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A preceding paper [M. Dhar, J. A. Dickinson, and M. A. Berg, J. Chem. Phys. 159, 054110 (2023)] shows how to remove additive noise from an experimental time series, allowing both the equilibrium distribution of the system and its Green's function to be recovered. The approach is based on nonlinear-correlation functions and is fully nonparametric: no initial model of the system or of the noise is needed. However, single-molecule spectroscopy often produces time series with either photon or photon-counting noise. Unlike additive noise, photon noise is signal-size correlated and quantized. Photon counting adds the potential for bias. This paper extends noise-corrected-correlation methods to these cases and tests them on synthetic datasets. Neither signal-size correlation nor quantization is a significant complication. Analysis of the sampling error yields guidelines for the data quality needed to recover the properties of a system with a given complexity. We show that bias in photon-counting data can be corrected, even at the high count rates needed to optimize the time resolution. Using all these results, we discuss the factors that limit the time resolution of single-molecule spectroscopy and the conditions that would be needed to push measurements into the submicrosecond region. [ABSTRACT FROM AUTHOR]

In this paper, we present the design and performance evaluation of a prototype device based on gain-driven polariton, which can function as an amplifier. This device can outperform a single microwave cavity in terms of phase noise and stability. Employed as a standalone amplifier, it demonstrates consistency between input and output phase noise, achieving a gain of up to 35 dB with a typical output of 5 dBm at 4.26 GHz. Despite its limited bandwidth, the device provides an effective solution for small signal amplification, ensuring minimal noise introduction. [ABSTRACT FROM AUTHOR]

The biochemical activity inside a cell has recently been suggested to act as a source of hydrodynamic fluctuations that can speed up or slow down enzyme catalysis [Tripathi et al., Commun. Phys. 5, 101 (2022).] The idea has been tested against and largely corroborated by simulations of activated barrier crossing in a simple fluid in the presence of thermal and athermal noise. The present paper attempts a wholly analytic solution to the same noise-driven barrier crossing problem but generalizes it to include viscoelastic memory effects of the kind likely to be present in cellular interiors. A calculation of the model's barrier crossing rate, using Kramers' flux-over-population formalism, reveals that in relation to the case where athermal noise is absent, athermal noise always accelerates barrier crossing, though the extent of enhancement depends on the duration τ0 over which the noise acts. More importantly, there exists a critical τ0—determined by the properties of the medium—at which Kramers' theory breaks down and, on approach to which, the rate grows significantly. The possibility of such a giant enhancement is potentially open to experimental validation using optically trapped nanoparticles in viscoelastic media that are acted on by externally imposed colored noise. [ABSTRACT FROM AUTHOR]

Noise is an unpleasant and unwanted sound for every human and animal. Noise can also interfere with one's communication and concentration. Nowadays, many sound absorber panels have been produced to overcome arising noise issues. A sound absorber panel works to absorb sound either in low or high frequencies. Usually, in Malaysia, synthetic materials are used for producing sound absorber panels. Glass fibre and minerals are the most common examples of synthetic materials used to produce sound absorber panels. In particular, glass fibre has a good result in sound absorption. However, it also brings negative effects to humans' health, such as skin inflammation, redness, cough, breathlessness, and others. Therefore, for this study, natural materials from recycling have been used to produce sound absorber panels, which are egg trays, papers, and plastics. The panels were tested with the impedance tube test to obtain the sound absorption coefficient (SAC) and the noise reduction coefficient (NRC). The values of sound absorption of plastics and papers are good at the frequency of 2,000 Hz (i.e., 0.75 and 0.74, respectively). However, the value of SAC for papers increased to 0.86, compared to the value of SAC for plastics that decreased to 0.67. Furthermore, the value of NRC for papers is better than plastics. Next, the reverberation room test was also performed on the panels to obtain the echo time value (RT) in the current unit. The comparison of echo time for this test is between the values for a room with and without panels. The results from the test showed that the value of echo time for the room with the panels is better than the room without panels. [ABSTRACT FROM AUTHOR]

Cellulose-based foams present a high potential for noise insulation applications. These materials are bio-degradable, eco-friendly by both embedded components and manufacturing process, have low density and high porosity, and are able to provide good noise insulation characteristics compared with available petroleum-based foams currently used on a large scale. This paper presents the results of some investigations performed by the authors in order to improve the functional characteristics in terms of free surface wettability and structural integrity. Native xylan and xylan-based derivatives (in terms of acetylated and hydrophobized xylan) were taken into account for surface treatment of cellulose foams, suggesting that hemicelluloses represent by-products of pulp and paper industry, and xylan polysaccharides are the most abundant hemicelluloses type. The investigations were mainly conducted in order to evaluate the level to which surface treatments have affected the noise insulation properties of basic cellulose foams. The results indicate that surface treatments with xylan derivatives have slowly affected the soundproofing characteristics of foams, but these clearly have to be taken into account because of their high decrease in wettability level and improving structural integrity. [ABSTRACT FROM AUTHOR]

This paper traces the acoustic imagination of modern Chinese literature, specifically through a close examination of the writings of Liu Yichang from wartime Chongqing. From 1942 to 1945, Liu worked as a radio transcriber prior to his literary stardom. He transcribed and translated English radio broadcasts into Chinese articles that would appear in print the day after they were broadcast, while writing intermittently for literary magazines. This paper analyses how the close listening – or the process of detecting and decoding information from noise – emerged out of wartime intelligence, governing Liu’s creative process. I argue that the desire to trace the source of sound is the driving force of the narrative in Liu’s short stories and prose. Furthermore, this paper studies the way in which Liu’s inattentive mode of listening transformed noise into productive disturbance that ensure a more active readership. By arguing for the central place for the acoustic aesthetics in Liu’s works composed between 1945 to 1950, this article constructs an interpretive frame that invites us to think about historical aural subjectivity modulated by the expressive and affective potential of wartime radio; and to explore the aesthetics of noise that emerged from new techniques of listening. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new algorithm called LL-Diff, which is innovative compared to traditional augmentation methods in that it introduces the sampling method of Langevin dynamics. This sampling approach simulates the motion of particles in complex environments and can better handle noise and details in low-light conditions. We also incorporate a causal attention mechanism to achieve causality and address the issue of confounding effects. This attention mechanism enables us to better capture local information while avoiding over-enhancement. We have conducted experiments on the LOL-V1 and LOL-V2 datasets, and the results show that LL-Diff significantly improves computational speed and several evaluation metrics, demonstrating the superiority and effectiveness of our method for low-light image enhancement tasks. The code will be released on GitHub when the paper has been accepted. [ABSTRACT FROM AUTHOR]

An adaptive Nesterov quasi-Newton acceleration (an-QNA)-optimized low-noise amplifier (LNA) is proposed in this paper. An optimized single-ended-to-differential two-stage LNA circuit is presented. It includes an improved post-linearization (IPL) technique to enhance the linearity. Traditional methods like conventional quasi-Newton (c-QN) often suffer from slow convergence and the tendency to get trapped in local minima. However, the proposed an-QNA method significantly accelerates the convergence speed. Furthermore, in this paper, modifications have been made to the an-QNA algorithm using a quadratic estimation to guarantee global convergence. The optimized an-QNA-based LNA, using standard 65 nm CMOS technology, achieves a simulated gain of 17.5 dB, a noise figure (NF) of 3.7 dB, and a 1 dB input compression point (IP1dB) of −13.1 dBm. It is also noted that the optimized LNA achieves a measured gain of 12.9 dB and an NF of 4.98 dB, and the IP1dB is −17.8 dB. The optimized LNA has a chip area of 0.67 mm2. [ABSTRACT FROM AUTHOR]

Parameter estimation is important in data-driven fractional chaotic systems. Less work has been reported due to challenges in discretization of fractional calculus operators. In this paper, several numerical schemes are newly derived for delay fractional difference equations of Caputo and Riemann–Liouville types. Then, loss functions are constructed and unknown parameters of the discrete fractional chaotic system are estimated by a neural network method. Parameter estimation results demonstrate high accuracy compared with real values. Robust analysis is provided under different noise levels. It can be concluded that this paper provides an efficient deep learning method based on fractional discrete-time systems. [ABSTRACT FROM AUTHOR]

As an underwater thruster, the pump-jet propulsor (PJP) exhibits low radiation noise but generates significant line spectral noise in the low-frequency band. In this paper, we equipped the PJP hub with two types of propeller boss cap fins (PBCF): one fixed and the other rotating with the rotor. The hybrid large eddy simulation and Reynolds-averaged Navier–Stokes method, along with the Ffowcs Williams-Hawkings (FW-H) equation, are employed to systematically analyze the hydrodynamics, exciting force, flow noise, and flow field of PJPs. The results indicate that the fixed PBCF improves the hydrodynamic performance and reduces the exiting force, raising the rotor's thrust coefficient by 9.22%–14.99%. The fixed PBCF also modifies the characteristics of line spectrum noise but causes an increase in the flow noise. The rotating PBCF increases the rotor's thrust coefficient by 2.03%–3.15%, decreasing both exciting force and line spectrum noise. For instance, at the advance coefficient of 0.8, its sound pressure level at the rotor frequency drops to 49.6%. Additionally, the rotating PBCF increases the pressure of the hub wake and effectively reduces the hub vortices' strengths. This paper provides a theoretical foundation for designing PJPs that enhance concealment and minimize vibrations and noise. [ABSTRACT FROM AUTHOR]

In this paper, to counteract the sensitivity of the traditional Hough transform to noise and the fluctuations in parameter estimation, we propose a hyperbolic warping transform that integrates all interference fringes in the time–frequency domain to accurately estimate the motion parameters of a single hydrophone. This method can accurately estimate the target motion parameters, including the time of closest point of approach ( t C P A ), the ratio of the nearest distance to the speed ( b = r C P A / v ), and the waveguide invariant (β). The two algorithms are compared by simulation and sea trial experiments. Hyperbola-warping improves the noise immunity performance by 10 dB in simulation experiments, increases the detection range by 20% in sea trial experiments, and demonstrates that the method proposed in this paper has better noise resistance and practicality. [ABSTRACT FROM AUTHOR]

This paper studies the autoregressive and moving average (ARMA) model with time‐functional variance (TFV) noises, called the ARMA‐TFV model. We first establish the consistency and asymptotic normality of its least squares estimator (LSE). The Wald tests and portmanteau tests are constructed based on the theory for variable selection and model checking. A simulation study is carried out to assess the performance of our approach in finite samples, and two real examples are given. It should be mentioned that the process generated from the ARMA‐TFV model is not stationary, and the technique in this paper is nonstandard and may provide insights for future research in this area. [ABSTRACT FROM AUTHOR]

In modern industrial production, noise can reflect the cutting state of the workpiece and tool to a certain extent, and the noise collection method cannot interfere with the complex processing environment. To further improve the cutting performance of coated cemented carbide micro-textured tools, this paper builds a friction and wear test platform for micro-textured cemented carbide pins with AlSiTiN-AlCrN coating and titanium alloy discs. Based on the test noise signal, the relationship between friction and wear and the noise of the workpiece was studied by the Hilbert–Huang transform (HHT). Through the change of noise in different periods, the micro-texture and coating life of cemented carbide pin under other processing parameters were analyzed. Based on the influence of the interaction between processing parameters and micro-texture diameter on the test results, the test parameters were optimized. The results show that the change of noise signal during the test presents a "V" curve with the grinding process, which mainly affects the noise through the shift of pin-disc friction form and the anti-wear effect of micro-texture. The interaction mainly affects the test results by affecting the micro-texture diameter, laser energy concentration, and the roughness of the inner wall of the pit. The optimized micro-texture geometry and preparation parameters are as follows: scanning times is 8, micro-texture diameter is 50 μm, scanning speed is 1500 mm/s, micro-texture spacing is 170 μm, and laser power is 40 W. The research content of this paper provides a reference for improving the surface properties of cemented carbide. [ABSTRACT FROM AUTHOR]

This paper presents a first implementation of gradient, divergence, and particle tracing schemes for the EMC3 code, a stochastic 3D plasma fluid code widely employed for edge plasma and impurity transport modeling in tokamaks and stellarators. These schemes are essential to accommodate plasma drift computations, which are currently absent in the code. Plasma drifts have been recognized to significantly influence transport of particles and energy, and their inclusion in future code upgrades will substantially enhance the code's predictive capabilities. For gradient and divergence calculations, we introduce a second‐order least‐squares gradient scheme. We confirm the second‐order convergence properties and assess the accuracy of several analytical test cases in the presence of synthetic noise. In the second part of this paper, we employ the validated gradient scheme in a fourth‐order Runge–Kutta particle tracing scheme to trace a particle through a generic drift velocity field. The impact of synthetic noise on the scheme's performance is investigated by evaluating various error metrics. We find that the implemented schemes function as intended and exhibit sufficient accuracy to enable drift computations. [ABSTRACT FROM AUTHOR]

Machine acoustics is an important area of research impacting the quality and comfort of human life. With increased levels of electrification and the wider use of electric motors, the contribution of motor drives towards quieter acoustic systems becomes increasingly important. This paper presents a novel acoustic improvement method involving the use of acoustic waves generated from High Frequency Injection to perform Active Noise Control. Although High Frequency Injection has been used widely in the domain of sensorless motor control, its acoustic generation process has been so far perceived as a negative by‐product. This paper presents the analysis and experimental results from the application of the proposed method to the Helicopter Electro‐Mechanical Actuation System. Considering the extensive use of motor drives in a number of industries, the proposed practice of High Frequency Injection Active Noise Control can have a significant impact to future applications. [ABSTRACT FROM AUTHOR]

In this paper, we propose two parameter choice rules for the discretizing Tikhonov regularization via multiscale Galerkin projection for solving linear ill-posed integral equations. In contrast to previous theoretical analyses, we introduce a new concept called the projection noise level to obtain error estimates for the approximate solutions. This concept allows us to assess how noise levels change during projection. The balance principle and Hanke–Raus rule are modified by incorporating the error estimates of the projection noise level. We demonstrate the convergence rate of these two modified parameter choice rules through rigorous proof. In addition, we find that the error between the approximate solution and the exact solution improves as the noise frequency increases. Finally, numerical experiments are provided to illustrate the theoretical findings presented in this paper. [ABSTRACT FROM AUTHOR]

This paper concentrates on the recovery of block-sparse signals, which are not only sparse but also nonzero elements are arrayed into some blocks (clusters) rather than being arbitrary distributed all over the vector, from linear measurements. We establish high-order sufficient conditions based on block RIP, which could ensure the exact recovery of every block s-sparse signal in the noiseless case via mixed l 2 / l p minimization method, and the stable and robust recovery in the case that signals are not accurately block-sparse in the presence of noise. Additionally, a lower bound on necessary number of random Gaussian measurements is gained for the condition to be true with overwhelming probability. Furthermore, a series of numerical experiments are conducted to demonstrate the performance of the mixed l 2 / l p minimization. To the best of the authors' knowledge, the recovery guarantees established in this paper are superior to those currently available. [ABSTRACT FROM AUTHOR]

In this paper, based on Hill dynamics and Michaelis-Menten equation, a theoretical model is established to study the noise effect in the coupled oscillation of genes and proteins between two cells. We found that in the Notch signaling pathway, the coupled oscillations of genes and proteins between two cells exhibit periodic oscillation characteristics, indicating the synchronous oscillation characteristics of intercellular signaling. "Intrinsic" noise and "external" noise have different effects on the coupled oscillation of genes and proteins between two cells. The internal noise is beneficial to increase the expression of genes and proteins in the intercellular Notch signaling pathway again. The expression levels of genes and proteins in external noise-induced pathways decrease, and periodic oscillations become damped. The combined action of internal and external noise can not only make gene expression appropriate and present a continuous oscillation pattern, but also make the corresponding protein process of gene transcription and synthesis between cells show a continuous oscillation mode. It shows that the internal and external noise of gene expression is beneficial to control the gene activation between cells and maintain the periodic rhythm of protein synthesis. The theoretical results in this paper reveal a regulatory mechanism of internal and external noise on the dynamics of the intercellular Notch signaling pathway. The respective regulatory effects of internal and external noise can be determined by our calculations, which clarify the physical mechanism of the continuous periodic oscillation of the regulation system under the combined effect of internal and external noise. The theoretical results are consistent with the experiments. It can provide a theoretical basis for the design of pathway therapies to prevent various diseases and cancers caused by Notch system gene and protein mutations. [ABSTRACT FROM AUTHOR]

This paper addresses the state estimation problem for a class of two‐dimensional shift‐varying systems with time‐correlated multiplicative measurement noises and additive noises. The time‐correlated multiplicative noises can be described as a linear system model corrupted by white noise. The main objective of this paper is to propose a recursive iterative coupled new‐type estimators and design the estimated gain reasonably to guarantee the minimum error covariance at each step. First, two new‐type coupling estimators are designed by introducing a new term. The unbiasedness of the two estimators are guaranteed by resorting to the mathematical inductive approach. Subsequently, an effective estimation is proposed given initial conditions. Moreover, the boundedness performance is investigated of the error covariance, and an upper bound is given based on the spectral norm. Finally, two numerical example are presented as an example to show the effectiveness of the estimation algorithm. [ABSTRACT FROM AUTHOR]

Sound is omnipresent in the underwater environment and can be produced by natural (waves, weather, animals) and man-made (shipping, wind farms, oil and gas activities) sources. For marine animals, such as whales, fish and even invertebrates, the auditory senses are very important. To evaluate the soundscape and to manage the marine environment with respect to underwater noise monitoring is very important. For management the impact of noise some options are available. These options need further consideration to be implemented effectively. • This paper describes results of the JOMOPANS project and discusses possible actions to manage the impact of underwater noise. [ABSTRACT FROM AUTHOR]

Domain randomness is inherent in the fabrication of periodically poled lithium niobate (PPLN). The main cause of such domain randomness in fabrication of PPLN is due to electric poling process. This domain randomness not only impacts the effectiveness of frequency conversion, but also enhances the effectiveness of nonphase matched parasitic processes, which in many cases limits the performance of the device. In this paper, we experimentally demonstrate a nondestructive characterization of domain randomness in PPLN by diffraction-noise pattern with uniform illumination. We measure the domain randomness of PPLN and provide an effective method for poling quality assessment either as good or poor quality of PPLN through this paper. [ABSTRACT FROM AUTHOR]

This field study aimed to evaluate the prevalence of annoyance and disturbance and the subjective perception of the sound environment due to noise, in an old and a new control room at a large paper mill. Working in a control room requires sustained attention and concentration and, in the case of error messages, rapid and correct decisions. In this study, the personnel's responses were collected by questionnaire, and detailed sound measurements were taken in both control rooms. The A-weighted sound pressure level in the new control room was 54.9 dB, a reduction from the 63.5 dB measured in the old room, and the C-weighted sound pressure level was 66.8 dB, a reduction from the 75.2 dB measured in the old room. The new control room was rated as being a less noisy environment; however, the personnel did complain about noise from other computers/equipment, radios, and the new laboratory. [ABSTRACT FROM AUTHOR]

Application of the nonlinear Kalman filtering method to logarithmically amplified low-coherence fringe signals measured from paper samples is considered. Experimental results of dynamic fringe envelope recovery in optical coherence tomography (OCT) systems are presented. The analog fringe envelope and digital dynamic fringe envelope recoveries from noisy signals are compared. The results show that the nonlinear discrete Kalman filtering method can be applied to estimate envelopes of logarithmically transformed low-coherence fringe signals with high noise immunity. Logarithmic amplification reduces quantization error in dealing with small signal values. The experimental results obtained demonstrate the possibility of purely digital signal processing in OCT. [ABSTRACT FROM AUTHOR]

: We analyze 6500 mm long fracture lines of paper as an example of crack propagation involving disorder. The cracks are asymptotically self-affine, with a roughness exponent close to 0.6. Systematic deviations from the power-law-scaling exist below a lengthscale related to the microscopic heterogeneities and possibly to a cross-over from 3d to 2d crack propagation. Several analysis methods are discussed, including first return analysis and the detection of correlated trends. [ABSTRACT FROM AUTHOR]

The main novelty of this paper lies in five aspects. (1) Our study on the fractional-order derivative stochastic Ginzburg–Landau equation (FODSGLE) has resulted in numerous exact solutions using Jacobian elliptic functions (JEFs). These solutions offer valuable insights into complex physical phenomena and have practical implications across various fields. (2) By examining the effect of noise on FODSGLE solutions, we found consistent behavior regardless of the form of fractional derivatives. As noise intensity increases, the solutions deteriorate and tend toward zero. This study contributes to the existing literature by providing new insights and surpassing previous efforts in understanding the dynamics of FODSGLE. (3) Our research investigates how fractional order affects noise in solutions of the FODSGLE. Surprisingly, we found that changes in the fractional order (α) have minimal influence on the system when the noise intensity (σ) is fixed. This indicates an aspect that has not been addressed extensively in existing literatures. (4) We compare different types of fractional derivatives within the context of the FODSGLE, presenting a novel contribution, while keeping the noise intensity or fractional order fixed. Our results demonstrate that the CFOD closely aligns with the MFOD, while displaying more differences with the solutions obtained using the BFOD. This comparison sheds light on an aspect that has not been thoroughly investigated in previous literatures. (5) This paper delves into the phase portraits of the FODSGLE and investigates the associated sensitivity and chaotic behaviors. Notably, previous studies on the stochastic Ginzburg–Landau equation (SGLE) have not extensively examined this aspect. By analyzing the phase portraits, we gain valuable insights into the dynamics and stability of FODSGLE solutions, uncovering intricate behaviors within the system. Our exploration of sensitivity and chaotic behaviors adds another dimension to understanding the (FODSGLE), laying a foundation for further research in this domain. [ABSTRACT FROM AUTHOR]

Publicly available ionograms are often in the form of pictures. This paper proposes a novel algorithm for extracting and repairing the F layer traces from pictorial ionograms. Extensive efforts have been invested in ionogram autoscaling and critical parameter identification to improve the efficiency of scaling algorithms. To obtain the parameters of the F layer automatically, it is necessary to accurately extract the F layer trace. However, research on F layer trace extraction with repair is relatively limited. The method employed in this study makes full use of the characteristics of different types of echoes on the ionograms, and the procedure includes noise preprocessing, coupling noise processing, and trace repair. To enhance the applicability of the repair, two different automatic filling algorithms are adopted to repair the F layer trace. The aim of this paper is to present an adaptive algorithm to automatically extract and repair F layer traces from different pictorial ionograms. The results of Hainan Fuke ionograms illustrate the reliability of the F layer trace extraction and trace repair. [ABSTRACT FROM AUTHOR]

Multifactor uncertain differential equations are powerful tools for studying dynamic systems under multi-source noise. A key challenge in this study is how to accurately estimate unknown parameters based on the framework of uncertainty theory in multi-source noise environments. To address this core problem, this paper innovatively proposes a least-squares estimation method. The essence of this method lies in constructing statistical invariants with a symmetric uncertainty distribution based on observational data and determining specific parameters by minimizing the distance between the population distribution and the empirical distribution of the statistical invariant. Additionally, two numerical examples are provided to help readers better understand the practical operation and effectiveness of this method. In addition, we also provide a case study of JD.com's stock prices to illustrate the advantages of the method proposed in this paper, which not only provides a new idea and method for addressing the problem of dynamic system parameter estimation but also provides a new perspective and tool for research and application in related fields. [ABSTRACT FROM AUTHOR]

The edge detection method based on the magnetic gradient tensor data plays an important role in magnetic exploration because it is free from geomagnetic interference and contains more abundant information. This paper proposes a new anomaly edge detection method using the magnetic gradient tensor components. The model is established to compare with other methods, such as directional total horizontal derivative (THDz), analytical signal (AS), tilt angle, theta map, and so on, under conditions of vertical magnetization, oblique magnetization, and noise interference. Through the study of the anomaly distribution of the rectangular model, it is observed that the edge detection method proposed in this paper is nearly impervious to noise interference, exhibits strong anti-interference capabilities, delivers a high-quality boundary identification effect, and provides greater accuracy in anomaly edges with minimal error. When multiple anomalous bodies are present, the edge detection results are less susceptible to interference from each other, resulting in higher resolution. The efficiency of the algorithm is demonstrated by real magnetic data from some study areas in Jiangxi Province, China. The experimental results show that the proposed method is more precise and accurate than the total horizontal derivative, analytical signal, tilt angle, and theta map methods. [ABSTRACT FROM AUTHOR]

Current research on noise and vibration control of high-speed maglev trains pays more attention to far-field noise, while the level of interior noise has a direct impact on the ride comfort and should be placed equal weight on. In this paper, inter-coach space, one of the main pressure fluctuation sources of a specific type of high-speed maglev train with a design speed of 600 km·h−1, is taken as the research object. The turbulent and acoustic components of wall pressure fluctuations (WPF) are separated based on a wavenumber-frequency analysis approach, and then each component is applied as different forms of source input to the vibroacoustic model, namely, finite element method-boundary element method (FEM-BEM) and statistical energy analysis (SEA) for low- and high-frequency ranges respectively, to investigate the contribution of both components to interior acoustic cavity in all frequency range. It can be seen quantitatively from the results that the amplitude of turbulent component is generally much higher than that of the acoustic one, but it can be vice versa when it comes to the interior response. The conclusion drawn in this paper are able to provide guidance for future researches on more targeted interior noise control of high-speed maglev trains. [ABSTRACT FROM AUTHOR]

Objectives: The conventional group sparse representation (GSR) model encounters challenges in precisely estimating the sparsity of individual image groups, because the influence of noise results in distortion in the restoration of original image group. Methods: This paper introduces a strategy denominated as the group sparse residual constraint. This strategy leverages non-local self-similarity priors to derive precise estimate of sparse coefficients for each original image group. Subsequently, the sparse coefficients of corresponding degraded image groups are constrained to approximate this estimate. Furthermore, the intricate nature of noise in area-array satellite images (e. g., Luojia3-01 satellite images), surpasses the simplicity of additive white Gaussian noise (AWGN). Consequently, conventional GSR model tailored for AWGN exhibits a reduction in efficacy when deployed in real image denoising scenarios. To address this, this paper introduces two distinct weight matrices into the data fidelity term and regularization, respectively, with the intent of characterizing the statistical features inherent in both images and noise. This paper adopts the alternating direction method of multipliers for optimizing the proposed image denoising task. Results: The effectiveness of the proposed model is validated by the experiments using simulated data and real images obtained from the Luojia3-01 satellite. In the experiments of simulated data, the proposed model outperforms other methods in removing AWGN and spatially variant noise. In the experiments of real images, the entropy of denoised images by the proposed model shows improvements of 2.03%, 1.18%, 1.26%, 1.24%, and 2.10%, compared to the block-matching and 3-D filtering method, multi-channel weighted nuclear norm minimization method, nonlocally centralized sparse representation method, low-rankness guided group sparse representation method, and trilateral weighted sparse coding method, respectively. Conclusions: The proposed method exhibits good performance in processing area-array satellite images with low signal-to-noise ratios and complex noise structures, significantly enhancing the quality of the image. By effectively reducing noise while preserving crucial details and edges, it provides a reliable solution for enhancing the usability and interpretability of area-array satellite images, particularly in challenging conditions. [ABSTRACT FROM AUTHOR]

It is a distinct privilege to produce this article to honor Professor Tam, the foremost authority on jet aeroacoustics. The fundamental characteristics of jet noise have been studied for 70 years, since the pioneering work of Lighthill in the 1950s. The acoustic analogy, with many variants, has served as the leading theory for nearly 50 years. Many leading researchers in the 1970s formulated theories to interpret the measured trends from subsonic and supersonic jets, using acoustic analogy and flow features as the framework. Quadrupoles, dipoles and monopoles were believed to constitute the sources of noise. The discovery of large-scale organized structures in free shear layers and jets sparked a different avenue of thinking about their importance for noise generation. Tam was the first to clearly demonstrate that these structures are efficient generators of noise and constitute the dominant noise sources, especially in the downstream direction. Now, two schools of thought emerged on the sources of jet noise. Experimental measurements showed that the mean flow as well as the turbulence statistics exhibit a self-similarity in the mixing layer and another similarity in the fully developed jet. Based on these observations, Tam proposed that since noise is generated by the turbulence of the jet, the noise spectra generated by fine-scale and large-scale turbulence should also exhibit self-similarity. By examining a large set of supersonic jet noise data acquired at NASA Langley, Tam offered evidence that the turbulent mixing noise of high-speed jets does consist of two independent self-similar components. In this paper, experimental evidence is compiled from an extensive database that quantifies the effect of several parameters that affect jet spectra. A new scaling method is developed and extended to noise predictions for realistic dual-stream nozzle geometries. The objectives of this paper are to serve as a synthesis of noise characteristics and to focus on application to real-world problems. Results from five different experimental measurements are examined: (1) farfield spectral characteristics; (2) azimuthal and polar correlations in the farfield; (3) correlations of jet turbulence fluctuations and farfield sound; (4) measurement of source distributions with an elliptic mirror; and (5) space-time correlation measurements in the nearfield with a cage array, and nearfield-farfield correlations. Two distinctly different trends are observed in the angular ranges of 50° – ∼120° and ∼120° – 165° for all the parameters investigated with the above five approaches. The salient observations are mutually supporting, and the cumulative weight lends credence to the proposition that there are two distinct sources of turbulent mixing noise. [ABSTRACT FROM AUTHOR]

Background: The potential effect of image noise artefacts on Digital Volume Correlation (DVC) analysis has not been thoroughly studied and, more particularly quantified, even though DVC is an emerging technique widely used in life and material science over the last decade. Objective: This paper presents the results of a sensitivity study to shed light on the effect of various noise artefacts on the full-field kinematic fields generated by DVC, both in zero and rigid body motion. Methods: Various noise artefacts were studied, including the Gaussian, Salt & Pepper, Speckle noise and embedded Ring Artefacts. A noise-free synthetic microstructure was generated using Discrete Element Modelling (DEM), representing an idealistic case, and acting as the reference dataset for the DVC analysis. Noise artefacts of various intensities (including selected extreme cases) were added to the reference image datasets using MATLAB (R2022) to form the outline of the parametric study. DVC analyses were subsequently conducted employing AVIZO (Thermo Fisher). A subset-based local approach was adopted. A three-dimensional version of the Structural Similarity Index Measure (SSIM) was used to define the similarity between the compared image datasets on each occasion. Sub-pixel rigid body motion was applied on the DEM-generated microstructure and subsequently "poisoned" with noise artefacts to evaluate mean bias and random error of the DVC analysis. Results: When the local approach is implemented, the sensitivity study on zero motion data revealed the insignificant effect of the Gaussian, Salt & Pepper, and Speckle noise on the DVC-computed kinematic field. Therefore, the presence of such noise artefacts can be neglected when DVC is executed. On the contrary, Ring Artefacts can pose a considerable challenge and therefore, DVC results need to be evaluated cautiously. A linear relationship between SSIM and the correlation index is observed for the same noise artefacts. Gaussian noise has a pronounced effect on the mean bias error for sub-pixel rigid body motion. Conclusions: Generating synthetic image datasets using DEM enabled the investigation of a variety of noise artefacts that potentially affect a DVC analysis. Given that, any microstructure – resembling the material studied – can be simulated and used for a DVC sensitivity analysis, supporting the user in appropriately evaluating the computed kinematic field. Even though the study is conducted for a two-phase material, the method elaborated in this paper also applies to heterogeneous multi-phase materials also. The conclusions drawn are valid within the environment of the AVIZO DVC extension module. Alternative DVC algorithms, utilising different approaches for the cross-correlation and the sub-pixel interpolation methods, need to be investigated. [ABSTRACT FROM AUTHOR]

Hyperspectral image (HSI) classification is a very important topic in remote sensing. There are many published methods for HSI classification in the literature. Nevertheless, it is not clear which method is the most robust to noise in HSI data cubes. In this paper, we conduct a systematic study to examine the effects of noise in HSI data cubes on classification methods. We compare ten existing methods for HSI classification when Gaussian white noise (GWN) and shot noise are present in the HSI data cubes. We have figured out which method is the most robust to GWN and shot noise respectively by experimenting on three widely used HSI data cubes. We have also measured the CPU computational time of every method compared in this paper for HSI classification. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, a new frontend for 5G receivers is proposed. In the presented work, a new bandwidth enhancement technique for low‐noise transconductance amplifiers and for wireless frontends has been proposed. The proposed frontend achieves low noise figure (NF) by using a noise cancelation scheme in the newly proposed LNTA. The linearity of the frontend is also improved by increasing the DC gain and the bandwidth of the opamp used in the transimpedance amplifier and by exploiting a linearity improvement method for the LNTA. The frontend has been implemented in a standard 0.18 μm CMOS process. The post‐layout simulation results prove the gain of 38 dB with less than 3 dB deviation in the pass‐band over a 6.5 GHz bandwidth. The results also show that NF is less than 8 dB, the worst‐case IIP3 is −2 dBm, the maximum S11 is equal to −9.5 dB while the frontend consumes 9.95 mW DC power from a single 1.8‐V supply, and the occupied area is 0.813 mm2. [ABSTRACT FROM AUTHOR]

Due to the influence of strong noise, it is difficult to extract and identify the fault features of rolling bearing when it is slightly damaged, which greatly increases the risk of fault miss detection. In this paper, the enhanced multi-layer Ramanujan decomposition (EMRD) method is proposed. On the one hand, EMRD method adopts accurate spectrum segmentation technology (ASST) to realise adaptive frequency band division. ASST firstly minimises the frequency erosion caused by noise through prior-unknown blind deconvolution method based on SOSO (SOSO-PUBD), then obtains relatively pure frequency distribution through power spectral density function, and finally realises frequency band segmentation by minimum segmentation method. On the other hand, EMRD method obtains the optimal number of decomposition modes in the form of multi-layer decomposition, and selects the optimal mode by Ramanujan spectrum signal-to-noise ratio index. The comparative experimental results show that EMRD method has excellent accuracy of frequency band segmentation and meets the requirements of rolling bearing fault diagnosis. [ABSTRACT FROM AUTHOR]

The influence line of bridge can reflect the performance of the bridge under the moving vehicle load. It has a wide range of applications in structural damage detection, performance evaluation, model correction and bridge weigh-in-motion. Fast moving vehicles will cause the dynamic effect of the bridge, resulting in the change of the bridge response curve and the difficulty of identifying the influence line. In this paper, an influence line identification method based on variational mode decomposition (VMD) combined with improved wavelet threshold denoising is proposed. Firstly, the mathematical model of influence line identification is established based on vehicle load matrix and bridge response. Then, VMD combined with improved wavelet threshold denoising method is used to eliminate dynamic fluctuation effect and noise. Finally, the elastic net penalty term is introduced in the influence line identification problem, and the B-spline basis function is used to reconstruct the influence line. In order to verify the effectiveness of the proposed method, a vehicle-bridge coupling model is established for numerical calculation, and the identification of bridge displacement influence lines under different conditions such as vehicle speed, noise level, road roughness and vehicle weight is investigated. The results show that the proposed method can effectively eliminate the dynamic fluctuation components and noise of the bridge response. In the case of good road roughness, the influence line can still be accurately identified when the vehicle speed reaches 15 m/s. [ABSTRACT FROM AUTHOR]

This paper concerns the modeling of smart health sensors for data monitoring, where the data are eventually noisy, with correlated noise. In this work, we applied Clifford-based wavelets/multiwavelets for correlated noise in multi-sensors health data monitoring by estimating the set of sensor nodes minimizing an eventual error computed by the signal values at the selected nodes mostly caused by the correlated noise. Instead of directly minimizing the estimation error, we focused on evaluating a multi-level scheme based on multiwavelets for the estimation of the error between the parameter vector and its sub-vector of those nodes. Numerical simulations are provided with a comparison to some recent existing works. This model showed a performance and a fast time execution compared to those existing works. This model exceeds these models by the non-necessity to assume a priory structure of the data. Wavelets are capable to detect, localize, and eliminate the noise, even correlated, efficiently via the independent uncorrelated multiwavelets’ components. [ABSTRACT FROM AUTHOR]

Time-varying polytope distance (TVPD) problems are prevalent in scientific and engineering applications and can be transformed into time-varying quadratic programming (TVQP) problems with both equality and inequality constraints. Concurrently, the noise interferences during the solution process are non-negligible and challenging to eliminate. Although zeroing neural networks (ZNNs) perform well in solving various types of time-varying problems, they still fall short in the suppression of unbounded noises, such as linear noise. To address this limitation, this paper proposes an improving integration-enhanced ZNN (IIEZNN) model for accurately solving TVPD problems under noise environments. Compared with the existing ZNN models, the IIEZNN model has stronger inherent robustness. The stability and robustness of the IIEZNN model are guaranteed by rigorous theoretical analysis. Firstly, the effectiveness of the IIEZNN model is verified via two TVQP examples. Then, the IIEZNN model is generalized to TVPD problem solving and has excellent performance. Specifically, in solving the TVPD under linear noises, the residual error of the IIEZNN model converges to the order of 10 - 5 , which is much lower than that of the existing noise-tolerant ZNN model with an order of 10 - 1 . [ABSTRACT FROM AUTHOR]

Videos or Vlogs primarily contain three types of information: natural language, facial movements, and audio activity. These three types of information can effectively portray the publisher's possible attitude. Most recent studies on the multimodal sentiment analysis challenge have focused on two angles. The first is to examine each mode in isolation, but doing so will ignore the interaction between them. The alternative is to integrate information from several modes and treat it all equally, but doing so will add a lot of noise input and disregard critical modes' dominant positions (such as text). The main fusion module based on the mask attention mechanism and the dynamic aggregation attention mechanism, together with the auxiliary fusion module based on the directed cross-modal transformer, can solve these challenges. At the same time, the issue of data misalignment caused by the various sampling rates of each modal sequence is also taken into account in this paper. Our model can deal with the ''unaligned" data, pay greater attention to the crucial modes and features of sentiment information, and reduce the noise input by using the main and auxiliary fusion mechanisms. The model has undergone thorough testing in two publicly accessible multimodal datasets (CMU-MOSI and CMU-MOSEI), and the findings show that our model performs significantly better than state-of-the-art models. [ABSTRACT FROM AUTHOR]

Robust and efficient multi-source image matching remains a challenging task due to nonlinear radiometric differences between image features. This paper proposes a pixel-level matching framework for multi-source images to overcome this issue. Firstly, a novel descriptor called channel features of phase congruency (CFPC) is first derived at each control point to create a pixelwise feature representation. The proposed CFPC is not only simple to construct but is also highly efficient and somewhat insensitive to noise and intensity changes. Then, a Fast Sequential Similarity Detection Algorithm (F-SSDA) is proposed to further improve the matching efficiency. Comparative experiments are conducted by matching different types of multi-source images (e.g., Visible–SAR; LiDAR–Visible; visible–infrared). The experimental results demonstrate that the proposed method can achieve pixel-level matching accuracy with high computational efficiency. [ABSTRACT FROM AUTHOR]

To address the limitations of single-view spammer detection methods in processing complex and diverse social network data, and the issues of information loss and noise interference due to existing multi-view fusion methods not fully considering the quality differences between views, this paper proposed a social spammer detection method based on MVEF. The method integrated and analyzed three views; social relationships, behavioral characteristics, and tweet content, to extract pivotal evidence. It employed Dirichlet distribution parameterization to assess the category credibility and overall uncertainty of each view in classification decisions. Through an efficient evidence fusion mechanism, the method skillfully utilized uncertainty to integrate key evidence from various views, constructing a comprehensive and reliable classification decision framework. Experimental results demonstrate that MVEF outperforms existing methods on two real-world Twitter datasets, effectively enhancing the accuracy and robustness of spammer detection. [ABSTRACT FROM AUTHOR]

The multi‐stage noise shaping (MASH) ΣΔ ADC has a good potential to achieve high‐order noise shaping (NS) and high resolution. However, it suffers from quantization noise leakage caused by the mismatch between the analogue NS filter and the digital cancellation filter, which greatly degrades the ADC performance. The sturdy MASH topology of the ΣΔ ADC can solve the leakage issue, but it cannot be implemented using the NS SAR ADC due to structural limitations. This paper proposes a sturdy MASH 2‐0 NS SAR to solve the noise leakage issue. The 4th‐order NS is achieved by only using a 2‐0 topology, which is hardware efficient. Instead of eliminating the first‐stage quantization error, the proposed sturdy MASH 2‐0 NS SAR shapes it, achieving better robustness to PVT variables. Furthermore, owing to the first‐stage 2nd‐order NS capability, the impairments of the residue amplifier, including the gain error and nonlinearity, are 2nd‐order shaped. The proposed 4th‐order sturdy MASH 2‐0 NS SAR is implemented in a 28 nm CMOS process, which achieves a SNDR of 85.6 dB and a SFDR of 101.3 dB with 10 MHz BW at OSR of 10, resulting in a Schreier FoM of 178.8 dB/179.4 dB (in SNDR/DR) with power consumption of 4.8 mW. [ABSTRACT FROM AUTHOR]

Cross-correlations of seismic ambient noise are frequently used to image Earth structure. Usually, tomographic studies assume that noise sources are uniformly distributed and interpret noise correlations as empirical Green's functions. However, previous research suggests that this assumption can introduce errors in the estimated models, especially when noise correlation waveforms are inverted. In this paper, we investigate changes in subsurface models inferred from noise correlation waveforms depending on whether the noise source distribution is considered to be uniform. To this end, we set up numerical experiments that mimic a tomographic study in Southern California exploiting ambient noise generated in the Pacific Ocean. Our results show that if the distribution of noise sources is deemed uniform instead of being numerically represented in the wave simulations, the misfit of the estimated models increases. In our experiments, the model misfit increase ranges between 5 and 21 per cent, depending on the heterogeneity of the noise source distribution. This indicates that assuming uniform noise sources introduces source-dependent model errors. Since the location of noise sources may change over time, these errors are also time-dependent. In order to mitigate these errors, it is necessary to account for the noise source distribution. The spatial extent to which noise sources must be considered depends on the propagation distance of the ambient noise wavefield. If only sources near the study area are considered, model errors may arise. [ABSTRACT FROM AUTHOR]

Robust recognition of objects is crucial across various applications, spanning from industrial automation to healthcare and security. Nevertheless, real-world datasets often introduce label noise, encoding inaccurate correlation patterns that compromise the performance of visual recognition systems. Recent approaches utilize the predicted label distributions of individual samples for noise verification and correction, potentially exacerbating the accumulation of noise. To tackle this concern, in this paper, we introduce the context-driven reliability assessment strategy (CRA) for object robust recognition, where the reliability of a candidate sample is re-evaluated and rectified by comparing it with its neighbors in feature space. Specifically, CRA is divided into two steps: (1) consistency-aware pure sample selection (CPS) for estimating and choosing reliable samples based on consistent relations with the candidate sample and its k-reciprocal neighbors; and (2) similarity-guided label noise refurbishment (SLR) for re-labeling noisy samples by penalizing the divergence of each example's prediction from a weighted combination of its neighbors' predictions, with weights determined by their similarity in feature space. Thereafter, auxiliary techniques are used to assist further model optimization. Extensive experiments on three commonly used benchmark datasets, i.e., CIFAR-10, CIFAR-100 and Webvision - 1.0, demonstrate that our proposed method considerably outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper studies the stochastic time-fractional heat diffusion equation involving a Caputo derivative in time of order α ∈ (1 2 , 1 ] , driven simultaneously by a random diffusion coefficient field and fractionally integrated multiplicative noise. First, the well-posedness of the underlying problem is established by proving the existence, uniqueness, and stability of the mild solution. Then a spatio-temporal discretization method based on a Milstein exponential integrator scheme and finite element method is constructed and analyzed. The strong convergence rate of the fully discrete solution is derived. Numerical experiments are finally reported to confirm the theoretical result. [ABSTRACT FROM AUTHOR]

ABSTRACT Measurement errors are ubiquitous in all experimental sciences. Depending on the particular experimental platform used to acquire data, different types of errors are introduced, amounting to an admixture of additive and multiplicative error components that can be uncorrelated or correlated. In this paper, we investigate the effect of different types of experimental error on the recovery of the subspace with principal component analysis (PCA) using numerical simulations. Specifically, we assessed how different error characteristics (variance, correlation, and correlation structure), loading structures, and data distributions influence the accuracy to estimate an error‐free (true) subspace from sampled data with PCA. Quality was assessed in terms of the mean squared reconstruction error and the congruence to the error‐free loadings, using the pseudorank and adjusting for rotational ambiguity. Analysis of variance reveals that the error variance, error correlation structure, and their interaction with the loading structure are the factors mostly affecting quality of loading estimation from sampled data. We advocate for the need to characterize and assess the nature of measurement error and the need to adapt formulations of PCA that can explicitly take into account error structures in the model fitting. [ABSTRACT FROM AUTHOR]

This paper introduces a method for forecasting the arrival of trains by analyzing track vibration signals. The proposed algorithms, based on H‐ranks of track vibration signals, can generate early alerts for approaching trains. These algorithms are robust to additive noise and environmental conditions. The theoretical foundation of the method involves the application of matrix operations to detect significant changes in vibration patterns, indicating an approaching train. [ABSTRACT FROM AUTHOR]