The superdirective beamformer, while attractive for processing broadband acoustic signals, often suffers from the problem of white noise amplification. So, its application requires well-designed acoustic arrays with sensors of extremely low self-noise level, which is difficult if not impossible to attain. In this paper, a new binaural superdirective beamformer is proposed, which is divided into two sub-beamformers. Based on studies and facts in psychoacoustics, these two filters are designed in such a way that they are orthogonal to each other to make the white noise components in the binaural beamforming outputs incoherent while maximizing the output interaural coherence of the diffuse noise, which is important for the brain to localize the sound source of interest. As a result, the signal of interest in the binaural superdirective beamformer's outputs is in phase but the white noise components in the outputs are random phase, so the human auditory system can better separate the acoustic signal of interest from white noise by listening to the outputs of the proposed approach. Experimental results show that the derived binaural superdirective beamformer is superior to its conventional monaural counterpart.
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http://dx.doi.org/10.3390/s21010074 | DOI Listing |
Alzheimers Dement
December 2024
Cumulus Neuroscience, Dublin, Ireland.
Background: Current tools for Alzheimer's disease screening and staging used in clinical research (e.g. ACE-3, ADAS-Cog) require substantial face-to-face time with trained professionals, and may be affected by subjectivity, "white coat syndrome" and other biases.
View Article and Find Full Text PDFKorean J Radiol
January 2025
Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.
Materials And Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.
Sci Rep
January 2025
Faculty of Life and Allied Health Sciences, MS Ramiah University of Applied Sciences (RUAS), MSR Nagar, New BEL Road, Bangalore, 560054, India.
Background Breast cancer represents a significant public health concern in India, accounting for 28% of all cancer diagnoses and imposing a substantial economic burden. This study introduces a novel approach to forecasting the number of breast cancer cases (based on prevalence rates) and estimating the associated economic impact in India using the autoregressive integrated moving average (ARIMA) model. Methods Data on the prevalence of breast cancer in India from 2000 to 2021 were obtained from the Global Burden of Disease (GBD) database.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institut FEMTO-ST, Université de Franche-Comté, CNRS, F-25000 Besançon, France.
Optical density measurement has been used for decades to determine the microorganism concentration and more rarely for mammalian cells. Although this measurement can be carried out at any wavelength, studies report a limited number of measurement wavelengths, mainly around 600 nm, and no consensus seems to be emerging to propose an objective method for determining the optimum measurement wavelength for each microorganism. In this article, we propose a method for analyzing the absorbance spectra of ESKAPEE bacteria and determining the optimum measurement wavelength for each of them.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Key Laboratory of Science and Technology on Micro-System, Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences, Shanghai 200050, China.
Frequency-modulated continuous-wave (FMCW) radar is used to extract range and velocity information from the beat signal. However, the traditional joint range-velocity estimation algorithms often experience significant performances degradation under low signal-to-noise ratio (SNR) conditions. To address this issue, this paper proposes a novel approach utilizing the complementary ensemble empirical mode decomposition (CEEMD) combined with singular value decomposition (SVD) to reconstruct the beat signal prior to applying the FFT-Root-MUSIC algorithm for joint range and velocity estimation.
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