In this paper, the method of differentiating asthmatic and non-asthmatic patients using the frequency analysis of capnogram signals is presented. Previously, manual study on capnogram signal has been conducted by several researchers. All past researches showed significant correlation between capnogram signals and asthmatic patients. However all of them are just manual study conducted through the conventional time domain method. In this study, the power spectral density (PSD) of capnogram signals is estimated by using Fast Fourier Transform (FFT) and Autoregressive (AR) modelling. The results show the non-asthmatic capnograms have one component in their PSD estimation, in contrast to asthmatic capnograms that have two components. Furthermore, there is a significant difference between the magnitude of the first component for both asthmatic and non-asthmatic capnograms. The effectiveness and performance of manipulating the characteristics of the first frequency component, mainly its magnitude and bandwidth, to differentiate between asthmatic and non-asthmatic conditions by means of receiver operating characteristic (ROC) curve analysis and radial basis function (RBF) neural network were shown. The output of this network is an integer prognostic index from 1 to 10 (depends on the severity of asthma) with an average good detection rate of 95.65% and an error rate of 4.34%. This developed algorithm is aspired to provide a fast and low-cost diagnostic system to help healthcare professional involved in respiratory care as it would be possible to monitor severity of asthma automatically and instantaneously.
Pomegranate peel is a rich source of phenolic compounds (such as punicalagin and hydroxybenzoic acids). However, the content of such bioactive compounds in the peel extract can be affected by extraction type and condition. It was hypothesized that the optimization of a pulsed ultrasound-assisted extraction (PUAE) technique could result in the pomegranate peel extract with higher yield and antioxidant activity. The main goal was to optimize PUAE condition resulting in the highest yield and antioxidant activity as well as the highest contents of punicalagin and hydroxybenzoic acids. The operation at the intensity level of 105W/cm(2) and duty cycle of 50% for a short time (10min) had a high efficiency for extraction of phenolics from pomegranate peel. The application of such short extraction can save the energy and cost of the production. Punicalagin and ellagic acid were the most predominant phenolic compounds quantified in the pomegranate peel extract (PPE) from Malas variety. PPE contained a minor content of gallic acid.