Changes In Noise Levels Research Articles

Correlation between Ambient Seismic Noises and Economic Growth

AbstractHuman activity is a major source of high-frequency seismic noise. Long-term ambient seismic noise levels and their influencing factors are investigated. The diurnal seismic noise level in 5–15 Hz display high correlation with human activities including traffic and industrial operations that are related to economic conditions. The temporal noise-level variations are consistent among three components. Analysis with seismic noises in three consecutive months of each year enables us to estimate the noise levels without seasonal effects. The daytime seismic noise-level changes in major cities of 11 countries are assessed using the 3 month records for decades. The annual seismic noise levels present strong correlations with gross domestic product (GDP), particularly with manufacturing and industrial GDP. The seismic noise levels increase quickly with GDP in low-GDP regions but slowly in high-GDP regions. This is because high-GDP regions already have large volumes of existing noise-inducing sources and because added sources contribute weakly. The seismic noise levels increased by 14%–111% for 5–23 yr depending on the economic conditions. The correlation between ambient seismic noise level and economy growth is a global feature. The high-frequency noise level may be a proxy to present the economic condition. Economic growth affects the Earth environment in a wide range of aspects.

Roaring and repetition: How bowhead whales adjust their call density and source level (Lombard effect) in the presence of natural and seismic airgun survey noise.

Over 500 000 automated and manual acoustic localizations, measured over seven years between 2008 and 2014, were used to examine how natural wind-driven noise and anthropogenic seismic airgun survey noise influence bowhead whale call densities (calls/km2/min) and source levels during their fall migration in the Alaskan Beaufort Sea. Noise masking effects, which confound measurements of behavioral changes, were removed using a modified point transect theory. The authors found that mean call densities generally rose with increasing continuous wind-driven noise levels. The occurrence of weak airgun pulse sounds also prompted an increase in call density equivalent to a 10-15 dB change in natural noise level, but call density then dropped substantially with increasing cumulative sound exposure level (cSEL) from received airgun pulses. At low in-band noise levels the mean source level of the acoustically-active population changed to nearly perfectly compensate for noise increases, but as noise levels increased further the mean source level failed to keep pace, reducing the population's communication space. An increase of >40 dB cSEL from seismic airgun activity led to an increase in source levels of just a few decibels. These results have implications for bowhead acoustic density estimation, and evaluations of the masking impacts of anthropogenic noise.

Time-Series Prediction of Environmental Noise for Urban IoT Based on Long Short-Term Memory Recurrent Neural Network

Noise pollution is one of the major urban environmental pollutions, and it is increasingly becoming a matter of crucial public concern. Monitoring and predicting environmental noise are of great significance for the prevention and control of noise pollution. With the advent of the Internet of Things (IoT) technology, urban noise monitoring is emerging in the direction of a small interval, long time, and large data amount, which is difficult to model and predict with traditional methods. In this study, an IoT-based noise monitoring system was deployed to acquire the environmental noise data, and a two-layer long short-term memory (LSTM) network was proposed for the prediction of environmental noise under the condition of large data volume. The optimal hyperparameters were selected through testing, and the raw data sets were processed. The urban environmental noise was predicted at time intervals of 1 s, 1 min, 10 min, and 30 min, and their performances were compared with three classic predictive models: random walk (RW), stacked autoencoder (SAE), and support vector machine (SVM). The proposed model outperforms the other three existing classic methods. The time interval of the data set has a close connection with the performance of all models. The results revealed that the LSTM network could reflect changes in noise levels within one day and has good prediction accuracy. Impacts of monitoring point location on prediction results and recommendations for environmental noise management were also discussed in this paper.

A note on the acoustic environment in a usually quiet residential area after the ‘state of emergency’ declaration due to COVID-19 pandemic in Japan was lifted: supplementary survey results in post-emergency situations

Abstract In a preceding report (UCL Open: Environment, 2020;1;6), an example of results on changes in the acoustic environment from a local-scale survey in a quiet residential area during and after the ‘state of emergency’ due to COVID-19 pandemic in Japan is presented: the noise level was 1–2 dBA lower during the state of emergency, which is smaller than reported from large cities. This note presents the results of a follow-up survey in the same area to provide some more examples to gain an insight into the acoustic environment in this area. In this note, the measurement results of noise levels in June 2020, a few weeks after the cancellation of the state of emergency, are mainly reported. As the results are almost the same as those from during the state of emergency, we can infer that either the noise level was reduced in June to a level that was almost the same as that during the state of emergency, or the noise level after its cancellation in May was possibly higher than usual. In either case, the change in noise level was small, and it was difficult to conclude which case was true.

Effect of Irradiation with 15-MeV Protons on Low Frequency Noise in Power SiC MOSFETs

Low frequency noise is studied in 4H-SiC power metal-oxide-semiconductor field-effect transistors (MOSFETs) irradiated with 15-MeV protons. Irradiation is carried out at room temperature in the frequency range from 1 Hz to 50 kHz upon irradiation with doses Φ of 1012 to 6 × 1013 cm–2. The frequency dependence of the spectral noise density SI follows the law SI ∝ 1/f with good accuracy. A correlation between the saturation current of the output characteristic Id(Vd) and the low-frequency noise level is traced. At doses in the range 1012 cm–2 ≤ Φ ≤ 6 × 1013 cm–2, the saturation current varies within about 20%, whereas the noise level changes by two orders of magnitude. The results of noise spectroscopy are used to estimate the trap density in the gate oxide, Ntv. In unirradiated structures, Ntv ≈ 5.4 × 1018 cm–3 eV–1. At Φ = 6 × 1013 cm–2, Ntv increases to ~7.2 × 1019 cm–3 eV–1.

Sperm whale (Physeter macrocephalus) acoustic ecology at Ocean Station PAPA in the Gulf of Alaska – Part 1: Detectability and seasonality

Sperm whales Physeter macrocephalus produce loud, stereotypical click sequences and are an ideal species to be studied with passive acoustic techniques. To increase our limited knowledge of sperm whale occurrence patterns in remote and inaccessible locations of the North Pacific, we analyzed a five-year-long (June 2007–April 2012) acoustic data set recorded at Ocean Station PAPA (OSP; 50°N, 145°W) in the Gulf of Alaska (GOA). Firstly, we assessed the sperm whale detection performance of the Passive Aquatic Listener (PAL), and secondly, we investigated temporal patterns of sperm whale presence at OSP. The PAL proved highly efficient, with above 50% probability of detecting more than two sperm whales, a condition met for over 50% of the recordings. Results indicated that sperm whale clicks were recorded year-round, with a clear seasonal pattern. The number of detections during the summer months was approximately 70% higher compared to winter. An ambient noise analysis showed that differences in detection rates were likely not driven by seasonal changes in ambient noise levels. The average propagation range of sperm whale clicks ranged between 7 and 8 km between summer and winter, with slightly decreased detection distances observed in winter. Seasonal shifts in the intensity of the Alaska Current and the latitudinal oscillations of the North Pacific Transition Zone results in changes in water mixing, transport of nutrients and the concentration of prey such as squid, which likely drives sperm whale distribution.

ALTIS: A new algorithm for adaptive long-term SNR estimation in multi-talker babble

We introduce a real-time capable algorithm which estimates the long-term signal to noise ratio (SNR) of the speech in multi-talker babble noise. In real-time applications, long-term SNR is calculated over a sufficiently long moving frame of the noisy speech ending at the current time. The algorithm performs the real-time long-term SNR estimation by averaging “speech-likeness” values of multiple consecutive short-frames of the noisy speech which collectively form a long-frame with an adaptive length. The algorithm is calibrated to be insensitive to short-term fluctuations and transient changes in speech or noise level. However, it quickly responds to non-transient changes in long-term SNR by adjusting the duration of the long-frame on which the long-term SNR is measured. This ability is obtained by employing an event detector and adaptive frame duration. The event detector identifies non-transient changes of the long-term SNR and optimizes the duration of the long-frame accordingly. The algorithm was trained and tested for randomly generated speech samples corrupted with multi-talker babble. In addition to its ability to provide an adaptive long-term SNR estimation in a dynamic noisy situation, the evaluation results show that the algorithm outperforms the existing overall SNR estimation methods in multi-talker babble over a wide range of number of talkers and SNRs. The relatively low computational cost and the ability to update the estimated long-term SNR several times per second make this algorithm capable of operating in real-time speech processing applications.

METHODUCAL APPROACH AND ASSESSMENT OF NOISE IMPACT OF RAIL TRANSPORT ON THE BASIS OF THE USE OF RISK ASSESSMENT METHODOLOGY

The paper presents the results of measurement, prediction and assessment of noise in the territory in the zone of the influence of the railway transport. The railway transport is established to be a source of excess acoustic impact on the environment within the area of sanitary break (100 m). The dependence of the change in noise levels from freight trains at a distance of 100 m from the source and up to 30 m from the ground surface was revealed. Equivalent sound levels in octave bands for the railway section of the model are calculated. Based on the results of field measurements and calculated data, the identification of indices of risk for adverse reactions in the population living in the zone of influence of the Railways was executed. The paper presents results of the calculation of the probability of occurrence of complaints on excessive noise and the likelihood of irritation at the noise, and the results of the calculation of risk indices of pathologies of the nervous and cardiovascular systems. The research made it possible to identify the regulatory documentation discrepancy in the definition of the health gap between the line source traffic noise and residential buildings. Field measurements and executed on their basis their modeling of the noise propagation (without obstacles) have shown that on the boundary of the regulatory sanitary protection zone (100m) in the congested section of the railway the noise level of 60-62 dBA is maintained. The risk of irritation to the noise and the likelihood of complaints is assessed as “acceptable”. The risk of pathology of the cardiovascular system is evaluated as “low”. At a distance of 50 m (65 dBA) with bearing in mind age-related changes after 70 years of exposure the risk reaches of extreme values - 0,935. Construction sites located less than 100 m from the railway were shown to fall into the zone of acoustic discomfort. There was substantiated the necessity of resolving differences in regulatory documentation by harmonizing sanitary and technical groups documents regulating methods of measurement, prediction and evaluation of sound levels on the territories in the zone of influence of the Railways.

MEDICAL AND BIOLOGICAL ASPECTS OF ACOUSTIC POLLUTION OF URBANIZED AREAS

Noise pollution of the urban environment in recent years has become a serious environmental and social problem, a threat to the health and well-being of the population. Although noise for the population is not such a priority, as, for example, chemical pollution of air and water, but it has always been the subject of public interest. There are varieties of noise generation sources of which the traffic noise could be a major source. Among the many factors affecting the health of the population, urban noise is the most common and aggressive. The article deals with the problem of the negative impact of noise on human health and on the structure of the general morbidity of the population. The authors addressed the problem of noise pollution in the city of Kaluga. Presents the dynamics of changes in the number of cars and noise pollution over the past ten years. It is shown that today cars are the dominant sources of urban noise environment. The interpretation of the results of full-scale acoustic measurements carried out on the main urban highways is given. The regularities of changes in noise levels in different seasons of the year are revealed. It is concluded that the permissible values of acoustic effects in the city of Kaluga are exceeded. The results of the integrated assessment of child morbidity associated with an increase in the number of vehicles in the city and an increase in acoustic load are presented.

Application of Multiple Linear Regression Technique to Predict Noise Pollution Levels and Their Spatial Patterns in the Tarkwa Mining Community of Ghana

Predicting and preventing intraurban noise levels in our communities are very challenging for urban planning, epidemiological studies and environmental management, especially in the developing world. Most existing noise-predicting models are limited in providing changes in noise levels during intraurban development and the corresponding noise pollution. In this study, noise levels were measured at 50 purpose-designed monitoring stations and then a land-use regression model was developed for the intraurban noise prediction applying the multiple linear regression (MLR) technique. The measured and the predicted noise levels were compared. These were further compared with noise estimates from a standard noise model, Lyons Empirical model. The results from the developed MLR model did not show any significant differences in the patterns as compared with those of the Lyons Empirical model. The model performance indicators showed a standard deviation of 1.585, high correlation (R) of 0.98, R2 of 0.961 and RMSE of 1.569. The resulting maps showed a heterogeneous distribution of the noise pollution levels in the community. This confirms the usefulness of the method for assessing the spatial pattern of noise pollution in a community. This makes it a useful tool for urban planning, epidemiological studies and environmental management.

Влияние протонного облучения (15 МэВ) на низкочастотный шум мощных SiC MOSFETs

Low frequency noise has been studied in power4H-SiC MOSFETs after proton(15 MeV) irradiation. The noise was studied at room temperature in the frequency range 1 Hz−50 kHz after irradiation with doses of 1012 ≤Ф≤ 6•1013 cm−2. Frequency dependence of the spectral noise density SI follows with good accuracy to the law SI∝1/f. The correlation between the saturation current of the output characteristics of Id(Vd) and the level of low-frequency noise is established. In the dose range Ф studied the value of the saturation current varies within about 20%, while the noise level changes by 2orders of magnitude. From the data of noise spectroscopy, the density of traps in the gate oxide, Ntv was estimated. In non-irradiated structures Ntv ≈5.4•1018cm−3•eV−1, at  = 6•1013 cm−2, Ntv increases to a value of Ntv ≈7.2•1019cm−3•eV−1.

Study of noise effect on bearing vibration signal based on statistical parameters

The signals emanating from the bearings are complex and contribute to various distributions. The effect of the distribution and mathematical operations are responsible for the change in the statistical moments. This paper investigates the effect of noise on statistical moments of the bearing vibration signals. Initially, the distribution function for Healthy, inner race defect (IRD), outer race defect (ORD), and ball defect (BD) are tested using Kolmogorov Smirnov test (K-S test). The resulting distributions obtained from the K-S test are normal and Laplacian distributed patterns and convey the faulty state of the bearings. The change in noise levels and their influence on the statistical moments are verified. It is observed, the kurtosis for IRD and ORD decreases with increase in noise, whereas, the trend increases for healthy and BD faults.

Longitudinal Development of Distortion Product Otoacoustic Emissions in Infants With Normal Hearing.

The purpose of this study was to describe normal characteristics of distortion product otoacoustic emission (DPOAE) signal and noise level in a group of newborns and infants with normal hearing followed longitudinally from birth to 15 months of age. This is a prospective, longitudinal study of 231 infants who passed newborn hearing screening and were verified to have normal hearing. Infants were enrolled from a well-baby nursery and two neonatal intensive care units (NICUs) in Cincinnati, OH. Normal hearing was confirmed with threshold auditory brainstem response and visual reinforcement audiometry. DPOAEs were measured in up to four study visits over the first year after birth. Stimulus frequencies f1 and f2 were used with f2/f1 = 1.22, and the DPOAE was recorded at frequency 2f1-f2. A longitudinal repeated-measure linear mixed model design was used to study changes in DPOAE level and noise level as related to age, middle ear transfer, race, and NICU history. Significant changes in the DPOAE and noise levels occurred from birth to 12 months of age. DPOAE levels were the highest at 1 month of age. The largest decrease in DPOAE level occurred between 1 and 5 months of age in the mid to high frequencies (2 to 8 kHz) with minimal changes occurring between 6, 9, and 12 months of age. The decrease in DPOAE level was significantly related to a decrease in wideband absorbance at the same f2 frequencies. DPOAE noise level increased only slightly with age over the first year with the highest noise levels in the 12-month-old age range. Minor, nonsystematic effects for NICU history, race, and gestational age at birth were found, thus these results were generalizable to commonly seen clinical populations. DPOAE levels were related to wideband middle ear absorbance changes in this large sample of infants confirmed to have normal hearing at auditory brainstem response and visual reinforcement audiometry testing. This normative database can be used to evaluate clinical results from birth to 1 year of age. The distributions of DPOAE level and signal to noise ratio data reported herein across frequency and age in normal-hearing infants who were healthy or had NICU histories may be helpful to detect the presence of hearing loss in infants.

Ship speed reduction is an effective mitigation for underwater noise effects

The Vancouver Fraser Port Authority’s ECHO Program led a voluntary 2-month ship slowdown trial during which 56% of piloted ships slowed down to <13 knots in a 16 nautical mile corridor. The goal was to determine if a slowdown could be used as a mitigation measure to reduce ship related underwater noise effects in core Southern Resident killer whale habitat. A calibrated hydrophone system was used to measure ambient noise levels from 10 Hz to 100 kHz during the trial and a representative 2-month baseline period. The hydrophone was located 2.3 (inbound) and 5 km (outbound) from the center of the shipping lanes at 23 m depth. Analyses of data with ships present showed a median broadband noise reduction of 2.5 dB. This reduction was highest in the 10–100 Hz decade band (3.1 dB) and lowest in the 10,000–100,000 Hz band (0.3 dB). A statistical model found that received noise levels were best described by the distance to ships, the presence of small boats, water velocity, slowdown period, ship speed through water, and wind speed. This highlights that appropriate temporal scales and the inclusion of covariate data are needed to adequately measure ship related changes in underwater ambient noise levels.

Real-Time Implementation of an Extended Kalman Filter and a PI Observer for State Estimation of Rechargeable Li-Ion Batteries in Hybrid Electric Vehicle Applications—A Case Study

The Li-Ion battery state-of-charge estimation is an essential task in a continuous dynamic automotive industry for large-scale and successful marketing of hybrid electric vehicles. Also, the state-of-charge of any rechargeable battery, regardless of its chemistry, is an essential condition parameter for battery management systems of hybrid electric vehicles. In this study, we share from our accumulated experience in the control system applications field some preliminary results, especially in modeling, control and state estimation techniques. We investigate the design and effectiveness of two state-of-charge estimators, namely an extended Kalman filter and a proportional integral observer, implemented in a real-time MATLAB environment for a particular Li-Ion battery. Definitely, the aim of this work is to find the most suitable estimator in terms of estimation accuracy and robustness to changes in initial conditions (i.e., the initial guess value of battery state-of-charge) and changes in process and measurement noise levels. By a rigorous performance analysis of MATLAB simulation results, the potential estimator choice is revealed. The performance comparison can be done visually on similar graphs if the information gathered provides a good insight, otherwise, it can be done statistically based on the calculus of statistic errors, in terms of root mean square error, mean absolute error and mean square error.

Disambiguating brain functional connectivity

Functional connectivity (FC) analyses of correlations of neural activity are used extensively in neuroimaging and electrophysiology to gain insights into neural interactions. However, analyses assessing changes in correlation fail to distinguish effects produced by sources as different as changes in neural signal amplitudes or noise levels. This ambiguity substantially diminishes the value of FC for inferring system properties and clinical states. Network modelling approaches may avoid ambiguities, but require specific assumptions. We present an enhancement to FC analysis with improved specificity of inferences, minimal assumptions and no reduction in flexibility. The Additive Signal Change (ASC) approach characterizes FC changes into certain prevalent classes of signal change that involve the input of additional signal to existing activity. With FMRI data, the approach reveals a rich diversity of signal changes underlying measured changes in FC, suggesting that it could clarify our current understanding of FC changes in many contexts. The ASC method can also be used to disambiguate other measures of dependency, such as regression and coherence, providing a flexible tool for the analysis of neural data.

Traffic Noise Assessment at Residential Areas in Skudai, Johor

Vehicles passing by on roadways in residential areas may produce unpleasant traffic noise that affects the residents. This paper presents the traffic noise assessment of three selected residential areas located in Skudai, Johor. The objectives of this study are to evaluate traffic characteristics at selected residential areas, determine related noise indices, and assess impact of traffic noise. Traffic characteristics such as daily traffic volume and vehicle speed were evaluated using automatic traffic counter (ATC). Meanwhile, noise indices like equivalent continuous sound pressure level (LAeq), noise level exceeded 10% (L10) and 90% (L90) of measurement time were determined using sound level meter (SLM). Besides that, traffic noise index (TNI) and noise pollution level (LNP) were calculated based on the measured noise indices. The results showed an increase in noise level of 60 to 70 dBA maximum due to increase in traffic volume. There was also a significant change in noise level of more than 70 dBA even though average vehicle speed did not vary significantly. Nevertheless, LAeq, TNI, and LNPvalues for all sites during daytime were lower than the maximum recommended levels. Thus, residents in the three studied areas were not affected in terms of quality of life and health.

Measurement of speech in noise abilities in laboratory and real-world noise

Aim: The present study aimed to investigate speech in noise perception abilities in normal-hearing adults using different types of noise (i.e., speech babble, traffic noise, and speech spectrum noise) and at different signal-to-noise ratios (SNRs) (i.e., +5 dB, 0 dB, −5 dB, and −10 dB). Methods: A total of 109 individuals with mean age of 23 years were participated in the study. All participants had English as second language and Telugu as native and first language. English disyllabic words (Hrish et al.) were used as speech stimuli under different noises and different SNRs. Results: Results have shown that for any type of noise the speech perception scores changed with the variance in SNRs, the scores have decreased when the SNRs were decreased from 0 dB to −10 dB SNR, and the scores have increased when SNRs increased from 0 dB to +5 dB SNR. Conclusion: From this study, it can be concluded that speech perception score in noise depends on the type of noise used in testing the speech in noise abilities. This factor is very important in the selection of the noise type when measuring speech perception in the presence of noise. It was also seen that change in noise level also had a different impact on speech perception in noise abilities.

Modeling Speech Level as a Function of Background Noise Level and Talker-to-Listener Distance for Talkers Wearing Hearing Protection Devices.

Studying the variations in speech levels with changing background noise level and talker-to-listener distance for talkers wearing hearing protection devices (HPDs) can aid in understanding communication in background noise. Speech was recorded using an intra-aural HPD from 12 different talkers at 5 different distances in 3 different noise conditions and 2 quiet conditions. This article proposes models that can predict the difference in speech level as a function of background noise level and talker-to-listener distance for occluded talkers. The proposed model complements the existing model presented by Pelegrín-García, Smits, Brunskog, and Jeong (2011) and expands on it by taking into account the effects of occlusion and background noise level on changes in speech sound level. Three models of the relationship between vocal effort, background noise level, and talker-to-listener distance for talkers wearing HPDs are presented. The model with the best prediction intervals is a talker-dependent model that requires the users' unoccluded speech level at 10 m as a reference. A model describing the relationship between speech level, talker-to-listener distance, and background noise level for occluded talkers could eventually be incorporated with radio protocols to transmit verbal communication only to an intended set of listeners within a given spatial range-this range being dependent on the changes in speech level and background noise level.

An automatic glucose monitoring signal denoising method with noise level estimation and responsive filter updating

Abstract Although continuous glucose monitoring (CGM) devices have been the crucial part of the artificial pancreas, their success has been discounted by random measurement noise. The difficulty of denoising methods for CGM is that the filter parameters are hard to be determined to well reflect the internal blood glucose dynamics and the real noise level. Besides, the noise level may change from device to device, subject to subject and also within the subject as time goes on which thus requires that the filter parameters should be adjusted to follow the noise changes. In this paper, we proposed an automatic CGM signal denoising method which covers three important components. First, the state transition matrix which reveals the internal blood glucose dynamics and plays an important role in determining filter parameters can be estimated in response to different patients. Second, the real noise level can be estimated which are used to set the values of filter parameters properly. Third, a responsive filter updating rule is developed which can judge whether the values of filter parameters should be updated in response to the variability of signal-to-noise ratio. The process of dealing with the CGM signals is executing as follows: the model parameters and the noise level are evaluated using Expectation Maximization (EM) algorithm which can fix proper filter parameters for the current signals. Then, a confidence interval is defined by computing the power spectral density (PSD) of the CGM signals to identify the changes of noise level which can tell whether or not the parameters of Kalman filter (KF) should be adjusted. The above issues are investigated based on thirty in silico subjects and ten clinical subjects. The proposed method can work well to identify the changes of noise level and determine proper filter parameters.