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EN
Diagnostic ambiguity between chronic pulmonary diseases like asthma and Chronic Obstructive Pulmonary Disease (COPD) is very high, as they exhibit similar symptoms, which is the factor responsible for misdiagnosis, leading to heavy deaths every year. To prevent misdiagnosis, some useful work is highly required. This article presents the implementation of a computerized lung sound (LS) based method to classify asthma and COPD cases. The study is conducted on 80 asthma, 80 COPD and 80 healthy LSs. The LS denoising is carried out using empirical mode decomposition (EMD), Hurst analysis and spectral subtraction method. Wavelet entropy (WE) and wavelet packet energy (WPE) features of LS’s are extracted. Various classifiers like support vector machine (SVM), decision tree (DT), k-nearest neighbor (KNN) and discriminant analysis (DA) are accessed to classify healthy, COPD and asthma using WE and WPE features of LS to produce better outcomes. Using the proposed algorithm, the study discriminates between healthy, asthma and COPD cases based on LS with a considerable classification accuracy of 99.3% using the decision tree (DT) classifier. Thus, the study confirms the successful differentiation of asthma and COPD based on LS. Future endeavours will be based on the validation of this algorithm to distinguish the real-time LS data acquired from asthmatic and COPD patients.
2
EN
The 0.5(BiGd0.05Fe0.95O3)-0.5(PbZrO3) composite was synthesized by means of a high temperature solid-state reaction technique using high purity ingredients. Preliminary X-ray structural analysis confirms the formation of the composite. The dielectric constant and loss tangent have been studied. The impedance parameters have been measured using an impedance analyzer in a wide range of frequency (102–106 Hz) at different temperatures. The Nyquist plot suggests the contribution of bulk effect only and the bulk resistance decreases with a rise in temperature. Electrical impedance confirms the presence of grain effect and hopping mechanism in the electrical transport of the material. The dc conductivity increases with a rise of temperature. The frequency variation of ac conductivity shows that the compound obeys Jonscher’s universal power law and from Jonscher’s power law fit confirms the Small Polaron (SP) tunneling effect. Temperature dependence of dc and ac conductivity indicates that electrical conduction in the material is a thermally activated process.
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