scholarly journals Analysis of Rattleback Chaotic Oscillations

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Michael Hanias ◽  
Stavros G. Stavrinides ◽  
Santo Banerjee
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Chaotic Dynamics ◽  
The Other ◽  
Strange Attractors ◽  
Rotational Behaviour ◽  
Chaotic Oscillations ◽  
Kinematic Behaviour ◽  
Ancient Times ◽  
Related Time Series

Rattleback is a canoe-shaped object, already known from ancient times, exhibiting a nontrivial rotational behaviour. Although its shape looks symmetric, its kinematic behaviour seems to be asymmetric. When spun in one direction it normally rotates, but when it is spun in the other direction it stops rotating and oscillates until it finally starts rotating in the other direction. It has already been reported that those oscillations demonstrate chaotic characteristics. In this paper, rattleback’s chaotic dynamics are studied by applying Kane’s model for different sets of (experimentally decided) parameters, which correspond to three different experimental prototypes made of wax, gypsum, and lead-solder. The emerging chaotic behaviour in all three cases has been studied and evaluated by the related time-series analysis and the calculation of the strange attractors’ invariant parameters.

Gear Damage Detection Using Chaotic Dynamics Techniques: A Preliminary Study

1995 ◽  
Author(s):  
M. Farid Golnaraghi ◽  
DerChyan Lin ◽  
Paul Fromme
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Damage Detection ◽  
Correlation Dimension ◽  
Chaotic Dynamics ◽  
Crack Detection ◽  
Gear Tooth ◽  
Vibration Signal ◽  
Nonlinear Time Series Analysis ◽  
Preliminary Study

Abstract This paper is a preliminary study applying nonlinear time series analysis to crack detection in gearboxes. Our investigations show that the vibration signal emerging from a gearbox is chaotic. Appearance of a crack in a gear tooth alters this response and hence the chaotic signature. We used correlation dimension and Lyapunov exponents to quantify this change. The main goal of this study is to point out the great potential of these methods in detection of cracks and faults in machinery.

Paradoxes of Pluralism, Privilege, and Persecution: Explaining Christian Growth and Decline Worldwide

2021 ◽  
Author(s):  
Nilay Saiya ◽  
Stuti Manchanda
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Population Growth ◽  
Growth Rates ◽  
The Other ◽  
Faith Traditions ◽  
Statistical Approaches ◽  
State Relations ◽  
Christian Population ◽  
Cross National

Abstract This article examines the effect of church–state relations on rates of Christian population growth or decline worldwide. It makes the paradoxical argument that contexts of both pluralism and persecution do not impede Christian growth rates. In these environments, Christians do not have the luxury of becoming complacent. On one hand, pluralism means that Christianity must actively compete with other faith traditions in order to gain and maintain adherents. On the other hand, persecution can, paradoxically, sometimes strengthen Christianity by deepening attachments to faith and reinforcing solidarity among Christians. Rather, it is a third type of relationship—privilege, or state support for Christianity—that corresponds to the greatest threat to growth in Christianity. Countries where Christianity is privileged by the state encourage apathy and the politicization of religion, resulting in a less dynamic faith and the overall decline of Christian populations. We test these propositions using a cross-national, time-series analysis of a global sample of countries from 2010 to 2020. Our findings provide support for our theory that Christianity suffers in contexts of privilege but not in environments of pluralism or persecution. The finding is robust to a number of model specifications and statistical approaches.

Simple Chaotic Electronic Circuits

2011 ◽  
pp. 68-90
Author(s):  
M.P. Hanias ◽  
G. S. Tombras
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Critical State ◽  
Strange Attractors ◽  
Embedding Dimension ◽  
Kolmogorov Entropy ◽  
Electronic Circuits ◽  
Series Analysis ◽  
Chaotic Circuits

Simple chaotic electronics circuits as diode resonator circuits, Resistor-Inductor-LED optoelectronic chaotic circuits, and Single Transistor chaotic circuits can be used as transmitters and receivers for chaotic cryptosystems. In these circuits we can change and investigate the influence of various circuit parameters to the complexity of the so generated strange attractors. Time series analysis is performed following Grassberger and Procaccia’s method while invariant parameters as correlation, and minimum embedding dimension are respectively calculated. The Kolmogorov entropy is also calculated and the RLT circuits in a critical state are examined.

TOPOLOGICAL ANALYSIS OF CHAOS IN EQUIVARIANT ELECTRONIC CIRCUITS

1996 ◽  
Vol 06 (12b) ◽  
pp. 2531-2555 ◽  
Author(s):  
C. LETELLIER ◽  
G. GOUESBET ◽  
N.F. RULKOV
Keyword(s):  
Time Series ◽  
Chaotic Dynamics ◽  
Electronic Circuit ◽  
Topological Analysis ◽  
Experimental System ◽  
Electronic Circuits ◽  
Chaotic Oscillations ◽  
Symmetry Properties

Chaotic oscillations in an electronic circuit are studied by recording two time series simultaneously. The chaotic dynamics is characterized by using topological analysis. A comparison with two models is also discussed. Some prescriptions are given in order to take into account the symmetry properties of the experimental system to perform the topological analysis.

scholarly journals INTERACTION BETWEEN THE ECONOMIC GROWTH AND THE CONSTRUCTION INDUSTRY: A TIME SERIES ANALYSIS ON TURKEY (2000-2012)

2013 ◽  
Vol 3 (1) ◽  
pp. 20-34 ◽  
Author(s):  
Bilal Kargı
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Analysis ◽  
Construction Industry ◽  
Developed Countries ◽  
The Other ◽  
Gdp Growth ◽  
Quarterly Data ◽  
Series Analysis ◽  
Gdp Growth Rate

In this study the relation between the economic growth and the construction industry has been tackled. While the growth the rate of the construction industry in the developing countries is more than the GDP growth rate, it is detected that the percent age it takes in the GDP of developed countries relatively diminishes. On the other hand the construction industry’s growth in the economic fluctuation periods, in the aftermath of a recession, is more than the GDP. These two proposals are tested by the quarterly data of 2000:01-2012:03 for Turkey. Additionally the relation between the economic growth and the construction industry is subjected to the Granger causality test.Keywords: Economic growth, construction industry, time series analysis.

Effects of Periodic and Stochastic Perturbations on Oscillations and Chaos in a Model of the Peroxidase-Oxidase Reaction

1985 ◽  
Vol 40 (12) ◽  
pp. 1283-1288 ◽  
Author(s):  
Lars F. Olsen
Keyword(s):  
Chaotic Dynamics ◽  
Experimental System ◽  
The Other ◽  
Random Perturbations ◽  
Chaotic Oscillations ◽  
Stochastic Perturbations ◽  
Small Random Perturbations ◽  
Periodic Dynamics ◽  
Oxidase Reaction ◽  
Small Periodic

The effects of periodic and random perturbations on the periodic and chaotic oscillations in a model of the peroxidase-oxidase reaction are investigated. The perturbations were chosen to be comparable in size and frequency to those measured in the experimental system. Small periodic perturbations did not affect the dynamics significantly. Small random perturbations, on the other hand, could totally obscure simple periodic dynamics whereas chaotic dynamics turned out to be relatively robust to such perturbations.

scholarly journals A Finite Mixture GARCH Approach with EM Algorithm for Energy Forecasting Applications

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2352
Author(s):  
Yang Zhang ◽  
Yidong Peng ◽  
Xiuli Qu ◽  
Jing Shi ◽  
Ergin Erdem
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Em Algorithm ◽  
Wind Power ◽  
Garch Model ◽  
Finite Mixture ◽  
Electricity Price ◽  
The Other ◽  
Volatility Modeling ◽  
Related Time Series

Enhancing forecasting performance in terms of both the expected mean value and variance has been a critical challenging issue for energy industry. In this paper, the novel methodology of finite mixture Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) approach with Expectation–Maximization (EM) algorithm is introduced. The applicability of this methodology is comprehensively evaluated for the forecasting of energy related time series including wind speed, wind power generation, and electricity price. Its forecasting performances are evaluated by various criteria, and also compared with those of the conventional AutoRegressive Moving-Average (ARMA) model and the less conventional ARMA-GARCH model. It is found that the proposed mixture GARCH model outperforms the other two models in terms of volatility modeling for all the energy related time series considered. This is proven to be statistically significant because the p-values of likelihood ratio test are less than 0.0001. On the other hand, in terms of estimations of mean wind speed, mean wind power output, and mean electricity price, no significant improvement from the proposed model is obtained. The results indicate that the proposed finite mixture GARCH model is a viable approach for mitigating the associated risk in energy related predictions thanks to the reduced errors on volatility modeling.

scholarly journals Analysis of changes in resources and outputs of companies and partnerships in Hungarian agriculture

2011 ◽  
pp. 65-68
Author(s):  
Mónika Harangi-Rákos
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Time Series Analysis ◽  
The Other ◽  
Eu Accession ◽  
Economic Weight ◽  
New Type ◽  
National Tax ◽  
Customs Administration ◽  
The Eu

The aim of the study was to examine the achievement of Hungarian agricultural companies and partnerships, particularly agricultural co-operatives based on the aggregated database of National Tax and Customs Administration (NAV)1. From the methodological aspect, descriptive statistical methods and time series analysis were used. One of the most important conclusions is that the socio-economic weight of the agricultural co-operatives was strongly decreased in the period after the EU accession. The other important statement is that apart from the general examination of economic actors on aggregated level the comparative analysis of the single organizations forms would be needed. In the case of co-operatives, separated examination of the former type producer co-operatives and the so-called new type ones (e.g. marketing co-operatives etc.) would be necessary.

scholarly journals Local linear conditional cumulative distribution function with mixing data

2019 ◽  
Vol 9 (2) ◽  
pp. 289-307 ◽  
Author(s):  
Oussama Bouanani ◽  
Saâdia Rahmani ◽  
Larbi Ait-Hennani
Keyword(s):  
Time Series ◽  
Distribution Function ◽  
Time Series Analysis ◽  
Cumulative Distribution Function ◽  
Random Variable ◽  
The Other ◽  
Cumulative Distribution ◽  
Mixing Conditions ◽  
Local Polynomial ◽  
Analysis Models

Abstract This paper investigates a conditional cumulative distribution of a scalar response given by a functional random variable with an $$\alpha $$ α -mixing stationary sample using a local polynomial technique. The main purpose of this study is to establish asymptotic normality results under selected mixing conditions satisfied by many time-series analysis models in addition to the other appropriate conditions to confirm the planned prospects.

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