Binary Noise Research Articles

Housing Australian Children: A Snapshot of Health Inequities in the First 2000 Days.

Housing is a critical social determinant of children's health. While individual pathways between housing and health are well evidenced, there has been less attention on the co-occurrence of housing disadvantages. We aim to identify typologies of children's housing disadvantage and describe the health inequities they generate. A cross-sectional latent class analysis (LCA) was conducted on 4355 Australian children aged 4 to 5years who participated in the Longitudinal Study of Australian Children. Nine binary indicators-dwelling tenure, external condition, affordability, stability, crowding, cleanliness, fuel poverty, and noise exposure-were used to generate latent housing typologies. Generalized linear models with robust standard errors described disparities in quality of life, injury, disability, and health service use across these housing typologies. Four distinct housing typologies were identified in this cohort: "good condition, affordable, and secure" (60%); "insecure" (11%); "crowded" (24%); and "unsuitable" (5%). Unsuitable housing, characterized by crowding, poor external conditions, and noise exposure, was more likely to be occupied by single-parent families, low-income households, and be headed by parents with low levels of education. Children in unsuitable housing lagged on quality of life indicators at preschool age (e.g., by 8.0 points on emotional functioning, 95% CI - 10.6, - 5.5), and underutilized primary healthcare services (e.g., prevalence ratio 0.76 for GP services, 95% CI 0.67, 0.87), compared to children in good quality housing. This finding supports the case for early intervention strategies that account for children's housing circumstances.

Skeleton-based noise removal algorithm for binary concrete crack image segmentation

Image processing methods for automated concrete crack detection are often challenged by binary noise. Noise removal methods decrease the false positive pixels of crack detection results, often at the cost of a reduction in true positives. This paper proposes a novel method for binary noise removal and segmentation of noisy concrete crack images. The method applies an area threshold before reducing the pixel groups in the image to a skeleton. Each skeleton is connected to its nearest neighbour before the remaining short skeletons in the image are removed using a length threshold. A morphological reconstruction follows to remove all elements in the original noisy image that do not intersect with the skeleton. Finally, pixel groups in close proximity to the endpoints of the pixel groups in the resulting image are reinstated. Testing was conducted on a dataset of noisy binary crack images; the proposed method (Skele-Marker) obtained recall, precision, intersection over union, and F1 score results of 77%, 91%, 72%, and 84%, respectively. Skele-Marker was compared to other methods found in literature and was found to outperform other methods in terms of precision, intersection over union and F1 score. The proposed method is used to make crack detection results more reliable, supporting the ever-growing demand for automated inspections of concrete structures.

An Optimized Method for Polar Code Construction

Polar codes are traditionally constructed by calculating the reliability of channels, then sorting them by intensive calculations to select the most reliable channels. However, these operations can be complicated especially when, the polar code length, N becomes great. This paper proposes a new low-complexity procedure for polar codes construction over binary erasure and additive white Gaussian noise (AWGN) channels. Using the proposed algorithm, the code construction complexity is reduced from O(Nlog N) to O(N), where N=2n (n≥1). The proposed approach involves storing the classification of channels by reliabilities in a vector of length L, and then deriving the classification of M channels for every M where M<=L. The proposed method is consistent with Bhattacharya parameter based Construction and Density Evolution with Gaussian Approximation (DEGA) based construction. In this paper, the Successive Cancellation Decoding algorithm (SCDA) is used. Thanks to its low complexity and its high error-correction capability.

Dynamic accentuated antagonism of heart rate control during different levels of vagal nerve stimulation intensity in rats.

Accentuated antagonism refers to a phenomenon in which the vagal effect on heart rate (HR) is augmented by background sympathetic tone. The dynamic aspect of accentuated antagonism remains to be elucidated during different levels of vagal nerve stimulation (VNS) intensity. We performed VNS on anesthetized rats (n = 8) according to a binary white noise signal with a switching interval of 500 ms at three different stimulation rates (low-intensity: 0-10 Hz, moderate-intensity: 0-20 Hz, and high-intensity: 0-40 Hz). The transfer function from VNS to HR was estimated with and without concomitant tonic sympathetic nerve stimulation (SNS) at 5 Hz. The asymptotic low-frequency (LF) gain (in beats/min/Hz) of the transfer function increased with SNS regardless of the VNS rate [low-intensity: 3.93 ± 0.70 vs. 5.82 ± 0.65 (P = 0.021), moderate-intensity: 3.87 ± 0.62 vs. 5.36 ± 0.53 (P = 0.018), high-intensity: 4.77 ± 0.85 vs. 7.39 ± 1.36 (P = 0.011)]. Moreover, SNS slightly increased the ratio of high-frequency (HF) gain to the LF gain. These effects of SNS were canceled by the pretreatment of ivabradine, an inhibitor of hyperpolarization-activated cyclic nucleotide-gated channels, in another group of rats (n = 6). Although background sympathetic tone antagonizes the vagal effect on mean HR, it enables finer HR control by increasing the dynamic gain of the vagal HR transfer function regardless of VNS intensity. When interpreting the HF component of HR variability, the augmenting effect from background sympathetic tone needs to be considered.

A Real-Time Tunable ECG Noise-Aware System for IoT-Enabled Devices

The Internet of Things (IoT)-enabled electrocardiogram (ECG) monitoring system is an evolution in healthcare, and it is used to monitor heart conditions during daily living conditions. However, the ECG signals from the wearable device are often contaminated with noise, such as power line interference, baseline wander, and muscle artefact. The presence of these noises increases the communication cost of IoT-enabled devices by transmitting unusable noisy signals as well as affecting the clinical decision-making at the application level. A real-time ECG noise detection system at the IoT-enabled gateway can reduce this communication cost and improve the overall quality of the transmitted signal. In this article, we propose a tunable ECG noise localization system to detect noisy ECG segments with a selected percentage of noise-free ECG levels. The proposed system will hold the following: 1) deployable ECG noise detector in the low-computational devices, such as smart phone; 2) reduce the data dropping rate at the network layer; 3) reduce the transmission cost; and 4) improve the reliability of the automated analysis of ECG at the IoT-enabled gateway. We evaluated the performance of the proposed ECG noise detector using publicly available and real-time ECG datasets from wearable ECG sensors. We also measured the data drop rate and compared it with the state-of-the-art algorithms. The impact of reduced data dropping rate also justifies using two commonly used R-peak detection algorithms. The proposed system reduces the data dropping rate by 21.09% on average over public and real-time datasets. Similarly, it increases the number of R-Peak detection by 15.33% on average compared with the existing binary noise classification system by saving partial noisy ECG segments. Thus, the proposed noise detection system improves the reliability of the automated ECG analysis. In summary, the study results support the necessity of a noise detection system for wearable ECG monitoring in daily living conditions to improve the data acquisition efficiency. In addition, a noise localizer can be used for dropping a noisy portion of the signal or filtering the only noisy segment of the ECG signal without blindly imposing a filter on both noise-free and noisy ECG signals.

Rate‐compatible spatially coupled LDPC code ensembles by partial repetition extension

Herein, one partial repetition extension method is proposed to construct the rate-compatible spatially coupled low-density parity-check (RC-SCLDPC) codes. For each position of the base SCLDPC code, a certain proportion of the variable nodes are first selected randomly and then repeated a certain number of times. By adjusting the selection proportions and the repetition times, a family of RC-SCLDPC codes with arbitrary rates from 0 to the rate of the base SCLDPC code can be obtained and the rate-compatibility is realized. Threshold analysis results show that all member codes in the proposed RC-SCLDPC code family display capacity-approaching thresholds over the binary erasure channel and additive white Gaussian noise channel. Finite length simulation results also confirm their excellent thresholds. Moreover, the decoding complexity can be significantly decreased using this partial repetition extension method.

Screening Dominance: A Comparison of Noisy Signals

This paper studies the impact of noisy signals on screening processes. It deals with a decision problem in which a decision-maker screens a set of elements based on noisy unbiased evaluations. Given that the decision-maker uses threshold strategies, we show that additional binary noise can potentially improve a screening, an effect that resembles a “ lucky coin toss.” We compare different noisy signals under threshold strategies and optimal ones, and we provide several characterizations of cases in which one noise is preferable over another. Accordingly so, we establish a novel method to compare noise variables using a contraction mapping between percentiles. (JEL D82)

Polar Coded Repetition

Constructing efficient low-rate error-correcting codes with low-complexity encoding and decoding has become increasingly important for applications involving ultra-low-power devices such as Internet-of-Things (IoT). To this end, schemes based on concatenating the state-of-the-art codes at moderate rates with repetition codes have emerged as practical solutions deployed in various standards. In this paper, we propose a novel mechanism for concatenating outer polar codes with inner repetition codes which we refer to as polar coded repetition. More specifically, we propose to transmit a slightly modified polar codeword by deviating from Arıkan’s standard <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2 \times 2$ </tex-math></inline-formula> Kernel in a certain number of polarization recursions at each repetition block. We show how this modification can improve the asymptotic achievable rate of the standard polar-repetition scheme, while ensuring that the overall encoding and decoding complexity is kept almost the same. The achievable rate is analyzed for the binary erasure channel (BEC) and additive white Gaussian noise (AWGN) channel. Moreover, we show that the finite-length performance of the polar coded repetition scheme under cyclic redundancy check (CRC) aided successive cancellation list (SCL) decoder over AWGN channel is better than the uncoded polar-repetition scheme at the cost of a slight increase in decoding complexity. We also compare the proposed scheme, in terms of performance and complexity, with other low-rate solution based on polar codes in the literature.

Deep learning approach for full-field displacement estimation in depth-resolved wavelength-scanning interferometry

To minimize the effect of optical crosstalk-generated noise (crosstalk), we present a deep learning approach to precisely estimate the full-field displacements for depth-resolved wavelength-scanning interferometry (DRWSI). A deep convolution neural network, where the transformer block is introduced to effectively capture higher-order features of the wrapped phase difference map in a strong noise environment, is applied for phase unwrapping. Furthermore, a binary phase noise map is used to update the loss function in an improved training model, enhancing the network generalization. Finally, the full-field displacements are estimated from phase unwrapping maps with a high signal-to-noise ratio. The simulation and the loading experiment verified that a higher accuracy reconstruction of displacement is implemented using our approach. The contribution of this work can make the DRWSI more practical in quantifying the mechanical property inside the sample.

Dynamics of Temporal Integration in the Lateral Geniculate Nucleus.

Before visual information from the retina reaches primary visual cortex (V1), it is dynamically filtered by the lateral geniculate nucleus (LGN) of the thalamus, the first location within the visual hierarchy at which nonretinal structures can significantly influence visual processing. To explore the form and dynamics of geniculate filtering we used data from monosynpatically connected pairs of retinal ganglion cells (RGCs) and LGN relay cells in the cat that, under anesthetized conditions, were stimulated with binary white noise and/or drifting sine-wave gratings to train models of increasing complexity to predict which RGC spikes were relayed to cortex, what we call “relay status.” In addition, we analyze and compare a smaller dataset recorded in the awake state to assess how anesthesia might influence our results. Consistent with previous work, we find that the preceding retinal interspike interval (ISI) is the primary determinate of relay status with only modest contributions from longer patterns of retinal spikes. Including the prior activity of the LGN cell further improved model predictions, primarily by indicating epochs of geniculate burst activity in recordings made under anesthesia, and by allowing the model to capture gain control-like behavior within the awake LGN. Using the same modeling framework, we further demonstrate that the form of geniculate filtering changes according to the level of activity within the early visual circuit under certain stimulus conditions. This finding suggests a candidate mechanism by which a stimulus specific form of gain control may operate within the LGN.

Improved noisy gradient descent bit-flipping algorithm over Rayleigh fading channel

&lt;span&gt;Gradient descent bit flipping (GDBF) and its many variants have offered remarkable improvements over legacy, or modified, bit flipping decoding techniques in case of decoding low density parity check (LDPC) codes. GDBF method and its many variants, such as noisy gradient descent bit flipping (NGDBF) have been extensively studied and their performances have been assessed over multiple channels such as binary symmetric channel (BSC), binary erasure channel (BEC) and additive white Gaussian noise (AWGN) channel. However, performance of the said decoders in more realistic channels or channel conditions have not been equally studied. An improved noisy gradient descent bit flipping algorithm is proposed in this paper that optimally decodes LDPC encoded codewords over Rayleigh fading channel and under various fade rates. Comparing to NGDBF method, our proposed decoder provides substantial improvements in both error performance of the code, and in the number of iterations required to achieve the said error performance. It subsequently reduces the end-to-end latency in applications with low or ultra-low latency requirements.&lt;/span&gt;

An adaptive IMM filter for jump Markov systems with inaccurate noise covariances in the presence of missing measurements

This paper derives a Kullback-Leibler average (KLA) based adaptive interacting multiple model (IMM) filter for jump Markov systems with inaccurate noise covariances in the presence of missing measurements. Firstly, a switching error model (SEM) is constructed to model the probability density function of measurement likelihood. The SEM can automatically choose appropriate error model for the real measurement or pure measurement noise by estimating a binary indicator. Secondly, by assigning conjugate priors on inaccurate noise covariances and binary indicator, the state, noise covariances and binary indicator are jointly estimated based on variational Bayesian (VB) technique. Finally, by using the KLA fusion scheme to fuse the conditioned estimates from every mode in the mixing and output phase, an adaptive IMM filter is derived. Simulation results demonstrate that the proposed filter achieves better performance than existing typical algorithms.

High-contrast, speckle-free, true 3D holography via binary CGH optimization

Holography is a promising approach to implement the three-dimensional (3D) projection beyond the present two-dimensional technology. True 3D holography requires abilities of arbitrary 3D volume projection with high-axial resolution and independent control of all 3D voxels. However, it has been challenging to implement the true 3D holography with high-reconstruction quality due to the speckle. Here, we propose the practical solution to realize speckle-free, high-contrast, true 3D holography by combining random-phase, temporal multiplexing, binary holography, and binary optimization. We adopt the random phase for the true 3D implementation to achieve the maximum axial resolution with fully independent control of the 3D voxels. We develop the high-performance binary hologram optimization framework to minimize the binary quantization noise, which provides accurate and high-contrast reconstructions for 2D as well as 3D cases. Utilizing the fast operation of binary modulation, the full-color high-framerate holographic video projection is realized while the speckle noise of random phase is overcome by temporal multiplexing. Our high-quality true 3D holography is experimentally verified by projecting multiple arbitrary dense images simultaneously. The proposed method can be adopted in various applications of holography, where we show additional demonstration that realistic true 3D hologram in VR and AR near-eye displays. The realization will open a new path towards the next generation of holography.

On Decoding of Reed-Muller Codes Using a Local Graph Search

We present a novel iterative decoding algorithm for Reed-Muller (RM) codes, which takes advantage of a graph representation of the code. Vertices of the considered graph correspond to codewords, with two vertices being connected by an edge if and only if the Hamming distance between the corresponding codewords equals the minimum distance of the code. The algorithm uses a greedy local search to find a node optimizing a metric, e.g. the correlation between the received vector and the corresponding codeword. In addition, the cyclic redundancy check can be used to terminate the search as soon as a valid codeword is found, leading to an improvement in the average computational complexity of the algorithm. Simulation results for both binary symmetric channel and additive white Gaussian noise channel show that the presented decoder approaches the performance of maximum likelihood decoding for RM codes of length less than 1024 and for the second-order RM codes of length less than 4096. Moreover, it is demonstrated that the considered decoding approach outperforms state-of-the-art decoding algorithms of RM codes with similar computational complexity for a wide range of block lengths and rates.

Data-driven Models for Advanced Control of Acid Gas Treatment in Waste-to-energy Plants

This paper presents a study of identification and validation of data-driven models for the description of the acid gas treatment process, a key step of flue gas cleaning in waste-to-energy plants. The acid gas removal line of an Italian plant, based on the injection of hydrated lime, Ca(OH)2, for the abatement of hydrogen chloride, HCl, is investigated. The final goal is to minimize the feed rate of reactant needed to achieve the required HCl removal performance, also reducing as a consequence the production of solid process residues. Process data are collected during dedicated plant tests carried out by imposing Generalized Binary Noise (GBN) sequences to the flow rate of Ca(OH)2. Various input-output and state-space models are identified with success, and related model orders are optimized. The models are then validated on different datasets of routine plant operation. The proposed modeling approach appears reliable and promising for control purposes, once implemented into advanced model-based control structures.

Ivabradine increases the high frequency gain ratio in the vagal heart rate transfer function via an interaction with muscarinic potassium channels.

Muscarinic potassium channels (I K,ACh) are thought to contribute to the high frequency (HF) dynamic heart rate (HR) response to vagal nerve stimulation (VNS) because they act faster than the pathway mediated by hyperpolarization‐activated cyclic nucleotide‐gated (HCN) channels. However, the interactions between the two pathways have not yet been fully elucidated. We previously demonstrated that HCN channel blockade by ivabradine (IVA) increased the HF gain ratio of the transfer function from VNS to HR. To test the hypothesis that IVA increases the HF gain ratio via an interaction with I K,ACh, we examined the dynamic HR response to VNS under conditions of control (CNT), I K,ACh blockade by tertiapin‐Q (TQ, 50 nM/kg), and TQ plus IVA (2 mg/kg) (TQ + IVA) in anesthetized rats (n = 8). In each condition, the right vagal nerve was stimulated for 10 min with binary white noise signals between 0–10, 0–20, and 0–40 Hz. On multiple regression analysis, the HF gain ratio positively correlated with the VNS rate with a coefficient of 1.691 ± 0.151 (×0.01) (p < 0.001). TQ had a negative effect on the HF gain ratio with a coefficient of −1.170 ± 0.214 (×0.01) (p < 0.001). IVA did not significantly increase the HF gain ratio in the presence of TQ. The HF gain ratio remained low under the TQ + IVA condition compared to controls. These results affirm that the IVA‐induced increase in the HF gain ratio is dependent on the untethering of the hyperpolarizing effect of I K,ACh.

Optimal Rates of Teaching and Learning Under Uncertainty

In this paper, we consider a recently-proposed model of teaching and learning under uncertainty, in which a teacher receives independent observations of a single bit corrupted by binary symmetric noise, and sequentially transmits to a student through another binary symmetric channel based on the bits observed so far. After a given number <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> of transmissions, the student outputs an estimate of the unknown bit, and we are interested in the exponential decay rate of the error probability as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> increases. We propose a novel block-structured teaching strategy in which the teacher encodes the number of 1s received in each block, and show that the resulting error exponent is the binary relative entropy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D\left({\frac {1}{2}\|\max (p,q)}\right)$ </tex-math></inline-formula> , where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> are the noise parameters. This matches a trivial converse result based on the data processing inequality, and settles two conjectures of [Jog and Loh, 2021] and [Huleihel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , 2019]. In addition, we show that the computation time required by the teacher and student is linear in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> . We also study a more general setting in which the binary symmetric channels are replaced by general binary-input discrete memoryless channels. We provide an achievability bound and a converse bound, and show that the two coincide in certain cases, including (i) when the two channels are identical, and (ii) when the student-teacher channel is a binary symmetric channel. More generally, we give sufficient conditions under which our learning rate is the best possible for block-structured protocols.

Adaptive incremental method for strain estimation in phase-sensitive optical coherence elastography.

We proposed an adaptive incremental method for the cumulative strain estimation in phase-sensitive optical coherence elastography. The method firstly counts the amount of phase noise points by mapping a binary noise map. After the noise threshold value is preset, the interframe interval is adaptively adjusted in terms of the phase noise ratio. Finally, the efficient estimation of cumulative strain is implemented by reducing the cumulative number. Since the level of phase noise is related to the different strain rates in accordance with the speckle decorrelation, the proposed method can estimate the large strains with high computation efficiency as well as signal-to-noise ratio (SNR) enhancement in nonlinear change of sample deformations. Real experiments of visualizing polymerization shrinkage with nonlinear change of deformations were performed to prove the superiority of adaptive incremental method in estimating the large strains. The proposed method expands the practicability of the incremental method in more complex scenes.

Estimation of trend and random components of conditional random field using Gaussian process regression

A method is proposed for simultaneously estimating the trend and random component of soil properties at arbitrary locations using Gaussian process regression with the superposition of multiple Gaussian random fields. The proposed method is applied to the estimation of the one-dimensional spatial distributions of the trend component of three synthetic datasets. A comparison of three covariance functions, namely Gaussian, Markovian, and binary noise, indicates that Gaussian covariance is most suitable for trend estimation. The scale of fluctuation and the standard deviation of the random component of the examples are estimated using the maximum likelihood estimation method. The proposed method is also applied to the estimation of the three-dimensional spatial distribution of the trend and random components based on measured cone penetration test data. It is shown that the trend and random components at arbitrary locations can be estimated. The Whittle-Matérn covariance function is found to be more suitable than the Markovian covariance function for the estimation of the random component of the cone penetration test data based on the Akaike information criterion and the Bayesian information criterion.

Ivabradine augments high-frequency dynamic gain of the heart rate response to low- and moderate-intensity vagal nerve stimulation under β-blockade.

Our previous study indicated that intravenously administered ivabradine (IVA) augmented the dynamic heart rate (HR) response to moderate-intensity vagal nerve stimulation (VNS). Considering an accentuated antagonism, the results were somewhat paradoxical; i.e., the accentuated antagonism indicates that an activation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels via the accumulation of intracellular cyclic adenosine monophosphate (cAMP) augments the HR response to VNS, whereas the inhibition of HCN channels by IVA also augmented the HR response to VNS. To remove the possible influence from the accentuated antagonism, we examined the effects of IVA on the dynamic vagal control of HR under β-blockade. In anesthetized rats (n = 7), the right vagal nerve was stimulated for 10 min according to binary white noise signals between 0 and 10 Hz (V0-10), between 0 and 20 Hz (V0-20), and between 0 and 40 Hz (V0-40). The transfer function from VNS to HR was estimated. Under β-blockade (propranolol, 2 mg/kg iv), IVA (2 mg/kg iv) did not augment the asymptotic low-frequency gain but increased the asymptotic high-frequency gain in V0-10 (0.53 ± 0.10 vs. 1.74 ± 0.40 beats/min/Hz, P < 0.01) and V0-20 (0.79 ± 0.14 vs. 2.06 ± 0.47 beats/min/Hz, P < 0.001). These changes, which were observed under a minimal influence from sympathetic background tone, may reflect an increased contribution of the acetylcholine-sensitive potassium channel (IK,ACh) pathway after IVA, because the HR control via the IK,ACh pathway is faster and acts in the frequency range higher than the cAMP-mediated pathway.NEW & NOTEWORTHY Since ivabradine (IVA) inhibits hyperpolarization-activated cyclic nucleotide-gated channels, interactions among the sympathetic effect, vagal effect, and IVA can occur in the control of heart rate (HR). To remove the sympathetic effect, we estimated the transfer function from vagal nerve stimulation to HR under β-blockade in anesthetized rats. IVA augmented the high-frequency dynamic gain during low- and moderate-intensity vagal nerve stimulation. Untethering the hyperpolarizing effect of acetylcholine-sensitive potassium channels after IVA may be a possible underlying mechanism.