Continuous Wavelet Research Articles

Accuracy improvement in plastics classification by laser-induced breakdown spectroscopy based on a residual network

The whole ecosystem is suffering from serious plastic pollution. Automatic and accurate classification is an essential process in plastic effective recycle. In this work, we proposed an accurate approach for plastics classification using a residual network based on laser-induced breakdown spectroscopy (LIBS). To increasing efficiency, the LIBS spectral data were compressed by peak searching algorithm based on continuous wavelet, then were transformed to characteristic images for training and validation of the residual network. Acrylonitrile butadiene styrene (ABS), polyamide (PA), polymethyl methacrylate (PMMA), and polyvinyl chloride (PVC) from 13 manufacturers were used. The accuracy of the proposed method in few-shot learning was evaluated. The results show that when the number of training image data was 1, the verification accuracy of classification by plastic type under residual network still kept 100%, which was much higher than conventional classification algorithms (BP, kNN and SVM). Furthermore, the training and testing data were separated from different manufacturers to evaluate the anti-interference properties of the proposed method from various additives in plastics, where 73.34% accuracy was obtained. To demonstrate the superiority of classification accuracy in the proposed method, all the evaluations were also implemented by using conventional classification algorithm (kNN, BP, SVM algorithm). The results confirmed that the residual network has a significantly higher accuracy in plastics classification and shows great potential in plastic recycle industries for pollution mitigation.

Causality between tourism and housing prices: a wavelet-based approach

ABSTRACT This paper aims to examine the relationship between tourism activities and housing prices (HP) in China’s eight central provinces using wavelet transform context structures. This innovative technique allows the decomposition of a time series at different time frequencies. In this work, the researchers used continuous wavelets, wavelet coherence and wavelet phase-difference based on Granger causality analysis to investigate the relationship between tourism activities and HP. The study results indicate that the relationship is generally positive but changes over time exhibiting low to high-frequency cycles. The government needs to increase tourism demand and further provide and nurture the expansion of tourism supply.

System for an acoustic detection, localisation and classification

<p class="Abstract">Currently, acoustic detection techniques of gunshots (gunshot detection and its classification) are increasingly being used not only for military applications but also for civilian purposes. Detection, localisation, and classification of a dangerous event such as gunshots employing acoustic detection is a perspective alternative to visual detection, which is commonly used. In some situations, to detect and localise the source of a gunshot, an automatic acoustic detection system, which can classify the caliber, may be preferable. This paper presents a system for acoustic detection, which can detect, localise and classify acoustic events such as gunshots. The system has been tested in open and closed shooting ranges and tested firearms are 9 mm short gun, 6.35 mm short gun, .22 short gun, and .22 rifle gun with various subsonic and supersonic ammunition. As ‘false alarms’, sets of different impulse acoustic events like door slams, breaking glass, etc. have been used. Localisation and classification algorithms are also introduced. To successfully classify the tested acoustic signals, Continuous Wavelet and Mel Frequency Transformation methods have been used for the signal processing, and the fully two-layer connected neural network has been implemented. The results show that the acoustic detector can be used for reliable gunshot detection, localisation, and classification.</p>

Experimental investigation on axial compressor stall phenomena using aeroacoustics measurements via empirical mode and proper orthogonal decomposition methods

In this work, we conduct experimental investigations on a single-stage axial compressor to shed lights on the dynamic stall phenomena via aeroacoustic measurements. For this, 8 acoustic pressure sensors are installed equally around the circumference of the compressor intake. The acoustic pressure data are simultaneously logged in real-time. Classical and conventional Fourier-transform based methods reveal that the compressor stall will occur beyond a critical pressure ratio or a flow coefficient as illustrated on a compressor map. However, there is no warning precursor obtained from the conventional signal analysis methods. Further investigations are conducted using a number of advanced signal processing techniques, such as empirical mode decomposition (EMD) and proper orthogonal decomposition (POD) and continuous wavelet (CW) methods. EMD analysis reveals that the compressor stall is corresponding to a low-frequency intrinsic mode function (IMF). It is growing rapidly from negligible amplitude random disturbances to limit cycle oscillations. POD shows that the number of the dominant acoustic modes contributing to more than 98.5% of the total fluctuation energy is changed from 3 to 7, when the stall occurs. This is insightful for low-order modeling of the compressor stall phenomena. Finally, applying CW transform could provide a warning of 0.05 s precursor on the tested axial compressor. In general, the present work opens up an alternative approach to study the dynamic physics of a compressor stall by applying an array of acoustic sensors with proper advanced data-processing methods implemented.

An improved algorithm for pile damage localization based on complex continuous wavelet transform

Since the complex continuous wavelet transform (CCWT) based pile damage detection method is empirical and subjective, an improved algorithm for pile damage localization based on CCWT is proposed by introducing K-means clustering and fast Fourier transform (FFT). In this method, the K-means clustering algorithm is used to accurately calculate the time coordinates of two energy concentrating points caused by the incident and reflected waves, respectively. Meanwhile, FFT is employed to estimate the concerned frequency band of the response signal. Therefore, a specific region in the time frequency plane is defined objectively and it can be used to search the phase angle turning points and localize pile damage. The proposed method is verified by numerical examples of piles with single and multiple damage positions. A parameter analysis is also conducted to investigate how damage depth and damage degree in piles affect the accuracy and effectiveness of the proposed method. The results demonstrate that the proposed method is able to localize a pile with a damage at least 2.5 m away from the pile head when the damage degree is as less as 5%. After that, dynamic tests of an actual square reinforced concrete pile and an actual circular reinforced concrete pile are investigated to verify the application of the proposed method on practical engineering. Although the proposed method is capable of localizing actual piles more accurately than the CCWT method, the problem of interference points needs to be addressed by mutual verification with other pile damage localization methods.

Análise da variabilidade da frequência cardíaca em crianças submetidas a jogos eletrônicos

Objetivo: avaliar a função autonômica do coração de crianças sadias em situações de jogos eletrônicos, mediante a análise de Variabilidade da Frequência cardíaca.Métodos: participaram deste estudo 60 crianças sadias, que foram monitoradas por um monitor de frequência cardíaca digital e submetidas ao experimento com o jogo eletrônico. A análise da Variabilidade da Frequência cardíaca foi calculadacom emprego da transformada Wavelet Contínua.Resultados: pode-se observar um aumento na intensidade dos valores de baixa frequência/alta frequência, sugerindo influência das fases do protocolo, de modo que houve uma elevação nos valores da fase de Repouso para a fase de Jogo, mas não foi encontrado um valor significativo. Entre as fases de Repouso (1,52±0,97 ms²) e Recuperação (1,89±1,04 ms²) houve um aumento significativo obtendo um valor de p=0,003. Comparando os valores de baixa frequência/alta frequência entre as fases Jogo 2,37±1,20 ms² e Recuperação 1,89±1,04 ms², verificou-se uma redução significativa da relação (p = 0,016).Conclusão: conclui-se que Jogos eletrônicos podem provocar um aumento da atividade simpática, diminuindo a Variabilidade da Frequência cardíaca das crianças estudadas, sugerindo uma situação estressante.

Significance and Causality in Continuous Wavelet and Wavelet Coherence Spectra Applied to Hydrological Time Series

Wavelet transform, wavelet spectra, and coherence are popular tools for studying fluctuations in time series in the form of a bidimensional time and scale representation. We discuss two aspects of wavelet analysis—namely the significance and stochastic/deterministic character of the wavelet spectra. Real-time series of discharge, sodium, and sulfate concentrations in the alpine Rhône River, Switzerland, are used to illustrate these issues. First, the consequences of using an arbitrary stochastic process (usually, AR (1)) instead of the best-fitted general ARMA process in the evaluation of the significance of wavelet spectra are analyzed. Using a general ARMA instead of AR (1) decreases the significance level of the differences in wavelet power spectra (WPS) of ARMA and AR (1) compared to the WPS of the time series in all cases studied and points to a possible systematic overestimation of significance in many published studies. Besides, the significance of particular patches in the spectra is affected by multiple testing. A (conservative) way to circumvent this problem, using global wavelet spectra and global coherence spectra, is evaluated. Finally, we discuss the issue of causality and investigated it in the three measured time series mentioned above. Even if the use of the best fitted ARMA pointed to no deterministic features being present in the corrected series studied (i.e., stochastic processes are dominant in the three data series), coherence spectra between variables allowed to reveal cause-effect relationships between two “coherent” variables and/or the existence of a common effect on both variables. Therefore, such type of analysis provides a useful tool to better understand data causal relationships.

Causality between Economic Policy Uncertainty and Tourism Using Three-dimensional Wavelet-based Approaches

ABSTRACT This study provides new insights into the relationship between economic policy uncertainty (EPU) and tourism activities in the BRIC (Brazil, Russia, India, and China) countries. We used continuous three-dimensional wavelets based on Granger causality analysis to investigate the relationship between EPU and tourism using the annual data. The finding shows that the relationships between the variables evolve through time and frequencies. We uncover significant wavelet coherence and strong lead–lag relationships changing over time, displaying low- to high-frequency cycles over the whole sample period.

Investigating the co‐movement between exchange rates and interest rates in the bi‐variate form: Evidence from Turkey

The exchange rate is considered one of the most important economic factors that monetary authorities seek to control in proportion to its current and its future economic activities. In this study, we investigate the interrelationship between the interest rate and exchange rate at different time horizons (overnight, 6 months and up to 1 year) in Turkey using wavelet analysis, mainly continuous wavelet, cross wavelet, and wavelet coherence, during the period from 2005 to 2019. The results indicate that the relationship in the long‐run and short‐run between exchange rate and interest rate is generally positive and this confirms the purchasing power parity theory and Keynesian approach theoretical predictions on the relationship between exchange rate and interest rate—the negative relationship in the short term is consistent with sticky price models. In terms of the causality, although there is no specified pattern for this relationship, it is evident that the behavior of the lead‐lag relationship between the variables, in the long run, is different from the short run, the exchange rate dominates in the long run. In contrast, in the short‐run, there is a bidirectional causality that varies substantially over time and virtually changes from day to day in the short‐run.

Experimental Flow-Induced Vibration Analysis of the Crossflow Past a Single Cylinder and Pairs of Cylinders in Tandem and Side-by-Side

Abstract Flow-induced vibration of a single cylinder and two cylinders in tandem and side-by-side configurations is experimentally investigated in this paper in the subcritical regime. The natural frequency of the system varied from 8.8 Hz to 46.2 Hz. The mass ratio, m*, ranged between 158 and 643 while the damping ratio, ζ, between 0.0005 and 0.009. The pairs of cylinders present a spacing ratio of 1.26 (P/D and L/D). In all cases, one and both cylinders (BV) were free to vibrate. Experiments were performed in an aerodynamic channel with a constant height and a variable width, for the evaluation of the influence of the blockage ratio (BR), using accelerometers and hot wire anemometry. The reference velocity, measured at the entrance of the test section was used to calculate the reduced velocity, Vr = U/fnD, with values from 4 to 132 and the Reynolds number between 3 × 103 and 8 × 104. The root-mean-square-values of the displacement amplitudes, Y/D, were obtained through the integration of the acceleration signals. Fourier and continuous wavelets were employed in the analysis. For a single cylinder free to vibrate, the higher amplitudes occur at two distinct reduced velocities, associated with the vibration modes of the cylinder. The vibration amplitude of a single cylinder increased as the blockage ratio increased, decreasing for the highest blockage ratio investigated. For the case of cylinders in tandem, the presence of the fixed cylinder in the wake of the cylinder free to vibrate amplifies the vibration response at high reduced velocities. When the blockage ratio is increased, a sudden increase in the vibration amplitude is observed. When both cylinders are free to vibrate, the relation between the natural frequencies of both cylinders influences the response amplitudes. In the case with two cylinders side-by-side, the vibration amplitude remains similar to a single cylinder, but when both cylinders are free to vibrate, the presence and the influence of flow bistability is observed.

Economic Policy Uncertainty and Tourism Nexus Dynamics in the G7 Countries: Further Evidence from the Wavelet Analysis

ABSTRACT This study examines the relationship between economic policy uncertainty (EPU) and tourism activities in the Group of Seven countries. The analysis is conducted using continuous wavelets, wavelet coherency and phase-difference based on Granger causality analysis to investigate the relationship between EPU and tourism. Our analyses indicate that the relationship is generally negative but changes over time, displaying low to high-frequency cycles. Moreover, the timing and frequency changes when EPU co-moves with tourism. The results suggest tourism-economic policy uncertainty led-hypothesis and economic policy uncertainty-tourism led hypothesis with worthy policy implications for tourist destinations across the world.

STRUKTUR VERTIKAL DAN VARIABILITAS ARLINDO YANG MASUK KE TEPI BARAT LAUT BANDA

Arus Lintas Indonesia (Arlindo) merupakan sistem arus antara samudera Pasifik dan Hindia yang melewati Laut Indonesia, seperti melalui jalur primer Selat Makassar ke Laut Flores dan melalui jalur sekunder Selat Lifamatola ke Laut Banda. Penelitian ini bertujuan untuk mengkaji struktur vertikal dan variabilitas Arlindo di Laut Flores Timur (Flores) dan Laut Banda Utara (Banda) yang berasal dari keluaran model laut INDESO antara tahun 2008 dan 2014. Analisis struktur Arlindo dengan menghitung rataan komponen arus secara vertikal. Volume transpor dihitung dari penampang di Laut Banda dan Laut Flores. Deret waktu Arlindo dianalisis variabilitasnya menggunakan filter band-pass dan transformasi wavelet kontinu. Hasil penelitian menunjukkan bahwa Arlindo Banda secara dominan mengalir ke selatan, sedangkan Arlindo Flores mengalir ke timur di sepanjang utara Kepulauan Nusa Tenggara. Struktur vertikal aliran Arlindo mengalami penguatan di kedalaman antara 50 m dan 150 m. Perkiraan total volume transpor selama periode 7 tahun dari kedua jalur Arlindo yang masuk ke Laut Banda bagian barat sebesar 6,27 Sv (±3,81 Sv), yang merupakan kesepakatan baik dengan studi model sebelumnya. Variasi tahunan transpor Arlindo Banda (Flores) maksimum selama musim Barat Laut (Tenggara) dan minimum selama musim Tenggara (Barat Laut). Variabilitas yang mendominasi pada transpor Arlindo Banda ialah periode intra-musiman (ISV) dan semi-tahunan (SAV), sedangkan variabilitas transpor Arlindo Flores didominasi oleh periode tahunan (AV).

Some new discrete biorthogonal wavelets constructed with Laguerre polynomials

In this study, we present a new family of discrete wavelets which are constructed with the help of Laguerre polynomials and the Daubechies biorthogonal wavelets construction method. Our aim is to propose the discrete version of some previously constructed continuous Laguerre wavelets and also to present a method of discrete wavelets construction by several iterations. With this scheme, we use two different sets of finite impulse response filters for the signal decomposition and their duals for reconstruction. The quadruplet finite impulse response filters respect the anti-aliasing and the perfect reconstruction conditions, and at the same time, they resemble as much as possible the continuous Laguerre wavelets when using the cascade algorithm. We use the mean squared error, the maximum deviation, and the standard deviation to quantify the similarity between the continuous Laguerre wavelets and the constructed discrete Laguerre wavelets. The results show that, they are both the same wavelets due to the small nature of these parameters. Our method is important because, it can permit the determination of the finite impulse response filter coefficients corresponding to many other continuous wavelets.

Decomposing a time-frequency relationship between economic policy uncertainty and tourism in the G8 countries through wavelet analysis

ABSTRACT This paper aims to examine the relationship between economic policy uncertainty (EPU) and tourism activities in the Group of Eight countries using wavelet transform context structures. This innovative technique allows the decomposition of time-series at different time frequencies. In this work, we used continuous wavelets, wavelet coherency and wavelet phase-difference based on Granger causality analysis to investigate the relationship between EPU and tourism. Results indicate that the relationship is generally negative but changes over time, displaying low to high frequency cycles. Moreover, the timing and frequency change when EPU co-moves with tourism. Accordingly, it can be recommended that the government increase and promote tourism demand and further provide and nurture the expansion of the tourism supply.

99-LB: Multiscale Biological Rhythms in Individuals with T1D on DIY Closed-Loop and SAPT

Background: Circadian and ultradian rhythms in BG have been observed in individuals without diabetes and are regulated both by time of day and meal intake, with ultradian fluctuations generally of smaller amplitude than circadian fluctuations. We assessed relative stability of circadian and ultradian rhythms in individuals without T1D (n=16), and individuals with T1D using two different therapies: sensor-augmented pump therapy (SAPT, n=100) and DIY closed loop (n=30). Methods: Frequency decomposition using continuous morlet wavelet transformation (A to C) were created to assess change in rhythmic composition of normalized blood glucose data. Results: Example Wavelet (C) in T1D illustrates high power in the 1-6H range, and lower power in the ~24H range for nearly all time points. The ratio of power in the 23-25H (circadian) range to power in the 1-6H (ultradian) range was calculated to estimate relative stability of circadian to ultradian rhythms. Those without T1D showed higher circadian compared to ultradian power, whereas both groups with T1D showed a comparably lower ratio (D). Conclusion: Wavelet analysis of BG in individuals with and without T1D reveals a difference in relative strength of daily and hourly rhythms, independent of therapy type. These results suggest current therapies do not recreate expected daily rhythmicity in blood glucose, perhaps due the lifespan of rapid-acting insulin and meal patterns. Disclosure D.M. Lewis: Research Support; Self; JDRF. A.D. Grant: None. L. Kriegsfeld: None. Funding JDRF

Uncertainty principles for the right-sided multivariate continuous quaternion wavelet transform

ABSTRACT In this paper, we present some new elements of harmonic analysis related to the right-sided multivariate continuous quaternion wavelet transform. The main objective of this article is to introduce the concept of the right-sided multivariate continuous quaternion wavelet transform and investigate its different properties using the machinery of multivariate quaternion Fourier transform. Last, we have proven a number of uncertainty principles for the right-sided multivariate continuous quaternion wavelet transform.

Impact of external applied currents in BVP model

The understanding of the activity of neurons in the brain has been modeled as nonlinear systems using mathematical modeling for decades. Nonlinearity in brain dynamics is complex structure to do mathematically but computational techniques make this area of research quite interesting and easy to study the dynamics. With advancement of new technology, mathematical and computational studies are more preferable to understand the behavior of neurons in a single cell to global cognitive process. In the present study, the impacts of different externally applied currents on the behavior of neurons in a simple BVP model (Bonhoeffer-Vander Pol Model) are analyzed thoroughly. The results of BVP model are similar to the characteristics of neurons shown by the Hodgkin-Huxley Model. In the BPV model, when system is stable, neurons are in resting-state. Unlike Hodgkin-Huxley model which follows all-or-none law, the BVP model does not follow this all-or-none rule. In the BVP model, there is an intermediate phase where no spike forms, but when sufficiently large input applied then spikes emerge. On applying constant current in BVP model, system is stable while it exhibits oscillatory behavior when current is applied externally above threshold value of it. If sinusoidal, continuous wavelet, and har wavelet form of external applied currents are injected then continuous firing emerges which have several interesting dynamics. Numerical simulations have been performed to understand the bifurcation analysis of the BVP model. Oneparameter and two-parameter bifurcation diagrams have been drawn in which threshold current values are discussed.

Improving speech recognition using bionic wavelet features

Bionic wavelet transform is a continuous wavelet, based on adaptive time frequency technique. This paper presents a speech recognition system for recognizing isolated words by discretizing the continuous Bionic Wavelet (BW). Conversion from continuous to discrete is achieved by adopting central frequency and thresholding techniques. The BW features of noisy signal are processed through MFCC to obtain the optimal features of the speech signal. SVM, Artificial Neural Network (ANN) and LSTM techniques are used to improve the recognition rate by enhancing the speech signals. The experiments are conducted on FSDD and Kannada data set. The speech feature vector is calculated using the parameters extracted by Bionic wavelet with different central frequencies of Morlet, Daubechies and Bior3.5, coiflet5 mother wavelets. The obtained Bionic-MFCC optimal features are fed to SVM, ANN and LSTM models for the classification and recognition process. The performance of the models is tabulated for correct recognition that varies from 95% to 96% among these models. The models are tested for various SNRs noise levels like 5 dB, 10 dB, 15 dB and the recognition accuracies of these models are presented for convoluted noisy speech data.

Multimodel ensemble projection of meteorological drought scenarios and connection with climate based on spectral analysis

AbstractPotential change in the hydrological cycles may lead to changes in extreme events such as drought due to the changes in intensity, frequency, and seasonality of precipitation and evaporative demand. In this study, projected drought scenarios and associated uncertainties in the late 21st century over the Continental United States are analysed based on seven regional climate models (RCMs) contributing to the Coordinated Regional Climate Downscaling Experiment. Meteorological drought scenarios are analysed based on standardized precipitation evapotranspiration index (SPEI). Here, we propose a new multimodel ensemble approach based on the similarity of spectral power of different frequency components of the SPEI time series. The approach combines output from different RCMs based on their ability to produce the observed power spectra as well as convergence towards the average spectra from all participating RCMs in the future climate. Furthermore, to understand the SPEI variability associated with climate teleconnection, continuous wavelet transform‐based spectral coherency between the SPEI and two climate indices: the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) is analysed. Results show that among‐model uncertainty is the dominant source of uncertainties in the projected drought scenarios with contributions as large as 97% to the total uncertainty. Fifteen to 20% more frequent droughts are projected in future climate due to a decrease in mean SPEI as well as an increase in the variability of SPEI. Observed SPEI variability is strongly associated with ENSO variability while PDO modulates the strength of correlation between the SPEI and the ENSO. Spectral analysis of future SPEI shows that the increase in the SPEI variability is due to an increase in interannual variability as well as an enhanced ENSO teleconnection over the study area. The results show the increased role of climatic variability and hence the enhanced predictability of drought scenarios in the future climate.

Tourism and House Prices: A Wavelet Analysis

ABSTRACT This paper aims to examine the relationship between tourism activities and house prices (HP) in first-tier cities of China (Beijing, Shanghai and Guangzhou) using the wavelet transform context structures. This innovative technique allows the decomposition of time-series at different time frequencies. In this work, we used continuous wavelets, wavelet coherence and wavelet phase difference based on Granger causality analysis to investigate the relationship between tourism activities and HP. Results indicate that the relationship is generally positive but changes over time, displaying low to high frequency cycles. There is a unidirectional causal influence of HP on tourism activities. Moreover, the timing and frequency changes when HP co-moves with tourism. Accordingly, it can be recommended that the government increases and promotes tourism demand and further provides and nurtures the expansion of tourism supply.