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This paper presents the feed-forward multichannel active noise control which was simulated on LabVIEW and experimented on two channel feed-forward active noise control in real-time. The simulation of feed-forward multichannel active noise control system was built on LabVIEW by using FxLMS algorithm and other algorithms such as Variable Step-size (VSS) and saturation compensation. Moreover, LMS and VSS LMS algorithm were used to train the secondary path in order to improve the convergence speed and stabilization of ANC system in the real-time. The experimental results show that the ANC system in real-time using variable step-size and without using variable step-size algorithm work effectively with noise sources which were synthesized from one to three frequencies. The noise level in these cases decreased around 12 dB - 35 dB and the noise reduction radius measured is about 3 cm around the microphone.

Thanks to the Electrocardiography (ECG) signal and its features, some serious heart diseases can be diagnosed and treated at the early stage. In this paper, we focus on the detecting QRS complex of ECG, more specifically, the R wave. While Pan — Tompkins's algorithm effectively extracts R peak, our new algorithm bases on Pan – Tompkins's model giving the same results but providing possibility of detecting separately Q, R and S features. In order to verify the performance of our method, we compared extracted features (R feature) of the new algorithm built on Simulink with the results from the original Pan – Tompkins's algorithm reassembled in Matlab. Besides, the delay and error analysis of the new algorithm on real-time system (TMS320C6713 DSK) had been done and gain some preliminary results.

The objective of our study was to compare a breath-hold fat-suppressed fast-recovery fast spin-echo (FSE) T2-weighted sequence with a respiratory-triggered fat-suppressed FSE T2-weighted sequence to assess the effect on image quality and lesion detection and characterization in clinical hepatic imaging.Both the breath-hold fat-suppressed fast-recovery FSE and respiratory-triggered fat-suppressed FSE T2-weighted sequences were acquired in 46 patients. Two radiologists, blinded to clinical data, independently evaluated randomized images from both sequences. Qualitatively, images were graded on a 5-point scale for five different characteristics. The number and location of lesions were recorded. The confidence of detection and the confidence of characterization (solid vs nonsolid) were graded on a 5-point scale. A consensus review using radiology, clinical, and pathology data served as the standard. Receiver operating characteristic (ROC) curve analysis (area under the ROC curve [A(z)]) was used to compare each reviewer's interpretation against the consensus interpretation. Quantitative analysis was performed by calculating the liver signal-to-noise ratio (SNR), liver-to-spleen contrast-to-noise ratio (CNR), and lesion-to-liver CNR. Both one- and two-tailed Student's t tests were used to check for significance.Qualitatively, both reviewers graded the breath-hold fat-suppressed fast-recovery FSE T2-weighted sequence better than the respiratory-triggered fat-suppressed FSE T2-weighted sequence on all five characteristics (p0.005). Of 78 lesions detected, 29 were characterized as solid; 47, nonsolid; and two, indeterminate. On ROC analysis, there were no significant differences between the breath-hold fat-suppressed fast-recovery FSE and respiratory-triggered fat-suppressed FSE T2-weighted sequences in lesion detection (A(z) reviewer 1, 0.77 and 0.83, respectively, [p = 0.12]; A(z) reviewer 2, 0.84 and 0.80, respectively [p = 0.12]) or in lesion characterization (A(z) reviewer 1, 0.86 and 0.92, respectively [p = 0.33]; A(z) reviewer 2, 0.90 and 0.91, respectively [p = 0.79]). Quantitatively, liver SNRs, spleen CNRs, and lesion CNRs (solid and nonsolid lesions) were significantly better on the breath-hold fat-suppressed fast-recovery FSE T2-weighted images than on the respiratory-triggered fat-suppressed FSE T2-weighted images (p0.005).Breath-hold fat-suppressed fast-recovery FSE T2-weighted images were of better quality than respiratory-triggered fat-suppressed FSE T2-weighted images, and lesion detection and characterization were comparable.