Politecnio die Bari - Catalogo di prodotti della Ricerca
Not a member yet
36616 research outputs found
Sort by
Design and experimental evaluation of unmanned aircraft systems communications
Get PDFLe reti 6G mirano a fornire una banda larga globale a bassissima latenza tramite reti non terrestri (NTN), che integrano droni, piattaforme ad alta quota e satelliti. Questo progetto introduce contributi per l'avanzamento delle capacità NTN, a partire dal Drone Control Layer (DCL), una soluzione middleware che consente un funzionamento efficiente di sciami di droni, dotata di interfacce per l'astrazione hardware, la comunicazione e la loro interconnettività. Inoltre, viene presentato IoD-Sim, un simulatore open source per la modellazione di ambienti NTN, tra cui le superfici riflettenti intelligenti (IRS) per una copertura ottimizzata. IoD-Sim consente una simulazione realistica dei protocolli di comunicazione e della mobilità dei droni in diversi scenari. Nell'Internet of Things (IoT), i droni estendono la durata della batteria del dispositivo IoT tramite Wireless Power Transfer (WPT), trasmettendo in modo efficiente i dati ai CubeSat, le cui simulazioni mostrano significativi guadagni nel trasferimento dei dati. Inoltre, la sicurezza e la protezione sono affrontate rispettivamente tramite Explainable AI (XAI), per la consapevolezza spaziale dei droni, e Counter-Unmanned Aircraft System (C-UAS), per il rilevamento non autorizzato dei droni mediante tecniche di fusione multisensore. Infine, un meccanismo di sicurezza a catena di servizi introduce autenticazione e autorizzazione personalizzati per salvaguardare il flusso di dati nei sistemi Terrestrial/NTN, integrati in un'architettura completa basata sul cloud orientata ai servizi. Questi contributi supportano lo sviluppo e l'implementazione di servizi di comunicazione integrati spazio-aria-terra resilienti, a vantaggio sia della ricerca che dell'industria.6G networks aim to deliver ultra-low-latency global broadband through Non-Terrestrial Networks (NTN), which integrate drones, high-altitude platforms, and satellites. This project introduces contributions for advancing NTN capabilities, starting with the Drone Control Layer (DCL), a middleware solution enabling efficient operation of mixed drone swarms, equipped with interfaces for hardware abstraction, communication, and drone interconnectivity. Furthermore, IoD-Sim is presented, an open-source simulator for modelling NTN environments, including Intelligent Reflecting Surfaces (IRS) for optimised coverage. IoD-Sim allows realistic simulation of communication protocols and drone mobility in diverse scenarios.
In the Internet of Things (IoT), drones extend IoT device battery life through Wireless Power Transfer (WPT), efficiently transmitting data to CubeSats, which simulations show significant gains in data transfer.
Additionally, safety and security are addressed via Explainable AI (XAI), for drone spatial awareness, and Counter-Unmanned Aircraft System (C-UAS), for unauthorised drone detection using multi-sensor fusion techniques. Finally, a secure service chain model introduces custom authentication and authorisation to safeguard data flow in Terrestrial/NTN systems, integrated in a comprehensive cloud-based service oriented architecture.
These contributions support the development and deployment of resilient space-air-ground integrated communication services, benefiting both research and industry
Investigation of the Radiation Response of a Dual-Stage Optical Amplifier
No full textWe studied the radiation response of a dual-stage optical amplifier (DSOA) in terms of gain degradation, noise figure, and radiation-induced attenuation (RIA) related to the corresponding active fiber, through an experimental-simulative approach. The DSOA consists of two fiber amplifiers connected in cascade: an erbium-doped fiber amplifier (EDFA) followed by an erbium–ytterbium-doped fiber amplifier (EYDFA). The erbium-doped fiber (EDF) and the erbium–ytterbium-doped fiber (EYDF) were irradiated during different runs at a dose rate of 0.28 Gy(SiO2)/s, reaching a total ionizing dose (TID) of 3 kGy(SiO2). Preirradiation DSOA gain is estimated at ~53 dB, with a degradation limited to ~13.8 dB for a cumulative dose of 3 kGy(SiO2) under X-rays. The noise figure, before irradiation, is ~6.3 dB and reaches ~10.7 dB at 3 kGy(SiO2). Good agreement was obtained between the experimental results and the simulation model for the evolution of gain degradation as a function of deposited dose (in different configurations). The proposed approach validates the simulation code even for applications in harsh environments, including cascaded optical amplifiers
Hierarchical multi-time-scale energy management system for secure and economic operation of islanded microgrids with GFM/GFL control
No full textIn-Flight Pose and Electromagnetic Experimental Characterization of UAV-Mounted Metasurfaces for Next-Generation Indoor Wireless Systems
No full textAs well known, the integration of Unmanned Aerial Vehicles (UAVs) and Intelligent Reflecting Surfaces (IRS) can enhance the reliability, coverage, robustness, and efficiency of next-generation wireless and mobile networks. Nevertheless, the performance of UAV-mounted Passive Metasurfaces (PMs), referred to as Aerial PMs (APMs), is significantly influenced by system configurations, electromagnetic signal propagation, UAV mobility, and wobbling. While most state-of-the-art studies rely on analytical models and simulations to assess these factors, this work presents an experimental investigation of an APM in a realistic operating environment. To this end, we developed an advanced experimental testbed that combines a precision tracking system with real-time electromagnetic measurements, enabling a detailed characterization of the metasurface response in an indoor scenario. Additionally, we compared the feasibility of APMs against a static setup where the metasurface is mounted on a fixed structure. Experimental results demonstrate that APMs can effectively maintain signal quality and spectral efficiency. However, they also reveal the impact of positioning, orientation, and in-flight stability on overall system performance. Our observations provide interesting insights into optimizing Aerial IRS-assisted networks, contributing to the design of more robust solutions for the Beyond 5th and 6th Generation networks
Deep learning strategies for semantic segmentation of pediatric brain tumors in multiparametric MRI
Get PDFAutomated segmentation of pediatric brain tumors (PBTs) can support precise diagnosis and treatment monitoring, but it is still poorly investigated in literature. This study proposes two different Deep Learning approaches for semantic segmentation of tumor regions in PBTs from MRI scans. Two pipelines were developed for segmenting enhanced tumor (ET), tumor core (TC), and whole tumor (WT) in pediatric gliomas from the BraTS-PEDs 2024 dataset. First, a pre-trained SegResNet model was retrained with a transfer learning approach and tested on the pediatric cohort. Then, two novel multi-encoder architectures leveraging the attention mechanism were designed and trained from scratch. To enhance the performance on ET regions, an ensemble paradigm and post-processing techniques were implemented. Overall, the 3-encoder model achieved the best performance in terms of Dice Score on TC and WT when trained with Dice Loss and on ET when trained with Generalized Dice Focal Loss. SegResNet showed higher recall on TC and WT, and higher precision on ET. After post-processing, we reached Dice Scores of 0.843, 0.869, 0.757 with the pre-trained model and 0.852, 0.876, 0.764 with the ensemble model for TC, WT and ET, respectively. Both strategies yielded state-of-the-art performances, although the ensemble demonstrated significantly superior results. Segmentation of the ET region was improved after post-processing, which increased test metrics while maintaining the integrity of the data
Test of lepton flavor universality in semileptonic Bc+ meson decays in proton-proton collisions at s=13 TeV
No full textA measurement of the ratio of branching fractions (Formula presented) in the (Formula presented), (Formula presented) decay channel is presented. This measurement uses a sample of proton-proton collision data collected at a center-of-mass energy of (Formula presented) by the CMS experiment in 2018, corresponding to an integrated luminosity of (Formula presented). The measured ratio, (Formula presented), agrees with the value of (Formula presented) predicted by the standard model, which assumes lepton flavor universality. By testing lepton flavor universality, this measurement is a probe of new physics using (Formula presented) mesons, which are currently only produced at the LHC
A Multi-criteria Optimization Framework for the Residential Hot Water Network Emphasizing on the Role of Control Strategy
No full textCutting-edge technologies and optimization frameworks for energy efficiency enhancement of the entire domestic hot water (DHW) chain are crucial to fulfill the ambitious goals of the future building regulations. In this context, the present study establishes a multi-objective optimization framework for the DHW network in a typical residential building, in which the hot water is supplied by a PV-BESS driven air source heat pump system relying on the thermal energy storage (TES) to decouple energy production and demand. Emphasizing on the role of in-building control strategies and user behavior, the optimization algorithm employs the response surface methodology (RSM) with central composite design (CCD). It seeks to simultaneously minimize the total energy use for DHW production and total heat loss from the DHW network, while maximizing the temperature of delivered hot water to users as well as the TES mean temperature. To examine interactions in components of the DHW network, dynamic simulations are carried out by developing a TRNSYS model coupled to a MATLAB code. The latter generates the hourly DHW consumption profiles using Gaussian distribution. It is shown that the developed optimization framework strikes a balance between conflictive design factors to meet the targets of multi-criteria optimization. The variable TES set-point is found to be the most influential factor in terms of providing hot water at a higher temperature to users. Furthermore, adjusting the activation time (and flow rate) of recirculating loop and the TES charging time slots in accordance with the user behavior (draw-off) and peak consumption timespans demonstrate a significant impact on minimizing either the total energy use or thermal loss
Creazione di una piattaforma digitale per la gestione del rischio da frana della rete autostradale
No full textSome observations regarding the stationary Buckley–Leverett equation
No full textThe basic hyperbolic–elliptic black-oil model describes oil–water displacement in a porous
medium. Given its mathematical complexity, there is a need for particular simple solutions
for validation of numerical methods. We present a class of stationary solutions, which are easy
to compute, and in many cases are given by explicit formulae. These solutions are constructed
by a nonlinear coupling of two linear equations, an elliptic pressure equation and a hyperbolic
saturation equation
Study and Characterization of Silicon Nitride Optical Waveguide Coupling with a Quartz Tuning Fork for the Development of Integrated Sensing Platforms
No full textHighlights: What are the main findings? We successfully coupled a silicon nitride waveguide with a custom-designed, low-frequency, and T-shaped QTF, enabling both Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) and Light-Induced Thermoelastic Spectroscopy (LITES) techniques for sensing. We achieved comparable signal-to-noise ratios with QEPAS and LITES when detecting 1.6% water vapor concentration, with performance limited by the output power illuminating the QTF. What is the implication of the main finding? Demonstrated the feasibility of integrating photonic components with piezoelectric resonators for portable gas-sensing applications. Identified on-chip laser-waveguide integration as a key route to compact sensing platforms. This work demonstrates an ultra-compact optical gas-sensing system, consisting of a pigtailed laser diode emitting at 1392.5 nm for water vapor (H2O) detection, a silicon nitride (Si3N4) optical waveguide to guide the laser light, and a custom-designed, low-frequency, and T-shaped Quartz Tuning Fork (QTF) as the sensitive element. The system employs both Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) and Light-Induced Thermoelastic Spectroscopy (LITES) techniques for trace gas sensing. A 3.8 mm-wide, S-shaped waveguide path was designed to prevent scattered laser light from directly illuminating the QTF. Both QEPAS and LITES demonstrated comparably low signal-to-noise ratios (SNRs), ranging from 1.6 to 3.2 for a 1.6% indoor H2O concentration, primarily owing to the reduced optical power (~300 μW) delivered to the QTF excitation point. These results demonstrate the feasibility of integrating photonic devices and piezoelectric components into portable gas-sensing systems for challenging environments