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Publications

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Scale Mutualized Perception for Vessel Border Detection in Intravascular Ultrasound Images
Authors: Xiujian Liu,Tianyuan Feng,Weipeng Liu,Liang Song,Yixuan Yuan,William Kongto Hau,Javier Del Ser,Zhifan Gao
Vessel border detection in IVUS images is essential for coronary disease diagnosis. It helps to obtain the clinical indices on the inner vessel morphology to indicate the stenosis. However, the existing methods suffer the challenge of scale-dependent interference. Early methods usually rely on the… Institute of Electrical and Electronics Engineers (IEEE)

Adaptive Deep Fourier Residual method via overlapping domain decomposition
Authors: Jamie M. Taylor,Manuela Bastidas,Victor M. Calo,David Pardo
The Deep Fourier Residual (DFR) method is a specific type of variational physics-informed neural networks (VPINNs). It provides a robust neural network-based solution to partial differential equations (PDEs). The DFR strategy is based on approximating the dual norm of the weak residual of a PDE.… Elsevier BV

Toward Fully Automated Inspection of Critical Assets Supported by Autonomous Mobile Robots, Vision Sensors, and Artificial Intelligence
Authors: Javier Sanchez-Cubillo,Javier Del Ser,José Luis Martin
Robotic inspection is advancing in performance capabilities and is now being considered for industrial applications beyond laboratory experiments. As industries increasingly rely on complex machinery, pipelines, and structures, the need for precise and reliable inspection methods becomes paramount… MDPI AG

Steady solutions for the Schrödinger map equation
Authors: Claudia García,Luis Vega
In this paper we use bifurcation methods to construct a new family of solutions of the binormal flow, also known as the vortex filament equation, which do not change their form. Our examples are complementary to those obtained by S. Kida in 1981, and therefore they are also related, thanks to the… Informa UK Limited

Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation
Authors: Yang Nan,Javier Del Ser,Zeyu Tang,Peng Tang,Xiaodan Xing,Yingying Fang,Francisco Herrera,Witold Pedrycz,Simon Walsh,Guang Yang
12 pages, 5 figures, Submitted to IEEE TNNLS
Institute of Electrical and Electronics Engineers (IEEE)

Monitoring Mooring Lines of Floating Offshore Wind Turbines: Autoregressive Coefficients and Stacked Auto-Associative-Deep Neural Networks
Authors: Sharma S.,Nava Vincenzo
This study introduces a pioneering monitoring system designed to mitigate operational costs and enhance the sustainability of Floating Offshore Wind Turbines (FOWT). The proposed framework combines Autoregressive models with a Stacked Auto-Associativebased Deep Neural Network (AANN-DNN) to detect… British Institute of Non-Destructive Testing (BINDT)

Condition monitoring of mooring systems for Floating Offshore Wind Turbines using Convolutional Neural Network framework coupled with Autoregressive coefficients
Authors: Smriti Sharma,Vincenzo Nava
This research presents a novel approach proposed for the monitoring of mooring systems in Floating Offshore Wind Turbines (FOWTs), employing a combination of Convolutional Neural Networks (CNNs) and Auto-Regressive (AR) models. CNN finds broad application in monitoring intricate structures, as they… Elsevier BV

Control co-design for wave energy farms: Optimisation of array layout and mooring configuration in a realistic wave climate
Authors: Yerai Peña-Sanchez,Demián García-Violini,Markel Penalba,Ander Zarketa-Astigarraga,Francesco Ferri,Vincenzo Nava,John V. Ringwood
This paper presents a novel Control Co-Design (CCD) methodology aimed at economically optimising the layout of wave energy converter (WEC) arrays. CCD ensures the synergy of optimised WEC and array parameters with the final control strategy, resulting in a comprehensive and efficient design of the… Elsevier BV

Imaginary past of a quantum particle moving on imaginary time
Authors: A. Uranga,E. Akhmatskaya,D. Sokolovski
The analytical continuation of classical equations of motion to complex times suggests that a tunneling particle spends in the barrier an imaginary duration i|T|. Does this… American Physical Society (APS)

Reducing Spatial Discretization Error on Coarse CFD Simulations Using an OpenFOAM-Embedded Deep Learning Framework
Authors: Gonzalez-Sieiro J.,Pardo D.,Nava V.,Calo V. M.,Towara M.
Abstract

We propose a method for reducing the spatial discretization error of coarse computational fluid dynamics (CFD) problems by enhancing the quality of low-resolution simulations using a deep learning model fed with high-quality data. We substitute the default differencing scheme… Springer Science and Business Media LLC

Robust Variational Physics-Informed Neural Networks
Authors: Sergio Rojas,Paweł Maczuga,Judit Muñoz-Matute,David Pardo,Maciej Paszyński
We introduce a Robust version of the Variational Physics-Informed Neural Networks method (RVPINNs). As in VPINNs, we define the quadratic loss functional in terms of a Petrov-Galerkin-type variational formulation of the PDE problem: the trial space is a (Deep) Neural Network (DNN) manifold, while… Elsevier BV

Non-imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Survey
Authors: Xiaodan Xing,Huanjun Wu,Lichao Wang,Iain Stenson,May Yong,Javier Del Ser,Simon Walsh,Guang Yang
Data quality is a key factor in the development of trustworthy AI in healthcare. A large volume of curated datasets with controlled confounding factors can improve the accuracy, robustness, and privacy of downstream AI algorithms. However, access to high-quality datasets is limited by the technical… Association for Computing Machinery (ACM)

A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends
Authors: M. Victoria Luzón,Nuria Rodríguez-Barroso,Alberto Argente-Garrido,Daniel Jiménez-López,Jose M. Moyano,Javier Del Ser,Weiping Ding,Francisco Herrera
Institute of Electrical and Electronics Engineers (IEEE)

Fast $K$-Medoids With the $l_{1}$-Norm
Authors: Marco Capó,Aritz Pérez,Jose A. Lozano
K-medoids clustering is one of the most popular techniques in exploratory data analysis. The most commonly used algorithms to deal with this problem are quadratic on the number of instances, n, and usually the quality of the obtained solutions strongly depends upon their initialization phase. In… Institute of Electrical and Electronics Engineers (IEEE)

Machine learning model to predict evolution of pulseless electrical activity during in-hospital cardiac arrest
Authors: Jon Urteaga,Andoni Elola,Anders Norvik,Eirik Unneland,Trygve C. Eftestøl,Abhishek Bhardwaj,David Buckler,Benjamin S. Abella,Eirik Skogvoll,Elisabete Aramendi
During pulseless electrical activity (PEA) the cardiac mechanical and electrical functions are dissociated, a phenomenon occurring in 25-42% of in-hospital cardiac arrest (IHCA) cases. Accurate evaluation of the likelihood of a PEA patient transitioning to return of spontaneous circulation (ROSC)… Elsevier BV

Dynamical Phenomena in the Martian Atmosphere Through Mars Express Imaging
Authors: Sánchez-Lavega, A.,del Río-Gaztelurrutia, T.,Spiga, A.,Hernández-Bernal, J.,Larsen, E.,Tirsch, Daniela,Cardesin-Moinelo, A.,Machado, P.
AbstractThis review describes the dynamic phenomena in the atmosphere of Mars that are visible in images taken in the visual range through cloud formation and dust lifting. We describe the properties of atmospheric features traced by aerosols covering a large range of spatial and temporal scales,… Springer Science and Business Media LLC

Intelligent Underwater Object Detection and Image Restoration for Autonomous Underwater Vehicles
Authors: Sheezan Fayaz,Shabir A. Parah,G. J. Qureshi,Jaime Lloret,Javier Del Ser,Khan Muhammad
This work was supported in part by the Department of Electronics and Instrumentation Technology, funded by the Indian Government through Science and Heritage Research Initiative (SHRI) scheme under Grant DST/TDT/SHRI-33/2018. The work of J. Del Ser was supported by the Basque Government through… Institute of Electrical and Electronics Engineers (IEEE)

Grounding spatial relations in text-only language models
Authors: Gorka Azkune,Ander Salaberria,Eneko Agirre
This paper shows that text-only Language Models (LM) can learn to ground spatial relations like "left of" or "below" if they are provided with explicit location information of objects and they are properly trained to leverage those locations. We perform experiments on a verbalized version of the… Elsevier BV

Cardiac output estimation using ballistocardiography: a feasibility study in healthy subjects
Authors: Svensøy, Johannes Nordsteien,Alonso, Erik,Elola Artano, Andoni,Bjørnerheim, Reidar,Ræder, Johan,Aramendi Ecenarro, Elisabete,Wik, Lars
AbstractThere is no reliable automated non-invasive solution for monitoring circulation and guiding treatment in prehospital emergency medicine. Cardiac output (CO) monitoring might provide a solution, but CO monitors are not feasible/practical in the prehospital setting. Non-invasive… Springer Science and Business Media LLC

A data-mining approach to understanding the impact of multi-doping on the ionic transport mechanism of solid electrolytes materials: the case of dual-doped Ga0.15/Scy Li7La3Zr2O12
Authors: Henry A. Cortés,Mauricio R. Bonilla,Herbert Früchtl,Tanja van Mourik,Javier Carrasco,Elena Akhmatskaya
Uncovering Ga/Sc dual-doping effects on Li-ion dynamics in LLZO through molecular dynamics, Monte Carlo simulations, and data mining clustering techniques.
Royal Society of Chemistry (RSC)

On generating trustworthy counterfactual explanations
Authors: Del Ser, Javier,Barredo-Arrieta, Alejandro,Díaz-Rodríguez, Natalia,Herrera, Francisco,Saranti, Anna,Holzinger, Andreas
Centro para el Desarrollo Tecnologico Industrial (CDTI)
Elsevier BV

Big Data Analysis for Industrial Activity Recognition Using Attention-Inspired Sequential Temporal Convolution Network
Authors: Altaf Hussain,Tanveer Hussain,Waseem Ullah,Samee Ullah Khan,Min Je Kim,Khan Muhammad,Javier Del Ser,Sung Wook Baik
Institute of Electrical and Electronics Engineers (IEEE)

A probabilistic generative model to discover the treatments of coexisting diseases with missing data
Authors: Onintze Zaballa,Aritz Pérez,Elisa Gómez-Inhiesto,Teresa Acaiturri-Ayesta,Jose A. Lozano
Comorbidities, defined as the presence of co-existing diseases, progress through complex temporal patterns among patients. Learning such dynamics from electronic health records is crucial for understanding the coevolution of diseases. In general, medical records are represented through temporal… Elsevier BV

A Least-Squares-Based Neural Network (Ls-Net) for Solving Linear Parametric Pdes
Authors: Shima Baharlouei,Jamie M. Taylor,Carlos Uriarte,David Pardo
Developing efficient methods for solving parametric partial differential equations is crucial for addressing inverse problems. This work introduces a Least-Squares-based Neural Network (LS-Net) method for solving linear parametric PDEs. It utilizes a separated representation form for the parametric… Elsevier BV

Reconstruction-Based Anomaly Detection in Wind Turbine Operation Time Series Using Generative Models
Authors: Amaia Abanda,Ainhoa Pujana,Javier Del Ser
Springer Nature Switzerland