Harmful Noise Research Articles

A hypothetical defenses-based training framework for generating transferable adversarial examples

Transfer-based attacks utilize the proxy model to craft adversarial examples against the target model and make significant advancements in the realm of black-box attacks. Recent research suggests that these attacks can be enhanced by incorporating adversarial defenses into the training process of adversarial examples. Specifically, adversarial defenses supervise the training process, forcing the attacker to overcome greater challenges and produce more robust adversarial examples with enhanced transferability. However, current methods mainly rely on limited input transformation defenses, which apply only linear affine changes. These defenses are insufficient for effectively removing harmful content from adversarial examples, resulting in restricted improvements in their transferability. To address this issue, we propose a novel training framework named Transfer-based Attacks through Hypothesis Defense (TA-HD). This framework enhances the generalization of adversarial examples by integrating a hypothesis defense mechanism into the proxy model. Specifically, we propose an input denoising network as the hypothesis defense to effectively remove harmful noise from adversarial examples. Furthermore, we introduce an adversarial training strategy and design specific adversarial loss functions to optimize the input denoising network’s parameters. The visualization of the training process demonstrates the effective denoising capability of the hypothesized defense mechanism and the stability of the training process. Extensive experiments show that the proposed training framework significantly improves the success rate of transfer-based attacks by up to 19.9%. The code is available at https://github.com/haolingguang/TA-HD.

Quieting the neonatal intensive care unit: A quality improvement initiative.

The neonatal intensive care unit (NICU) is vital for preterm infants but is often plagued by harmful noise levels. Excessive noise, ranging from medical equipment to conversations, poses significant health risks, including hearing impairment and neurodevelopmental issues. The American Academy of Pediatrics recommends strict sound limits to safeguard neonatal well-being. Strategies such as education, environmental modifications, and quiet hours have shown to reduce noise levels. However, up to 60% of the noises remain avoidable. High noise exposure exacerbates physiological disturbances, impacting vital functions and long-term neurological outcomes. Effective noise reduction in the NICU is crucial for promoting optimal neonatal development. To measure the sound levels in a NICU and reduce ambient sound levels by at least 10% from baseline. A quasi-experimental quality improvement project was conducted over 4 mo in a 20-bed level 3 NICU in a tertiary care medical college. Baseline noise levels were recorded continuously using a sound level meter. The interventions included targeted education, environmental modifications, and organizational changes, and were implemented through three rapid Plan-Do-Study-Act (PDSA) cycles. Weekly feedback and monitoring were conducted, and statistical process control charts were used for analysis. The mean noise values were compared using the paired t-test. The baseline mean ambient noise level in the NICU was 67.8 dB, which decreased to 50.5 dB after the first cycle, and further decreased to 47.4 dB and 51.2 dB after subsequent cycles. The reduction in noise levels was 21% during the day and 28% at night, with an overall decrease of 25% from baseline. The most significant reduction occurred after the first PDSA cycle (mean difference of -17.3 dB, P < 0.01). Peak noise levels decreased from 110 dB to 88.24 dB after the intervention. A multifaceted intervention strategy reduced noise in the NICU by 25% over 4 months. The success of this initiative emphasizes the significance of comprehensive interventions for noise reduction.

Multi-spectral image fusion for moving object detection

This study delves into the problem of moving object detection in infrared and visible images. While existing approaches primarily focus on single-task detection using single-spectral image data, such as thermal infrared or visible images, they often ignore the differences between different spectral images and the interconnectedness of related tasks such as image fusion and segmentation. To tackle these problems, we present a novel multi-spectral image fusion network with quality and semantic awareness for moving object detection (MOD), particularly in scenarios where ground truth labels for both infrared and visible images are unavailable. Our approach fuses multi-spectral images, incorporating additional subtasks in the image fusion to obtain content and quality perception of infrared and visible images. In addition, we design a novel residual global perception module (RGPM) and multi-spectral fusion loss, which can capture more hidden features and contextual information across various scales. This enhanced capability leads to more precise detection and tracking of moving objects, particularly in challenging situations involving occlusions and dynamic backgrounds. Compared with single-spectral moving object detection optimization, the hurdles of utilizing deep learning for multi-spectral image fusion, e.g., without ground truth labels and harmful noise, are significantly mitigated. Extensive quantitative and qualitative comparative experiments demonstrate its effectiveness, robustness, and superior performance compared to contemporary methods. Concisely, the proposed fusion representation learning has gained 44.2%,31.2%,36.3%,41.6%,5.3%,31.2%,76.2% on EI, SF, DF, AG, MI, SD and Nabf metrics compared with the best competitors.

Exposure to Noise or Music in Clinical Trials: A Scoping Review on Ethical and Methodological Considerations.

Use of noise or music in experimental human studies requires balancing the need to avoid subjecting participants to potentially harmful noise levels while still reaching levels that will produce a measurable change in the primary outcome. Several methodological and ethical aspects must be considered. This study aims to summarize ethical and methodological aspects, and reported outcomes, of previously published experimental paradigms using loud noise/music. Four databases (Medline, Central, Web of Science, and Scopus) and two trials registries (Clinicaltrials.gov and EU Clinical Trials) were searched. Extracted items had the details of author and year of publication, study design and purpose, population, setting timeline and material, selected battery test, and effect of noise/music on participants' hearing. Thirty-four studies were included. Exposure safety considerations were reported in five studies. Eleven studies assessing hearing loss used white or narrow-band noise [(NBN (0.5-4 kHz), up to 115 dBA, duration range: 3'-24 hours)], and 10 used pop music (up to 106 dBA, duration range: 10'-4 hours). Experimental setting varied significantly. Temporary thresholds shift (TTS) and reduction in distortion product otoacoustic emissions were found at 1-8 kHz, with maximum average TTS∼21.5 dB at 4 kHz after NBN and ∼11.5 dB at 6 kHz after music exposure. All participants recovered their hearing, except for one participant in one study. In the 13 non-hearing loss studies, no hearing testing was performed after exposure, but loud noise was associated with temporary stress, bradygastria, and cardiovascular changes. Noise-induced subjective stress may be higher for participants with tinnitus. Loud noise (100 dBA, 10') increased diastolic and mean blood pressure only in participants with hypertension. Experimental exposure paradigms can produce temporary changes to hearing without measurable long-term health consequences. Methodological and ethical aspects identified in this review should be considered for the development of future paradigms.

Citizens’ exposure to predominant noise sources in agglomerations

Abstract Environmental noise directive requires Member States to produce and periodically update strategic noise maps for agglomerates in order to evaluate citizens’ noise exposure before the action plan. Its ultimate purpose is to mitigate the highest or most harmful noise levels. Available tools do not provide a point-to-point indication of the predominant sources to be addressed by intervention on the sources by individual owners. Recently, noise source predominance maps were developed to show the predominant source at each point of the calculation grid of the strategic noise map by means of polygons and colors. Intensity noise source predominance maps were also developed to add the visualization of noise exposure levels by coloring the polygons according to a color scale. This work investigates their applicability in agglomerates and defines an additional indicator with the purpose of connecting the high levels of citizen exposure to its predominant source. The new approach provides an aid to administrations in identifying areas where singular noise mitigations would be truly effective in improving the citizen’s quality of life by ensuring a noticeable decrease in total noise while reducing exposure to the specific source.

DiffBEV: Conditional Diffusion Model for Bird’s Eye View Perception

BEV perception is of great importance in the field of autonomous driving, serving as the cornerstone of planning, controlling, and motion prediction. The quality of the BEV feature highly affects the performance of BEV perception. However, taking the noises in camera parameters and LiDAR scans into consideration, we usually obtain BEV representation with harmful noises. Diffusion models naturally have the ability to denoise noisy samples to the ideal data, which motivates us to utilize the diffusion model to get a better BEV representation. In this work, we propose an end-to-end framework, named DiffBEV, to exploit the potential of diffusion model to generate a more comprehensive BEV representation. To the best of our knowledge, we are the first to apply diffusion model to BEV perception. In practice, we design three types of conditions to guide the training of the diffusion model which denoises the coarse samples and refines the semantic feature in a progressive way. What's more, a cross-attention module is leveraged to fuse the context of BEV feature and the semantic content of conditional diffusion model. DiffBEV achieves a 25.9% mIoU on the nuScenes dataset, which is 6.2% higher than the best-performing existing approach. Quantitative and qualitative results on multiple benchmarks demonstrate the effectiveness of DiffBEV in BEV semantic segmentation and 3D object detection tasks.

Using acoustic monitoring to evaluate the co-benefits of urban restoration

Restoring urban greenspaces is an increasingly common nature-based solution aiming to bolster biodiversity while benefiting human wellbeing. However, there is limited understanding of the co-benefits, including potential trade-offs and synergies between outcomes for nature and people. Although passive acoustic recording may be a valuable outcome monitoring tool, appropriate analytical techniques are unknown. We explore how different acoustic analyses capture patterns in species diversity and harmful noise pollution using 2021– 2023 acoustic data from Detroit, Michigan. Data were collected as part of a longitudinal panel study aimed at quantifying the effects of park restoration on physical activity, stress, and cardio-metabolic health. We used AudioMoth recording devices at 100 sites: 10 in the neighborhood around each of 5 restored parks, where native plants were seeded, and 10 around each of 5 unmaintained control parks, matched to restored parks based on specified conditions. Recordings were analyzed by manually identifying bird species and noise in a subset of spectrograms, using an artificial neural network (BirdNET), and using acoustic indices. We found that using acoustic indices in a model could accurately predict bird species diversity and richness, but not community composition. We compared outputs from each type of analysis with mental health indicators of study participants.

Psychoacoustic analyses of urban noise from long-term monitoring—Findings and outlook

Urban noise is usually assessed using sound pressure level indicators to assess harmful noise effects. However, studies have shown that human responses to environmental noise are driven by psychoacoustic properties even beyond sound pressure level indicators. Although the value of psychoacoustic parameters for an improved characterization of environmental noise appears plausible and has often been shown in laboratory studies, a systematic examination of psychoacoustic parameters over long measurement intervals is lacking. In the research project SALVE+, long-term acoustic measurements at several locations in a German city were subject to psychoacoustic analyses and the location-dependent behavior of psychoacoustic parameters over time was examined. The measurements were analyzed to determine the acoustic quality of urban sound beyond sound pressure level and noise annoyance. Based on statistical analyses, the psychoacoustic properties of urban locations considering their land use are discussed regarding an improved characterization of acoustic environments. Based on this approach, the suitability of psychoacoustic parameters for mapping of spatial and temporal patterns is investigated. The presentation aims to highlight the value of noise monitoring in cities and analyze opportunities for improved urban noise management that additionally considers issues such as restoration quality and health promotion.

Preventing Excessive Noise Exposure in Infants, Children, and Adolescents.

Noise exposure is a major cause of hearing loss in adults. Yet, noise affects people of all ages, and noise-induced hearing loss is also a problem for young people. Sensorineural hearing loss caused by noise and other toxic exposures is usually irreversible. Environmental noise, such as traffic noise, can affect learning, physiologic parameters, and quality of life. Children and adolescents have unique vulnerabilities to noise. Children may be exposed beginning in NICUs and well-baby nurseries, at home, at school, in their neighborhoods, and in recreational settings. Personal listening devices are increasingly used, even by small children. Infants and young children cannot remove themselves from noisy situations and must rely on adults to do so, children may not recognize hazardous noise exposures, and teenagers generally do not understand the consequences of high exposure to music from personal listening devices or attending concerts and dances. Environmental noise exposure has disproportionate effects on underserved communities. In this report and the accompanying policy statement, common sources of noise and effects on hearing at different life stages are reviewed. Noise-abatement interventions in various settings are discussed. Because noise exposure often starts in infancy and its effects result mainly from cumulative exposure to loud noise over long periods of time, more attention is needed to its presence in everyday activities starting early in life. Listening to music and attending dances, concerts, and celebratory and other events are sources of joy, pleasure, and relaxation for many people. These situations, however, often result in potentially harmful noise exposures. Pediatricians can potentially lessen exposures, including promotion of safer listening, by raising awareness in parents, children, and teenagers. Noise exposure is underrecognized as a serious public health issue in the United States, with exposure limits enforceable only in workplaces and not for the general public, including children and adolescents. Greater awareness of noise hazards is needed at a societal level.

Smart mobility procedure for road traffic noise dynamic estimation by video analysis

Road Traffic Noise is a major concern in Europe, with more than 20% of people exposed to harmful noise levels. Efficient monitoring and assessment of the sound levels in critical areas are crucial to support decision strategies to control/reduce noise exposure. However, continuous and long-time ranged spatio-temporal measurements require high-cost equipment and maintenance duties. Therefore, this paper aims to develop a cost-efficient smart mobility procedure for the estimation of traffic noise levels based on roadside video images. The developed procedure involves an algorithm that extracts traffic volumes, identifies vehicle classes, estimates each vehicle’s speed from video recordings, and a noise assessment component using dynamic microscopic models. These latter are based on existing Noise Emission Models – NEMs, for the assessment of the source sound power levels, coupled with a sound propagation model able to consider each on-road vehicle speed as input and evaluate the equivalent continuous A-weighted sound pressure levels. The developed approach is characterized by a modular structure that easily allows to replace NEMs and/or incorporate extra variables in the sound propagation model. The procedure is tested on a rural road of a medium-sized city, under different levels of service, and results show that the errors concerning the noise estimations are below 1 dBA, revealing high accuracy.

Investigation of the structure and properties of highly damped alloys of the Cu-Mn system

Currently, there is a rapid development of technology, an increase in speed and an increase in the power of machinery and equipment. This leads to an increase in harmful noise and vibration, which negatively affects working conditions. One of the highly effective ways to reduce harmful noise and vibration is the use of damping materials. Alloys of the manganese-copper system belong to this group of materials. In some cases, this method is the only possible noise reduction method. Therefore, the development and study of new materials, the provision of new opportunities, their application is relevant. In the course of the study, methods of X-ray fluorescence spectroscopy, tests for the wear resistance of the material under unsteady friction, the method of homogenization, methods of microstructure research were used. It has been found that in quaternary alloys of the Mn-Cu-Ni-Al system, the effect of nickel slowing down the decomposition processes can be balanced with aluminum in a nickel-aluminum ratio of 2:1. It is known that the formation of the Ni-Al phase can further strengthen the alloy. The obtained results of tests on the wear resistance of the zirconium-doped alloy provided the basis for further research in the development of new Mn-Cu-based alloys. Before and after heat treatment, the alloy structure was studied, the chemical composition was determined, hardness and microhardness were measured, and the coefficient of wear resistance was determined. The results can be used to determine the direction of further development in the field of structural materials.

Mechanical spring discharge-based multipillar triboelectric nanogenerator with enhanced power output

With the extensive use of small portable electronics in digital healthcare, the triboelectric nanogenerator (TENG), which can convert mechanical energy into electricity, has been developed for these portable electronics. However, the high mechanical input power for TENG performance improvement causes constant damage and excessive noise, which can make applying portable devices in daily life inconvenient. Nevertheless, the TENG electrical limitation, generating a low current output as nanoampere to microampere, still is not overcome. In this study, a portable multipillar TENG (PMP-TENG) with conductive springs can provide amplified output, developed mechanical characteristics simultaneously. When a moving electrode with a surface charge contacts the springs, the PMP-TENG continuously generates a high discharge output and increases the output frequency through the elastic force of the spring. In addition, the spring can prevent crack damage and harmful noise via shock absorption of the moving electrode. During the PMP-TENG operating mechanical input of 2.5 Hz, the average peak voltage, current is 165 V, 34 mA, respectively. The PMP-TENG is used to charge small electronics or power warning lights in portable devices during human motion, such as walking, running, and jumping, increasing its advantages.

Traffic Noise as a Factor of Health Risks and Restrictions on the Use of Land Plots of Urban and Rural Settlements

Introduction: Noise is one of the priority risk factors for human health and the environment. Urban noise exposure demonstrates a steady increase. New instruments of government regulation are necessary to prevent sanitary and epidemiological ill-being of the population. The existing regulatory framework and methodological approaches facilitate management of the current situation while maintaining health of citizens. Objective: To zone the territory of a large city by noise levels for the tasks of urban planning and assessment of health risks posed by road traffic noise. Materials and methods: Data on 4,200 sections of the road network as sources of urban noise with the average daily traffic of ca. 300,000 vehicles were used for acoustic modeling. Complex acoustic calculations were performed using the “Ecolog-Noise” software incorporating current regulations and guidelines on spatial distribution of noise for the entire area of the city within the boundaries of the computational rectangle sized 50 × 35 km and a grid step of 200 meters. The mapping of zoning results was made using geographic information systems. Potential risks of health disorders were assessed in accordance with the current methodology for assessing human health risk posed by traffic noise. Results: Based on simulation and situational acoustic modeling of spatial distribution, we zoned the territory of the city by noise levels for the tasks of urban development and assessed potential health risks for its citizens. We established zones of acoustic discomfort with the noise levels above 55 dBA and 45 dBA, taken as safety criteria for daytime and nighttime, respectively. Three major zones with different levels of noise exposure were identified: zone 1 (&lt; 45 dBA) with the area of 255.44 km2 ; zone 2 (45–55 dBA), 263.72 km2 ; and zone 3 (&gt; 55 dBA), 289.88 km2 . We estimated that most city inhabitants (893,306 people) lived in the third zone and were at risk of noise-related health disorders. The results of health risk assessment showed that long-term exposure to urban noise generated moderate risks by 14 years of age and high and very high risks by 45 and 55 years of age, respectively. Conclusion: Under current circumstances, the use of certain land plots in the city is limited. Such areas require effective noise protection and minimal residential development to eliminate human exposure to harmful noise levels. Our findings have substantiated managerial decisions on the spatial development of urban territories.

Risk of Noise-Induced Hearing Loss for Orthopaedic Surgeons.

Noise-induced hearing loss (NIHL) affects the ability of an individual to communicate and can negatively impact quality of life. The risk to orthopaedic surgeons of developing NIHL as a result of occupational exposures in the operating room (OR) is currently unknown. Hearing protection is recommended for levels of >85 decibels (dB), irrespective of length of exposure. The primary goal of the present study was to determine whether orthopaedic surgeons are exposed to harmful noise levels in the OR that puts them at risk for developing NIHL. A prospective review was conducted with use of intraoperative audio recordings across 6 orthopaedic subspecialties. Recordings were made in ORs prior to the surgical start time to serve as baseline controls. Decibel levels were reported as the maximum dB level (MDL), defined as the highest sound pressure level during the measurement period, and as the time-weighted average (TWA), defined as the average dB level projected over an 8-hour time period. Noise doses were reported as the percentage of maximum allowable daily noise (dose) and as the measured dose projected forward over 8 hours (projected dose). Three hundred audio recordings were made and analyzed. The average MDL ranged from 96.9 to 102.0 dB, with noise levels for all subspeciality procedures being significantly greater compared with the control recordings (p < 0.001). Overall, MDLs were >85 dB in 84% of cases and >100 dB in 35.0% of cases. The procedure with the highest noise dose was a microdiscectomy, which reached 11.3% of the maximum allowable daily noise and a projected dose of 104.1%. Among subspecialties, adult reconstruction had the highest dose and projected dose per case among subspecialties. The present results showed that orthopaedic surgeons are regularly exposed to damaging noise levels (i.e., >85 dB), putting them at risk for permanent hearing loss. Further investigation into measures to mitigate noise exposure in the OR and prevent hearing loss in orthopaedic surgeons should be undertaken. Orthopaedic surgeons are at risk for NIHL as a result of occupational exposures in the OR.

Energy distribution of bifurcated waveguide structure with planar and non-planar surfaces

The present communication addresses the reflection and transmission analysis of a two-dimensional waveguide structure with planar and non-planar surfaces. In the fields of physics, engineering and applied mathematics, research is being carried out to control or reduce unwanted and harmful noise to an acceptable level. Our aim is to solve the boundary value problem developed to simulate the transmission and reflection of a bifurcated waveguide structure in the channels or ducts that have abrupt changes in the height together with planar and non-planar surfaces. Furthermore, the eigenfunctions are linearly independent and non-orthogonal. To solve non-orthogonal eigenfunctions, a generalized orthogonality relation has been developed. Solution is obtained using mode matching technique (MMT) along with generalized orthogonal relations. In the last section, solution is viewed graphically in the inner and outer ducts or channels for different frequencies and height. The expressions for energy distribution in different duct regions are obtained and sketched subject to the various properties of the waveguide material. The results are well supported for a number of mathematical and physical reasons.

Attention-based gating optimization network for multivariate time series prediction

Multivariate time series prediction is helpful for scientific decision-making and reliable assessments in numerous fields. Capturing time series nonlinear change rules with increasing dependency complexity among multivariate time series remains challenging. We propose an attention-based gating optimization network (AGON) to solve this issue. To relieve the conflict between external and target factors, the AGON divides the original time series into external factors and target factor for two parallel encoder inputs. One encoder employs feature-perceived attention to distinguish external factors’ contributions and limit the impact of low-contributing factors on high-level semantics. The other leverages long short term memory (LSTM) to establish the temporal dependencies of the target factor. In the decoder phase, fine-grained denoising attention is designed to assign an attention weight vector instead of a single scalar to filter fine-grained harmful noise in the hidden state to the uttermost. Finally, information fusion LSTM is introduced to maintain the output balance between external and target factors. An extensive experiment of three fields of energy, environment, and finance (wind speed, PM2.5, four stock datasets) is presented. AGON is able to achieve 38%, 37%, and 46% improvements in the average MAE, RMSE, and MAPE results over state-of-the-art methods across all three datasets and three-step-ahead forecasting, which implies that AGON can be very competitive and holds versatility for diverse industries’ multivariate time series even if the dataset presents strong fluctuation and a nonlinear changing tendency.

Sound-Quality-Based Decision Making in Multiobjective Optimisation of Operations for Sustainable Airport Scenarios

The paper deals with a community-oriented approach to the multiobjective optimisation of sustainable takeoff and landing procedures of commercial aircraft. The objective functions to be minimised are defined as the measure of area surrounding the airport where the Sound Exposure Level (SEL) is higher than 60 dBA, and the amount of fuel burned during the procedure. The first merit factor is a measure of the number of citizens affected by a potentially harmful noise level, whereas the second is proportional to the chemical emissions. The novelty of the present approach is the use of a criterion based on sound quality for the selection of the optimal procedure from the Pareto front set. The spectrum of the noise produced by each non-dominated solution is compared to a reference spectrum, the target sound. This is synthesised to meet the acceptance requirements that emerged by a campaign of psychometric tests. The rationale underlying the research is tightly linked to the expected transformation of civil aviation, with the advent of new air transport solutions in urban and suburban environments. The breakthrough nature of the emerging scenarios requires a drastic renewal of the approaches used in the management of operations, and the present work represents a contribution to this evolution. The optimisation is attained adopting a global, deterministic method, and numerical results are obtained for single- and twin-aisle aircraft.

Development of a novel green coating process with laser

Corrosion causes costs of about 3–4% of each country’s gross domestic product, and due to the climate change, the corrosion rates on infrastructure are likely to increase furtherly in the future1,2. For corrosion protection, hard chrome plating (HCP) is commercially used since the early 20th3. Yet the biggest drawback concerns environmental protection, since toxic and carcinogenic hexavalent chromium Cr6+ is used. As an alternative, thermal spray (TS) is increasingly used since the last 20 years. Nevertheless, the coatings are technologically constrained in regard to high porosity, low material efficiency and poor bonding to the base material. Therefore, the demand for an environmental friendly and economical process that produces high-quality coatings is increasingly coming into the research focus. With laser, dense, metallurgically bonded and therefore well-adhering coatings with high material efficiency of > 90% can be produced from a large number of metallic alloys without the need to use environmentally harmful chemicals or noise emissions. However, the typical area coating rate of < 0.4 m2/h is significantly lower than that of TS of about 10 m2/h4,5, and is too small for coating large-scale components. In this regard, a novel coating process with laser was developed in this work. By decoupling the melding of powder from the coating speed, the coating speed of < 2 m/min in conventional laser coating can be increased to > 500 m/min. Defect-free layers that metallurgically bond to the base material with a thickness of 50–250 µm and a material efficiency of > 90% can be achieved. According to the results, an area coating rate up to 20 m2/h is achievable. The pioneer work of applications in offshore and automobile sectors show, this process is already providing beneficial for the industry.

A Circadian Rhythms Neural Network for Solving the Redundant Robot Manipulators Tracking Problem Perturbed by Periodic Noise

Redundant robot manipulators are usually applied to various complex scenarios where harmful noise especially periodic calculating noise always exists. In order to avoid the task failure affected by the periodic noise, a circadian rhythms neural network (CRNN) is applied to solve motion planning problems of redundant robot manipulators suffering from the periodic noise. First, in this article, we formulate a tracking problem of redundant manipulators as a convex quadratic programming (QP) problem. Second, the QP problem is converted into a matrix equation. Third, based on the neural dynamic design method, a CRNN model is exploited and developed to solve the matrix equation of the tracking problem. Comparative simulations between the proposed CRNN and the traditional zeroing neural network show that the CRNN has better robustness and performance on solving the end-effector tracking task. Two physical experiments are conducted to further certify the effectiveness, robustness, and practicability of the proposed CRNN.

Personal Audio Systems Unsafe At Any Sound

Personal Audio Systems Unsafe At Any Sound