Environmental Noise - Science topic

The monitoring of intraoperative optic nerve protection using visual evoked potential has been increasingly used in neurosurgical procedures. Although visual evoked potential is a valuable tool, its application is often hindered by anesthetic limitations and challenges related to measurement and recording environments. This case study indicates the...

Accumulating evidence shows improved syntactic processing after exposure to a rhythmically regular compared to an irregular musical prime, environmental noise, or silence. One potentially shared system between musical rhythm and language processing may be responsible for the construction of hierarchical sequences. Following findings of a shorter-li...

While being disturbed by environmental noises, the acoustic masking technique is a conventional way to reduce the annoyance in audio engineering that seeks to cover up the noises with other dominant yet less intrusive sounds. However, misalignment between the dominant sound and the noise-such as mismatched downbeats-often requires an excessive volu...

Logical qubits can be protected against environmental noise by encoding them into a highly entangled state of many physical qubits and actively intervening in the dynamics with stabilizer measurements. In this work, we numerically optimize the rate of these interventions: the number of stabilizer measurement rounds for a logical qubit encoded in a...

The implementation of shortcuts to adiabaticity (STA) enables a substantial reduction in the evolution time relative to traditional adiabatic methods, concurrently mitigating detrimental environmental interference. In this manuscript, we present a protocol using STA for the one-step generation of squeezed-light states of arbitrary photons. By start...

In the monitoring of complex industrial processes, uncertainty arising from factors such as sensor degradation and environmental noise often leads to deviations in measurement data from true values, presenting significant challenges for fault detection. Typically, only a subset of variables is affected by uncertainty in real industrial systems. How...

Holonomic quantum computation (HQC) offers an inherently robust approach to quantum gate implementation by exploiting quantum holonomies. While adiabatic HQC benefits from robustness against certain control errors, its long runtime limits practical utility due to increased exposure to environmental noise. Nonadiabatic HQC addresses this issue by en...

Terahertz coded‐aperture imaging technology (TCAI) has attracted considerable attention due to its high‐resolution characteristics in the field of staring imaging. Recent research in metasurface have demonstrated its potential for enhancing terahertz applications by enabling precise control over electromagnetic waves. However, traditional methods f...

This article proposes a robust brain-inspired audio feature extractor (RBA-FE) model for depression diagnosis, using an improved hierarchical network architecture. Most deep learning models achieve state-of-the-art performance for image-based diagnostic tasks, ignoring the counterpart audio features. In order to tailor the noise challenge, RBA-FE l...

We propose a novel multi-scale attention mechanism (MSAM) that specifically addresses the challenges of environmental noise in industrial defect segmentation. The MSAM is composed of two submodules, namely the multi-scale feature filtering (MSFF) submodule and the scale selection (SS) submodule. The MSFF generates spatial attention weights that pro...

Environmental noises from rail crossing are an under-appreciated public health issue, especially in rural towns in developing nations. This case study examines exposure to noises at a railway line crossing in Sreemangal, Bangladesh, with the NIOSH Sound Level Meter (SLM) app for iPhone 14 Pro Max. From a two-minute sample recorded at 9:00 PM, the e...

Frequency-agile lasers that can simultaneously feature low noise characteristics and fast mode-hop-free frequency tuning are keystone components for applications ranging from LiDAR and distributed sensing to communication and quantum information processing. Hybrid integrated lasers have recently demonstrated faster tuning and lower phase noise than...

As cryptographic systems evolve, increasingly sophisticated countermeasures have been developed that significantly challenge the efficacy of side-channel attacks by introducing distortions and noise into leakage traces. Current denoising methods often fail to effectively mitigate environmental noise and interference induced by these countermeasures...

Rotating machinery (RM) serves as a critical component in modern industry, with widespread applications in diverse sectors ranging from energy production to manufacturing processes. Fault diagnosis of RM is essential for preventing unexpected failures and enhancing overall equipment reliability. However, strong interference sources and heavy enviro...

Environmental noise is a significant public health issue, particularly in rapidly urbanizing cities where commercial activities contribute to elevated noise pollution. Despite its numerous implications, few studies have focused on noise levels in commercial environments in developing countries. This study aims to fill this existing gap by assessing...

Understanding the influence of realistic noise on quantum algorithms is paramount for the advancement of quantum computation. While often modeled as Markovian, environmental noise in quantum systems frequently exhibits temporal correlations, leading to non-Markovian dynamics that can significantly alter algorithmic performance. This paper investiga...

Recent advancements in foundation models have significantly enhanced the robustness and scalability of traditional methods in a variety of domains. However, their application to specialized ecological environments, where challenges such as data scarcity, camouflage, and environmental noise persist, remains an area requiring further exploration. Thi...

In the noisy medium-scale quantum era, quantum computers are constrained by a limited number of qubits, restricted physical topological structures, and interference from environmental noise, making efficient and stable circuit scheduling a significant challenge. To improve the feasibility of quantum computing, it is essential to optimize the schedu...

Nuclear factor-κB (NF-κB) participates in various cellular processes to encompass cell fate through differential gene expression, but the underlying molecular mechanism behind this phenomenon is still elusive. Two factors in this process can control the gene expression for determining the cell’s fate: (i) synthesized proteins may have a considerabl...

Bird sound classification is a valuable tool in ecological monitoring and species identification, particularly for non-invasive assessment in natural environments. However, challenges such as limited labeled data and environmental noise often reduce the reliability of classification models. This study presents a lightweight bird sound classificatio...

This study explored and proposed the migration-modified stochastic logistic growth model (MM-SLGM), developed to capture the complex dynamics of population growth under the influence of both deterministic and stochastic forces. The model incorporates intrinsic growth rate, environmental carrying capacity, net migration effects and environmental noi...

Recent technological developments have brought optically pumped magnetometers (OPMs) within reach of the larger neuroscientific community. The current state-of-the-art consists of whole-head systems that measure the magnetic field at >100 locations. OPM sensors can be constructed to measure the field in either 1, 2, or 3 orientations. Consequently,...

Vibration analysis is commonly used for monitoring the condition of bearings. However, the collected vibration signals are often contaminated by structural, measurement, and environmental noises. Therefore, filtering the signals is essential before conducting further diagnostic issues. While various filters have been developed, most are designed fo...

to detect and interpret human emotions from facial features. This method enhances emotion recognition in real-time applications like human-computer interaction and surveillance. Traditional facial expression systems rely heavily on handcrafted features, which limits flexibility. They are often sensitive to environmental noise and fail in dynamic or...

Conventional waste monitoring relies heavily on manual inspection, while most detection models are trained on close-range, simplified datasets, limiting their applicability for real-world surveillance. Even with surveillance imagery, challenges such as cluttered backgrounds, scale variation, and small object sizes often lead to missed detections an...

Dynamical decoupling (DD) is a well-established technique for protecting quantum systems from environmental noise. DD effectively mitigates decoherence in superconducting quantum computing systems, where precise implementation plays a crucial role in optimizing its performance. This study investigates how DD implementation timing and sequence desig...

We explore the quantum features of two gravitational cats (gravcats) modeled by two qubits, focusing on quantum steerability, concurrence, and geometric quantum discord under varying conditions of gravitational interaction strength, temperature, and excitation energy. We first analyze the system without dephasing effects, revealing that two-way qua...

Introduction Photosynthesis is fundamental to agricultural productivity, but its relatively low light-to-biomass conversion efficiency represents an opportunity for enhancement. High-throughput phenotyping is crucial for unraveling the genetic basis of variation in photosynthetic activity. However, the heritability of chlorophyll fluorescence param...

In multi-modal perception tasks, test-phase data often suffers from environmental noise and sensor degradation, which causes distribution shifts from the training phase. Test-time adaptation (TTA) is an emerging unsupervised learning strategy that allows pre-trained models to adapt to new data distributions during testing without requiring source d...

Hardware Trojans (HTs) pose a significant threat to the integrity and security of integrated circuits, particularly in critical systems where stealthy hardware modifications can lead to catastrophic consequences. Detecting such Trojans through side-channel analysis (SCA) remains a major challenge due to subtle signal variations and environmental no...

Forests are increasingly under pressure due to rapid population growth, unplanned urbanization, and the conversion of forest land for non-forestry uses. In Istanbul, large-scale infrastructure projects—including a major airport, motorways, and a bridge—constructed in forested northern regions have led to significant land use change, generating comp...

Quantum computers hold the potential to solve complex problems intractable for classical supercomputers. However, the inherent susceptibility of quantum systems to decoherence and environmental noise poses the most significant barrier to realizing this potential. Quantum Error Correction (QEC) codes aim to preserve the integrity of quantum informat...

Crack detection plays a critical role in maintaining the structural integrity and longevity of civil infrastructure, yet computer vision-based methods face limitations from inconsistent lighting, environmental noise, and complex backgrounds, which can hinder accurate crack detection. To address these challenges, this work introduces an enhanced cra...

Environmental noise, a significant public health concern, is associated with adverse health effects, including cardiovascular diseases, cognitive impairments, and psychological distress. Noise reduction strategies are essential for mitigating these effects. Despite evidence of their health benefits, limited information exists on the cost-effectiven...

In response to the need for cable outer sound source localization, this paper proposes a collaborative localization method based on an improved generalized cross-correlation phase transform (GCC-PHAT) and multi-sensor fusion. By constructing a secondary cross-shaped sensor array model, employing a phase transform weighting function to suppress envi...

The RAD7 detector is widely used for measuring the radon exhalation rate from thesurfaces of media such as soil, rocks, and building materials. However, during the measurementprocess, the accuracy of the results is prone to interference due to the instrument's inherentstatistical errors and environmental noise. To reduce these measurement errors, t...

Charge fluctuations along stacked nucleobases in the DNA double helix play a key role in processes such as DNA repair and replication. While classical charge transfer mechanisms between adjacent bases due to energetic excitations are well established, quantum effects can also contribute significantly. Specifically, the overlap of \documentclass[12p...

Planetary gearboxes, a critical component in industrial transmission systems, present significant challenges for condition‐monitoring technologies owing to their complex motion characteristics. Traditional monitoring methods are often susceptible to environmental noise interference and rely on external power supply systems, complicating maintenance...

El impacto humano en las condiciones ambientales de las zonas urbanas se traduce en un aumento de la contaminación y una disminución de la calidad de vida de los habitantes. Para comprender cómo cambian las condiciones ambientales en el tiempo y el espacio, y su relación con la actividad humana, es esencial contar con equipos que puedan monitorear...

With the fast development of zero-shot text-to-speech technologies, it is possible to generate high-quality speech signals that are indistinguishable from the real ones. Speech editing, including speech insertion and replacement, appeals to researchers due to its potential applications. However, existing studies only considered clean speech scenari...

Accurate thrust measurement is essential for spacecraft propulsion and space-based gravitational wave detection. However, thrust measurements are highly sensitive to environmental noise, making effective noise suppression critical for reliable signal acquisition. Thrust signals typically exhibit nonlinear abrupt transitions alongside smooth trends,...

Bridge bearings are important components that connect the upper and lower structures of bridges, and their health status directly affects the safety of bridges. However, existing bridge bearing damage identification methods have problems such as low sensitivity of damage indicators and susceptibility to environmental noise. Therefore, this study pr...

The next-generation dual-rotor turboshaft engine adopts a bearing cavity structure with flexible stators to reduce weight. However, under complex operating conditions, this structure promotes coupled nonlinear vibrations and rub-impact issues between the rotors. Inter-rotor rub-impact in a dual-rotor turboshaft engine is often obscured by rotor-to-...

We present a computational investigation of exciton transport within the Fenna-Matthews-Olson (FMO) complex, a model system in quantum biology known for its role in photosynthetic energy transfer in green sulfur bacteria. Using a seven-site Hamiltonian matrix derived from experimental data by Adolphs & Renger (2006), we represent site energies and...

With the widespread adoption of wearable devices, pulse oximeters face challenges such as motion artifacts and environmental noise in dynamic scenarios, limiting their accuracy and reliability. This study focuses on optimizing a hybrid filtering framework combining low-pass filtering and LMS adaptive filtering to enhance the performance of photople...

As the signature gas released before coal combustion, methane’s telemetry accuracy is susceptible to environmental influences, which is a difficult problem that needs to be solved. This article provides a detailed exposition on the application of Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology in the field of gas monitoring, with par...

Europe is acting to fight noise pollution. The Environmental Noise Directive (2002/49/EC) requires EU Member States to determine the exposure to environmental noise through strategic noise mapping, and elaborate action plans to reduce noise pollution. Road traffic noise is a common environmental noise source; henceforth, EU countries are obliged to...

The health status of drivers directly affects traffic safety, particularly as fatigue or sudden illness can lead to serious traffic accidents. Existing monitoring methods are challenging to apply effectively in complex in-vehicle environments. This paper presents VeHealth, a wireless in-vehicle monitoring system based on Commercial Off-The-Shelf RF...

Unmanned aerial vehicles (UAVs) emerge as a flexible and cost‐effective solution for mobile quantum communication, showing significant potential. Despite the challenges posed by environmental noise in free‐space channels for efficient entanglement distribution, the noise‐resistant properties of high‐dimensional (HD) quantum states provide a promisi...

The separation and identification of bird sounds are crucial for scientific research and ecological conservation. However, environmental noise and the distance between birds and recording devices pose significant challenges to sound separation. To address these issues, we propose BirdDenoiser, a time-domain bird sound denoising network based on opt...

Background: Exposure to environmental noise may have a negative impact on a population’s mental health. We estimated the prevalence of exposure perception to high environmental noise in the Valencian Community, a region on the Mediterranean coast of Spain, and analysed its association with poor mental health risk, adjusting for demographic, socioec...

Environmental noise from railway systems is an increasingly relevant concern in urban settings due to its effects on human health and comfort. This study explores the feasibility of applying machine learning techniques to forecast short-term train noise levels, using data collected from six monitoring sites along the Semarang–Cepu railway corridor...

Broadband and highly sensitive mid-infrared (MIR) light detection and imaging play a crucial role in environmental monitoring, gas detection, biomedical applications, and national defense security. However, the detection of high-frequency, long-distance dynamic targets with MIR thermal emission is still limited by the long response time of commerci...

In this paper, we present an orthogonal ghost imaging (OGI) method based on two-dimensional discrete cosine transform (2D-DCT) patterns. Unlike traditional methods that are based on random or sinusoidal patterns, our method relies on structured orthogonal patterns to enhance both image quality and reconstruction speed, outperforming random and sinu...

Uruguay is a small country in Latin America. It has 178.500 km² and approximately 3,400,000 inhabitants. Its environmental legislation is still incomplete; for example, there has been a national act about noise pollution since 2004 but it has never been regulated. Thus, no national regulation on noise but only departmental Ordinances in each of its...

Medium-voltage cables in hydropower plants are typically arranged in multi-circuit configurations to ensure reliability, yet their exposure to harsh operational conditions accelerates insulation degradation and increases partial discharge risks. Traditional fault localization methods, such as the traveling wave method using wavelet transform to pro...

Human-machine voice interaction based on speech recognition offers an intuitive, efficient, and user-friendly interface, attracting wide attention in applications such as health monitoring, post-disaster rescue, and intelligent control. However, conventional microphone-based systems remain challenging for complex human-machine collaboration in nois...

Traffic millimeter-wave radar suffers from environmental noise, dynamic changes in the number of vehicles, and feature similarity leading to degradation of point-trace clustering accuracy when measuring moving vehicle targets. We propose a new density-based clustering algorithm to address this problem. Unlike traditional datasets, the radar measure...

Multivariate time series data (MTSD) anomaly detection due to complex spatio-temporal dependencies among sensors and pervasive environmental noise. The existing methods struggle to balance anomaly detection accuracy with robustness against data contamination. Hence, this paper proposes a robust multivariate temporal data anomaly detection method ba...

The Volterra series filtering model is most prevalent in nonlinear systems. However, when non-Gaussian noise exists in the environment, the parameter identification ability of the Volterra series algorithm is greatly affected, and the model has a high computational cost. Therefore, this paper proposes a data-selective Volterra filtering algorithm b...

Quantum Key Distribution (QKD) enables theoretically secure communication by leveraging quantum mechanical principles. However, practical implementations face challenges due to environmental noise, which can disrupt quantum states and compromise key generation. This study investigates the maximum tolerable noise levels for secure communication usin...

Background Accepting the fact of a growing urban population and associated health risks, such as increased exposure to pollutants, and considering the high prevalence of chronic diseases, this study aims to investigate the relationship between exposure to environmental noise and depression. The primary objective is to determine the potential mediat...

In this paper, on the basis of the theories and methods of ecology, a deterministic phytoplankton–zooplankton (PZ) model as well as its stochastic differential equation version, which takes into account the synergistic effect of salinity and pH, is established. A key advantage of considering salinity and pH effects is that it can make the dynamic b...

Motorized traffic often causes road noise directly in front of our homes and windows. Yet long-term exposure to noise impact life's quality and can potentially cause negative effects on human health. Furthermore, social and behavioral effects have been measured. To protect people's health and well-being from such noise, the European Noise Directive...

Achieving precise 3D pose estimation in real-world scenarios using open-source stereo calibration techniques remains a significant challenge due to external factors such as camera positioning, calibration target size, and environmental noise. Existing calibration methods often rely on specialized hardware, controlled environments, or computationall...

This paper explores the advancements in modern weighing systems, focusing on the integration of Artificial Intelligence (AI) and Machine Learning (ML) to enhance accuracy and performance. The study highlights the role of load cells for precise weight measurement and the application of AI/ML-driven intelligent controllers in optimizing system perfor...

Recent advances have defined nontrivial phases of matter in open quantum systems, such as many-body quantum states subject to environmental noise. In this work, we experimentally probe and characterize mixed-state phases on Quantinuum's H1 quantum computer using two measures: Renyi correlators and the coding performance of a quantum error-correctin...

This study introduces a Voice Frequency Detector (VFD) framework to enhance biometric password authentication by addressing key challenges such as spoofing attacks, environmental noise, and natural variations in speaker voice due to health, emotion, or aging. The system leverages dynamic vocal features including fundamental frequency (F0), Mel-Freq...

Three-dimensional ocean observation is the foundation for accurately predicting ocean information. Although ocean observation sensor arrays can obtain internal data, their deployment is difficult, costly, and prone to component failures and environmental noise, resulting in discontinuous data. To address the severe missing data problem in three-dim...

Addressing the detrimental impact of non-stationary environmental noise on automatic speech recognition (ASR) has been a persistent and significant research focus. Despite advancements, this challenge continues to be a major concern. Recently, data-driven supervised approaches, such as deep neural networks, have emerged as promising alternatives to...

Music has been shown to increase arousal and attention and even facilitate processing during non-musical tasks, including those related to speech and language functions. Mind wandering has been studied in many sustained attention tasks. Here, we investigated the intersection of these two phenomena: the role of mind wandering while listening to fami...

Noise pollution is a threat to modern society, as it continues to endanger the health of humans and animals. Defined as unwanted sound, it is becoming more prevalent as urbanization expands due to a growing population’s infrastructural needs (Kight & Swaddle, 2011). This paper focuses on what anthropogenic noise entails for human health. Physiologi...

Plant breeding has been the key powerful strength for productivity gains in main food, feed and industrial crop plants. The traditional and Marker-Assisted Breeding (MAB) are the two prime strategies utilized to implement crop improvement programmes. The traditional breeding encompasses crossing of contrast parents and selection over succeeding gen...

The civil aircraft ramp noise directly reflects the airport environmental noise level when the aircraft is working on the ground, which is related to aircraft maintenance and the physical and mental health of ground personnel. The International Civil Aviation Organization (ICAO) also has requirements for apron noise indicators. The inlet and exhaus...

This study investigates the development and acoustic performance of a layered composite structure composed of plastic microfibre pulp (PMFP) and plastic acoustic metamaterial (PAM), designed for low-frequency sound wave control. Addressing the dual challenge of reducing plastic waste and enhancing low-frequency sound absorption, the research explor...

The escalating global demand for sustainable agriculture necessitates innovative solutions to optimize crop yield and minimize herbicide dependency. In this context, accurate and automated weed classification across multiple crop types has emerged as a critical challenge. This study explores the efficacy of transfer learning and fine-tuning Vision...

Environmental noise from railway systems is an increasingly relevant concern in urban settings due to its effects on human health and comfort. This study explores the feasibility of applying machine learning techniques to forecast short-term train noise levels, using data collected from six monitoring sites along the Semarang–Cepu railway corridor...

The spread of Internet of Things (IoT)-based healthcare systems has considerably enhanced real-time patient monitoring, but the performance of such systems largely relies on the integrity and accuracy of sensor data. Heartbeat sensors, although unavoidable, are prone to environmental noise, hardware degradation, and cyber threats, resulting in pote...

The manipulation of ultracold atoms in radio-frequency (RF)-dressed potentials offers unique advantages over static magnetic traps, such as the ability to create more complex potential landscapes, better control of atomic states, and increased robustness to environmental noise. Among the accessible geometries, ring traps are particularly promising...

This article introduces a novel predictive world modeling system grounded in the principles of dynamic actualization and adaptive predicate filtering. At its core, the model operates on minimal informational elements-termed "crumbs"-which serve as the foundational input for constructing a continuously evolving probabilistic representation of the ex...

This project presents an improved approach for enhancing bird sound recordings by applying visual sound denoising through deep learning-based image segmen-tation. A custom encoder-decoder neural network was developed, utilizing a specially designed CNN for encoding features and a lightweight decoder for precise segmentation. The dataset used in thi...

Detecting individual spins--including stable and metastable states--represents a fundamental challenge in quantum sensing with broad applications across condensed matter physics, quantum chemistry, and single-molecule magnetic resonance imaging. While nitrogen-vacancy (NV) centers in diamond have emerged as powerful nanoscale sensors, their perform...

Abstract: Emotion recognition from speech is a cornerstone of next-generation human-computer interaction, social robotics, and healthcare technologies. While traditional approaches have relied heavily on handcrafted acoustic features like Mel-Frequency Cepstral Coefficients (MFCCs), recent advances in deep learning have shifted the paradigm toward...