Noise reduction

Coherent Doppler wind lidar (CDWL) uses transmitted laser pulses to measure wind velocity distribution. However, the echo signal of CDWL is easily affected by atmospheric turbulence, which can decrease the signal-to-noise ratio (SNR) of lidar. To improve the SNR, this paper proposes a pulse accumulation method based on the cross-correlation function to estimate the phase of the signal. Compared with incoherent pulse accumulation, the proposed method significantly enhances the correlation between signals from different periods to obtain high SNR gains that arise from pulse accumulation...

The correlation between magnetic Barkhausen noise (MBN) features and the surface hardness of two types of die steels (Cr12MoV steel and S136 steel in Chinese standards) was investigated in this study. Back-propagation neural network (BP-NN) models were established with MBN magnetic features extracted by different methods as the input nodes to realize the quantitative prediction of surface hardness. The accuracy of the BP-NN model largely depended on the quality of the input features. In the extraction process of magnetic features, simplifying parameter settings and reducing manual intervention could significantly improve the stability of magnetic features...

The paper explores maritime environmental regulations, analyzing industry perspectives and their operational execution. It critically assesses the International Maritime Organization (IMO) regulations' effectiveness in mitigating climate challenges within the shipping domain. The central argument is that the evolving and intricate nature of maritime regulations often impedes policy goal realization, enforcement, impact evaluation, and equity perception. Utilizing both quantitative and qualitative methodologies, this research gathers, analyses, and interprets data via surveys and interviews...

By generating massive gene transcriptome data and analyzing transcriptomic variations at the cell level, single-cell RNA-sequencing (scRNA-seq) technology has provided new way to explore cellular heterogeneity and functionality. Clustering scRNA-seq data could discover the hidden diversity and complexity of cell populations, which can aid to the identification of the disease mechanisms and biomarkers. In this paper, a novel method (DSINMF) is presented for single cell RNA sequencing data by using deep matrix factorization...

Wearable sensing has become a vital approach to cardiac health monitoring, and seismocardiography (SCG) is emerging as a promising technology in this field. However, the applicability of SCG is hindered by motion artifacts, including those encountered in practice of which the strongest source is walking. This holds back the translation of SCG to clinical settings. We therefore investigated techniques to enhance the quality of SCG signals in the presence of motion artifacts. To simulate ambulant recordings, we corrupted a clean SCG dataset with real-walking-vibrational noise...

Deep learning-based image reconstruction and noise reduction (DLIR) methods have been increasingly deployed in clinical CT. Accurate assessment of their data uncertainty properties is essential to understand the stability of DLIR in response to noise. In this work, we aim to evaluate the data uncertainty of a DLIR method using real patient data and a virtual imaging trial framework and compare it with filtered-backprojection (FBP) and iterative reconstruction (IR). The ensemble of noise realizations was generated by using a realistic projection domain noise insertion technique...

INTRODUCTION: With the increase of urban population density, urban sanitation becomes more severe; urban sanitation has important influence on public health. Therefore, in order to realize the detection of public health in smart cities, the research will use cutting-edge scientific and technological methods to improve urban environmental health, so as to promote the realization of public health achievements. This study introduces public health detection and optimizationtechnologies for smart cities...

BACKGROUND: The relationship between CDH23 gene variants and NIHL is unclear. This study investigates the association between cadherin 23 ( CDH23 ) gene variants and noise-induced hearing loss (NIHL). METHODS: This is a case-control study. Workers who were exposed to noise from a steel factory in North China were recruited and divided into two groups: the case group (both ears' high-frequency threshold average [BHFTA] ≥40dB) and the control group (BHFTA ≤25 dB)...

BACKGROUND: Global shortages of iodinated contrast media (ICM) during COVID-19 pandemic forced the imaging community to use ICM more strategically in CT exams. PURPOSE: The purpose of this work is to provide a quantitative framework for preserving iodine CNR while reducing ICM dosage by either lowering kV in single-energy CT (SECT) or using lower energy virtual monochromatic images (VMI) from dual-energy CT (DECT) in a phantom study. MATERIALS AND METHODS: In SECT study, phantoms with effective diameters of 9...

BACKGROUND: ICU outcomes are continuing to improve. However, this has not been matched by similar improvements of the ICU bedspace environment, which can detrimentally impact on patient outcomes. Excessive sound and noise, especially, has been linked with adverse and potentially preventable patient outcomes and staff errors. There are many sources of sound in the ICU, with alarms from bedside equipment frequently listed as a main source. The number of alarms is increasing in parallel with the introduction of new and more sophisticated technologies to monitor and support patients...

Objective
Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-printed PixelPrint lung phantom to evaluate a commercial DLR algorithm across a wide range of radiation dose levels.

Method
The lung phantom used in this study is based on a patient chest CT scan containing ground glass opacities and was fabricated using PixelPrint 3D-printing technology...

Numerous efforts have been undertaken to mitigate the Debye screening effect of FET biosensors for achieving higher sensitivity. There are few reports that show sub-femtomolar detection of biomolecules by FET mechanisms but they either suffer from significant background noise or lack robust control. In this aspect, deformed/crumpled graphene has been recently deployed by other researchers for various biomolecule detection like DNA, COVID-19 spike proteins and immunity markers like IL-6 at sub-femtomolar levels...

INTRODUCTION: Acoustic noise from magnetic resonance imaging (MRI) can cause hearing loss and needs to be mitigated to ensure the safety of patients and personnel. Capturing MR personnel's insights is crucial for guiding the development and future applications of noise-reduction technology. This study aimed to explore how MR radiographers manage acoustic noise in clinical MR settings. METHODS: Using a qualitative design, we conducted semi-structured individual interviews with fifteen MR radiographers from fifteen hospitals around Sweden...

Adopting energy-saving and noise-reducing technologies in vehicle transportation has the potential to mitigate urban traffic pollution and promote sustainable urban mobility. However, a universal analytical framework for obtaining the combined energy savings and noise reduction patterns in vehicles is still lacking. This study addresses this gap by integrating a fundamental traffic noise model with a vehicle energy conservation equation. A theoretical framework was constructed that establishes the relationship between vehicle noise and energy consumption, with the theoretical origins of this framework explained...

Intelligent diagnostic algorithms based on convolutional neural networks (CNNs) have shown great potential in diagnosing various conditions. However, accurately and robustly diagnosing faults in noisy situations remains challenging. This study presents an adaptive fully convolutional network (AFCN) for identifying bearing defects in noisy environments. First, we use a novel large kernel convolution method for high-frequency noise reduction and wide-area temporal feature extraction. By utilizing a sequence of stacked residual adaptive convolution blocks, the AFCN achieves a selective emphasis on significant features and adaptive adjustment of feature weights at various convolution scales...

Medical imaging AI systems and big data analytics have attracted much attention from researchers of industry and academia. The application of medical imaging AI systems and big data analytics play an important role in the technology of content based remote sensing (CBRS) development. Environmental data, information, and analysis have been produced promptly using remote sensing (RS). The method for creating a useful digital map from an image data set is called image information extraction. Image information extraction depends on target recognition (shape and color)...

PURPOSE OF REVIEW: To describe the role of health equity in the context of carbon capture, utilization, and sequestration (CCUS) technologies. RECENT FINDINGS: CCUS technologies have the potential to both improve and worsen health equity. They could help reduce greenhouse gas emissions, a major contributor to climate change, but they could also have negative health impacts like air and noise pollution. More research is needed to fully understand the health equity implications of CCUS technologies...

MRI systems have a thin conducting layer placed between the gradient and RF coils, this acts as a shield at the RF-frequency, minimizing noise coupled into the experiment, and decreasing the coupling between the RF and gradient coils. Ideally, this layer should be transparent to the gradient fields to reduce eddy currents. In this work the design of such a shield, specifically for low-field point-of-care Halbach based MRI devices, is discussed. A segmented double layer shield is designed and constructed based on eddy current simulations...

A study is presented of the thermal-mechanical noise and response to sound of microphones that are designed to be driven by the viscous forces in air rather than by sound pressure. Virtually all existing microphone designs are intended to respond to sound pressure. The structures examined here consist of thin, micro-scale, cantilever beams. The viscous forces that drive the beams are proportional to the relative velocity between the beams and fluid medium. The beams' movement in response to sound is similar to that of the air in a plane acoustic wave...

The application of Scirpus grossus (SG) fiber as a sound absorber is important to reduce the level of noise affected the physical and mental wellbeing of people. The sound absorption coefficient (SAC) and noise reduction coefficient (NRC) of the SG specimen were evaluated based on a typical model-based design using the data analysis with MATLAB. The results showed that SG specimen with a thickness of 20 mm coated with the perforated aluminum sheet (PAS) compared to that without coating can improve the capability of sound absorption by 14% at the frequency of 4000 Hz...