Publications

Detection of shockable rhythms using convolutional neural networks during chest compressions provided by a load distributing band
Authors: Iraia Isasi,Jan-Åge Olsen,Lars Wik,Elisabete Aramendi,Unai Irusta
Load Distributing Band (LDB) mechanical chest compression devices are used to treat out-of-hospital cardiac arrest (OHCA) patients. The artefacts that LDB chest compressions induce in the ECG impede a reliable shock/no-shock diagnosis, resulting in compression interruptions to analyze the ECG. The… Computing in Cardiology

Identifying common treatments from Electronic Health Records with missing information. An application to breast cancer
Authors: Onintze Zaballa,Aritz Pérez,Teresa Acaiturri Ayesta,Jose A. Lozano,Jose A. Lozano,Elisa Gómez Inhiesto
The aim of this paper is to analyze the sequence of actions in the health system associated with a particular disease. In order to do that, using Electronic Health Records, we define a general methodology that allows us to: (i) identify the actions in the health system associated with a disease; (… Public Library of Science (PLoS)

A critical literature survey and prospects on tampering and anomaly detection in image data
Authors: Kelton A.P. da Costa,João P. Papa,Leandro A. Passos,Danilo Colombo,Javier Del Ser,Khan Muhammad,Victor Hugo C. de Albuquerque
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Petrobras Eusko Jaurlaritza Eusko Jaurlaritza: IT1294-19 Concernings related to image security have increased in the last years. One of the main reasons relies on the replacement of conventional photography to digital images, once… Elsevier BV

FRIPON: a worldwide network to track incoming meteoroids
Authors: Zouhair Benkhaldoun,Hadrien A. R. Devillepoix,A. Pagola,Ruggero Stanga,M. Jobin,S. Cointin,B. Grouiez,P. Volpini,B. Caillier,A. Calegaro,A. Calegaro,M. D’Elia,E. Mandon,L. Luciani,E. Huet,C. Nablanc,M. K. Kwon,P. Rougier,P. Le Dû,J. Galard,Enrico Cascone…
Context.Until recently, camera networks designed for monitoring fireballs worldwide were not fully automated, implying that in case of a meteorite fall, the recovery campaign was rarely immediate. This was an important limiting factor as the most fragile – hence precious – meteorites must be… EDP Sciences

Mutual information based feature subset selection in multivariate time series classification
Authors: Josu Ircio,Aizea Lojo,Usue Mori,Jose A. Lozano,Jose A. Lozano
Grant agreement no. KK-2019/00095 IT1244-19 TIN2016-78365-R PID2019-104966GB-I00
Elsevier BV

Cross-environment activity recognition using word embeddings for sensor and activity representation
Authors: Aitor Almeida,Gorka Azkune,Eneko Agirre
Abstract Cross-environment activity recognition in smart homes is a very challenging problem, specially for data-driven approaches. Currently, systems developed to work for a certain environment degrade substantially when applied to a new environment, where not only sensors, but also the… Elsevier BV

A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities
Authors: Salvador García,Javier Del Ser,Lior Rokach,Francisco Herrera,Sergio González
Abstract Ensembles, especially ensembles of decision trees, are one of the most popular and successful techniques in machine learning. Recently, the number of ensemble-based proposals has grown steadily. Therefore, it is necessary to identify which are the appropriate algorithms for a certain… Elsevier BV

Vision-based personalized Wireless Capsule Endoscopy for smart healthcare: Taxonomy, literature review, opportunities and challenges
Authors: Neeraj Kumar,Javier Del Ser,Khan Muhammad,Seyedali Mirjalili,Salman Khan
Abstract Wireless Capsule Endoscopy (WCE) is a patient-friendly approach for digestive tract monitoring to support medical experts towards identifying any anomaly inside human’s Gastrointestinal (GI) tract. The automatic recognition of such type of abnormalities is essential for early diagnosis… Elsevier BV

PADL: A Modeling and Deployment Language for Advanced Analytical Services
Authors: Josu Díaz-de-Arcaya,Raúl Miñón,Ana I. Torre-Bastida,Javier Del Ser,Aitor Almeida
In the smart city context, Big Data analytics plays an important role in processing the data collected through IoT devices. The analysis of the information gathered by sensors favors the generation of specific services and systems that not only improve the quality of life of the citizens, but also… MDPI AG

Convective storms and atmospheric vertical structure in Uranus and Neptune
Authors: R. Hueso,T. Guillot,A. Sánchez-Lavega
The ice giants Uranus and Neptune have hydrogen-based atmospheres with several constituents that condense in their cold upper atmospheres. A small number of bright cloud systems observed in both planets are good candidates for moist convective storms, but their observed properties (… The Royal Society

Restoration of the electrocardiogram during mechanical cardiopulmonary resuscitation
Authors: Isasi Liñero, Iraia,Irusta Zarandona, Unai,Aramendi Ecenarro, Elisabete,Idris, Ahamed,Sornmo, Leif
An artefact-free electrocardiogram (ECG) is essential during cardiac arrest to decide therapy such as defibrillation. Mechanical cardiopulmonary resuscitation (CPR) devices cause movement artefacts that alter the ECG. This study analyzes the effectiveness of mechanical CPR artefact suppression… IOP Publishing

A robust cyberattack detection approach using optimal features of SCADA power systems in smart grids
Authors: Md. Rafiul Hassan,Javier Del Ser,Abdu Gumaei,Abdu Gumaei,David Camacho,Mohammad Mehedi Hassan,Shamsul Huda,Giancarlo Fortino
Abstract Smart grids are a type of complex cyber–physical system (CPS) that integrates the communication capabilities of smart devices into the grid to facilitate remote operation and control of power systems. However, this integration exposes many existing vulnerabilities of conventional… Elsevier BV

DESIGN TOOLS FOR OFFSHORE RENEWABLE ENERGY
Authors: VILLATE MARTINEZ, JOSE LUIS,RUIZ MINGUELA, PABLO,PEREZ MORAN, GERMAN,NAVA, VINCENZO,ROBLES, EIDER
The crisis caused by the COVID-19 has awakened the fear of forgetting the fight against Climate Change coming up with a number of initiatives demanding to accelerate the European Green Deal, as the best way out of the crisis. Offshore renewable energy sources, including offshore wind, wave power… UK Zhende Publishing Limited Company

In-depth analysis of SVM kernel learning and its components
Authors: Jose A. Lozano,Jose A. Lozano,Alexander Mendiburu,Ibai Roman,Roberto Santana
The performance of support vector machines in non-linearly-separable classification problems strongly relies on the kernel function. Towards an automatic machine learning approach for this technique, many research outputs have been produced dealing with the challenge of automatic learn- ing of good… Springer Science and Business Media LLC

Review of Systems Engineering (SE) Methods and Their Application to Wave Energy Technology Development
Authors: Pablo Ruiz-Minguela,Vincenzo Nava,Jonathan Hodges,Jesús M. Blanco
The design of effective and economically viable wave energy devices involves complex decision-making about the product based on conceptual design information, including stakeholder requirements, functions, components and technical parameters. The great diversity of concepts makes it extremely… MDPI AG

Do all roads lead to Rome? Understanding the role of initialization in iterative back-translation
Authors: Mikel Artetxe,Gorka Labaka,Noe Casas,Eneko Agirre
Back-translation provides a simple yet effective approach to exploit monolingual corpora in Neural Machine Translation (NMT). Its iterative variant, where two opposite NMT models are jointly trained by alternately using a synthetic parallel corpus generated by the reverse model, plays a central… Elsevier BV

A painless automatic hp-adaptive strategy for elliptic problems
Authors: Darrigrand, V.,Pardo, D.,Chaumont-Frelet, T.,Gómez-Revuelto, I.,Garcia-Castillo, E.
In this work, we introduce a novel hp-adaptive strategy. The main goal is to minimize the complexity and implementational efforts hence increasing the robustness of the algorithm while keeping close to optimal numerical results. We employ a multi-level hierarchical data structure imposing Dirichlet… Elsevier BV

PADL: a Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments
Authors: Ana I. Torre-Bastida,Raúl Miñón,Josu Díaz-de-Arcaya,Javier Del Ser,Aitor Almeida
In this paper we introduce PADL, a language for modeling and deploying data-based analytical pipelines. The novelty of this language relies on its independence from both the infrastructure and the technologies used on it. Specifically, this descriptive language aims at embracing all the… IEEE

Transfer Learning and Online Learning for Traffic Forecasting under Different Data Availability Conditions: Alternatives and Pitfalls
Authors: Javier Del Ser,Ibai Laña,Eric L. Manibardo
This work aims at unveiling the potential of Transfer Learning (TL) for developing a traffic flow forecasting model in scenarios of absent data. Knowledge transfer from high-quality predictive models becomes feasible under the TL paradigm, enabling the generation of new proper models with few data… IEEE

Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment
Authors: Jesus L. Lobo,Javier Del Ser,Ibai Laña,Eneko Osaba,Eric L. Manibardo,Izaskun Oregi,Miren Nekane Bilbao,Eleni I. Vlahogianni
In short-term traffic forecasting, the goal is to accurately predict future values of a traffic parameter of interest occurring shortly after the prediction is queried. The activity reported in this long-standing research field has been lately dominated by different Deep Learning approaches,… IEEE

Dilated LSTM Networks for Short-Term Traffic Forecasting using Network-Wide Vehicle Trajectory Data
Authors: Eleni I. Vlahogianni,Panagiotis Fafoutellis,Javier Del Ser
Short-term traffic forecasting is anticipated as an always evolving research topic, boosted by the tremendous recent advances of Machine Learning and Deep Learning, as well as computational power of modern PCs. In this paper, the Dilated Recurrent Neural Networks are introduced in traffic… IEEE

Bearing assessment tool for longitudinal bridge performance
Authors: Daniel Alvear,David Pardo,David Pardo,David Pardo,David Garcia-Sanchez,Diego Zamora Sánchez,Ana Fernández-Navamuel,Ana Fernández-Navamuel
AbstractThis work provides an unsupervised learning approach based on a single-valued performance indicator to monitor the global behavior of critical components in a viaduct, such as bearings. We propose an outlier detection method for longitudinal displacements to assess the behavior of a… Springer Science and Business Media LLC

DeepReS: A Deep Learning-Based Video Summarization Strategy for Resource-Constrained Industrial Surveillance Scenarios
Authors: Khan Muhammad,Tanveer Hussain,Javier Del Ser,Vasile Palade,Victor Hugo C. de Albuquerque
The exponential growth in the production of video contents in different industries causes an urgent need for effective video summarization (VS) techniques, in order to get an optimal storage and preservation of key information in the video. Compared to other domains, industrial videos are more… Institute of Electrical and Electronics Engineers (IEEE)

Swarm Intelligence for Automatic Color and Contrast Retrieval of Digital Images of Paintings
Authors: Javier Del Ser,Iztok Fister,Eneko Osaba,Andrees Iglesias,Akemi Gaalvez
We address the following problem: given an initial high-quality reference image and a variation of it, how to compute suitable values for color map and contrast such that, when applied to this variation, we get an image very similar visually to the reference image. This problem can be formulated as… IEEE

Automatic Detection of Ventilations During Mechanical Cardiopulmonary Resuscitation
Authors: Xabier Jaureguibeitia,Unai Irusta,Elisabete Aramendi,Pamela C. Owens,Henry E. Wang,Ahamed H. Idris
Feedback on chest compressions and ventilations during cardiopulmonary resuscitation (CPR) is important to improve survival from out-of-hospital cardiac arrest (OHCA). The thoracic impedance signal acquired by monitor-defibrillators during treatment can be used to provide feedback on ventilations,… Institute of Electrical and Electronics Engineers (IEEE)