Listar LCC - Artículos por título
Mostrando ítems 59-78 de 217
-
Comparative Genomics, Evolution, and Drought-Induced Expression of Dehydrin Genes in Model Brachypodium Grasses.
Decena Rodríguez, María Ángeles; Gálvez-Rojas, Sergio
; Agostini, Federico; Sancho, Rubén; Contreras-Moreira, Bruno; Des Marais, David; Hernández Molina, Pilar; Catalán Rodríguez, Pilar[et al.] (MDPI, 2021-12-03)
Dehydration proteins (dehydrins, DHNs) confer tolerance to water-stress deficit in plants. We performed a comparative genomics and evolutionary study of DHN genes in four model Brachypodium grass species. Due to limited ... -
Content-based image retrieval by ensembles of deep learning object classifiers.
Hamreras, Safa; Boucheham, Bachir; Molina-Cabello, Miguel Ángel; Benítez-Rochel, Rafaela; López-Rubio, Ezequiel (2020-05-20)
Ensemble learning has demonstrated its efficiency in many computer vision tasks. In this paper, we address this paradigm within content based image retrieval (CBIR). We propose to build an ensemble of convolutional neural ... -
Context-aware energy-efficient applications for cyber-physical systems
Horcas-Aguilera, José Miguel; Pinto-Alarcón, Mónica; Fuentes-Fernández, Lidia (Elsevier, 2019-01)
El artículo ilustra cómo abordar el problema de desarrollar aplicaciones energéticamente eficientes que tengan en cuenta el contexto. Se define un asistente ecológico que utiliza métodos avanzados de ingeniería de software, ... -
Context-dependent reconfiguration of autonomous vehicles in mixed traffic
Horcas-Aguilera, José Miguel; Monteil, Julien; Bouroche, Mélanie; Pinto-Alarcón, Mónica; Fuentes-Fernández, Lidia; Clarke, Siobhán[et al.] (Wiley, 2018-04)
Human drivers naturally adapt their behaviour depending on the traffic conditions, such as the current weather and road type. Autonomous vehicles need to do the same, in a way that is both safe and efficient in traffic ... -
Cost-Effective Markers and Candidate Genes Analysis at Wheat MQTL Loci.
Mérida García, Rosa; Gálvez-Rojas, Sergio; Paux, Etienne; Dorado-Pérez, Gabriel; Pascual, Laura; Giraldo, Patricia; Hernández Molina, Pilar[et al.] (MDPI, 2020-11-30)
High-resolution melting analysis (HRM) is a resolutive technique, using PCR amplification and in-tube detection, which is based on the PCR product’s melting analysis. It is a promising technique for breeding analysis, as ... -
Data driven tools to assess the location of photovoltaic facilities in urban areas
Rodríguez-Gómez, Francisco; Del-Campo-Ávila, José; Ferrer Cuesta, Marta; Mora-López, Llanos (Elsevier, 2022-10-01)
Urban sustainability is a significant factor in combating climate change. Replacing polluting by renewable energies is fundamental to reduce the emission of greenhouse gases. Photovoltaic (PV) facilities harnessing solar ... -
Data mining process to detect suicidal behaviour in out-of-hospital emergency departments
Del-Campo-Ávila, José; Ramos Martín, Javier; Gómez-Sánchez-Lafuente, Carlos; García-Pedrosa, Johanna; García-Martín, Saúl; Martínez-García, Ana I.; Guzmán-Parra, José; Morales-Bueno, Rafael; Moreno-Kustner, Berta[et al.] (Elsevier, 2024-07-13)
Out-of-hospital emergency departments receive multiple types of requests daily. Their management requires a balance to be found between available resources and the actual needs of the requesting party. Those regarding ... -
Deep Learning-Based Attack Detection and Classification in Android Devices.
Gómez Alfonso, Bernardo; Muñoz-Gallego, Antonio Jesús (MDPI, 2023-07-28)
The increasing proliferation of Androidbased devices, which currently dominate the market with a staggering 72% global market share, has made them a prime target for attackers. Consequently, the detection of Android ... -
Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting
Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel; Domínguez, Enrique; Luque-Baena, Rafael Marcos; Roé-Vellvé, Núria (Elsevier, 2020-07-20)
The image acquisition process in the field of magnetic resonance imaging (MRI) does not always provide high resolution results that may be useful for a clinical analysis. Super-resolution (SR) techniques manage to increase ... -
Deep learning-based video surveillance system managed by low cost hardware and panoramic cameras
Benito-Picazo, Jesús; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José; López-Rubio, Ezequiel (IOS Press, 2020)
The design of automated video surveillance systems often involves the detection of agents which exhibit anomalous or dangerous behavior in the scene under analysis. Models aimed to enhance the video pattern recognition ... -
Designing problem-specific operators for solving the Cell Switch-Off problem in ultra-dense 5G networks with hybrid MOEAs
Galeano-Brajones, Jesús; Luna-Valero, Francisco; Carmona Murillo, Javier; Zapata Cano, Pablo Helio; Valenzuela-Valdés, Juan Francisco (Elsevier, 2023)
The massive deployment of base stations is one of the key pillars of the fifth generation (5G) of mobile communications. However, this network densification entails high energy consumption that must be addressed to enhance ... -
Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size
García Aguilar, Iván; García-González, Jorge; Medina, Daniel; Luque-Baena, Rafael Marcos; Domínguez-Merino, Enrique; López-Rubio, Ezequiel[et al.] (Elsevier, 2023-11-17)
Autonomous driving requires information such as the velocity of other vehicles to prevent potential hazards. This work proposes a real-time deep learning-based framework to estimate vehicle speeds from image captures through ... -
Detection of Node Capture Attack in Wireless Sensor Networks
Agrawal, Sarita; Lal Das, Manik; López-Muñoz, Francisco Javier (IEEE Xplore, 2019-03)
Wireless sensor networks (WSNs) deployed in hostile environments for applications such as battle-field surveillance are vulnerable to various attacks, including node capture attack wherein an adversary physically captures, ... -
Determining drivers of private equity return with computational approaches
(Springer, 2024)Private equity (PE) represents the acquisition of stakes in non-listed companies, often long-term, with the objective of improving the performance and value of the company to obtain significant benefits at time of ... -
Development and Implementation of a Hybrid Wireless Sensor Network of Low Power and Long Range for Urban Environments
Bravo-Arrabal, Juan; Fernández-Lozano, Juan Jesús; Serón-Barba, Javier; Gómez-Ruiz, José Antonio; García-Cerezo, Alfonso José (MDPI, 2021)
The urban population, worldwide, is growing exponentially and with it the demand for information on pollution levels, vehicle traffic, or available parking, giving rise to citizens connected to their environment. This ... -
Dynamic and adaptive fault-tolerant asynchronous federated learning using volunteer edge devices
Morell Martínez, José Ángel; Alba-Torres, Enrique (Elsevier, 2022)
The number of devices, from smartphones to IoT hardware, interconnected via the Internet is growing all the time. These devices produce a large amount of data that cannot be analyzed in any data center or stored in the ... -
Dynamic learning rates for continual unsupervised learning.
Fernández-Rodríguez, Jose David; Palomo-Ferrer, Esteban José; Ortiz-de-Lazcano-Lobato, Juan Miguel; Ramos-Jiménez, Gonzalo Pascual; López-Rubio, Ezequiel (IOS Press, 2023)
The dilemma between stability and plasticity is crucial in machine learning, especially when non-stationary input distributions are considered. This issue can be addressed by continual learning in order to alleviate ... -
Dynamic Reconfiguration of Security Policies in Wireless Sensor Networks
Pinto-Alarcón, Mónica; Gámez, Nadia; Fuentes-Fernández, Lidia; Amor-Pinilla, María Mercedes; Horcas-Aguilera, José Miguel; Ayala-Viñas, Inmaculada[et al.] (2015-03)
Providing security and privacy to wireless sensor nodes (WSNs) is very challenging, due to the heterogeneity of sensor nodes and their limited capabilities in terms of energy, processing power and memory. The applications ... -
EARMO: An Energy-Aware Refactoring Approach for Mobile Apps
(IEEE, 2017)The energy consumption of mobile apps is a trending topic and researchers are actively investigating the role of coding practices on energy consumption. Recent studies suggest that design choices can conflict with energy ... -
Edge-Assisted Vehicular Networks Security.
Onieva-González, José Antonio; Ríos-del-Pozo, Rubén; Román-Castro, Rodrigo; López-Muñoz, Francisco Javier (2019)
Edge Computing paradigms are expected to solve some major problems affecting current application scenarios that rely on Cloud computing resources to operate. These novel paradigms will bring computational resources ...