Graph neural networks (GNNs) have achieved effective performance in many graph-related
tasks involving recommendation systems, social networks, and bioinformatics. Recent …

In the digital world, social media have become important for people with disabilities in terms
of communication and visibility. They have also become the ideal place for activism, as they …

Introducción: Con el auge tecnológico y el despliegue de dispositivos digitales, el fenómeno
instagramer se convierte en una revolución global, produciendo un cambio del paradigma …

Malicious actors often use phishing attacks to compromise legitimate users' credentials.
Machine learning is a promising approach for phishing detection. While the accuracy of …

Supervised machine learning is often used to detect phishing websites. However, the
scarcity of phishing data for training purposes limits the classifier's performance. Further …

The automatic generation of digital twins of industrial processes requires the integration of
several sources of information. If the twin is expected to accurately capture thermo-hydraulic …

Among the operational shortfalls that hinder law enforcement from achieving greater
success in preventing terrorist attacks is the difficulty in dynamically assessing individualized …

Identification and tracking of individuals or groups perpetrating latent or emergent behaviors
are significant in home-land security, cyber security, behavioral health, and consumer …

When a sufficient amount of training data is available, Machine Learning (ML) models show
great promise for solving problems involving complex and dynamic patterns. Social and …

Identification and analysis of latent and emergent behavioral patterns are core tasks in
investigative domains such as homeland security, counterterrorism, and crime prevention …