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Two radiowave propagation models which calculate the multiple-building diffraction losses through the corresponding Uniform Theory of Diffraction-Physical Optics (UTD-PO) formulations are validated with measurements performed in different locations of an urban environment. The main advantage of such solutions is that, since they are recursive, the calculations are expressed in terms of single diffractions (high-order diffraction terms are not considered in the diffraction coefficients), thus showing better computational efficiency than other existing methods. Buildings are modeled as flat-topped obstacles and one formulation assumes plane-wave incidence over the obstacles while the other considers a spherical wave impinging over the array of rooftops. The locations in which the spherical-wave model should be used instead of the plane-wave method in order to obtain more realistic results are discussed. [ABSTRACT FROM AUTHOR]

Underwater insertion loss of a material is a key parameter for many applications where acoustic requirements exist. Typically, environmental noise control and mitigation or SONAR are disciplines commonly demanding the knowledge of insertion losses of the material used for such purposes. Materials selected for these applications usually have good structural properties but also are lightweight and have good corrosion behavior and specific acoustic performances (e.g. baffling, transparency). In this sense, glass-reinforced plastics, as well as carbon fiber materials, synthetic or natural rubbers, urethane compounds, etc. are, more and more, part of tailored underwater structures, pods, covers, or acoustic windows. In this work, the underwater acoustic insertion losses of monolithic and isotropic typical panels are theoretically calculated and properly validated via measurements for a wide range of frequencies (10–60 kHz) and angles of incidence (0–80°). The theoretical calculation is carried out through the model proposed by G. Roche and based on the Brekhovskikh formulation, which is implemented within an ad hoc software tool developed by the authors (Sailor). The measurements were performed by the Centro Tecnológico Naval y del Mar – Marine Technology Center (CTN) in a freshwater-calibrated pool/tank located in the town of Cartagena (Spain). The results reveal a solid agreement between the measurements and the simulations carried out with the Sailor software, therefore validating the model proposed by Roche and shedding new light on a field where, to the best of the authors' knowledge, previous investigations were scarce or lacking. [ABSTRACT FROM AUTHOR]

This work presents a wireless channel characterization based on an extensive campaign of massive multiple-input multiple-output (mMIMO) measurements conducted under line-of-sight (LOS) conditions. These measurements focus on the 94 GHz band (W band), and the results are compared to the same positions measured at 60 GHz. The values of the relative received power, root mean square (RMS) delay spread, maximum excess delay (MED), and coherence bandwidth in an indoor laboratory environment are analyzed. The results of this study can contribute to a better understanding of the propagation channel behavior in the 94 GHz band, and can be used to assess the potential of this band for the upcoming sixth-generation (6G) networks in laboratory environments. [ABSTRACT FROM AUTHOR]

Diabetes Mellitus (DM) represents a metabolic disorder characterized by consistently elevated blood glucose levels due to inadequate pancreatic insulin production. Type 1 DM (DM1) constitutes the insulin-dependent manifestation from disease onset. Effective DM1 management necessitates daily blood glucose monitoring, pattern recognition, and cognitive prediction of future glycemic levels to ascertain the requisite exogenous insulin dosage. Nevertheless, this methodology may prove imprecise and perilous. The advent of groundbreaking developments in information and communication technologies (ICT), encompassing Big Data, the Internet of Medical Things (IoMT), Cloud Computing, and Machine Learning algorithms (ML), has facilitated continuous DM1 management monitoring. This investigation concentrates on IoMT-based methodologies for the unbroken observation of DM1 management, thereby enabling comprehensive characterization of diabetic individuals. Integrating machine learning techniques with wearable technology may yield dependable models for forecasting short-term blood glucose concentrations. The objective of this research is to devise precise person-specific short-term prediction models, utilizing an array of features. To accomplish this, inventive modeling strategies were employed on an extensive dataset comprising glycaemia-related biological attributes gathered from a large-scale passive monitoring initiative involving 40 DM1 patients. The models produced via the Random Forest approach can predict glucose levels within a 30-minute horizon with an average error of 18.60 mg/dL for six-hour data, and 26.21 mg/dL for a 45-minute prediction horizon. These findings have also been corroborated with data from 10 Type 2 DM patients as a proof of concept, thereby demonstrating the potential of IoMT-based methodologies for continuous DM monitoring and management. The integration of innovative biological signal sensors and the application of transformative trends in ICT can offer a novel perspective on DM treatment, ensuring precise and secure glucose level management. [ABSTRACT FROM AUTHOR]

The possibility of estimating the multiple-diffraction attenuation caused by a rectangular obstacle, when illuminated from a low source (i.e., the transmitter height is smaller than the obstacle height), from the results obtained when considering the corresponding double knife-edge configuration is hereby analyzed, at millimeter-wave frequencies. The theoretical analysis shows that the rectangular obstacle propagation losses can be predicted by the addition of a proper offset to the double knife-edge case attenuation values. Numerical results are carried out, for both vertical and horizontal polarization, as a function of the angle of incidence, the distance between the transmitter and the obstacle, the width of the obstacle, and the distance between the obstacle and the receiver. [ABSTRACT FROM AUTHOR]

Frequency Modulated Continuous Wave (FMCW) radars are part of the new sensing devices installed in vehicles in order to explore the surroundings. Millimetric wave (mmW) frequency bands provide enough information to apply imaging algorithm. The Multifrequency Bifocusing (MFBF) imaging algorithm in the W-band using FMCW radar has a direct applicability in enhancing detection of concealed weapons, as proximity sensors to avoid collisions and pedestrian detection in vehicles. This paper assesses the feasibility of using the Intermediate Frequency (IF) signal provided by homodyne FMCW radar operating in 77 GHz as input to the mmW MFBF monostatic-bistatic algorithm from a theoretical point of view and by means of simulation. MFBF algorithm results using FMCW radar are compared with that obtained using FSCW, equivalent to the parameter S 21 obtained from a Vector Network Analyzer (VNA). [ABSTRACT FROM AUTHOR]