The Influence of Noise on the Vocal Dose in Women

2019 ◽  
Vol 33 (2) ◽  
pp. 214-219 ◽  
Author(s):  
Alessandra Terra Vasconcelos Rabelo ◽  
Juliana Nunes Santos ◽  
Bárbara Oliveira Souza ◽  
Ana Cristina Côrtes Gama ◽  
Max de Castro Magalhães
Keyword(s):  
Vocal Dose ◽  
Influence Of Noise

TECHNICAL SEISMICITY AND STRUCTURAL NOISE SPREADING FROM TRANSPORT - THEIR INFLUENCE ON BUILDINGS CONSTRUCTIONS

Akustika ◽  
2020 ◽  
Vol 36 (36) ◽  
pp. 35-45
Author(s):  
Jana Dolejší ◽  
Jan Dolejší
Keyword(s):  
Urban Areas ◽  
Rail Transport ◽  
Building Construction ◽  
Building Structures ◽  
Structural Noise ◽  
Railway Tunnel ◽  
Noise And Vibration ◽  
Influence Of Noise

This paper deals with the influence of noise and vibration sources from which vibrations propagate through subsoil into building structures. Structural noise is usually then emitted by building structures into interiors. Especially within city centers and urban areas the approach of building construction towards sources such as road and rail transport differ in particular, whether the objects are located directly above the metro or railway tunnel, or objects close to roads or railways.

scholarly journals Measuring the Influence of Noise Reduction on Listening Effort in Hearing-Impaired Listeners Using Response Times to an Arithmetic Task in Noise

2021 ◽  
Vol 25 ◽  
pp. 233121652110144
Author(s):  
Ilja Reinten ◽  
Inge De Ronde-Brons ◽  
Rolph Houben ◽  
Wouter Dreschler
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Speech Intelligibility ◽  
Response Times ◽  
Hearing Impaired ◽  
Listening Effort ◽  
Arithmetic Task ◽  
Test Retest Reliability ◽  
Influence Of Noise ◽  
Measured Response

Single microphone noise reduction (NR) in hearing aids can provide a subjective benefit even when there is no objective improvement in speech intelligibility. A possible explanation lies in a reduction of listening effort. Previously, we showed that response times (a proxy for listening effort) to an auditory-only dual-task were reduced by NR in normal-hearing (NH) listeners. In this study, we investigate if the results from NH listeners extend to the hearing-impaired (HI), the target group for hearing aids. In addition, we assess the relevance of the outcome measure for studying and understanding listening effort. Twelve HI subjects were asked to sum two digits of a digit triplet in noise. We measured response times to this task, as well as subjective listening effort and speech intelligibility. Stimuli were presented at three signal-to-noise ratios (SNR; –5, 0, +5 dB) and in quiet. Stimuli were processed with ideal or nonideal NR, or unprocessed. The effect of NR on response times in HI listeners was significant only in conditions where speech intelligibility was also affected (–5 dB SNR). This is in contrast to the previous results with NH listeners. There was a significant effect of SNR on response times for HI listeners. The response time measure was reasonably correlated ( R142 = 0.54) to subjective listening effort and showed a sufficient test–retest reliability. This study thus presents an objective, valid, and reliable measure for evaluating an aspect of listening effort of HI listeners.

scholarly journals Influence of Noise-Limited Censored Path Loss on Model Fitting and Path Loss-Based Positioning

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 987
Author(s):  
Aki Karttunen ◽  
Mikko Valkama ◽  
Jukka Talvitie
Keyword(s):  
Model Fitting ◽  
Path Loss ◽  
Threshold Level ◽  
Training Data ◽  
Link Distance ◽  
Strength Based ◽  
Radio Systems ◽  
Two Phases ◽  
Wireless Standards ◽  
Influence Of Noise

Positioning is considered one of the key features in various novel industry verticals in future radio systems. Since path loss (PL) or received signal strength-based measurements are widely available in the majority of wireless standards, PL-based positioning has an important role among positioning technologies. Conventionally, PL-based positioning has two phases—fitting a PL model to training data and positioning based on the link distance estimates. However, in both phases, the maximum measurable PL is limited by measurement noise. Such immeasurable samples are called censored PL data and such noisy data are commonly neglected in both the model fitting and in the positioning phase. In the case of censored PL, the loss is known to be above a known threshold level and that information can be used in model fitting and in the positioning phase. In this paper, we examine and propose how to use censored PL data in PL model-based positioning. Additionally, we demonstrate with several simulations the potential of the proposed approach for considerable improvements in positioning accuracy (23–57%) and improved robustness against PL model fitting errors.

Brain stem – from general view to computational model based on switchboard rules of operation

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Włodzisław Duch ◽  
Dariusz Mikołajewski
Keyword(s):  
Brain Stem ◽  
Large Scale ◽  
Ionic Channels ◽  
General View ◽  
The Central Nervous System ◽  
Network States ◽  
Large Scale Simulations ◽  
Influence Of Noise ◽  
The Brain ◽  
Sufficient Precision

Abstract Despite great progress in understanding the functions and structures of the central nervous system (CNS) the brain stem remains one of the least understood systems. We know that the brain stem acts as a decision station preparing the organism to act in a specific way, but such functions are rather difficult to model with sufficient precision to replicate experimental data due to the scarcity of data and complexity of large-scale simulations of brain stem structures. The approach proposed in this article retains some ideas of previous models, and provides more precise computational realization that enables qualitative interpretation of the functions played by different network states. Simulations are aimed primarily at the investigation of general switching mechanisms which may be executed in brain stem neural networks, as far as studying how the aforementioned mechanisms depend on basic neural network features: basic ionic channels, accommodation, and the influence of noise.

Influence of noise on the averaged false neighbors method for analyzing time series

2006 ◽  
Vol 223 (2) ◽  
pp. 229-241 ◽  
Author(s):  
Sofiane Ramdani ◽  
Jean-François Casties ◽  
Frédéric Bouchara ◽  
Denis Mottet
Keyword(s):  
Time Series ◽  
Influence Of Noise

On the Influence of Noise on the Bianchi ix and viii Cosmological Models

1998 ◽  
Vol 9 (11) ◽  
pp. 1813-1825 ◽  
Author(s):  
John Argyris ◽  
Ioannis Andreadis ◽  
Corneliu Ciubotariu
Keyword(s):  
Cosmological Models ◽  
Bianchi Ix ◽  
Influence Of Noise

Complex network structure of flocks in the Vicsek Model with Vectorial Noise

2014 ◽  
Vol 25 (03) ◽  
pp. 1350095 ◽  
Author(s):  
Gabriel Baglietto ◽  
Ezequiel V. Albano ◽  
Julián Candia
Keyword(s):  
Phase Transition ◽  
Complex Network ◽  
Network Structure ◽  
Time Step ◽  
Vicsek Model ◽  
Disorder Phase Transition ◽  
First Order ◽  
Direction Of Movement ◽  
Long Range Ordering ◽  
Influence Of Noise

In the Vicsek Model (VM), self-driven individuals try to adopt the direction of movement of their neighbors under the influence of noise, thus leading to a noise-driven order–disorder phase transition. By implementing the so-called Vectorial Noise (VN) variant of the VM (i.e. the VM-VN model), this phase transition has been shown to be discontinuous (first-order). In this paper, we perform an extensive complex network study of VM-VN flocks and show that their topology can be described as highly clustered, assortative, and nonhierarchical. We also study the behavior of the VM-VN model in the case of "frozen flocks" in which, after the flocks are formed using the full dynamics, particle displacements are suppressed (i.e. only rotations are allowed). Under this kind of restricted dynamics, we show that VM-VN flocks are unable to support the ordered phase. Therefore, we conclude that the particle displacements at every time-step in the VM-VN dynamics are a key element needed to sustain long-range ordering throughout.

Sign in / Sign up

Export Citation Format

Share Document