Navigation in cluttered environments is an important challenge for animals and robots alike and has been the subject of many studies trying to explain and mimic animal navigational abilities. However, the question of selecting an appropriate home location has, so far, received only little attention. This is surprising, since the choice of a home location might greatly influence an animal's navigation performance. To address the question of home choice in cluttered environments, a systematic analysis of homing trajectories was performed by computer simulations using a skyline-based local homing method. Our analysis reveals that homing performance strongly depends on the location of the home in the environment. Furthermore, it appears that by assessing homing success in the immediate vicinity of the home, an animal might be able to predict its overall success in returning to it from within a much larger area.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844572 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194070 | PLOS |
Int J Lang Commun Disord
January 2025
Division of Communication Sciences and Disorders, University of Cape Town, Rondebosch, South Africa.
Background: There is a global need for synthetic speech development in multiple languages and dialects, as many children who cannot communicate using their natural voice struggle to find synthetic voices on high-technology devices that match their age, social and linguistic background.
Aims: To document multiple stakeholders' perspectives surrounding the quality, acceptability and utility of newly created synthetic speech in three under-resourced South African languages, namely South African English, Afrikaans and isiXhosa.
Methods & Procedures: A mixed methods research design was selected.
J Neurosci
January 2025
Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo FI-00076, Finland.
Our visual system enables us to effortlessly navigate and recognize real-world visual environments. Functional magnetic resonance imaging (fMRI) studies suggest a network of scene-responsive cortical visual areas, but much less is known about the temporal order in which different scene properties are analysed by the human visual system. In this study, we selected a set of 36 full-colour natural scenes that varied in spatial structure and semantic content that our male and female human participants viewed both in 2D and 3D while we recorded magnetoencephalography (MEG) data.
View Article and Find Full Text PDFNoise Health
January 2025
Department of Neurology, Faculty of Medicine, Ondokuz Mayis University, Samsun, Turkey.
Background: Patients with multiple sclerosis (MS) experience difficulties in understanding speech in noise despite having normal hearing.
Aim: This study aimed to determine the relationship between speech discrimination in noise (SDN) and medial olivocochlear reflex levels and to compare MS patients with a control group.
Material And Methods: Sixty participants with normal hearing, comprising 30 MS patients and 30 healthy controls, were included.
Am J Audiol
January 2025
Department of Otolaryngology, University of Utah, Salt Lake City.
Purpose: Unilateral cochlear implant (CI) recipients with limited hearing in the contralateral ear are deprived of the advantages of binaural hearing. To address speech recognition challenges arising from the head shadow effect, a contralateral routing of signal (CROS) device can be used; however, less is known of the broader impact of a CROS device on an individual's quality of life (QoL) or that of their frequent communication partners (FCPs). This preliminary study aimed to evaluate the impact of CROS on speech recognition in noise and its influence on the QoL of unilateral CI recipients and their FCPs.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India.
In short-range microwave imaging, the collection of data in real environments for the purpose of developing techniques for target detection is very cumbersome. Simultaneously, to develop effective and efficient AI/ML-based techniques for target detection, a sufficiently large dataset is required. Therefore, to complement labor-intensive and tedious experimental data collected in a real cluttered environment, synthetic data generation via cost-efficient electromagnetic wave propagation simulations is explored in this article.
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