A combined kalman filter — Discrete wavelet transform method for leakage detection of crude oil pipelines

Author(s):  
Zhang Yu ◽  
Li Jian ◽  
Zeng Zhoumo ◽  
Shijiu Jin
2015 ◽  
Vol 81 ◽  
pp. 56-64 ◽  
Author(s):  
U. Rajendra Acharya ◽  
K. Sudarshan Vidya ◽  
Dhanjoo N. Ghista ◽  
Wei Jie Eugene Lim ◽  
Filippo Molinari ◽  
...  

2010 ◽  
Vol 139-141 ◽  
pp. 2029-2032
Author(s):  
Dong Cao ◽  
Jian Wei Ye ◽  
Jun Yi ◽  
Wen Jie Ruan ◽  
Chong Chen

The human pulse-condition diagnosis is an important part of the traditional Chinese medicine (TCM) which is difficult to recognize accurately by doctor’s subjective experience. Objective identification of pulse-conditions has important meanings for modernization of TCM. In this paper human pulse-condition system transfer function model and model parameter estimation were introduced, which are used to construct four kinds of typical pulse-conditions simulation signals. There are normal pulse, taut pulse, slippery pulse and thready pulse. And then, discrete wavelet transform for extracting the multi-scale energy characteristics and wavelet packet decomposition for extracting the multi-band energy characteristics are proposed so as to recognize the pulse-conditions simulation signals. The results show that the recognition effect of discrete wavelet transform method is better. Moreover, the data features of characteristic parameters demonstrate the reality of simulation signals.


Author(s):  
J. Jerisha Liby ◽  
T. Jaya

This paper proposes a new watermarking algorithm based on a single-level discrete wavelet transform (DWT). This method initially chooses ‘[Formula: see text]’ number of carrier frames to hide the data. After estimating the carrier frames, each frame is separated into RGB frames. Each R, G, and B frames are decomposed using a single-level DWT. The horizontal and vertical coefficients are selected to embed the watermark information since small changes in the horizontal and vertical coefficients do not highly affect the quality of the video frame. The watermark image pixels are shuffled using a predetermined key before embedding. The shuffled pixels are converted to binary, and they are grouped into three data matrices. Each data matrix is embedded in horizontal and vertical coefficients of the R, G and B frames of the video frame. After embedding the data, the watermarked video is reconstructed using the original approximation coefficients, the embed coefficients, and the original diagonal coefficients. During the extraction process, the watermark is extracted from the horizontal and vertical coefficients of the watermarked video. Experimental result reveals that the proposed method outperforms other related methods in terms of video quality and structural similarity index measurement.


Author(s):  
Abdullah Al Kafee ◽  
Aydin Akan

Electrogastrogram is used for the abdominal surface measurement of the gastric electrical activity of the human stomach. The electrogastrogram technique has significant value as a clinical tool because careful electrogastrogram signal recordings and analyses play a major role in determining the propagation and coordination of gastric myoelectric abnormalities. The aim of this article is to evaluate electrogastrogram features calculated by line length features based on the discrete wavelet transform method to differentiate healthy control subjects from patients with functional dyspepsia and diabetic gastroparesis. For this analysis, the discrete wavelet transform method was used to extract electrogastrogram signal characteristics. Next, line length features were calculated for each sub-signal, which reflect the waveform dimensionality variations and represent a measure of sensitivity to differences in signal amplitude and frequency. The analysis was carried out using a statistical analysis of variance test. The results obtained from the line length analysis of the electrogastrogram signal prove that there are significant differences among the functional dyspepsia, diabetic gastroparesis, and control groups. The electrogastrogram signals of the control subjects had a significantly higher line length than those of the functional dyspepsia and diabetic gastroparesis patients. In conclusion, this article provides new methods with increased accuracy obtained from electrogastrogram signal analysis. The electrogastrography is an effective and non-stationary method to differentiate diabetic gastroparesis and functional dyspepsia patients from the control group. The proposed method can be considered a key test and an essential computer-aided diagnostic tool for detecting gastric myoelectric abnormalities in diabetic gastroparesis and functional dyspepsia patients.


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