Reduce Noise Levels Research Articles

Hearing Aid apps: are they safe, practical and beneficial for children and teens in challenging situations?

An adult version of an app giving users the control over the level of the volume, microphone directionality and noise reduction was adapted for children. The main purpose of this study was to evaluate the effect of changes made to microphone directionality and noise reduction in the myPhonak Junior (the app) on Speech intelligibility in challenging listening environments in children and teens. The randomized, non-blinded interventional study with a single group of subjects involved two study visits with a home trial in-between. In the final study session speech assessment in noise was conducted in three different, randomly assigned conditions: default mode (Autosense Sky OS), preffered (self-adjusted) and the extreme condition. Questionnaire based assessment was conducted to assess the subjective benefit of using the app in different daily situations. The best scores (speech results in noise) were achieved with the preferred setting and the default Autosense Sky OS setting was significantly better than the extreme setting. The self-reported benefit through the questionnaire indicates significantly better result when adjusting the hearing aids through the app. The app is an easy-to-use way of controlling the level of noise reduction and the beam forming for children 11 years and older. It has the potential to help customizing the hearing aids beyond the default setting and helping to improve speech understanding in noise.

Tunnel oxide passivating contact enabled by polysilicon on ultra-thin SiO2 for advanced silicon radiation detectors

Conventional silicon junction detectors encounter significant carrier recombination within the heavily doped p+ and n+ layers, as well as beneath the metal contact regions, creating the so-called “dead layers”, especially on the detector side. In this study, we present the tunnel oxide passivating contact with doped polysilicon on oxide, which demonstrates exceptional surface passivation and carrier selectivity. The key innovation lies in an ultra-thin (~ 1.5 nm) interfacial oxide layer that facilitates efficient majority carrier transportation via tunneling while effectively block minority carriers. Remarkably low saturation current densities, ranging from 5 to 10 fA/cm2 even with the metal contact, underscore the superiority of both n-type and p-type tunnel oxide passivating contacts. In contrast, conventional p–n junction or high-low junction exhibit saturation current densities ranging from 10 to 90 fA/cm2 in the studied p+ and n+ layers with surface passivation schemes due to Auger recombination and surface recombination, and 1000–6000 fA/cm2 with metal contacts due to intense metal-induced recombination at the interface. These findings indicate the potential and superiority of implementing n-type tunnel oxide passivating contact on the detector side and p-type contact on the back side for advanced silicon radiation detectors. This approach would enable thorough collection of generated charge carriers along the track of incident ionizing radiation particles, leading to improved energy resolution and reduced noise levels.

Utility of Echo-planar Imaging with Compressed Sensitivity Encoding (EPICS) in the Evaluation of Small Breast Cancers Using Diffusion-weighted Imaging with Background Suppression (DWIBS).

High b-value acquisition and diffusion-weighted imaging with background suppression (DWIBS) are desirable in high-specificity breast cancer diagnosis on non-contrast-enhanced magnetic resonance imaging; however, this inherently results in a lower signal-to-noise ratio (SNR). Compressed sensitivity encoding (C-SENSE), which combines SENSE with compressed sensing, improves the SNR by reducing noise. Recent technological improvements allow us to incorporate this acceleration technique into echo-planar imaging, called echo-planar imaging with C-SENSE (EPICS). This study aimed to compare image quality and reliability of the apparent diffusion coefficient (ADC) between DWIBS obtained using SENSE and EPICS in patients with small breast cancers. Thirty-seven patients with pathologically confirmed breast cancer underwent DWIBS, and images were reconstructed using both conventional SENSE (SENSE-DWIBS) and EPICS (EPICS-DWIBS). Two board-certified radiologists independently evaluated lesion conspicuity (LC) and noise using a 5-point grading scale. The same 2 radiologists independently measured SNR, contrast-to-noise ratio (CNR), and the mean cancer ADC. The Pearson coefficient and Bland-Altman plot were applied to assess the accuracy of ADCs. LC scores were higher with EPICS than with SENSE, reaching significance for one reviewer but not the other reviewer. Noise ratings on visual evaluation were significantly lower with EPICS than with SENSE (P < 0.001 for both reviewers). SNR was significantly higher with EPICS than with SENSE (P < 0.005 for both reviewers). CNR was significantly higher with EPICS than with SENSE (P < 0.001 for both reviewers). Bland-Altman plots of cancer ADCs using EPICS-DWIBS and SENSE-DWIBS showed excellent concordance, with a bias of 0.026 × 10-3 mm2/s and limits of agreement ranging 0.054 × 10-3 mm2/s; the Pearson's correlation coefficient was 0.997 (P < 0.0001). EPICS enhances breast DWIBS image quality, with improved SNR and CNR and reduced noise levels. The ADCs of breast cancers obtained using EPICS were almost perfectly correlated with those obtained using conventional SENSE.

Landing force reveals new form of motion-induced sound camouflage in a wild predator.

Predator-prey arms races have led to the evolution of finely tuned disguise strategies. While the theoretical benefits of predator camouflage are well established, no study has yet been able to quantify its consequences for hunting success in natural conditions. We used high-resolution movement data to quantify how barn owls (Tyto alba) conceal their approach when using a sit-and-wait strategy. We hypothesized that hunting barn owls would modulate their landing force, potentially reducing noise levels in the vicinity of prey. Analysing 87,957 landings by 163 individuals equipped with GPS tags and accelerometers, we show that barn owls reduce their landing force as they approach their prey, and that landing force predicts the success of the following hunting attempt. Landing force also varied with the substrate, being lowest on man-made poles in field boundaries. The physical environment, therefore, affects the capacity for sound camouflage, providing an unexpected link between predator-prey interactions and land use. Finally, hunting strike forces in barn owls were the highest recorded in any bird, relative to body mass, highlighting the range of selective pressures that act on landings and the capacity of these predators to modulate their landing force. Overall, our results provide the first measurements of landing force in a wild setting, revealing a new form of motion-induced sound camouflage and its link to hunting success.

Landing force reveals new form of motion-induced sound camouflage in a wild predator

Predator-prey arms races have led to the evolution of finely tuned disguise strategies. While the theoretical benefits of predator camouflage are well established, no study has yet been able to quantify its consequences for hunting success in natural conditions. We used high-resolution movement data to quantify how barn owls (Tyto alba) conceal their approach when using a sit-and-wait strategy. We hypothesized that hunting barn owls would modulate their landing force, potentially reducing noise levels in the vicinity of prey. Analysing 87,957 landings by 163 individuals equipped with GPS tags and accelerometers, we show that barn owls reduce their landing force as they approach their prey, and that landing force predicts the success of the following hunting attempt. Landing force also varied with the substrate, being lowest on man-made poles in field boundaries. The physical environment, therefore, affects the capacity for sound camouflage, providing an unexpected link between predator-prey interactions and land use. Finally, hunting strike forces in barn owls were the highest recorded in any bird, relative to body mass, highlighting the range of selective pressures that act on landings and the capacity of these predators to modulate their landing force. Overall, our results provide the first measurements of landing force in a wild setting, revealing a new form of motion-induced sound camouflage and its link to hunting success.

Flow-induced noise and vibration in axial fan: a case study

AbstractReducing axial fan noise is crucial in residential, commercial, and industrial applications. This study explores how attaching different add-on designs to axial fans reduces aerodynamic noise. Eight design cases were examined, including extending the outlet and inlet ducts, using Chevron nozzles, placing internal spherical balls in staggered and straight patterns, applying a wavy inner wall treatment, and combining some of these nozzle designs. CFD and acoustic analyses were performed using Ansys Fluent 2022 R1. Noise reduction was measured at the nozzle outlet in each design case. All nozzle modifications reduced noise levels, with noise reductions ranging from 3 to 10% at the blade tip and 26–55% at the outlet. As an add-on to existing fan cases, the design cases investigated in this study can potentially improve the acoustic environment in various settings. The findings of this study can contribute to the development of quieter axial fans.

Design optimization of floor plan for public housing buildings in Hong Kong with consideration of natural ventilation, noise, and daylighting

Indoor environmental quality plays a crucial role in determining the overall quality of life. This study aims to develop a design optimization approach for the floor plan of public housing buildings with modular flat design in Hong Kong, with focus on enhancing natural ventilation, reducing noise levels, and improve daylighting conditions. The evaluation of these environmental factors was conducted using deep neural network models and a mathematically based Calculation of Road Traffic Noise model. A general floor plan representation was developed for three- and four-winged structures of public housing buildings. An optimization approach utilizing Bayesian optimization was applied to three studied cases: Hung Shing House, Hung Hei House, and Cheung Tai House. The optimization process resulted in an average 41.5 % improvement in average natural ventilation rate. The optimized building shapes effectively served as noise barriers, leading to an average reduction of 20 % in average noise levels. The existing window configurations of each unit type under the modular flat design already provided sufficient daylighting, resulting in only a minor improvement from the optimization process.

Enhanced nonlinear active noise control: A novel approach using brain storm optimization algorithm

Active Noise Control (ANC) systems play a crucial role in reducing unwanted noise in various settings. Traditional ANC methods, like the Filtered-x Least Mean Squares (FxLMS) algorithm, are effective in linear noise scenarios. However, they often struggle with more nonlinear and complex noise patterns. This paper introduces a novel approach using the brain storm optimization (BSO) algorithm in nonlinear ANC systems, which represents a significant departure from conventional techniques. The BSO algorithm, inspired by human brainstorming processes, excels in addressing the complexities of nonlinear noise by incorporating principles, such as delayed evaluation, free imagination, quantity and quality, and comprehensive improvement. By combining the BSO algorithm with an Extended Kalman Filter (EKF), a new ANC system is proposed that can adapt to a wide range of noise types with improved speed and accuracy. Experimental results showcase the superior performance of the BSO algorithm, achieving an impressive noise reduction of up to 48 dB (dB) in a 500Hz sinusoidal noise scenario, with a convergence time as fast as 0.01 s, outperforming the FxLMS algorithm by a significant margin. Moreover, in complex environments with multi-frequency and random noise, the BSO algorithm consistently demonstrates better noise reduction and quicker convergence, reducing noise levels by up to 27 dB within 0.001 s. The innovative use of the BSO algorithm in ANC systems not only enhances noise reduction capabilities, especially for nonlinear and complex noise signals, but also improves convergence times, paving the way for future advancements in ANC technologies.

Investigation of methods to estimate NLR of residential structures for airport sound insulation programs

This paper investigates methods to estimate outdoor-to-indoor noise level reduction (NLR) for single family residential structures before and after the installation of sound insulation treatments to improve the structure's NLR. Acoustical modeling results and Outdoor-Indoor Transmission Class (OITC) ratings are evaluated in the context of treatment design for airport sound insulation programs and assessment of soundproofing product performance. Overall, post-construction NLR predictions are observed to have a high degree of accuracy when the results are generated using a combination of pre-construction measurement data and acoustical modeling techniques. The composite OITC rating of the noise exposed building façade is also shown to be an effective metric for predicting NLR values.

Airborne acoustic assessment of impact-resistant fitness flooring systems

Fitness facilities in residential and mixed-used commercial buildings introduce important acoustic design challenges that must be considered in a building. Cardio activities such as running on treadmills, group classes for high intensity training, and weight training areas introduce high levels of unwanted noise and vibration into a building structure. Isolated floor constructions are generally coordinated and implemented during design but are not practical when buildings are completed and occupied. Impact-resistant fitness flooring systems are typically explored and installed as an alternate approach to reduce the transmission of impact noise and vibration. Non-standardized field airborne noise measurements of weight drops were conducted on an existing gym and on four possible impact-resistant fitness flooring upgrades to assess the reduction of impact noise levels in the offices located below the gym. The measurements were also compared to the HVAC background noise levels to observe the increase above background conditions and provide a subjective evaluation. The results of the measurements show that impact-resistant fitness flooring systems provide a noticeable reduction of impact noise, compared to standard fitness flooring systems. The results also show that impact-resistant fitness flooring systems that include specialty engineered shock pads as a base layer provide a significant reduction of impact noise levels.

Exploring Progress and Future Trends in Reducing Traffic Noise: A Scoping Review on the Influence of Pavement Characteristics

This scoping review seeks to summarize current research on reducing traffic noise, focusing on how pavement characteristics affect road-tyre mechanical vibrations, which contribute significantly to urban noise pollution. The present study analyzes numerous research investigations on novel asphalt mixtures and rubber binders to identify current trends in pavement design that help reduce noise. Issues such as the longevity of noise-reducing pavements and the trade-off between noise reduction and other practical needs such as safety and cost-efficiency are examined. This assessment emphasizes the impact of new technologies, such as the Internet of Things (IoT), on improving pavement performance and reducing noise levels. Future directions stress the importance of a multidisciplinary approach involving material science, urban design, and acoustic engineering to create sustainable and effective solutions for traffic noise pollution. This review provides valuable input to the scholarly discussion on reducing traffic noise and also presents useful guidance for politicians and engineers aiming to improve urban livability by decreasing noise levels.

Car wash noise reduction - case study

A car wash is installed in one corner of a large industrial building with the exit feeding into the building interior. The building interior is largely open space with a high roof. This houses multiple activities going on at any given time including part fabrication and vehicle retrofitting. The space available for the car wash necessitates the exit door to open during the drying cycle. The blower noise during the drying cycle with the exit door open is not loud enough to require hearing protection in the facility. The functions held within the space eventually expanded to include meetings requiring speech communication. The noise during the drying cycle was loud enough to disrupt audibility. An ad hoc team worked to reduce noise levels sufficiently to allow all other activities to continue without noise disruption during car wash operation. This paper addresses the diagnostic work and countermeasures put in place to achieve this goal.

TRNet: Two-level Refinement Network leveraging speech enhancement for noise robust speech emotion recognition

One persistent challenge in Speech Emotion Recognition (SER) is the ubiquitous environmental noise, which frequently results in deteriorating SER performance in practice. In this paper, we introduce a Two-level Refinement Network, dubbed TRNet, to address this challenge. Specifically, a pre-trained speech enhancement module is employed for front-end noise reduction and noise level estimation. Later, we utilize clean speech spectrograms and their corresponding deep representations as reference signals to refine the spectrogram distortion and representation shift of enhanced speech during model training. Experimental results validate that the proposed TRNet substantially promotes the robustness of the proposed system in both matched and unmatched noisy environments, without compromising its performance in noise-free environments.

SCIENTIFIC APPROACHES TO THE DEVELOPMENT OF COMPOSITES MATERIALS FOR REDUCING VIBRATION AND NOISE IN PRODUCTION

Goal. Scientific approaches to the development of composite materials for noise and vibration reduction in the workplace and evaluation of their effectiveness. Methodology. Сomplex of scientific methods for assessing the impact of environmental factors, such as noise and vibration, on the worker was used for the research. Сomparative evaluation of the effectiveness of the developed composite materials with the existing ones was carried out in terms of their ability to reduce noise and vibration at the worker's workplace. Results. New composite materials with an extended spectrum of action have been developed. Their effectiveness in laboratory and production conditions was evaluated. Their effectiveness was evaluated at those workplaces where an increased level of noise and vibration is registered, a comparative analysis of the new vibration-absorbing materials developed by the authors with those existing in laboratory and production conditions was carried out.Conducted studies have shown that «Vibroshtil» and «Vibroshtilmaxi» vibration-absorbing materials are characterized by a higher level of sound absorption compared to both domestic and materials of the same purpose produced in other countries, and are proposed for implementation in production, railway transport and the subway. Conducted studies have shown that «Vibroshtil» and «Vibroshtilmaxi» vibration-absorbing materials are characterized by the higher level of sound absorption compared to both domestic and materials of the same purpose produced in other countries, and are proposed for implementation in production, railway transport and the subway. The comparative evaluation made it possible to prove the effectiveness of the developed composite vibration-absorbing materials for the correction and reduction of noise and vibration levels in workplaces. The results were achieved due to the optimal selection of ingredients of composite materials and their ratio. Scientific novelty. The effectiveness of new composite materials «Vibrostil» and «Vibrostilmax» for reducing noise and vibration levels at workplaces was developed and evaluated, and their effectiveness was evaluated in order to prevent the risk of workers suffering from vibration sickness. Practical significance. The introduction of developed vibration-absorbing materials will reduce the level of noise and vibration in the workplace and reduce the risk of workers suffering from vibration sickness.

An optimal sensor layout method based on noise reduction estimation for active road noise control

Active noise control (ANC) is an effective method to suppress vehicle road noise. The rapid selection of the reference sensor set and rational selection of its layout position are crucial for determining the vibration noise transmission paths with high contributions, which determines the noise reduction performance of the active road noise control (ARNC) system. The reference sensor set selected by the conventional multiple coherence function (MCOH) method does not always ensure the optimal noise reduction performance and the matrix singularity problem based on the Fisher information matrix (FIM) expansion method. To alleviate this problem, this paper proposes a method based on the overall level of noise reduction (OANR) and the FIM to select a set of reference sensors and determine their positions. This method uses an optimal causally constrained Wiener filter to estimate the theoretical OANR for each control area to ensure the reference sensor selected has the optimal noise reduction performance, and it expands efficiently based on the FIM method to select a set of reference sensors. Besides, the matrix singularity problems in the FIM-based expansion method are solved using noise frequency summation and matrix operation, which makes the method more universally applicable. Numerical simulations are performed to analyze and evaluate the noise reduction performance and selection efficiency of the proposed method under different conditions. In addition, a series of real vehicle ANC experiments are conducted. The results show that the reference sensor set selected based on the proposed method has an obvious advantage in noise reduction performance, and only four reference sensors are needed to achieve 4.63 dB(A) noise reduction in ARNC experiments. It fully confirms the effectiveness of the proposed method in real vehicle applications.

Evaluation of Noise-Reduction Techniques for Gas-Turbine Test Stands: A Preliminary Analysis

Emphasizing the importance of acoustic attenuation in maintaining compliance with stringent noise regulations and enhancing workplace safety, this analysis covers theoretical and practical aspects of prediction methods used for the development of sound attenuators for gas-turbine testing stands. This paper presents a preliminary analysis and evaluation of the improvement of the Embleton method for projecting a noise attenuator for industrial applications, especially for gas-turbine test stands. While primarily focusing on the static acoustic behavior of the attenuator, certain considerations were also made regarding flow conditions, Mach number-dependent attenuation, pressure drop, and self-generated noise aspects to provide a comprehensive perspective on applying a suitable evaluation method. The study investigates different calculation methods for the assessment of noise reduction for linear and staggered baffles applied on a scaled reduced model of an attenuator. Thus, the critical parameters and development requirements necessary for effective noise reduction in high-performance gas-turbine testing environments will be evaluated in a downscaled model. Key factors examined include the selection of design parameters and configurations from various topological options (single, double, and triple parallel baffles vs. double and triple staggered baffles). Advanced computational methods, like analytic and finite-element analysis (FEM), are used to predict acoustic performance and evaluate the prediction method. Experimental validation is performed to corroborate the simulation results, ensuring the reliability and efficiency of the attenuator. The results indicate that an improved prediction method led to a better design for a sound-attenuator module, which can significantly reduce noise levels without compromising the operational performance of the gas turbine inside a test cell.

Явные решения в проблеме звукоизоляции с использованием многослойных структур при нормальном прохождении волн

The problem of sound isolation at ultra-low frequencies (30–200 Hz) by using multilayered structures is con-sidered, taking into account the normal wave propagation and an arbitrary number of layers. It is assumed that the multilayered structure consists of parallel acoustic layers, connected to each other along vertical boundary lines; acoustic half-spaces (air) are located to the left and right of the structure. For the problem, we define the acoustic parameters of the structure. The wave equations of the harmonic process are described for the left and right half-spaces of the structure, using the Helmholtz equation and a system of linear algebraic equations with given boundary conditions. Besides, explicit analytical solutions are obtained to find the transmission coefficient (transparency coefficient), with an arbitrary number of layers. Examples of solution for low-frequency sound absorption for building structures with different numbers of layers of alternating building materials and air spaces are considered. The effectiveness of using mixed structures, in which air layers are sandwiched between high impedance layers, for low-frequency sound absorption has been confirmed by assessing the level of noise reduction.

Muffler Design for Noise Reduction and Pressure Loss Optimization Using Multiobjective Genetic Algorithm

The muffler plays a crucial role in reducing the noise generated by the internal combustion engine exhaust gases. Therefore, an effective muffler design should be capable of significantly reducing noise levels. However, we must also consider backpressure, which can negatively impact engine performance. Backpressure is the additional pressure exerted by the muffler towards the engine, and it can have adverse effects on engine performance, thus requiring minimization. These two objectives often conflict with each other. Hence, in this research, we utilize multiobjective genetic algorithms as a tool to optimize muffler design. Inspired by the natural selection process, genetic algorithms aim to find a muffler design that is not only effective in reducing noise but also produces minimal backpressure. Thus, this study aims to achieve a balance between noise reduction and backpressure minimization in muffler design. The multiobjective genetic algorithm proposes 105 muffler design solutions. These solutions are not dominated by each other against both TL and PL objectives. The design that has the best value in the TL objective is solution 1 with TL and PL values of 26.06 dBA and 2.27 kPa. The design that has the best value in the PL objective is solution 3 with TL and PL values of 8.36 dBA and 1.87 kPa. The muffler compromise design chosen was a solution 41 with TL and PL values of 17.78 dBA and 2.07 kPa.

Reduction of finite sampling noise in quantum neural networks

Quantum neural networks (QNNs) use parameterized quantum circuits with data-dependent inputs and generate outputs through the evaluation of expectation values. Calculating these expectation values necessitates repeated circuit evaluations, thus introducing fundamental finite-sampling noise even on error-free quantum computers. We reduce this noise by introducing the variance regularization, a technique for reducing the variance of the expectation value during the quantum model training. This technique requires no additional circuit evaluations if the QNN is properly constructed. Our empirical findings demonstrate the reduced variance speeds up the training and lowers the output noise as well as decreases the number of necessary evaluations of gradient circuits. This regularization method is benchmarked on the regression of multiple functions and the potential energy surface of water. We show that in our examples, it lowers the variance by an order of magnitude on average and leads to a significantly reduced noise level of the QNN. We finally demonstrate QNN training on a real quantum device and evaluate the impact of error mitigation. Here, the optimization is feasible only due to the reduced number of necessary shots in the gradient evaluation resulting from the reduced variance.

How can optimized forest management plan regulate noise levels from wind turbines?

Wind energy has emerged as one of the most economically viable renewable energy options in the transition towards a fossil-free society. In Finland, wind farms, consisting of several wind turbines, are commonly located in forested areas, prompting concerns about their potential audio-visual impacts. Despite this, research into how forests might mitigate the adverse effects of wind farms are limited. Forests can effectively serve as noise barrier, with their noise attenuation capacity varying based on the forest’s characteristics. Specifically, the attenuation level depends on the sound’s travel distance through the forest, as well as the size and density of trees. Our study findings indicate that forests can provide up to 10 dB of additional noise attenuation. This was achieved by integrating a forest structure-based model into forest planning calculations, aimed at mitigating noise pollution from wind turbines. Incorporating this noise model as a management objective significantly reduced noise levels in the pilot study area, outperforming traditional business-as-usual management strategies. Furthermore, adapting a combination of uneven-aged and even-aged forest management approaches resulted in more forested landscape, which was more effective in mitigating higher noise levels. Our results contribute important insights that, along with further research, can guide future forest planning and management towards enhanced sustainability.