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13th IEEE-APS Topical Conference on Antennas and Propagation in Wireless communications, APWC 2024

作者： Imaz-Lueje, Borja Martinez-De-Rioja, Daniel Vaquero, Alvaro F. Lopez-Fernandez, Jesus A. Pino, Marcos R. Arrebola, Manuel Universidad Rey Juan Carlos Department of Signal Theory and Communications and Telematic Systems and Computing Fuenlabrada Spain Universidad Politécnica de Madrid Information Processing and Telecommunications Center Madrid Spain Universidad de Oviedo Signal Theory and Communications Group Gijón Spain

ISBN: (纸本)9798350360776

Modern satellite communications rely on high-gain antennas on board the satellite to establish deep-space communications, provide high-throughput links, or perform high-resolution radiometry. Conventional reflector antennas provide high gain beams, although their large aperture and doubly curved surface make them difficult to manufacture, mount on the satellite, and fold and deploy after the satellite launch. © 2024 IEEE.

关键词： Satellite antennas

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Deep learning in crowd counting:A survey

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CAAI Transactions on Intelligence Technology 2024年第5期9卷 1043-1077页

作者： Lijia Deng Qinghua Zhou Shuihua Wang Juan Manuel Górriz Yudong Zhang School of Computing and Mathematical Sciences University of LeicesterLeicesterUK Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Signal Theory Networking and CommunicationsUniversity of GranadaGranadaSpain

Counting high-density objects quickly and accurately is a popular area of *** counting has significant social and economic value and is a major focus in artificial *** many advancements in this field,many of them are not widely known,especially in terms of research *** authors proposed a three-tier standardised dataset taxonomy(TSDT).The Taxonomy divides datasets into small-scale,large-scale and hyper-scale,according to different application *** theory can help researchers make more efficient use of datasets and improve the performance of AI algorithms in specific ***,the authors proposed a new evaluation index for the clarity of the dataset:average pixel occupied by each object(APO).This new evaluation index is more suitable for evaluating the clarity of the dataset in the object counting task than the image ***,the authors classified the crowd counting methods from a data-driven perspective:multi-scale networks,single-column networks,multi-column networks,multi-task networks,attention networks and weak-supervised networks and introduced the classic crowd counting methods of each *** authors classified the existing 36 datasets according to the theory of three-tier standardised dataset taxonomy and discussed and evaluated these *** authors evaluated the performance of more than 100 methods in the past five years on different levels of popular ***,progress in research on small-scale datasets has slowed *** are few new datasets and algorithms on small-scale *** studies focused on large or hyper-scale datasets appear to be reaching a saturation *** combined use of multiple approaches began to be a major research *** authors discussed the theoretical and practical challenges of crowd counting from the perspective of data,algorithms and computing *** field of crowd counting is moving towards combining multiple methods and requ

关键词： artificial intelligence computer vision image analysis image processing

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Dual-Band Reflectarray-Based Electromagnetic Skin to Provide Millimeter-Wave Coverage in the 28/60-GHz Bands

Dual-Band Reflectarray-Based Electromagnetic Skin to Provide...

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European Conference on Antennas and Propagation, EuCAP

作者： Jorge Vallejo Eduardo Martinez-de-Rioja Ana Arboleya Department of Signal Theory and Communications and Telematic Systems and Computing Universidad Rey Juan Carlos Madrid Spain

In this contribution, a low-profile dual-band smart electromagnetic skin (SES) is proposed to improve wireless communications in millimeter-wave 5G. The SES is based on a single-layer reflectarray panel that can operate simultaneously at the 28 and 60 GHz bands. The reflectarray unit-cell consists of a central lower frequency element which is surrounded by four higher frequency elements. The SES has been designed to provide a different coverage for each frequency (i.e., two separate beams with different pointing directions). A beamforming technique has been applied to broaden the beams in azimuth and achieve a wider coverage. The proposed device can be used to enable wireless communications in millimeter-wave 5G by providing enhanced coverage in nonline-of-sight (NLOS) scenarios.

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UNDERSTANDING THE DISPARITIES IN MATHEMATICS PERFORMANCE: AN INTERPRETABILITY-BASED EXAMINATION

arXiv

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arXiv 2025年

作者： Gomez-Talal, Ismael Bote-Curiel, Luis Rojo-Alvarez, Jose Luis Department of Signal Theory and Communications and Telematic Systems and Computation Madrid28943 Spain

Problem. Educational disparities in Mathematics performance are a persistent challenge. This study aims to unravel the complex factors contributing to these disparities among students internationally, with a focus on the interpretability of the contributing factors. Methodology. Utilizing data from the Programme for International Student Assessment (PISA), we conducted rigorous preprocessing and variable selection to prepare for applying binary classification interpretability models. These models were trained using the Stratified K-Fold technique to ensure balanced representation and assessed using six key metrics. Solution. By applying interpretability models such as Shapley Additive Explanations (SHAP) analysis, we identified critical factors impacting student performance, including reading accessibility, critical thinking skills, gender, and geographical location. Results. Our findings reveal significant disparities linked to resource availability, with students from lower socioeconomic backgrounds possessing fewer books and demonstrating lower performance in Mathematics. The geographical analysis highlighted regional educational disparities, with certain areas consistently underperforming in PISA assessments. Gender also emerged as a determinant, with females contributing differently to performance levels across the spectrum. Conclusion. The study provides insights into the multifaceted determinants of student Mathematics performance and suggests potential avenues for future research to explore global interpretability models and further investigate the socioeconomic, cultural, and educational factors at play. Copyright © 2025, The Authors. All rights reserved.

关键词： Students

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Dual-Polarized Reflectarray for Coverage-Enhancing Applications in sub-THz 6G Networks

Dual-Polarized Reflectarray for Coverage-Enhancing Applicati...

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URSI Atlantic Radio Science Conference (URSI AT-RASC)

作者： Alejandro Feito-Rojo Jesús Palací Eduardo Martinez-de-Rioja Ana Arboleya Dept. of Signal Theory and Communications and Telematic Systems and Computing Universidad Rey Juan Carlos Madrid Spain

ISBN: (数字)9789463968102

ISBN: (纸本)9798350360257

This contribution presents the design and simulation results of a dual-polarized reflectarray antenna for coverage-enhancing applications in sub-THz 6G communication networks. A 68 mm x 68 mm reflectarray panel, comprising a planar array of 40 x 40 cells, has been designed to produce two independent beams in orthogonal linear polarizations at 100 GHz, in order to cover two different regions of mobile users. The beams have been broadened by the application of a beamforming technique to cover a wider angular region. The proposed design procedure can be applied to design passive reflectarrays for operation as base station antennas or reflecting intelligent surfaces, capable of improving wireless coverage in future sub-THz 6G systems.

关键词： 6G mobile communication Wireless communication Antenna measurements Base stations Array signal processing Simulation Planar arrays

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Fast Surface Error Diagnosis for Radiotelescopes Using Linearized Microwave Holography

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IEEE Transactions on Antennas and Propagation 2025年第6期73卷 3527-3536页

作者： Romero, Celia Fonta Varela, Fernando Rodriguez Iraguen, Belen Galocha Lopez-Perez, Jose-Antonio Universidad Politécnica de Madrid Information Processing and Telecommunications Center Radiation Group Department of Signals Systems and Radiocommunications MadridE-28040 Spain Universidad Rey Juan Carlos Group of Microwave Engineering and Radiocommunication Systems Department of Signal Theory and Communications and Telematic Systems and Computing MadridE-28942 Spain Centro Astronómico de Yebes Dirección General del Instituto Geográfico Nacional Guadalajara19001 Spain

Radiotelescopes are typically composed of large reflector antennas located outdoors. These antennas are designed to achieve high levels of gain, which is possible due to their large size and RF systems designed for working at high frequencies. However, various sources of error (such as mounting imperfection or deformations caused by gravity and weather effects) are difficult to identify and can significantly degrade the performance of the radiotelescope, reducing its gain. The correct diagnosis of these errors has been a challenge in radioastronomy. The most widely used technique is microwave holography, in which mechanical errors are detected through long electromagnetic acquisitions. The measured far-field is processed to obtain the aperture field and thus the errors affecting the surface or the phase distribution. In this paper, a novel methodology is proposed to diagnose reflector errors using holography. The proposed approach defines a system that models all possible aperture errors as a combination of basis functions, directly relating the errors to the acquired far-field and reducing the number of samples required for analysis. © 1963-2012 IEEE.

关键词： Reflection

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Sequential Networks for Predicting the Clinical Risk of Chronic Patients Using Drug Dispensation

Sequential Networks for Predicting the Clinical Risk of Chro...

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17th International Joint Conference on Biomedical Engineering systems and Technologies, BIOSTEC 2024

作者： Hijosa-Guzmán, Daniel Jurado-Camino, Marıa Teresa Miguel-Bohoyo, Pablo de Mora-Jiménez, Inmaculada Dept. Signal Theory and Communications Telematics and Computing Systems Rey Juan Carlos University Madrid Spain University Hospital of Fuenlabrada Madrid Spain

Chronic diseases are one of the leading causes of death worldwide, with diabetes, hypertension, congestive heart failure, and chronic obstructive pulmonary disease among the most common ones. In this sense, the extraction of clinical patterns from the data recorded in the Electronic Health Record is of great interest and motivates research in models to predict the temporal evolution of the patient’s health status. Predictive models would be of great help in the treatment of chronic patients to carry out preventive policies. Our approach considers the Gated Recurrent Unit neural network to extract temporal patterns of drug dispensation and to predict the progression of Chronic Conditions (CCs) towards a more complex health status. Real-world data linked to chronic patients of a Spanish hospital were considered, obtaining the most probable health status among a set of 10, including single dominant or moderate CCs, significant CCs in multiple organ systems, and dominant CC in three or more organ systems. Accuracy rates above 70% for single dominant or moderate CCs and nearly 50% for significant/dominant conditions across multiple organs were obtained. These results show the potential of sequential networks to predict the clinical risk of chronic patients and support clinical decision-making. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Electronic health record

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Naïve Bayes as a Probabilistic Tool for Monitoring the Health Status of Chronic Patients

Naïve Bayes as a Probabilistic Tool for Monitoring the Heal...

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17th International Joint Conference on Biomedical Engineering systems and Technologies, BIOSTEC 2024

作者： Martínez-Marquina, Laura Teresa Jurado-Camino, María Teresa Caballero-López-fando, Isabel Mora-Jiménez, Inmaculada Dept. Signal Theory and Communications Telematics and Computing Systems Rey Juan Carlos University Madrid Spain University Hospital of Fuenlabrada Madrid Spain

Chronic diseases have emerged as a pervasive global health concern, standing as a leading cause of mortality. Among these, prevalent conditions encompass diabetes, hypertension, congestive heart failure and chronic obstructive pulmonary disease. The large amount of data in Electronic Health Records is being exploited by machine learning schemes to design clinical decision support systems, usually of limited practical application because of lack of transparency. To overcome this issue and given the dynamic nature of the health-status over time, we propose here a patient health monitoring scheme based on a Näive Bayes approach because of its interpretability, minimal computational cost, and efficient handling of high-dimensional and unbalanced data. Our approach considers clinical codes (diagnosis and drugs) on real data collected by a Spanish hospital and provides a probability score for different chronic health-statuses. A gender-based approach has also been explored, exhibiting promising performance when there is a significant patient population for each sex. We conclude that pharmacological codes are more informative, although the best performance was obtained by using all the clinical codes and demographic features. Though a more exhaustive study on patient monitoring is necessary, the proposed NB scheme can be considered a proof of concept which has demonstrated to be a valuable tool and easily interpretable method. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Electronic health record

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Irregular Temporal Classification of Multidrug Resistance Development in Intensive Care Unit Patients

Irregular Temporal Classification of Multidrug Resistance De...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Martín-Palomeque, Paula Escudero-Arnanz, Óscar Álvarez-Rodríguez, Joaquin Soguero-Ruiz, Cristina Rey Juan Carlos University Dept. of Signal Theory and Communications Telematics and Computing Systems Fuenlabrada Madrid Spain University Hospital of Fuenlabrada Intensive Care Department Fuenlabrada Madrid Spain

ISBN: (纸本)9798350386226

The rising incidence of Multidrug-Resistant (MDR) infections in Intensive Care Units (ICUs) presents a critical challenge to global healthcare, leading to adverse patient outcomes and increased costs. Early identification of MDR pathogens is crucial for timely implementation of isolation protocols and prevention of cross-infections. This study introduces a novel Deep Learning (DL) framework for temporal prediction of MDR status in ICU patients, addressing the complexities of irregular classification tasks. We utilize Electronic Health Records from 3,502 anonymized ICU patient records spanning 17 years at the University Hospital of Fuenlabrada, Madrid, Spain. Five advanced DL architectures are systematically evaluated: Vanilla Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Unit, and Transformer, each adapted for irregular Multivariate Time Series (MTS) data. Notably, this is the first study to assess the impact of temporal window size on predictive performance and to adapt different RNN models for irregular temporal classification in MTS. Our results show that the LSTM model, when applied to a 4-day temporal window, achieves the highest predictive performance, with a mean Receiver Operating Characteristic Area Under the Curve of 79.78 ± 2.78. This study highlights the importance of early temporal windows in capturing critical indicators of MDR infections and significantly advances the state-of-the-art in MDR prediction, providing a robust foundation for more effective ICU management and potential reduction of MDR infections in healthcare settings. © 2024 IEEE.

关键词： Electronic health record

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Dual-Band Metasurface-Based Radome for Millimeter-Wave 5G Applications

Dual-Band Metasurface-Based Radome for Millimeter-Wave 5G Ap...

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European Conference on Antennas and Propagation, EuCAP

作者： Roman Soroka Ana Arboleya Eduardo Martinez-De-Rioja M. E. De Cos Gómez Department of Signal Theory and Communications and Telematic Systems and Computing Universidad Rey Juan Carlos Madrid Spain Electrical Engineering Department TSC Universidad de Oviedo Gijón Spain

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This contribution presents the design of a dual-band metasurface-based radome (metaradome, MTR) for antenna protection applications in millimeter-wave 5G. The proposed MTR has two transmission bands at 28 GHz and 39 GHz. A parametric study has been carried out to characterize the frequency response of the MTR. Then, the designed MTR has been combined with a reflectarray-based Smart Electromagnetic Skin (SES) to analyze the impact of the MTR on the radiation performance of the SES: first, the MTR unit-cell has been combined with the SES unit-cell to analyze its performance; then, the complete SES has been loaded with the MTR and the radiation patterns of the structure have been computed. The simulated results confirm the potential of the proposed MTR to protect the SES without degrading its performance and allowing for a much more compact design than a conventional half-wavelength radome.

关键词： 5G mobile communication Parametric study Dual band Millimeter wave propagation Metasurfaces Skin Frequency response Radomes Protection Electromagnetics

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