We propose a method for the reconstruction of time-delayed feedback systems having unobserved variables from scalar time series. The method is based on the modified initial condition approach, which allows one to significantly reduce the number of starting guesses for an unobserved variable with a time delay. The proposed method is applied to the reconstruction of the Lang-Kobayashi equations, which describe the dynamics of a single-mode semiconductor laser with external optical feedback. We consider the case where only the time series of laser intensity is observable and the other two variables of the model are hidden. The dependence of the quality of the system reconstruction on the accuracy of assignment of starting guesses for unobserved variables and unknown laser parameters is studied. The method could be used for testing the security of information transmission in laser-based chaotic communication systems.
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http://dx.doi.org/10.1103/PhysRevE.101.042218 | DOI Listing |
Accid Anal Prev
December 2024
School of Transportation, Southeast University, Nanjing 211189, China; Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing 211189, China.
There has been an increase in the use of the extreme value theory (EVT) approach for conflict-based crash risk estimation and its application such as conducting the evaluation of safety countermeasures. This study proposes a cross-sectional approach for evaluating the effectiveness of a right-turn safety treatment using a conflict-based EVT approach. This approach combines traffic conflicts of different sites at the same period and develops the generalized extreme value (GEV) models.
View Article and Find Full Text PDFEcon Hum Biol
December 2024
Department of Economics, McMaster University, Hamilton, Ontario, Canada. Electronic address:
Objective: The objective is to estimate the effect of provincial minimum wage increases in Canada on heavy drinking, binge drinking and average daily alcohol consumption.
Method: We estimate standard regression models by gender-age group with drinking behaviours as the dependent variables and the minimum wage among the independent variables. We employ the Canadian National Population Health Survey which began in 1994 and ended in 2011, a period comparable to that used by many U.
Inquiry
December 2024
Department of Economics, University of Kashmir, Srinagar, India.
This study investigates the relationship between out-of-pocket (OOP) healthcare spending, economic growth, population growth, and government health expenditure as a proportion of general government expenditure using National Health Accounts (NHA) estimates. Out-of-Pocket (OOP) healthcare spending imposes a substantial financial burden on households, especially in developing economies such as India. Understanding the factors that influence OOP payments is crucial for policymakers seeking to enhance healthcare systems and achieve Universal Health Coverage (UHC).
View Article and Find Full Text PDFMath Biosci Eng
October 2024
School of Public Health, Georgia State University, Atlanta, Georgia, USA.
Traditional compartmental models of epidemic transmission often predict an initial phase of exponential growth, assuming uniform susceptibility and interaction within the population. However, empirical outbreak data frequently show early stages of sub-exponential growth in case incidences, challenging these assumptions and indicating that traditional models may not fully encompass the complexity of epidemic dynamics. This discrepancy has been addressed through models that incorporate early behavioral changes or spatial constraints within contact networks.
View Article and Find Full Text PDFBMC Psychol
December 2024
Department of Nursing, Ataturk University, Erzurum, Turkey.
Background: In this study, the effects of individuals' digital obesity and phubbing behaviors on their life satisfaction were investigated by latent profile analysis (LPA) method. LPA is a statistical technique used to identify unobserved subgroups within a population based on individuals' responses to various observed variables.
Methods: The present study was conducted in a correlational cross-sectional descriptive design between November 2023- January 2024.
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