• Journal of radiological science and technology
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• v.32 no.1
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• pp.17-24
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• 2009

Noise evaluation for an image has been performed by root mean square (RMS) granularity, autocorrelation function (ACF), and Wiener spectrum. RMS granularity stands for standard deviation of photon data and ACF is acquired by integration of 1 D function of distance variation. Fourier transform of ACF results in noise power spectrum which is called Wiener spectrum in image quality evaluation. Wiener spectrum represents noise itself. In addition, along with MTF, it is an important factor to produce detective quantum efficiency (DQE). The proposed evaluation method using Wiener spectrum is expected to contribute to educate the concept of Wiener spectrum in educational organizations, choose the appropriate imaging detectors for clinical applications, and maintain image quality in digital imaging systems.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.9-17
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• 2013

Purpose: The goal of this study was to develop a methodology for the demand forecast of tractor, riding type rice transplanter and combine harvester using an ARIMA (autoregressive integrated moving average) model, one of time series analysis methods, and to forecast their demands from 2012 to 2021 in South Korea. Methods: To forecast the demands of three kinds of machines, ARIMA models were constructed by following three stages; identification, estimation and diagnose. Time series used were supply and stock of each machine and the analysis tool was SAS 9.2 for Windows XP. Results: Six final models, supply based ones and stock based ones for each machine, were constructed from 32 tentative models identified by examining the ACF (autocorrelation function) plots and the PACF (partial autocorrelation function) plots. All demand series forecasted by the final models showed increasing trends and fluctuations with two-year period. Conclusions: Some forecast results of this study are not applicable immediately due to periodic fluctuation and large variation. However, it can be advanced by incorporating treatment of outliers or combining with another forecast methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.33-41
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• 1994

A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.187-199
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• 2022

Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

• Journal of Biomedical Engineering Research
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• v.36 no.4
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• pp.103-108
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• 2015

Discrimination of Parkinson's disease (PD) from Essential tremor (ET) is often misdiagnosed in clinical practice. Since tremor is time-varying signal, and dominant and harmonic frequencies are shown in tremor only with moderate or severe symptom, there are some limitations to use frequency related features. Moreover, patients with PD or ET can suffer from both resting tremor and postural tremor. In this study, 28 patients with PD and 17 patients with ET were enrolled. Tremor was measured with accelerations on the more affected hand during resting and postural conditions. The ratio of root mean square (RMS) of resting tremor to RMS of postural tremor, the mean coefficients of autocorrelation function (ACF), and the mean of differences of two adjacent coefficients of ACF at resting and postural were calculated and compared between PD and ET. The performance showed 98% accuracy with support vector machine and leave-one-out cross validation. In addition, the method accurately differentiated the patients with tremor-dominant PD from patients with ET, with 100% accuracy. Therefore, the developed algorithm can assist clinicians in diagnosing and categorizing patients with tremor, especially, patients with mild symptom or the early stage of a disease, for proper treatment.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.239-246
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• 2017

This paper compares the speech signal parameters between Korean and Chinese for Korean pronunciation /ㄹ/, which is caused many errors by Chinese leaners. Allophones of /ㄹ/ in Korean is divided into lateral group and tap group. It has been investigated the reasons for these errors by studying the similarity and the differences between Korean /ㄹ/ pronunciation and its corresponding Chinese pronunciation. In this paper, for the purpose of comparison the speech signal parameters such as energy, waveform in time domain, spectrogram in frequency domain, pitch based on ACF, Formant frequencies are used. From the phonological perspective the speech signal parameters such as signal energy, a waveform in the time domain, a spectrogram in the frequency domain, the pitch (F0) based on autocorrelation function (ACF), Formant frequencies (f1, f2, f3, and f4) are measured and compared. The data, which are composed of the group of Korean words by through a philological investigation, are used and simulated in this paper. According to the simulation results of the energy and spectrogram, there are meaningful differences between Korean native speakers and Chinese leaners for Korean /ㄹ/ pronunciation. The simulation results also show some differences even other parameters. It could be expected that Chinese learners are able to reduce the errors considerably by exploiting the parameters used in this paper.

• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.169-180
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• 2007

When an image is captured, motion blurs are caused by relative motion between the camera and the scene, In the case of the camera is moving, the extents of the motion blur are spatially variant according to distances from the camera to the objects. Although the camera is fixed, the extents of the motion blur are spatially variant according to various speeds of the moving objects. Unexpected blur effect very often degrades the quality of the image and it needs to be restored, To restore the spatially variant blurred image, each of the point spread function (PSF) should be identified, In this paper, we propose a new method for the identification of blur extent locally from the image in which the spatially variant motion blur is caused. Experiment shows that the proposed method identifies blur extent well.