• Journal of the Korean Society for Nondestructive Testing
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• v.16 no.1
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• pp.34-45
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• 1996

The signal pattern recognition program which can perform signal acquisition and processing, the extraction and selection of features, the classifier design and the evaluation, is developed and applied to the classification of artificial defects in the weld zone of Austenitic STS304. The neural network classifier is compared with the linear discriminant function classifier and the empirical Bayesian classifier. The signal through a broadband sensor is compared with that through a resonance type sensor. In recognition rate, the neural network classifier is best, and the signal through a broadband sensor is better.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.107-110
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• 2003

In this paper, the optimal position selection of error sensors and transducers to attenuate interior noise from outside noise sources using active control techniques is presented. To get an optimal control characteristics in adaptive noise control systems, it is necessary to optimize the positions of sensors and transducers. A new type of simulated annealing method has been proposed as searching technique to find optimal transducers and sensors positions in which the sum of the squared pressures at sensor position in an enclosure can be best minimized. Computer simulations and experiments have been performed to show the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4A
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• pp.291-301
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• 2009

In this paper, the effect of ISI(Inter-Symbol Interference) and ICI(Inter-Carrier Interference) due to time difference of arrival on OFDMA-based mobile multi-hop relay (MMR) systems is analyzed. Analyses are performed for the ISI caused by the previous OFDMA symbol transmitted from neighboring macro or relay cell as well as the ISI caused by the next OFDMA symbol transmitted from neighboring macro or relay cell. Then, an effective SINR(Signal to Interference plus Noise Ratio) estimation method and a path selection method considering time difference of arrival are proposed to minimize the effect of ISI and ICI. It is shown by simulation that the performance degradation caused by time difference of arrival can be significantly mitigated when the proposed path selection method is applied to the uplink of OFDMA-based MMR systems.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.2
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• pp.6-14
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• 2007

In this paper, we propose and observe the Adaptive Modulation system with optimal Turbo Coded V-BLAST (Vertical-Bell-lab Layered Space-Time) technique that is applied the extrinsic information from MAP (Maximum A Posteriori) Decoder in decoding Algorithm of V-BLAST: ordering and slicing. The extrinsic information is used by a priori probability and the system decoding process is composed of the Main Iteration and the Sub Iteration. And comparing the proposed system with the Adaptive Modulation system using conventional Turbo Coded V-BLAST technique that is simply combined V-BLAST with Turbo Coding scheme, we observe how much throughput performance has been improved. In addition, we observe the proposed system using STD (Selection Transmit Diversity) scheme. As a result of simulation, Comparing with the conventional Turbo Coded V-BLAST technique with the Adaptive Modulation systems, the optimal Turbo Coded V-BLAST technique with the Adaptive Modulation systems has better throughput gain that is about 350 Kbps in 11 dB SNR range. Especially, comparing with the conventional Turbo Coded V-BLAST technique using 2 transmit and 2 receive antennas, the proposed system with STD (Selection Transmit Diversity) scheme show that the improvement of maximum throughput is about 1.77 Mbps in the same SNR range.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.5
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• pp.603-608
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• 2013

Hanwoo have been subjected over the last seventy years to intensive artificial selection with the aim of improving meat production traits such as marbling and carcass weight. In this study, we performed a signature of selection analysis to identify recent positive selected regions driven by a long-term artificial selection process called a breeding program using whole genome SNP data. In order to investigate homozygous regions across the genome, we estimated iES (integrated Extended Haplotype Homozygosity SNP) for the each SNPs. As a result, we identified two highly homozygous regions that seem to be strong and/or recent positive selection. Five genes (DPH5, OLFM3, S1PR1, LRRN1 and CRBN) were included in this region. To go further in the interpretation of the observed signatures of selection, we subsequently concentrated on the annotation of differentiated genes defined according to the iES value of SNPs localized close or within them. We also described the detection of the adaptive evolution at the molecular level for the genes of interest. As a result, this analysis also led to the identification of OLFM3 as having a strong signal of selection in bovine lineage. The results of this study indicate that artificial selection which might have targeted most of these genes was mainly oriented towards improvement of meat production.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2080-2085
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• 2018

There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3647-3653
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• 2012

In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.141-147
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• 2017

Scalable extension of High Efficiency Video Coding (SHVC) standard uses the up-sampled residual data from the base layer to make a residual data in the enhancement layer. This paper describes an efficient algorithm for improving coding gain by using the filtered residual signal of base layer in the Scalable extension of High Efficiency Video Coding (SHVC). The proposed adaptive filter selection mechanism uses the smoothing and sharpening filters to enhance the quality of inter-layer prediction. Based on two filters and the existing up-sampling filter, a rate-distortion (RD)-cost fuction-based competitive scheme is proposed to get better quality of video. Experimental results showed that average BD-rate gains of 1.5%, 2.1%, and 1.7% for Y, U and V components, respectively, were achieved, compared with SHVC reference software 5.0, which is based on HEVC reference model (HM) 13.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.3
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• pp.22-30
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• 2010

This paper proposes a combination system of Adaptive Modulation and Coding (AMC) and Multiple Input Multiple Output (MIMO), which improves the throughput and has a better reliability. In addition, the system includes Precoding, Antenna Subset Selection and MIMO Mode Selection scheme. Finally, we make a performance analysis of the proposed system. The principal environmental parameters for the simulation experiment consist of a frequency non-selective rayleigh fading channel and a Spreading Factor (SF) of 16. Other parameters may be included in order to fulfill the requirements of the HSDP A Standard. The proposed system has a higher throughput and more reliability than the conventional system, which does not include MIMO Mode Selection scheme, Precoding or Antenna Subset Selection. According to the simulation results, the proposed system reaches the maximum throughput at 8dB, presentlng an improvement of 6dB and twice higher throughput, respect to the conventional system. Specifically, at the point of -6dB, the conventional system reaches 2.5Mbps, while the proposed system reaches 6.4Mbps at the same SNR. Also, at the point of 2dB, each system reaches 7.5Mbps (conventional system) and 15.3Mbps (proposed system), with near twice the difference. According to the results exposed above, we can conclude that the system proposed in this paper has, as the greatest contribution, the improvement of the throughput, especially, the average throughput.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1168-1182
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• 2017

In the past decades, various image regularization methods have been introduced. Among them, total variation model has drawn much attention for the reason of its low computational complexity and well-understood mathematical behavior. However, regularization parameter estimation of total variation model is still an open problem. To deal with this problem, a novel adaptive regularization parameter selection scheme is proposed in this paper, by means of using the local spectral response, which has the capability of locally selecting the regularization parameters in a content-aware way and therefore adaptively adjusting the weights between the two terms of the total variation model. Experiment results on simulated and real noisy image show the good performance of our proposed method, in visual improvement and peak signal to noise ratio value.