PurposeSustainable development of entrepreneurship could be comprehensively analyzed using a simulation model for entrepreneurship ecosystem based on the system dynamics approach. Thus, a complete ...analysis of the entrepreneurship ecosystem is of high importance. However, an effective analysis of entrepreneurship ecosystem involves many challenges, such as the presence of several factors which interact with each other in various ways with different complex effects in time. Therefore, the approach used in this study is employing analysis of entrepreneurship ecosystems in sports industry using analysis of dynamic systems.Design/methodology/approachSeveral applied issues such as entrepreneurship opportunities, infrastructures, market opportunities and entrepreneurship space in the borders of the dynamic model developed based on the literature and experts' opinion. Finally, a set of strategies based on experts' opinion are ranked with the objective of improvement of evaluation measures using network analysis decision-making approach and fuzzy TOPSIS.FindingsThe results obtained indicate the important role of sports entrepreneurship opportunities, sports tourism, market opportunities, entrepreneurship infrastructures and entrepreneurship-oriented environment in the development of sports entrepreneurship infrastructure in Iran. The credibility and efficiency of the proposed model for analysis of sports entrepreneurship have been ultimately shown.Originality/valueA holistic approach is proposed based on the hybrid system dynamics approach and fuzzy decision-making method to analyses sports entrepreneurship ecosystem.
In this paper we use global analysis techniques to investigate an economic growth model with environmental negative externalities, giving rise to a three-dimensional dynamic system (the framework is ...the one introduced by Wirl (1997)). The dynamics of our model admits a locally attracting steady state which is, in fact, a poverty trap, coexisting with another steady state possessing saddle-point stability. Global dynamical analysis shows that, under some conditions on the parameters, if the economy state variables are close enough to those of the attractive point, then there exists a continuum of equilibrium orbits approaching the poverty trap and one orbit approaching the saddle-point.
Z. 120 = nr 1253
Opening date of the postdoctoral thesis 1.XII.1994
Habilitation 27.XI.1995
Z. 120 = Nr 1253
Data otwarcia przewodu habilitacyjnego 1.XII.1994 r.
Habilitacja 27.XI.1995 r.
The objective of this manuscript is to examine the non-linear characteristics of the modified equal width-Burgers equation, known as the generalized Kadomtsive–Petviashvili equation, and its ability ...to generate a long-wave with dispersion and dissipation in a nonlinear medium. We employ the Lie symmetry approach to reduce the dimension of the equation, resulting in an ordinary differential equation. Utilizing the newly developed generalized logistic equation method, we are able to derive solitary wave solutions for the aforementioned ordinary differential equation. In order to gain a deeper understanding of the physical implications of these solutions, we present them using various visual representations, such as 3D, 2D, density, and polar plots. Following this, we conduct a qualitative analysis of the dynamical systems and explore their chaotic behavior using bifurcation and chaos theory. To identify chaos within the systems, we utilize various chaos detection tools available in the existing literature. The results obtained from this study are novel and valuable for further investigation of the equation, providing guidance for future researchers.
•Application of the generalized logistic equation method to address the dynamics of solitary wave solutions for the generalized KP–MEW-Burgers equation.•Computation of the invariant transformations and symmetry reductions using Lie symmetry analysis.•Bifurcation and phase portraits of the unperturbed dynamical system using the idea of bifurcation theory of dynamical systems.•Chaos behavior of the perturbed dynamical system is identified through different chaos detecting tools using chaos theory of dynamical systems.
Averaged recurrence quantification analysis Pánis, Radim; Adámek, Karel; Marwan, Norbert
The European physical journal. ST, Special topics,
02/2023, Letnik:
232, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Recurrence quantification analysis (RQA) is a well established method of nonlinear data analysis. In this work, we present a new strategy for an almost parameter-free RQA. The approach finally omits ...the choice of the threshold parameter by calculating the RQA measures for a range of thresholds (in fact recurrence rates). Specifically, we test the ability of the RQA measure determinism, to sort data with respect to their signal to noise ratios. We consider a periodic signal, simple chaotic logistic equation, and Lorenz system in the tested data set with different and even very small signal-to-noise ratios of lengths
10
2
,
10
3
,
10
4
,
and
10
5
. To make the calculations possible, a new effective algorithm was developed for streamlining of the numerical operations on graphics processing unit (GPU).
We propose a novel recurrence plot-based approach, the difference recurrence plot (DRP), to detect small deviations between measurements. By using a prototypical model system, we demonstrate the ...potential of DRPs and the difference to alternative measures, such as Pearson correlation, spectral analysis, or cross and joint recurrence analysis. Real-world data comes from an application of guided ultrasonic waves for structural health monitoring to detect damages in a composite plate. The specific challenge for this damage detection is to differentiate between defects and the influence of temperature. We show that DRPs are suited in the following sense: DRPs of two time series that derive from measurements at different temperatures hold practically full recurrence, whereas DRPs of one time series from a measurement without and one time series with defect show a hugely reduced recurrence rate.
The last decade has witnessed a number of important and exciting developments that had been achieved for improving recurrence plot-based data analysis and to widen its application potential. We will ...give a brief overview about important and innovative developments, such as computational improvements, alternative recurrence definitions (event-like, multiscale, heterogeneous, and spatio-temporal recurrences) and ideas for parameter selection, theoretical considerations of recurrence quantification measures, new recurrence quantifiers (e.g. for transition detection and causality detection), and correction schemes. New perspectives have recently been opened by combining recurrence plots with machine learning. We finally show open questions and perspectives for futures directions of methodical research.
Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. Creating features useful for the analysis of the EEG recording can be challenging. Here we introduce a ...new method of pre-processing the time-series for the analysis of the resting state and binary task classification using recurrence quantification analysis (RQA) and compare it with the existing state-of-the-art approach based on signal embedding. To reveal patterns that unfold brain dynamics, we present a new pipeline that does not rely on selection of embedding parameters for RQA. Instead of using EEG time-series signals directly, Short-term Fourier transform (STFT) is used to generate new time-series, based on the power spectra from sliding, overlapping windows. Recurrence plots are created in a standard way from embedded EEG signals, and the STFT vectors. The efficiency of RQA features extracted from such plots is compared in classification of EEG segments that correspond to open and closed eye conditions. In contrast to the common approaches to such analysis, no filtering into separate frequency bands was needed. Differences between the two representations of EEG signals are illustrated using histograms of RQA features and UMAP plots. Classification results at the 95.9% level were obtained using selected features for less than 10 electrodes.
Irregularly sampled time series analysis is a common problem in various disciplines. Since conventional methods are not directly applicable to irregularly sampled time series, a common interpolation ...approach is used; however, this causes data distortion and consequently biases further analyses. We propose a method that yields a regularly sampled time series spectrum of costs with minimum information loss. Each time series in this spectrum is a stationary series and acts as a difference filter. The transformation costs approach derives the differences between consecutive and arbitrarily sized segments. After obtaining regular sampling, recurrence plot analysis is performed to distinguish regime transitions. The approach is applied to a prototypical model to validate its performance and to different palaeoclimate proxy data sets located around Africa to identify critical climate transition periods during the last 5 million years and their characteristic properties.
