Digital Noise Research Articles

Methods of Real-Time Parametric Diagnostics for Marine Diesel Engines

Abstract Using modern high-performance microcontrollers with wireless interfaces, built-in ADCs and low overall consumption, we develop a portable, real-time parametric diagnostic system for marine engines. The system is based on the use of modern Android/iOS gadgets that receive information from sensors via Bluetooth and then carry out the necessary calculations and display charts and data in real time. The system developed here uses a combination of a gas pressure sensor in the working cylinder and a vibroacoustic sensor, which expands the diagnostic capabilities of marine diesel engines under operating conditions. This solution allows for diagnosis of the fuel injection system, the valve train mechanism, and several other engine systems. In order to develop a portable diagnostic system for marine diesel engines, it is first necessary to solve the problem of analytically determining top dead centre (TDC), since such a system does not use special sensors for this. An algorithm for determining TDC is proposed here, based on an analysis of the measured pressure diagram rather than its derivative, which minimises the influence of digital and analogue noise. Our algorithm for determining TDC and subsequent data synchronisation is applicable in the absence of information about the actual compression ratio in the cylinder, which is a typical scenario for modern engines with variable valve timing. The algorithm also works under conditions of only approximate data on the charge air pressure, which are refined during the iteration process. A formula is proposed for determining the initial TDC position. Parameters for irregular operation of the engine are considered, and can be calculated in real time using time diagrams of pressure and vibration. Methods for expressly assessing the stability of the functioning of the main engine systems by monitoring and analysing a number of successive operating cycles are considered. To assess the unevenness of operation of the engine, a dispersion estimate of the deviations in the main parameters is used. To enable a comprehensive assessment of the engine stability in real time, the CII (cycle irregularity index) criterion is developed. The data processing methods described in this article provide an accurate estimate of the indicated power, due to the precise determination of TDC, thereby enabling an analysis of the stability of the operating cycles, optimal tuning of the engine systems, and monitoring of the results during operation.

Neural network recognition system for video transmitted through a binary symmetric channel

The demand for transmitting video data is increasing annually, necessitating the use of high-quality equipment for reception and processing. The paper presents a neural network recognition system for videos transmitted via a binary symmetrical channel. The presence of digital noise in the data makes it challenging to recognize objects in videos even with advanced neural networks. The proposed system consists of a noise interference detector, a noise purification system based on an adaptive median filter, and a neural network for recognition. The experiment results demonstrate that the proposed system effectively reduces video noise and accurately identifies multiple objects. This versatility makes the system applicable in various fields such as medicine, life safety, physics, and chemistry. The direction of further research may be to improve the model neural network, increasing the database for training or using other noises for modeling.

Digital Image Noise Reduction Based on Proposed Smoothing and Sharpening Filters

In order to reduce noise in digital photographs, this paper provides a thorough analysis of sophisticated sharpness enhancement and image smoothing approaches. The research compares and contrasts different approaches, including well-known filters like Gaussian filter, Mean filter, Weighted Averaging filter, Laplacian filters, and Unsharp mask, with suggested strategies aimed at achieving optimal efficiency. The performance of these techniques is evaluated in several circumstances with speckle noise and Gaussian noise corrupted images. The results show how well the suggested strategy performs in terms of reducing noise, preserving image features, and improving overall image quality. The comparative advantage of the suggested technique over conventional filters is highlighted by comparative analysis. The study's conclusion offers information on the possible uses and future developments of these methods in practical image processing situations.

Literary Appreciation In A Cacophony

In the cacophony of the digital age, literary appreciation of literary works presents both unique challenges and opportunities. The rapid proliferation of digital platforms has transformed how literature is accessed, consumed, and interpreted. This research explores the evolving landscape of literary appreciation amidst the digital cacophony, highlighting both the advantages and drawbacks. It examines how digital tools and platforms facilitate broader access to diverse literary works, enabling global communities to engage with literature in unprecedented ways. However, it also acknowledges the potential dilution of deep reading practices and critical analysis in favor of quick consumption and superficial engagement. Furthermore, the research discusses strategies to cultivate meaningful literary appreciation in the digital age, emphasizing the importance of promoting deep reading, critical thinking, and cultural understanding. Ultimately, it underscores the enduring value of literature in fostering empathy, cultural appreciation, and intellectual growth amidst the digital noise.

Traversing the social media landscape: Digital health communications in 2024

Amidst a post-pandemic landscape marked by dis- and misinformation, new technologies, and platform shifts, health communications will need to be rightly balanced between convenience, quality, and trust to cut through the digital noise online. Navigating the dynamic social media terrain will require adherence to regulatory standards, while the adoption of new trends like artificial intelligence offers new approaches for content creation and audience insights. Medical communicators will need to harness the power of new technologies, employ content strategies tailored to audiences and platforms, and continue to measure social media metrics to stay ahead of the times and deliver effective and impactful campaigns.

Stewards or Manipulators? Knowledge Brokers’ Complex Positionality in Combating the COVID-19 Infodemic in Malawi

ABSTRACT In the era of the COVID-19 pandemic, the spread of misinformation has become a significant challenge, undermining public health efforts and causing confusion among the general population. Amidst this infodemic, knowledge brokers have emerged as crucial figures in combating the proliferation of false and misleading information. These individuals serve as vital intermediaries, bridging the gap between the scientific community and the broader society, ensuring that accurate and reliable information reaches the public. The paper explored 72 knowledge brokers’ experiences and challenges with the COVID-19 pandemic and vaccine science communication through the qualitative descriptive exploratory method, in Malawi. The findings revealed ineffective government engagement with communities, which side-lined knowledge brokers, enabled vaccine doubts; religious and political figures’ worldviews shaped COVID-19 narratives; and digital illiteracy overwhelmed brokers. These deficiencies left brokers vulnerable to myths about the pandemic and vaccines, which they propagated. Key challenges arose for knowledge brokers trying to navigate conflicting information needs. For instance, political interference and digital noise obstructed brokers from analysing issues fairly to serve their communities. Still, knowledge brokers became vital as local fact-checkers. Their unique position bridging online/offline spheres was core to brokers’ positionality, blending interpersonal credibility with virtual content interpretation. This paper proposes guidelines for community-rooted communication intermediaries to strengthen crisis resilience by diagnosing systemic constraints, mitigation strategies, and ethical imperatives. It reveals potential amidst pitfalls for contextual knowledge brokers promoting sound interpretations of science. Ultimately, substantive broker training and mentoring are essential to optimize roles while avoiding the spread of inadvertent misinformation.

Research on health monitoring and damage recognition algorithm of building structures based on image processing

With the continuous deepening of the urbanization process and the progress of science and technology, people transform nature and develop nature on a larger and larger scale, among which the most iconic transformation is a variety of building structures built by people. And with the passage of time, the building structure in the perennial wind and sun, there will be signs of “illness”, if not timely treatment, it will have a huge impact on the stability and safety of the building structure. Based on this, in this paper, according to the characteristics of crack identification on the surface of concrete structure, background subtraction algorithm is selected for image noise reduction processing. Through three steps of digital image noise reduction, crack extraction and crack parameter identification, the quantitative recognition of cracks is completed and a complete system of crack parameter identification is formed. The experimental results show that the machine learning model of building structure health monitoring and damage recognition algorithm proposed in this paper has excellent statistical performance, and the relative error accuracy of recognition can be controlled within 10%.

Application of Sports Video Image Analysis Based on Fuzzy Support Vector Machine

Sports video image has always been a hot topic in sports video processing. The theoretical and experimental analysis of digital image noise reduction technology is a challenging topic. In this paper, a sports video denoising algorithm is designed by combining the excellent characteristics of curvilinear transformation theory and fuzzy support vector machine. Firstly, the image with noise is curvilinear, and the conversion coefficient is obtained. Then, according to the distribution characteristics of the system noise, the system parameters are divided into space, and the system learning features are constructed. The fuzzy classification of high-frequency curves is realized using the adaptive threshold denoising method. Then, the noise reduction coefficient is reconstructed by the curve-wave method to obtain the processed image. The simulation results show that this method can overcome the pseudo-Gibbs effect effectively and suppress the noise well. This algorithm has a good application prospect in sports video image processing.

Effect of Digital Noise Reduction in Hearing Aids on Speech Intelligibility in Both Quiet and Noisy Environments.

Digital noise reduction (DNR) minimizes the effect of noise on speech signals by continuously monitoring frequency bands in the presence of noise. In the present study, we explored the effect of DNR technology on speech intelligibility in individuals using hearing aids (HAs) and investigated implications for daily use. Eighteen participants with bilateral moderate sensorineural hearing loss (aged 16-45 years) were included. Bilateral receiver-in-the-ear HAs were fitted in the participants. The adaptive and nonadaptive (with a signal-to-noise ratio (SNR) of +5 and -5 dB, respectively) Turkish matrix sentence test (TURMatrix) in noise and free-field hearing assessments, including hearing thresholds with hearing aids, speech recognition thresholds (SRT), and speech discrimination scores, were conducted in two different conditions: HA in the DNR-on and DNR-off conditions. No significant difference was observed between free-field hearing assessments with the HA in the DNR-off and DNR-on conditions (P > 0.05). Furthermore, the adaptive and nonadaptive TURMatrix revealed significant differences between the scores under the DNR-on and DNR-off conditions (P < 0.05). Nevertheless, under the DNR-on condition, there was no correlation between free-field hearing assessments with HA and TURMatrix results (P > 0.05). However, a significant correlation was observed between SRT scores with HA and TURMatrix scores (adaptive and nonadaptive, +5 and -5 dB SNR, respectively) under the DNR-off condition (P < 0.05). Our study findings suggest that DNR can improve speech intelligibility in noisy environments. Therefore, DNR can enhance an individual's auditory comfort by improving their capacity to grasp speech in background noise.

Modeling the relationship between listener factors and signal modification: A pooled analysis spanning a decade

The overarching goal of our work is to understand how listeners respond to hearing aid processing and consequently inform individualized hearing aid treatment. Our previous work demonstrated that individual cognitive abilities, age, and hearing loss contribute to variability in response to cumulative signal modifications introduced by hearing aid processing and background noise. Specifically, older individuals with poorer working memory and more hearing loss were more susceptible to signal modifications introduced by hearing aid processing. These relationships were established in independent studies involving systematic manipulations of compression, digital noise reduction, frequency lowering, or microphone directionality. In this study, we present a hierarchical pooled analysis of data collected from six previous studies to develop a unified statistical model of the relationships between response to signal modification and individual listener variables. Across studies, signal modification is quantified using a cepstral correlation metric that accounts for cumulative envelope distortions arising from hearing aid processing and background noise. The statistical model will determine how working memory, age, and degree of hearing loss mediate the relationship between signal modification and speech intelligibility in noise across a large dataset. Both inferential and predictive applications of the combined data and model will be discussed. [Work supported by NIDCD.]

The theoretical maximum intelligibility improvement that can be provided by hearing aids

One goal of hearing aids is to increase the intelligibility of speech by improving the signal-to-noise ratio through the use of directional microphones and/or digital noise reduction. With this objective in mind, an ideal hearing aid would output amplified target speech with a signal-to-noise ratio of +∞. However, even in this ideal scenario, vent effects would allow background noise to enter the ear canal via the direct sound path while also allowing amplified sound to escape from the ear canal. In this experiment, a range of hearing aid fittings were simulated to account for these vent effects. Hearing-impaired listeners were tested using the ideal simulated hearing aid, and the results will show the maximum theoretical hearing aid benefit.

A digital prediction compensation for DR improvement in CT DSM with digital noise coupling

AbstractThis paper presents a prediction‐based dynamic range (DR) compensation technique in continuous‐time (CT) delta ‐sigma modulator (DSM) with digital‐domain noise coupling (DNC) structure. A digital prediction technique is proposed to address the issue of maximum stable amplitude (MSA) loss caused by DNC. The proposed prediction method has been shown to significantly extend the MSA of CT DSM with DNC. Moreover, through the extension of MSA, the DR and SNDR is significantly improved. A CTDSM with proposed compensation achieves a SNDR of 85.1dB at ‐1dBFS and a DR of 89dB.

Revealing spoofing of classical radar using quantum noise

Electromagnetic remote sensing technologies such as radar can be misled by targets that generate spoof pulses. Typically, a would-be spoofer must make measurements to characterize a received pulse in order to design a convincing spoof pulse. The precision of such measurements is ultimately limited by quantum noise. Here we introduce a model of electromagnetic spoofing that includes effects of practical importance that were neglected in prior theoretical studies. In particular, the model includes thermal background noise and digital quantization noise, as well as loss in transmission, propagation, and reception. We derive the optimal probability of detecting a spoofer allowed by quantum physics. We show that heterodyne reception and thresholding closely approaches this optimal performance. Finally, we show that a high degree of certainty in spoof detection can be reached by Bayesian inference from a sequence of received pulses. Together these results suggest that a practically realizable receiver could plausibly detect a radar spoofer by observing errors in the spoof pulses due to quantum noise. Published by the American Physical Society 2024

The Effects of Signal to Noise Ratio, T60 , Wide-Dynamic Range Compression Speed, and Digital Noise Reduction in a Virtual Restaurant Setting.

Hearing aid processing in realistic listening environments is difficult to study effectively. Often the environment is unpredictable or unknown, such as in wearable aid trials with subjective report by the wearer. Some laboratory experiments create listening environments to exert tight experimental control, but those environments are often limited by physical space, a small number of sound sources, or room absorptive properties. Simulation techniques bridge this gap by providing greater experimental control over listening environments, effectively bringing aspects of the real-world into the laboratory. This project used simulation to study the effects of wide-dynamic range compression (WDRC) and digital noise reduction (DNR) on speech intelligibility in a reverberant environment with six spatialized competing talkers. The primary objective of this study was to determine the efficacy of WDRC and DNR in a complex listening environment using virtual auditory space techniques. Participants of greatest interest were listeners with hearing impairment. A group of listeners with clinically normal hearing was included to assess the effects of the simulation absent the complex effects of hearing loss. Virtual auditory space techniques were used to simulate a small restaurant listening environment with two different reverberation times (0.8 and 1.8 sec) in a range of signal to noise ratios (SNRs) (-8.5 to 11.5 dB SNR). Six spatialized competing talkers were included to further enhance realism. A hearing aid simulation was used to examine the degree to which speech intelligibility was affected by slow and fast WDRC in conjunction with the presence or absence of DNR. The WDRC and DNR settings were chosen to be reasonable estimates of hearing aids currently available to consumers. A WDRC × DNR × Hearing Status interaction was observed, such that DNR was beneficial for speech intelligibility when combined with fast WDRC speeds, but DNR was detrimental to speech intelligibility when WDRC speeds were slow. The pattern of the WDRC × DNR interaction was observed for both listener groups. Significant main effects of reverberation time and SNR were observed, indicating better performance with lower reverberation times and more positive SNR. DNR reduced low-amplitude noise before WDRC-amplified the low-intensity portions of the signal, negating one potential downside of fast WDRC and leading to an improvement in speech intelligibility in this simulation. These data suggest that, in some real-world environments that include both reverberation and noise, older listeners with hearing impairment may find speech to be more intelligible if DNR is activated when the hearing aid has fast compression time constants. Additional research is needed to determine the appropriate DNR strength and to confirm results in wearable hearing aids and a wider range of listening environments.

Digital image noise removal towards soybean and cotton plant disease using image processing filters

The processing of noisy images does not provide accurate outcomes. In most existing techniques, many filters have been employed to eradicate the noises and enhance the image quality. However, most of the works fail to generate enhanced outcomes because of degraded capability and increased time consumption. Hence, in the proposed research work, a novel pre-processing method called the optimization assisted cascaded filtering approach (OptCFA) is introduced. In the proposed Opt_CFA model, the Gaussian Amended Bilateral filter (GABF) is designed where the multilevel thresholds are calculated for the GABF outcomes. The filter parameters are optimized using the Amended Pelican optimization algorithm (AmPel) for first stage noise removal. The outcomes are then cascaded with an Extended Savitzky-Golay filter (E_SGF) for second stage noise removal. The proposed Opt_CFA model is a single approach with the integration of GABF, AmPel and E_SGF methods. In the results section, some existing pre-processing filters, like the median, bilateral, and Gaussian filters, are analyzed for comparison. The individual performance of GABF and E_SGF methods used in the proposed model are also analyzed. Through the proposed technique, the noises can be extensively removed, and the image quality can be greatly enhanced. Several existing filters are compared with the proposed model, whereas the results are analyzed using PYTHON.

Finding Your Niche as a Jazz Music Entrepreneur

Abstract: Since we continue to live in a digital age where billions of people are connected through the internet, and entrepreneurship opportunities become more realistic and accessible, an increasing number of jazz musicians are exploring ways where they can transform their art into a viable music business. "What does it take to run my own music business?" and "can I really have an independent and sustainable music career as a jazz artist?" are questions that are becoming increasingly common among student jazz musicians with entrepreneurial mindsets. The first step at achieving a viable music business is finding one's niche. Once a jazz entrepreneur finds their niche, they can then identify their target market. This Quick Hit aims to provide a method of approach to which jazz musicians can find their niche to stand out among the digital noise of other jazz competitors so they can identify their target market. Additionally, tips on how jazz educators can help their students find their niche will be discussed.

The electroacoustic performance of digital noise reduction systems in commercial hearing aids with Malay speech-plus-noise test signals

One of the most frequent complaints of hearing-impaired individuals is difficulty understanding speech in noisy environments. In order to improve listening comforts in background noise, digital noise reduction (DNR) has been incorporated into the hearing aid. However, each hearing aid manufacturer has their own proprietary algorithm for their DNR. Therefore, this study aimed to evaluate the efficacy of the DNR system in commercial hearing aids using the Malay speech-in-noise test. Electroacoustic testing has been performed on six hearing aids that have similar technology but different brands using newly developed Malay speech-in-noise test signals in the condition of DNR on and off. The total root-mean-square (RMS) gain reduction for each HA was calculated. The results show that the type of noise, the signal-to-noise ratio (SNR) and the gender of the speaker have a significant effect on the amount of gain reduction shown by the DNR of the tested hearing aids (p&lt;0.05). In conclusion, clinicians need to measure and understand methods to verify the functionality of DNR before fitting a patient's hearing aid to ensure its effectiveness in real life.

EXPERIMENTAL STUDIES OF NOISE POLLUTION OF MECHANICAL PROCESSING PLANTS

Purpose. Determination of noise pollution at the workplace of workers of metal-cutting machines of turning, milling and drilling groups. Methodology. An experimental study of the noise load at the workplace of workers working on lathes, milling and drilling group machines. The research was carried out using a testo 816-1 digital noise level meter, Sound Forge Pro software and a mathematical package for the formation of noise dependences on the type and mode of operation of the machines. Results. An experimental study of the noise load at the workplace of workers working on metal-cutting machines, namely universal lathe-screw-cutting machines (type 1K62 and CA6136), vertical milling machines (type 6P11A and F2-250), vertical milling machine with CNC (type XS5036C) and radial drilling machine (type 2L53U). In addition, it was established that the type of machine affects the level of noise pollution at the workplace of metal-cutting machine workers. For example, the machines used for drilling are characterized by high noise values in all octave frequency ranges and all operating modes, increasing the noise level by 15 dB (16.5%) on average. Milling machines, compared to lathes, show higher noise values at medium and high octave frequencies by 7 dB (8.4%). Based on the results of the study, an adequate polynomial dependence of the fifth order was determined, which describes the noise levels relative to the frequency and corresponds to the results of the natural experiment. The resulting dependencies have practical applications in the development of component materials for simultaneous shielding of both magnetic fields of an electromagnetic field of industrial frequency and electromagnetic fields of different frequencies. Scientific novelty. The solution of this problem can be used in the future to assess the risk of occupational diseases among workers working at mechanical processing stations. Practical significance. The determined dependence will allow further consideration of the issue related to the protection of employees of mechanical processing stations from noise pollution arising during the operation of metal-cutting machines of various groups. Key words: railway, metalworking machine, noise pollution, noise.

Adaptive analog and digital active noise control

Digital adaptive controllers are widely used for active noise control. The secondary path delay, including the anti-aliasing, sampling, and reconstruction effects, must be shorter than that in the primary path to maintain good broadband performance. To eliminate the added delay of the sampling, a mixed analog and digital adaptive feedforward controller is developed. The analog controller is based on a state-filtered adaptive linear combiner, while the digital one uses an adaptive finite-impulse-response filter. The adaptation of the analog controller is derived based on a sampled version of the normalized projection algorithm, while the digital controller adaptation is based on the filtered-reference least-mean-squares algorithm. Two configurations are considered for the analog combiner. One aims to minimize the electrical noise by introducing individual state filters, all driven by the same reference signal. The other gives a superior bandwidth by driving each component filter with the previous filter output. The performance of the proposed controller is assessed and compared with separate analog or digital controllers. The results highlight that the suggested controller obtains significant attenuation levels close to the causality limit using the analog controller but also allows long impulse responses using the sampled controller.

Paediatric amplification protocol, based on individualization of the hearing aids’ fitting parameters

Background. There are no paediatric amplification clinical practice guidelines in Russia at the moment. At the same time the technological progress of hearing aids (HA), new algorithms and functions requires the objective evidence of safety and effectiveness for the hearing impaired children. For these reasons paediatric amplification algorithm was developed by the authors. Besides the standard procedures the algorithm includes an objective electroacoustic verification of the output parameters and separate HA functions. The research is devoted to the investigation of the protocols advantages. &#x0D; Aim development and evaluation the paediatric amplification protocol, based on objective electroacoustic verification of the output and functions of hearing aid. &#x0D; Materials and Methods. Prospective, randomized, controlled clinical trial was performed. Two protocols effectiveness were compared. Standard protocol (control group) is based on the subjective verification. Experimental protocol suggests an electroacoustic verification of the output and different HA functions: feedback cancellation, amplitude and frequency compression, microphone directionality, digital noise reduction (experimental group). Each group included 56 children (317 years old) with permanent hearing loss from moderate to moderately-severe degree. Initial amplification was performed for each child; the results were estimated in 1, 3 and 6 months using PEACH and LIFE questionnaires, speech audiometry and phoneme testing. DataLogging and first fitting appointment time were also estimated. &#x0D; Results. In preschool-age children of the experimental group post-amplification PEACH results were 6% better than in controls. In school-age children (LIFE questionnaire) results were 11% better comparing with control group. Speech intelligibility in quiet was 3.1% (p 0.05) higher for pre-schoolers in the experimental group and 9.3% (p 0.01) higher for school-age children comparing with control group. Speech intelligibility in noise was higher in experimental group than in control: 7.8% (p 0.05) in pre-schoolers and 13% (p 0.01) for school-age children. Phoneme recognition was better in experimental group as well: 4.5% (p 0.05) in pre-schoolers and 9.8% (p 0.01) in school-agers than in control group. After HA fitting following an experimental protocol DataLogging time was 1112% longer in comparison with standard procedure. On the other hand, experimental protocol took in average 1.5 hours for the first fitting and standard protocol 53 minutes. &#x0D; Conclusions. Protocol of paediatric amplification based on objective electroacoustic verification of HA output and functions allows to significantly increase the effectiveness of hearing rehabilitation in children.