Embodied AI and the Educational Turn – From Cognition to Situated Presence

This chapter explores the transformative potential of embodied artificial intelligence (Embodied AI) in education, focusing on fragile learning ecologies such as rural schools and homebound instruction. Grounded in the theoretical framework of embodied cognition, the work critically reframes educational technology by emphasizing the bodily, relational, and emotional dimensions of learning. Drawing on international literature and Italian case studies—particularly those involving small schools ...

Polynomial Normal Transformations and Quasi-Monte Carlo Method for Probabilistic Voltage Stability Analysis

The inherent randomness of renewable and demand powers has significantly increased the importance of probabilistic techniques in the operation and planning of power systems. In this context, the paper introduces a novel approach for probabilistic voltage stability analysis in unbalanced power systems. We employ the polynomial normal transformations (PNTs) to accurately model input variable uncertainties. PNT’s versatility allows it to represent a wide range of probability distributions and ef...

Artificial Intelligence and Machine Learning in Project Management

GraphSAGEnES: A Graph Neural Network Designed for Graphs with Low Feature Discriminability

Graph Neural Networks (GNNs) have emerged as powerful tools for learning representations of structured data. An essential element of these models is neighborhood aggregation, where a node’s representation is updated based on its context (neighbors). Some variants of GNNs consider only local neighbor information during node updating. Ignoring global structural details leads to inadequate learning and differentiation of graph structures. To address these challenges, we introduce GraphSAGEnES (G...