Results 71 to 80 of about 2,034 (255)
ABSTRACT According to prevalent views, autistic individuals have a stronger tendency to allocate attention to details, as supported by reports of enhanced visual search performance. However, both the dynamics and the types of information involved in attentional guidance in autism are not fully understood.
Zainab Naaran, Amit Yashar
wiley +1 more source
Intact Visual Correlation Detection in Autistic Adults
ABSTRACT The ability to detect recurring temporal co‐occurrence, or temporal correlation, of sensory events is fundamental for organizing perceptual input into coherent representations. Although past work has revealed differences across several aspects of temporal processing in autism, it is unknown whether autistic and non‐autistic individuals differ ...
Lukas Vogelsang +6 more
wiley +1 more source
Aims To determine the prevalence of non‐adherence to antihypertensive medicines and to identify demographic and behavioral factors associated with non‐adherence in subjects enrolled in the May Measurement Month (MMM) 2023, as part of the permanent public health action Hunting the silent killer.
Valerija Bralić Lang +12 more
wiley +1 more source
AI voice journaling for future language teachers: A path to well‐being through reflective practices
Abstract This study aimed to explore the perceived impact of using an AI‐powered voice journaling app in overcoming the challenges and stressors encountered by senior students enrolled in teaching practicum at an English Language Teaching Bachelor's programme.
Bora Demir, Duygu Özdemir
wiley +1 more source
Abstract As front‐line observers and active participants in pupils' daily lives, teachers closely monitor pupils' social interactions, emotional states and behavioural changes. Their unique perspective enables them to detect problems in the social lives of their pupils that may not be immediately visible to peers, parents or mental health professionals.
Yixuan Zheng +4 more
wiley +1 more source
Detection of Driver Distraction Using Spatio-Temporal Graph Convolutional Networks (ST-GCN) and Attention Mechanism [PDF]
Detecting driver distraction is critically important, as it remains a major contributor to road accidents and traffic-related injuries worldwide. This study introduces a novel hybrid deep learning model that integrates Spatio-Temporal Graph Convolutional
Mahdi Davari, Razieh Rastgoo
doaj +1 more source
Dual-Flow Driver Distraction Driving Detection Model Based on Sobel Edge Detection
Cognitive or visual distraction caused by drivers using mobile phones, operating the central console, or conversing with passengers while driving is a significant contributing factor to road traffic accidents.
Binbin Qin, Bolin Zhang
doaj +1 more source
Abstract School Attendance Problems (SAPs) represent a significant challenge requiring early identification and intervention. Current service provision often does not recognise early indicators that parents observe, creating gaps between when initial concerns are raised and formal support is provided.
Tereza Aidonopoulou‐Read +4 more
wiley +1 more source
Chilean science teachers' conceptualisations of disability when teaching students with autism
Abstract This study examines how Chilean secondary science teachers conceptualise disability when teaching students with autism in integrated classroom settings. Grounded in critical disability studies, the research employs a qualitative story‐completion method, using a fictional classroom scenario to prompt teachers to construct narratives that reveal
Alexis Gonzalez‐Donoso +1 more
wiley +1 more source
Distracted Driver Detection Using AI
Driver distraction has emerged as one of the leading causes of road accidents in recent years, posing a significant threat to public safety. Tackling this critical issue has become a priority for researchers worldwide, leading to the development of various methodologies aimed at detecting and mitigating driver distraction.
null Ms. Rekha M S +3 more
openaire +3 more sources

