• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.2
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• pp.101-111
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• 2008

Strain imaging in a medical ultrasound imaging system can differentiate the cancer or tumor in a lesion that is stiffer than the surrounding tissue. In this paper, a strain imaging technique using quasistatic compression is implemented that estimates the displacement between pre- and postcompression ultrasound echoes and obtains strain by differentiating it in the spatial direction. Displacements are computed from the phase difference of complex baseband signals obtained using their autocorrelation, and errors associated with converting the phase difference into time or distance are compensated for by taking into the center frequency variation. Also, to reduce the effect of operator's hand motion, the displacements of all scanlines are normalized with the result that satisfactory strain image quality has been obtained. These techniques have been incorporated into implementing a medical ultrasound strain imaging system that operates in real time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.10-17
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• 2007

The echo signal on ultrasonic transducer is a mixed signal from tissues, blood vessel walls, blood cells and noise. In this mixed-signal, the signal reflected from tissues and blood vessel walls is called clutter. It is necessary to extract pure blood signal from this mixed-signal, when measuring blood flow velocity with medical ultrasonic system The quality of measured blood flow velocity is highly dependent on sufficient attenuation of the clutter signals. In this paper, we suggest a clutter rejection method using ICA For simulation, the echo signals are generated by Field n ultrasonic simulation program In this echo signals, independent signals are separated by using ICA Then the blood signal is obtained from the separated signals. Blood flow velocity is measured by 2D autocorrelation method. We compare ICA clutter rejection method with PCA-based eigen filter method using both measured blood flow velocity profiles by 2D autocorrelation. In simulation results, ICA clutter rejection method can be better applied measuring blood flow velocity in noisy echo signals.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.3
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• pp.1-14
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• 2011

In order to determine temporal changes of the urban landscape, interdependence and interaction among geo-spatial objects can be analyzed using GIS analytic methods. In this study, to investigate changes in the landscape structure of the Namyangju area, the size and shape of landscape patches, and the distance between the patches were analyzed with the Spatial Autocorrelation Method. In addition, both global and local spatial autocorrelation analyses were conducted. The results of global Moran's I revealed that both patch size and shape index transformed to a more dispersed pattern over time. Next, the local Moran's I of patch size in all time series determined that almost all patches were of a high-low pattern. Meanwhile, the local Moran's I of the shape index was found to have changed from a high-high pattern to a high-low pattern in time series. Finally, as time passes, the number of hot spot patches about size and shape index had been decreased according to the results of hot spot analysis. These changes appeared around the development projects in the study area. From the results of this study, degradation of landscape patches in Namyangju were ascertained and their specific areas were delineated. Such results can be used as useful data in selecting areas for conservation and for preparing plans and strategies in environmental restoration.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.118-125
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• 2012

When monitoring an instrumental process, one often collects a host of data such as characteristic signals sent by a sensor in short time intervals. Characteristic data of short time intervals tend to be autocorrelated. In the instrumental processes often the practice of adjusting the setting value simply based on the previous one, so-called 'adjacent point operation', becomes more critical, since in the short run the deviations are harder to detect and in the long run they have amplified consequences. Stochastic modelling using ARIMA or AR models are not readily usable here. Due to the difficulty of dealing with autocorrelated data conventional practice is resorting to choosing the time interval where autocorrelation is weak enough then to using I-MR control chart to judge the process stability. In the autocorrelated instrumental processes it appears that using the Shewhart chart and the time interval data where autocorrelation is relatively not existent turns out to be a rather convenient and very useful practice to determine the process stability. However in the autocorrelated instrumental processes we intend to show that one would presumably do better using the EWMA control chart rather than just using the Shewhart chart along with some arbitrarily intervalled data, since the former is more sensitive to shifts given appropriate weights.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.731-740
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• 1999

Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.381-389
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• 2007

In this paper, the measuring method of underwater acoustic communication channel characteristics in the shallow water using the autocorrelation characteristic of PN sequence and the undorwater communication channel analysis results from the received signal sample data are described. For measuring the underwater acoustic communication channel characteristics, two PN sequences are used as a transmitted data of I-channel and Q-channel of QPSK symbol and QPSK signal is transmitted with symbol rate of 5 kHz and carrier frequency of 25 kHz. In the receiver the received signal, which pass through 675 m and 1492 m, is sampled and then stored. Using the stored sample data, the scattering function, coherent time, delay power profile, spaced-tone autocorrelation function, delay spread, and coherent bandwidth of each propagation distance cases are analyzed. Based on the analysis results, several guidelines are suggested for the design and implementation of underwater transmission system.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.247-256
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• 2009

In mass production industries such as steel making that have large equipment, sudden stops of production process due to machine failure can cause severe problems. To prevent such situations, machine diagnosis techniques play important roles. Many methods have been developed focusing on this subject. In this paper, we propose a method for the early detection of the failure on rotating machine, which is the most common theme in the machine failure detection field. A simplified method of calculating autocorrelation function is introduced and is utilized for ARMA model identification. Furthermore, an absolute deterioration factor such as Bicoherence is introduced. Machine diagnosis can be executed by this simplified calculation method of system parameter distance with weight. Proposed method proved to be a practical index for machine diagnosis by numerical examples.

• ETRI Journal
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• v.38 no.3
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• pp.425-434
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• 2016

A novel average magnitude difference function (AMDF)-based pitch detection scheme (PDS) is proposed to achieve better performance in speech quality. A performance evaluation of the proposed PDS is carried out through both a simulation and a real-time implementation of a speech analysis-synthesis system. The parameters used to compare the performance of the proposed PDS with that of PDSs that are based on either a cepstrum, an autocorrelation function (ACF), an AMDF, or circular AMDF (CAMDF) methods are as follows: percentage gross pitch error (%GPE); a subjective listening test; an objective speech quality assessment; a speech intelligibility test; a synthesized speech waveform; computation time; and memory consumption. The proposed PDS results in lower %GPE and better synthesized speech quality and intelligibility for different speech signals as compared to the cepstrum-, ACF-, AMDF-, and CAMDF-based PDSs. The computational time of the proposed PDS is also less than that for the cepstrum-, ACF-, and CAMDF-based PDSs. Moreover, the total memory consumed by the proposed PDS is less than that for the ACF- and cepstrum-based PDSs.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3E
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• pp.84-94
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• 2008

Displacement estimation is a crucial step in ultrasonic strain imaging. The displacement between a pre- and postcompression signal in the current data window is estimated by first shifting the postcompression signal by the displacement obtained in the previous data window to reduce their decorrelation and then determining the remaining part of the displacement through autocorrelation and conversion of phase difference into time delay. However, since strain image quality tends to vary with the amount of compression applied, we propose two new methods for enhancing strain image quality, i.e., displacement normalization and adaptive persistence. Both in vitro and in vivo experiments are carried out to acquire ultrasound data and produce strain images in real time under the application of quasi static compression. The experimental results demonstrate that the methods are quite effective in improving strain image quality and thus can be applied to implementing an ultrasound elasticity imaging system that operates in real time.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.895-898
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• 2004

본 논문에서는 기존의 개인 식별 방법의 한계를 해결하는 대안으로 떠오르고 있는 생체인식 기술 중 인식률이 뛰어난 홍채인식 시스템에 대해 연구하고자 한다. 먼저 홍채인식 시스템의 구현을 위해 신호처리 분야에서 많이 사용되고 있는 wavelet 변환 중 Haar wavelet과 고차 국소 자기 상관 특징을 이용하여 홍채의 특징을 추출하여 특징벡터의 크기를 최소화 하였다. 또, 인식률을 높이기 위해 오류 역전파 학습 알고리즘을 이용하여 홍채패턴에 기반한 신원 확인 및 검증을 위한 개선된 방법을 제시하였다. 학습이 완료된 신경망에 대한 학습데이터와 테스트 데이터의 인식률을 실험한 결과 학습된 데이터는 평균 인식률 $97.4\%$, 테스트 데이터는 $95.5\%$의 인식률을 보였다.