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Create and share a MATLAB library that performs data augmentation algorithms for audio data. This study aims to help machine learning researchers to improve their models using the algorithms proposed by the authors.

The authors structured our library into methods to augment raw audio data and spectrograms. In the paper, the authors describe the structure of the library and give a brief explanation of how every function works. The authors then perform experiments to show that the library is effective.

The authors prove that the library is efficient using a competitive dataset. The authors try multiple data augmentation approaches proposed by them and show that they improve the performance.

A MATLAB library specifically designed for data augmentation was not available before. The authors are the first to provide an efficient and parallel implementation of a large number of algorithms.

The purpose of this paper is to detect the source of stray current interference on underground pipelines in urban areas using a joint time/frequency method of signal analysis.

Investigations are performed on an underground pipeline located in the vicinity of the two direct current tractions: a tramway line and a train line. The results of the analysis are presented in the form of spectrograms, which illustrate changes in the spectral power density of the potential of the rails and of the potential of the pipe in the joint domain time‐frequency.

The comparison of the spectrograms can be used to evaluate if and which stray current source has influence on the investigated metal construction.

The combined analysis in the domain of time and frequency can be used as a supplementary one providing new information useful in the evaluation of stray current corrosion hazard. In the presence of several electric field sources in urban areas, this method reveals the complete time‐frequency characteristic of each stray current source and its interference on the investigated construction.

This paper aims to present an approach of utilizing multiple-input multiple-output (MIMO) radar concept to enhance pedestrian classification in automotive sensors. In a practical environment, radar signals reflected from pedestrians and slow-moving vehicles are similar in terms of reflecting angle and Doppler returns, inducing difficulty for target discrimination. An efficient discrimination between the two targets depends on the ability of the sensor to extract unique characteristics from each target, for example, by exploiting Doppler signatures. This study describes the utilization of MIMO radar for Doppler measurement and demonstrates its application to improve pedestrian classification through actual laboratory measurements.

Multiple non-modulated sinusoidal signals are transmitted orthogonally over a MIMO array using time division scheme, illuminating human and non-human targets. The reflected signal entering each of the receiving antenna are combined at the radar receiver prior to Doppler processing. Doppler histogram was formulated based on a series of measurements, and the Doppler spread of the targets was determined from the histograms. Results were compared between MIMO and conventional single antenna systems.

Measurement results indicated that the MIMO configuration provides able to capture more Doppler information compared to conventional single antenna systems, enabling a more precise discrimination between pedestrian and other slow-moving objects on the road.

The study demonstrated the effectiveness of using MIMO configuration in radar-based automotive sensor to enhance the accuracy of Doppler estimation, which is seldom highlighted in literature of MIMO radars. The result also indicated its usefulness in improving target discrimination capability of the radar, through actual measurement.

A new method of spectral analysis has been proposed for non‐stationary harmonic analysis of corrosion processes. The current of a model circuit has been considered which would simulate a first‐order electrode reaction proceeding in conditions of a linearly changing electrode potential with a superimposed sinusoid signal. It has been shown that the Fourier transformation approach does not reflect the amplitude changes of harmonic components as a function of constant potential. In addition, it has been shown mathematically that application of Gabor transformation in spectral analysis is a means of obtaining the correct frequency components. The Gabor transform correctly reflects amplitude changes of harmonic components as a function of potential. Digital analysis of current changes by Gabor transformation unequivocally confirmed the usability of this method for harmonic analysis of corrosion processes.

This paper sets out to detect and characterize electric fields in the ground (such as stray current fields) using a tandem time/frequency method of signal analysis.

Results were obtained from investigations performed in the presence of a generated electric field with controlled variable characteristics, and in the presence of an electric field generated by a tramline. The analysis of measurement registers was performed using Short‐Time Fourier Transformation. The results were presented in the form of spectrograms, which illustrate changes in the spectral power density of the measured signal versus time.

Tandem time/frequency analysis reveals the random or deterministic character of the electric field, enabling its complete time/frequency characteristics to be obtained. Such information is inaccessible using exclusively the frequency analysis methods that utilize classical Fourier transformations. Moreover, an analysis of the spectral power density distribution of the signals in three directions on the ground surface makes it possible to define the localization of the field source.

Analysis methods for electric fields in the ground should be adapted to the evaluation of non‐stationary signals because the stray currents are of this type. Such a possibility is given by combined analysis in the domains of time and frequency. This method can be used as complementary to applied measurement techniques of stray current interference.

The method of electric field detection and characterization, as related to stray currents, previously has not been presented in the literature. This method of signal analysis may be adopted for other investigations that are reliant on the registration of voltages or potentials characterized by arbitrary frequencies.

This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure.

The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques.

The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge.

The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

The purpose of this paper is to discuss the asymptotic models of different parts with a pitting fault in rolling bearings.

For rolling bearings with a pitting fault, the displacement deviation between raceways and rolling elements is usually considered to vary instantaneously. However, the deviation should change gradually. Based on this shortcoming, the variation rule and calculation method of the displacement deviation are explored. Asymptotic models of different parts with a pitting fault are discussed, respectively. Besides, rolling bearing systems have prominent fractional characteristics unconsidered in the traditional models. Therefore, fractional calculus is introduced into the modeling of rolling bearings. New dynamic asymptotic models of different parts with a pitting fault are proposed based on fractional damping. The numerical simulation is performed based on the proposed model, and the dynamic characteristics are analyzed through the bifurcation diagrams, trajectory diagrams and frequency spectrograms.

Compared with the model based on integral calculus, the proposed model can better reflect the periodic characteristics and fault characteristics of rolling bearings. Finally, the proposed model is verified by the experiment. The dynamic characteristics of rolling bearings at different rotating speeds are analyzed. The experimental results are consistent with the simulation results. Therefore, the proposed model is effective.

(1) The above models are idealized, i.e. the local pitting fault is treated as a rectangle. When a component comes into contact with the fault, the displacement deviation between the component and the fault component immediately releases if the component enters the fault area and restores if the component leaves. However, the displacement deviation should change gradually. Only when the component touches the fault bottom, the displacement deviation reaches the maximum. (2) Due to the material's memory and fluid viscoelasticity, rolling bearing systems exhibit significant fractional characteristics. However, the above models are all proposed based on integral calculus. Integral calculus has some local characteristics and is not suitable for describing historical dependent processes. Fractional calculus can better describe the essential characteristics of the system.

The purpose of this paper is to present a method to analyze the noise in aircraft cabins through the VHF Aeronautical Communication Channel, aimed at examining an environment that has the possibility of communication problems between the aircraft crew and the professionals responsible for the controls on land.

This analysis includes equipment normally used for identification and comparison of electromagnetic noise, the cabin and the environment that are present in an airport, as well as equipment for frequency analysis and intensity of those signals. The analysis is done in a reverse way, eliminating situations that are not common in the examined environment, until the identification of the situation with the irregularity.

According to the results, the implementation of the Fourier transform for noise analysis in the cabin was efficient. These results demonstrate that through this transformation, the noise sources can be identified in the environments in cases where there is much spectrum pollution.

This kind of noise analysis is important, considering the importance of having good accuracy in airport environment analysis.

The paper presents the main trends in the future of aviation communications, and describes the new applications that aim to minimize problems with the current VHF channel.

This paper aims to disentangle Chinese-English-rich resources linguistic and speaker timbre features, achieving cross-lingual speaker transfer for Cambodian.

This study introduces a novel approach: the construction of a cross-lingual feature disentangler coupled with the integration of time-frequency attention adaptive normalization to proficiently convert Cambodian speaker timbre into Chinese-English without altering the underlying Cambodian speech content.

Considering the limited availability of multi-speaker corpora in Cambodia, conventional methods have demonstrated subpar performance in Cambodian speaker voice transfer.

The originality of this study lies in the effectiveness of the disentanglement process and precise control over speaker timbre feature transfer.

To provide an overview of the similarity‐based modeling (SBM) technology and review its application to condition monitoring of rotating equipment using features calculated from vibration sensor signals.

Concentrates on the practical capabilities and underlying technology of SBM. Examines the effectiveness of it as an approach to detect and diagnose faults in an electric motor‐driven shaft during variable speed operating conditions.

The SBM is a non‐parametric pattern recognition technology developed by SmartSignal that is applied generally to multivariate condition monitoring problems. A vibration sensor is monitored by first transforming the digitized time domain sensor signal into relevant features over time. These features are monitored continuously in real time to detect any discernable differences from normality. The deviations in turn, produce fault signatures in time‐feature space that aid in fault diagnosis.

Gives information on an approach that employs a multivariate similarity‐based modeling technique to characterize the expected behavior of vibration signal features which enables the detection of incipient faults in rotating machinery.