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The present study uses machine learning and time series spectral analysis to develop a novel technique to forecast the sunspot number (SN) in both hemispheres for the remainder of Solar Cycle 25 and Solar Cycle 26. This enables us to offer predictions for hemispheric SN until January 2038 (using the 13-month running average). For the Northern hemisphere, we find maximum peak values for Solar Cycles 25 and 26 of 58.5 in April 2023 and 51.5 in November 2033, respectively (root mean square error of 6.1). For the Southern hemisphere, the predicted maximum peak values for Solar Cycles 25 and 26 are 77.0 in September 2024 and 70.1 in November 2034, respectively (root mean square error of 6.8). In this sense, the results presented here predict a Southern hemisphere prevalence over the Northern hemisphere, in terms of SN, for Solar Cycles 25 and 26, thus continuing a trend that began around 1980, after the last period of Northern hemisphere prevalence (which, in turn, started around 1900). On the other hand, for both hemispheres, our findings predict lower maxima for Solar Cycles 25 and 26 than the preceding cycles. This fact implies that, when predicting the total SN as the sum of the two hemispheric forecasts, Solar Cycles 24 – 26 may be part of a centennial Gleissberg cycle's minimum, as was the case in the final years of the 19th century and the start of the 20th century (Solar Cycles 12, 13, and 14). [ABSTRACT FROM AUTHOR]

This study introduces a novel method for predicting the sunspot number ( S N ) of Solar Cycles 25 (the current cycle) and 26 using multivariate machine-learning techniques, the Sun's polar flux as a precursor parameter, and the fast Fourier transform to conduct a spectral analysis of the considered time series. Using the 13-month running average of the version 2 of the S N provided by the World Data Center—SILSO, we are thus able to present predictive results for the S N until January 2038, giving maximum peak values of 131.4 (in July 2024) and 121.2 (in September 2034) for Solar Cycles 25 and 26, respectively, with a root mean square error of 10.0. These predicted dates are similar to those estimated for the next two polar flux polarity reversals (April 2024 and August 2034). Furthermore, the values for the S N maxima of Solar Cycles 25 and 26 have also been forecasted based on the known correlation between the absolute value of the difference between the polar fluxes of both hemispheres at an S N minimum and the maximum S N of the subsequent cycle, obtaining similar values to those achieved with the previous method: 142.3 ± 34.2 and 126.9 ± 34.2 for Cycles 25 and 26, respectively. Our results suggest that Cycle 25 will have a maximum amplitude that lies below the average and Cycle 26 will reach an even lower peak. This suggests that Solar Cycles 24 (with a peak of 116.4), 25, and 26 would belong to a minimum of the centennial Gleissberg cycle, as was the case in the final years of the 19th and the early 20th centuries (Solar Cycles 12, 13, and 14). [ABSTRACT FROM AUTHOR]

This article introduces a uniform theory of diffraction–physical optics (UTD–PO) formulation for analyzing radiowave multiple diffraction emanating from trees and buildings in green urban areas, considering illumination from a low transmitter and assuming spherical-wave incidence. Based on Babinet's principle, this solution models buildings as rectangular sections and accounts for the influence of tree crowns (assuming these rise above the average rooftop height) by incorporating appropriate attenuation factors/phasors into the diffraction phenomena of buildings. The validation of the formulation is achieved through measurements made at the 39 GHz 6G mmWave frequency on a scale model of a green urban environment comprising bonsai trees and bricks. The main advantage of the proposed solution is that the calculations only include single diffractions due to recursion, circumventing the need to use higher-order diffraction terms in the diffraction coefficients, thus reducing the computation time and power. Our results may be beneficial for the design of mobile communication systems, including 6G networks, situated in green urban areas and with transmission source positioned lower than the surrounding infrastructure. [ABSTRACT FROM AUTHOR]

The main goal of this research was to design and study the best structure, location, and shape of acoustic diffusers to be fitted on the ceilings of multipurpose auditoriums. Their absorbing properties can enhance the acoustics when installed on high ceilings, and behind suspended reflecting panels, by mitigating or nullifying specular reflections that could overcome the panels and, thus, avoiding time delay gaps exceeding 30–40 ms compared with the direct sound. For this purpose, a typical medium-sized room, with inclined floors, a stage, and 20 rows of seats, was considered. The allocation and height of the considered diffusers were based on the Schroeder quadratic residue sequence, and they were modeled as rectangles, wedges, cylinders, and Y-shaped elements. A standardized speech source spectrum was analyzed for up to five different receiver locations. In this way, the attenuation parameter as a function of frequency was evaluated and compared between the candidate diffusers in order to identify the best absorber. The simulations were undertaken with a software tool previously validated by the authors called PARDOS, which incorporates an innovative formulation based on the uniform theory of diffraction (UTD) to analyze multiple diffractions and reflections of acoustic waves. The results show that the new Y-shaped diffusers proposed, tuned for the hearing frequency band from 250 Hz up to 10,000 Hz, attained the best acoustic performance in terms of absorption. [ABSTRACT FROM AUTHOR]

The fundamental objective of acoustic barriers is to preserve the inhabitants of nearby areas from the high noise generated by road traffic. It is possible to significantly improve the performance of conventional acoustic barriers by attaching small acoustic diffusers on their upper part (caps) that do not imply an appreciable height increase of the barrier, thereby adhering to any height regulation or restriction. This work deepens and yields findings in the study of the acoustic performance of barriers with diffusers of different shapes, number and arrangement through the calculation of their insertion losses (IL). In this research, a design of four Y-shaped diffusing elements arranged according to the well-known fractal pattern called Cantor set is presented and validated through two types of traffic noise sources ('Car' and 'Ambulance'), one listener and a wide frequency band up to 10 kHz. The results demonstrate that the proposed diffuser provides a significant increase in acoustic losses compared to the results obtained in previous works without raising the height of the barrier. To the best of the authors' knowledge, there are no diffuser structures like the one presented here that have been installed or even proposed/analysed. [ABSTRACT FROM AUTHOR]

There is an increasing need for innovative educational methods that can motivate and engage students in subjects that are often perceived as difficult or boring. One such approach is the UPCT-Bloopbusters educational project, developed by a group of professors at the Universidad Politécnica de Cartagena (UPCT), Spain, wherein concepts from the fields of physics and technology are presented and exemplified in the classroom through scenes from different movies in conjunction with experiments. The project was conducted on three subjects, one from each of the three bachelor of electrical engineering degree programs offered at the UPCT, namely Physics I, Applied Physics, and Optical Communications. This paper describes the methodology of the educational project and then presents and discusses the academic results of the students involved in terms of success and performance rates both before and after the application of the new methodology. Moreover, the results of a survey carried out on the students are presented. Finally, some of the exercises used in this methodology for the teaching and learning of science based on different movie scenes are provided as examples. The results of the project show that the students were receptive of the methodology and further indicated that it may lead to increased academic performance due to their enhanced understanding of physics and technology concepts. [ABSTRACT FROM AUTHOR]

Nonlinear acoustics offers a new range of acoustic applications that are currently being exploited. The parametric nonlinear effect—the occurrence of low frequencies with modulated high-frequency emission—is of particular interest. This work provides a systematic exposition of the theoretical framework on which the so-called parametric nonlinear effect is based. In relation to this behavior is an analytical discussion of how to solve the problem for two cases: (i) nonlinear behavior with modulation, and (ii) parametric emission of two monochromatic waves (bi-frequency). Subsequently, parametric emission experiments were carried out in air and water using the same transducer to compare the results with those obtained theoretically. In this sense, directivity and attenuation measurements are obtained. Conclusively, this research offers a proof of concept for underwater acoustic communications. It is characterized by the transmission of a binary sequence through Frequency Shift Keying (FSK) modulation, and the subsequent decoding of each received bit (either 1 or 0) utilizing advanced signal processing with the cross-correlation technique. This paper accentuates the significant potential of employing the parametric effect for specialized communication applications. [ABSTRACT FROM AUTHOR]

The knowledge of signal demodulation processes using superheterodyne receivers is of great importance in the field of telecommunications. Superheterodyne receivers receive the current focus of many scientists in a wide variety of applications. This topic is part of the syllabus of the Communication Theory course at the School of Telecommunications of the Polytechnic University of Cartagena, Spain. The authors found that the academic performance of the students had not been entirely satisfactory in recent years. This situation was aggravated during the COVID-19 lockdown. Students had to reinforce their knowledge independently at home, despite the support provided by teachers. To the best of the authors' knowledge, there is a noticeable lack of educational tools in this area; of those that are available, they exhibit a mismatch with the specific needs of this subject. This manuscript shows how the design of the educational software tool DOSHER, tailored to enhance the understanding of superheterodyne receivers, successfully alleviated the aforementioned drawbacks. DOSHER was designed, developed, and applied during the 2020–2021 academic year (during the COVID-19 lockdown). The results show that students were not only very satisfied with its use, but they also improved their marks. Analysis of students' academic performance in the year of DOSHER implementation showed an average improvement in their marks of between 9–12% compared with previous years. In 2021–2022, when DOSHER was fully operational from the start, the improvement in terms of pass rate (31%) at the first mid-term was significant compared to previous years (<20%). [ABSTRACT FROM AUTHOR]

The focus of this work is to determine at which threshold can the results for both plane and spherical wave incidence assumptions either converge or deviate when performing multiple diffraction attenuation calculations. The analysis has been carried out—for various millimeter-wave frequencies, inter-obstacle spacings, and angles of incidence—by employing a pair of two-dimensional (2D) hybrid formulations based on both the uniform theory of diffraction and physical optics (UTD-PO). This way, we seek to demonstrate under which circumstances each wave incidence assumption can be valid in environments that entail millimeter-wave bands. Based on this, we may ensure the minimum necessary distance from the transmitter to the first diffracting obstacle for the convergence of the spherical wave incidence solution onto that of the plane wave with a relative error below 0.1%. Our results demonstrate that for less than four diffracting elements, the minimum necessary distance engages in quasi-linear behavior under variations in both the angle of incidence and obstacle spacing. Notably, the considered frequencies (60–100 GHz) have almost no bearing on the results. Our findings will facilitate the simplified, more accurate and realistic planning of millimeter-wave radio communication systems, with multiple diffractions across various obstacles. [ABSTRACT FROM AUTHOR]

We present a new method for the calculation of the multiple acoustic diffraction caused by the presence of a wide barrier. Our solution decomposes the initial scenario into an equivalent sum of geometries that only consider knife-edges. Then, by applying Babinet's principle, the total acoustic field that reaches the receiving point, which can be located at an arbitrary position, can be calculated via the uniform theory of diffraction. This method is mathematically less complex and computationally more efficient than most existing techniques. The results are validated (with and without ground reflection) by the solid agreement obtained with other solutions that solve the problem by considering the wide barrier as such, with our proposed method yielding a lower computational time (except against semi-empirical formulations) and better accuracy when compared with measurements. The presented solution can be applied in urban environments where the impact of traffic noise on residential buildings located along roads or highways needs to be evaluated, as well as in scenarios in which the insertion loss caused by a rectangular obstacle, such as a noise barrier, is to be calculated. [ABSTRACT FROM AUTHOR]

Individuals with diabetes mellitus type 1 (DM1) tend to check their blood sugar levels multiple times daily and utilize this information to predict their future glycemic levels. Based on these predictions, patients decide on the best approach to regulate their glucose levels with considerations such as insulin dosage and other related factors. Nevertheless, modern developments in Internet of Things (IoT) technology and innovative biomedical sensors have enabled the constant gathering of glucose level data using continuous glucose monitoring (CGM) in addition to other biomedical signals. With the use of machine learning (ML) algorithms, glycemic level patterns can be modeled, enabling accurate forecasting of this variable. Constrained devices have limited computational power, making it challenging to run complex machine learning algorithms directly on these devices. However, by leveraging edge computing, using lightweight machine learning algorithms, and performing preprocessing and feature extraction, it is possible to run machine learning algorithms on constrained devices despite these limitations. In this paper we test the burdens of some constrained IoT devices, probing that it is feasible to locally predict glycemia using a smartphone, up to 45 min in advance and with acceptable accuracy using random forest. [ABSTRACT FROM AUTHOR]

This paper presents two uniform theories of diffraction–physical optics (UTD-PO) formulations to undertake analysis of radiowave multiple diffraction resulting from the presence of both buildings and trees in vegetated urban areas, with the assumption of spherical-wave incidence. The solutions presented consider buildings modeled as knife-edges and rectangular sections (the latter being more complex and realistic) and the effect of the tree canopy (the assumption is that this exceeds the height of the average rooftop) is taken into account by adding proper attenuation factors/phasors to building diffraction phenomena. The validation of these formulations has been undertaken by comparing with other methods and measurements performed at 39 GHz on a scaled-model of the environment under analysis, consisting of an array of bricks and bonsai trees. The chief advantage of the solutions put forward is that because of recursion, the calculations only include single diffractions. This avoids any requirement for higher-order diffraction terms in the diffraction coefficients, which means less computer time/power is demanded. The results of this work may be useful when planning future mobile communication systems, including 6G networks and beyond. [ABSTRACT FROM AUTHOR]

Type 1 Diabetes Mellitus (DM1) is a condition of the metabolism typified by persistent hyperglycemia as a result of insufficient pancreatic insulin synthesis. This requires patients to be aware of their blood glucose level oscillations every day to deduce a pattern and anticipate future glycemia, and hence, decide the amount of insulin that must be exogenously injected to maintain glycemia within the target range. This approach often suffers from a relatively high imprecision, which can be dangerous. Nevertheless, current developments in Information and Communication Technologies (ICT) and innovative sensors for biological signals that might enable a continuous, complete assessment of the patient's health provide a fresh viewpoint on treating DM1. With this, we observe that current biomonitoring devices and Continuous Glucose Monitoring (CGM) units can easily obtain data that allow us to know at all times the state of glycemia and other variables that influence its oscillations. A complete review has been made of the variables that influence glycemia in a T1DM patient and that can be measured by the above means. The communications systems necessary to transfer the information collected to a more powerful computational environment, which can adequately handle the amounts of data collected, have also been described. From this point, intelligent data analysis extracts knowledge from the data and allows predictions to be made in order to anticipate risk situations. With all of the above, it is necessary to build a holistic proposal that allows the complete and smart management of T1DM. This approach evaluates a potential shortage of such suggestions and the obstacles that future intelligent IoMT-DM1 management systems must surmount. Lastly, we provide an outline of a comprehensive IoMT-based proposal for DM1 management that aims to address the limits of prior studies while also using the disruptive technologies highlighted before. [ABSTRACT FROM AUTHOR]

This paper examines the propagation of radio waves in so-called urban street canyons through formulations based on Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD). As this type of environment comprises a street flanked by tall buildings more or less equally spaced on both sides (creating a canyon-like morphology), estimating the attenuation that radio signals may experience in these scenarios is crucial to the planning of urban device-to-device (D2D) wireless communication. In this sense, the results obtained through the analysis based on GO/UTD (in the horizontal plane containing the transmitter and receiver) are validated by a comparison with experimental measurements, showing good agreement. This work demonstrates how the use of GO/UTD-based formulations can contribute to a simpler and computationally more efficient planning of D2D mobile communication systems in which the considered propagation environment can be modeled as an urban street canyon comprising rectangular and equispaced buildings. [ABSTRACT FROM AUTHOR]

This work analyzes the impact of admission grade point average (AGPA) on academic results of electrical engineering university students throughout their undergraduate studies. The analysis was carried out on two bachelor engineering degree programs offered at the School of Telecommunication Engineering at the Universidad Politécnica de Cartagena, Spain: Telecommunication Systems Engineering and Telematics Engineering. Data from seven consecutive academic years were used to compute three indicators regarding the same cohort of students: exam attendance rate, success rate, and performance rate. The results show that although there exists a significant correlation between AGPA and student performance, it is truly relevant only in the first two academic courses (in this work, a course is assumed to be the compilation of all subjects in a year). In view of the results, a set of guidelines is proposed in order to soften the impact of AGPA on the progress of university students. [ABSTRACT FROM AUTHOR]

The study of solar activity holds special importance since the changes in our star's behavior affect both the Earth's atmosphere and the conditions of the interplanetary environment. They can interfere with air navigation, space flight, satellites, radar, high-frequency communications, and overhead power lines, and can even negatively influence human health. We present here a machine learning-based prediction of the evolution of the current sunspot cycle (solar cycle 25). First, we analyze the Fourier Transform of the total time series (from 1749 to 2022) to find periodicities with which to lag this series and then add attributes (predictors) to the forecasting models to obtain the most accurate result possible. Consequently, we build a trained model of the series considering different starting points (from 1749 to 1940, with 1 yr steps), applying Random Forests, Support Vector Machines, Gaussian Processes, and Linear Regression. We find that the model with the lowest error in the test phase (cycle 24) arises with Random Forest and with 1915 as the start year of the time series (yielding a Root Mean Squared Error of 9.59 sunspots). Finally, for cycle 25 this model predicts that the maximum number of sunspots (90) will occur in 2025 March. [ABSTRACT FROM AUTHOR]

Since the beginning of the 21st century, the fields of astronomy and astrophysics have experienced significant growth at observational and computational levels, leading to the acquisition of increasingly huge volumes of data. In order to process this vast quantity of information, artificial intelligence (AI) techniques are being combined with data mining to detect patterns with the aim of modeling, classifying or predicting the behavior of certain astronomical phenomena or objects. Parallel to the exponential development of the aforementioned techniques, the scientific output related to the application of AI and machine learning (ML) in astronomy and astrophysics has also experienced considerable growth in recent years. Therefore, the increasingly abundant articles make it difficult to monitor this field in terms of which research topics are the most prolific or novel, or which countries or authors are leading them. In this article, a text‐mining‐based scientometric analysis of scientific documents published over the last three decades on the application of AI and ML in the fields of astronomy and astrophysics is presented. The VOSviewer software and data from the Web of Science (WoS) are used to elucidate the evolution of publications in this research field, their distribution by country (including co‐authorship), the most relevant topics addressed, and the most cited elements and most significant co‐citations according to publication source and authorship. The obtained results demonstrate how application of AI/ML to the fields of astronomy/astrophysics represents an established and rapidly growing field of research that is crucial to obtaining scientific understanding of the universe. This article is categorized under:Algorithmic Development > Text MiningTechnologies > Machine LearningApplication Areas > Science and Technology [ABSTRACT FROM AUTHOR]

This work compares the academic performance and retention rates of women and men in electrical engineering studies. The analysis is carried out in two bachelor engineering degree programs offered in the School of Telecommunication Engineering, at the Universidad Politécnica de Cartagena, Spain: Telecommunication Systems Engineering and Telematics Engineering. Data from seven consecutive academic years have been used to compute three indicators regarding the same cohort of students: exam attendance rate, success rate, and performance rate. The results show that, in general, women obtain better academic performance rates than men in the first two academic courses while, from the third course on, there seems to be a trend toward uniformity in the academic results between female and male students. Furthermore, women generally present lower attrition rates than men, especially in the first year, and better graduation rates. Such facts could be explained by the higher motivation of female students when enrolling engineering programs—due to the adverse stereotyped context that they have to overcome—which lead to higher retention rates throughout the academic years as compared to their male counterparts. [ABSTRACT FROM AUTHOR]

Type 1 diabetes mellitus (DM1) is a metabolic disease derived from falls in pancreatic insulin production resulting in chronic hyperglycemia. DM1 subjects usually have to undertake a number of assessments of blood glucose levels every day, employing capillary glucometers for the monitoring of blood glucose dynamics. In recent years, advances in technology have allowed for the creation of revolutionary biosensors and continuous glucose monitoring (CGM) techniques. This has enabled the monitoring of a subject's blood glucose level in real time. On the other hand, few attempts have been made to apply machine learning techniques to predicting glycaemia levels, but dealing with a database containing such a high level of variables is problematic. In this sense, to the best of the authors' knowledge, the issues of proper feature selection (FS)—the stage before applying predictive algorithms—have not been subject to in-depth discussion and comparison in past research when it comes to forecasting glycaemia. Therefore, in order to assess how a proper FS stage could improve the accuracy of the glycaemia forecasted, this work has developed six FS techniques alongside four predictive algorithms, applying them to a full dataset of biomedical features related to glycaemia. These were harvested through a wide-ranging passive monitoring process involving 25 patients with DM1 in practical real-life scenarios. From the obtained results, we affirm that Random Forest (RF) as both predictive algorithm and FS strategy offers the best average performance (Root Median Square Error, RMSE = 18.54 mg/dL) throughout the 12 considered predictive horizons (up to 60 min in steps of 5 min), showing Support Vector Machines (SVM) to have the best accuracy as a forecasting algorithm when considering, in turn, the average of the six FS techniques applied (RMSE = 20.58 mg/dL). [ABSTRACT FROM AUTHOR]

Gender-Based Violence (GBV) is a serious problem that societies and governments must address using all applicable resources. This requires adequate planning in order to optimize both resources and budget, which demands a thorough understanding of the magnitude of the problem, as well as analysis of its past impact in order to infer future incidence. On the other hand, for years, the rise of Machine Learning techniques and Big Data has led different countries to collect information on both GBV and other general social variables that in one way or another can affect violence levels. In this work, in order to forecast GBV, firstly, a database of features related to more than a decade's worth of GBV is compiled and prepared from official sources available due to Spain's open access. Then, secondly, a methodology is proposed that involves testing different methods of features selection so that, with each of the subsets generated, four techniques of predictive algorithms are applied and compared. The tests conducted indicate that it is possible to predict the number of GBV complaints presented to a court at a predictive horizon of six months with an accuracy (Root Median Squared Error) of 0.1686 complaints to the courts per 10,000 inhabitants—throughout the whole Spanish territory—with a Multi-Objective Evolutionary Search Strategy for the selection of variables, and with Random Forest as the predictive algorithm. The proposed methodology has also been successfully applied to three specific Spanish territories of different populations (large, medium, and small), pointing to the presented method's possible use elsewhere in the world. [ABSTRACT FROM AUTHOR]

The primary function of noise barriers is to shield inhabitants of affected areas from excessive noise generated by road traffic. To enhance the performance of noise barriers while simultaneously adhering to height restrictions, the attachment of structures (caps) of different shapes to the tops of conventional screens can be considered. These caps can significantly impact the diffracted sound energy, thereby increasing the desired global acoustic losses. This work presents a comprehensive study of the acoustic performance of noise barriers with single and double attached caps of different shapes through a calculation of their insertion losses (IL). This study comprehensively addresses and compares different types, sizes, combinations, and numbers of noise barrier caps for different scenarios (including sloping and absorbent grounds) and sources ("car" and "ambulance") for an extended frequency band up to 10 kHz. To the best of the authors' knowledge, this is a range that has not previously been analyzed. A variety of different cap shapes were considered including cylinders, rectangles, trapezoids, and Y/T-shaped forms. To calculate the IL, an innovative and fast uniform theory of diffraction (UTD)-based method developed by the authors was applied in all simulations. The results showed that the Y-shaped single and double barrier caps were, in general, the most effective at increasing IL without raising the height of the barrier, thereby successfully managing the aesthetic impact. The results also showed how the consideration of sloping and absorbent floors could also contribute to improved noise abatement. [ABSTRACT FROM AUTHOR]

The metabolic disease Type 1 Diabetes Mellitus (DM1) is caused by a reduction in the production of pancreatic insulin, which causes chronic hyperglycemia. Patients with DM1 are required to perform multiple blood glucose measurements on a daily basis to monitor their blood glucose dynamics through the use of capillary glucometers. In more recent times, technological developments have led to the development of cutting-edge biosensors and Continuous Glucose Monitoring (CGM) systems that can monitor patients' blood glucose levels on a real-time basis. This offers medical providers access to glucose oscillations modeling interventions that can enhance DM1 treatment and management approaches through the use of novel disruptive technologies, such as Cloud Computing (CC), big data, Intelligent Data Analysis (IDA) and the Internet of Things (IoT). This work applies some advanced modeling techniques to a complete data set of glycemia-related biomedical features—obtained through an extensive, passive monitoring campaign undertaken with 25 DM1 patients under real-world conditions—in order to model glucose level dynamics through the proper identification of patterns. Hereby, four methods, which are run through CC due to the high volume of data collected, are applied and compared within an IoT context. The results show that Bayesian Regularized Neural Networks (BRNN) offer the best performance (0.83 R2) with a reduced Root Median Squared Error (RMSE) of 14.03 mg/dL. [ABSTRACT FROM AUTHOR]

Transitioning a Terrestrial Trunked Radio (TETRA) network to a Long-Term Evolution (LTE) network in public protection and disaster relief (PPDR) systems is a path to providing future services requiring high radio interface throughput and allowing broadband PPDR (BB-PPDR) radio communications. Users of TETRA networks are currently considering how to deploy a BB-PPDR network in the coming years. This study offers several radio planning considerations in TETRA to LTE migration for such networks. The conclusions are obtained from a case study in which both measurements and radioelectric coverage simulations were carried out for the real scenario of the Murcia Region, Spain, for both TETRA and LTE systems. The proposed considerations can help PPDR agencies efficiently estimate the cost of converting a TETRA network to an LTE network. Uniquely in this study, the total area is divided into geographical areas of interest that are defined as administrative divisions (region, municipal areas, etc.). The analysis was carried out using a radio planning tool based on a geographic information system and the measurements have been used to tune the propagation models. According to the real scenario considered, the number of sites needed in the LTE network—for a specific quality of service (90% for the whole region and 85% for municipal areas)—is a factor of 2.4 higher than for TETRA network. [ABSTRACT FROM AUTHOR]

Type 1 diabetes mellitus (DM1) is a growing disease, and a deep understanding of the patient is required to prescribe the most appropriate treatment, adjusted to the patient’s habits and characteristics. Before now, knowledge regarding each patient has been incomplete, discontinuous, and partial. However, the recent development of continuous glucose monitoring (CGM) and new biomedical sensors/gadgets, based on automatic continuous monitoring, offers a new perspective on DM1 management, since these innovative devices allow the collection of 24-hour biomedical data in addition to blood glucose levels. With this, it is possible to deeply characterize a diabetic person, offering a better understanding of his or her illness evolution, and, going further, develop new strategies to manage DM1. This new and global monitoring makes it possible to extend the “on-board” concept to other features. This well-known approach to the processing of variable “insulin” describes some inertias and aggregated/remaining effects. In this work, such analysis is carried out along with a thorough study of the significant variables to be taken into account/monitored—and how to arrange them—for a deep characterization of diabetic patients. Lastly, we present a case study evaluating the experience of the continuous and comprehensive monitoring of a diabetic patient, concluding that the huge potential of this new perspective could provide an acute insight into the patient’s status and extract the maximum amount of knowledge, thus improving the DM1 management system in order to be fully functional. [ABSTRACT FROM AUTHOR]

Type 1 Diabetes Mellitus (DM1) is a metabolic disease that is characterized by chronic hyperglycemia due to a lack of pancreatic insulin production. This forces patients to perform several blood glucose measurements per day—by means of capillary glucometers—in order to infer a trend and try to predict future values. In this way, a decision about the insulin dosage that has to be exogenously injected to maintain glycemia within the desirable levels is made. Unfortunately, this method usually suffers from relatively high imprecision. However, recent advances in information and communication technologies (ICT), along with novel biosensors that could provide a real-time comprehensive condition of the patient, offer a new perspective in DM1 management. In this sense, new disruptive technologies like Big Data, the Internet of Things (IoT), and Cloud Computing, as well as Machine Learning (ML) can play an important role in managing DM1. In this work, firstly, an analysis of previously published ICT-based methods for the management of diabetes continuous monitoring is carried out. In this way, an assessment of the possible lack of such proposals is presented, along with the challenges to be overcome in forthcoming smart DM1 management systems. Finally, an overview of a holistic ICT-based platform for DM1 management that try to solve the limitations of previous works, while at the same time, taking advantage of the abovementioned disruptive technologies is hereby proposed. [ABSTRACT FROM AUTHOR]

A comparison of plane against spherical-wave incidence consideration in multiple-cylinder diffraction analysis is performed, at several millimeter-wave frequencies, in order to clarify the margin in which both incidence results converge or differ. The mentioned comparison is carried out through a pair of two-dimensional (2D) hybrid uniform theory of diffraction-physical optics (UTD-PO) solutions (the plane-wave formulation for cylinders is firstly proposed in this work), and is intended to show the validity of each wave-incidence assumption in environments where millimeter or sub-millimeter-wave bands are being employed. In this sense, results can be used to achieve a more accurate and realistic planning of such radio communication systems when multiple-diffraction over rounded obstacles has to be considered (e.g. communication systems operating in stadiums). [ABSTRACT FROM AUTHOR]

A formulation based on the uniform theory of diffraction (UTD) for the analysis of the multiple-diffraction of a spherical sound wave caused by a series of wedges or knife-edges is hereby presented. The receiver location has to be considered at the same height as the preceding obstacles and at the same inter-obstacle distance from the last wedge. The solution, which is based on a UTD-physical optics formulation for radio-wave multiple-diffraction and has been validated through comparison with a geometrical theory of diffraction acoustic model, is computationally more efficient than other existing methods thanks to the fact that only single diffractions are involved in the calculations (high-order diffraction terms are not considered in the diffraction coefficients), thus allowing for the consideration of a great number of obstacles. In such a way, the proposed solution overcomes the limitations of previous works when multiple acoustic diffraction caused by an array of elements of equal height is to be analyzed. Therefore, the results can be applied in the study of sound propagation in scenarios where multiple-diffraction over a series of edges of equal height and periodical spacing has to be considered, such as the typical audience seating of a concert hall. [ABSTRACT FROM AUTHOR]

This work presents directional radio channel measurements in the W-band using a commercial versatile channel sounder based on a vector network analyzer (VNA), capable of measuring scattering parameters from 75 to 500 GHz with frequency converters. The commercial setup has been modified by increasing the distance for one of the converters using precision coaxial cables and avoiding the use of amplifiers. Firstly, initial distance-dependent single-input single-output (SISO) measurements of indoor radio channels are presented to assess the validity of the setup in the 75-110 GHz frequency band with highly directive horn antennas. Then, single-input multiple-output (SIMO) radio channels were measured at 94 GHz using one directional and one omnidirectional antenna mounted on two positioners. Initial channel characterization is presented comprising root mean square (rms) delay spread, rms angular spread, K-factor, and path loss in an indoor environment at 94 GHz. [ABSTRACT FROM AUTHOR]

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A study of a Multiple-Input Multiple-Output (MIMO) system in a street corner is presented in order to analyze the keyhole effect. First, MIMO channel matrices are calculated in this environment by using a ray launching model to theoretically analyze the problem. In this sense, results show that, in a Non-Line-of-Sight (NLoS) situation, capacity is close to the keyhole limit, since only diffracted rays are received. Moreover, measurements carried out in a similar environment are also presented, and results are compared with the theoretical results. The keyhole effect was difficult to measure in the real environment, since many other contributions were received. However, in the NLoS positions, and by analyzing only the diffracted contribution, a nearly keyhole capacity is found. [ABSTRACT FROM AUTHOR]

In this work, an efficient field estimation technique is developed. This technique uses a single simulation of a ray tracing tool, at one spatial point at one frequency, to compute the field in the vicinity of the simulated point throughout a complete frequency range. The developed technique is a two-step procedure. Firstly, it operates over the images and field contributions generated by the ray tracing tool at the simulated receiver point to obtain an appropriate set of field contributions for each new receiver point. Secondly, once the new set of images and contributions at one frequency is obtained, a very simple extrapolation procedure is applied to obtain the electric field throughout a frequency range. The whole technique is computationally very efficient and it is also accurate, as the measurements comparison shows. [ABSTRACT FROM AUTHOR]

This letter presents an extensive multidimensional analysis of line-of-sight (LOS) experimental data and simulations at 60 GHz over a 9-GHz bandwidth. Numerical versions of the measured multiple-input-multiple-output (MIMO) channel transfer functions were obtained with a ray-tracing engine that includes single-order diffuse scattering. The received power, RMS delay spread (DS), and maximum excess delay (MED) computed from both measured and simulated data indicate that diffuse scattering improves ray-tracing-based modeling. Moreover, the multipath components (MPCs) extracted from both sets of data using the high-resolution estimator RiMAX were statistically compared. The analysis of the results shows that even a raw description of the environment can be used to predict millimeter-wave (mmW) propagation with ray tracing. [ABSTRACT FROM AUTHOR]

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In this paper, a 4 × 4 indoor multiple-input multiple-output (MIMO) measurement campaign at a frequency of 2.45 GHz is presented. The main contribution of this work is the analysis of the impact of radio-wave polarization in MIMO systems operating at a typical indoor scenario through the calculation—from the measurements carried out-of a great deal of parameters such as the mean path loss, the cross polarization discrimination (XPD), and the RMS delay spread, which are all essential to estimate the performance of real MIMO systems. In this sense, some path loss models—which have been adjusted according to the measurements-are given, taking into account polarization, attenuation through walls, and the effect of T-junctions existing in the considered indoor scenario. Moreover, additional parameters such as the K-factor and statistical distribution, as well as spatial parameters, are discussed. [ABSTRACT FROM AUTHOR]

The current trend in vehicles is to integrate a wide number of antennae and sensors operating at a variety of frequencies for sensing and communications. The integration of these antennae and sensors in the vehicle platform is complex because of the way in which the antenna radiation patterns interact with the vehicle structure and other antennae/sensors. Consequently, there is a need to study the radiation pattern of each antenna or, alternatively, the currents induced on the surface of the vehicle to optimize the integration of multiple antennae. The novel concept of differential imaging represents one method by which it is possible to obtain the surface current distribution without introducing any perturbing probe. The aim of this study was to develop and confirm the assumptions that underpin differential imaging by means of full-wave electromagnetic simulation, thereby providing additional verification of the concept. The simulation environment and parameters were selected to replicate the conditions in which real measurements were taken in previous studies. The simulations were performed using Ansys HFSS simulation software. The results confirm that the approximations are valid, and the differential currents are representative of the induced surface currents generated by a monopole positioned on the top of a vehicle. [ABSTRACT FROM AUTHOR]

The next generation of connected and autonomous vehicles will be equipped with high numbers of antennas operating in a wide frequency range for communications and environment sensing. The study of 3D spatial angular responses and the radiation patterns modified by vehicular structure will allow for better integration of the associated communication and sensing antennas. The use of near-field monostatic focusing, applied with frequency-dimension scale translation and differential imaging, offers a novel imaging application. The objective of this paper is to theoretically and experimentally study the method of obtaining currents produced by an antenna radiating on top of a vehicular platform using differential imaging. The experimental part of the study focuses on measuring a scaled target using an imaging system operating in a terahertz band—from 220 to 330 GHz—that matches a 5G frequency band according to frequency-dimension scale translation. The results show that the induced currents are properly estimated using this methodology, and that the influence of the bandwidth is assessed. [ABSTRACT FROM AUTHOR]

Motor imagery (MI)-based brain-computer interface (BCI) systems detect electrical brain activity patterns through electroencephalogram (EEG) signals to forecast user intention while performing movement imagination tasks. As the microscopic details of individuals' brains are directly shaped by their rich experiences, musicians can develop certain neurological characteristics, such as improved brain plasticity, following extensive musical training. Specifically, the advanced bimanual motor coordination that pianists exhibit means that they may interact more effectively with BCI systems than their non-musically trained counterparts; this could lead to personalized BCI strategies according to the users' previously detected skills. This work assessed the performance of pianists as they interacted with an MI-based BCI system and compared it with that of a control group. The Common Spatial Patterns (CSP) and Linear Discriminant Analysis (LDA) machine learning algorithms were applied to the EEG signals for feature extraction and classification, respectively. The results revealed that the pianists achieved a higher level of BCI control by means of MI during the final trial (74.69%) compared to the control group (63.13%). The outcome indicates that musical training could enhance the performance of individuals using BCI systems. [ABSTRACT FROM AUTHOR]

This paper presents the design and features of frequency-selective wallpaper—based on periodic and symmetric metallic hexagons—intended to be attached to standard walls for filtering out 5 GHz signals (e.g., IEEE 802.11a systems) without blocking other selected radio communication services (e.g., cellular mobile communication signals). It analyzes the characteristics of the radio channel—as found within standard indoor environments—with both regular walls and walls with the proposed frequency-selective wallpaper, examined using a ray-launching program for single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems. This allows the harvesting of parameters, including channel capacity, power delay profile, and signal-to-interference ratio, for proper comparison between the two environments under study: with and without the presented wallpaper. The achieved results clearly show that the use of the proposed frequency-selective wallpaper in an indoor scenario reduces interference levels by an additional attenuation of up to 20 dB in comparison to an unpapered wall. Additionally, with MIMO systems, radio channel characteristics, such as capacity, are improved due to the increase in the magnitude of all singular values of the channel transfer matrix compared to the unpapered wall case, thereby leading to the existence of more relevant subchannels. [ABSTRACT FROM AUTHOR]

A uniform theory of diffraction (UTD)-based method for analysis of the multiple diffraction of acoustic waves when considering a series of symmetric obstacles with arbitrary modeling, height and spacing is hereby presented. The method, which makes use of graph theory, funicular polygons and Fresnel ellipsoids, proposes a novel approach by which only the relevant obstacles and paths of the scenario under study are considered, therefore simultaneously providing fast and accurate prediction of sound attenuation. The obstacles can be modeled either as knife edges, wedges, wide barriers or cylinders, with some other polygonal diffracting elements, such as doubly inclined, T- or Y-shaped barriers, also considered. In view of the obtained results, this method shows good agreement with previously published formulations and measurements whilst offering better computational efficiency, thus allowing for the consideration of a large number of obstacles. [ABSTRACT FROM AUTHOR]