Mechanism of Spectral Distortion for Real-Time Crack Propagation on Aluminum Alloy Structure

This study investigates four characteristic damage mechanisms of fiber Bragg grating (FBG) sensors, with fatigue crack propagation in aluminum alloy. The multipeak wavelength distinguish algorithm was developed for FBG spectrum quantitative analysis. The results distinguish a subordinate peak skewing significantly, associated with strain patterns along the FBG, corresponding to various crack lengths. For parallel bonded direction grating, the subordinate peak skewing appears at the strain pattern transition region. This is located at the ratio 32%-34% of crack length lying in the crack tip. Meanwhile, the four damage characteristics correspond to subordinate peak skewing. When the strain is distributed along the grating, spectral distortion occurs. In this region, the cubic strain pattern determines the shorter wavelength location of subordinate peaks. This corresponds to the 15%-17% ratio of crack length lying in the grating, causing spectral oscillations.

Influence of audibility and distortion on the recognition of reverberant speech for children and adults with hearing aid amplification

Background: Adults and children with sensorineural hearing loss (SNHL) have trouble understanding speech in rooms with reverberation when using hearing aid amplification. While the use of amplitude compression signal processing in hearing aids may contribute to this difficulty, there is conflicting evidence on the effects of amplitude compression settings on speech recognition. Less clear is the effect of a fast release time for adults and children with SNHL when using compression ratios derived from a prescriptive procedure. Purpose: To determine whether release time impacts speech recognition in reverberation for children and adults with SNHL and to determine if these effects of release time and reverberation can be predicted using indices of audibility or temporal and spectral distortion. Research Design: A quasi-experimental cohort study. Participants used a hearing aid simulator set to the Desired Sensation Level algorithm m[i/o] for three different amplitude compression release times. Reverberation was simulated using three different reverberation times. Participants: Participants were 20 children and 16 adults with SNHL. Data Collection and Analyses: Participants were seated in a sound-attenuating booth and then nonsense syllable recognition was measured. Predictions of speech recognition were made using indices of audibility, temporal distortion, and spectral distortion and the effects of release time and reverberation were analyzed using linear mixed models. Results: While nonsense syllable recognition decreased in reverberation; release time did not significantly affect nonsense syllable recognition. Participants with lower audibility were more susceptible to the negative effect of reverberation on nonsense syllable recognition. Conclusions: We have extended previous work on the effects of reverberation on aided speech recognition to children with SNHL. Variations in release time did not impact the understanding of speech. An index of audibility best predicted nonsense syllable recognition in reverberation and, clinically, these results suggest that patients with less audibility are more susceptible to nonsense syllable recognition in reverberation.

Serial GANs: A Feature-Preserving Heterogeneous Remote Sensing Image Transformation Model

In recent years, the interpretation of SAR images has been significantly improved with the development of deep learning technology, and using conditional generative adversarial nets (CGANs) for SAR-to-optical transformation, also known as image translation, has become popular. Most of the existing image translation methods based on conditional generative adversarial nets are modified based on CycleGAN and pix2pix, focusing on style transformation in practice. In addition, SAR images and optical images are characterized by heterogeneous features and large spectral differences, leading to problems such as incomplete image details and spectral distortion in the heterogeneous transformation of SAR images in urban or semiurban areas and with complex terrain. Aiming to solve the problems of SAR-to-optical transformation, Serial GANs, a feature-preserving heterogeneous remote sensing image transformation model, is proposed in this paper for the first time. This model uses the Serial Despeckling GAN and Colorization GAN to complete the SAR-to-optical transformation. Despeckling GAN transforms the SAR images into optical gray images, retaining the texture details and semantic information. Colorization GAN transforms the optical gray images obtained in the first step into optical color images and keeps the structural features unchanged. The model proposed in this paper provides a new idea for heterogeneous image transformation. Through decoupling network design, structural detail information and spectral information are relatively independent in the process of heterogeneous transformation, thereby enhancing the detail information of the generated optical images and reducing its spectral distortion. Using SEN-2 satellite images as the reference, this paper compares the degree of similarity between the images generated by different models and the reference, and the results revealed that the proposed model has obvious advantages in feature reconstruction and the economical volume of the parameters. It also showed that Serial GANs have great potential in decoupling image transformation.

Orthognathic speech pathology: impacts of Class III malocclusion on speech

Summary Introduction Patients with dentofacial disharmonies (DFDs) seek orthodontic care and orthognathic surgery to address issues with mastication, esthetics, and speech. Speech distortions are seen 18 times more frequently in Class III DFD patients than the general population, with unclear causality. We hypothesize there are significant differences in spectral properties of stop (/t/ or /k/), fricative (/s/ or /ʃ/), and affricate (/tʃ/) consonants and that severity of Class III disharmony correlates with the degree of speech abnormality. Methods To understand how jaw disharmonies influence speech, orthodontic records and audio recordings were collected from Class III surgical candidates and reference subjects (n = 102 Class III, 62 controls). A speech pathologist evaluated subjects and recordings were quantitatively analysed by Spectral Moment Analysis for frequency distortions. Results A majority of Class III subjects exhibit speech distortions. A significant increase in the centroid frequency (M1) and spectral spread (M2) was seen in several consonants of Class III subjects compared to controls. Using regression analysis, correlations between Class III skeletal severity (assessed by cephalometric measures) and spectral distortion were found for /t/ and /k/ phones. Conclusions Class III DFD patients have a higher prevalence of articulation errors and significant spectral distortions in consonants relative to controls. This is the first demonstration that severity of malocclusion is quantitatively correlated with the degree of speech distortion for consonants, suggesting causation. These findings offer insight into the complex relationship between craniofacial structures and speech distortions.

Designs, Experiments, and Applications of Multichannel Structures for Hearing Aids

The structures of common multichannel processing for hearing aids include equal bandwidth (BW) finite impulse response (FIR) filter bank, nonuniform BW FIR filter bank, and fast Fourier transform (FFT) plus inverse FFT (IFFT). This paper analyzes their operation principles, indicates the design methods by means of MATLAB R2018b resources, and describes the main characteristics: synthetical ripple, bank filters’ group delays, and individual filter sidelobe attenuation. Three schemes are proposed: equal BW sixteen-filter bank, logarithmic BW eight-filter bank, and 128-point FFT plus IFFT with overlap-add operation. To build the experimental modules, we introduce the settings of spectrum scopes, the acquirement of realistic speech and noises, and the gain enhancing/reducing needs of hearing aid features; the characteristics of synthetical outputs confirm precise control ability of the multichannel modules and differences between the three schemes. Subsequently, this paper illustrates two applications of the multichannel structures in hearing aids, the equal BW sixteen-filter bank with spectral subtraction (SS) for an artificial intelligence (AI) noise reduction (NR) and 128-point FFT plus IFFT spectral distortion removal for a directional microphone (DM). In Amy’s speech mixed with ringing, milk steamer, and strong wind noises separately, the SS processor improves signal-noise-ratio (SNR) by 6.5 to 15.9 dB. By measuring waveforms and spectra at the DM input and output, the DM system seamlessly removes the spectral distortion.

A Distributed Fusion Framework of Multispectral and Panchromatic Images Based on Residual Network

Remote sensing images have been widely applied in various industries; nevertheless, the resolution of such images is relatively low. Panchromatic sharpening (pan-sharpening) is a research focus in the image fusion domain of remote sensing. Pan-sharpening is used to generate high-resolution multispectral (HRMS) images making full use of low-resolution multispectral (LRMS) images and panchromatic (PAN) images. Traditional pan-sharpening has the problems of spectral distortion, ringing effect, and low resolution. The convolutional neural network (CNN) is gradually applied to pan-sharpening. Aiming at the aforementioned problems, we propose a distributed fusion framework based on residual CNN (RCNN), namely, RDFNet, which realizes the data fusion of three channels. It can make the most of the spectral information and spatial information of LRMS and PAN images. The proposed fusion network employs a distributed fusion architecture to make the best of the fusion outcome of the previous step in the fusion channel, so that the subsequent fusion acquires much more spectral and spatial information. Moreover, two feature extraction channels are used to extract the features of MS and PAN images respectively, using the residual module, and features of different scales are used for the fusion channel. In this way, spectral distortion and spatial information loss are reduced. Employing data from four different satellites to compare the proposed RDFNet, the results of the experiment show that the proposed RDFNet has superior performance in improving spatial resolution and preserving spectral information, and has good robustness and generalization in improving the fusion quality.