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Journal articles on the topic 'Environmental Noise'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 May 2025

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1

Zhang, Lu, Mingjiang Wang, Qiquan Zhang, and Ming Liu. "Environmental Attention-Guided Branchy Neural Network for Speech Enhancement." Applied Sciences 10, no. 3 (February 9, 2020): 1167. http://dx.doi.org/10.3390/app10031167.

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The performance of speech enhancement algorithms can be further improved by considering the application scenarios of speech products. In this paper, we propose an attention-based branchy neural network framework by incorporating the prior environmental information for noise reduction. In the whole denoising framework, first, an environment classification network is trained to distinguish the noise type of each noisy speech frame. Guided by this classification network, the denoising network gradually learns respective noise reduction abilities in different branches. Unlike most deep neural network (DNN)-based methods, which learn speech reconstruction capabilities with a common neural structure from all training noises, the proposed branchy model obtains greater performance benefits from the specially trained branches of prior known noise interference types. Experimental results show that the proposed branchy DNN model not only preserved better enhanced speech quality and intelligibility in seen noisy environments, but also obtained good generalization in unseen noisy environments.
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2

Reuter, Eric. "Environmental noise." Journal of the Acoustical Society of America 150, no. 4 (October 2021): A46. http://dx.doi.org/10.1121/10.0007580.

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3

Ingrisano, Dennis R.-S., Cecyle K. Perry, and Kairsten R. Jepson. "Environmental Noise." American Journal of Speech-Language Pathology 7, no. 1 (February 1998): 91–96. http://dx.doi.org/10.1044/1058-0360.0701.91.

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The effects of environmental noise were estimated from automatic computer-assisted analyses of voice samples. Signals consisted of a live voice sample and a synthesized triangular waveform. Noise was generated from a personal computer fan. Six different A-weighted signal-to-noise [S/N(A)] conditions were created for the live voice and synthetic signal— 25, 20, 15, 10, 5, and 0 dB. Results revealed that automatic estimates were systematically affected by different S/N levels. As the noise floor increased, baseline estimates of jitter and shimmer also increased in value. Results are discussed with reference to safeguards and standards in voice recording and analysis.
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4

Cherukuru, Pavani, and Mumtaz Begum Mustafa. "CNN-based noise reduction for multi-channel speech enhancement system with discrete wavelet transform (DWT) preprocessing." PeerJ Computer Science 10 (February 28, 2024): e1901. http://dx.doi.org/10.7717/peerj-cs.1901.

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Speech enhancement algorithms are applied in multiple levels of enhancement to improve the quality of speech signals under noisy environments known as multi-channel speech enhancement (MCSE) systems. Numerous existing algorithms are used to filter noise in speech enhancement systems, which are typically employed as a pre-processor to reduce noise and improve speech quality. They may, however, be limited in performing well under low signal-to-noise ratio (SNR) situations. The speech devices are exposed to all kinds of environmental noises which may go up to a high-level frequency of noises. The objective of this research is to conduct a noise reduction experiment for a multi-channel speech enhancement (MCSE) system in stationary and non-stationary environmental noisy situations with varying speech signal SNR levels. The experiments examined the performance of the existing and the proposed MCSE systems for environmental noises in filtering low to high SNRs environmental noises (−10 dB to 20 dB). The experiments were conducted using the AURORA and LibriSpeech datasets, which consist of different types of environmental noises. The existing MCSE (BAV-MCSE) makes use of beamforming, adaptive noise reduction and voice activity detection algorithms (BAV) to filter the noises from speech signals. The proposed MCSE (DWT-CNN-MCSE) system was developed based on discrete wavelet transform (DWT) preprocessing and convolution neural network (CNN) for denoising the input noisy speech signals to improve the performance accuracy. The performance of the existing BAV-MCSE and the proposed DWT-CNN-MCSE were measured using spectrogram analysis and word recognition rate (WRR). It was identified that the existing BAV-MCSE reported the highest WRR at 93.77% for a high SNR (at 20 dB) and 5.64% on average for a low SNR (at −10 dB) for different noises. The proposed DWT-CNN-MCSE system has proven to perform well at a low SNR with WRR of 70.55% and the highest improvement (64.91% WRR) at −10 dB SNR.
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S. Ashwin, J., and N. Manoharan. "Audio Denoising Based on Short Time Fourier Transform." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 1 (January 1, 2018): 89. http://dx.doi.org/10.11591/ijeecs.v9.i1.pp89-92.

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<p>This paper presents a novel audio de-noising scheme in a given speech signal. The recovery of original from the communication channel without any noise is a difficult task. Many de-noising techniques have been proposed for the removal of noises from a digital signal. In this paper, an audio de-noising technique based on Short Time Fourier Transform (STFT) is implemented. The proposed architecture uses a novel approach to estimate environmental noise from speech adaptively. Here original speech signals are given as input signal. Using AWGN, noises are added to the signal. Then noised signals are de-noised using STFT techniques. Finally Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR) values for noised and de-noised signals are obtained.</p>
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Storozhuk, V. M., B. Y. Kshyvetskyy, O. M. Mayevska, H. V. Somar, I. A. Sokolovskyi, and A. V. Melnikov. "Main aspects of environmental protection from urban noise." Scientific Messenger of LNU of Veterinary Medicine and Biotechnologies 23, no. 96 (December 2, 2021): 88–92. http://dx.doi.org/10.32718/nvlvet-f9615.

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The main sources of noise pollution in modern cities, that generate significant levels of sound pressure, which significantly, sometimes at times exceed permissible noise levels have been identified. The consequences of the negative impact of noise of the urban environment on the human body, fauna and flora are described. The sanitary-hygienic, engineering-technical, architectural-planning, construction-acoustic and economic-social aspects of scientific researches concerning protection of the environment from noise pollution are singled out. The main methods and ways to reduce urban noise are described, among which are: reducing the sound power level of existing equipment and vehicles, or replacing them with less noisy ones, and during design-taking measures to minimize noise emissions from machines; carrying out timely cleaning, adjustment, repair of machines, mechanisms and equipment, restriction or complete prohibition of noisy works and operation of the most intensive noise sources at night; rational orientation of the noise source or place of noise radiation, taking into account the direction indicator; placement of noise sources and objects of protection – at the maximum possible distance from each other; the use of building structures with improved sound insulation, the use of sound-absorbing materials for lining the enclosing structures of buildings and structures; zoning of sources and objects of protection, application of territorial gaps, noise protection buildings, acoustic screens and strips of greenery. It was found that the maximum possible impact on noise pollution of modern cities and surrounding areas can be achieved in the case of integrated application of methods, means of protection against acoustic blocking of the duration, direction and use of noise emissions in its sources and through noise level on the way to its spread, as well as through the implementation of appropriate organizational and technical measures.
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7

Stojiljković, Milan, and Vlado Delic. "Noise Metric ‐ Environmental Noise Analysis Software." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3655. http://dx.doi.org/10.1121/1.2934957.

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8

Shen, Kenan, and Dongbiao Zhao. "An EMD-LSTM Deep Learning Method for Aircraft Hydraulic System Fault Diagnosis under Different Environmental Noises." Aerospace 10, no. 1 (January 5, 2023): 55. http://dx.doi.org/10.3390/aerospace10010055.

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Aircraft hydraulic fault diagnosis is an important technique in aircraft systems, as the hydraulic system is one of the key components of an aircraft. In aircraft hydraulic system fault diagnosis, complex environmental noises will lead to inaccurate results. To address the above problem, hydraulic system fault detection methods should be capable of noise resistance. Previous research has mainly focused on noise-free conditions and many effective approaches have been proposed; however, in real-world aircraft flying conditions, the aircraft hydraulic system often has strong and complex noises. The methods proposed may not have good fault detection results in such a noisy environment. According to the situation, this work focuses on aircraft hydraulic system fault classification under the influence of a hydraulic working environment with Gaussian white noise. In order to eliminate the noise interference and adapt to the actual noisy environment, a new aircraft hydraulic fault diagnostic method based on empirical mode deposition (EMD) and long short-term memory (LSTM) is presented. First, the hydraulic system is constructed by AMESIM. One normal state and five fault states are considered in this paper. Eight-channel signals of different states are collected for network training and testing. Second, the EMD method is used to obtain the different intrinsic mode functions (IMFs) of the signals. Third, principal component analysis (PCA) is used to obtain the main component of the IMFs. Fourth, three different LSTM methods are chosen to compare and the best structure that is chosen is the gate recurrent unit (GRU). After that, the network parameters are optimized. The results under different noise environments are given. Then, a comparison between the EMD-GRU with several different machine learning methods is considered, and the result shows that the method in this paper has a better anti-noise effect. Therefore, the proposed method is demonstrated to have a strong ability of fault diagnosis and classification under the working noises based on the simulation results.
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9

Passchier-Vermeer, Willy, and Wim Passchier. "Environmental Noise Exposure." Environmental Health Perspectives 106, no. 11 (November 1998): A527. http://dx.doi.org/10.2307/3434244.

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10

Lizana, Pablo. "Environmental noise culture." Journal of the Acoustical Society of America 128, no. 4 (October 2010): 2422. http://dx.doi.org/10.1121/1.3508647.

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11

Waldron, Denise. "Environmental noise control." Nature Reviews Genetics 16, no. 11 (September 29, 2015): 624–25. http://dx.doi.org/10.1038/nrg4021.

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12

Raichel, Daniel R. "Environmental Urban Noise." Journal of the Acoustical Society of America 114, no. 3 (September 2003): 1199. http://dx.doi.org/10.1121/1.1603229.

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13

Xu, Luwen, Ni Qiu, Bo Yang, and Shiwei Peng. "Separation of Urban Substation Noise and Environmental Noise based on Independent Component Analysis." Journal of Physics: Conference Series 2427, no. 1 (February 1, 2023): 012021. http://dx.doi.org/10.1088/1742-6596/2427/1/012021.

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Abstract With the development of urbanization, substations have started to be established in urban areas where the population is concentrated. To realize effective control of the substation noise, accurate measurements of the noise inside the substation and the surrounding area are necessary. However, in an urban area, the background noise, such as traffic noise, causes the sampled signals to contain not only the substation noise but also the background noise, which decreases the measurement accuracy. Thus, separating the substation noise from the environmental background noise is necessary. An independent component analysis method is used to realize the separation of the substation noise from complex environmental noises. In this paper, two typical environmental noises are selected, and their characteristics and the urban substation noise are analyzed. Then, a separation method based on the independent component analysis is constructed for separating substation noise. Its accuracy is evaluated using measured mixed signals. The verification shows that the separated substation noise is very close to the original substation noise signal, which shows that the method can be used in practical substation noise control engineering applications.
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14

Luo, Li-Yan, Shu-Ting Guo, Mei Wang, Hong-Bing Qiu, and Zheng-Hong Liu. "Adaptive Noise Reduction Algorithm Based on SPP and NMF for Environmental Sound Event Recognition under Low-SNR Conditions." Wireless Communications and Mobile Computing 2023 (January 21, 2023): 1–11. http://dx.doi.org/10.1155/2023/6582296.

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Nonnegative matrix factorization- (NMF-) based noise reduction methods can effectively improve the performance of environmental sound recognition. However, when the environmental sound overlaps highly with the noise, the spectral line loss and noise residue will occur in the low signal-to-noise ratio (SNR) condition. An adaptive noise reduction algorithm was proposed in this paper. First, noisy environmental sound is separated into estimated noise and environmental sound using NMF. Then, the estimated noise is used to calculate sound presence probability (SPP), which is adapted to decrease spectral line loss and achieve accurately estimated noise. Subsequently, the estimated noise combines with noisy environmental sound to obtain the estimated environmental sound. Finally, SPP is applied to reduce residual noise in the estimated environmental sound and reconstruct the environmental sound. The simulation results demonstrate that the proposed algorithm outperforms the traditional algorithms and NMF-based methods in terms of perceptual evaluation of speech quality (PESQ) and global SNR with increase of X% and X%, respectively. Moreover, the proposed method can effectively improve the environmental sound recognition rate. Particularly, the proposed method makes a 16.2% increase of F1-score in car horn recognition under the realistic acoustic condition.
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15

Dundurs, Janis, and Miervaldis Lacis. "Environmental Noise and Policy Implication in Latvia." Applied Mechanics and Materials 471 (December 2013): 143–48. http://dx.doi.org/10.4028/www.scientific.net/amm.471.143.

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The European Directive 2002/49/EC on the assessment and management of environmental noise obliges European Union Member states to draw noise maps of communities with more than 100,000 inhabitants (agglomerations) and of areas near the major transport infrastructures for the assessment of noise outdoors. The Latvian law On Pollution and the Cabinet Regulation No 597 Procedures for Noise Assessment and Management (Adopted 13 July 2004) were harmonized with this European Directive to provide the legislative background for the local authorities to draw noise maps to be used as a basis for noise reduction plans. Riga Agglomeration strategic noise map was calculated using software IMMI 6.3. The map shows Riga City as rather noisy city because major roads and railway lines cross the city center and close to it. Riga Freeport, located on the banks of river Daugava, with its supply roads and branch-ways also add to contribute in the total noise levels. The European Directive 2002/49/EC on the assessment and management of environmental noise also obliges European Union Member states to draw Noise reduction Action plans. In Latvia, Capital Riga and Daugavpils are required to have the Action Plans. Action Plans must be completed by 18 July 2008. Much to our regret the Riga City noise reduction Action Plan is still under consideration and in process of development because it touches the interests of many parties.
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16

Kaleniuk, Maksym, Oleg Furman, and Taras Postranskyy. "Influence of traffic flow intensity on environmental noise pollution." Transport technologies 2021, no. 1 (June 18, 2021): 39–49. http://dx.doi.org/10.23939/tt2021.01.039.

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The modern urban environment, with the development of industry, the growth of the vehicle's number on the roads, and the increase in the density of buildings, is increasingly capable of negatively affect the health and well-being of the city's population. Among the factors influencing the environment is noise pollution, namely man-made noise - unwanted and harmful sounds created as a result of human activities. Today, noise is one of the most common factors of pollution among all others. The most common source of noise pollution is transport, including cars and trucks, buses, railways, airplanes, etc. The negative phenomenon of traffic noise is that almost everyone is greatly affected. This can often be accompanied by other harmful factors, such as vibration. According to scientific researches, noise can cause irritation under constant acoustic exposure. As a result, there are sleep disorders, decreased mental capacity, and the development of stress, and stress development in humans. Traffic noise is created from the operation of engines, the friction of wheels with the road surface, brakes, and aerodynamic features of vehicles, etc. In general, the level of traffic noise depends on such basic indicators as the intensity, speed, and composition of the traffic flow. Therefore, an important task is the study of traffic noise, its measurement, the establishment of appropriate dependencies, and further evaluation of the results. Knowing the level of noise generated by vehicles, further measures to reduce it are possible, such as redistribution of traffic flows on the road network, speed limits, improving the quality of the road surface, the use of basic means of reducing noise pollution, the use of noise protection devices, etc. Based on this, the negative impact of this phenomenon on the human body and the environment, in general, can be reduced.
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17

Ridwan Gucci, Dinda Okta Dwiyanti, Muhammad Adi Sukma Nalendra, and Fauziah Fatma Ramadhani. "Environmental Ergonomic Analysis: Understanding Noise Effects on Security and Comfort." Jurnal Sains dan Teknologi Industri 21, no. 2 (May 10, 2024): 237. http://dx.doi.org/10.24014/sitekin.v21i2.29411.

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In activities production PT. XYZ has several forms of production processes. It is a grinding process, which has the potential to give rise to noise coming from the tools used during the production process. The continuous noise produced can damage healthy hearing workers. To know the noise level produced during the grinding process on module 04 and module 05 of the Santos project and calculate the recommended time When exposed to noise. Data collection will use a sound level meter to gauge noise. Data calculations using distribution frequency and counting level noise equivalent ( Leq ) obtain point noise on Dilinta Sembiring and Saiful above the Threshold Limit Value (NAV), namely 86.87 dBA and 85.35 dBA. Calculated exposure time use method NIOSH recommends that Crossed Sembiring can work for 5 hours 19 minutes and Saiful for 7 hours 37 minutes. If No, use PPE when exposed continuously. Keywords: Ergonomics Environment, Noise, Grinding, NOISH
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C, Shraddha, Chayadevi M L, Anusuya M A, and Vani H Y. "Enhancing Noise Reduction with Bionic Wavelet and Adaptive Filtering." Inteligencia Artificial 27, no. 74 (September 4, 2024): 214–26. http://dx.doi.org/10.4114/intartif.vol27iss74pp214-226.

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Speech signals often contain different forms of background and environmental noise. For the development of an efficient speech recognition system, it is essential to preprocess noisy speech signals to reduce the impact of these disturbances. Notably, prior research has paid limited attention to pink and babble noises. This gap in knowledge inspired us to develop and implement hybrid algorithms tailored to handle these specific noise types. We introduce a hybrid method that combines the Bionic Wavelet transform with Adaptive Filtering to enhance signal strength. The performance of this method is assessed using various metrics, including Mean Squared Error, Signal-to-Noise Ratio, and Peak Signal-to-Noise Ratio. Notably, our findings indicate that SNR and PSNR metrics are especially effective in enhancing the handling of pink and babble noises.
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Sahoo, Lokanath, Krushnendu Sundar Sahoo, and Nitish Kumar Nayak. "The effect of environmental noise on speech perception of individuals with sensorineural hearing loss: a prospective observational study." International Journal of Otorhinolaryngology and Head and Neck Surgery 6, no. 7 (June 25, 2020): 1263. http://dx.doi.org/10.18203/issn.2454-5929.ijohns20202778.

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<p class="abstract"><strong>Background:</strong> This study was done to identify the effect that environmental noises have on speech perception of individual with sensorineural hearing loss. The objectives were to develop evidence-based approach to support the need for sophisticated technology and to choose the better one for daily listening purposes of Hearing-Impaired individual to obtain a speech perception score when environmental noises are used as competing signal.</p><p class="abstract"><strong>Methods:</strong> The study was executed in three phases. In phase 1, developing a noise check list and recording the noise levels at different places by using sound level meter, in phase 2, analyzing the recorded noises into spectral and temporal distributions by using software and phase 3, testing the hearing loss individual’s syllables in the presence of recorded noises. </p><p class="abstract"><strong>Results:</strong> For 0 dB signal to noise ratio (SNR), the mean scores for white noise and temple noise were higher than for other noise types. The bus and auto noise conditions also showed significant difference in values between them. For +10 dB SNR, speech scores obtained for audiometry noise differed statistically from only restaurant and traffic noise. The traffic noise being the poorest differed statistically from all other noise types. On the other end of range, restaurant noise showed highest speech scores.</p><p class="abstract"><strong>Conclusions:</strong> The overall the scores were a lot higher for only restaurant noise and noise of travel in auto. These showed effect of masking release and that hearing impaired are better able to understand conversations in these situations at least.</p>
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Oh, Soo Hee, and Kyoungwon Lee. "Aircraft Noise of Airport Community in Korea." Audiology and Speech Research 16, no. 1 (January 31, 2020): 1–10. http://dx.doi.org/10.21848/asr.200001.

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Aircraft noise is one of the serious environmental noises with the increased use of flight traffic. The purpose of this study is to understand aircraft noise levels of airport communities in Korea using baseline data for audiologic management. Aircraft noise levels were retrieved from the National Noise Information System every month between 2004 and 2018. We reviewed aircraft noise levels obtained from total of 111 airport communities across 14 airports. In order to understand aircraft noise levels of civil and military airports, the aircraft noise levels measured in civil and military airport communities compared with the noise levels from civil airport communities. The data showed average 71-73 weight equivalent continuous perceived noise level (WECPNL) for fifteen years across airport cities and the average noise levels did not increase over time between 2004 and 2018 years. The civil and military airports showed about 12 WECPNLs of increased noise levels compared to the civil airports. The most civil and military airport communities, including Gwangju, Gunsan, Daegu, Wonju, and Cheongju generated the maximum noise levels and ranked as the highest airport for aircraft noise levels. Although aircraft noise levels in airport communities were similar over the past decade, civil and military airports generated increased noised levels compared to civil airports due to jet plane noises and other military-related noises. Careful consideration is necessary to implement noise reduction policy for civil and military airport communities. Ongoing noise control, hearing monitoring, education, and relevant policies are required to improve the quality of life in the airport community residences.
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van, Keulen. "Impact of noise on health: Measures to control excessive traffic noise levels." Education and Research in Health Sciences 2, no. 1 (2023): 22–30. http://dx.doi.org/10.5937/erhs2-43976.

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Long-standing research has shown that noise pollution has harmful consequences on human health. Environmental noise is becoming a significant problem in most nations. The spread of undesired noises into the environment is known as noise pollution. We are virtually constantly surrounded by noise. Environmental noise causes an illness burden that is second only to the air pollution-related disease burden in terms of scale. Due to noise from roads, trains, and airports, one in three persons is annoyed during the day and one in five has sleep disturbances at night. Noise exposure may have both a direct and an indirect impact on one's physical health. In extreme circumstances, loud noises might really harm your hearing. In addition to severely harming human health, this excessive noise prevents individuals from going about their everyday lives at home, at work, at school, and in their free time. Chronic exposure to environmental noise has a considerable negative impact on both physical and mental health. The most common source of environmental noise and the main factor in the overall negative impact of noise on health is road traffic noise. The most popular technique for noise reduction, if noise mitigation is determined to be practical and appropriate, is the application of noise barriers. However, out of the several technologies available to road authorities, the application of noise-reducing pavements is not only the most cost-effective but also can be implemented on short notice.
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22

Baker, Carol F. "Discomfort to environmental noise." Critical Care Nursing Quarterly 15, no. 2 (August 1992): 75. http://dx.doi.org/10.1097/00002727-199208000-00006.

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23

Stein, Benjamin P. "Did environmental “noise” trigger." Physics Today 55, no. 3 (March 2002): 9. http://dx.doi.org/10.1063/1.4796682.

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24

Tian, Jing, and Yi Wang. "Environmental noise in Beijing." Journal of the Acoustical Society of America 115, no. 5 (May 2004): 2591. http://dx.doi.org/10.1121/1.4809356.

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Prascevic, Momir, Darko Mihajlov, Dragan Cvetkovic, and Aleksandar Gajicki. "Assessment of Environmental Noise by Harmonica Index – Case Study: The City of Niš." Applied Mechanics and Materials 801 (October 2015): 51–59. http://dx.doi.org/10.4028/www.scientific.net/amm.801.51.

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Noise is a very present environmental nuisance, especially in urban areas. Information on the noise environment of agglomerations over 100,000 inhabitants is now available thanks to the publication of the first strategic noise maps made for the 2002/49/EC European directive. However, it currently remains difficult to understand the environmental noise data because of the used noise indicators expressed in decibel unit, which is complicated to explain and relatively far-removed from the perception of people. Acoucité and Bruitparif, two French organizations specialized for management and organization of urban noise observatories in France, have worked on a proposal for a new index closer to the perception of people. At the end of the HARMONICA project a new environmental noise index called the Harmonica index is suggested. The Harmonica index is an adimensional index with values between 0 and 10. This is why 93% of people surveyed during the project find the Harmonica index easy to understand. According to the Harmonica index the sound environment can be assessed as quiet, noisy and very noisy. The overview of the Harmonica index, the structure of Toots software for the Harmonica index calculation and an example of application of the Harmonica index for assessment of environmental noise in the city of Niš will be given in this paper.
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Vladimirov, Lyubomir, and Nikolay Kovachev. "STUDY OF THE ENVIRONMENTAL NOISE POLLUTION IN PRODUCTION ECONOMICAL ACTIVITIES." Journal scientific and applied research 4, no. 1 (October 10, 2013): 154–62. http://dx.doi.org/10.46687/jsar.v4i1.94.

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The paper presents results of a study of the environmental noise pollution in sewing and metal working manufacture and the harvester in agriculture. Indiscrete method for noise measurements were created. They are characterized by high precision, wide range of determination of the noise and large sample size of measured values. A probabilistic method for noise pollution assessment is introduced. Seven groups of indicators were used. The method is approbated in practice. The results show large coverage and accuracy.
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Nelson, David. "Long-term environmental noise measurement methods for industrial noise sources." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 266, no. 2 (May 25, 2023): 972–77. http://dx.doi.org/10.3397/nc_2023_0116.

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Industrial noise sources can impact nearby residential communities, especially in rural areas. In order to assess the situation after commissioning, plant noise must be reliably differentiated from prevailing ambient, transient environmental noises, and weather-related events. Continuously attending such measurements is generally impractical. On the other hand, classifying events by eyeballing a stream of Leq values after the fact isn't sufficiently reliable in most cases either. An effective approach is presented that involves measurement and statistical, observational, and analytical methods to perform much of the work in an automated fashion. Methods include statistically excluding transients from the Leq, filtering to eliminate birds and bugs, spectral characteristics of wind events, and potential spectral identifiers indicative of operation. Classifications are confirmed by listening to periodic and/or event-driven audio segments. This approach works best when both the plant noise and prevailing ambient are quasi-steady; plant-generated transients and weather events may require manual reclassification. Examples from long-term environmental noise studies are provided. The methods are neither dramatic nor novel but their effectiveness in combination may be useful, especially for those new to this type of work.
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Gagliano, Antonio, Francesco Nocera, Andrea Cicero, Luigi Marletta, and Gianpiero Evola. "Mitigation of environmental noise in urban streets through lightweight transparent screens." Noise Mapping 7, no. 1 (April 13, 2020): 57–73. http://dx.doi.org/10.1515/noise-2020-0005.

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AbstractNoise pollution is one of the main environmental stressors in urban areas. In particular, strong noise pollution can be experienced at nighttime in downtown areas with intense anthropic activities: here, dwellers may suffer from disturbance to their rest, which induces stress and – in turn – adverse effects on health.Usually, local authorities implement actions to tackle noise pollution, e.g. limiting the time allowed for outdoor events. However, these measures are often inadequate because the noise annoyance comes directly by the shouting of people spending time outdoors till late night.In this framework, this study proposes a procedure to optimize the shape of customized lightweight transparent noise screens that can be applied to façades in order to reduce noise disturbance in urban canyons. The case study of the “movida” area in the downtown of Marina di Ragusa (Southern Italy) is discussed to test the applicability of the proposed procedure.The results of this analysis allow defining the shape and the size of the noise screens that minimize the noise annoyance perceived by residents. The proposed mitigation approach can be applied in cities affected by significant noise pollution.
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Manley, David, and Joseph Horesco. "Amplified concert noise modeling with environmental noise software." Journal of the Acoustical Society of America 146, no. 4 (October 2019): 2827. http://dx.doi.org/10.1121/1.5136794.

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Dubbink, David T. "Presenting Environmental Noise Data Using Recorded Noise Examples." Noise Control Engineering Journal 41, no. 3 (1993): 351. http://dx.doi.org/10.3397/1.2827849.

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Bouamri, Mohammed, and Mourad Berrabah. "Environmental impact of seawater desalination plant: industrial noise calculation and simulation." STUDIES IN ENGINEERING AND EXACT SCIENCES 6, no. 1 (January 20, 2025): e13518. https://doi.org/10.54021/seesv6n1-017.

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Algeria has an expanding in seawater desalination plants. These plants have an environmental impact on humans and their environment. Among these impacts, we mention the noise pollution emitted by many noisy elements such as feed pumps (seawater intake pump), high pressure (HP) pumps, energy recovery devices (ERD), ERD feed booster pump (booster pumps), compressors and expedition pumps. The aim of this paper is to model and to simulate the noise effect in the case of one of the most important seawater desalination plants (200 000 m3/d) using reverse osmosis as a seawater desalination process which is the Beni Saf Water Company (BWC), Algeria. Noise modelling was undertaken using Code_Tympan noise modelling software to predict the effects of industrial noise generated by the Beni Saf seawater desalination plant. Noise mapping is used in our case to study the effect of noise, delineated the outline of these effects, which takes into account the topology of the industrial buildings, machines, information on meteorological conditions, dimensions, etc.
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BENEDETTI, CLAUDIA, FABRIZIO BUSCEMI, PAOLO BORDONE, and MATTEO G. A. PARIS. "EFFECTS OF CLASSICAL ENVIRONMENTAL NOISE ON ENTANGLEMENT AND QUANTUM DISCORD DYNAMICS." International Journal of Quantum Information 10, no. 08 (December 2012): 1241005. http://dx.doi.org/10.1142/s0219749912410055.

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We address the effect of classical noise on the dynamics of quantum correlations, entanglement and quantum discord (QD), of two non-interacting qubits initially prepared in a Bell state. The effect of noise is modeled by randomizing the single-qubit transition amplitudes. We address both static and dynamic environmental noise corresponding to interaction with separate and common baths in either Markovian and non-Markovian regimes. In the Markov regime, a monotone decay of the quantum correlations is found, whereas for non-Markovian noise sudden death and revival phenomena may occur, depending on the characteristics of the noise. Entanglement and QD show the same qualitative behavior for all kind of noises considered. On the other hand, we find that separate and common environments may play opposite roles in preserving quantum correlations, depending on the noise regime considered.
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Xiao, Tong, Benjamin Halkon, Sipei Zhao, Ben Cooper-Woolley, Fergus Strange, and Adam Ferguson. "Environmental noise tagging via audio spectrogram transformer." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 1 (November 30, 2023): 7394–400. http://dx.doi.org/10.3397/in_2023_1125.

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Environmental noise pollution is a significant concern for public health and well-being. It is important to accurately identify and classify environmental noise sources to develop effective noise reduction strategies. This paper examines using an audio spectrogram transformer (AST) for environmental noise tagging tasks. The AST is a pure attention-based model that takes the spectrograms of the audio signals as input and calculates the self-attention without convolutions. Previously, it was pre-trained on large datasets such as ImageNet and AudioSet, showing higher precision than prior work. Although the hyperparameters were given, many have not been clear from the previous literature. Results show that there are a few choices for the patch split overlap, more overlap does not result in significantly improved performance. It is also shown that instead of the default 128 frequency bins, 96 is another choice, which can reduce the computations. The results further show that 30% - 40% can be masked for the frequency, 20% - 50% for the time dimension. The trained model is further tested on the dataset of different environmental noise sources collected by SiteHive Hexanodes across Australia and New Zealand. Results show that the AST model can achieve high accuracy in identifying different environmental noises.
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Badaracco, Francesca. "Environmental noises in current and future gravitational-wave detectors." Journal of Physics: Conference Series 2156, no. 1 (December 1, 2021): 012077. http://dx.doi.org/10.1088/1742-6596/2156/1/012077.

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Abstract Gravitational–wave (GW) detectors are very sensitive instruments that suffer from a huge number of noises. If we aim to observe gravitational waves with earthbound detectors, we need to take care of every source that can prevent the observation. Seismic noise poses a huge challenge to the sensitivity in the the low-frequency band and it is tackled with suspensions and active controls. The low–frequency band can also be threatened by the so–called Newtonian noise, generated by the fluctuations of the gravity field. If this has not been a problem in the first generation gravitational-wave detectors, it will be so in the next runs and especially in the third–generation detectors, like the Einstein Telescope. We need then to be prepared to suppress as much as possible these noises, otherwise they might become the last wall for the sensitivity of our detectors. This manuscript will explore environmental noises with a particular detail on Newtonian and seismic noise and the techniques that we can employ to reduce their effects.
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Alani, Rose Anthony, Olajomi Mary Ogunmoyela, Chukwuma John Okolie, and Olagoke Emmanuel Daramola. "Geospatial analysis of environmental noise levels in a residential area in Lagos, Nigeria." Noise Mapping 7, no. 1 (October 27, 2020): 223–38. http://dx.doi.org/10.1515/noise-2020-0019.

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AbstractNoise is an inevitable part of daily life and has been identified as a cause of several health deficiencies across the world. It has increasingly become a significant concern on the health and well-being of people. Studies are required to advance knowledge on the sources and impacts of noise in residential neighbourhoods of Lagos State, Nigeria. Therefore, this study assesses the spatial variation of noise levels within a section of the Festac residential area in Lagos in line with noise limits specified by the World Bank Group International Finance Corporation (IFC) Environmental, Health, and Safety (EHS) Guidelines and the Nigerian National Environmental Standards and Regulations Enforcement Agency (NESREA) Noise Standards and Control guidelines for community noise. Data for this research come from a field study comprising measurements of noise levels from 6 observation stations and questionnaire survey with 200 respondents. The criteria for siting the stations was based on factors such as proximity to the roadside, land use and population density, while the questionnaire was administered at random to assess the peoples’ level of awareness on the sources and effects of noise. A digital sound level meter was used to measure noise level variations over a period of 3 weeks for morning, afternoon and evening periods. The measured noise levels were analysed using Analysis of Variance (ANOVA) statistics and the Kriging Geostatistical interpolation technique. Also, logistic regression was used to determine the relationship between the respondents’ perceptions to noise and noise levels. The results indicated that the mean noise levels were within the approximate range of 53.5 – 94.0dBA over the entire period. The highest mean noise levels occurred in the north-western part of the study area where a bus park is present. In general, the noise levels in the area surpass the recommended noise limit of 55dBA, and the logistic regression showed that morning, afternoon and evening mean noise levels were significant predictors of noise variation as perceived by the dwellers. Proper legislation to regulate human activities with respect to noise generation is highly recommended to the local, state and national legislators.
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Lee, Jeong-Geun, Kwang Sik Kim, and Jang Hyun Lee. "Sound-Based Unsupervised Fault Diagnosis of Industrial Equipment Considering Environmental Noise." Sensors 24, no. 22 (November 16, 2024): 7319. http://dx.doi.org/10.3390/s24227319.

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The influence of environmental noise is generally excluded during research on machine fault diagnosis using acoustic signals. This study proposes a fault diagnosis method using a variational autoencoder (VAE) and domain adaptation neural network (DANN), both of which are based on unsupervised learning, to address this problem. The proposed method minimizes the impact of environmental noise and maintains the fault diagnosis performance in altered environments. The fault diagnosis algorithm was implemented using acoustic signals containing noise, present in the malfunctioning industrial machine investigation and inspection open dataset, and the fault prediction performance in noisy environments was examined based on forklift acoustic data using the VAE and DANN. The VAE primarily learns from normal state acoustic data and determines the occurrence of faults based on reconstruction error. To achieve this, statistical features of Mel frequency cepstral coefficients were extracted, generating features applicable regardless of signal length. Additionally, features were enhanced by applying noise reduction techniques via magnitude spectral subtraction and feature optimization, reflecting the characteristics of rotating equipment. Furthermore, data were augmented using generative adversarial networks to prevent overfitting. Given that the forklift acoustic data possess time-series characteristics, the exponentially weighted moving average was determined to quantitatively track time-series changes and identify early signs of faults. The VAE defined the reconstruction error as the fault index, diagnosing the fault states and demonstrating excellent performance using time-series data. However, the fault diagnosis performance of the VAE tended to decrease in noisy environments. Moreover, applying DANN for fault diagnosis significantly improved diagnostic performance in noisy environments by overcoming environmental differences between the source and target domains. In particular, by adapting the model learned in the source domain to the target domain and considering the domain differences based on signal-to-noise ratio, high diagnostic accuracy was maintained regardless of the noise levels. The DANN evaluated interdomain similarity using cosine similarity, enabling the accurate classification of fault states in the target domain. Ultimately, the combination of the VAE and DANN techniques enabled effective fault diagnosis even in noisy environments.
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Albaji, Ali Othman, Rozeha Bt A. Rashid, and Siti Zeleha Abdul Hamid. "Investigation on Machine Learning Approaches for Environmental Noise Classifications." Journal of Electrical and Computer Engineering 2023 (May 31, 2023): 1–26. http://dx.doi.org/10.1155/2023/3615137.

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This project aims to investigate the best machine learning (ML) algorithm for classifying sounds originating from the environment that were considered noise pollution in smart cities. Sound collection was carried out using necessary sound capture tools, after which ML classification models were utilized for sound recognition. Additionally, noise pollution monitoring using Python was conducted to provide accurate results for sixteen different types of noise that were collected in sixteen cities in Malaysia. The numbers on the diagonal represent the correctly classified noises from the test set. Using these correlation matrices, the F1 score was calculated, and a comparison was performed for all models. The best model was found to be random forest.
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MARKUS, Miklos. "Environmental noise protection problems of Hungary's old heavy industrial areas." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 270, no. 2 (October 4, 2024): 9720–27. http://dx.doi.org/10.3397/in_2024_4291.

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Hungary's first domestic environmental noise regulation entered into force in 1984. Several heavy industrial areas operate in the country, which were established in the first half of the last century or in the decades following the Second World War. During this period, aspects of environmental noise protection were not yet considered. These heavy industry plants are usually located in huge industrial areas, operate thousands of diverse technological equipment and still remain significant factors of the Hungarian national economy. The reason for the development of the environmental noise problem is that during the intensive socialist industrialization, to satisfy the huge demand for labor, they developed residential areas around the industrial areas. This led to a situation, when environmental noise protection legislation came into force, these heavy industry plants found themselves in violation without any changes in their operations. The plants implemented noise reductions and attempted to comply with the limits, but mostly with little success. This presented an unsolvable problem to the plants, the authorities, and the residents too. The solution to the problem is the introduction of regulations on the designated highly noisy areas and several additional measures, following the international practice of designating noise protection zones.
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Hintzsche, Matthias. "Environmental Noise Directive ‐ results of noise mapping in Germany." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3136. http://dx.doi.org/10.1121/1.2933099.

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Cheng, Hsiu-Lien, Ji-Yan Han, Wei-Zhong Zheng, Yen-Fu Cheng, Yuan-Chia Chu, Chia-Mei Lin, Ming-Chang Chiang, Wen-Huei Liao, and Ying-Hui Lai. "Objective Signal Analysis for Investigating Feasibility of Active Noise Cancellation in Hearing Screening." Sensors 22, no. 19 (September 27, 2022): 7329. http://dx.doi.org/10.3390/s22197329.

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With the development of active noise cancellation (ANC) technology, ANC has been used to mitigate the effects of environmental noise on audiometric results. However, objective evaluation methods supporting the accuracy of audiometry for ANC exposure to different levels of noise have not been reported. Accordingly, the audio characteristics of three different ANC headphone models were quantified under different noise conditions and the feasibility of ANC in noisy environments was investigated. Steady (pink noise) and non-steady noise (cafeteria babble noise) were used to simulate noisy environments. We compared the integrity of pure-tone signals obtained from three different ANC headphone models after processing under different noise scenarios and analyzed the degree of ANC signal correlation based on the Pearson correlation coefficient compared to pure-tone signals in quiet. The objective signal correlation results were compared with audiometric screening results to confirm the correspondence. Results revealed that ANC helped mitigate the effects of environmental noise on the measured signal and the combined ANC headset model retained the highest signal integrity. The degree of signal correlation was used as a confidence indicator for the accuracy of hearing screening in noise results. It was found that the ANC technique can be further improved for more complex noisy environments.
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41

Arthur, Tsamouo Tsokeng, Tchoffo Martin, and Lukong Cornelius Fai. "Quantum correlations and coherence dynamics in qutrit–qutrit systems under mixed classical environmental noises." International Journal of Quantum Information 15, no. 06 (September 2017): 1750047. http://dx.doi.org/10.1142/s0219749917500472.

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We investigate the dynamics of entanglement, quantum discord (QD) and state coherence in a bipartite and noninteracting spin-qutrits system under mixed classical noises. Specifically, the collective effects of static noise (SN) and random telegraphic noise (RTN) each being coupled with a marginal system, are analyzed. While the static noise models a non-Markovian environment, the dynamic noise can model both a Markovian or a non-Markovian environment, and both dynamics are studied. We show that quantum correlations and coherence may survive the noise degrading effects at sufficiently long time when the Markovian regime of the RTN is considered. Meanwhile, the opposite is found in the non-Markovian regime, wherein the nonmonotonic dynamics of quantum features avoid sudden death phenomena. However, the static noise is more fatal to the survival of quantum correlations and quantum state coherence as compared to the RTN.
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42

Yonemura, Miki, Hyojin Lee, and Shinichi Sakamoto. "Subjective Evaluation on the Annoyance of Environmental Noise Containing Low-Frequency Tonal Components." International Journal of Environmental Research and Public Health 18, no. 13 (July 3, 2021): 7127. http://dx.doi.org/10.3390/ijerph18137127.

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Recently in Japan, noises from wind turbines and domestic use heat sources sometimes cause an increase in noise annoyance owing to low-frequency tonal components. The purpose of this study was to investigate the effects of the tonal components on the annoyance of the environmental noise. The authors conducted an auditory test in the laboratory to evaluate the annoyance of tonal noise using a seven-step rating method. The stimuli were composed of a broadband noise modeling of the environmental noise (25, 30, and 35 dB) and a low-frequency tonal component. With the tonal component added to the broadband noise, the frequency and tonal audibility were varied to 40, 50, 100, 200, and 400 Hz and 0, 3, 6, 9, and 12 dB, respectively. The amount of increase in annoyance owing to the addition of the tonal component was quantitatively evaluated as a tonal adjustment by comparing it with broadband noise. As a result, tonal adjustment ranged from 0 to 7 dB, and the higher the tonal frequency, the larger the value. For the test background noise level, the lower the background noise level of the test sound, the greater the value. This trend suggests that the influence of tonal components on subjective impressions is stronger in quiet environments such as residential areas. This result may provide a basis for the evaluation method, which varies the penalty in the noise evaluation according to the frequency of the pure tones and the noise level.
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Yang, Wonyoung, Hyeun Jun Moon, and Myung-Jun Kim. "Combined effects of short-term noise exposure and hygrothermal conditions on indoor environmental perceptions." Indoor and Built Environment 27, no. 8 (April 7, 2017): 1119–33. http://dx.doi.org/10.1177/1420326x17703774.

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Realistic thermal conditions with various humidity levels have been considered to examine the combined effects of noise and thermal conditions on indoor environmental perceptions. Subjective assessments of temperature, humidity and psychoacoustics were conducted with 26 subjects under combined environments of seven thermal conditions (18℃: RH 30, 60%, 24℃: RH 27, 43, 65%, 30℃: RH 30, 60%), two noise types (fan and babble noises) and five noise levels (45, 50, 55, 60 and 65 dBA). Three-minute moderate noise exposure did not affect temperature or humidity sensations. However, the temperature and humidity levels affected loudness, annoyance and acoustic preferences when noise was presented as babble. Fan noise perceptions were found to be independent of thermal conditions. Gender differences were clearly found in terms of thermal and psychoacoustic perceptions. Men were more sensitive to hot sensations than women, and women were more sensitive to arid sensations than men. Women were more sensitive to noise levels than men. Gender differences were also found in terms of different types of noise. Men were found to be significantly less sensitive to fan noise than women. Even though psychoacoustic parameters were affected by indoor thermal conditions, thermal parameters were not affected by short-term moderate noise. The combined effect of various types of noise and temperature is still unclear, and this will be considered in a future larger cohort study.
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44

FUJIMORI, Shigeyuki. "Consideration of new "Environmental standard which concerns noise". "Environmental standard which concerns noise" and environmental impact assessment." Journal of Environmental Conservation Engineering 28, no. 10 (1999): 731–36. http://dx.doi.org/10.5956/jriet.28.731.

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Alías, Francesc, Rosa Ma Alsina-Pagès, Ferran Orga, and Joan Claudi Socoró. "Detection of Anomalous Noise Events for Real-Time Road-Traffic Noise Mapping: The Dynamap’s project case study." Noise Mapping 5, no. 1 (July 1, 2018): 71–85. http://dx.doi.org/10.1515/noise-2018-0006.

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Abstract Environmental noise is increasing year after year, especially in urban and suburban areas. Besides annoyance, environmental noise also causes harmful health effects on people. The Environmental Noise Directive 2002/49/EC (END) is the main instrument of the European Union to identify and combat noise pollution, followed by the CNOSSOS-EU methodological framework. In compliance with the END legislation, the European Member States are required to publish noise maps and action plans every five years. The emergence of Wireless Acoustic Sensor Networks (WASNs) have changed the paradigm to address the END regulatory requirements, allowing the dynamic ubiquitous measurement of environmental noise pollution. Following the END, the LIFE DYNAMAP project aims to develop a WASN-based low-cost noise mapping system to monitor the acoustic impact of road infrastructures in real time. Those acoustic events unrelated to regular traffic noise should be removed from the equivalent noise level calculations to avoid biasing the noise map generation. This work describes the different approaches developed within the DYNAMAP project to implement an Anomalous Noise Event Detector on the low-cost sensors of the network, considering both synthetic and real-life acoustic data.Moreover, the paper reflects on several open challenges, discussing how to tackle them for the future deployment of WASN-based noise monitoring systems in real-life operating conditions.
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Campos, L. M. B. C. "Environmental Concerns: Noise and Emissions." International Journal of Acoustics and Vibration 25, no. 4 (December 30, 2020): 488. http://dx.doi.org/10.20855/ijav.2020.25.4e98.

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Kotzen, B. "PLANTS AND ENVIRONMENTAL NOISE BARRIERS." Acta Horticulturae, no. 643 (January 2004): 265–75. http://dx.doi.org/10.17660/actahortic.2004.643.34.

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Zhang, Hai Ying, and Guo Xian Ma. "Developing of Environmental Noise Control." Applied Mechanics and Materials 249-250 (December 2012): 1264–67. http://dx.doi.org/10.4028/www.scientific.net/amm.249-250.1264.

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Environmental noise control is a compulsory special course for students of Environmental Engineering. Through leaning this course, the students should know basic knowledge of noise, noise control technologies and how to test and control environmental noise. With increasing importance attached on environment, requirement of noise control is more stringent than ever before. In order to maintain the competitiveness of undergraduates, it is necessary to give the course in bilingual language, especially those who study in Environmental Engineering. This paper first analyzes the characteristics and probes the problems of this course. Then it proposes a developing plan for the course from the following aspects: necessity of learning this course, course aims, course content, related courses and teaching methods.
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Vasseur, David A., and Peter Yodzis. "THE COLOR OF ENVIRONMENTAL NOISE." Ecology 85, no. 4 (April 2004): 1146–52. http://dx.doi.org/10.1890/02-3122.

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50

Cavanaugh, W. J. "Progress in environmental noise control." Journal of the Acoustical Society of America 91, no. 4 (April 1992): 2393. http://dx.doi.org/10.1121/1.403306.

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