되었다.

• International Journal of Aeronautical and Space Sciences
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• 제8권2호
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• pp.126-131
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• 2007

In this paper, Monte Carlo Simulation (MCS) method was used as an uncertainty assessment tool for air flow, net thrust measurement. Uuncertainty sources of the net thrust measurement were analyzed, and the probability distribution characteristics of each source were discussed. Detailed MCS methodology was described including the effect of the number of simulation. Compared to the conventional sensitivity coefficient method, the MCS method has advantage in the uncertainty assessment. The MCS is comparatively simple, convenient and accurate, especially for complex or nonlinear measurement modeling equations. The uncertainty assessment result by MCS was compared with that of the conventional sensitivity coefficient method, and each method gave different result. The uncertainties in the net thrust measurement by the MCS and the conventional sensitivity coefficient method were 0.906% and 1.209%, respectively. It was concluded that the first order Taylor expansion in the conventional sensitivity coefficient method and the nonlinearity of model equation caused the difference. It was noted that the uncertainty assessment method should be selected carefully according to the mathematical characteristics of the model equation of the measurement.

• 수산해양기술연구
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• 제39권4호
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• pp.326-336
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• 2003

본 연구는 현용 전어 선망 어구$.$어법에 대한 실태조사에서 파악된 문제점과 조업시 어구의 수중 형상 및 어구에 대한 어군의 행동을 조사$.$분석한 전보의 결과를 바탕으로 어구 개발에 대한 방향을 설정한 후 고려되는 몇 가지 형태의 어구를 제시하고 이들 어구에 대한 모형 실험을 실시하였는데, 그 결과를 요약하면 다음과 같다. 1. 현용 어구와 현용 어구의 75% 규모로 축소 (뜸줄 길이 기준)한 어구에 짐줄을 채택하였을 경우, 짐줄이 완전히 체결되기도 전에 발줄이 수면으로 부상하거나 수심 2∼3m 에서 짐줄이 체결되어 현용 어구구조에는 짐줄을 사용하는 것은 오히려 어획 성능을 저하시키는 것으로 나타났다. 2. 뜸줄과 발줄의 길이는 현용 어구의 60% 규모로 하고 그물의 양쪽 옆 부위를 최소 전개 깊이인 20m로 고정한 채 중앙부로 갈수록 깊이를 점차 증대시킨 어구 중 중앙부 깊이가 50m인 어구는 짐줄이 수심 20∼23m 이상에서 체결되고, 중앙부 깊이가 40m 와 30m인 어구는 체결 수심이 7∼15m 사이로 나타나 모든 어구에서 어군을 차단하는데 충분한 깊이를 보이지만 조업 어장의 수심과 조류 등을 고려하였을 경우 현장에 적용하기에는 중앙부 깊이가 40m 와 30m인 어구가 더 유리하다고 판단된다.

• Korean Journal of Radiology
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• 제20권8호
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• pp.1275-1284
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• 2019

Objective: To develop algorithms using convolutional neural networks (CNNs) for automatic segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) and compare them with conventional algorithms, including a thresholding-based segmentation. Materials and Methods: Between September 2005 and August 2015, 429 patients presenting with acute cerebral ischemia (training:validation:test set = 246:89:94) were retrospectively enrolled in this study, which was performed under Institutional Review Board approval. Ground truth segmentations for acute ischemic lesions on DWI were manually drawn under the consensus of two expert radiologists. CNN algorithms were developed using two-dimensional U-Net with squeeze-and-excitation blocks (U-Net) and a DenseNet with squeeze-and-excitation blocks (DenseNet) with squeeze-and-excitation operations for automatic segmentation of acute ischemic lesions on DWI. The CNN algorithms were compared with conventional algorithms based on DWI and the apparent diffusion coefficient (ADC) signal intensity. The performances of the algorithms were assessed using the Dice index with 5-fold cross-validation. The Dice indices were analyzed according to infarct volumes (< 10 mL, ≥ 10 mL), number of infarcts (≤ 5, 6-10, ≥ 11), and b-value of 1000 (b1000) signal intensities (< 50, 50-100, > 100), time intervals to DWI, and DWI protocols. Results: The CNN algorithms were significantly superior to conventional algorithms (p < 0.001). Dice indices for the CNN algorithms were 0.85 for U-Net and DenseNet and 0.86 for an ensemble of U-Net and DenseNet, while the indices were 0.58 for ADC-b1000 and b1000-ADC and 0.52 for the commercial ADC algorithm. The Dice indices for small and large lesions, respectively, were 0.81 and 0.88 with U-Net, 0.80 and 0.88 with DenseNet, and 0.82 and 0.89 with the ensemble of U-Net and DenseNet. The CNN algorithms showed significant differences in Dice indices according to infarct volumes (p < 0.001). Conclusion: The CNN algorithm for automatic segmentation of acute ischemic lesions on DWI achieved Dice indices greater than or equal to 0.85 and showed superior performance to conventional algorithms.

• 수산해양기술연구
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• 제40권1호
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• pp.37-46
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• 2004

제주도 연안 정치망 조업 시스템 개량과 개발분야에서 연안해역에서 널리 사용되고 있는 각망어구의 구조개량을 위한 기초연구로서 현재 사용되고 있는 실물망을 1/20로 축소하여 개량된 입구 구조를 갖춘 모형 어구 8종류를 제작하고, 실험 수조에서 고등어 어군을 이용하여 모형 어구에 대한 어군의 입 ${\cdot}$ 출망 행동을 관찰 분석하였는데, 그 결과는 다음과 같다. 1. 원통그물내에서의 어군의 행동 패턴은 원형 모양으로 한쪽 원통그물내에 체류하는 행동과 긴 타원형 모양으로 좌 ${\cdot}$ 우 원통그물내를 왕복 유영하는 행동패턴으로 분류할 수 있었다. 2. 모형 어구 내에서의 고등어 어군의 평균 유영 속도는 원통 그물 중간 부분에서 24.9cm/sec, 오른쪽 원통그물내에서 12.6cm/sec, 입구에서 32.0cm/sec였다. 3. 어군의 입망율은 경과 시간 60초일 때 표준 모형 어구에서는 47%였고, 깔대기 그물이 길이가 35cm 의 모형 어구에서는 40%로 나타났는데, 양자의 차이는 7% 정도로 그다지 크지 않았다. 4. 어군의 출망율은 경과 시간 60초일 때 표준 모형 어구에서는 69%였고, 깔대기 그물의 길이가 35cm 의 모형 어구에서는 10%로 나타났는데, 양자의 차이는 59% 정도로 그 폭이 컸다. 5. 어군의 잔여율은 경과 시간 60초일 때 표준 모형 어구에서는 31%였고, 깔대기 그물의 길이가 35cm의 모형 어구에서는 90%로 나타났는데, 양자의 차이는 59% 정도였다.

• 전자공학회논문지B
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• 제30B권12호
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• pp.12-20
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• 1993

In a conventional adaptive echo canceller, an ADF(Adaptive Digital Filter) with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to compute the coefficients, and NET detector using energy comparison method prevents the ADF to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yields more accurate detection of the start point of the NET signal.

• 융합정보논문지
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• 제11권10호
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• pp.45-52
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• 2021

본 논문에서는 U-Net 기반의 semantic segmentation 방법에서 정확도를 개선하기 위한 Atrous Residual U-Net (AR-UNet)을 제안하였다. U-Net은 의료 영상 분석, 자율주행 자동차, 원격 감지 영상 등의 분야에서 주로 사용된다. 기존 U-Net은 인코더 부분에서 컨볼루션 계층 수가 적어 추출되는 특징이 부족하다. 추출된 특징은 객체의 범주를 분류하는 데 필수적이며, 부족할 경우 분할 정확도를 저하시키는 문제를 초래한다. 따라서 이 문제를 개선하기 위해 인코더에 residual learning과 ASPP를 활용한 AR-UNet을 제안하였다. Residual learning은 특징 추출 능력을 개선하고, 연속적인 컨볼루션으로 발생하는 특징 손실과 기울기 소실 문제 방지에 효과적이다. 또한 ASPP는 특징맵의 해상도를 줄이지 않고 추가적인 특징 추출이 가능하다. 실험은 Cityscapes 데이터셋으로 AR-UNet의 효과를 검증하였다. 실험 결과는 AR-UNet이 기존 U-Net과 비교하여 향상된 분할 결과를 보였다. 이를 통해 AR-UNet은 정확도가 중요한 여러 응용 분야의 발전에 기여할 수 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.641-644
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• 2000

This paper studies coverability tree and reach-ability set of Petri net under the earliest filing rule. Conventional algorithm for coverability tree for ‘normal’ Petri net is not good for Petri net under the earliest firing rule. More over, it is shown that there exists no coverability graph for general class of earliest firing Petri net. Some subclasses are studied where coverability graph can be constructed.