Publications

Displaying 101 - 125 of 1227

Publication	Date
Human Short Long-Term Cognitive Memory Mechanism for Visual Monitoring in IoT-Assisted Smart Cities Authors: Shuai Wang,Xinyu Liu,Shuai Liu,Khan Muhammad,Ali Asghar Heidari,Javier Del Ser,Victor Hugo C. de Albuquerque In the Industry 4.0 era, the visualization and real-time automatic monitoring of smart cities supported by the Internet of Things is becoming increasingly important. The use of filtering algorithms in smart city monitoring is a feasible method for this purpose. However, maintaining fast and… Institute of Electrical and Electronics Engineers (IEEE)	2022-05-15
Vessel-GAN: Angiographic reconstructions from myocardial CT perfusion with explainable generative adversarial networks Authors: Chulin Wu,Heye Zhang,Jiaqi Chen,Zhifan Gao,Pengfei Zhang,Khan Muhammad,Javier Del Ser Elsevier BV	2022-05-01
Technology-Agnostic Assessment of Wave Energy System Capabilities Authors: Pablo Ruiz-Minguela,Jesus M. Blanco,Vincenzo Nava,Henry Jeffrey Developing new wave energy technologies is risky, costly and time-consuming. The large diversity of concepts, components and evaluation criteria creates a vast design space of potentially feasible solutions. This paper aims to introduce a novel methodology for the holistic assessment of wave energy… MDPI AG	2022-04-03
Adaptive Multifactorial Evolutionary Optimization for Multitask Reinforcement Learning Authors: Aritz D. Martinez,Javier Del Ser,Eneko Osaba,Francisco Herrera Evolutionary computation has largely exhibited its potential to complement conventional learning algorithms in a variety of Machine Learning tasks, especially those related to unsupervised (clustering) and supervised learning. It has not been until lately when the computational efficiency of… Institute of Electrical and Electronics Engineers (IEEE)	2022-04-01
Predictive Maintenance of Floating Offshore Wind Turbine Mooring Lines using Deep Neural Networks Authors: Gorostidi, N.,Nava, V.,Aristondo, A.,Pardo, D. Abstract The recent massive deployment of onshore wind farms has caused controversy to arise mainly around the issues of land occupation, noise and visual pollution and impact on wildlife. Fixed offshore turbines, albeit beneficial in those aspects, become economically unfeasible… IOP Publishing	2022-04-01
On quadrature rules for solving Partial Differential Equations using Neural Networks Authors: Rivera, Jon A.,Taylor, Jamie M.,Omella, Ángel J.,Pardo, David Neural Networks have been widely used to solve Partial Differential Equations. These methods require to approximate definite integrals using quadrature rules. Here, we illustrate via 1D numerical examples the quadrature problems that may arise in these applications and propose different… Elsevier BV	2022-04-01
Supervised Deep Learning with Finite Element simulations for damage identification in bridges Authors: Ana Fernandez-Navamuel,Diego Zamora-Sánchez,Ángel J. Omella,David Pardo,David Garcia-Sanchez,Filipe Magalhães This work proposes a supervised Deep Learning approach for damage identification in bridge structures. We employ a hybrid methodology that incorporates Finite Element simulations to enrich the training phase of a Deep Neural Network with synthetic damage scenarios. The neural network is based on… Elsevier BV	2022-04-01
Analysis of Few-Shot Techniques for Fungal Plant Disease Classification and Evaluation of Clustering Capabilities Over Real Datasets Authors: Itziar Egusquiza,Itziar Egusquiza,Artzai Picon,Artzai Picon,Unai Irusta,Arantza Bereciartua-Perez,Till Eggers,Christian Klukas,Elisabete Aramendi,Ramon Navarra-Mestre Plant fungal diseases are one of the most important causes of crop yield losses. Therefore, plant disease identification algorithms have been seen as a useful tool to detect them at early stages to mitigate their effects. Although deep-learning based algorithms can achieve high detection accuracies… Frontiers Media SA	2022-03-07
NATURE- AND BIO-INSPIRED OPTIMIZATION: THE GOOD, THE BAD, THE UGLY AND THE HOPEFUL Authors: Daniel Molina Cabrera,JAVIER POYATOS AMADOR,ENEKO OSABA ICEDO,JAVIER DEL SER LORENTE,FRANCISCO HERRERA TRIGUERO Nowadays, optimization has become an important issue for industrial systems and product development. From an engineering perspective, optimization implies adjusting or fine tuning the design of the system considering performance factors. Unfortunately, in many real-world problems there are no… UK Zhende Publishing Limited Company	2022-03-01
Physiological effects of providing supplemental air for avalanche victims. A randomised trial Authors: Lars, Wik,Guttorm, Brattebø,Øyvind, Østerås,Jörg, Assmus,Unai, Irusta,Elisabete, Aramendi,Sigurd, Mydske,Tore, Skaalhegg,Sven Christjar, Skaiaa,Øyvind, Thomassen Survival from avalanche burial is dependent on time to extraction, breathing ability, air pocket oxygen content, and avoiding rebreathing of carbon dioxide (COA prospective randomized crossover experimental field study enrolled 20 healthy subjects in Hemsedal, Norway in March 2019. Subjects… Elsevier BV	2022-03-01
Randomization-based machine learning in renewable energy prediction problems: Critical literature review, new results and perspectives Authors: J. Del Ser,D. Casillas-Perez,L. Cornejo-Bueno,L. Prieto-Godino,J. Sanz-Justo,C. Casanova-Mateo,S. Salcedo-Sanz 88 pages, 14 figures, 12 tables. Under review Elsevier BV	2022-03-01
Constraints on the structure and seasonal variations of Triton’s atmosphere from the 5 October 2017 stellar occultation and previous observations Authors: J. Marques Oliveira,B. Sicardy,A. R. Gomes-Júnior,J. L. Ortiz,D. F. Strobel,T. Bertrand,F. Forget,E. Lellouch,J. Desmars,D. Bérard,A. Doressoundiram,J. Lecacheux,R. Leiva,E. Meza,F. Roques,D. Souami,T. Widemann,P. Santos-Sanz,N. Morales,R. Duffard,E.… Context. A stellar occultation by Neptune’s main satellite, Triton, was observed on 5 October 2017 from Europe, North Africa, and the USA. We derived 90 light curves from this event, 42 of which yielded a central flash detection. Aims. We aimed at constraining Triton’s atmospheric structure and the… EDP Sciences	2022-03-01
Error representation of the time-marching DPG scheme Authors: Muñoz-Matute, Judit,Demkowicz, Leszek,Pardo, David In this article, we introduce an error representation function to perform adaptivity in time of the recently developed time-marching Discontinuous Petrov–Galerkin (DPG) scheme. We first provide an analytical expression for the error that is the Riesz representation of the residual. Then, we… Elsevier BV	2022-03-01
Exploiting the Kronecker product structure of φ−functions in exponential integrators Authors: Muñoz‐Matute, Judit,Pardo, David,Calo, Victor M. AbstractExponential time integrators are well‐established discretization methods for time semilinear systems of ordinary differential equations. These methods use functions, which are matrix functions related to the exponential. This work introduces an algorithm to speed up the computation of the… Wiley	2022-03-01
A Finite Element based Deep Learning solver for parametric PDEs Authors: Uriarte, Carlos,Pardo, David,Omella, Ángel Javier We introduce a dynamic Deep Learning (DL) architecture based on the Finite Element Method (FEM) to solve linear parametric Partial Differential Equations(PDEs). The connections between neurons in the architecture mimic the Finite Element connectivity graph when applying mesh refinements. We select… Elsevier BV	2022-03-01
Information retrieval and question answering: A case study on COVID-19 scientific literature Authors: Arantxa Otegi,Iñaki San Vicente,Xabier Saralegi,Anselmo Peñas,Borja Lozano,Eneko Agirre Biosanitary experts around the world are directing their efforts towards the study of COVID-19. This effort generates a large volume of scientific publications at a speed that makes the effective acquisition of new knowledge difficult. Therefore, Information Systems are needed to assist biosanitary… Elsevier BV	2022-03-01
A novel approach for the detection of anomalous energy consumption patterns in industrial cyber‐physical systems Authors: Izaskun Mendia,Sergio Gil‐Lopez,Iñaki Grau,Javier Del Ser AbstractMost scenarios emerging from the Industry 4.0 paradigm rely on the concept of cyber‐physical production systems (CPPS), which allow them to synergistically connect physical to digital setups so as to integrate them over all stages of product development. Unfortunately, endowing CPPS with AI… Wiley	2022-02-25
A deep learning approach to design a borehole instrument for geosteering Authors: M. Shahriari,A. Hazra,D. Pardo Deep neural network (DNN)-based methods are suitable for the rapid inversion of borehole resistivity measurements. They approximate the forward and the inverse problem offline during the training phase, and they only require a fraction of a second for the online evaluation (aka prediction). Herein… Society of Exploration Geophysicists	2022-02-16
Energy-Aware Multi-Objective Job Shop Scheduling Optimization with Metaheuristics in Manufacturing Industries: A Critical Survey, Results, and Perspectives Authors: Jesus Para,Javier Del Ser,Antonio J. Nebro In recent years, the application of artificial intelligence has been revolutionizing the manufacturing industry, becoming one of the key pillars of what has been called Industry 4.0. In this context, we focus on the job shop scheduling problem (JSP), which aims at productions orders to be carried… MDPI AG	2022-01-29
Deep learning enhanced principal component analysis for structural health monitoring Authors: Fernandez-Navamuel, Ana,Magalhães, Filipe,Zamora-Sánchez, Diego,Omella, Ángel J,Garcia-Sanchez, David,Pardo, David This paper proposes a Deep Learning Enhanced Principal Component Analysis (PCA) approach for outlier detection to assess the structural condition of bridges. We employ partially explainable autoencoder architecture to replicate and enhance the data compression and reconstruction ability of PCA.… SAGE Publications	2022-01-18
From storms to cyclones at Jupiter’s poles Authors: Agustín Sánchez-Lavega Springer Science and Business Media LLC	2022-01-10
A Multidirectional Deep Neural Network for Self-Supervised Reconstruction of Seismic Data Authors: Mohammad Mahdi Abedi,David Pardo Seismic studies exhibit gaps in the recorded data due to surface obstacles. To fill in the gaps with self-supervised deep learning, the network learns to predict different events from the recorded parts of data and then applies it to reconstruct the missing parts of the same dataset. We propose two… Institute of Electrical and Electronics Engineers (IEEE)	2022-01-01
1D Painless Multi-level Automatic Goal-Oriented h and p Adaptive Strategies Using a Pseudo-Dual Operator Authors: Felipe Vinicio Caro,Vincent Darrigrand,Julen Alvarez-Aramberri,Elisabete Alberdi Celaya,David Pardo The main idea of our Goal-Oriented Adaptive (GOA) strategy is based on performing global and uniform h- or p-refinements (for h- and p-adaptivity, respectively) followed by a coarsening step, where some basis functions are removed according to their estimated importance. Many Goal-Oriented Adaptive… Springer International Publishing	2022-01-01
The association of race with CPR quality following out-of-hospital cardiac arrest Authors: Schmicker, Robert H.,Blewer, Audrey,Lupton, Joshua R.,Aufderheide, Tom P.,Wang, Henry E.,Idris, Ahamed H.,Aramendi, Elisabete,Hagahmed, Mohamed B,Traynor, Owen T.,Colella, M. Riccardo,Daya, Mohamud R. Previous studies have shown racial disparities in outcomes after out-of-hospital cardiac arrest. Although several treatment factors may account for these differences, there is limited information regarding differences in CPR quality and its effect on survival in underrepresented racial populations.… Elsevier BV	2022-01-01
R-Adaptive Deep Learning Method for Solving Partial Differential Equations Authors: Ángel J. Omella,David Pardo 19 pages Elsevier BV	2022-01-01