Information has become more accessible than ever due to web technologies, standards, and assistive technologies. Still, here are unresolved issues that can hinder equal access to all. This study reports on work-in-progress ...

The emergence of new technologies changes how students’ study and learn. This project investigated relationships between voice assistants and students’ study efficacy, effectiveness, and efficiency. A questionnaire was ...

Individuals with reduced vision may rely on handheld magnifiers for near reading of texts on household items such as food packaging, and far reading of information notices and signposts. Smartphones have become favoured ...

Deep Neural Networks have been shown to perform poorly or even fail altogether when deployed in real-world settings, despite exhibiting excellent performance on initial benchmarks. This typically occurs due to relative ...

Importance: Lumber disc herniation surgery can reduce pain and disability. However, a sizable minority of individuals experience minimal benefit, necessitating the development of accurate prediction models. Objective: ...

We address ECG data classification, using methods from explainable artificial intelligence (XAI). In particular, we focus on the extended performance of the ST-CNN-5 model compared to established mod- els. The model ...

This paper introduces a novel solution for personal recommendation in consumer electronic applications. It addresses, on the one hand, the data confidentiality during the training, by exploring federated learning and trusted ...

Advances in Deep Learning (DL), Big Data and image processing have facilitated online disinformation spreading through Deepfakes. This entails severe threats including public opinion manipulation, geopolitical tensions, ...

Artificial intelligence-based algorithms are widely adopted in critical applications such as healthcare and autonomous vehicles. Mitigating the security and privacy issues of AI models, and enhancing their trustworthiness ...

One of the most challenging problems when diagnosing autism spectrum disorder (ASD) is the need for long sets of data. Collecting data during such long periods is challenging, particularly when dealing with children. This ...