El pasado 23 de Octubre se ha defendido en la ETSI de Telecomunicación la tesis doctoral de Óscar Araque, titulada "A Distributional Semantics Perspective of Lexical Resources for Affect Analysis: An application to Extremist Narratives". El acto ha transcurrido con normalidad, y la tesis ha recibido la máxima calificación, con la mención de Cum Laude.

El documento de la tesis se puede encontrar en este enlace.

The virtual kick-off of the TETRAMAX project VLP-Automation (Task Automation based on Visible Light Positioning and Blockchain) has been held on 3rd September 2020. 

The project VLP-Automation aims at designing and implementing a task automation and access management system that uses blockchain and Visible Light Positioning system based on Li-Fi indoor technology.

This system will have the ability to detect the approximate positioning of different objects/people using the LED lighting infrastructure already available and automate tasks based on this input .

The development will be based on an already existing hybrid VLC communication system (BEIA) integrated with the task automation platform (UPM)  

Un miembro del GSI, DIego Benito Sánchez, ha recibido el premio IN-NOVA al mejor TFM en Aplicaciones y Servicios para la Ciberdefensa y la Ciberseguridad, otorgado por la Asociación y el Colegio de Ingenieros de Telecomunicación.

The article "An Emotion-Aware Learning Analytics System Based on Semantic Task Automation" by Sergio Muñoz, Enrique Sánchez and Carlos A. Iglesias has been published in Electronics, indexed by JCR Q2.

Abstract. E-learning has become a critical factor in the academic environment due to the endless number of possibilities that it opens for the learning context. However, these platforms often suppose to increase the difficulties for the communication between teachers and students. Without having real contact between teachers and students, the former finds it harder to adapt their methods and content to their students, while the students also find complications for maintaining their focus. This paper aims to address this challenge with the use of emotion and engagement recognition techniques. We propose an emotion-aware e-learning platform architecture that recognizes students’ emotions and attention in order to improve their academic performance. The system integrates a semantic task automation system that allows users to easily create and configure their own automation rules to adapt the study environment. The main contributions of this paper are: (1) the design of an emotion-aware learning analytics architecture; (2) the integration of this architecture in a semantic task automation platform; and (3) the validation of the use of emotion recognition in the e-learning platform using partial least squares structural equation modeling (PLS-SEM) methodology.

The article is available at: