Generating an Iris-based Seed for Key-pairs in a Blockchain Platform

is a critical concern in cybersecurity, and the challenge of combining security with ease of use remains a pressing issue. Biometric authentication methods, particularly iris recognition, leverage unique physical characteristics to confirm identity, presenting an effective solution to enhance security over traditional password systems. However, the management of sensitive biometric data requires privacy measures to protect user information from potential misuse. This work proposes a novel Blockchain-based system that utilizes biometric data, specifically iris scans, as a seed for generating cryptographic key-pairs. By employing feature extraction and hashing techniques, the system ensures that sensitive biometric information is neither stored centrally nor accessible in its original form, thereby preserving user anonymity and privacy. The architecture is designed to distribute fragmented biometric data across multiple nodes in the Blockchain, enhancing scalability and security. The system's functionality is validated through extensive testing scenarios that demonstrate its reliability and robustness in various operational conditions. This research highlights the potential of combining Blockchain technology with biometric authentication to create secure and privacy-preserving identity management solutions, paving the way for applications in sectors such as finance, healthcare, and secure voting systems

Advanced embedded systems for autonomous robots control

In recent years, Autonomous Underwater Vehicles (AUVs) and Remotely Operated Underwater Vehicles (ROUVs) have become essential for various underwater missions, including environmental monitoring, offshore resource exploration, structural inspection, and rescue operations. A primary challenge in these missions is precise underwater navigation, particularly during structure inspections, where acoustic and optical systems offer complementary benefits. These tasks require building a local 3D map of the object using inertial systems, a process complicated by the fact that global navigation methods like LBL (Long Base Line) or USBL (Ultra-Short Base Line) are often impractical due to acoustic signal transmission limitations from surface beacons. While optical systems deliver detailed object information, they are hindered by issues like stereo vision distortions, lighting variability, and noise from suspended particles. Conversely, Forward Looking Sonar (FLS) provides robustness against environmental noise but operates at lower resolution and in polar coordinates, complicating data alignment with optical data devices like stereo camera. At the first part of our research we developed a nonlinear model of the ROUV in Computer-Aided Design (CAD) application and identified essential parameters, such as hydrostatic and hydrodynamic coefficients, through Computational Fluid Dynamics (CFD) simulations. These findings enabled accurate modeling of dynamic behaviors, including Coriolis effects and damping forces, forming the basis of the vehicle’s control equations. Additionally, a fractional-order PI controller was designed for yaw control, derived from a 6 DoF nonlinear model of the ROUV. The integration of Robot Operating System (ROS) and the Gazebo simulator allowed testing of control algorithms and sensor interactions within a digital twin environment, which included an Inertial Measurement Unit (IMU), FLS, Doppler Velocity Log (DVL) and stereo camera. This setup facilitated a smooth transition of navigation, computer vision, and path-planning functionalities from simulation to real-world deployment. Based on the designed nonlinear model of the ROUV and the developed control algorithm, we integrated a multimodal inertial-visual mapping and navigation system. This system enabled us to analyze the impact of the vehicle’s movement on the accuracy and stability of the visual-inertial system in a dynamically changing environment. Mapping, navigation, and control of the underwater vehicle equipped with a visual-inertial system that merges multimodal data from FLS, DVL, IMU, and a stereo camera devices through unsupervised deep-learning detector and descriptor algorithm is a core study of this research. Our research focuses on the geometric and computational integration of optical and sonar images. Given that a classical computer vision and supervised deep-learning feature matching algorithms is inadequate for opti-acoustic data fusion, we introduce an unsupervised feature matching approach tailored to sonar and optical datasets. This novel method enhances motion estimation by utilizing a hybrid direct and indirect matching strategy together with opti-acoustic epipolar constrains, where sonar data refines the depth of optical visual features. Both Sonar-to-Optical and Optical-to-Sonar mappings are employed to improve feature matching reliability under varying lighting and turbidity conditions. In our research, we introduced opti-acoustic image processing, including a calibration approach for each device and both devices the sonar and stereo camera, along with imaging enhancements to improve data fusion quality. To further enhance degraded optical images, we implemented a method combining stereo calibration in air and further data improving via physically guided underwater image enhancement framework based on synthetic and real images integration. By integrating unsupervised deep learning algorithm we was able to map sonar features onto optical images, enhancing image depth estimation while preserving key details. Testing across various scene geometries showed substantial improvements in visual odometry accuracy, which is crucial for effective navigation and inspection in challenging underwater conditions. Lastly, this research presents a robust framework for simulating underwater missions by combining CFD-based dynamics modeling, control algorithms, and sensor fusion techniques with optical and acoustic data. This comprehensive platform addresses underwater navigation and 3D mapping complexities, providing a unified system for testing and optimizing ROUV operations in diverse environments

Interactive mixed reality widgets for precise dexterity of tool manipulation to enhance surgical procedures in Industry 4.0 realm

Le procedure mediche complesse, in particolare quelle che coinvolgono interventi chirurgici, richiedono una precisione eccezionale nella manipolazione degli strumenti spaziali a 6DOF (Sei Gradi di Libertà), dove anche errori minimi possono causare danni irreversibili o risultati indesiderati. In questo contesto, l’allineamento preciso degli strumenti è cruciale, sia nelle chirurgie minimamente invasive che in procedure delicate come l'implantologia dentale. La tecnologia della Realtà Mista (MR) è emersa come uno strumento promettente per affrontare queste sfide, fornendo ai chirurghi una guida spazialmente accurata in tempo reale attraverso risorse visive conosciute come widget. Questi widget MR hanno il potenziale di supportare i chirurghi sovrapponendo informazioni utili direttamente sull'ambiente fisico, permettendo loro di eseguire compiti complessi con maggiore precisione. Tuttavia, nonostante i progressi nella tecnologia MR, gli approcci attuali rimangono prevalentemente statici o quasi statici, portando a errori persistenti a causa della mancanza di soluzioni adattive e dinamiche. Inoltre, l'assenza di linee guida standardizzate per la progettazione dei widget e la scarsa enfasi sulle considerazioni relative all'interfaccia utente (UI) nei sistemi MR esacerbano i problemi di usabilità, aumentando il carico cognitivo e fisico per i chirurghi e, in ultima analisi, compromettendo le prestazioni e i risultati. Questa tesi affronta queste sfide attraverso un'indagine sistematica che impiega metodologie sperimentali, comprese indagini con chirurghi e esperti del settore, per valutare e ottimizzare soluzioni innovative basate sulla MR. Una revisione completa della letteratura evidenzia significative lacune nei sistemi MR esistenti, come la progettazione inadeguata dei widget, l'usabilità subottimale, l'alto carico cognitivo e la limitata adattabilità nei contesti chirurgici in tempo reale, in particolare in odontoiatria. Un contributo chiave di questo lavoro è il miglioramento della comprensione del design dell'interfaccia utente centrato sull'utente per i sistemi di guida precisione strumento-obiettivo. Questa ricerca sottolinea l'importanza di affrontare sfide persistenti come il disordine visivo, l'occlusione e l'inclusività, assicurandosi che i widget soddisfino le diverse esigenze degli utenti, inclusi quelli con disabilità visive o capacità cognitive variabili. Sfruttando queste intuizioni, questa tesi introduce widget interattivi che integrano principi di percezione cognitiva, in particolare quelli derivati dalla teoria della Gestalt. Applicando principi della Gestalt come la prossimità, la continuità e l'organizzazione figura-sfondo, la ricerca si concentra sull'ottimizzazione del design visivo e sull'incorporazione di meccanismi di feedback sugli errori in tempo reale che rispondano alle azioni dell'utente. Il risultato è un set di widget interattivi che migliorano significativamente la precisione posizionale e angolare degli strumenti, gestendo efficacemente il carico cognitivo e il tempo di completamento dei compiti. I risultati dimostrano che i widget proposti superano i design tradizionali e statici in termini di precisione, efficienza e usabilità. Questi widget migliorano l'accuratezza nella manipolazione degli strumenti, semplificano i processi cognitivi coinvolti nelle procedure ad alto rischio, riducono i tempi di completamento dei compiti e migliorano la preferenza dell'utente. Inoltre, la natura modulare e adattabile di questi design si estende oltre le applicazioni mediche, offrendo soluzioni preziose per settori che richiedono alta precisione e sicurezza, come la produzione, la manutenzione e l'assemblaggio. Inoltre, questa ricerca presenta un framework di valutazione flessibile e open-source per la progettazione dei widget MR, promuovendo metodologie di test standardizzate e favorendo una maggiore collaborazione all'interno della comunità scientifica. Questo framework facilita lo sviluppo e la valutazione coerente dei sistemi MR, garantendo affidabilità e applicabilità trasversale ai vari settori. Guardando al futuro, questa ricerca esplora diverse direzioni per migliorare la progettazione dei widget MR, tra cui l'integrazione di sistemi di feedback tattili e uditivi per aumentare la fedeltà dell'interazione, lo sviluppo di interfacce utente adattive e personalizzate su misura per le esigenze individuali degli utenti e l'istituzione di linee guida progettuali standardizzate per incoraggiare l'innovazione e la coerenza tra i vari settori. L'obiettivo è aprire la strada a risultati più sicuri, efficienti e precisi nelle procedure e nei sistemi assistiti dalla MR, fornendo una base per i continui progressi negli strumenti di precisione basati sulla MR.Complex medical procedures, particularly those involving surgery, demand exceptional precision in spatial 6DOF (Six Degrees of Freedom) tool manipulation, where even minor errors can result in irreversible damage or undesirable outcomes. In this context, precise tool alignment is crucial, whether in minimally invasive surgeries or delicate procedures such as dental implantology. Mixed Reality (MR) technology has emerged as a promising tool for addressing these challenges by providing surgeons with real-time, spatially accurate guidance through visual assets known as widgets. These MR widgets have the potential to support surgeons by superimposing helpful information directly onto the physical environment, enabling them to perform complex tasks with higher precision. However, despite the advancements in MR technology, current approaches remain predominantly static or quasi-static, leading to persistent errors due to a lack of adaptive and dynamic solutions. Additionally, the absence of standardized guidelines for widget design and the underemphasis of user interface (UI) considerations in MR systems exacerbate usability issues, leading to increased cognitive and physical task loads for surgeons and ultimately detracting from performance and outcomes. This thesis addresses these challenges through a systematic investigation that employs experimental methodologies, including user studies with surgeons and domain experts, to evaluate and optimize innovative MR-based solutions. A comprehensive literature review reveals significant gaps in existing MR systems, such as inadequate widget design, suboptimal usability, high cognitive task demands, and limited adaptability in real-time surgical contexts, particularly in dentistry. A key contribution of this work is advancing the understanding of user-centered UI design for precision tool-to-target guidance systems. This research highlights the importance of addressing persistent challenges such as visual clutter, occlusion, and inclusivity, ensuring that widgets cater to diverse user needs, including those with visual impairments or varying cognitive capabilities. Building on these insights, this thesis introduces interactive widgets that integrate principles of cognitive perception, particularly those derived from Gestalt theory. By applying Gestalt principles such as proximity, continuity, and figure-ground organization, the research focuses on optimizing visual design and incorporating real-time error feedback mechanisms that respond to user actions. The result is a set of interactive widgets that significantly enhance the positional and angular precision of the tools while managing cognitive load and task completion time effectively. The findings demonstrate that the proposed widgets outperform traditional, static designs in terms of precision, efficiency, and usability. These widgets improve tool manipulation accuracy, streamline cognitive processes involved in high-stakes procedures, reduce task completion times, and enhance user preference. Moreover, these designs’ modular and adaptable nature extends beyond medical applications, offering valuable solutions for industries requiring high precision and safety, such as manufacturing, maintenance, and assembly. Furthermore, this research presents a flexible, open-source evaluation framework for MR widget design, promoting standardized testing methodologies and fostering greater collaboration within the scientific community. This framework facilitates consistent development and assessment of MR systems, ensuring reliability and cross-domain applicability. Looking to the future, this research explores several directions for enhancing MR widget design, including integrating haptic and auditory feedback systems to increase interaction fidelity, developing adaptive and personalized user interfaces tailored to individual user needs, and establishing standardized design guidelines to encourage innovation and consistency across industries. The aim is to pave the way for safer, more efficient, and precise outcomes in MRassisted procedures and systems, providing a foundation for continued advancements in MR-based precision tools

Forme innovate in terra stampata per il progetto urbano e il benessere outdoor

L’obiettivo della presente ricerca consiste nell’indagare le relazioni che intercorrono tra la tecnologia di manifattura additiva, alla scala dell’edificio, e la forma architettonica espressa dal sistema produttivo oltre ai materiali coinvolti nel processo e la funzione assunta dal manufatto. Il lavoro nella prima parte tratta dettagliatamente l’evoluzione delle tecniche utilizzate per le costruzioni in terra cruda. Questo excursus storico mira a validare il metodo additivo del Material Extrusion come nuova frontiera tecnica nel progetto e nella costruzione dell’architettura in terra cruda attraverso l’analisi di opere realizzate. La tesi prosegue prendendo in considerazione le metodologie progettuali e processuali necessarie per questa categoria di progetti affrontando criticamante il ruolo dell’architetto nell’era della progettazione computazionale e dei processi produttivi automatizzati nel settore edile. I risultati della ricerca si sostanziano in un modello che raccoglie alcuni criteri compositivi per consentire di operare nella progettazioe di shelter urbani prodotti attraverso tecnologia additiva con l’uso di materiali naturali in contesti di spazio pubblico in area mediterranea. Infine, in linea allo sviluppo di analoghe ricerche scientifiche internazionali, è stato realizzato un dimostratore architettonico a scala reale, avvalendosi delle attrezzature che il Politecnico di Bari offre nei suoi laboratori. In questo contesto, il processo di definizione formale, le tecnologie di realizzazione e i materiali impiegati collaborano sinergicamente per migliorare le condizioni termo-igrometriche dell’ambiente contribuendo, allo stesso tempo, al benessere di chi ne fruisce.The aim of the following research is to investigate the relationships between the Additive Manufacturing technology, at the scale of the building and: the architectural shape expressed by the production system; the materials involved in the process; the function taken by the product. In the first part, the research gives a detailed analysis of the evolution in the techniques used for constructions made of raw earth. The historical excursus aims to validate the additive method of Material Extrusion as a new technical frontier in the design and construction made of raw earth architecture through the analysis of existing projects. The thesis then moves on considering the design and process methodologies required for similar projects, analysing the role of the architect in the era of computational design and automated production processes in the construction industry. The results of the research lead to a model that brings together a set of compositional criteria for the design of urban shelters produced through additive technology and the use of natural materials in contexts such as the public space of Mediterranean cities. Lastly, in line with similar internWational scientific research, a full-scale architectural demonstrator was realised, using the equipment that the Polytechnic of Bari provides in its laboratories. In this context, the form-finding process, the construction technologies and the materials used, work together synergistically to improve the thermo-hygrometric conditions of the environment while contributing to the well-being of those who use it

An ML-based framework for predicting prestressing force reduction in reinforced concrete box-girder bridges with unbonded tendons

The paper presents a machine learning (ML) based framework to predict the prestressing force reduction in prestressed reinforced concrete (PSC) box-girder bridges with unbonded tendons. In the field of road network safety, the reliable assessment of some bridge typologies, such as PSC box-girder bridges, depends on different aspects, among which the inaccessibility of internal unbonded tendons, the difficulty in measuring the effective prestressing force reduction over time, the design of an efficient structural health monitoring (SHM) system. To address the above issues, the proposed approach exploits the results of experimental tests on a scaled PSC box-girder to validate a nonlinear modelling strategy and, in turn, to generate a sample dataset for training different ML algorithms. To ensure generalizability of the proposed ML model, the variability of several parameters, including geometrical and mechanical properties, was accounted for. The obtained results, evaluated in terms of statistical metrics and through an eXplainability approach, revealed that the proposed surrogate model is able to predict the prestressing force reduction for this bridge typology, knowing the current prestressing force, the elastic modulus of the concrete, and the strain variation in specific cross-sections of the structure. The application of the framework on a scaled PSC box-girder experimentally tested, demonstrated its suitability for: i) estimating the prestressing force reduction without employing periodic and expensive onsite tests; and ii) providing the best strategy for employing a sensor-based SHM system

Designing and Optimizing a 2.4 GHz Complementary Metal–Oxide-Semiconductor Class-E Power Amplifier Combining Standard and High-Voltage Metal–Oxide-Semiconductor Field-Effect Transistors

The advent of CMOS power amplifiers has enabled compact and cost-effective solutions for RF applications. Among the available options, switching amplifiers are the most competitive due to their superior efficiency. In this paper, we present the design of a fully integrated 130 nm CMOS class-E RF power amplifier optimized for 2.4 GHz ISM band operations that is compliant with the Bluetooth Low Energy (BLE) standard. The amplifier is based on a cascode configuration with charging acceleration capacitance and a combination of standard and high-voltage (HV) MOSFETs, ensuring optimal performance while maintaining device reliability. To identify the best configuration for the proposed circuit, we first provide an overview of basic class-E amplifier operations and critically review optimization techniques proposed in the scientific literature. This review is complemented by a numerical analysis of the potential advantages of using a combined standard-HV MOSFET structure. Post-layout simulations with parasitic parameter extraction demonstrated that the amplifier achieves 40.85% Power Added Efficiency and 20.52 dBm output power

Enhancing Motor Function and Quality of Life Combining Advanced Robotics and Biomechatronics in an Adult with Dystonic Spastic Tetraparesis: A Case Report

This case report explores the innovative integration of robotic and biomechatronic technologies, including the Motore and Ultra+ devices and neuro-suits, in a 10-session rehabilitation program for a young adult with dystonic spastic tetraparesis. Notable improvements were observed in upper limb motor function, coordination, and quality of life as measured by an increase of 18 pints on the Fugl-Meyer scale and a 25% improvement in the Bartle Index. Range of motion measurements showed consistent improvements, with task execution times improving by 10 s. These findings suggest the potential of combining wearable, robotic, and biomechatronic systems to enhance neurorehabilitation. Further refinement of these technologies might support clinicians in maximizing their integration in therapeutics, despite technical issues like synchronization issues that must be overcome

Local Generalized Nash Equilibria with Nonconvex Coupling Constraints

We address a class of Nash games with nonconvex coupling constraints for which we define a novel notion of local equilibrium, here named local generalized Nash equilibrium (LGNE). Our first technical contribution is to show the stability in the game theoretic sense of these equilibria on a specific local subset of the original feasible set. Remarkably, we show that the proposed notion of local equilibrium can be equivalently formulated as the solution of a quasi-variational inequality with equal Lagrange multipliers. Next, under the additional proximal smoothness assumption of the coupled feasible set, we define conditions for the existence and local uniqueness of a LGNE. To compute such an equilibrium, we propose two discrete-time dynamics, or fixed-point iterations implemented in a centralized fashion. Our third technical contribution is to prove convergence under (strongly) monotone assumptions on the pseudo- gradient mapping of the game and proximal smoothness of the coupled feasible set. Finally, we apply our theoretical results to a noncooperative version of the optimal power flow control problem