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This paper presents a discrimination method of Sleep Apnea Syndrome (SAS) and early detection of potential Sleep Apnea Syndrome (Pre-SAS) using sleep breath sound, by which each subject can take the required data for the diagnosis at home only with a voice recorder. Sleep breath sound of around two hours is analyzed statistically for detecting SAS patients. Long silence sections in the sleep breath sound and the biggest sound pressure typically occurred after them are compared for distinguishing Pre-SAS, SAS patients and non-patients. The k-means method is applied for classifying the above sound data. The proposed method drastically reduces the time and effort required for SAS diagnosis compared to the current medical approaches. Experimental results show the effectiveness of the proposed method, by which 100 % accuracy of discrimination is achieved.

In this paper, we propose the novel directional Wavelet Transform based on the Complex Discrete Wavelet Transform(CDWT). The CDWT is one of the Wavelet Transform and widely used as space-frequency analysis method for the signal and the image. The CDWT decomposes the image into directional components from the frequency analysis. And then, we can get the border, discontinuities and edges in the image. This property is called Directional Selection and this property is expected to give us shape information and geometric features. But, previous Directional Selection only offers the six directional components and features. Thus we firstly design the directional filter that can extract many directional feature rather than previous one. Secondly we propose the novel directional Wavelet Transform combining with previous CDWT and designed directional filters. Finally, we apply the proposed method into medical image processing.

In this study, in order to verify the effectiveness of the variable-band-filters discrete wavelet transform (VBF-DWT) and construction method of the variable band filter (VBF), a fetal ECG extraction has been carried out and the main results obtained are shown as follows. The approach to configuration variable band filter (VBF) by selecting the frequency band only fetal ECG component presented is effective to configure the optimal base sensible signal. The extraction of the fetal electrocardiogram is successful by applying soft-thresholding to VBF-DWT, which uses the constructed VBF. The information extropy is selected as an evaluation index, and two kinds of ECG signal are used to evaluate the relative performance of the wavelet packet transform (WPT) and the proposed VBF-DWT. The first kind of ECG signal is synthesized using a maternal ECG, fetal ECG, and white noise; the second kind is real measured mixed noisy maternal-fetal ECG obtained using ICA. The results show that the VBF-DWT basis (designed using VBF) outperforms the WPT basis that was elected by the basis algorithm (BBA).

In this study, high-speed tensile testing for notched specimen is conducted to investigate the impact property of Polydimethylsiloxane copolymerized Polycarbonate (PDMS-PC) compared with Polycarbonate (PC). Depending on the test temperature and tensile speed, brittle or ductile fractures are observed for PC. However, only ductile fractures are seen for PDMS-PC even at the high speed 7000mm/s and low temperature 243K. The impact properties are also considered in terms of the time-temperature superposition principle. Then, master curves for the final fracture elongation for both PC and PDMS-PC are constructed in terms of the strain rate at the notch in conjunction with shift factors. The fracture behavior can be predicted for the wide range of impact speed under various temperatures from these master curves.