Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics,
cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer …

The majority of machine learning methodologies operate with the assumption that their
environment is benign. However, this assumption does not always hold, as it is often …

Deep Neural Networks (DNN) are vulnerable to adversarial samples that are generated by
perturbing correctly classified inputs to cause DNN models to misbehave (eg …

The introduction of deep learning (DL) technology can improve the performance of cyber–
physical systems (CPSs) in many ways. However, this also brings new security issues. To …

Deep Learning (DL) models have created a paradigm shift in our ability to comprehend raw
data in various important fields, ranging from intelligence warfare and healthcare to …

The future of work embodies changes to the workplace, work, and workforce, which require
additional occupational safety and health (OSH) stakeholder attention. Examples include …

In recent years, advancements in the field of the artificial intelligence (AI) gained a huge
momentum due to the worldwide appliance of this technology by the industry. One of the …

The pervasiveness of abusive content on the internet can lead to severe psychological and
physical harm. Significant effort in Natural Language Processing (NLP) research has been …

Deep Learning (DL) models have caused a paradigm shift in our ability to comprehend raw
data in various important fields, ranging from intelligence warfare and healthcare to …

Given the availability of abundant data, deep learning models have been advanced and
become ubiquitous in the past decade. In practice, due to many different reasons (eg …