For the unique dual-channel sound speed profiles of the Canadian Basin and the Chukchi Plateau in the Arctic, based on the propagation characteristics of refracted normal modes under dual-channel sound speed profiles, an inversion method using refracted normal modes for dual-channel sound speed profiles is proposed. This method proposes a dual-parameter representation method for dual-channel sound speed profiles, tailored to the characteristics of dual-channel sound speed profiles. A dispersion structure extraction method is proposed for the dispersion structure characteristics of refracted normal modes under dual-channel sound speed profiles. Combining the parameter representation method of sound speed profiles and the dispersion structure extraction method, an inversion method for dual-channel sound speed profiles is proposed. For the common horizontal variation of sound speed profiles in long-distance acoustic propagation, a method for inverting horizontally varying dual-channel sound speed profiles is proposed. Finally, this article verifies the effectiveness of the dual-channel sound speed profile inversion method using the Arctic low-frequency long-range acoustic propagation experiment. Compared with previous sound speed profile inversion methods, the method proposed in this article has the advantages of fewer inversion parameters and faster inversion speed. It can be implemented using only a single hydrophone passively receiving random air gun signals, and it also solves the inversion problem of horizontal variation of sound speed profiles. It has significant advantages such as low cost, easy deployment, and fast computation speed.
How would the sound in a studio change with a carpeted floor and acoustic tiles on the walls? We introduce the task of material-controlled acoustic profile generation, where, given an indoor scene with specific audio-visual characteristics, the goal is to generate a target acoustic profile based on a user-defined material configuration at inference time. We address this task with a novel encoder-decoder approach that encodes the scene's key properties from an audio-visual observation and generates the target Room Impulse Response (RIR) conditioned on the material specifications provided by the user. Our model enables the generation of diverse RIRs based on various material configurations defined dynamically at inference time. To support this task, we create a new benchmark, the Acoustic Wonderland Dataset, designed for developing and evaluating material-aware RIR prediction methods under diverse and challenging settings. Our results demonstrate that the proposed model effectively encodes material information and generates high-fidelity RIRs, outperforming several baselines and state-of-the-art methods.
Thompson David J., Elliott Stephen J., Morfey Chris L.
et al.
The Institute of Sound and Vibration Research (ISVR) at the University of Southampton was founded in 1963 from the Aeronautics Department. It grew rapidly into a leading centre for noise and vibration, combining research, teaching and consultancy. Although the initial focus was on the noise from aircraft and on their vibration-induced structural fatigue, there was already a recognition of the wider issues of sound in society and its subjective and medical effects. Consequently, the research interests of the ISVR quickly expanded to include aeroacoustics, automotive noise, structural dynamics, vibroacoustics, human responses to sound and vibration, data analysis and signal processing, active control, underwater acoustics and railway noise and vibration. The ISVR was a pioneer of university-industry collaboration, having many faculty positions that were supported by industrial funding as well as a strong consultancy activity. Unusual for an engineering department, teaching and research in clinical audiology featured strongly, and led to the establishment of a Cochlear Implant Centre in 1990. The paper gives a review of achievements of the ISVR in the 20th Century, identifying some of the main researchers and engineers who have inspired and guided its activities.
Acoustics in engineering. Acoustical engineering, Acoustics. Sound
Accurately localizing 3D sound sources and estimating their semantic labels -- where the sources may not be visible, but are assumed to lie on the physical surface of objects in the scene -- have many real applications, including detecting gas leak and machinery malfunction. The audio-visual weak-correlation in such setting poses new challenges in deriving innovative methods to answer if or how we can use cross-modal information to solve the task. Towards this end, we propose to use an acoustic-camera rig consisting of a pinhole RGB-D camera and a coplanar four-channel microphone array~(Mic-Array). By using this rig to record audio-visual signals from multiviews, we can use the cross-modal cues to estimate the sound sources 3D locations. Specifically, our framework SoundLoc3D treats the task as a set prediction problem, each element in the set corresponds to a potential sound source. Given the audio-visual weak-correlation, the set representation is initially learned from a single view microphone array signal, and then refined by actively incorporating physical surface cues revealed from multiview RGB-D images. We demonstrate the efficiency and superiority of SoundLoc3D on large-scale simulated dataset, and further show its robustness to RGB-D measurement inaccuracy and ambient noise interference.
M. P. Peiró-Torres, M. J. Parrilla Navarro, M. Ferri
et al.
This article presents the use of advanced tools applied to the design of devices that can solve specific acoustic problems, improving the already existing devices based on classic technologies. Specifically, we have used two different configurations of a material called Sonic Crystals, which is formed by arrays of acoustic scatterers, to obtain acoustic screens with high diffusion properties by means of an optimization process. This design procedure has been carried out using a multiobjective evolutionary algorithm along to an acoustic simulation model developed with the numerical method called Finite Difference Time Domain (FDTD). The results obtained are discussed in terms of both the acoustic performance and the robustness of the devices achieved.
We discuss the properties of the two-flavor quark-meson diquark (QMD) model as a renormalizable low-energy model for QCD in the 2SC phase of QCD. The effective degrees of freedom are the mesons (sigma and pions), quarks, and diquarks. Some of the parameters of the model can be determined by expressing them in terms of the vacuum meson masses and the pion decay constant using the on-shell renormalization scheme. The remaining parameters are considered free, although they in principle can be calculated from QCD. The thermodynamic potential is calculated in a mean-field approximation taking only quark loops into account. In this approximation, we derive a set of renormalization group equations for the running masses and couplings. The solutions to these equations are used to improve the thermodynamic potential $Ω$ and thereby thermodynamic quantities. Four parameter sets are chosen and the phase diagram in the $\barμ$--$T$ plane is obtained (with $\barμ={1\over3}μ_B$). We also calculate the speed of sound $c_s$ as a function of $\barμ$ at vanishing temperature. For large values of $\barμ$, the speed of sound approaches the conformal limit $c_s={1\over\sqrt{3}}$ from above, in disagreement with perturbative calculations, but agreement with hard-dense-loop resummed perturbation theory.
Madeleine E. Yu, Natalie Fecher, Elizabeth K. Johnson
Vocal recognition of socially relevant conspecifics is an important skill throughout the animal kingdom. Human infants recognize their own mother at birth, and they distinguish between unfamiliar female talkers by 4.5 months of age. Can 4.5-month-olds also distinguish between unfamiliar male talkers? To date, no adequately powered study has addressed this question. Here, a visual fixation procedure demonstrates that, unlike adults, 4.5-month-olds (N = 48) are worse at telling apart unfamiliar male voices than they are at telling apart unfamiliar female voices. This result holds despite infants' equal attentiveness to unfamiliar male and female voices.
This study examined the effects of high-pressure homogenization (HPH) and ultrasonication pre-treatment on the structural and physicochemical properties of proteins extracted from defatted Nannochloropsis Oceania biomass (DNOB). HPH treatment was found to enhance the solubility of protein extracted from DNOB compared to ultrasound, where samples pretreated with three passes (3P) of HPH exhibited lower solubility than two passes (2P). The morphology of extracted samples was visualized by scanning electron microscopy, which HPH pre-treatment, especially with more passes, were able to breakdown DNOB into fragments. Alternatively, more holes were displayed on the surface of the extracts pretreated with ultrasound especially when higher amplitude applied. The particle size of extracts from HPH3P (129.5 µm) significant dropped from HPH2P (314.25 µm), where samples pretreated with ultrasound at 20 % amplitude (US20) also decreased in particle size compared to 40 % amplitude (US40), from 115.25 µm to 78.22 µm. Protein flexibility of DNOB extracts were enhanced by both HPH2P and HPH3P but decreased for ultrasound samples. β-sheets were found to be the most abundant protein secondary structure for all samples, where samples treated with HPH3P contained the highest percentage of β-sheets (72 %) than control, HPH2P, ultrasonication at 20 and 40 % amplitude (52–62 %). The high percentage of β-sheets found in HPH3P sample also contributed to its outstanding emulsifying properties which stood out among all, especially at concentrations over 1 mg/ml. Results obtained from this study helped to direct the application of DNOB extracts as functional food ingredient for future food innovation.
AbstractTo understand sound, noise, and their effects on health, we must quantify sound using the concept of ‘acoustics’. This chapter provides an introduction to acoustics and outlines different ways that acousticians measure, predict and quantify sound to understand its effects. The chapter also contains a glossary of acoustic terminology that is used throughout this book and can be referred to when reading any of the other chapters in the book.
The dual-channel sound speed profiles of the Chukchi Plateau and the Canadian Basin have become current research hotspots due to their excellent low-frequency sound signal propagation ability. Previous research has mainly focused on using sound propagation theory to explain the changes in sound signal energy. This article is mainly based on the theory of normal modes to study the fine structure of low-frequency wide-band sound propagation dispersion under dual-channel sound speed profiles. In this paper, the problem of the intersection of normal mode dispersion curves caused by the dual-channel sound speed profile (SSP) has been explained, the blocking effect of seabed terrain changes on dispersion structures has been analyzed, and the normal modes has been separated by using modified warping operator. The above research results have been verified through a long-range seismic exploration experiment at the Chukchi Plateau. At the same time, based on the acoustic signal characteristics in this environment, two methods for estimating the distance of sound sources have been proposed, and the experiment data at sea has also verified these two methods.
This paper proposes an unsupervised anomalous sound detection method using sound separation. In factory environments, background noise and non-objective sounds obscure desired machine sounds, making it challenging to detect anomalous sounds. Therefore, using sounds not mixed with background noise or non-purpose sounds in the detection system is desirable. We compared two versions of our proposed method, one using sound separation as a pre-processing step and the other using separation-based outlier exposure that uses the error between two separated sounds. Based on the assumption that differences in separation performance between normal and anomalous sounds affect detection results, a sound separation model specific to a particular product type was used in both versions. Experimental results indicate that the proposed method improved anomalous sound detection performance for all Machine IDs, achieving a maximum improvement of 39%.
Parboiling is gaining increasing attention as it can enhance the head rice yield (HRY) and nutritional quality of non-pigmented rice. The traditional parboiling process with high-temperature immersion requires a long immersion period and results in hard texture of cooked parboiled black rice (PBR), which may be addressed by ultrasound-assisted immersion. In this study, we evaluated the effect of power, time and temperature of ultrasonic immersion on the HRY, texture profile and nutritional quality of PBR. Proper ultrasound-assisted immersion could increase the HRY by about 20% and the GABA content by up to 133%, as well as reduce the arsenic and cadmium content by up to 61% and 79% relative to untreated black rice (UBR), respectively. Moreover, it could increase the content of essential minerals such as calcium, iron and zinc to some extent, and free and bound polyphenols, despite of a certain loss of anthocyanins. It could also improve the palatability of cooked rice. Furthermore, response surface experiments based on the Box-Behnken design were performed to obtain and validate the optimal conditions of ultrasound-assisted immersion (540 W, 45 min, 57 °C). On this basis, morphological changes might be one reason for the improved HRY, nutrition and texture of PBR compared with those of UBR, namely the disappearance of cracks near the aleurone layer and formation of new cracks in the interior of rice.
In the present study, experiments of membraneless alkaline sono-electrolysis are combined to a mathematical model describing the performance of a sono-electrolyzer based on the electrochemical resistances and overpotentials (activation, Ohmic and concentration) and the oscillation of the acoustic cavitation bubble, and its related sono-physical and sonochemical effects, as a single unit and within population. The study aims to elucidate the mechanism of action of acoustic cavitation when coupled to alkaline electrolysis, using a membraneless H-cell configuration and indirect continuous sonication (40 kHz, 60 We). The calorimetric characterization constituted the bridge between experimental results and the numerical and simulation approach, while the quantification of the rate of produced hydrogen both experimentally and numerically highlighted the absence of the contribution of sonochemistry, and explained the role of ultrasounds by the action of shockwaves and microjets. Finally, the energetic sono-physical approach allowed an estimation of the predominance of the shockwaves and microjets effects according to the bubble size distribution within the population corresponding to the acoustic conditions of the study. The resulting macroscopic effect in sono-electrolysis process has been assessed considering the induced degassing. A reduction in the fraction of electrodes’ coverage by bubbles from 76% to 42% has been recorded, corresponding to a decrease of 7.2% in Ohmic resistance and 62.35% in bubble resistance.
This paper proposes a benchmark of submissions to Detection and Classification Acoustic Scene and Events 2021 Challenge (DCASE) Task 4 representing a sampling of the state-of-the-art in Sound Event Detection task. The submissions are evaluated according to the two polyphonic sound detection score scenarios proposed for the DCASE 2021 Challenge Task 4, which allow to make an analysis on whether submissions are designed to perform fine-grained temporal segmentation, coarse-grained temporal segmentation, or have been designed to be polyvalent on the scenarios proposed. We study the solutions proposed by participants to analyze their robustness to varying level target to non-target signal-to-noise ratio and to temporal localization of target sound events. A last experiment is proposed in order to study the impact of non-target events on systems outputs. Results show that systems adapted to provide coarse segmentation outputs are more robust to different target to non-target signal-to-noise ratio and, with the help of specific data augmentation methods, they are more robust to time localization of the original event. Results of the last experiment display that systems tend to spuriously predict short events when non-target events are present. This is particularly true for systems that are tailored to have a fine segmentation.
Traditional sound diffusers are quasi-random phase gratings attached to reflecting surfaces whose purpose is to augment the spatiotemporal incoherence of the acoustic field scattered from reflective surfaces. This configuration allows one to cover a large reflecting surface by periodically tiling the diffuser unit cells to cover a large area while reducing undesirable specular reflection for incident plane waves. However, the periodic arrangement of the unit cells leads to coherent constructive and destructive interference in the scattered field in some directions which is undesirable for achieving acoustic diffusivity. The spatial uniformity of acoustic energy scattered from conventional diffusers constructed in this way is a fundamental limitation of the traditional approach which is not easily overcome when one wishes to cover large reflecting surfaces. In this work, we investigate spatiotemporal modulation of the surface acoustic admittance of an acoustic diffuser as a new approach to improve the sound diffusion. We develop a semi-analytical model that employs Fourier series expansion to determine the scattered sound field from a surface admittance consisting of a quadratic residue diffuser (QRD) design whose individual well admittances are modulated with a traveling wave with modulation frequency, $ω_{\mrm{m}}$, amplitude, $Y_\mrm{m}$, and a wavenumber that matches the unit cell length, $Λ$. We observe significant improvement in diffusion performance due to the fact that the spatiotemporal modulation scatters sound into additional frequency--wavenumber pairs associated with harmonics of the modulation frequency and their diffraction orders. The semi-analytical model results are verified using time-domain finite element model.
Purpose The Reflective Middleware for Acoustic Management (ReM-AM), based on the Middleware for Cloud Learning Environments (AmICL), aims to improve the interaction between users and agents in a Smart Environment (SE) using acoustic services, in order to consider the unpredictable situations due to the sounds and vibrations. The middleware allows observing, analyzing, modifying and interacting in every state of a SE from the acoustics. This work details an extension of the ReM-AM using the ontology-driven architecture (ODA) paradigm for acoustic management.Design/methodology/approach This work details an extension of the ReM-AM using the ontology-driven architecture (ODA) paradigm for acoustic management. In this paper are defined the different domains of knowledge required for the management of the sounds in SEs, which are modeled using ontologies.Findings This work proposes an acoustics and sound ontology, a service-oriented architecture (SOA) ontology, and a data analytics and autonomic computing ontology, which work together. Finally, the paper presents three case studies in the context of smart workplace (SWP), ambient-assisted living (AAL) and Smart Cities (SC).Research limitations/implications Future works will be based on the development of algorithms for classification and analysis of sound events, to help with emotion recognition not only from speech but also from random and separate sound events. Also, other works will be about the definition of the implementation requirements, and the definition of the real context modeling requirements to develop a real prototype.Practical implications In the case studies is possible to observe the flexibility that the ReM-AM middleware based on the ODA paradigm has by being aware of different contexts and acquire information of each, using this information to adapt itself to the environment and improve it using the autonomic cycles. To achieve this, the middleware integrates the classes and relations in its ontologies naturally in the autonomic cycles.Originality/value The main contribution of this work is the description of the ontologies required for future works about acoustic management in SE, considering that what has been studied by other works is the utilization of ontologies for sound event recognition but not have been expanded like knowledge source in an SE middleware. Specifically, this paper presents the theoretical framework of this work composed of the AmICL middleware, ReM-AM middleware and the ODA paradigm.
To produce an edible film with high mechanical and physicochemical properties, Tuna skin collagen-chitosan (TSC-CTS) composite films were prepared by incorporating ultrasound (UT) and pomegranate polyphenols including gallic acid (GA), tannic acid (TA), and ellagic acid (EA), respectively. The tensile strength and the DPPH scavenging activity of the GA-UT-TSC-CTS film (ultrasound frequency of 28 ± 0.5 kHz, power of 100 W/L, sweep frequency cycle of 100 ms, duty ratio of 77% and time of 10 min; GA concentration of 1.0 g/L and reaction time of 10 min) were increased by 47.03% and 24.16 folds, respectively compared to the control (TSC-CTS film). Meanwhile, light transmittance and water vapor permeability of the GA-UT-TSC-CTS film were decreased by 29.26% and 15.70%, respectively. These positive modification results were attributed to the altered structure during the film formation process, which were verified by Fourier transform infrared spectroscopy (FTIR), circular dichroism (CD), X-ray diffraction (XRD), and thermogravimetry results. Moreover, the GA-UT-TSC-CTS film possessed moderate thermal stability and color indexes and improved antibacterial activity. The antibacterial effect of the film against Bacillus subtilis was the highest, followed by Escherichia coli, Listeria monocytogenes, and Staphylococcus aureus. Overall, the combination modification of gallic acid and ultrasound was an efficient modification method to improve the mechanical, antioxidant, and antibacterial properties of edible TSC-CTS films.
We theoretically propose a method to achieve an optimum absorbing material through a modulus-near-zero (MNZ) metamaterial immersed in air or water with a change in slit width part. The destructive interference has paved the way to achieve perfect absorption (PA). Depending upon theoretical analysis, an acoustic metamaterial (AMMs) that supports resonance with a monopole (140 Hz) is developed to construct a low-frequency sound-absorbing technology. The dissipative loss effect can be by attentively controlling onto slit width to achieve perfect absorption. When there are thin slit width and visco-thermal losses in the structure, it is observed that they lead to high absorption. We use finite element simulations via COMSOL Multiphysics software to theoretical measurement in impedance tube and show the influence of structural parameters in both mediums. The results are of extraordinary correspondence at low frequency to achieve optimum perfect absorption (99%). That might support AMMs to actual engineering-related applications in the process of mitigating noise, slow sound trapping, notch filtering, energy conversion, and time reversal technology.