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Reconstruction of the dynamics of a complex system by the time sequence of the release of elastic energy during deformation and destruction of wood and wood-based materials

Kulman S.

Annals of Warsaw University of Life Sciences - SGGW. Forestry and Wood Technology

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2018

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No. 104

147--153

EN

The non-linear nature of the deformation of wood and wood composites under the influence of an external thermal-moisture-strength load on it requires, in its study, to consider this system as complexity. The analysis shows a certain determinism in the process of deformation-destruction: the system that generates such a release of elastic energy is not random and is controlled by a small number of determining variables. To describe a dynamic system in our case, it is sufficient to identify three variables whose variation in time will adequately describe the process of deformationdestruction. The time sequence analysis technique developed in the theory of dynamical systems makes it possible to distinguish between random and deterministic chaotic systems and to assess the complexity of these systems.

2

Testing fractal coefficients sensitivity on real and simulated earthquake data

Gospodinov D., Marinov A., Marekova E.

Acta Geophysica

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2012

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Vol. 60, no. 3

794-808

EN

We examined the behavior of different fractal dimensions when applied to study features of earthquake spatial distribution on different types of data. We first examined simulated spatial fields of points of different clustering level, following the so called Soneira-Peebles model. The model was chosen because it displays some similarity to the real clustering structure of earthquakes occurring on hierarchically ordered faults. The analysis of the capacity, clustering and correlation dimensions revealed that their behavior did not completely correlate with the clustering level of the simulated data sets. We also studied temporal variations of the fractal coefficients, characterizing the spatial distribution of the 1999 Izmit-Düzce aftershock sequence. The calculated coefficient values demonstrated analogous behavior like for the simulated data. They exposed different variability in time, but for all of them a systematic fluctuation was observed before the occurrence of the Düzce earthquake. Our analysis revealed that although fractal coefficients could be applied to measure earthquake clustering, they should be used with caution, trying to figure out the best coefficient for a certain data set.

3

Zastosowanie układu FPGA do akceleracji obliczeń całki korelacji interwałów RR

Pawlak S.

Pomiary Automatyka Kontrola

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2007

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R. 53, nr 5

102-104

PL

Analiza sygnałów biomedycznych jest jednym z ważniejszych obszarów badań naukowych. Istnieje duże zapotrzebowanie na wydajne systemy obliczeniowe, które pozwalały by na analizę sygnałów biomedycznych wielu pacjentów. W artykule przedstawiono propozycję architektury systemu obliczającego całkę korelacji interwałów międzyuderzeniowych RR, wykorzystującego układ FPGA do akceleracji obliczeń.

EN

Biomedical signal analysis is a very important field of research. This paper describes architecture of FPGA-accelerated computational system proposed by Author. The main purpose of this system is calculation of the correlation integral of RR intervals in cardiological patients.

4

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

Mitchell R.H.

Biocybernetics and Biomedical Engineering

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1999

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Vol. 19, no. 2

109-117

EN

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.

PL

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.