Search

Multi-Media applications are amongst the most demanding services, requiring high amounts of network capacity and computational resources for synchronous audio-visual streaming with high quality. Gaming streaming is one of the most demanding of these media applications. Recent technological advances in the 5G domain, precisely Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC), unlock media industries’ potential by offering high-quality media services through dynamic and efficient resource allocation with low latency. This work presents a multi-site gaming streaming use case implemented over an end-to-end 5G-enabled platform provided by the EU H2020 5G-PPP 5G EVE project. Furthermore, we present the executed use case experiment scenarios to validate the use case performance following a set of defined Quality of Experience(QoE)-related Key Performance Indicators (KPIs). In particular, this paper discusses the design workflow and orchestration of the multi-site gaming streaming use case across two 5G EVE sites (i.e., Spain and Greece), providing a detailed description of the network function applications and resources utilized for the use case. Subsequently, leveraging the 5G EVE monitoring platform, this paper elaborates on the executed experiment scenarios that provide the defined KPI metrics data. Finally, this paper presents, discusses, and analyzes the obtained KPI metrics data results and provides recommendations on future works for these kinds of use cases. [ABSTRACT FROM AUTHOR]

In this paper, we design an Anomaly Detection (AD) framework for mobile data traffic, capable of identifying different types of anomalous events generated by flash crowds in metropolitan areas. We state the problem using a semi-supervised approach and exploit the great performance of different Recurrent Neural Network (RNN) models to learn the temporal context of input sequences. Our proposal processes real traffic traces from the unencrypted LTE Physical Downlink Control Channel (PDCCH) of an operative network, gathered during an extensive measurement campaign in two major cities in Spain. The AD framework is designed to perform: i) a-posteriori analysis to understand users’ behavior and urban environment variations; ii) real-time analysis to automatically and on-the-fly alert urban anomalies; and iii) estimation of the duration of the periods identified as anomalous. Numerical results show the higher performance of our AD framework compared to classic AD algorithms and confirm that the proposed framework predicts anomalous behaviours with high accuracy and regardless of their cause. [ABSTRACT FROM AUTHOR]

The use of protons and heavy ions for the treatment of tumors is increasing since it provides a better relative biological effectiveness (RBE) than traditional radiotherapy. Accurate knowledge of the energy deposition at submicrometric scales is paramount for RBE characterization. This paper shows the latest version of the silicon cylindrical microdosimeter array developed by the Instituto de Microelectrónica de Barcelona, Centro Nacional de Microelectrónica (IMB-CNM, Spain). The detector consists of a matrix of $11 \times 11$ cylindrical sensitive unit cells with individual readout etched within the silicon substrate available in different diameters and pitches between detectors. The detector employed in this paper had a diameter of $15~\mu \text{m}$ , a pitch of $200~\mu \text{m}$ , and a thickness of $5.5~\mu \text{m}$. The detectors were tested in the clinical facilities of Fondazione Centro Nazionale di Adronterapia Oncologica (CNAO) (Pavia, Italy) employing a 12C pencil beam at a therapeutic beam fluence rate. Microdosimetric spectra of lineal energy were measured in different depths of polymethyl methacrylate (PMMA) up to the Bragg peak. Results were then compared with Monte Carlo simulations using the FLUKA particle transport code, showing an excellent agreement between experimental and simulated microdosimetric distributions even at the high fluence rates associated with clinical beams. [ABSTRACT FROM AUTHOR]

Banks are the backbone of the financial sector and catalysts in the economic development of any country. Current changes in their global business ecosystem make knowledge of about the fund-supplying and fund-demanding parties of the society a key resource for the fulfillment of banks’ investment and saving functions. This paper addresses the relationship between the performance and a learning culture that is supported by knowledge processes within the organization. Given the relevance of this subject for organizations from most knowledge-intensive domains, this research has focused on the Spanish banking sector. Using a structural equation model, feedback received from 215 employees from 142 individual branches from a major banking institution in Spain is studied. The results of the data analysis show that in addition to maximizing on what is already known about the customer base, employees’ learning about the potential new stakeholders and also about the internal strategies, tools, and techniques is directly related to the bank's performance, which, in turn, influences the economic recovery and socio-economic development. Results support that an active pursuit of learning within the context of the organization is required for banks to remain competitive in the dynamic, global business ecosystem, where international, national, and local banking sectors operate. [ABSTRACT FROM AUTHOR]

This paper addressesthe problem of real-time state estimation in European-type four-wire low-voltage distribution networks with advanced metering infrastructure based on power line communication (PLC). The main drawback of this type of infrastructure is its high latency and a sequential data sampling process. Both factors make it difficult to obtain instantaneous values from the smart meters in a timely and adequate manner to estimate the real-time state of the system. This problem may be solved in the future with the deployment of metering systems based on other technologies such as 5G. However, PLC technology prevails in many countries, and is not likely to be replaced in the medium term. In the meantime, a solution is needed to provide acceptable real-time state estimates in low voltage networks, not to hinder the active management of these assets in the context of smart grids. In this work, a solution is proposed that allows estimating the state of the low voltage network with a reasonable accuracy considering the low quality of the measurements provided by the deployed infrastructure. The system is validated using a portion of a real pilot network located in the north of Spain fed by a transformer station with seven feeders. [ABSTRACT FROM AUTHOR]

The large penetration of renewable energy resources is demanding additional flexibility for the operation of power systems. In this sense, real world applications are proving that wind power units are able to provide part of the required flexibility. Therefore, these new sources of flexibility need to be considered by power system planners in order to make appropriate generation capacity expansion decisions. This paper proposes a generation and storage capacity expansion formulation considering that wind power units are able to participate in the reserve provision service. The proposed model is a stochastic linear program that is solved using a commercial solver. A case study based on the isolated power system of Lanzarote and Fuerteventura in Spain is solved to quantify the impact of considering the reserve provision of wind power in capacity investment decisions. [ABSTRACT FROM AUTHOR]

5G is a key tool for the cloud-based wireless production of audio-visual contents. By providing higher throughput and lower latency than previous mobile network technologies, as well as flexible allocation of network resources, it enables that some content production pipelines, which are currently implemented using wired connectivity, are provided on top of a 5G network. This brings down production costs, reduces environmental impact and increases operational efficiency. In particular, live immersive production services, such as free-viewpoint video (FVV), can be provided in a much more efficient way. In this paper, we address the challenge of producing and streaming FVV services in real time through 5G networks. We have adapted a state-of-the-art FVV system to integrate it within a 5G architecture, using three key technological enablers: mmWave radio access network to support the uplink traffic requirements from FVV cameras, multi-access edge computing to run video processing algorithms with minimum latency, and end-to-end slicing to guarantee a sufficient quality of service (QoS) within the production pipeline. We have built a field trial over the production network of a telecommunication operator, including a mmWave pilot deployment, edge cloud processing, and remote content production, involving three different locations across Spain. We have measured the key performance indicators at the relevant parts of our trial deployment, showing that, with existing 5G technology, it is possible to achieve live FVV production, although with some limitations. We have also analyzed such limitations, obtaining some insights on how the next generation of 5G networks can overcome them to achieve higher quality of experience (QoE). [ABSTRACT FROM AUTHOR]

Non-technical losses (NTL) in electricity utilities are responsible for major revenue losses. In this paper, we propose a novel end-to-end solution to self-learn the features for detecting anomalies and frauds in smart meters using a hybrid deep neural network. The network is fed with simple raw data, removing the need of handcrafted feature engineering. The proposed architecture consists of a long short-term memory network and a multi-layer perceptrons network. The first network analyses the raw daily energy consumption history whilst the second one integrates non-sequential data such as its contracted power or geographical information. The results show that the hybrid neural network significantly outperforms state-of-the-art classifiers as well as previous deep learning models used in NTL detection. The model has been trained and tested with real smart meter data of Endesa, the largest electricity utility in Spain. [ABSTRACT FROM AUTHOR]

The recently approved regulation about self-consumption in Spain will dramatically change the level of penetration of photovoltaic distributed generation combined with storage devices at residential level in short term. In this paper, we will study the impact of the massive installation of such technologies under the constraints imposed by the new regulation, over the terminal distribution network. As it will be demonstrated, this impact will be drastic in terms of energy demand, voltage profile, and load curves. [ABSTRACT FROM AUTHOR]

In this paper, a new method for prediction of future performance and demand on emergency department (ED) in Spain is presented. Increased life expediency and population aging in Spain, along with their corresponding health conditions such as non-communicable diseases (NCDs), have been suggested to contribute to higher demands on ED. These lead to inferior performance of the department and cause longer ED length of stay (LoS). Prediction and quantification of behavior of ED is, however, challenging as ED is one of the most complex parts of hospitals. Using detailed computational approaches integrated with clinical data behavior of Spain's ED in future years was predicted. First, statistical models were developed to predict how the population and age distribution of patients with non-communicable diseases change in Spain in future years. Then, an agent-based modeling approach was used for simulation of the emergency department to predict impacts of the changes in population and age distribution of patients with NCDs on the performance of ED, reflected in ED LoS, between years 2019 and 2039. Results from different projection scenarios indicated that Spain would experience a continuous increase in total ED LoS from 5.7 million hours in 2019 to 6.2 million hours in 2039 if same human and physical resources, as well as same ED configuration, are used. The results from this study can provide health care provider with quantitative information on required staff and physical resources in the future and allow health care policymakers to improve modifiable factors contributing to the demand and performance of ED. [ABSTRACT FROM AUTHOR]

Tunnels represent strong multipath environments for communications, where wireless propagation differs from regular indoor or outdoor scenarios. Moreover, with an adequate operating frequency choice, a tunnel behaves as an oversized waveguide, extending the communication range but affecting the signal with strong fadings. These fadings have been closely studied in the literature in the longitudinal dimension (tunnel length). Nevertheless, they also occur in the cross section, where they have only been analyzed statistically and on a small scale. In this paper, we present the results from an extensive measuring campaign carried out at the Somport tunnel, in Spain. We have adopted the modal theory approach to analyze the large-scale fadings (also known as slow fadings) in the longitudinal, transversal, and vertical dimensions. More specifically, the modes’ geometry allowed for the adequate placement of transmitters to create different periodic fading structures and to virtually divide the tunnel cross section into sectors, where the fadings presented a phase shift of 180°. This study enabled the development of large-scale spatial diversity schemes and navigation techniques to improve communication and localization inside these scenarios. [ABSTRACT FROM AUTHOR]

Minimizing energy consumption in buildings is one of the priorities of the European Union energy strategy. The European legislation has defined a legal framework to determine the energy qualification of a building that is used by each of the member states to define its own energy qualification procedure. This paper presents a methodology to evaluate the effect of climate conditions in the energy qualification procedure. It evaluates the effectiveness of the qualification in representing the yearly energy demand and \CO2 emissions. Moreover, it determines the effects of improvements in different parameters of the procedure (e.g., the construction materials of the enclosure, thermal installations, etc.) in order to improve qualifications. It has been applied to the Spanish legislation using a series of simulations of a typical domestic building, with climatic data from different zones of the Spanish territory. The most significant results are the similarity in the energy certification values obtained in all scenarios and the lack of concordance between the energy rating scale, energy consumption, and \CO2 emissions. [ABSTRACT FROM PUBLISHER]

The COVID-19 pandemic presents unprecedented challenges to the healthcare systems around the world. In 2020, Spain was among the countries with the highest Intensive Care Unit (ICU) hospitalization and mortality rates. This work analyzes data of COVID-19 patients admitted to a Spanish ICU during the first wave of the pandemic. The patients in our study either died (deceased patients) or were discharged from the ICU (non-deceased patients) and underwent the following landmarks: beginning of symptoms; arrival at the emergency department; beginning of the hospital stay; and ICU admission. Our goal is to create a graph-based data-science methodology to find associations among patients’ comorbidities, previous medication, symptoms, and the COVID-19 treatment, and to analyze their evolution across landmarks. Towards that end, we first perform a hypothesis test based on bootstrap to identify discriminative features among deceased and non-deceased patients. Then, we leverage graph-based representations and network analytics to determine pairwise associations and complex relations among clinical features. The descriptive statistical analysis confirms that deceased patients exhibit multiple comorbidities with stronger levels of association and are treated with a wider range of drugs during the ICU stay. We also observe that the most common treatment was the simultaneous administration of lopinavir/ritonavir with hydroxychloroquine, regardless of the patients’ outcome. Our results illustrate how graph tools and representations yield insights on the relations among comorbidities, drug treatments, and patients’ evolution. All in all, the approach puts forth a new data-analysis tool for clinicians that can be applied to analyze (post-COVID) symptom/patient evolution. [ABSTRACT FROM AUTHOR]

In this paper, experimental broadband propagation measurements in a typical sea port scenario at 5.8 GHz are presented. Measurements were performed in Cádiz Bay, Spain, by sounding the channel with a periodic pulsed signal, from which power delay profiles (PDPs) were estimated for several locations. The study focuses on propagation scenarios based on low-height antenna deployments. Experimental PDPs are found with a spiky shape that can be explained from the nature of the environment. This result is significantly different from the one expected in other regular environments (urban, indoor, etc.) where continuous shaped profiles are common. Furthermore, time-dispersive parameters, such as mean delay, delay spread, and coherence bandwidth, are extracted. The estimated values for mean delay and delay spread remain small, which indicates that the channel can be regarded as flat for typical low-bandwidth signals employed over the sea. In fact, the median value for coherence bandwidth is found to be 8 MHz, hence these channels are suitable to support relatively high data rates by using simple communication systems. [ABSTRACT FROM AUTHOR]

Presents information on the ICDL 2022 Conference. [ABSTRACT FROM AUTHOR]

This is the fourth article in the series of eight, opened in September and published monthly in the Global Communications Newsletter, which covers all areas of IEEE ComSoc Member Relations. In this series of articles, I introduce the seven Member Relations Directors (namely: Sister and Related Societies; Membership Programs Development; AP, NA, LA, EAME Regions; Marketing and Industry Relations) and the Chair of the Women in Communications Engineering (WICE) Standing Committee. In each article, one by one they present their activities and plans. [ABSTRACT FROM PUBLISHER]

Remote spectral imaging of coastal areas can provide valuable information for their sustainable management and conservation of their biodiversity. Unfortunately, such areas are very sensitive to changes due to human activity, natural phenomenon, introduction of non-native species, and climate change. Thus, the main objective of this research is the implementation of a robust image processing methodology to produce accurate bathymetry maps in shallow coastal waters using high-resolution multispectral WorldView-2/3 satellite imagery for the monitoring at the maximum spatial and spectral resolutions. Two different island ecosystems have been selected for the assessment, since they stand out for their richness in endemic species and they are more vulnerable to climate change: Cabrera National Park and Maspalomas Natural Protected area, located in the Balearic and Canary Islands, Spain, respectively. In addition, a third example to show the applicability of the mapping methodology to monitor the construction of a new port in Granadilla (Canary Islands) is presented. Contributions of this work focus on improving the preprocessing methodology and, mainly, on the proposal and assessment of new satellite-derived regression and machine learning bathymetric models, which have been validated and compared with respect to measured reference bathymetry. After a thorough analysis of nine techniques, using visual and quantitative statistical parameters, ensemble learning approaches have demonstrated excellent performance, even in challenging scenarios up to 35-m depth, with mean RMSE values around 2 m. [ABSTRACT FROM AUTHOR]

Contribution: This article explores the factors favoring the enrollment in engineering studies in Spain, analyzing gender differences. Background: Understanding the motivation of choosing engineering studies is very important in order to strengthen this choice in future promotions in Spain, considering that it is well below the average of the European Union at the present time. Research Questions: What are the main factors that influence students to choose engineering studies? Are there any noticeable differences between those affecting male and female students? Methodology: Data were collected from a survey completed by 624 students and an exploratory study was performed extracting five components. Independent sample $T$ -tests were used to determine significant differences between the answers of males and females. Findings: The factors found in the exploratory analysis were “Interest and development,” “Career advice and previous contact,” “Outcome expectations,” “Social influences” and “Not preferred option.” Significant differences between the answers given by males and females were also found. The outcome of this study is important for the development of new interventions aimed to increase interest, enrollment, and retention of engineering students, especially among females. [ABSTRACT FROM AUTHOR]

Controlled-source electromagnetic (CSEM) measurements are complementary data for magnetotelluric (MT) characterization although its methodology on land is not sufficiently developed and tested as in marine environments. Acquiring expertise in CSEM is crucial for surveys in places where MT cannot be performed due to high levels of cultural noise. To acquire that expertise, we perform CSEM experiments in the Vallès fault [Northeast (NE), Spain], where MT results have been satisfactory and allow us to verify the CSEM results. The Vallès basin is relevant for potential heat generation because of the presence of several geothermal anomalies and its nearby location in urban areas. In this article, we present the experimental setup for that region, a 2-D joint MT+CSEM inverse model, several 3-D CSEM simulations in the presence of metallic casing, and its comparison with real data measurements. We employ a parallel and high-order vector finite element algorithm to discretize the governing equations. By using an adapted meshing strategy, different scenarios are simulated to study the influence of the source position/direction and the conductivity model in a metallic casing presence. An excellent agreement between the simulated data and analytical/real field data demonstrates the feasibility of study metallic structures in realistic configurations. Our numerical results confirm that metallic casing strongly influences electromagnetic (EM) responses, making surface measurements more sensitive to resistivity variations near the metallic structure. It could be beneficial getting higher signal-to-noise ratios and sensitivity to deep targets. However, such a casing effect depends on the input model (e.g., conductivity contrasts, frequency, and geometry). [ABSTRACT FROM AUTHOR]

The 2021 Nations League Cup Final was a soccer/football match played between France and Spain. It was settled by a goal scored by a player who was in an offside position when a ball was passed toward him by his teammate, but was not penalized because in its trajectory, the ball scraped the studs of an opponent trying to intercept the ball. According to FIFA’s laws of the game “A player in an offside position receiving the ball from an opponent who deliberately plays the ball, $\ldots $ is not considered to have gained an advantage” and therefore has not caused an offside offense. The goal was allowed to stand, and France duly won the match, and the cup, with this the winning goal. [ABSTRACT FROM AUTHOR]

This article presents the Schumann resonance (SR) variations, obtained in the extreme low frequency (ELF) signal observatory of Sierra de Filabres belonging to the University of Almería Spain, in operation since 2011. This station has two large and sensitive orthogonal sensors operating between 1 and 100 Hz. A 24 bit low-noise, high-resolution system processes the signal. The Sierra de Filabres ELF station is operating to offer valuable information on SRs’ activity in this area. This system allows us to have a broader range of comparison patterns to study correlations with other phenomena. The information presented in this work deals with the diurnal and seasonal variations of the first six modes of the SRs in 2016 and 2017. The graphs have been obtained through Lorentzian functions. We explain the diurnal variation based on the position and distance to the most important lightning hotspots and demonstrate its relation with the first mode captured in our observatory. We introduce a new yearly evolution method based on the resonance frequency through the most representative lightning activity hours in one year. This article is supported by the comparison between our signals and the global thunderstorm center’s activity. [ABSTRACT FROM AUTHOR]

This article evaluates the effect of the double-bounce (DB) decorrelation term that appears in single-pass bistatic acquisitions, as in the TanDEM-X system, on the inversion of scene parameters by means of polarimetric SAR interferometry (PolInSAR). The retrieval of all scene parameters involved in the Random Volume over Ground (RVoG) model (i.e., ground topography, vegetation height, extinction, and ground-to-volume ratios) is affected by this term when the radar response from the ground is dominated by the DB. The estimation error in all these parameters is analyzed by means of simulations over a wide range of system configurations and scene variables for both agricultural crops and forest scenarios. Simulations demonstrate that the inclusion of the DB term, which complicates the inversion algorithm, is necessary for the angles of incidence shallower than 30° to achieve an estimation error below 10% in vegetation height and to avoid a significant underestimation in the ground-to-volume ratios. At steep incidences, this decorrelation term does not affect the estimation of vegetation height and ground-to-volume ratios. Regarding the extinction, this parameter is intrinsically not well estimated, since most retrieved values are close to the initial guesses employed for the optimization algorithm, regardless of the use or not of the DB decorrelation term. Finally, these findings are compared with the experimental results from the TanDEM-X data acquired over the rice fields in Spain for the available system parameters (baseline and incidence angle) of the acquired data set. [ABSTRACT FROM AUTHOR]

Together with the continuous development of passive microwave surface soil moisture (SSM) products from newly launched satellites, it is necessary to perform reliable validations to assess their accuracy. With this aim, a new “bottom-up” validation approach is proposed based on the synergistic use of in situ SSM measurements from the soil moisture measurement station network (REMEDHUS) of the University of Salamanca, Salamanca, Spain, and optical/thermal infrared observations over 18 cloud-free days from Landsat-8. An SSM estimation method using the boundary information from the land surface temperature and normalized difference vegetation index triangle space was developed for regional SSM mapping. The retrieved SSM reached a relatively good performance (mean $\text{R}^{2}$ and root-mean-squared error of 0.64 and 0.033 $\text{m}^{3}/\text{m}^{3}$ , respectively). Then, the regional SSM was aggregated into the grid-cell scale of the Advanced Microwave Scanning Radiometer 2 (AMSR2) L3 high-resolution (0.1° /10 km) soil moisture product to validate it both at network and grid-cell levels. At the network level, the derived regional SSM showed a good agreement with the averaged in situ measurements over the network ($R = 0.731$). However, at the grid-cell level, small variations were observed for the cells over the network between the estimates and the AMSR2 product, with negative biases (−0.044 to $-0.090~\text{m}^{3}/\text{m}^{3}$) and positive correlations ($R > 0.25$) for most cells. In addition, it is shown that the descending product has a slightly better performance than does the ascending one. The preliminary assessments suggested that the proposed method provides new insights into the validation of passive microwave soil moisture products, while avoiding the common issue related to the big disparity in spatial scales between satellite observation and in situ measurements. [ABSTRACT FROM AUTHOR]

Merit order of renewable generation has produced an increasing, relevant number of zero values in Spanish electricity spot prices since 2010, in contrast with the rest of markets which rarely present zero values. This letter shows that existing methodologies for normalizing the price distribution fail to yield a proper normalization. This letter proposes a new algorithm based on Nataf transformation which addresses this issue and ensures a correct normalization. Numerical results validate the proposed algorithm. [ABSTRACT FROM AUTHOR]