Noise Related Issues Research Articles

Exploring the Therapeutic Potential of Acoustic Interventions in Healing Environments

High noise levels in hospitals pose risks to both patients and staff, inducing stress, discomfort, and restlessness. This study presents results from a noise survey conducted in a Dhaka teaching hospital, revealing daytime levels ranging from 48 to 63 dB LAeq, exceeding Bangladesh standards. Noise levels correlated with ward layout and sources, not patient demographics. Strategies such as noise reduction, acoustic materials, and staff/patient programs can improve hospital acoustics effectively. This study reviews research from multiple disciplines including medicine, psychology, architecture, and acoustics, focusing on topics such as hospital noise, sleep quality, patient privacy, and music therapy. Findings indicate hospitals often exceed recommended noise levels, negatively impacting patients and staff with sleep problems, higher blood pressure, and burnout. Poorly designed sound environments compromise patient privacy and communication. Strategies like private rooms, sound-absorbing materials, and music therapy are recommended to reduce noise levels and improve communication. To enhance patient confidentiality, private rooms with sound-blocking features are suggested. Overall, the study underscores the importance of sound management in healthcare and advocates for design strategies to mitigate noise-related issues while ensuring effective communication. KEY WORDS: Noise, patient, acoustic, healthcare, hospital.

Pedagogical strategies to enhance learning and awareness of acoustics within our engineering school community

Acoustics is taught at the École de technologie supérieure (ÉTS, Montreal, Canada) in a single advanced specialization course during the final year of the mechanical engineering bachelor's program. This course aims to equip students with the skills needed to measure and reduce noise based on the theoretical foundations of industrial acoustics and associated experimental techniques. The fact that the science of acoustics is not well-known among engineering students, coupled with the optional nature of this course, results in an average enrollment of only about thirty students each year (across two distinct sessions), a number further reduced since 2020 due to the unfortunate impact of the pandemic. Paradoxically, Quebec lacks engineers trained in this discipline and often recruits them from abroad. This presentation will aim to showcase various strategies and pedagogical tools that have been used and experimented with in recent years (e.g., flipped classroom, in-class experiments, cellphone measurements, community service-oriented semester projects). The goal is to ensure the quality and enjoyment of student learning and to contribute to raising awareness about acoustics and noise-related issues within the ÉTS community.

Subjective Response Test of Auralized Brushless Direct Current Motor-Propeller System Noise

The auralization can be an effective asset in the design of unmanned aerial vehicles (UAV) and urban air mobility vehicles, serving as a valuable resource in decision-making regarding the mitigation of noise-related issues. However, in order to be effective, the auralization must be perceptually accurate. During the process of auralization, a multirotor noise evaluation framework based on multidisciplinary principles was employed to model the periodical fluctuations in rotational speed. The subjective response test was utilized to evaluate synthesized UAV-like noise. The tests included participants becoming acquainted with different noise sources (ice-breaking), assessing participants' emotional responses to different noises (helicopter and UAV-like), and evaluating participants' ability to differentiate between measured and auralized sounds. Statistical analysis of the results of the subjective response test showed that the measured noise and the auralized noise were not identical, but were not perfectly indistinguishable. These results demonstrate the effectiveness of psychoacoustic methods and statistical analysis in the perceptual assessment of noise and validate a comprehensive rotor noise assessment framework based on a multidisciplinary approach.

A semi-agnostic ansatz with variable structure for variational quantum algorithms

Quantum machine learning—and specifically Variational Quantum Algorithms (VQAs)—offers a powerful, flexible paradigm for programming near-term quantum computers, with applications in chemistry, metrology, materials science, data science, and mathematics. Here, one trains an ansatz, in the form of a parameterized quantum circuit, to accomplish a task of interest. However, challenges have recently emerged suggesting that deep ansatzes are difficult to train, due to flat training landscapes caused by randomness or by hardware noise. This motivates our work, where we present a variable structure approach to build ansatzes for VQAs. Our approach, called VAns (Variable Ansatz), applies a set of rules to both grow and (crucially) remove quantum gates in an informed manner during the optimization. Consequently, VAns is ideally suited to mitigate trainability and noise-related issues by keeping the ansatz shallow. We employ VAns in the variational quantum eigensolver for condensed matter and quantum chemistry applications, in the quantum autoencoder for data compression and in unitary compilation problems showing successful results in all cases.

Development of a real-time noise estimation model for construction sites

As construction noise negatively affects the health and quality of life of stakeholders, field managers need to properly monitor and manage noise. Thus, the authors developed a model that estimates real-time noise levels at a construction site and the surroundings to enable preemptive responses to noise-related issues. To accurately estimate noise, necessary field data were collected using an unmanned aerial vehicle (UAV) and noise sensors. The noise estimation model was composed of two sub-models: the noise-customized spatial interpolation model and the noise propagation model. The noise-customized spatial interpolation model was developed to estimate the internal noise of the construction site using a few sensor noise levels. Meanwhile, the noise propagation model was developed to estimate the noise level outside the construction site using internal noise estimation results, obstacles, weather information, and noise sources information. The model was evaluated through field tests at a construction technology demonstration center, environments identical to real construction sites in South Korea. The model showed satisfactory performance, with an accuracy of 96.71% and a root mean square error (RMSE) of 2.62 for the internal construction site noise and an accuracy of 96.03% and an RMSE of 2.70 for outside the construction site. To facilitate the usage of the noise estimation results for field managers, the research team visualized the results using the Unity 3D Engine. The results will enable field managers to assess workers’ long-term noise exposure and respond to potential civil complaints, gearing up to realize environmental, social, and governance (ESG) goals in the construction industry.

Implementation and parametric study of J-integral data reduction methods for the translaminar toughness of hierarchical thin-ply composites

Three different J-integral formulations to derive the experimental translaminar toughness of composites from compact tension tests with a large-scale fracture process zone are implemented and discussed. They improve the existing approaches by taking advantage of stereo-digital image correlation to acquire full-field displacement fields. A field fitting procedure based on robust and efficient piecewise cubic smooth splines addresses noise-related issues reported in previous studies. Additionally, the paper proposes a novel crack tip extraction procedure to report the energy release rate as a function of the crack increment, even if knowledge of the crack tip is not required for the proposed J-integral method. The three methods are discussed in light of a parametric study conducted on synthetic and experimental data, including artificially noisy data. The study reveals that the proposed J-integral methods are suitable for translaminar toughness evaluation of a wide range of materials without the need for restrictive assumptions. However, variations in propagation values were observed when applied to experimental data. Finally, guidelines are drawn to chose the most suitable parameters for the algorithms that are proposed as a Python package.

A Novel Generative Adversarial Network-Based Approach for Automated Brain Tumour Segmentation.

Background: Medical image segmentation is more complicated and demanding than ordinary image segmentation due to the density of medical pictures. A brain tumour is the most common cause of high mortality. Objectives: Extraction of tumorous cells is particularly difficult due to the differences between tumorous and non-tumorous cells. In ordinary convolutional neural networks, local background information is restricted. As a result, previous deep learning algorithms in medical imaging have struggled to detect anomalies in diverse cells. Methods: As a solution to this challenge, a deep convolutional generative adversarial network for tumour segmentation from brain Magnetic resonance Imaging (MRI) images is proposed. A generator and a discriminator are the two networks that make up the proposed model. This network focuses on tumour localisation, noise-related issues, and social class disparities. Results: Dice Score Coefficient (DSC), Peak Signal to Noise Ratio (PSNR), and Structural Index Similarity (SSIM) are all generally 0.894, 62.084 dB, and 0.88912, respectively. The model's accuracy has improved to 97 percent, and its loss has reduced to 0.012. Conclusions: Experiments reveal that the proposed approach may successfully segment tumorous and benign tissues. As a result, a novel brain tumour segmentation approach has been created.

Intelligent Geodemographic Clustering Based on Neural Network and Particle Swarm Optimization

Most of the techniques involved in customer clustering and segmentation are based on conventional methods of quantitative analysis or traditional data mining approaches such as the K-Means algorithm. However, clustering approaches based on artificial neural networks (ANNs), evolutionary algorithms, and fuzzy methods can be more efficient since they can reveal nonlinear patterns. They also seem to be more robust in coping with noise-related issues and relevant noise handling operations. They do not make any statistical distributional assumptions regarding the nature of the data. In this article, we develop a hybrid approach based on ANNs and swarm intelligence to reveal the underlying pattern structure of customers of an insurance company in the Republic of Ireland. This model is tailored to the scope of segmenting administrative districts, or “small areas,” given policyholders’ spatial characteristics. To that end, the geospatial features of customers are taken into account. Geodemographically speaking, by implementing such a hybrid model, the relative similarity among spatial objects (small areas in this work) are preserved. In this way, the similarity of each small area to all other small areas is characterized. Consequently, the pattern of customers is analyzed using an optimal and intelligent solution. We can also visualize the results of this study.

Citizen Science as Part of the Primary School Curriculum: A Case Study of a Technical Day on the Topic of Noise and Health

In this paper, we summarise lessons learned conducting citizen science (CS) activities within the CitieS-Health H2020 project on the topic of noise exposure and health at a primary school in Ljubljana, Slovenia. Activities were organised in the form of a School Tech-Day Event (STDE) as part of the school’s curriculum involving second-grade pupils, ages 7–8. The STDE was aligned with the project’s methodological framework, which is based on co-creation and co-design principles. To this end, the pupils initially were involved in identifying noise-related issues and translation of selected topics into research questions. Next, together with mentors, they participated in the process of hypothesis formulation and the designing of data collection protocols. Finally, they participated in three focussed noise measurement experiments, as well as data analysis and presentation. We report and critically evaluate the whole chain of activities, focussing on the participant dimension using selected components of the citizen science evaluation framework. The event was very well-received by both pupils and teachers, and their active participation and hands-on experience with scientific processes contributed to their improved scientific literacy. Overall, the demonstrated concept of CS activities has great potential for ongoing inclusion in the school curriculum in its current format, or else adjusted according to specifics from other science and technology fields.

RETRACTED: A Hybrid Approach for Plant Leaf Disease Detection and Classification Using Digital Image Processing Methods

Detection of plant leaf disease has been considered an interesting research field which is helpful to improve the crop and fruit yield. Computer vision and machine learning based approaches have gained huge attraction in digital image processing field. Several visual computing based techniques have been presented in the past for early prediction of plant leaf diseases. However, detection accuracy is still considered as a challenging task. Hence, in order to overcome this issue, we introduce a novel hybrid approach carried out in three forms. During the first phase, image enhancement and image conversion scheme are incorporated, which helps to overcome the low-illumination and noise related issues. In the next phase, a combined feature extraction technique is developed by using GLCM, Complex Gabor filter, Curvelet and image moments. Finally, a Neuro-Fuzzy Logic classifier is trained with the extracted features. The proposed approach is implemented using MATLAB simulation tool where PlantVillage Database is considered for analysis. The average detection accuracy has been obtained as more than 90% for 2 test cases which shows that the proposed combination of feature extraction and image pre-processing process is able to obtain improved classification accuracy. This work is useful for the students of UG/PG programme to carry out Project-based learning.

Workplace noise assessments by open-plan office occupants: Relationship with ISO 3382-3 metrics, and psychoacoustic parameters

ISO 3382-3:2012 is the international standard for measuring the acoustics of open-plan offices. These measurements are performed in unoccupied offices, and it has recently been shown that some of the ISO 3382-3 metrics, especially distraction distance, are useful in predicting the occupants’ perceived disturbance due to noise. The current research compares the ISO 3382-3 metrics, with several psychoacoustic parameters (loudness, fluctuation strength, etc.) derived from measurements done in an occupied state of open-plan offices, in terms of their usefulness in predicting occupants’ perception of several aspects of workplace noise. This comparison was based on using measurements performed in several offices in both occupied and unoccupied states, along with a workplace noise survey that was conducted in these offices. The results will enable a more comprehensive understanding of noise-related issues in open-plan offices, as it involves both physical acoustic, and psychoacoustic considerations.

Construction Noise Prediction Model Based on Case-Based Reasoning in the Preconstruction Phase

AbstractConstruction activities are associated with various noise-related issues, including health problems, cost overruns, and schedule delays. These issues could be averted by conducting comprehe...

Noise Control Plans in Cities – Selected Issues and Necessary Changes in Approach to Measures and Methods of Protection

The Directive (2002) establishing the assessment and management of environmental noise mandates that the Member States of the EU to prepare action plans to manage noise-related issues and consequences of acoustic impact on areas adjacent to the busiest roads, railway lines, main airports and the biggest agglomerations. Every five years there are environmental noise control plans developed in the EU countries for the biggest cities with a population exceeding 100 thousand inhabitants. Each plan contains a set of proposed remedial measures aimed at improving noise conditions of the areas that have the greatest number of inhabitants exposed to noise above the limit values. As a rule, a few selected remedial measures are possible to apply in those areas and their combined effect is meant to result in a sensible improvement of noise conditions. In most programs, the tasks related to protection against environmental noise are based on single methods, which often present little effectiveness and are unrelated to other programs and policies.The present report describes the results of studies and analyses that were performed in most Polish cities where noise control plans were delivered. The studies enabled to determine the basic problems encountered in relation to noise control plans as well as issues confronted while adopting actual measures protecting the environment against noise. The conclusion points out the necessity to introduce changes in the approach to noise protection measures and methods in cities.

Design and Optimization of Wafer-Level Compression Molding Process for One Chip Plus Multiple Decaps

Decaps are the panacea for the noise-related issues. Due to the short distance advantage, decaps are embedded in the fan-out wafer-level package instead of the printed circuit board. These decaps, generally thicker than chips, will have a crucial influence on the molding process as well. A lot of issues are encountered in the molding process, especially with lots of decaps, i.e., voids issues, incomplete filling issues, and die shift issues. In an optimized design, all these issues should be prevented or reduced as much as possible. In this paper, design flow for the wafer-level molding process is demonstrated and design guidelines are provided. Three important evaluation standards are used to evaluate the design, i.e., incomplete filling, drag force, and voids. Two kinds of design parameters, structure parameters (i.e., die placement, die size and thickness, and so on) and process parameters (i.e., vacuum pressure, filling speed, and so on), are optimized in the whole study. Optimization of these parameters helps the real wafer-level molding process to be conducted smoothly.

Design and Stability Analysis of a Frequency Controlled Sliding-Mode Buck Converter

Power management of mobile digital systems-on-chip necessitates large voltage regulation performances. DC/DC converters used to supply digital cores are facing stringent constraints with respect to load transients, reference tracking and accuracy. The fast transient response offered by sliding-mode control is well suited to DC/DC converters with fast varying load. Fixed switching-frequency is also mandatory for EMI and noise related issues. Fixed-switching frequency sliding-mode control has been experimented as a multi-loop system. There is a necessity to investigate the stability when multi-loops interact and the parameter set for each loop is quite large. The paper details a methodology for the stability analysis of a frequency-controlled sliding-mode DC/DC converter. The proposed stability analysis takes the possible cross-interactions into account and can be used to optimise the DC/DC controller without the limitations of a non-interaction criterion. As a verification a DC/DC converter is implemented in CMOS 130 nm. Experimental results agree with the analysis main recommendations.

Mapping deciduous forests by using time series of filtered MODIS NDVI and neural networks

Multi-temporal images are now of standard use in remote sensing of vegetation during monitoring and classification. Temporal vegetation signatures (i. e., vegetation indices as functions of time) generated, poses many challenges, primarily due to signal to noise-related issues. This study investigates which methods generate the most appropriate smoothed curves of vegetation signatures on MODIS NDVI time series. The filtering techniques compared were the HANTS algorithm which is based on Fourier analyses and Wavelet temporal algorithm which uses the wavelet analysis to generate the smoothed curves. The study was conducted in four different regions of the Minas Gerais State. The smoothed data were used as input data vectors for vegetation classification by means of artificial neural networks for comparison purpose. A comparison of the results was ultimately discussed in this work showing encouraging results and similarity between the two filtering techniques used.

What knowledge do ICU nurses have with regard to the effects of noise exposure in the Intensive Care Unit?

This small-scale study was undertaken to assess what knowledge nursing staff from a General Intensive Care Unit held with regard to noise exposure. To assess knowledge a self-administered multiple-choice questionnaire was used. Rigorous peer-review insured content validity. This study produced poor results in terms of the knowledge nurses held with regard to noise related issues in particular the psychophysiological effects and current legislation concerning its safe exposure. Non-parametric testing, using Kruskal-Wallis found no significant difference between nursing grades, however, descriptive analysis demonstrated that the staff nurse grade (D and E) performed better overall. Whilst the results of this study may seem self-evident in some respects, it is the problems of exposure to excessive noise levels for both patients and hospital personnel, which are clearly not understood. The effects noise exposure has on individuals for example decreased wound healing; sleep deprivation and cardiovascular stimulation must be of concern especially in terms of patient care but more so for nursing staff especially the effects noise levels can have on cognitive task performance.

EHPnet: Noise Pollution Clearinghouse

Not all sound is bad, but too much of the wrong sounds harm your health. What many people don’t know is that everyday items such as lawn mowers and kitchen blenders can emit noise at hazardous levels. More than 30 million Americans work at al job where they are exposed to hazardous sound levels on a regular basis. One-third of Americans with some degree of hearing loss can attribute that loss to sound exposure. And the evidence is building to point toward other noise-related health effects. The Noise Pollution Clearinghouse (NPC) is one group whose mission is to foster awareness of noise-related issues. On the NPC’s website, located at http://www.nonoise.org/, visitors can find many different resources to learn about what noise pollution is and how it can be fought. The NPC has four ongoing campaigns: Quiet Classrooms, Quiet Lawns, Quiet Lakes, and Silencing Car Alarms. The Quiet Classrooms portion of the site offers tips to students, teachers, and others on how to make the learning environment as quiet as possible, while the Quiet Lawns page rates 40 different lawn mowers in terms of noisiness. The Quiet Lakes page features information on the noise caused by sport watercraft and what the NPC is doing to fight this noise source. The Silencing Car Alarms portion of the site tells why the NPC thinks car alarms should be outlawed and lists quieter alternatives for keeping cars safe from thieves. For the layperson, the NPC has assembled an online library of almost 50 articles, reports, and seminal documents from a variety of sources. Within this section is a dictionary of noise terms, a primer on environmental noise, and more technical documents from national and international experts. A separate library contains noise-related documents just from the U.S. Environmental Protection Agency. This page also links to the full text of the Noise Control Act and federal regulations from the Office of Noise Abatement and Control, as well as to Noise Effects Handbook: A Desk Reference to Health and Welfare Effects of Noise. This 10-chapter textbook was written by the Office of Noise Abatement and Control to address effects ranging from fetal impacts to how loss of hearing affects speech and other activities. Starting once more from the homepage, the Hearing Loss and Occupational Noise Library includes documents from the Occupational Health and Safety Administration, the National Institute for Occupational Safety and Health, and the Mining Safety and Health Administration. Located here are criteria, guides, and standards for protecting workers’ hearing, plus a bibliography of 2,500 references on hearing and ear protection, among other topics. The NPC also is building an online noise law library with federal, state, local, and European noise-related laws and regulations as well as proposed regulations. For people who want to put their knowledge to work, the NPC Resource Library page has links for activists, educational resources, upcoming noise conferences and meetings, and potential funding sources. The NPC also provides pages on its website for local noise organizations that could not otherwise afford to host their own sites.

Reciprocating Machinery Dynamics: Design and Analysis

9R5. Reciprocating Machinery Dynamics: Design and Analysis. - AS Rangwala (Center for Eng Tech, Cincinnati OH). Marcel Dekker, New York. 2001. 761 pp. CD-ROM included. ISBN 0-8247-0531-9. $195.00. Reviewed by EL Amromin and S Kovinskaya (Mechmath LLC, 2109 Windsong, Edmond OK 73034).In recent decades, diverse structural dynamics software has became an important tool in machinery design. However, the application of software requires from a designer or an engineer deep understanding of structural dynamics and physics of modeling machines. The author considers probably all significant mechanical, acoustical, thermal, and fluid-related processes in reciprocating machinery. Because of the comprehensive analysis of numerous processes that has to be taken into account in design, this book is an excellent textbook for students and a helpful guide for practicing engineers. The author has put together problems that the engineer can meet. There are conceptual design, dynamic analysis, problems of optimization, and corresponding measurements. Because reciprocating machinery is broadly used in numerous engines, pumps, and other devices, this book includes classification and construction of reciprocating machines. The dynamic analysis of the machinery in the book is based on several selected topics of classical vibration theory described in a few chapters that are thoughtfully distributed in the text. As was mentioned above, the range of described physical phenomena is very wide. It seems that a reader can find any problem related to this machinery. Reciprocating machinery transfers significant flux of energy, but some part of energy is spent for troubling vibration and noise. It is both a technical and environmental problem to reduce this. The book contains procedures for noise evaluation, methods to control noise, and some measurement and signal processing techniques. There are 14 chapters namely, Vibrational Theory Fundamentals, Classification and Construction of Reciprocating Machinery, The Crankshaft and Associated Components, Crank Mechanism Dynamics, Balancing of Periodic Inertia and Gas Pressure Loads, Torsional Vibrations, Flexural Vibrations, Advanced Analytical Methods, Vibration Measurement and Balancing, Applications from Computational Fluid Dynamics, Pressure Pulsations in Compressors and Pumps, Reciprocating Machinery Dynamics and Noise, Design Optimization, and Computer Programs Illustrating Case Histories. Fundamentals of vibration theory are introduced in Chapter 1. The overall description of contemporary reciprocating machinery in Chapter 2 and a detailed description of crankshafts in Chapter 3 give the necessary knowledge for any reader, regardless of his background. Chapter 4 gives initial information on dynamics of some selected devices. The general explanation on mechanical equilibrium of reciprocating machinery elements and their vibration is done in Chapters 5, 6, 7, and 11; the noise-related issues are discussed in Chapter 12. Chapters 8, 9, and 10 give an introduction to employment of analytical, experimental, and computational methods to the above mechanical problem. Some information on employment of custom software and design optimization can be found in Chapters 13 and 14. Each chapter has references and a bibliography and helpful solutions of example problems. The book’s mathematical basis looks optimal for the wide audience of engineers. There are several unavoidable differential equations where it is necessary for operations with principal categories, but many secondary details are avoided. The author prefers to discuss rather quite simple formulas, and this is generally reasonable in a textbook. The author’s intent is to describe a large variety of physical phenomena; their profound description would be impossible in this one book. All chapters are well illustrated, and figures are clear enough. One can find a weakness in their certain simplification; for example, flow-related measurements (like in Figs. 10.8, 10.10, 11.21) should be presented with dispersion that always occurs in experiments. However, such illustrations correspond to the author’s aim. Some definitions should be described with the additional conditions that are default. Nevertheless, based on an overall impression, Reciprocating Machinery Dynamics: Design and Analysis is an excellent textbook. Its price does not look too high, and it is appropriate for purchase by both libraries and individuals.