Browsing by Author "Fontenla-Romero, Óscar"
Now showing items 1-19 of 19
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A Machine Learning Solution for Distributed Environments and Edge Computing
Penas-Noce, Javier; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (MDPI AG, 2019-08-09)[Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ... -
A novel intelligent approach for man-in-the-middle attacks detection over internet of things environments based on message queuing telemetry transport
Michelena, Álvaro; Aveleira Mata, Jose Antonio; Jove, Esteban; Bayón Gutiérrez, Martín; Novais, Paulo; Fontenla-Romero, Óscar; Calvo-Rolle, José Luis; Alaiz Moretón, Héctor (Wiley, 2024)[Abstract]: One of the most common attacks is man-in-the-middle (MitM) which, due to its complex behaviour, is difficult to detect by traditional cyber-attack detection systems. MitM attacks on internet of things systems ... -
A One-Class Classification method based on Expanded Non-Convex Hulls
Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (Elsevier, 2023)[Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ... -
A Review and Future Trends of Precision Livestock Over Dairy and Beef Cow Cattle With Artificial Intelligence
Michelena, Álvaro; Fontenla-Romero, Óscar; Calvo-Rolle, José Luis (Oxford University Press, 2024)[Abstract] The demand for meat and dairy products is expected to rise significantly in the current demographic and economic growth context. Concurrently, various factors, including financial crises and reduced profitability, ... -
Adaptive Real-Time Method for Anomaly Detection Using Machine Learning
Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (MDPI AG, 2020-08-20)[Abstract] Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring ... -
Comparative Analysis of Unsupervised Anomaly Detection Techniques for Heat Detection in Dairy Cattle
Michelena, Álvaro; Díaz-Longueira, Antonio; Novais, Paulo; Simić, Dragan; Fontenla-Romero, Óscar; Calvo-Rolle, José Luis (Elsevier, 2025-02-14)[Abstract] Population growth has increased the demand for meat and dairy products, making livestock, especially cattle, key to meeting this demand. This has led to an increase in herd size, complicating efficient herd ... -
Development of a Virtual Sensor for COD Measurement in a Wastewater Treatment Plant
Díaz-Longueira, Antonio; Timiraos, Míriam; Michelena, Álvaro; Fontenla-Romero, Óscar; Calvo-Rolle, José Luis (Universidade da Coruña, Servizo de Publicacións, 2023)[Abstract] The objective of the work is to develop a system that allows predicting, from a global perspective, the behavior of the process in a wastewater treatment plant. To do this, the chemical oxygen demand, a variable ... -
DSVD-autoencoder: A scalable distributed privacy-preserving method for one-class classification
Fontenla-Romero, Óscar; Pérez-Sánchez, Beatriz; Guijarro-Berdiñas, Bertha (John Wiley and Sons Ltd, 2021-01)[Abstract]: One-class classification has gained interest as a solution to certain kinds of problems typical in a wide variety of real environments like anomaly or novelty detection. Autoencoder is the type of neural network ... -
Estudio, implementación y análisis de nuevos algoritmos de aprendizaje y nuevas medidas de tolerancia al ruido para redes funcionales y neuronales
Fontenla-Romero, Óscar (2002)[Resumen] Esta tesis doctoral está organizada en dos partes, En la primera parte de la memoria se presentan nuevos algoritmos para el aprendizaje de redes de neuronas artificiales con alimentación hacia delante. En ... -
Experiencias para la mejora del proceso de aprendizaje y la motivación de los estudiantes basadas en proyectos
Bellas, Francisco; Fontenla-Romero, Óscar; Becerra Permuy, José Antonio (2020)[Resumen] El presente artículo presenta una experiencia de aplicación de Aprendizaje Basado en Proyectos (ABP) a nivel de educación superior, con el objetivo de incrementar la motivación de los alumnos y mejorar su ... -
Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated?
Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (2024-07)In the current landscape, user opinions exert an unprecedented influence on the trajectory of companies. In the field of online review platforms, these opinions, transmitted through text reviews and numerical ratings, ... -
Fast deep autoencoder for federated learning
Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (Elsevier Ltd, 2023-11)[Abstract]: This paper presents a novel, fast and privacy preserving implementation of deep autoencoders. DAEF (Deep AutoEncoder for Federated learning), unlike traditional neural networks, trains a deep autoencoder network ... -
FedHEONN: Federated and homomorphically encrypted learning method for one-layer neural networks
Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha; Hernández-Pereira, Elena; Pérez-Sánchez, Beatriz (Elsevier B.V., 2023)[Abstract]: Federated learning (FL) is a distributed approach to developing collaborative learning models from decentralized data. This is relevant to many real applications, such as in the field of the Internet of Things, ... -
Introducción a la representación del conocimiento y el razonamiento en educación pre-universitaria mediante una actividad STEM
Guerreiro-Santalla, Sara; Fontenla-Romero, Óscar; Romero, Alejandro; Bellas, Francisco (Asociación de Enseñantes Universitarios de la Informática (AENUI), 2022)[Resumen]: Este trabajo presenta un recurso docente de acceso libre, orientado a estudiantes de últimos años de secundaria o bachillerato, centrado en el ámbito de la enseñanza de la Inteligencia Artificial (IA) preuniversitaria. ... -
Machine Learning Techniques to Predict Different Levels of Hospital Care of CoVid-19
Hernández-Pereira, Elena; Fontenla-Romero, Óscar; Bolón-Canedo, Verónica; Cancela, Brais; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (Springer, 2022)[Abstract] In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019) will need different levels of hospital ... -
Novel adaptive approach for anomaly detection in nonlinear and time-varying industrial systems
Michelena, Álvaro; Zayas-Gato, Francisco; Jove, Esteban; Casteleiro-Roca, José-Luis; Quintián, Héctor; Fontenla-Romero, Óscar; Calvo-Rolle, José Luis (Oxford University Press, 2024)[Abstract] The present research describes a novel adaptive anomaly detection method to optimize the performance of nonlinear and time-varying systems. The proposal integrates a centroid-based approach with the real-time ... -
SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets
Fernández Barrero, David; Fontenla-Romero, Óscar; Lamas-López, Francisco; Novoa-Paradela, David; R-Moreno, María; Sanz, David (MDPI, 2021)[Abstract] Predictive maintenance has lately proved to be a useful tool for optimizing costs, performance and systems availability. Furthermore, the greater and more complex the system, the higher the benefit but also the ... -
Testing Scenarios to Achieve Workplace Sustainability Goals : Using Backcasting and Agent-Based Modeling
García-Mira, Ricardo; Dumitru, Adina; Alonso-Betanzos, Amparo; Sánchez-Maroño, Noelia; Fontenla-Romero, Óscar; Craig, Tony; Polhill, J. Gary (The Environmental Design Research Association, 2016-10-26)[Abstract] Pro-environmental behaviors have been analyzed in the home, with little attention to other important contexts of everyday life, such as the workplace. The research reported here explored three categories of ... -
The School Path Guide: A Practical Introduction to Representation and Reasoning in AI for High School Students
Guerreiro-Santalla, Sara; Bellas, Francisco; Fontenla-Romero, Óscar (Springer, 2021-06-12)[Abstract]: This paper presents a structured activity to introduce high school students in the topics of representation and reasoning in Artificial Intelligence, which are completely new for them at this educational ...