In traditional approaches to building software systems (that do not include an Artificial
Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) …

Abstract Context: Engineering Artificial Intelligence (AI) software is a relatively new area with
many challenges, unknowns, and limited proven best practices. Big companies such as …

Crop improvement and production domains encounter large amounts of expanding data
with multi-layer complexity that forces researchers to use machine-learning approaches to …

Artificial intelligence (AI) in its various forms finds more and more its way into complex
distributed systems. For instance, it is used locally, as part of a sensor system, on the edge …

Background Relaxation methods determine residual stresses by measuring the
deformations produced by incremental removal of a subdomain of the specimen. Measured …

Good test data is crucial for driving new developments in computer vision (CV), but two
questions remain unanswered: which situations should be covered by the test data, and how …

AI literacy commonly refers to essential skills and knowledge needed in a world where AI is
ubiquitous. This work explores the literature on AI literacy, aiming to understand how AI …

The inductive nature of artificial neural models makes dataset quality a key factor of their
proper functionality. For this reason, multiple research studies proposed metrics to assess …

Research on algorithms has drastically increased in recent years. Various sub-disciplines of
computer science investigate algorithms according to different objectives and standards …

Pain assessment is a vital part of newborn treatment in Intensive Care Units. However,
clinical pain assessment is highly subjective and does not support continual pain …