No abstract

The authors derive closed form solutions for the minimum mean square error (MMSE) and maximum a posteriori estimators for speech enhancement in additive Gaussian noise assuming a t-location-scale probability density function (PDF) as clean speech prior. Fitting a t-location-scale PDF to the real and imaginary parts of the discrete fourier transform (DFT) coefficients of clean speech signals demonstrates the lower Jensen-Shannon divergence compared to the other heavy-tailed distributions such as Laplacian and gamma. The authors utilise the two presented estimators along with the Wiener filter and MMSE estimators based on Laplacian, gamma, and generalised gamma prior PDFs to enhance noisy signals from the NOIZEUS database. All the estimators are compared together in terms of both signal and noise distortions. The obtained results show that their proposed MMSE estimator results in the minimum squared error and signal distortion to estimate the complexvalued DFT coefficients of speech. The quality assessments of the enhanced signals are also performed in terms of perceptual evaluation of speech quality, segmental and general SNRs.

No abstract

No abstract

No abstract

Background: Based upon WHO (World Health Organization) Coronavirus Dashboard more than 5 million deaths worldwide have been attributed to the COVID-19 (Coronavirus Disease 2019) caused by the SARS-Cov-2 virus (Severe Acute Respiratory Syndrome Coronavirus) till November 2021. The annual flu vaccination has raised many questions about the vaccine's effects on Covid-19 outcomes. Several possible mechanisms including cross-reactivity and cross-protection have been reported to be responsible for the potential protective effect of the flu vaccine on the COVID-19 infection. This study was performed to evaluate the possible effect of the influenza vaccine on the disease severity, the mortality rate, and the length of hospitalization in COVID-19 patients.  Methods: The data of 1300 patients were recorded from May 2020 to October 2020. Patients with a previous history of COVID-19, patients under 18 years old, and patients who did not have accurate information about their influenza vaccination history were excluded. 498 hospitalized unvaccinated COVID-19 patients with typical clinical manifestations and a positive PCR (Polymerase Chain Reaction) test for COVID-19 were included in this observational, cross-sectional study. The participants were divided into two groups (vaccinated and unvaccinated) based on the history of influenza vaccination at the time of admission. Results: The length of hospital stay was lower in the vaccinated compared to the unvaccinated group (p < 0.05). However, there was no significant difference between the mortality rate, the need for ICU (Intensive Care Unit) admission, and the severity of the disease between the two groups (p> 0.05). Conclusion: Since the patients studied in this article did not receive any of the Covid-19 vaccines; Therefore, the effect of influenza vaccination on the clinical course of Covid-19 can be evaluated using the results of this study. A longer length of hospital stay was observed in the unvaccinated patients in our study, which may suggest the possible protective effect of the influenza vaccine against COVID-19.

No abstract

Utilizing unmanned aerial vehicles (UAVs) as aerial base stations is a new and promising technology that enables the connectivity of a large volume of devices such as sensors and machines, referred to as massive Internet of Things (mIoT). This article aims to analyze and optimize the area spectral efficiency (ASE) by investigating the efficient deployment of UAVs to ensure reliable uplink communication from ground IoT devices to UAVs. We utilize the tools from stochastic geometry to derive the closed form expression of the ASE in the interference-limited regime. We propose a novel framework for maximizing the ASE of UAV-enabled networks by simultaneous optimization of UAVs' altitude and density. The simulation results demonstrate that deploying UAVs with combined optimal density and altitude outperforms more conventional deployment strategies in terms of the ASE.