• Journal of the Korean Wood Science and Technology
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• v.13 no.3
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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.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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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.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.251-258
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• 2021

In this paper, we proposed an encoder-decoder model utilizing residual learning to improve the accuracy of the U-Net-based semantic segmentation method. U-Net is a deep learning-based semantic segmentation method and is mainly used in applications such as autonomous vehicles and medical image analysis. The conventional U-Net occurs loss in feature compression process due to the shallow structure of the encoder. The loss of features causes a lack of context information necessary for classifying objects and has a problem of reducing segmentation accuracy. To improve this, The proposed method efficiently extracted context information through an encoder using residual learning, which is effective in preventing feature loss and gradient vanishing problems in the conventional U-Net. Furthermore, we reduced down-sampling operations in the encoder to reduce the loss of spatial information included in the feature maps. The proposed method showed an improved segmentation result of about 12% compared to the conventional U-Net in the Cityscapes dataset experiment.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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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.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.326-336
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• 2003

In order to modify the construction of gizzard shad coastal purse seine net with possible to the laborsaving of fishing operation in the coastal small fishing vessels, the model experiments were carried out on the model nets for several conventional nets using in the field and the experimental nets was manufactured as 1/100 and 1/60 of the full scale net. The results obtained are summarized as follows；1. In the case of the conventional net and reduction rate 75% in conventional net with purse line the fishing efficiency decreased, the lead line was upward for the surface and the pursing depth of pursing line was very shallow to 2∼3m. 2. In the case of the net having maximum depth in center part designed in this study, the length of float and lead line was 60% of conventional net, the depth of net was fixed 20m to selvage line of the both of the end and extend gradually with 50m, 40m, 30m to the center. Among the these net, depth of pursing line was 20∼23m for 50m and 7∼15m for 40m, 30m the depth of net. These results were suitable for interception of fish school in fishing ground, but several problems will be caused by the depth and current of fishing ground.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.1
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• pp.37-46
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• 2004

In order to increase fishing efficiencies of the fyke net used in the coast of Jeju Island, water tank experiment was caried out entering and escaping behavior using nets that were reduced to 1/20 of the size of the full scale fyke net and were improved to have antrance structure, and mackerel Scomber japonicus as experimental fish. The results of measurement are as follows : 1. Fish school behavior in the main net was showed two different patterns : swimming in a circle in the right space of the main net and swimming back and forth in ellipse in the right and left space. 2. The swimming speed of mackerel school was 23.9. 12.6 and 32.0cm/sec in the center space, right space of main net and in the mouth 3. The entering rate of fish school was 40% in net with 35cm length of the upper and funnel net in the mouth of fyke model net and 49% in conventional type fyke model net. 4. The escaping rate of fish school was 10% in net with 35cm length of the upper and funnel net in the mouth of fyke model net and 69% in conventional type fyke model net. 5. The remain rate of fish school was 90% in net with 35cm length of the upper and funnel net in the mouth of fyke model net and 31% in conventional type fyke model net.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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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.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.45-52
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• 2021

In this paper, we proposed an Atrous Residual U-Net (AR-UNet) to improve the segmentation accuracy of semantic segmentation method based on U-Net. The U-Net is mainly used in fields such as medical image analysis, autonomous vehicles, and remote sensing images. The conventional U-Net lacks extracted features due to the small number of convolution layers in the encoder part. The extracted features are essential for classifying object categories, and if they are insufficient, it causes a problem of lowering the segmentation accuracy. Therefore, to improve this problem, we proposed the AR-UNet using residual learning and ASPP in the encoder. Residual learning improves feature extraction ability and is effective in preventing feature loss and vanishing gradient problems caused by continuous convolutions. In addition, ASPP enables additional feature extraction without reducing the resolution of the feature map. Experiments verified the effectiveness of the AR-UNet with Cityscapes dataset. The experimental results showed that the AR-UNet showed improved segmentation results compared to the conventional U-Net. In this way, AR-UNet can contribute to the advancement of many applications where accuracy is important.

• Proceedings of the IEEK Conference
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• 2000.07b
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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.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.329-332
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• 1991

This paper presents an algorithm to reduce the time to solve Power Equations using a Neural Net. The Neural Net is trained with samples obtained through the conventional AC Load Flow. With these samples, the Neural Net is constructed and has the function of a linear interpolation network. Given arbitrary load level, this Neural Net generates voltage magnitudes and angles which are linear interpolation of real and reactive powers. Obtained voltage magnitudes and angles are substituted to Power Equations, Real and reactive powers are found. Thus, a new sample is generated. This new experience modifies weight matrix. Continuing to modify the weight matrix, the correct solution is achieved. comparing this method with AC Load flow, this method is faster. If we consider parallel processing, this method is far faster than conventional ones.