Publications

Displaying 226 - 250 of 1307

Publication	Date
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 Abstract 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 the development of new technologies for image processing, as much as it has helped in the evolution of many new… Elsevier BV	2020-12-01
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	2020-11-24
Convective storms and atmospheric vertical structure in Uranus and Neptune Authors: Guillot, Tristan,Hueso, R.,Sánchez-Lavega, A. 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	2020-11-09
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	2020-11-06
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	2020-11-01
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	2020-11-01
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	2020-10-21
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	2020-10-20
A painless automatic hp-adaptive strategy for elliptic problems Authors: Darrigrand, Vincent,Pardo, David,Chaumont-Frelet, Théophile,Gómez-Revuelto, Ignacio,Garcia-Castillo, Emilio Luis 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	2020-10-01
Do all roads lead to Rome? Understanding the role of initialization in iterative back-translation Authors: Artetxe Zurutuza, Mikel,Labaka Intxauspe, Gorka,Casas, Noe,Agirre Bengoa, Eneko 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	2020-10-01
PADL: a Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments Authors: Diaz-de-Arcaya, Josu,Minon, Raul,Torre-Bastida, Ana I.,Del Ser, Javier,Almeida, Aitor 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	2020-09-23
Transfer Learning and Online Learning for Traffic Forecasting under Different Data Availability Conditions: Alternatives and Pitfalls Authors: Manibardo, Eric L.,Lana, Ibai,Del Ser, Javier 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	2020-09-20
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	2020-09-20
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	2020-09-20
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	2020-09-02
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)	2020-09-01
Strong increase in dust devil activity at Gale crater on the third year of the MSL mission and suppression during the 2018 Global Dust Storm Authors: Agustín Sánchez-Lavega,Ricardo Hueso,I. Ordonez-Etxeberria Abstract The Rover Environmental Monitoring Station (REMS) instrument in the Mars Science Laboratory (MSL) mission has collected atmospheric data from Gale crater for more than three Martian years. These data correspond to a path travelled by the Curiosity rover of 18 km in length with… Elsevier BV	2020-09-01
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)	2020-09-01
Swarm Intelligence for Automatic Color and Contrast Retrieval of Digital Images of Paintings Authors: Gaalvez, Akemi,Osaba, Eneko,Iglesias, Andrees,Del Ser, Javier,Fister, Iztok 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	2020-09-01
A Novel Formulation for the Energy Storage Scheduling Problem in Solar Self-consumption Systems Authors: Javier Del Ser,Sandra Riaño,Ricardo S. Alonso,Icíar Lloréns,Sergio Gil-Lopez Energy storage systems are key components to increase photovoltaic (PV) self-consumption profitability. Indeed, they allow for the intermittency dampening of the PV production so as to adequately cover end-users’ consumption. Given that in most grid-connected PV systems electricity prices are… Springer International Publishing	2020-08-29
Robust image classification against adversarial attacks using elastic similarity measures between edge count sequences Authors: Izaskun Oregi,Javier Del Ser,Aritz Pérez,José A. Lozano Due to their unprecedented capacity to learn patterns from raw data, deep neural networks have become the de facto modeling choice to address complex machine learning tasks. However, recent works have emphasized the vulnerability of deep neural networks when being fed with intelligently manipulated… Elsevier BV	2020-08-01
A Comparison of Numerical Approaches for the Design of Mooring Systems for Wave Energy Converters Authors: Imanol Touzon,Vincenzo Nava,Borja de Miguel,Victor Petuya This paper analyses the numerical outcome of applying three different well-known mooring design approaches to a floating wave energy converter, moored by means of four catenary lines. The approaches include: a linearized frequency domain based on a quasistatic model of the mooring lines, a time… MDPI AG	2020-07-16
Towards the Prediction of Rearrest during Out-of-Hospital Cardiac Arrest Authors: Andoni Elola,Elisabete Aramendi,Enrique Rueda,Unai Irusta,Henry Wang,Ahamed Idris A secondary arrest is frequent in patients that recover spontaneous circulation after an out-of-hospital cardiac arrest (OHCA). Rearrest events are associated to worse patient outcomes, but little is known on the heart dynamics that lead to rearrest. The prediction of rearrest could help improve… MDPI AG	2020-07-09
Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples Authors: Alejandro Barredo-Arrieta,Javier Del Ser 7 pages, 5 figures. Accepted for its presentation at WCCI 2020 IEEE	2020-07-01
Bat Algorithm Method for Automatic Determination of Color and Contrast of Modified Digital Images Authors: Galvez, Akemi,Iglesias, Andres,Osaba, Eneko,Del Ser, Javier This paper presents a new artificial intelligence-based method to address the following problem: given an initial digital image (source image), and a modification of the image (mod image) obtained from the source through a color map and visual attributes assumed to be unknown, determine suitable… IEEE	2020-07-01