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This study presents a rigorous investigation into the mathematical and physical properties inherent in the Fourier phase spectrum of earthquake ground motions. This exploration includes a detailed examination of the probability distribution of phase angles and differences, elucidated through two novel numerical experiments utilizing the reduction ad absurdum approach. Moreover, the study scrutinizes the physical attributes of earthquake ground motion's phase spectrum, employing the circular frequency-dependent phase derivative as a key analytical factor. In a novel approach, the research delves into the relationship between circular frequency-dependent phase derivatives and Fourier amplitudes, shedding light on essential connections within earthquake phenomena, particularly addressing non-stationarity. Expanding the scope, the study comprehensively examines the influence of source, propagation path, and site on both the phase spectrum and accelerogram. Employing the control variate technique facilitates this analysis, providing valuable insights into the underlying physical mechanisms governing earthquake wave behavior. The findings highlight the temporal properties of the phase spectrum, attributing its complexity to the temporal heterogeneity in energy release during the fault rupture and dispersion of earthquake waves. This novel approach not only enhances the understanding of earthquake dynamics, but also underscores the significance of considering temporal variations in earthquake events. [ABSTRACT FROM AUTHOR]

Aquifer diffusivity is a basic physical parameter used in hydrogeological calculations and is important for the evaluation and rational utilization of water resources, pollution prevention, and wetland protection. In this study, with the assumptions of aquifer isotropy, i.e., no vertical flow and constant saturated aquifer thickness, by using the Fourier transform and convolution theorem, a 1D analytical solution of the phase spectrum for an unconfined aquifer system was derived, which subsequently led to a phase spectrum solution for aquifer diffusivity. To test the efficacy, the proposed method was applied to a study site in the middle reach of the Hutuo River in the North China Plain. The estimated aquifer diffusivity ranged from 1.9 × 103 to 4.9 × 104 m2/d, with a mean of 2.2 × 104 m2/d, which was consistent with the results obtained using power spectral analysis, pumping tests, and inverse numerical models. The phase spectral approach proposed in this paper can estimate the aquifer properties on a larger scale. If long time series of hydraulic heads are available, it can estimate hydrogeological parameters accurately and quickly. Considering the similarity of the linearized governing equations, it can also be applied to the river–aquifer system and the confined aquifer system. [ABSTRACT FROM AUTHOR]

This study presents a rigorous investigation into the mathematical and physical properties inherent in the Fourier phase spectrum of earthquake ground motions. This exploration includes a detailed examination of the probability distribution of phase angles and differences, elucidated through two novel numerical experiments utilizing the reduction ad absurdum approach. Moreover, the study scrutinizes the physical attributes of earthquake ground motion’s phase spectrum, employing the circular frequency-dependent phase derivative as a key analytical factor. In a novel approach, the research delves into the relationship between circular frequency-dependent phase derivatives and Fourier amplitudes, shedding light on essential connections within earthquake phenomena, particularly addressing non-stationarity. Expanding the scope, the study comprehensively examines the influence of source, propagation path, and site on both the phase spectrum and accelerogram. Employing the control variate technique facilitates this analysis, providing valuable insights into the underlying physical mechanisms governing earthquake wave behavior. The findings highlight the temporal properties of the phase spectrum, attributing its complexity to the temporal heterogeneity in energy release during the fault rupture and dispersion of earthquake waves. This novel approach not only enhances the understanding of earthquake dynamics, but also underscores the significance of considering temporal variations in earthquake events.

Benefited from the latest advances in deep learning, convolutional neural network (CNN)-based SAR target recognition has made an excellent breakthrough. However, the most previous works pay attention to improve accuracy but neglect the working process analysis of the CNN models. Here, feature extraction of CNN plays an important role in recognition task. Moreover, in image processing field, frequency analysis is a classical way, which can directly reflect the frequency components of images. In view of that, we provide a feature extraction analysis method of pre-trained CNN in frequency domain in this paper. There are two analytical perspectives, i.e. amplitude and phase spectrum. Firstly, we can observe direction and range of pass-frequency through amplitude spectrum of convolution kernels, which represents information of raw SAR image and feature map captured from the convolution layer. Secondly, phase spectrums of SAR images store contour information of targets. We can understand the role of contour information from raw SAR images and feature maps in recognition task by phase spectrum analysis. In experiment part, according to the proposed feature extraction analysis method, we discuss the working process of several pre-trained CNN models. To some extent, it explains why the joint CNN has strong robustness against speckle noise in SAR image target recognition task. In short, the proposed feature extraction analysis method can improve the transparency and credibility of pre-trained CNN used for SAR target recognition. [ABSTRACT FROM AUTHOR]

We have demonstrated both numerically and experimentally a 2D plasmonic metamaterial the unit cell of which comprised an Archimedean spiral with a C-shaped resonator. Such metasurface enables the excitation of spoof localized plasmon resonances (LPRs) in the terahertz frequency range, similar in properties to the familiar LPRs in the visible range. We have compared the thin-film sensing potentials of the fundamental and dark resonant modes supported by the metasurface in the range of 0.2–0.5 THz. Both the amplitude and phase transmission spectra have been studied. A sensitivity of 21.1%/RIU (78.7 GHz/RIU) and a figure of merit (FOM) of 14.4 RIU−1 have been achieved. The FOM and Q factor obtained from the phase transmission spectra were shown to be about twice higher than those obtained from the amplitude spectra. [ABSTRACT FROM AUTHOR]

• An object azimuth measurement method based on OAM phase spectrum under tilted irradiation condition is proposed. • We analyze the relationship between the measurement error caused by the beam oblique irradiation and the angle of tilt and propose an error compensation method. After error compensation, the average error is kept below 0.73° at all tilt angles. • A four-step phase-shifting method is used to measure the helical phase of a vortex beam. In optical remote sensing, a beam carrying orbital angular momentum can be used to identify the azimuth of an object. However, most of the studies reported currently require the beam to be illuminated vertically to the surface of the object, and the general case of tilted irradiation for the beam has not been fully discussed. In this paper, an object azimuth measurement method based on orbital angular momentum phase spectrum under tilted irradiation condition is proposed. We analyze the relationship between the measurement error caused by the beam oblique irradiation and the angle of tilt and propose an error compensation method. In the experiment, the orbital angular momentum phase spectrum of the Laguerre-Gaussian beam is obtained by a four-step phase-shifting method, and the error caused by tilt modulation is measured. After implementing the error compensation scheme, the maximum absolute error in azimuth measurement under tilted irradiation conditions is maintained within 2.15°. Across all tilt angles, the average absolute error remains below 0.73°. The method proposed in this paper has a certain reference value for expanding the practical application of orbital angular momentum beams in the field of remote sensing. [ABSTRACT FROM AUTHOR]

We have evaluated the characteristics of the guided modes of a coupled SPR-Waveguide (SPR-WG) configuration consisting of Prism-gold-Dielectric 1-Dielectric 2-analyte and then have compared it with the conventional SPR structures. The penetration depth, the magnetic field distribution profile, the amplitude and phase spectra in this sensor strongly depend on the thickness of the dielectric layers used and the refractive index of the sensing medium (ns). The value of the field penetration depth in the proposed sensor can be increased by changing ns. The results indicated that the penetration depth values for the refractive indices of 1.333 and 1.533 are 8 µm and 80 µm, respectively. In addition, it was found that the SPR-WG sensor provides the highest sensitivity (equivalent to 200 RIU−1) among all sensors at ns = 1.533. The results also showed that the proposed sensor has a high phase sensitivity compared to the conventional SPR sensor. Overall, by adjusting the geometry parameters and ns, these sensors can be used as a useful tool for extracting optical information from biological samples, including prokaryotic and eukaryotic cells. [ABSTRACT FROM AUTHOR]

Summary: The stress state of steel members is an important indicator in evaluating structural safety. The ultrasonic time‐of‐flight method of measuring the stress of steel members based on acoustoelastic theory has been fully developed. However, the time difference is hard to be measured. The present paper proposes a new method of measuring the uniaxial stress of steel members using the phase spectrum of the ultrasonic transverse wave. The effect of interference of the two wave components generated by shear‐wave birefringence under uniaxial stress is investigated. It is found that the derivative curve of the phase spectrum of the pulse‐echo comprising the two wave components reaches a maximum periodically, and the frequency corresponding to the maxima is sensitive to stress and relatively easy to be measured. On this basis, a theoretical formula for the measurement of the uniaxial stress of steel members based on the phase spectrum is derived. Results of calibration tests show a good linear relationship between the stress and the reciprocal of the first response frequency corresponding to the maximum of the derivative curve of the phase spectrum. The uniaxial stress can then be measured by obtaining the first response frequency of the phase spectrum of the in‐service structural steel member. In addition, the effects of the thickness of steel members and the sampling rate of the oscilloscope on the uniaxial stress measurement are investigated. The present paper also illustrates the correspondence between the amplitude spectrum method and phase spectrum method. [ABSTRACT FROM AUTHOR]

This paper proposes an automatic ship detection approach in Synthetic Aperture Radar (SAR) Images using phase spectrum. The proposed method mainly contains two stages: Firstly, sea-land segmentation of SAR Images is one of the key stages for SAR image application such as sea-targets detection and recognition, which are easily detected only in sea regions. In order to eliminate the influence of land regions in SAR images, a novel land removing method is explored. The removing method employs a Harris corner detector to obtain some image patches belonging to land, and the probability density function (PDF) of land area can be estimated by these patches. Thus, an appropriate land segmentation threshold is accordingly obtained. Secondly, an automatic ship detector based on phase spectrum is proposed. The proposed detector is free from various idealized assumptions and can accurately detect ships in SAR images. Experimental results demonstrate the efficiency of the proposed ship detection algorithm in diversified SAR images.

Turbulence coherence in mountainous areas necessitates meticulous evaluation due to the complex terrain blocking. This study focuses on the turbulence coherence of the non-uniform wind field in a canyon via the anemometers positioned along a bridge span. Based on a proposed multi-point clustering, two categories of strong winds impacted by a nearby ridge are identified. The turbulence coherence of the two strong winds is then investigated with an extra focus on the phase spectrum. Several complex coherence functions are extended from commonly employed real forms, including the simplified Krenk's formula proposed. The fitting results of them all suggest that parameters such as the decay factor of the two strong winds show a negative linear correlation with separation but their relationship with wind speed is not significant. For the phase spectrum, in addition to skew winds, the contribution of horizontal wind shear is first emphasized in the two strong winds with piecewise fittings. This paper also discusses single-point coherence between the along-wind and vertical turbulence components. It is found to be unusually positive in sign due to the influence of the local topography and a formula with a constant term is suggested that substantially improves the fitting compared to Solari's formula. • The turbulence coherence with different separations is studied in a non-uniform wind field. • The strong winds are classified by multi-point clustering of the orthogonal components. • The contributions of horizontal wind shear and skew wind to the phase spectrum are emphasized. • The single-point coherence between different turbulence components is investigated. [ABSTRACT FROM AUTHOR]

Prioritized processing of fearful compared to neutral faces has been proposed to result from evolutionary adaptation of the contrast sensitivity function (CSF) to the features of emotionally relevant faces and/or vice versa. However, it is unknown whether a stimulus merely has to feature the amplitude spectrum of a fearful face to be prioritized or whether the relevant spatial frequencies have to occur with specific phases and orientations. Prioritized processing is indexed by specific increases of Event‐Related Potentials (ERPs) of the EEG and occurs throughout different early processing stages, indexed by emotion‐related modulations of the P1, N170, and EPN. In this pre‐registered study, we manipulated phase and amplitude properties of the Fourier spectra of neutral and fearful faces to test the effect of phase coherence (PC, face vs. scramble) and orientation coherence (OC, original vs. rotational average) and their interactions with differential emotion processing. We found that differential emotion processing was not present at the level of P1 but strongly affected N170 and EPN. In both cases, intact phase coherence was required for enhanced processing of fearful faces. OC did not interact with emotion. While faces produced the typical N170 effect, we observed a reversed effect for scrambles. Additional exploratory independent component analysis (ICA) suggests that this reversal could signal a mismatch between an early "perceptual hypothesis" and feedback of configural information. In line with our expectations, fearful‐neutral differences for the N170 and EPN depend on configural information, i.e., recognizable faces. Human contrast sensitivity is optimally tuned to the frequency spectrum of emotional faces, suggesting that a primary visual feature analysis contributes to emotional face processing. We show that electrophysiological indices of threat processing in fearful faces require intact phase information in their spectra. Orientation information does not show significant effects. In the absence of intact phase information, mid‐latency effects are reversed, possibly indicating a mismatch between an early "perceptual hypothesis" and feedback of configural information. [ABSTRACT FROM AUTHOR]

The existing deep neural network speech enhancement methods ignore the importance of phase spectrum learning and cause the enhanced speech quality to be unsatisfactory. In view of this problem, a speech enhancement method based on convolutional recurrent network and non-local modules is proposed in the present study. By designing an encoder-decoder network, the time-domain representation of the speech signal is used as the input of the encoding end for deep feature extraction, so as to make full use of the amplitude information and phase information of the speech signal. Non-local modules are added to the convolutional layers of the encoder and decoder to extract key features of the speech sequence while suppressing useless features. A gated loop unit network is introduced to capture the timing correlation information between the speech sequences. The experimental results on the ST-CMDS Chinese speech dataset show that compared with the unprocessed noisy speech, the quality and intelligibility of the enhanced speech are improved by 61% and 7.93% on average. [ABSTRACT FROM AUTHOR]

With the improvement of people's security awareness, numerous monitoring equipment has been put into use, resulting in the explosive growth of surveillance video data. Key frame extraction technology is a paramount technology for improving video storage efficiency and enhancing the accuracy of video retrieval. It can extract key frame sets that can express video content from massive videos. However, the existing key frame extraction algorithms of surveillance video still have deficiencies, such as the destruction of image information integrity and the inability to extract key frames accurately. To this end, this paper proposes a key frame extraction algorithm of surveillance video based on quaternion Fourier saliency detection. Firstly, the algorithm used colors, and intensity features to perform quaternion Fourier transform on surveillance video sequences. Next, the phase spectrum of the quaternion Fourier transformed image was obtained, and he image visual saliency map was obtained according to the quaternion Fourier phase spectrum. Then, the image visual saliency map of two adjacent frames is used to characterize the change of target motion state. Finally, the frames that can accurately express the motion state of the target are selected as key frames. The experimental results show that the method proposed in this paper can accurately capture the changes of the local motion state of the target while maintaining the integrity of the image information. [ABSTRACT FROM AUTHOR]

In this article, phase of the Fourier transform (FT), which has observed to be a crucial component in image representation, is utilized for visual target tracking. The main aim of the proposed scheme is to reduce the computational complexity of cross-correlation-based matching frameworks. Normalized cross-correlation (NCC) function-based object tracker is converted to a phase minimization problem under the following assumption: In visual object tracking applications, if the frame rate is high, the moving object can be considered to have translational shifts in image domain in a small time window. Since the proposed tracking framework works in the Fourier domain, the translational shifts in the image space are converted to phase variations in the Fourier domain due to the "translational invariance" property of the FT. The proposed algorithm estimates the spatial target position based on the phase information of the target region. The proposed framework uses the ℓ 1 -norm and provides a computationally efficient solution for the tracking problem. Experimental studies indicate that the proposed phase-based technique obtain comparable results with baseline tracking algorithms which are computationally more complex. [ABSTRACT FROM AUTHOR]

We have demonstrated both numerically and experimentally a 2D plasmonic metamaterial the unit cell of which comprised an Archimedean spiral with a C-shaped resonator. Such metasurface enables the excitation of spoof localized plasmon resonances (LPRs) in the terahertz frequency range, similar in properties to the familiar LPRs in the visible range. We have compared the thin-film sensing potentials of the fundamental and dark resonant modes supported by the metasurface in the range of 0.2–0.5 THz. Both the amplitude and phase transmission spectra have been studied. A sensitivity of 21.1%/RIU (78.7 GHz/RIU) and a figure of merit (FOM) of 14.4 RIU−1 have been achieved. The FOM and Q factor obtained from the phase transmission spectra were shown to be about twice higher than those obtained from the amplitude spectra.

How non-symbolic numerosity is visually extracted remains a matter of intense debate. Most evidence suggests that numerosity is directly extracted on individual objects following Weber's law, at least for a moderate numerical range. Alternative accounts propose that, whatever the range, numerosity is indirectly derived from summary texture-statistics of the raw image such as spatial frequency (SF). Here, to disentangle these accounts, we tested whether the well-known behavioural signature of numerosity encoding (ratio effect) is preserved despite the equalisation of the SF content. In Experiment 1, participants had to select the numerically larger of two briefly presented moderate-range numerical sets (i.e., 8-18 dots) carefully matched for SF; the ratio between numerosities was manipulated by levels of increasing difficulty (e.g., 0.66, 0.75, 0.8). In Experiment 2, participants performed the same task, but they were presented with both the original and SF equalised stimuli. In both experiments, the results clearly showed a ratio-dependence of the performance: numerosity discrimination became harder and slower as the ratio between numerosities increased. Moreover, this effect was found to be independent of the stimulus type, although the overall performance was better with the original rather than the SF equalised stimuli (Experiment 2). Taken together, these findings indicate that the power spectrum per se cannot explain the main behavioural signature of Weber-like encoding of numerosities (the ratio effect), at least over the tested numerical range, partially challenging alternative indirect accounts of numerosity processing. [ABSTRACT FROM AUTHOR]

The geostatistical analysis of multivariate spatial data for inference as well as joint predictions (co-kriging) ordinarily relies on modeling of the marginal and cross-covariance functions. While the former quantifies the spatial dependence within variables, the latter quantifies the spatial dependence across distinct variables. The marginal covariance functions are always symmetric; however, the cross-covariance functions often exhibit asymmetries in the real data. Asymmetric cross-covariance implies change in the value of cross-covariance for interchanged locations on fixed order of variables. Such change of cross-covariance values is often caused due to the spatial delay in effect of the response of one variable on another variable. These spatial delays are common in environmental processes, especially when dynamic phenomena such as prevailing wind and ocean currents are involved. Here, we propose a novel approach to introduce flexible asymmetries in the cross-covariances of stationary multivariate covariance functions. The proposed approach involves modeling the phase component of the constrained cross-spectral features to allow for asymmetric cross-covariances. We show the capability of our proposed model to recover the cross-dependence structure and improve spatial predictions against traditionally used models through multiple simulation studies. Additionally, we illustrate our approach on a real trivariate dataset of particulate matter concentration ( PM 2.5 ), wind speed and relative humidity. The real data example shows that our approach outperforms the traditionally used models, in terms of model fit and spatial predictions. Supplementary materials accompanying this paper appear on-line. [ABSTRACT FROM AUTHOR]

Trypophobia refers to the visual discomfort experienced by some people when viewing clustered patterns (e.g., clusters of holes). Trypophobic images deviate from the 1/f amplitude spectra typically characterizing natural images by containing excess energy at mid-range spatial frequencies. While recent work provides partial support for the idea of excess mid-range spatial frequency energy causing visual discomfort when viewing trypophobic images, a full factorial manipulation of image phase and amplitude spectra has yet to be conducted in order to determine whether the phase spectrum (sinusoidal waveform patterns that comprise image details like edge and texture elements) also plays a role in trypophobic discomfort. Here, we independently manipulated the phase and amplitude spectra of 31 Trypophobic images using a standard Fast Fourier Transform (FFT). Participants rated the four different versions of each image for levels of visual comfort, and completed the Trypophobia Questionnaire (TQ). Images having the original phase spectra intact (with either original or 1/f amplitude) explained the most variance in comfort ratings and were rated lowest in comfort. However, images with the original amplitude spectra but scrambled phase spectra were rated higher in comfort, with a smaller amount of variance in comfort attributed to the amplitude spectrum. Participant TQ scores correlated with comfort ratings only for images having the original phase spectra intact. There was no correlation between TQ scores and comfort levels when participants viewed the original amplitude / phase-scrambled images. Taken together, the present findings show that the phase spectrum of trypophobic images, which determines the pattern of small clusters of objects, plays a much larger role than the amplitude spectrum in determining visual discomfort.

The article is devoted to a survey of the known basic Time-Delay Estimation (TDE) methods in the application for detecting fluid leaks in pipeline transport and distribution systems. In the paper, both active and passive estimation methods are considered with respect to the presented generalized classification. However, the main attention is paid to the study of passive methods and their algorithmic implementation. Among the passive methods the Absolute Difference Function (ADF) minimizing algorithms, the Basic Cross-Correlation (BCC) algorithm, the adaptive Least Mean Square (LMS) filtering algorithm are implemented, investigated and compared using a mathematical model of a leak noise signal. All the algorithms are described and the results of the comparison are provided. The advantage of the LMS algorithm in processing the noisy signals is shown. However, its implementation requires choosing a convergence parameter. The necessity in choice of the additional parameter makes the LMS algorithm less practically applicable than the BCC algorithm. The ADF algorithm showed the lowest noise resistivity and can be considered as useful for signal detection, but not for TDE. Some conclusions regarding algorithms’ use for solving the problem of locating leaks are stated. In particular, correlation-based TDE algorithms, as generalized cross-correlation and time-frequency cross-correlation, appear to be the best choice for the implementation of leak detection software.

Trypophobia refers to the visual discomfort experienced by some people when viewing clustered patterns (e.g., clusters of holes). Trypophobic images deviate from the 1/ f amplitude spectra typically characterizing natural images by containing excess energy at mid-range spatial frequencies. While recent work provides partial support for the idea of excess mid-range spatial frequency energy causing visual discomfort when viewing trypophobic images, a full factorial manipulation of image phase and amplitude spectra has yet to be conducted in order to determine whether the phase spectrum (sinusoidal waveform patterns that comprise image details like edge and texture elements) also plays a role in trypophobic discomfort. Here, we independently manipulated the phase and amplitude spectra of 31 Trypophobic images using a standard Fast Fourier Transform (FFT). Participants rated the four different versions of each image for levels of visual comfort, and completed the Trypophobia Questionnaire (TQ). Images having the original phase spectra intact (with either original or 1/ f amplitude) explained the most variance in comfort ratings and were rated lowest in comfort. However, images with the original amplitude spectra but scrambled phase spectra were rated higher in comfort, with a smaller amount of variance in comfort attributed to the amplitude spectrum. Participant TQ scores correlated with comfort ratings only for images having the original phase spectra intact. There was no correlation between TQ scores and comfort levels when participants viewed the original amplitude / phase-scrambled images. Taken together, the present findings show that the phase spectrum of trypophobic images, which determines the pattern of small clusters of objects, plays a much larger role than the amplitude spectrum in determining visual discomfort. [ABSTRACT FROM AUTHOR]

Signal processing applications dealing with secure transmission are enjoying increasing attention lately. This paper provides some theoretical insights as well as a practical solution for transmitting a hash of an image to a central server to be compared with a reference image. The proposed solution employs a rigid image registration technique viewed in a distributed source coding perspective. In essence, it embodies a phase encoding framework to let the decoder estimate the transformation parameters using a very modest amount of information about the original image. The problem is first cast in an ideal setting and then it is solved in a realistic scenario, giving more prominence to low computational complexity in both the transmitter and receiver, minimal hash size, and hash security. Satisfactory experimental results are reported on a standard images set. [ABSTRACT FROM AUTHOR]

Infrared small target detection is a crucial part of infrared search and track system, and it has been a significant research topic in the past decades. Inspired by previous studies showing that phase spectrum of quaternion Fourier transform (PQFT) great superiority in salient region extraction and the desirable characteristics of multi-scale, multi-direction and shift-invariant with non-subsampled shearlet transform (NSST), a new target detection method is proposed based on NSST and PQFT in this paper. The original image is first subjected to NSST decomposition to obtain a low frequency component and four high frequency components by NSP. Next, directional localization is achieved by shearing filters which provides multi-directional decomposition. Then, four direction high frequency sub-images decomposed by NSST are introduced as four data channels of PQFT. The reconstruction map that highlights the salient region in the time domain is computed using the inverse PQFT. Lastly, the real target is directly segmented by an adaptive threshold. The proposed method is validated by five test sequences. The experimental results show that our method is superior to other traditional methods in terms of robustness and effectiveness in complex background. [ABSTRACT FROM AUTHOR]

Due to a high similarity between the recaptured voice recorded by high-fidelity ripping equipment and the original voice,the automatic speaker verification（ASV）system used to be attacked illegally by the recaptured voice.In order to improve the ability of resisting the attack,a recaptured voice detection method was proposed based on the difference of phase spectrum between original and recaptured voices for the ASV system.In addition,the effects of different recording and replay devices,the FFT were discussed.Experimental results show that the proposed method can accurately recognize the recording voice,of which detection rate is 99.04%。Meanwhile,the equal error rate (EER) of the ASV system has dropped about 22% with this method being integrated,which indicates that the system’s ability of resisting playback attack is enhanced.

The article presents the results of research on opportunities of revealing a weak target movement in foliage-penetration environment with the use of Stepped Frequency Continuous Wave Radar in the frequency range of 1 200…1 800 MHz. The entropy weighed coherent integration (EWCI) algorithm is adopted to phase fluctuations of radar returns and it allows the multipath effects to be mitigated and the detectability and visibility of targets behind foliage brushes and trees to become significantly better.

In the dry-cured ham industry, an accurate control of the dry-salting process is especially complex because of the great heterogeneity of the meat pieces and the effect of different operational variables. The main objective of this study was to evaluate the feasibility of using an ultrasound system and methodology, adapted to the industry requirements, for the online monitoring of the ham dry-salting process. For that purpose, hams were dry salted for different times (4, 10, 11, 14, 16 and 30 days) at 2 °C. The cushion zone of the ham was placed over the transducers during salting and ultrasonic signals were taken automatically (5 min interval by using pulse-echo mode. Several methods of signal analysis were considered in order to assess the time of flight (TOF). TOF estimations by means of the energy threshold and cross-correlation methods (between the initial ultrasonic signal and the remaining signals measured during salting and between consecutive signals 5 min apart without interpolation) were affected by the low signal-to-noise ratio and the pulse distortion and were discarded for the online monitoring of ham salting. Otherwise, the cross-correlation method between consecutive signals (5 min apart) with interpolation n = 3 (CCM-CS n = 3), between non-consecutive signals (1 h apart) (CCM-NCS) and the phase spectrum method (PSM), provided close estimations of the variation of the TOF, which correlated well with the ham salt gain (R2 = 0.83 for CCM-CS n = 3, 0.93 for CCM-NCS and 0.90 for PSM). Consequently, the use of ultrasonic pulse-echo TOF measurements could be considered as a simple, non-invasive, non-destructive and reliable technique for the industrial monitoring of the ham dry-salting process. • The feasibility of using ultrasonics for online monitoring of ham salting has been proved. • Salting induced low signal-to-noise ratio and pulse distortion which hindered signal analysis. • Time of flight variations (ΔTOF) were adequately assessed by cross correlation and phase spectrum methods. • Time of flight decreased during salting due to the increase in the meat elastic stiffness. • Salt gain in the hams was well correlated with ΔTOF. [ABSTRACT FROM AUTHOR]

Spatial images with unnatural amplitude spectra tend to appear uncomfortable. Analogous effects are found in the temporal domain, yet discomfort in flickering patterns is also strongly dependent on the phase spectrum. Here we examined how discomfort in temporal flicker is affected by adaptation to different amplitude and phase spectra. Adapting and test flicker were square wave or random phase transitions in a uniform field filtered by increasing (blurred) or decreasing (sharpened) the slope of the amplitude spectrum. Participants rated the level of discomfort or sharpness/blur for the test flicker. Before adaptation, square wave transitions were rated as most comfortable when they had "focused" edges, which were defined as characterized by 1/f amplitude spectra, while random phase transitions instead appeared more comfortable the more blurred they were. After adapting to blurred or sharpened transitions, both square wave and random phase flicker appeared more sharpened or blurred, respectively, and these effects were consistent with renormalization of perceived temporal focus. In comparison, adaptation affected discomfort in the two waveforms in qualitatively different ways, and exposure to the adapting stimulus tended to increase rather than decreased its perceived discomfort. These results point to a dissociation between the perceived amplitude spectrum and perceived discomfort, suggesting they in part depend on distinct processes. The results further illustrate the importance of the phase spectrum in determining visual discomfort from flickering patterns. [ABSTRACT FROM AUTHOR]

One of the interesting problems is the determination of the phase position and phase jitter of electron bunches in the field of an accelerating electromagnetic wave. It is shown that the phase position and phase jitter of the cosine segment is possible to determine by the phase spectrum in the microwave range. [ABSTRACT FROM AUTHOR]

Earthquake engineers are typically faced with the challenge of safely and economically designing structures in highly uncertain seismic environments. Yield strength demand spectra provide basic information for the seismic design of structures and take nonlinear behavior into account. The designed structures, however, must be checked for seismic performance through dynamic analysis. Design-response spectra compatible earthquake motions (DRSCEM) are commonly used for this purpose. Because DRSCEM are strongly affected by the assigned phase characteristics, in this paper, we simulate realistic earthquake motion phase based on a stochastic process that modifies fractional Brownian motion (fBm). The parameters that control this process were determined via regression equations as functions of the earthquake magnitude and epicenter distance, which were obtained through a regression analysis that was performed on data from a database of recorded ground motions. After validating the efficiency of the modeled phase spectrum, large numbers of DRSCEMs were simulated with which several ductility demand spectra were obtained. By statistically analyzing these results, a rigorous yield seismic coefficient demand spectrum is proposed. [ABSTRACT FROM AUTHOR]

Abstract Aim at nondestructively characterizing the interfacial roughness of coatings, ultrasonic reflection coefficient phase spectrum (URCPS) as a function of interfacial roughness is derived based on the phase screen approximation theory [ 1 ]. For inhomogeneous coatings, the attenuation coefficient α (f) shows a non-negligible effect on the URCPS. The relationship of α (f) on frequency f is used to decouple the URCPS. The constructed URCPS is used to determine the interfacial roughness and thickness of specimens through a two-parameter inversion utilizing the cross-correlation algorithm. The effects of the coating inhomogeneity (such as porosity) on the roughness measurement are analyzed through numerical calculation. A series of simulations with interfacial roughness from 6.2 to 12.7 μm indicate that measurement errors of the thickness are all less than 8.0%. The relative errors of the measured roughness of models without porosity and models with the porosity of 3% are less than 11.8%. For the models with porosity 5%, when the roughness is larger than 10.3 μm, the relative error is still larger than 11.7%. Ultrasonic experiments were carried out on a tungsten carbide (WC Ni) coating utilizing water immersion, flat transducer. The WC-Ni coating, with unknown interfacial roughness, was sprayed on a stainless steel using the high-velocity oxygen fuel (HVOF) method. Experimental results show that the interfacial roughness of specimen obtained by the proposed ultrasonic measurement are in good agreement with that of SEM observations, the absolute error of the measured roughness is less than 1.4 μm and the relative error was less than 11.0%. Highlights • An URCPS as a function of interfacial roughness is developed to test the roughness and thickness of inhomogeneous coatings. • Coatings morphology is constructed using a random pore model based on Gaussian distribution and autocorrelation function. • Attenuation coefficient α (f) acting on the URCPS is decoupled based on the scattering mechanism presented by Sayers. • URCPS function was resolved through cross-correlation algorithm by reducing the offset of URCPS. • The roughness measured by ultrasonic method is in good agreement with those observed by SEM with less than 11.0% error. [ABSTRACT FROM AUTHOR]

In the seismic reliability analysis of engineering structures, it is often necessary to adopt stochastic ground motions as inputs. However, the current methods used to generate stochastic samples, such as the spectral representation method, the spectral transfer method, the dynamic source method, the physical source method, and the comprehensive method, etc., are not very convincing since they do not contain the complete information of seismic occurrence and propagation. In this study, an improved finite-fault model for stochastic simulation of ground motions is proposed. Compared to existing stochastic finite-fault model, the improved model considers the propagation law of phase spectrum, local site effect, and the impact of wave velocity on the arrival time of seismic waves. Besides, identification and statistics of model parameters are carried out based on ground motion records. Reasonable samples of stochastic ground motions are then obtained. In addition, parameter sensitivity analysis is conducted to determine critical random variables, which reduces the complexity of stochastic simulation. Simulation results are compared with recorded accelerograms from the 1999 Chi-Chi earthquake. It is shown that the improved stochastic finite-fault model is reliable, and the acceleration response spectra of simulated samples are consistent with those of station records collected at various site classes and the design spectra. • An improved finite-fault model for stochastic simulation of ground motions is proposed. • Parameter sensitivity analysis is conducted to determine critical random variables of model. • Simulation results are compared with recorded accelerograms from the 1999 Chi-Chi earthquake. • Acceleration response spectra of simulated samples are consistent with those of station records and design spectra. [ABSTRACT FROM AUTHOR]