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The research and application of heart sound (HS) analysis for cardiovascular disease (CVD) diagnosis has attracted more attention recently. Unlike other relevant HS analysis research, such as HS detection/component segmentation, HS feature extraction/classification etc., the proposed research treats HS as a whole and focuses mainly on comparing the similarity of acoustical characteristics reflecting pathological condition between two HSs, one of which is HS under test and another is the HS with known CVD. The concrete procedure refers to alignment of the HS into sequence and evaluating the similarity index through complexity and similarity analysis. In accordance with specific characteristics of HS, several relevant technologies such as musical instrument digital interface (MIDI), binary coding, N-gram, Lempel-Ziv (L-Z) complexity as well as super-symmetric comparison distance (SCD) similarity metric etc. are researched to be adapted and cascaded to realize the aforementioned target successfully. The contribution lies in that the aligning schemes including binary and N-gram are thoroughly investigated and then testing results witnessing the superiority of using N-gram in proposed approach are presented. The success of such a novel approach would not only assign a the new life to the traditional auscultation CVD diagnosis, but also simplify CVD diagnosis greatly leading to extensive application of such an efficient non-invasive physical diagnostic method in e-home healthcare.

Extraction and instant translation of text from static images and dynamic videos is a very challengeable young research area, which nevertheless attracts increasing researchers' attentions. The traditional scanner-based document analysis techniques provide a good reference and technical background, but they cannot be adapted directly on camera- captured images or videos. It is found that the text extraction from camera-captured images or video frames had highly suffered from low resolution, blur, perspective distortion, and various brightness or grayscale, as well as complex layout and interaction of the content with background, which had become the inevitable obstacles in realizing the visual translation. Towards solving the aforementioned bottleneck problems, a novel technique of detecting and extracting text regions on camera-captured and video images for realizing more accurate text recognition is proposed. As a result, the higher accuracy of camera-based visual translation is witnessed from the obtained testing results.

Ferromagnetic-nonmagnetic heterogeneous Fe27Co23Pb50 ternary metal nanowire arrays were successfully fabricated by alternating current electrodeposition into anodic alumina oxide (AAO) template. The effects of the different annealing temperatures (100, 200, 300, 400, 500, 600°C) on the structure and magnetic properties have been discussed. X-ray diffraction observations indicated that FeCo and Pb phases coexist for the as-deposited and annealed samples. Magnetic measurements indicate that the nanowire arrays have high perpendicular magnetic anisotropy with their easy axis parallel to the nanowire arrays. The coercivity and remanence ratio increases as the annealing temperature rises, reaches their maximum at 400°C, and then decreases as the annealing temperature rises further. The mechanism of the magnetic properties and magnetic variety should be attributed to the special structure of the nanowires∕AAO.