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TechRxiv 2022年

作者： Domínguez-Dorado, Manuel Carmona-Murillo, Javier Polo, David Cortés Rodríguez Pérez, Francisco J. Department of Information Systems and Digital Toolkit. Public Business Entity Red.es. Madrid28020 Spain Department of Computing and Telematics Engineering Universidad de Extremadura Cáceres10003 Spain Department of Signal Theory and Communications and Telematics Systems and Computing Rey Juan Carlos University Móstoles Madrid28933 Spain

Currently different reference models are used to manage cybersecurity, although practically none are applicable "as is" to lower levels as they do not detail specific procedural aspects for them. However, they urge organizations to develop a methodological foundation to manage cybersecurity at those levels. Although they allow organizations to adhere to a recognized standard at the strategic level, this advantage vanishes when organizations must define specific low-level procedures, allowing the appearance of inconsistency at tactical and operational levels between departments of the same organization or between organizations. The design of these elements with the required holism and homogeneity is difficult, and this is why generic processes focused on getting certified regarding a standard are usually originated, but they are insufficient to obtain effective cybersecurity because they are not focused on dealing with real cyber threats. Because of the great responsibility of lower levels to achieve effective cybersecurity, this lack of methodological definition makes it difficult to adapt cybersecurity to the highly dynamic cyber context with the required holism and strategic alignment. Our proposal provides CyberTOMP, a process for managing cybersecurity at lower levels, as well as a set of methodological elements that support it. The novelty of these contributions is that they complement the strategic standard selected by the organization, providing it with a set of procedural elements ready to be used out of the box, contributing those aspects required by high-level frameworks to manage cybersecurity at lower levels, for which there is no alternative with a managerial approach. © 2022, CC BY-SA.

关键词： Cybersecurity

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Temporal feature selection for characterizing antimicrobial multidrug resistance in the intensive care unit 1

Temporal feature selection for characterizing antimicrobial ...

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1st International AAI4H - Advances in Artificial Intelligence for Healthcare Workshop, AAI4H 2020

作者： Escudero-Arnanz, Oscar Mora-Jimenez, Inmaculada Martinez-Aguero, Sergio Alvarez-Rodriguez, Joaquin Soguero-Ruiz, Cristina Department of Signal Theory and Communications Telematics and Computing Systems Rey Juan Carlos University Madrid28943 Spain Intensive Care Department University Hospital of Fuenlabrada Madrid28942 Spain

The emergence and increase of antimicrobial multidrug resistance (AMR) is a demographic and economic problem for current health systems. AMR is particularly problematic in clinical units such as the intensive care unit (ICU), where the risk of infection is high, principally due to the extensive use of antimicrobials and invasive devices. In this work, we propose the use of different temporal feature selection and classification approaches to ascertain the most informative features and extract knowledge for characterizing AMR in the ICU. For this purpose, a set of demographic and temporal features such as antibiotics taken daily by the patient and the use of mechanical ventilation are considered. According to the results obtained in this work, it could be concluded that temporal features such as mecanic ventilation provide powerful insights to predict AMR in ICU. Copyright © 2020 for this paper by its authors.

关键词： Intensive care units

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A Bayesian inference and model selection algorithm with an optimisation scheme to infer the model noise power

arXiv

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arXiv 2021年

作者： López-Santiago, Javier Martino, L. Vázquez, M.A. Miguez, J. Dep. of Signal Theory and Communications Universidad Carlos III de Madrid Av. de la Universidad 30 LeganésE-28911 Spain Dep. of Signal Theory and Communications Telematic Systems and Computation Universidad Rey Juan Carlos Camino del Molino s/n. FuenlabradaE-28943 Spain

Model fitting is possibly the most extended problem in science. Classical approaches include the use of least-squares fitting procedures and maximum likelihood methods to estimate the value of the parameters in the model. However, in recent years, Bayesian inference tools have gained traction. Usually, Markov chain Monte Carlo methods are applied to inference problems, but they present some disadvantages, particularly when comparing different models fitted to the same dataset. Other Bayesian methods can deal with this issue in a natural and effective way. We have implemented an importance sampling algorithm adapted to Bayesian inference problems in which the power of the noise in the observations is not known a priori. The main advantage of importance sampling is that the model evidence can be derived directly from the so-called importance weights - while MCMC methods demand considerable postprocessing. The use of our adaptive target, adaptive importance sampling (ATAIS) method is shown by inferring, on the one hand, the parameters of a simulated flaring event which includes a damped oscillation and, on the other hand, real data from the Kepler mission. ATAIS includes a novel automatic adaptation of the target distribution. It automatically estimates the variance of the noise in the model. ATAIS admits parallelisation, which decreases the computational run-times notably. We compare our method against a nested sampling method within a model selection problem. Copyright © 2021, The Authors. All rights reserved.

关键词： Importance sampling

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Predicting A New Hotel Rating System by Analysing UGC Content from Tripadvisor: Machine Learning Application to Analyse Service Robots Influence

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Procedia Computer Science 2022年 200卷 1078-1083页

作者： Jorge Calero-Sanz Alicia Orea-Giner Teresa Villacé-Molinero Ana Muñoz-Mazón Laura Fuentes-Moraleda Signal and Communications Theory and Telematic Systems and Computing Rey Juan Carlos University Madrid Spain Department of Applied Mathematics and Statistics EIAE Technical University of Madrid Madrid Spain High Performance Research Group OPENINNOVA Rey Juan Carlos University Madrid Spain EIREST Université Paris 1 Panthéon-Sorbonne Paris France Business economics Rey Juan Carlos University Madrid Spain Centro Universitario de Estudios Turísticos Rey Juan Carlos University Madrid Spain

Industry 4.0 tools permit computerized creation measures, and Artificial Intelligence (AI) approaches are pivotal in investigating the travel industry. Applying these devices to decipher User Generated Content (UGC) is fundamental to understand better client’s necessities, opinions, and assumptions regarding tourism services. Through this research, an exploratory analysis of results is developed through Machine Learning Models to understand better the role played by robot and traveler typologies on the rating given to hotels considering TripAdvisor reviews of 74 hotels. The purpose of this exploratory research is to develop a methodology focused on analyzing online reviews related to service robots in hotels using Machine Learning techniques to train the data collected from TripAdvisor. Preliminary results show a link between the hotel rating given in TripAdvisor and the robot typology implemented in hotels.

关键词： robot typology traveler TripAdvisor Rating Machine Learning

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Wideband Hybrid Dielectric Resonator Antenna Array for 5G mmWave Mobile Applications

Wideband Hybrid Dielectric Resonator Antenna Array for 5G mm...

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Global Power, Energy and Communication Conference (GPECOM)

作者： Ali Zidour Mohammad Alibakhshikenari Mouloud Ayad Chan Hwang See Ernesto Limiti Department of Electrical Systems Engineering Faculty of Technology University of M’Hamed Bougara Boumerdes Algeria Department of Signal Theory and Communications Universidad Carlos III de Madrid Leganés Madrid Spain Department of Electronics Faculty of Technology Ferhat Abbas University of Setif1 Setif Algeria School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK Electronic Engineering Department University of Rome “Tor Vergata” Rome Italy

ISBN: (数字)9798350351088

ISBN: (纸本)9798350351095

In this paper, a wideband hybrid dielectric resonator antenna (HDRA) array design is presented for fifth-generation (5G) millimeter wave (mmWave) applications. The hybrid antenna integrates three resonant radiators of feeding slot, ring patch, and DRA to generate four resonances around 28 and 38 GHz frequency bands. The antenna element within an overall size of 0.46λ L × 0.46λ L × 0.1λ L (λ L is the free-space wavelength at 28 GHz) can achieve wide impedance bandwidth, covering n257, n259, n260 and n261, simultaneously. The 1 × 4 HDRA array is designed and simulated based on the antenna element which can achieve high realized gain varies between 10.3 to 12.5 dBi and wide beam scanning angles of ±55° and ±40° at 28 and 38 GHz frequency bands, respectively.

关键词： Slot antennas 5G mobile communication Resonant frequency Mobile antennas Dielectric resonator antennas Dielectrics Broadband antennas

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Corrigendum to “Understanding the disparities in Mathematics performance: An interpretability-based examination” [Eng. Appl. Artif. Intell. 133 Part B (2024) 108109]

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Engineering Applications of Artificial Intelligence 2025年 150卷

作者： Ismael Gómez-Talal Luis Bote-Curiel José Luis Rojo-Álvarez Rey Juan Carlos University Department of Signal Theory and Communications and Telematic Systems and Computation Camino del Molino s/n Fuenlabrada 28943 Madrid Spain D!lemmaLab Ldt. Camino del Molino s/n Fuenlabrada 28943 Madrid Spain

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On Using Deep Learning for Automatic Classification System of Microseisms at Cotopaxi Volcano

On Using Deep Learning for Automatic Classification System o...

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IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI)

作者： Román Lara-Cueva Iván Iglesias Alejandro Rosero Diego Benítez Noel Pérez-Pérez José Luis Rojo Ad Hoc Networks Research Center (CIRAD) Grupo de Investigación en Sistemas Inteligentes (WiCOM-Energy) Departamento de Eléctrica Electrónica y Telecomunicaciones Universidad de las Fuerzas Armadas ESPE Sangolquí Ecuador Colegio de Ciencias e Ingenierías “El Politécnico” Universidad San Francisco de Quito USFQ Quito Ecuador Department of Signal Theory and Communications Telematics and Computing Systems Universidad Rey Juan Carlos Madrid Spain

ISBN: (数字)9798331516901

ISBN: (纸本)9798331516918

This paper presents an automatic classification system of Long Period (LP) and Volcano Tectonic (VT) events from the Cotopaxi volcano, by using two Deep Learning techniques: Stack Autoencoders and Deep Neural Networks. We used a dataset provided by the Instituto Geofísico de la Escuela Politécnica Nacional (IGEPN) containing 1,044 LP and 101 VT events, in addition, we employed data augmentation process by considering a synthetic microseisms generator based on Conditional Generative Adversarial Network. Our dataset comprises 10,000 microseisms, including both real and synthetic instances. In the feature extraction stage, which involves computing Power Spectral Density (PSD) by using Welch’s estimator with a Fast Fourier Transform (FFT) of 512 points, resulting in 257 frequency-based features. Additionally, we extracted coefficients from the Discrete Wavelet Transform using Symlet as the mother wavelet with six decomposition levels; then, PSD was computed on these coefficients, yielding an additional 257 frequency-scale features. Deep Learning algorithms were trained on this feature rich dataset and evaluated using standard performance metrics. The autoencoder technique yielded the best results, achieving an accuracy of 99.73% and a balanced error rate (BER) of 0.0027, indicating misclassification of only 3 out of 1000 microseisms. These results exceed the geophysical requirement of a BER below 0.01. This study demonstrates the effectiveness of Deep Learning techniques in classifying LP and VT events, offering promising avenues for improved volcanic risk monitoring and assessment.

关键词： Deep learning Measurement Fast Fourier transforms Transforms Feature extraction Volcanoes Discrete wavelet transforms

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Single-layer dual-band frequency selective surface for coverage-enhancing applications in millimeter-wave 5G

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Results in Engineering 2025年 27卷

作者： Mousa Abdollahvand Eduardo Martinez-de-Rioja Kanishka Katoch Ana Arboleya Celia Fontá Department of Electrical and Computer Engineering University of Mohaghegh Ardabili Ardabil Iran Department of Signal Theory and Communications and Telematic Systems and Computing Universidad Rey Juan Carlos 28942 Fuenlabrada Spain Department of Electronics and Communication Engineering JUIT Waknaghat Solan Himachal Pradesh India Information Processing and Telecommunications Center Department of Signals Systems and Radiocommunications Universidad Politecnica de Madrid 28040 Madrid Spain

This work presents a dual-band Frequency Selective Surface (FSS) for improving 5G communications at millimeter-wave bands. The FSS is based on a single-layer configuration which supports dual polarization, with a unit-cell period of 4 mm x 4 mm. The structure exhibits two reflection bands at 28 GHz and 39 GHz. An equivalent circuit model has been developed for the proposed FSS, showing good agreement with full-wave electromagnetic simulations. A 200 mm x 200 mm prototype of the FSS, comprising an array of 50 × 50 unit-cells has been fabricated and tested, and the measured transmission and reflection coefficients agree well with the simulations. Moreover, the frequency response of the FSS shows good stability for incidence angles up to 40°. The proposed single-layer dual-band FSS has applications in the design of smart reflecting surfaces to enhance wireless communications in 5G networks operating at the 28 and 39 GHz bands, either alone or in combination with metasurface or reflectarray elements that could be placed on its upper side.

关键词： 5G communications Coverage enhancement Dual band Electromagnetic skin Frequency selective surface Millimeter waves

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Different Ventricular Fibrillation Types in Low-Dimensional Latent Spaces

SSRN

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SSRN 2022年

作者： Bernal-Oñate, Carlos Paúl Melgarejo-Meseguer, Francisco Manuel Carrera, Enrique Vinicio Sánchez-Muñoz, Juan José García-Alberola, Arcadi Rojo-Álvarez, José Luis Departamento de Eléctrica Electrónica y Telecomunicaciones Universidad de las Fuerzas Armadas – ESPE Sangolqui Ecuador Department of Signal Theory and Communications Telematics and Computing Systems Universidad Rey Juan Carlos Madrid Spain Unidad de Arritmias Hospital Clínico Universitario Virgen de la Arrixaca Murcia Spain

The causes of ventricular fibrillation (VF) are not yet elucidated, and it has been proposed that even different mechanisms might exist. Moreover, conventional analysis methods do not seem to provide time or frequency domain features capable of recognizing different VF patterns in electrode-recorded biopotentials. The present work aims to determine whether low-dimensional latent spaces could exhibit discriminative features for different mechanisms or conditions during VF episodes. For this purpose, manifold learning using autoencoder neural networks was analyzed on surface ECG recordings from the onset of the VF episode and lasting 6 minutes in an experimental database (based on an animal model) with five situations, including control, drug intervention (amiodarone, diltiazem, and flecainide), and autonomic nervous system blockade (ANSB). Latent spaces from unsupervised schemes yielded moderate but noticeable separability among the different types of VF according to their type or intervention, reaching a multi-class classification accuracy of 66%. At the same time, supervised structures improved the separability of the generated latent spaces providing a classification accuracy of up to 74%. In addition, conventional audio features in the frequency domain yielded separability for both the unsupervised and supervised manifolds, reaching 58% multi-class accuracy. We can conclude that manifold learning schemes can provide a valuable tool for studying different types of VF while working in low-dimensional latent spaces. Hence, these techniques can be helpful in current research towards elucidating the existence of different VF underlying mechanisms. © 2022, The Authors. All rights reserved.

关键词： Frequency domain analysis

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Comparison of Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) Filters in Cardiac Optical Mapping Records 2nd

Comparison of Infinite Impulse Response (IIR) and Finite Imp...

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2nd International Conference on Applied Technologies, ICAT 2020

作者： Rivas-Lalaleo, David Muñoz-Romero, Sergio Huerta, Monica Bautista-Naranjo, Víctor García-Quintanilla, Jorge Moreno-Planas, Javier Rojo-Álvarez, José Luis Departamento de Eléctrica Y Electrónica Universidad de Las Fuerzas Armadas ESPE Av. General Rumiñahui S/n Sangolquí171-5-231B Ecuador Department of Signal Theory and Communications and Telematic Systems and Computation Universidad Rey Juan Carlos Madrid28933 Spain Universidad Politécnica Salesiana Cuenca Ecuador Hospital Clínico San Carlos Madrid Spain Arrhythmia Unit Hospital Ramon y Cajal Ctra. de Colmenar Viejo Madrid Spain

ISBN: (纸本)9783030715021

Optical cardiac mapping is an experimental method developed to record the electrical behavior of the heart, through the analysis of films filmed at high speed. Due to the conditions of the experiment along with the signal, a great amount of noise from different sources is stored. In this article, the comparison of the IIR type filters and the FIR filters is proposed, where the order of the filters, the phase difference and the application on the film have been compared. From this analysis it is determined that a 9th order IIR filter behaves in the same way as a 256 order FIR filter. Therefore, it can be determined that a 9th order IIR filter can be used for filtering this type of signal, reducing the computational costs in its application. © 2021, Springer Nature Switzerland AG.

关键词： FIR filters

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