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Chaotic behaviour of acoustic emission induced in hard coal by gas sorption-desorption

100%

Majewska Z. , Mortimer Z.

2006

tom Vol. 54, no. 1

50-59

This paper presents study of non-linear dynamics of acoustic emission (AE) generated in coal samples subjected to gas sorption-desorption. Carbondioxide and methane were used as sorbats. Experimental facilities used in high pressure sorption of CO2 and/or CH4 on coal comprised a pressure vessel and associated pressurisa-tion and monitoring systems. Tests were conducted on mediumrank coal obtained from the Upper Silesia Basin. Several approaches to the treatment of experimental results are proposed in order to detect and characterize deterministic chaos: (1) analysis of fractal/multi- fractal character of AE energy rate, using fractal generalised dimensions Dq(q); (2) analysis of temporal changes of AE energy rate and its fractal correlation di-mension D2; and (3) evaluation of attractor dimension within the reconstructed phase space from experimental time series. It was shown that AE generated during CO2 sorption on mediumrank coal is a more heterogeneous and lower dimensional process in comparison with AE induced by CO2 desorption. Yet, the AE associated with desorption of CO2 exhibits higher heterogeneity than the AE generated during desorption of CH4. There are certain similarities between changes of D2 during desorption of CO2 as well desorption of CH4. However, dynamics of these changes and character of time distributions of D2 differ, depending on a sorbate. We do not know the precise reason for observed differences, but we presume that the carbon-dioxide molecules dissimilarity to methane molecules can account for them.

Non-linear dynamical analysis of heart rate variability data in premature infants

72%

Mitchell R. H.

1999

tom Vol. 19, no. 2

109-117

Anovel method is presented in this paper that distinguished between normal premature infants and premature infants with Respiratory Distress Syndrome (RDS). The method uses Heart-Rate Variability (HRV) data that is derived from the time-series of consecutive R-R intervals from ECG recordings, and is unique in three aspects: (1) the data does not require pre-filtering to remove artefacts; (2) the method essentially exploits Chaos Theory as applied to time-series data without requiring large data records; (3) the computational time is minimal.

Artykuł opisuje nową metodę pozwalającą na rozpoznanie Zespołu Błon Szklistych (RDS) u wcześniaków. Omawiana metoda opiera się na danych dotyczących zmienności rytmu serca (HRV), uzyskanych na podstawie analizy przebiegów czasowych następujących po sobie odcinków R-R w zapisie EKG i jest unikatowa z trzech powodów: (1) dane nie wymagają przekształcania danych wejściowych w celu wyeliminowania artefaktów; (2) metoda wykorzystuje Teorię Chaosu do analizy przebiegów czasowych nie wymagając jednak dużych zbiorów danych; (3) wymagany czas obliczeń jest minimalny.