LCC - Contribuciones a congresos científicos
Envíos recientes
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Analysis and optimisation of SPL products using goal models.
The Internet of Things is one of the core drivers of variability modelling and requires explicit mechanisms to manage it. A key technology for addressing this variability is product line engineering. This approach uses a ... -
Human Activity Recognition From Sensorised Patient´s Data in Healthcare: A Streaming Deep Learning-Based Approach.
Hurtado-Requena, Sandro José
; García-Nieto, José Manuel; Popov, Anton; Navas-Delgado, Ismael (SISTEDES, 2023)
Physical inactivity is one of the main risk factors for mortality, and its relationship with the main chronic diseases has experienced intensive medical research. A well-known method for assessing people’s activity is ... -
Towards Self-Adaptive Software for Wildfire Monitoring with Unmanned Air Vehicles.
Wildfires have evolved significantly over the last decades, burning increasingly large forest areas every year. Smart cyber-physical systems like small Unmanned Air Vehicles (UAVs) can help to monitor, predict, and mitigate ... -
A Unified Metamodel for NoSQL and Relational Databases.
(2023)The Database field is undergoing significant changes. Although relational systems are still predominant, the interest in NoSQL systems is continuously increasing. In this scenario, polyglot persistence is envisioned as the ... -
A generic LSTM neural network architecture to infer heterogeneous model transformations.
Models capture relevant properties of systems. During the models’ life-cycle, they are subjected to manipulations with different goals such as managing software evolution, performing analysis, increasing developers’ ... -
Un analizador de modelos de variabilidad basado en el árbol de características.
Horcas-Aguilera, José Miguel; Pinto-Alarcón, Mónica; Fuentes-Fernández, Lidia (Sistedes, 2023-09-12)
Un árbol de características generalizado (GFT) es un modelo de variabilidad en el que las restricciones textuales han sido eliminadas manteniendo la semántica del modelo. La ventaja de un GFT es que se puede analizar ... -
Impacto de la heterogeneidad espacial del tráfico de red en el problema del apagado de celdas en redes ultra-densas.
Galeno-Brajones, Jesús; Luna-Valero, Francisco; Carmona Murillo, Javier; Valenzuela-Valdés, Juan Francisco; Zapata Cano, Pablo Helio (2023)
The ultra-dense deployment of small base stations is one of the enabling technologies for the next generation of mobile networks (5G and 6G), which leads to an increase in the energy consumption of the infrastructure. This ... -
Parallel proccessing applied to object detection with a Jetson TX2 embedded system.
Benito-Picazo, Jesús; Fernández Rodríguez, Jose David; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José; López-Rubio, Ezequiel (2023)
Video streams from panoramic cameras represent a powerful tool for automated surveillance systems, but naïve implementations typically require very intensive computational loads for applying deep learning models for automated ... -
Elimination of constraints for parallel analysis of feature models.
Horcas-Aguilera, José Miguel; Ballesteros-Gómez, Joaquín; Pinto-Alarcón, Mónica; Fuentes-Fernández, Lidia (2023)
Cross-tree constraints give feature models maximal expressive power since any interdependency between features can be captured through arbitrary propositional logic formulas. However, the existence of these constraints ... -
Clinical text classification in Cancer Real-World Data in Spanish
Moreno-Barea, Francisco J.; Mesa, Héctor; Ribelles-Entrena, Nuria; Alba-Conejo, Emilio; Jerez-Aragonés, José Manuel (2023-06-29)
Healthcare systems currently store a large amount of clinical data, mostly unstructured textual information, such as electronic health records (EHRs). Manually extracting valuable information from these documents is costly ... -
Named Entity Recognition for De-identifying Real-World Health Records in Spanish.
López-García, Guillermo; Moreno-Barea, Francisco J.; Mesa, Héctor; Jerez-Aragonés, José Manuel; Ribelles-Entrena, Nuria; Alba-Conejo, Emilio; Veredas-Navarro, Francisco Javier[et al.] (Springer Nature, 2023)
A growing and renewed interest has emerged in Electronic Health Records (EHRs) as a source of information for decision-making in clinical practice. In this context, the automatic de-identification of EHRs constitutes an ... -
Deep learning for coronary artery disease severity classification
Jiménez-Partinen, Ariadna; Thurnhofer-Hemsi, Karl; Palomo-Ferrer, Esteban José; Molina-Ramos, Ana I. (2023)
Medical imaging evaluations are one of the fields where computed-aid diagnosis could improve the efficiency of diagnosis supporting physician decisions. Cardiovascular Artery Disease (CAD) is diagnosed using the gold ... -
GreenSenti-IA: A Workflow Approach for Biodiversity Analysis in Urban Green Area Monitoring.
Benítez-Hidalgo, Antonio; García-Nieto, José Manuel; Aldana Martín, José Francisco; Cardas Ezeiza, Cristian; Aldana-Montes, José Francisco; Navas-Delgado, Ismael[et al.] (2023)
Nowadays, efficient urban planning cannot be conceived without carefully considering its ecological footprint. In particular, the smart design and monitoring of urban green areas is an important challenge in modern cities ... -
Photovoltaic energy prediction using machine learning techniques.
Solar energy is becoming one of the most promising power sources in residential, commercial, and industrial applications. Solar photovoltaic (PV) facilities use PV cells that convert solar irradiation into electric power. ... -
A FaaS approach for long-term monitoring in rehabilitation
The function as a service (FaaS) model, in which the costs are linked to the function time of use, is especially suitable in IoT or similar systems, where the information is collected periodically to consume less energy. ... -
Pneumonia Detection in Chest X-ray Images using Convolutional Neural Networks
Pneumonia is an infectious and deadly disease which strikes over millions of people. Usually, chest X-rays are used by radiotherapist to diagnose pneumonia. In this paper, a Computer- Aided Diagnosis (CAD) system for ... -
Stenosis detection in coronary angiography images using deep learning models
Luque-Baena, Rafael Marcos; Romero Granados, Irene; Jiménez-Partinen, Ariadna; Palomo-Ferrer, Esteban José (2022)
The emergence of deep learning has caused its massive application to different fields in industry and research, among which is the clinical field, especially in those where the data is structured in the form of images ... -
Combining OCL and Natural Language: a Call for a Community Effort
Cabot, Jordi; Delgado, David; Burgueño-Caballero, Lola (ACM, 2022-10)
The growing popularity and availability of pretrained natural language models opens the door to many interesting applications combining natural language (NL) with software artefacts. A couple of examples are the generation ... -
Dataciones absolutas de yacimientos protohistóricos de la bahía de Málaga en el contexto de la primera presencia fenicia en el sur de la Península Ibérica
Caro-Herrero, José Luis; Suárez-Padilla, Jose (XCIEFP 2022. X Congreso Internacional de Estudios Fenicios y Púnicos, 2022)
En el presente artículo pretendemos aportar un nuevo conjunto de dataciones para la primera presencia fenicia en la bahía de Málaga. Así, se aportarán dataciones complementarias a las existentes en yacimientos fenicios y ... -
Moving object detection in noisy video sequences using deep convolutional disentangled representations.
García-González, Jorge; Luque-Baena, Rafael Marcos; Ortiz-de-Lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel (2022)
Noise robustness is crucial when approaching a moving de- tection problem since image noise is easily mistaken for movement. In order to deal with the noise, deep denoising autoencoders are commonly proposed to be applied ...