Noise Rate Research Articles

Rapid characterization of silicon photomultipliers for noble liquid experiments

Silicon photomultipliers (SiPMs) are emerging as the photodetector technology to be used in upcoming noble liquid experiments. Newly developed SiPMs sensitive to vacuum ultraviolet (VUV) light will be directly used for the readout of scintillation photons (λ = 175 nm) from liquid xenon in future tonne-scale experiments, such as nEXO, searching for neutrinoless double beta decay in 136Xe. In this research project, VUV-SiPMs from two different vendors are characterized using current–voltage (IV) and pulse-level measurements performed at TRIUMF, from room temperature to liquid xenon temperature. These data are analysed to extract the SiPM’s features such as breakdown voltage, gain, crosstalk, afterpulsing and dark noise rates. The IV and pulse-level results are compared. A method is proposed for rapid quality control of large numbers of SiPM using IV measurements.

Meta-analysis of different joint interfaces in total hip arthroplasty under long-term follow-up

To compare the long-term follow-up effect and complications of ceramic on ceramic (CoC) interface and ceramic on polyethyleneon ceramic (CoP) interface in primary total hip arthroplasty, and provide clinical evidence. Search PubMed, EMBase, the CoChrane Library databases, Web of science, Wanfang database, and CNKI from January 2000 to September 2021, screening and inclusion of randomized controlled trials (RCTs) comparing the long-term efficacy and complications of CoC interface and CoP interface in total hip arthroplasty. Literature screening, quality evaluation and data extraction were carried out according to the inclusion and exclusion criteria, using Review Manager 5.3 statistical software. The software was used to perform statistical analysis on joint function, revision, prosthesis fracture, abnormal joint noise, and prosthesis wear rate after CoC or CoP. Seven RCTs studies were included, including 390 cases of hips with CoC artificial joints and 384 cases of hips with CoP artificial joints. The long-term joint function improvement of CoC and CoP artificial joints was similar and there was no significant differences, with an average difference was MD=0.63, 95%CI=(-1.81, 3.07), P=0.61. About the postoperative complications, CoC artificial joints have higher incidence rate of abnormal joint noise, with odds ratio (OR)=11.05, 95%CI=(2.04, 59.84), P=0.005. CoP artificial joints wear faster, with an average MD=-87.11, 95%CI=(-114.40, -59.82), P<0.000 1. There was no significant difference between the two groups in the replacement-related complications such as joint dislocation, prosthesis loosening, osteolysis, and the rate of prosthesis revision caused by various reasons. The clinical function results and complications of CoC artificial joints are comparable to those of CoP artificial joints. Although CoP artificial joint prosthesis has a faster wear rate, it does not affect joint function and increase complications, and there is no abnormal joint noise. CoC is expensive and the long-term efficacy is equivalent to CoP. Clinicians should consider cost performance when choosing CoC.

Topological Navigation for Autonomous Underwater Vehicles in Confined Semi-Structured Environments.

In this work, we present the design, implementation, and simulation of a topology-based navigation system for the UX-series robots, a spherical underwater vehicle designed to explore and map flooded underground mines. The objective of the robot is to navigate autonomously in the 3D network of tunnels of a semi-structured but unknown environment in order to gather geoscientific data. We start from the assumption that a topological map has been generated by a low-level perception and SLAM module in the form of a labeled graph. However, the map is subject to uncertainties and reconstruction errors that the navigation system must address. First, a distance metric is defined to compute node-matching operations. This metric is then used to enable the robot to find its position on the map and navigate it. To assess the effectiveness of the proposed approach, extensive simulations have been carried out with different randomly generated topologies and various noise rates.

A study on the control indices and emission limits of substation noise

Equivalent continuous A-weighted sound pressure level (LAeq) underestimates the influence of low-frequency components of substation noise, so it is necessary to optimise control indices and emission limits of substation noise. To this end, 148 noise samples from 110 kV–1000 kV substations were selected. 280 subjects were randomly recruited for listening tests in which the 11-point numerical scale specified by ISO 15666-2021 was used. The mean noise annoyance (Am) of each noise sample was obtained to establish the LAeq-Am model of substation noise. Meanwhile, the LAeq-LFNR model was established based on the low-frequency noise rating number (LFNR) proposed by Broner. Based on these models, the LFNR corresponding to the limit of LAeq could be determined. The limit of sound pressure level of substation noise was proposed at each 1/1 octave band from 31.5 Hz to 500 Hz and the limit-exceeding ratio for the existing substations noise of China was analyzed. Results showed that Am of 500 kV–1000 kV substation noise was 1.0 higher than that of 110 kV–220 kV substation noise on average when LAeq was 25 dBA–80 dBA. LAeq of the latter were 6.1 dBA higher than that of the former on average when Am was 1–10. It was estimated that utmost 20 % of substations need further to take noise control measures in order to meet the limit suggested by this study in China. Binding with the limit of LAeq, the limit of sound pressure level at each octave band proposed according to equal noise annoyance can better evaluate the influence of substation noise.

Near-zero-dispersion soliton and broadband modulational instability Kerr microcombs in anomalous dispersion

The developing advances of microresonator-based Kerr cavity solitons have enabled versatile applications ranging from communication, signal processing to high-precision measurements. Resonator dispersion is the key factor determining the Kerr comb dynamics. Near the zero group-velocity-dispersion (GVD) regime, low-noise and broadband microcomb sources are achievable, which is crucial to the application of the Kerr soliton. When the GVD is almost vanished, higher-order dispersion can significantly affect the Kerr comb dynamics. Although many studies have investigated the Kerr comb dynamics near the zero-dispersion regime in microresonator or fiber ring system, limited by dispersion profiles and dispersion perturbations, the near-zero-dispersion soliton structure pumped in the anomalous dispersion side is still elusive so far. Here, we theoretically and experimentally investigate the microcomb dynamics in fiber-based Fabry-Perot microresonator with ultra-small anomalous GVD. We obtain 2/3-octave-spaning microcombs with ~10 GHz spacing, >84 THz span, and >8400 comb lines in the modulational instability (MI) state, without any external nonlinear spectral broadening. Such widely-spanned MI combs are also able to enter the soliton state. Moreover, we report the first observation of anomalous-dispersion based near-zero-dispersion solitons, which exhibits a local repetition rate up to 8.6 THz, an individual pulse duration <100 fs, a span >32 THz and >3200 comb lines. These two distinct comb states have their own advantages. The broadband MI combs possess high conversion efficiency and wide existing range, while the near-zero-dispersion soliton exhibits relatively low phase noise and ultra-high local repetition rate. This work complements the dynamics of Kerr cavity soliton near the zero-dispersion regime, and may stimulate cross-disciplinary inspirations ranging from dispersion-controlled microresonators to broadband coherent comb devices.

A Noise Rate Estimation Method for Image Classification with Label Noise

In a dataset, the misidentified labels can be assumed as the true labels flipped with a probability. In this paper, we study a general situation in which sample labels are corrupted at random. We propose a noise rate estimation method and prove that by adopting importance reweighting, the accuracy of classification with label noise problem can rise approximately 10% through any surrogate loss function. The two classification methods we choose for robustness analysis are convolutional neural network and convolutional neural network with importance reweighting. The details of these two methods are fully illustrated in this paper. We discuss the label noise problems and solutions in the introduction part and explain how the importance reweighting method and the noise rate estimation method are combined to deal with this problem. Experiments on Fashion-MNIST0.5, Fashion-MNIST0.6, and CIFAR with noise verify our approach. In the end, we also provide the transition matrix of the flip rate for each dataset.

Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data.

A large number of works have presented the single-cell RNA sequencing (scRNA-seq) to study the diversity and biological functions of cells at the single-cell level. Clustering identifies unknown cell types, which is essential for downstream analysis of scRNA-seq samples. However, the high dimensionality, high noise and pervasive dropout rate of scRNA-seq samples have a significant challenge to the cluster analysis of scRNA-seq samples. Herein, we propose a new adaptive fuzzy clustering model based on the denoising autoencoder and self-attention mechanism called the scDASFK. It implements the comparative learning to integrate cell similar information into the clustering method and uses a deep denoising network module to denoise the data. scDASFK consists of a self-attention mechanism for further denoising where an adaptive clustering optimization function for iterative clustering is implemented. In order to make the denoised latent features better reflect the cell structure, we introduce a new adaptive feedback mechanism to supervise the denoising process through the clustering results. Experiments on 16 real scRNA-seq datasets show that scDASFK performs well in terms of clustering accuracy, scalability and stability. Overall, scDASFK is an effective clustering model with great potential for scRNA-seq samples analysis. Our scDASFK model codes are freely available at https://github.com/LRX2022/scDASFK.

Construction and testing of the sMDT system for the HL-LHC ATLAS muon detector upgrade

The ATLAS HL-LHC upgrade includes an upgrade to the Muon Spectrometer in which the Monitored Drift Tube (MDT) chambers in the barrel inner small-sectors are replaced with new small-diameter MDT chambers (sMDT). The sMDT chambers will make space for a new triple-layer of Resistive Plate Chambers to improve the Level-1 muon triggering. There are 96 new sMDT chambers for this upgrade which are under construction at the Max Planck Institute Munich and the University of Michigan. This document reports the construction and testing of the sMDT chambers at both production sites. Through stringent measurements on mechanical precision, noise rate, efficiency, and tracking resolution, all chambers produced so far satisfy the precision and performance requirements.

Experimental Study on Fan Aerodynamic Noise Variation Characteristics under Non-Proportional Variation Law

This paper presents the noise characteristics of axial fans in the process of variable frequency adjustment, so as to clarify the basis of frequency adjustment and high-risk area division for practical purposes. In the aerodynamic performance experiment, 11 kinds of operating conditions (OC) were divided into 3 groups, and the air flow rate and power consumption were measured. At the same time, an aerodynamic noise experiment was carried out, and nine measuring points were selected to test the noise of the air inlet and shell. The data showed that the aerodynamic performance parameters have the characteristics of non-proportional law. The maximum ventilation coefficient of OC2, OC7, OC11 is 3.9%, and its noise always has a negative growth rate. Furthermore, the typical OC were selected from all experiments, and broadband noise and discrete noise analyses were performed. The results indicated that the fan noise of the changes under variable frequency adjustment may come from boundary layer noise and shedding noise. In addition, the fundamental frequency sound pressure level of discrete noise is the highest in the whole frequency band. At the high-speed condition, the contribution of higher harmonics to the fan overall noise increases, but the broadband noise is still the dominant noise. Finally, the noise rating was introduced, and the high-risk noise index was divided for the noise of the air inlet and the shell. It was found that the main noise variation index of typical OC mostly exceeded the high-risk noise index, and the main target frequency band of noise control is 250–4000 Hz.

Image Steganography Based on Chaos Function and Randomize Function

The exchange of data is not limited to personal text information or information about institutions and governments, but includes digital media transferred via the Internet including everything, whether texts, images or videos and audio, or animation. These media need high-security protection and high speed during its transmission from one site to another. In this study, a new method is suggested for hiding a gray-level image within a larger color image based on the proposed steganography map that merged chaotic function and randomize function. The size of the chaos and randomize functions is 16 bytes. Experimental results obtained a successful method based on mean squared error, signal-to-noise ratio, peak signal noise rate, embedding capacity, entropy, and histogram. This method can rapidly hide and extract ciphertext in and from the gray image. The original image and the stego image are difficult to distinguish because the correlation between them is very close to 1, indicating that attackers cannot easily differentiate these images with the naked eye. This condition can successfully hide information on the Internet.

Analogical Assessment of Train-Induced Vibration and Radiated Noise in a Proposed Theater

This study presents the analogical assessment of the train-induced vibration and radiated noise in a proposed theater. The theater is to be constructed in a region with crowded metro lines, and the assessment is implemented in an analogical building with comparable structural type and metro condition. Prior to the assessment, the comparability of the analogical building with the theater is validated using the train-induced ground vibration. With the same horizontal distance from the metro line, the train-induced vibration level in the analogical building is 9 dB higher than that in the construction site of the theater. Such results indicate that the lack of soil layers may lead to a dramatic increase in train-induced vibration in the building. In the staircase of the analogical building, the train-induced radiated noise reached 55 dB (A), which is 10 dB (A) higher than the daytime allowable level. As the most important indicator, the noise rating number in the cinema of the analogical building is NR-43, which put forward an enormous challenge on the construction of the theater with a denoise demand of 23 dB. The analogical method applied in this study provides an effective and practical way for the assessment of train-induced vibration and radiated noise in proposed vibration-sensitive buildings. The assessment results that provide necessary reference and support for the anti-vibration design will help guarantee the stage effect of the theater.

A MATLAB Simulink Study on the Performance of QAM Modulation Scheme in AWGN, Rayleigh, and Rician Fading Channels: BER Analysis

Wireless communication is the fastest-growing segment in the communication industry, with mobile communication being the most widely used. However, it faces several technical challenges, such as Fading, Shadowing, Interference, and Propagation path loss. Meeting the higher demand for capacity with high-quality service is crucial. Orthogonal Frequency Division Multiplexing (OFDM) is a technique that converts wideband signals into narrowband signals for transmission, making it a suitable option for high bandwidth data transmission. The transmission of these narrowband signals is executed with an orthogonal carrier. This paper focuses on building a QAM model using MATLAB to simulate Bit Error Rate (BER) performance for real data communication under different communication channels, including AWGN and fading channels (Rayleigh and Rician). The aim is to investigate the reduction of noise and bit error rate in communication channels. The simulation model built for this research work demonstrates that QAM scheme performs better in AWGN channels than Rayleigh or Rician fading channels.

Optimization of capacitively coupled Low Gain Avalanche Diode (AC-LGAD) sensors for precise time and spatial resolution

Capacitively-coupled Low-Gain Avalanche Diode (AC-LGAD) sensors are being developed for high-energy particle physics experiments as a detector which provides fast time information with fine spatial resolution. This paper describes optimizations of AC-LGAD sensor fabrication parameters, such as doping concentrations of the gain and electrode layers as well as the AC insulator capacitance, to realize O(10) μm spatial resolution, small charge cross talk to the neighboring electrodes, detection efficiency higher than 99% at a 10−4 noise rate and time resolution of about 30 ps. The radiation tolerance of the sensor is presented. In addition, further application to a device capable of visible and infra-red light detection is discussed.

High Optical Feedback Tolerance of a Detuned DBR Laser for 10-Gbps Isolator-Free Operation

The optical feedback tolerance (OFT) of a distributed Bragg reflector (DBR) laser was investigated experimentally. The static and modulation performance of the DBR laser under optical feedback was examined by evaluating its relative intensity noise (RIN) and bit error rate (BER). It is shown that the OFT of the DBR laser is closely related to its peak wavelength detuning relative to the Bragg wavelength. A high tolerance to optical feedback was demonstrated, both in the continuous wave (CW) and the direct modulation (DM) states, when the DBR laser was red-detuned relative to the Bragg wavelength. The excess RIN induced by optical feedback was well suppressed to a level of −140 dB/Hz at a feedback level of −9 dB in the CW state. In a 10 Gbps direct modulation state, bit error rates (BER) below 1 × 10−9 and 3 × 10−7 were obtained under a feedback level of −15 dB and −9 dB, respectively, for the case of back-to-back transmission. After 20 km fiber transmission, the BER still maintained below 1 × 10−7 under a feedback level of −15 dB, with a power penalty of less than 1 dB.

Signal Modulation Recognition System Based on Different Signal Noise Rate Using Artificial Intelligent Approach

Everyone has paid much attention to modulation-type recognition in the past few years. There are many ways to find the modulation type, but only a few good ways to deal with signals with a lot of noise. This study comes up with a way to test how well different machine learning algorithms can handle noise when detecting digital and analogue modulations. This study looks at the four most common digital and analogue modulations: Phase Shift Keying, Quadrature Phase Shift Keying, Amplitude Modulation, and Morse Code. A signal noise rate from -10dB to +25dB is used to find these modulations. We used machine learning algorithms to determine the modulation type like Decision Tree, Random Forest, Support Vectors Machine, and k-nearest neighbours. After the IQ samples had been converted to the amplitude of samples and radio frequency format, the accuracy of each method looked good. Still, in the format of the sample phase, each algorithm's accuracy was less. The results show that the proposed method works to find the signals that have noises. When there is less noise, the random forest algorithm gives better results than SVM, but SVM gives better results when there is more noise.

NRN-RSSEG: A Deep Neural Network Model for Combating Label Noise in Semantic Segmentation of Remote Sensing Images

The performance of deep neural networks depends on the accuracy of labeled samples, as they usually contain label noise. This study examines the semantic segmentation of remote sensing images that include label noise and proposes an anti-label-noise network framework, termed Labeled Noise Robust Network in Remote Sensing Image Semantic Segmentation (NRN-RSSEG), to combat label noise. The algorithm combines three main components: network, attention mechanism, and a noise-robust loss function. Three different noise rates (containing both symmetric and asymmetric noise) were simulated to test the noise resistance of the network. Validation was performed in the Vaihingen region of the ISPRS Vaihingen 2D semantic labeling dataset, and the performance of the network was evaluated by comparing the NRN-RSSEG with the original U-Net model. The results show that NRN-RSSEG maintains a high accuracy on both clean and noisy datasets. Specifically, NRN-RSSEG outperforms UNET in terms of PA, MPA, Kappa, Mean_F1, and FWIoU in the presence of noisy datasets, and as the noise rate increases, each performance of UNET shows a decreasing trend while the performance of NRN-RSSEG decreases slowly and some performances show an increasing trend. At a noise rate of 0.5, the PA (−6.14%), MPA (−4.27%) Kappa (−8.55%), Mean_F1 (−5.11%), and FWIOU (−9.75%) of UNET degrade faster; while the PA (−2.51%), Kappa (−3.33%), and FWIoU of NRN-RSSEG (−3.26) degraded more slowly, MPA (+1.41) and Mean_F1 (+2.69%) showed an increasing trend. Furthermore, comparing the proposed model with the baseline method, the results demonstrate that the proposed NRN-RSSEG anti-noise framework can effectively help the current segmentation model to overcome the adverse effects of noisy label training.

Transitions in Computational Complexity of Continuous-Time Local Open Quantum Dynamics.

We analyze the complexity of classically simulating continuous-time dynamics of locally interacting quantum spin systems with a constant rate of entanglement breaking noise. We prove that a polynomial time classical algorithm can be used to sample from the state of the spins when the rate of noise is higher than a threshold determined by the strength of the local interactions. Furthermore, by encoding a 1D fault tolerant quantum computation into the dynamics of spin systems arranged on two or higher dimensional grids, we show that for several noise channels, the problem of weakly simulating the output state of both purely Hamiltonian and purely dissipative dynamics is expected to be hard in the low-noise regime.

TelePix – A fast region of interest trigger and timing layer for the EUDET Telescopes

Test beam facilities are essential to study the response of novel detectors to particles. At the DESY II Test Beam facility, users can test their detectors with an electron beam with a momentum from 1–6 GeV. To track the beam particles, EUDET-style telescopes are provided in each beam area. They provide excellent spatial resolution, but the time resolution is limited by the rolling shutter architecture to a precision of approximately 230 μs. Since the demand on particle rates – and hence track multiplicities – is increasing timing is becoming more relevant. DESY foresees several upgrades of the telescopes. TelePix is an upgrade project to provide track timestamping with a precision of better than 5 ns and a configurable region of interest to trigger the telescope readout. Small scale prototypes have been characterized in laboratory and test beam measurements. Laboratory tests with an injection corresponding to 2300 electrons show a S/N of above 20. Test beam characterization shows efficiencies of above 99% over a threshold range of more than 100 mV and time resolutions of 2.4 ns at low noise rates.

Gaussian‐like measurement likelihood based particle filter for extended target tracking

AbstractExtended target tracking based on the star‐convex model is a multi‐dimensional nonlinear estimation problem. To approximate the shape of an extended target, the star‐convex model requires a higher‐order Fourier series expansion, which will increase the dimensionality of the extended state, so that the nonlinear filters under Gaussian assumptions cannot converge to the optimal state estimation. In this paper, a novel particle filter algorithm based on Gaussian‐like measurement likelihood (GL) is proposed. As latent variables with high uncertainty in the measurement model, the scattering centres are modelled as a Gaussian‐like probability distribution characterising the target's shape. Then the measurement noise is integrated into the Gaussian‐like probability distribution via Gaussian quadrature to obtain the accurate measurement likelihood. Moreover, particle swarm optimization is employed to reduce computational complexity. It enables particles to move into the vicinity of measurements, thereby increasing the diversity of the particles belonging to the target's shape. The simulation results show that the GL can improve the accuracy of shape estimation under high measurement noise and low measurement rates. Furthermore, the proposed particle filter can track the extended target effectively with an aeroplane‐like shape.

Microstructure and Corrosion Resistance of AZ91 Magnesium Alloy after Surface Remelting Treatment.

The effect of surface remelting treatment on the microstructure and corrosion resistance of the AZ91 magnesium alloy was studied. The surface layer was remelted by GTAW (gas tungsten arc welding). An original two-burner system with welding torches operating in a tandem configuration was used, allowing the combination of cleaning the surface from oxides with the remelting process. The studies of the corrosion resistance of the alloy included electrochemical tests and measurements of the rate of hydrogen evolution. The results showed that surface remelting treatment leads to favorable microstructural changes, manifested in strong grain refinement and a more uniform arrangement of the β-Mg17Al12 phase. The changes in the microstructure caused by remelting and the accompanying fast crystallization contributed to an increase in the corrosion resistance of the remelted samples in comparison to their non-remelted equivalents. The results obtained on the basis of the polarization curves showed three-fold lower values of the corrosion current density in the case of the remelted material than the value of the corrosion current density determined for the starting material. In turn, in the case of measurements of the electrochemical noise and corrosion rate determined by the method of measuring the rate of hydrogen evolution, this value for the remelted alloy was two times lower. The research also showed that GTAW technology is highly effective and can be a valuable alternative to laser techniques. The complete experimental details, obtained results and their analyses are presented in this paper.