Daylaustsen1138

Piles are the state-of-the-art foundation type for offshore structures like offshore wind turbines. The pile driving process induces high sound pressure levels into the water, which are potentially harmful for the marine environment. To protect the marine life, regulations for these levels apply in many regions of the world. Therefore, detailed pile driving noise models are necessary to allow for both a prognosis of the underwater noise levels and the dimensioning and optimization of possible noise mitigation systems. In this paper, an established model based on a finite element approach is validated by means of three measurement campaigns. These have been conducted at different sites in the North Sea and include piling with and without noise mitigation measures. The noise mitigation systems are modelled as fully absorbing by applying a mixed Dirichlet-Neumann boundary condition at its position. Therefore, the computational results with noise mitigation measures are generally below the measured data and present the highest achievable noise reduction. The measurement campaigns have been conducted with a big bubble curtain and a noise mitigation screen. The occurring differences between the modelled and measured results with and without noise mitigation are shown.Older adults exhibit deficits in auditory temporal processing relative to younger listeners. These age-related temporal processing difficulties may be further exacerbated in older adults with cochlear implant (CIs) when CI electrodes poorly interface with their target auditory neurons. The aim of this study was to evaluate the potential interaction between chronological age and the estimated quality of the electrode-neuron interface (ENI) on psychophysical forward masking recovery, a measure that reflects single-channel temporal processing abilities. Fourteen CI listeners (age 15 to 88 years) with Advanced Bionics devices participated. Forward masking recovery was assessed on two channels in each ear (i.e., the channels with the lowest and highest signal detection thresholds). Results indicated that the rate of forward masking recovery declined with advancing age, and that the effect of age was more pronounced on channels estimated to interface poorly with the auditory nerve. These findings indicate that the quality of the ENI can influence the time course of forward masking recovery for older CI listeners. Channel-to-channel variability in the ENI likely interacts with central temporal processing deficits secondary to auditory aging, warranting further study of programming and rehabilitative approaches tailored to older listeners.Frequency selectivity in the amplitude modulation (AM) domain has been demonstrated using both simultaneous AM masking and forward AM masking. This has been explained using the concept of a modulation filter bank (MFB). Here, we assessed whether the MFB occurs before or after the point of binaural interaction in the auditory pathway by using forward masking in the AM domain in an ipsilateral condition (masker AM and signal AM applied to the left ear with an unmodulated carrier in the right ear) and a contralateral condition (masker AM applied to the right ear and signal AM applied to the left ear). The carrier frequency was 8 kHz, the signal AM frequency, fs, was 40 or 80 Hz, and the masker AM frequency ranged from 0.25 to 4 times fs. Contralateral forward AM masking did occur, but it was smaller than ipsilateral AM masking. Tuning in the AM domain was slightly sharper for ipsilateral than for contralateral masking, perhaps reflecting confusion of the signal and masker AM in the ipsilateral condition when their AM frequencies were the same. The results suggest that there might be an MFB both before and after the point in the auditory pathway where binaural interaction occurs.Categorical perception (CP) describes how the human brain categorizes speech despite inherent acoustic variability. We examined neural correlates of CP in both evoked and induced electroencephalogram (EEG) activity to evaluate which mode best describes the process of speech categorization. Listeners labeled sounds from a vowel gradient while we recorded their EEGs. Using a source reconstructed EEG, we used band-specific evoked and induced neural activity to build parameter optimized support vector machine models to assess how well listeners' speech categorization could be decoded via whole-brain and hemisphere-specific responses. We found whole-brain evoked β-band activity decoded prototypical from ambiguous speech sounds with ∼70% accuracy. However, induced γ-band oscillations showed better decoding of speech categories with ∼95% accuracy compared to evoked β-band activity (∼70% accuracy). Induced high frequency (γ-band) oscillations dominated CP decoding in the left hemisphere, whereas lower frequencies (θ-band) dominated the decoding in the right hemisphere. Moreover, feature selection identified 14 brain regions carrying induced activity and 22 regions of evoked activity that were most salient in describing category-level speech representations. Among the areas and neural regimes explored, induced γ-band modulations were most strongly associated with listeners' behavioral CP. The data suggest that the category-level organization of speech is dominated by relatively high frequency induced brain rhythms.This paper proposes an acoustic model of the saxophone mouthpiece as a transfer matrix (TM). The acoustical influence of the mouthpiece is investigated, and the TM mouthpiece model is compared to previously reported mouthpiece representations, including cylindrical and lumped models. A finite element mouthpiece model is first developed, from which the TM model is derived, and both models are validated by input impedance measurements. The comparison of acoustic properties among different mouthpiece models shows that the TM mouthpiece is more accurate than the other two models, especially in preserving the high-frequency acoustic characteristics. The TM model also produces the best overall tuning of the first several impedance peaks when coupled to a measured saxophone impedance. The internal and radiated sound pressure are synthesized for an alto saxophone connected to different mouthpiece models by jointly modeling the input impedance and the radiation transfer function using recursive parallel filters. Differences are found among mouthpiece models in terms of oscillation thresholds, playing frequencies, spectral centroids, pressure waveforms, and bifurcation delays, which can be partially explained by differences in the tuning and high-frequency characteristics.Vertical underwater acoustic (UWA) communications play a crucial role in deep-sea applications. A vertical UWA channel generally features a moderate multipath but with time-varying Doppler shifts as well as loud impulsive noise. To achieve a robust vertical single-carrier UWA communication, this paper proposes an enhanced iterative receiver. First, a spline interpolation-based timing estimation approach is proposed to compensate for the time-varying Doppler effects efficiently. Then, the residual timing errors and the multipath interference are tackled by a fractionally spaced self-iterative soft equalizer (SISE) based on the vector approximate message passing (VAMP) algorithm. The VAMP-SISE consists of four parts an inner soft slicer and an inner soft equalizer for symbol detection as well as a denoiser and a minimum mean-squared error estimator for impulsive noise suppression. Epacadostat manufacturer Different parts iteratively exchange extrinsic information to improve the equalization performance. Last, a channel-fitting irregular convolutional code and a unity-rate code are employed at the transmitter to lower the signal-to-noise ratio threshold for reliable communications. Deep-sea experiments verify the performance superiority of the proposed receiver over existing schemes.This paper presents a boundary element-based scheme for the sensitivity analysis of acoustic eigenfrequencies of both interior and exterior acoustic systems. The nonlinear eigenvalue problem generated by the acoustic boundary element method is first reformulated into a generalized eigenvalue problem of reduced dimension through a contour integral approach. The sensitivity formulations for acoustic eigenfrequencies are then derived based on an adjoint method that uses both the right and left eigenvectors. The adaptive cross approximation in conjunction with the hierarchical matrices is used to reduce the solution burden of the boundary element systems. The Burton-Miller-type combined formulation is applied to shift the spurious eigenfrequencies and their sensitivities, and the strategies to identify the spurious results are suggested. Three numerical examples are used to verify the accuracy and applicability of the developed scheme.A deep transfer learning (DTL) method is proposed for the direction of arrival (DOA) estimation using a single-vector sensor. The method involves training of a convolutional neural network (CNN) with synthetic data in source domain and then adapting the source domain to target domain with available at-sea data. The CNN is fed with the cross-spectrum of acoustical pressure and particle velocity during the training process to learn DOAs of a moving surface ship. For domain adaptation, first convolutional layers of the pre-trained CNN are copied to a target CNN, and the remaining layers of the target CNN are randomly initialized and trained on at-sea data. Numerical tests and real data results suggest that the DTL yields more reliable DOA estimates than a conventional CNN, especially with interfering sources.Traditionally, real-time generation of spectro-temporally modulated noise has been performed on a linear amplitude scale, partially due to computational constraints. Experiments often require modulation that is sinusoidal on a logarithmic amplitude scale as a result of the many perceptual and physiological measures which scale linearly with exponential changes in the signal magnitude. A method is presented for computing exponential spectro-temporal modulation, showing that it can be expressed analytically as a sum over linearly offset sidebands with component amplitudes equal to the values of the modified Bessel function of the first kind. This approach greatly improves the efficiency and precision of stimulus generation over current methods, facilitating real-time generation for a broad range of carrier and envelope signals.Optical generation of ultrasound using nanosecond duration laser pulses has generated great interest both in industrial and biomedical applications. The availability of portable laser devices using semiconductor technology and optical fibres, as well as numerous source material types based on nanocomposites, has proliferated the applications of laser ultrasound. The nanocomposites can be deposited on the tip of optical fibres as well as planar hard and soft backing materials using various fabrication techniques, making devices suitable for a variety of applications. The ability to choose the acoustic material properties and the laser pulse duration gives considerable control over the ultrasound output. Here, an analytical time-domain solution is derived for the acoustic pressure waveform generated by a planar optical ultrasound source consisting of an optically absorbing layer on a backing. It is shown that by varying the optical attenuation coefficient, the thickness of the absorbing layer, the acoustic properties of the materials, and the laser pulse duration, a wide variety of pulse shapes and trains can be generated.