Sinclairdaniel6918

Parametric arrays have been widely investigated due to their high directivity in the low-frequency region when measuring the acoustic characteristics of materials, such as sound transmission and reflection properties, in the limited space of acoustic water tanks. Because a parametric array utilizes nonlinear interaction across the frequency components, nonlinear phenomena arise in both the acoustic medium and the hydrophone system. The unwanted nonlinear sound generated in the hydrophone and instrumentation is termed pseudo-sound. This study devised an experiment to measure the pseudo-sound without a truncator to assess the effect of the pseudo-sound in the near field. In order to separately measure the pseudo-sound, the hydrophone was placed close to the projector so that the pseudo-sound was dominantly generated. The method is based on the fact that, if we can suppress a parametric signal by minimizing the propagation path length in the medium, the resulting measured signal can be attributed to the pseudo-sound. The resultant signal levels were matched to the levels at corresponding distances based on the primary levels of a (separately conducted) distance-varying experiment. Finally, the suitability of the proposed technique was evaluated by comparing its results with the pseudo-sound levels measured using a truncator.Magnetic resonance (MR) imaging is becoming an established tool in capturing articulatory and physiological motion of the structures and muscles throughout the vocal tract and enabling visual and quantitative assessment of real-time speech activities. Although motion capture speed has been regularly improved by the continual developments in high-speed MR technology, quantitative analysis of multi-subject group data remains challenging due to variations in speaking rate and imaging time among different subjects. In this paper, a workflow of post-processing methods that matches different MR image datasets within a study group is proposed. Each subject's recorded audio waveform during speech is used to extract temporal domain information and generate temporal alignment mappings from their matching pattern. The corresponding image data are resampled by deformable registration and interpolation of the deformation fields, achieving inter-subject temporal alignment between image sequences. A four-dimensional dynamic MR speech atlas is constructed using aligned volumes from four human subjects. Similarity tests between subject and target domains using the squared error, cross correlation, and mutual information measures all show an overall score increase after spatiotemporal alignment. The amount of image variability in atlas construction is reduced, indicating a quality increase in the multi-subject data for groupwise quantitative analysis.The connections between the vortical and near-acoustic fields of three-stream, high-speed jets are investigated for the ultimate purpose of developing linear surface-based models for the noise source. Those models would be informed by low-cost, Reynolds-averaged Navier-Stokes (RANS) computations of the flow field. The study uses two triple-stream jets, one is coaxial and the other has eccentric tertiary flow that yields noise suppression in preferred directions. Large eddy simulations (LES) validate the RANS-based models for the convective velocity Uc of the noise-generating turbulent eddies. In addition, the LES results help define a "radiator surface" on which the jet noise source model would be prescribed. The radiator surface is located near the boundary between the rotational and irrotational fields and defined as the surface on which the Uc distribution, obtained from the space-time correlations of the pressure, matches that inferred from the RANS model. The edge of the mean vorticity field is nearly coincident with the radiator surface, which suggests a RANS-based criterion for locating this surface. The two-dimensional space-time correlations show how the asymmetry of the tertiary stream and the resulting thicker low-speed flow weakens the generation of acoustic disturbances from the vortical field.Transfer functions relating sound source strengths and the sound pressure at field points are important for sound field control. Recently, two modal domain methods for transfer function estimation have been compared using numerical simulations. Selleck BTK inhibitor One is the spatial harmonic decomposition (SHD) method, which models a sound field with a series of cylindrical waves; while the other is the singular value decomposition (SVD) method, which uses prior sound source location information to build an acoustic model and obtain basis functions for sound field modelling. In this paper, the feasibility of the SVD method using limited measurements to estimate transfer functions over densely spaced field samples within a target region is demonstrated experimentally. Experimental results with various microphone placements and system configurations are reported to demonstrate the geometric flexibility of the SVD method compared to the SHD method. It is shown that the SVD method can estimate broadband transfer functions up to 3099 Hz for a target region with a radius of 0.083 m using three microphones, and allow flexibility in system geometry. Furthermore, an application example of acoustic contrast control is presented, showing that the proposed method is a promising approach to facilitating broadband sound zone control with limited microphones.Whistle classification plays an essential role in studying the habitat and social behaviours of cetaceans. We obtained six categories of sweep whistles of two Tursiops aduncus individual signals using the passive acoustic mornitoring technique over a period of eight months in the Xiamen area. First, we propose a depthwise separable convolutional neural network for whistle classification. The proposed model adopts the depthwise convolution combined with the followed point-by-point convolution instead of the conventional convolution. As a result, it brings a better classification performance in sample sets with relatively independent features between different channels. Meanwhile, it leads to less computational complexity and fewer model parameters. Second, in order to solve the problem of an imbalance in the number of samples under each whistle category, we propose a random series method with five audio augmentation algorithms. The generalization ability of the trained model was improved by using an opening probability for each algorithm and the random selection of each augmentation factor within specific ranges. Finally, we explore the effect of the proposed augmentation method on the performance of our proposed architecture and find that it enhances the accuracy up to 98.53% for the classification of Tursiops aduncus whistles.The quality of polarization images is easy to be affected by the noise in the image acquired by a polarization camera. Consequently, a de-noising method optimized with a Pulse Coupled Neural Network (PCNN) for polarization images is proposed for a Field-Programmable Gate Array (FPGA)-based polarization camera in this paper, in which the polarization image de-noising is implemented using an adaptive PCNN improved by Gray Wolf Optimization (GWO) and Bi-Dimensional Empirical Mode Decomposition (BEMD). Unlike other artificial neural networks, PCNN does not need to be trained, but the parameters of PCNN such as the exponential decay time constant, the synaptic junction strength factor, and the inherent voltage constant play a critical influence on its de-noising performance. GWO is able to start optimization by generating a set of random solutions as the first population and saves the optimized solutions of PCNN. In addition, BEMD can decompose a complicated image into different Bi-Dimensional Intrinsic Mode Functions with local stabilized characteristics according to the input source image, and the decomposition result is able to lower the complexity of heavy noise image analysis. Moreover, the circuit in the polarization camera is accomplished by FPGA so as to obtain the polarization image with higher quality synchronously. These two schemes are combined to attenuate different types of noises and improve the quality of the polarization image significantly. Compared with the state-of-the-art image de-noising algorithms, the noise in the polarization image is suppressed effectively by the proposed optimized image de-noising method according to the indices of peak signal-to-noise ratio, standard deviation, mutual information, structural similarity, and root mean square error.The mid-infrared range is an important spectrum range where materials exhibit a characteristic response corresponding to their molecular structure. A free-electron laser (FEL) is a promising candidate for a high-power light source with wavelength tunability to investigate the nonlinear response of materials. Although the self-amplification spontaneous emission (SASE) scheme is not usually adopted in the mid-infrared wavelength range, it may have advantages such as layout simplicity, the possibility of producing a single pulse, and scalability to a short-wavelength facility. To demonstrate the operation of a mid-infrared SASE FEL system in an energy recovery linac (ERL) layout, we constructed an SASE FEL setup in cERL, a test facility of the superconducting linac with the ERL configuration. Despite the adverse circumstance of space charge effects due to the given boundary condition of the facility, we successfully established the beam condition at the undulators and observed FEL emission at a wavelength of 20 μm. The results show that the layout of cERL has the potential for serving as a mid-infrared light source.Double-sided silicon strip detectors (DSSDs) have been widely used in interplanetary exploration. In this study, the prototype readout electronics of a DSSD for space exploration is presented. It mainly includes a front-end readout module (FEM) and a data acquisition module (DAM). The FEM is responsible for acquiring the charge of the DSSD signals based on an application-specific integrated circuit and polarity inverter circuits. The DAM with a field programmable gate array is employed to perform online calculations of the position and energy as well as data packaging and transfer. Test results show that the electronics has dynamic ranges of 6-2500 and -6 to -2500 fC with an integral nonlinearity of no more than 0.5%, while the root-mean-square noise level is less than 1.9 fC. Joint tests with the DSSD indicate that a full width at half maximum energy resolution of 3.25% at 5.486 MeV and a position resolution of 1.19 mm were achieved.In ultrashort pulse laser applications, optical dispersion seriously affects the energy concentration in the laser pulse duration and lowers the peak power. Accordingly, this study proposes a rapid dispersion estimation mechanism to facilitate the compensation of optical dispersion using a closed-loop control system. In the proposed approach, the optical dispersion information of the laser pulse is estimated directly from a frequency-resolved optical gating trace without the need for an iterative pulse-retrieval algorithm. In particular, the group delay dispersion (GDD) is determined from frequency and delay marginals, which are related to the laser spectrum and intensity autocorrelation, respectively, using a simple lookup table approach. The accuracy of the estimated GDD results is confirmed via a comparison with the spectral phase distribution of the electric field reconstructed using the principal component generalized projections algorithm. It is shown that the computation time of the proposed direct estimation method is around 13 times faster than that of the traditional iterative algorithm.