• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.481-493
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• 1995

An ARIMA signal observed with measurement error is shown to have another ARIMA representation with nonlinear restrictions on parameters. For this model, the restricted Newton-Raphson estimator(RNRE) of the unit root is shown to have the same limiting distribution as the ordinary least squares estimator of the unit root in an AR(1) model tabulated by Dickey and Fuller (1979). The RNRE of parameters of the ARIMA(p,1,k) process and unit root tests base on the RNRE are developed.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.429-436
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• 2009

This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) process that is being adjusted automatically after each observation using a minimum mean squared error adjustment policy. When the control chart signals after the occurrence of a special cause, the special cause will be detected and eliminated from the process by the rectifying action. However, when the elimination of the special cause costs high or is not practically possible, an alternative action is to readjust the process with appropriately modified adjustment scheme. In this paper, we propose the readjustment procedure after having a true signal, and show that the use of the readjustment can reduce the deviation of a process from the target.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.84-89
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• 2014

Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.3
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• pp.169-176
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• 2000

The partial discharge(PD) signal, may seems to be stochastic and merely random, was investigated using the method to discern between chaos and random signal, e.g. correlation integral, Lyapunov characteristic exponents and etc. For the purpose of obtaining experimental data, partial discharge detecting system via computer aided acoustic sensor, detect PD signal from the insulating system, was used. While this method is very different from typical statistical analysis from the point of view of a nonlinear analysis, it can provide better interpretable criterion according to the time evolution with a degradation process in the same type insulating system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1545-1550
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• 2014

Fault detection and diagnosis (FDD) of photovoltaic (PV) power systems is one of significant techniques for reducing economic loss due to abnormality occurred in PV modules. This paper presents a new FDD method against PV power systems by using statistical comparison. This comparative approach includes deviation signals between the outputs of two neighboring PV modules. We first define a binary hypothesis testing under such deviation and make use of a generalized likelihood ratio testing (GLRT) theory to derive its FDD algorithm. Additionally, a recursive computational mechanism for our proposed FDD algorithm is presented for improving a computational effectiveness in practice. We carry out a real-time experiment to test reliability of the proposed FDD algorithm by utilizing a lab based PV test-bed system.

• Tribology and Lubricants
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• v.30 no.3
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• pp.139-145
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• 2014

Nowadays, most micro-patterns are manufactured during flow line production. However, a conventional rotary chemical mechanical polishing (CMP) system has a limited throughput for the fabrication of large and flexible electronics. To overcome this problem, we propose a novel linear roll-CMP system for the planarization of large-area electronics. In this paper, we present a statistical analysis on the linear roll-CMP process of copper-clad laminate (CCL) to determine the impacts of process parameters on the material removal rate (MRR) and its non-uniformity (NU). In the linear roll-CMP process, process parameters such as the slurry flow rate, roll speed, table feed rate, and down force affect the MRR and NU. To determine the polishing characteristics of roll-CMP, we use Taguchi's orthogonal array L16 (44) for the experimental design and F-values obtained by the analysis of variance (ANOVA). We investigate the signal-to-noise (S/N) ratio to identify the prominent control parameters. The "higher is better" for the MRR and "lower is better" for the NU were selected for obtaining optimum CMP performance characteristics. The experimental and statistical results indicate that the down force and roll speed mainly affect the MRR and the down force and table feed rate determine the NU in the linear roll-CMP process. However, over 186.3 N of down force deteriorates the NU because of the bending of substrate. Roll speed has little relationship to the NU and the table feed rate does not impact on the MRR. This study provides information on the design parameter of roll-CMP machine and process optimization.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.160-163
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• 2002

This paper presents a statistical technique for audio watermarking. We describe the application of the promising public key watermarking method to the patchwork algorithm. Its detection process does not need the original content nor the secret key used in the embedding process. Special attention is given to statistical method working in the frequency domain. We will present a solution of robust watermarking of audio data. In this scheme, an extension of patchwork audio watermarking is presented which enables public detection of the watermark. Experimental results show good robustness of the approach against MP3 compression and other common signal processing manipulations.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.276-283
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• 2021

In this paper, we propose an effective noise reduction method for photon counting imaging using a discrete wavelet transform. Conventional 2D photon counting imaging was used to visualize the object under dark conditions using statistical methods, such as the Poisson random process. The photons in the scene were estimated using a statistical method. However, photons which disturb the visualization and decrease the image quality may occur in the background where there is no object. Although median filters are used to reduce the noise, the noise in the scene remains. To remove the noise effectively, our proposed method uses the discrete wavelet transform, which removes the noise in the scene using a specific thresholding method that utilizes photon counting imaging characteristics. We conducted an optical experiment to demonstrate the denoising performance of the proposed method.

• Journal of Sensor Science and Technology
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• v.8 no.6
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• pp.469-475
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• 1999

The chips may be produced in the form of either broken chips or unbroken chips in turning process. The unbroken chips are dangerous to the operator and difficult to handle at high speed machining. The signal of Acoustic Emission is related to cutting conditions, tool materials, test conditions and tool geometry in turning. The relationship between AE signal and chip formation was experimentally investigated. The experimental results show that two types of chip formations are possible to classify from the statistical analysis of the amplitude of AE signal. The AE-sensor could be used to monitor the chip condition in turning.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.33-38
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• 2005

Degradation is generated by several causes in the process of digitalization or transmission of data. And its essential cause is noise. Therefore, researches for wavelet-based methods which reconstruct signal degraded by noise have continued. In AWGN(addtive white gaussian noise) environment, the general trend for denoising is to use the thresholding method. Reconstructed signal includes a lot of noise because these methods only consider statistical characteristic regarding noise. In this paper, we present a new method which uses the cumulation of wavelet detail coefficients. As a result, reconstruction of edges and denoising performance are improved. Also we compare existing methods using SNR(signal-to-noise ratio) as the standard of judgement of improvemental effect.