scholarly journals Quantification of Boiling Flows in Single and Multiple Heater Rods Assembly by Recurrence Plots and Recurrence Quantification Analysis

2022 ◽  
pp. 100241
Author(s):  
Ashutosh Yadav ◽  
Shantanu Roy
Keyword(s):  
Recurrence Quantification Analysis ◽  
Recurrence Plots ◽  
Recurrence Quantification ◽  
Quantification Analysis

RECURRENCE QUANTIFICATION ANALYSIS OF ELECTROOCULOGRAPHY SIGNAL TO A CONTROL QUESTION TEST: A NEW APPROACH FOR THE DETECTION OF DECEPTION

2020 ◽  
Vol 32 (04) ◽  
pp. 2050029
Author(s):  
Mohamad Amin Younessi Heravi ◽  
Morteza Pishghadam ◽  
Hosnieh Raoufian ◽  
Akram Gazerani
Keyword(s):  
Detection System ◽  
Lie Detection ◽  
Recurrence Quantification Analysis ◽  
Recurrence Plots ◽  
New Approach ◽  
Control Question ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Detection Of Deception ◽  
One Way Anova

This study aimed to evaluate a lie-detection system by nonlinear analysis of electrooculography (EOG) signals in the polygraph test. The physiological signals such as photoplethysmography signal, electrodermal response, respiratory changes as well as EOG signal were recorded based on a Control Question Test (CQT). Three psychophysiological signals were evaluated based on the extracted features in the seven-position numerical scoring. The dynamics of EOG signals in subjects that had a total negative score were analyzed by recurrence quantification analysis (RQA). The six values of RQA were calculated to analyze the EOG signals in relevant questions compared to other questions. A one-way ANOVA with multiple comparisons was performed to evaluate the extracted variables in different questions. Eleven subjects had a total score of [Formula: see text]2 and less, so the EOG signals of these subjects were evaluated. Recurrence plots (RPs) of EOG signals showed clear differences in the two types of questions. The recurrence quantification analysis of vertical EOG signal indicated that [Formula: see text] and determinism (DET) values decreased significantly for relevant questions compared to other questions. Moreover, a significant decrease was observed in all RQA parameters except RR for the horizontal EOG signal. The differences of EOG signals in relevant questions observed using RPs and RQA were possibly related to the underlying changes in rapid eye movement due to the stress. The results of this study illustrate that the RQA technique is well suited to analyze the EOG signals in the detection of deception.

Recurrence Plots for Diesel Engine Variability Tests

2009 ◽  
Vol 64 (1-2) ◽  
pp. 96-102 ◽  
Author(s):  
Rafał Longwic ◽  
Grzegorz Litak ◽  
Asok K. Sen
Keyword(s):  
Diesel Engine ◽  
Wavelet Analysis ◽  
Low Frequency ◽  
Recurrence Quantification Analysis ◽  
Maximum Pressure ◽  
Recurrence Plots ◽  
Frequency Bands ◽  
Recurrence Quantification ◽  
Quantification Analysis

Cycle-to-cycle variations of maximum pressure in a diesel engine are studied by using the methods of recurrence plots and recurrence quantification analysis. The pressure variations are found to exhibit strong periodicities in low frequency bands and intermittent oscillations at higher frequencies. The results are confirmed by wavelet analysis.

Recurrence Plot and Recurrence Quantification of the Dynamic Properties of Cross-Shaped Laminated Energy Harvester

2016 ◽  
Vol 849 ◽  
pp. 95-105 ◽  
Author(s):  
Peter Harris ◽  
Grzegorz Litak ◽  
Joanna Iwaniec ◽  
Chris R. Bowen
Keyword(s):  
Power Output ◽  
Dynamic Properties ◽  
Electrical Power ◽  
Mechanical Vibration ◽  
Recurrence Plot ◽  
Recurrence Quantification Analysis ◽  
Recurrence Plots ◽  
Recurrence Quantification ◽  
Time Histories ◽  
Quantification Analysis

The paper examines the dynamic properties of bistable cross-shaped laminate plates for broadband energy harvesting applications by converting mechanical vibration energy into the electrical power output. Bistable laminates plates coupled to piezoelectric transducers were excited by application of harmonic excitations and exhibited a range of vibration patterns. The vibration patterns included single-well oscillations and snap-through vibrations of both periodic and chaotic character; such vibration patterns led to a different power output. Classical spectral analysis of measured voltage, displacement and velocity time histories indicated the presence of a variety of nonlinear and chaotic phenomena. As a result, an analysis of the measured displacement and voltage time histories was carried out with the use of the Recurrence Plots and the Recurrence Quantification Analysis methods. The Recurrence Plots method was used for detection of qualitative changes in the dynamic behaviour of the non-linear harvesting system. In order to facilitate interpretation of piezoelectric voltage and laminate displacement, a detailed analysis using Recurrence Plots, Recurrence Quantification Analysis was employed.

UNSTABLE CARDIAC SINGULARITIES MAY LEAD TO ATRIAL FIBRILLATION

2011 ◽  
Vol 21 (04) ◽  
pp. 1141-1151 ◽  
Author(s):  
C. L. WEBBER ◽  
Z. HU ◽  
J. G. AKAR
Keyword(s):  
Atrial Fibrillation ◽  
Full Range ◽  
Central Line ◽  
Recurrence Quantification Analysis ◽  
Spiral Waves ◽  
Atrial Arrhythmias ◽  
Recurrence Plots ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Derivatives Of

A total of 53 atrial electrograms were recorded from 12 human patients diagnosed with different degrees of atrial arrhythmias and fibrillation, but not atrial flutter. The atrial waves were highly complex, noisy, nonuniform, nonlinear, and nonstationary in time and well suited for recurrence quantification analysis (RQA), spectral analysis (FFT) and atrial rate (AR) measurements. Differing degrees of atrial arrhythmias were quantified by measuring singularities in the electrograms. Singularities were defined as the maximum periods of relative isopotential squared (msec2) and presented as unfilled squares along the central line of identity (LOI) on recurrence plots. These nonsolid (unfilled) squares indicate that most singularities were unstable with noisy baselines. All measured variables were plotted against their corresponding unstable singularities. The best correlations were found for variables Vmaxand Laminar over the full range of log10(singularity). That is, the higher the degree of fibrillation the smaller the size of the singularity and the shorter Vmaxand Laminar. The shorter singularities are associated with faster spiral waves. However, since Vmaxand Laminar are direct derivatives of Singularity, this variable remains the sole best quantifier of choice to identify aberrant pacemaker regions.

scholarly journals HOW TO AVOID POTENTIAL PITFALLS IN RECURRENCE PLOT BASED DATA ANALYSIS

2011 ◽  
Vol 21 (04) ◽  
pp. 1003-1017 ◽  
Author(s):  
NORBERT MARWAN
Keyword(s):  
Data Analysis ◽  
Recurrence Plot ◽  
Recurrence Quantification Analysis ◽  
The Other ◽  
Recurrence Plots ◽  
Deep Foundation ◽  
Recurrence Quantification ◽  
Potential Problems ◽  
Quantification Analysis ◽  
The One

Recurrence plots and recurrence quantification analysis have become popular in the last two decades. Recurrence based methods have on the one hand a deep foundation in the theory of dynamical systems and are on the other hand powerful tools for the investigation of a variety of problems. The increasing interest encompasses the growing risk of misuse and uncritical application of these methods. Therefore, we point out potential problems and pitfalls related to different aspects of the application of recurrence plots and recurrence quantification analysis.

scholarly journals Application of Recurrence Quantification Analysis for Non-Linear Dynamical Systems

2019 ◽  
Vol 9 (1S5) ◽  
pp. 92-94
Keyword(s):  
Time Series ◽  
Phase Space ◽  
Dynamical Systems ◽  
Recurrence Plot ◽  
Recurrence Quantification Analysis ◽  
Recurrence Plots ◽  
Space Trajectories ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Phase Space Trajectories

The Recurrence plots (RPs) have been introduced in several different scientific and medical disciplines. The main purpose of recurrence plot is used to of identify the higher dimensional phase space trajectories. RPs are purely graphically representation which have been designed for the detection of hidden dynamical patterns and non-linearity present in the data, the evaluation of error which is caused by observational noise can be done by Recurrence Quantification Analysis (RQA). RQA method is initially used to minimize the error present in the given signals. RQA method is a basically a technique for the analysis of nonlinear data to quantify the number and duration of a dynamical systems. The recurrence plot is used for time series domain for multidimensional signal also. Recurrence is the property of non-stationary and dynamical system to characteristics the time series analysis in phase space trajectories. Recurrence Quantification Analysis is used to derive from recurrence plots, which are based upon distances matrices of time series.

STATISTICAL TESTS FOR SERIAL DEPENDENCE AND LAMINARITY ON RECURRENCE PLOTS

2011 ◽  
Vol 21 (04) ◽  
pp. 1077-1084 ◽  
Author(s):  
YOSHITO HIRATA ◽  
KAZUYUKI AIHARA
Keyword(s):  
Binomial Distribution ◽  
Statistical Tests ◽  
Surrogate Data ◽  
Recurrence Quantification Analysis ◽  
Serial Dependence ◽  
Recurrence Plots ◽  
Recurrence Quantification ◽  
Significance Levels ◽  
Quantification Analysis ◽  
Patterns Of Recurrence

Although recurrence quantification analysis provides useful information about underlying dynamics, it cannot be used to obtain significance levels on its own. Therefore, we propose methods to determine significance levels of serial dependence and laminarity from plotted patterns of recurrence plots. We evaluate the probability of two recurrences with an assumption that these recurrences are statistically independent. By modeling the number of simultaneous recurrences with a binomial distribution, we obtain the significance levels of serial dependence and laminarity without generating surrogate data. Further, we apply the proposed methods to a real wind dataset and find that it has serial dependence and laminarity.

Recurrence plots and recurrence quantification analysis of human motion data

2016 ◽  
Author(s):  
Henryk Josiński ◽  
Agnieszka Michalczuk ◽  
Adam Świtoński ◽  
Agnieszka Szczęsna ◽  
Konrad Wojciechowski
Keyword(s):  
Human Motion ◽  
Recurrence Quantification Analysis ◽  
Recurrence Plots ◽  
Motion Data ◽  
Recurrence Quantification ◽  
Quantification Analysis
Sign in / Sign up

Export Citation Format

Share Document