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Structural damage detection using an unmanned aerial vehicle-based 3D model and deep learning on a reinforced concrete arch bridge
Full text linkVisual inspection is a common method for detecting structural damage, but has limitations in terms of subjectivity, time, and access. This research proposes an innovative approach to identify cracks using a 3D model generated from photographs of an unmanned aerial vehicle (UAV) and the use of a convolutional neural network (CNN). These networks are effective in detecting complex patterns, improving the accuracy and efficiency of damage identification based on simple visual inspection. The case study is the old Villena Rey bridge in Lima, Peru. The methodology covers (i) the development of a 3D model of the bridge structure, (ii) the extraction of photographs of the model and its binary segmentation, (iii) the application of deep learning through the training and testing phase of a CNN to achieve crack detection in photographs, and (iv) damage location within the 3D model. An 88.4% accuracy was achieved in crack detection, identifying 18 damage points, of which 3 turned out to be false positives. Additionally, it was determined that the left pillar in the southern area of the bridge presented the highest concentration of damage, which underlines the effectiveness of the method used.Peer ReviewedPostprint (published version
Bistatic SAR imaging and precise orbit determination using geostationary telecommunication satellites
Full text link© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.SAR Satellite missions from Geostationary orbits (GEOSAR) would offer the short revisit times required in the observation of fast phenomena. Multiple baseline inteferometry based on receiving ground stations is a technique under study for precise orbit determination of GEO satellites, a requirement for SAR processing echo data in GEOSAR missions.
This interferometric technique can be complementary to GNSS based orbit determination which is degraded for high altitude
missions above the MEO GNSS constellations. A multichannel coherent receiver is presented with two complementary functions:
interferometric orbit determination and bistatic SAR imaging using present GEO telecommunication satellites transmissions. To
improve orbit determination large baselines are formed based on urban reflectors of opportunity. The obtained orbits are the basis
for Synthetic Aperture focusing of received echo data allowing to form images from the urban and natural areas surrounding
the inteferometer site. In return the images allow to select new reflectors of opportunity that can be used to increase the number
of baselines and further improve the orbits. The paper describes the developed system, the synergies between both orbit and
imaging functions and preliminary experimental results with interferometric and polarimetric applications.This work has been supported by the Spanish MCINN funds Unidad de Excelencia Maria de Maeztu MDM-2016-0600 and under projects TEC2017-85244-C2-2-P and PID2020-117303GB-C21/AEI/10.13039/501100011033, and by the Spanish Ministry of Science and Innovation under grant PRE2018-086003Peer ReviewedPostprint (published version
Estandarización de software del SOC MSSP en plataformas multicliente multiherramienta
No full textEste trabajo de fin de grado aborda la estandarización de soluciones de ciberseguridad en un entorno multicliente y multiherramienta. La estandarización permite una gestión centralizada y eficiente, reduciendo la complejidad operativa y los costes, mejorando la visibilidad y el control y, facilitando la incorporación de nuevas tecnologías y clientes. En este trabajo se implementa un método estandarizable en Python que sirve como responder de la web app de TheHive, permitiendo automatizar y gestionar respuestas a incidentes de seguridad de manera eficiente. Se exploran diversas tecnologías de ciberseguridad como SIEM, EDR, Firewall y SASE, así como herramientas internas como Python, Visual Studio Code, WinSCP, Putty, TheHive y Cortex. Este proyecto demuestra que la estandarización es una estrategia efectiva para optimizar procesos y garantizar una gestión más coherente de la seguridad.Aquest treball de fi de grau aborda l'estandardització de solucions de ciberseguretat en un entorn multiclient i multieina. L'estandardització permet una gestió centralitzada i eficient, reduint la complexitat operativa i els costos, millorant la visibilitat i el control i, facilitant la incorporació de noves tecnologies i clients. En aquest treball s'implementa un mètode estandarditzable en Python que serveix com a responder de l'aplicació web de TheHive, permetent automatitzar i gestionar respostes a incidents de seguretat de manera eficient. S'exploren diverses tecnologies de ciberseguretat com SIEM, EDR, Firewall i SASE, així com eines internes com Python, Visual Studio Code, WinSCP, Putty, TheHive i Cortex. Aquest projecte demostra que l'estandardització és una estratègia efectiva per optimitzar processos i garantir una gestió més coherent de la seguretat.This final degree project addresses the standardization of cybersecurity solutions in a multi-client and multi-tool environment. Standardization allows for centralized and efficient management, reducing operational complexity and costs, improving visibility and control and facilitating the incorporation of new technologies and clients. In this project, a standardizable method in Python is implemented, serving as a responder for TheHive web app, allowing for efficient automation and management of security incident responses. Various cybersecurity technologies such as SIEM, EDR, Firewall, and SASE are explored, as well as internal tools like Python, Visual Studio Code, WinSCP, Putty, TheHive, and Cortex. This project demonstrates that standardization is an effective strategy to optimize processes and ensure more coherent security management
Dynamic mode decomposition in thermal convection between rotating concentric spheres using data analysis tools
No full textTítol alternatiu emprat a la intranet docent de l'EPSEVG: "Dynamic mode decomposition in thermal convection between rotating concentric spheres using data analysis tools"Aquest estudi investiga la convecció tèrmica entre dues esferes concèntriques en rotació sota diferents valors del Nombre de Rayleigh mitjançant l’anàlisi de Descomposició de Modes Dinàmics (DMD).
L’objectiu del projecte és identificar els modes i freqüències dominants del sistema, proporcionant informació clau sobre el seu comportament complex. S’ha emprat un anàlisi DMD per a analitzar conjunts de dades de simulacions, revelant els patrons essencials i l’evolució dels mecanismes de transferència de calor a mesura que augmenta el Nombre de Rayleigh.
Els resultats demostren que valors del Nombre de Rayleigh més alts, condueixen a estructures de flux més complexes, passant de règims dominants per conducció a règims dominats per convecció, i introduint un comportament caòtic i més impredictible.
Una comparació amb la Descomposició Ortogonal Pròpia Espectral (SPOD) i treballs prèviament publicats, valida els resultats obtinguts amb DMD, destacant la seva eficàcia en la captura de dinàmiques temporals.
El treball termina destacant la importància de les tècniques de descomposició modal en l’anàlisi i comprensió de sistemes geofísics, i suggereix direccions per a futures investigacions, com l’augment de recursos computacionals i l’ampliació dels valors del Nombre de Rayleigh.Este estudio investiga la convección térmica entre dos esferas concéntricas en rotación bajo diferentes valores del Número de Rayleigh mediante el análisis de Descomposición de Modos Dinámicos (DMD).
El proyecto busca identificar los modos y frecuencias dominantes del sistema, proporcionando información clave sobre su comportamiento complejo. Se ha empleado un análisis DMD para analizar conjuntos de datos de simulaciones, revelando los patrones esenciales y la evolución de los mecanismos de transferencia de calor a medida que aumenta el número de Rayleigh.
Los resultados demuestran que valores del Número de Rayleigh más altos, conducen a estructuras de flujo más complejas, pasando de regímenes dominados por conducción a regímenes dominados por convección, e introduciendo un comportamiento caótico y más impredecible.
Una comparación con la Descomposición Ortogonal Propia Espectral (SPOD) y trabajos previamente publicados, valida los resultados obtenidos con DMD, destacando su eficacia en la captura de dinámicas temporales.
El trabajo termina destacando la importancia de las técnicas de descomposición modal en el análisis y comprensión de sistemas geofísicos, y sugiere direcciones para investigaciones futuras, como el aumento de recursos computacionales y la ampliación de los valores del Número de Rayleigh.This study investigates the thermal convection between two rotating concentric spheres under varying Rayleigh number values through the application of Dynamic Mode Decomposition (DMD) analysis.
The project aims to identify the dominant modes and frequencies of the system, providing insights into its complex behavior. DMD was used to analyze datasets from simulations, revealing key patterns and the evolution of heat transfer mechanisms as the Rayleigh number increased.
Results demonstrate that higher Rayleigh numbers lead to more complex flow structures, transitioning from conduction-dominated to convection-dominated regimes, and introducing a chaotic and more unpredictable behavior.
A comparison with Spectral Proper Orthogonal Decomposition (SPOD) and previously published works, validates the DMD results, emphasizing its effectiveness in capturing time-resolved dynamics.
The work, ends up highlighting the significance of modal decomposition techniques in the analysis and comprehension of geophysical systems, and suggests directions for future research, such as increasing computational resources and extending the Rayleigh number values
Sessió ordinària del Claustre Universitari, sessió del 10 de desembre de 2024
No full textEl Claustre Universitari de la UPC s'ha reunit el 10 de desembre en sessió ordinària
Privacy protection against user profiling through optimal data generalization
Full text linkPersonalized information systems are information-filtering systems that endeavor to tailor information-exchange functionality to the specific interests of their users. The ability of these systems to profile users based on their search queries at Google, disclosed locations at Twitter or rated movies at Netflix, is on the one hand what enables such intelligent functionality, but on the other, the source of serious privacy concerns. Leveraging on the principle of data minimization, we propose a data-generalization mechanism that aims to protect users’ privacy against non-fully trusted personalized information systems. In our approach, a user may like to disclose personal data to such systems when they feel comfortable. But when they do not, they may wish to replace specific and sensitive data with more general and thus less sensitive data, before sharing this information with the personalized system in question. Generalization therefore may protect user privacy to a certain extent, but clearly at the cost of some information loss. In this work, we model mathematically an optimized version of this mechanism and investigate theoretically some key properties of the privacy-utility trade-off posed by this mechanism. Experimental results on two real-world datasets demonstrate how our approach may contribute to privacy protection and show it can outperform state-of-the-art perturbation techniques like data forgery and suppression by providing higher utility for a same privacy level. On a practical level, the implications of our work are diverse in the field of personalized online services. We emphasize that our mechanism allows each user individually to take charge of their own privacy, without the need to go to third parties or share resources with other users. And on the other hand, it provides privacy designers/engineers with a new data-perturbative mechanism with which to evaluate their systems in the presence of data that is likely to be generalizable according to a certain hierarchy, highlighting spatial generalization, with practical application in popular location based services. Overall, a data-perturbation mechanism for privacy protection against user profiling, which is optimal, deterministic, and local, based on a untrusted model towards third parties.Javier Parra-Arnau is the recipient of a ‘‘Ramón y Cajal’’ fellowship
(ref. RYC2021-034256-I) funded by the Spanish Ministry of Science
and Innovation and the European Union – ‘‘NextGenerationEU’’/PRTR
(Plan de Recuperación, Transformación y Resiliencia). This work was
also supported by the Spanish Government under the project ‘‘Enhancing Communication Protocols with Machine Learning while Protecting
Sensitive Data (COMPROMISE)’’ PID2020-113795RB-C31, funded by
MCIN/AEI/10.13039/501100011033, Spain; the project ‘‘Anonymization technology for AI-based analytics of mobility data (MOBILYTICS)’’
(TED2021-129782B-I00), funded by MCIN/AEI/10.13039/50110001
1033 and the European Union ‘‘NextGenerationEU’’/PRTR; and funded
by the Generalitat de Catalunya, Spain, under AGAUR grant ‘‘2021 SGR
01413’’.Peer ReviewedPostprint (published version
Amazonian manatee critical habitat revealed by artificial intelligence-based passive acoustic techniques
Full text linkFor many species at risk, monitoring challenges related to low visual detectability and elusive behavior limit the use of traditional visual surveys to collect critical information, hindering the development of sound conservation strategies. Passive acoustics can cost-effectively acquire terrestrial and underwater long-term data. However, to extract valuable information from large datasets, automatic methods need to be developed, tested and applied. Combining passive acoustics with deep learning models, we developed a method to monitor the secretive Amazonian manatee over two consecutive flooded seasons in the Brazilian Amazon floodplains. Subsequently, we investigated the vocal behavior parameters based on vocalization frequencies and temporal characteristics in the context of habitat use. A Convolutional Neural Network model successfully detected Amazonian manatee vocalizations with a 0.98 average precision on training data. Similar classification performance in terms of precision (range: 0.83–1.00) and recall (range: 0.97–1.00) was achieved for each year. Using this model, we evaluated manatee acoustic presence over a total of 226¿days comprising recording periods in 2021 and 2022. Manatee vocalizations were consistently detected during both years, reaching 94% daily temporal occurrence in 2021, and up to 11¿h a day with detections during peak presence. Manatee calls were characterized by a high emphasized frequency and high repetition rate, being mostly produced in rapid sequences. This vocal behavior strongly indicates an exchange between females and their calves. Combining passive acoustic monitoring with deep learning models, and extending temporal monitoring and increasing species detectability, we demonstrated that the approach can be used to identify manatee core habitats according to seasonality. The combined method represents a reliable, cost-effective, scalable ecological monitoring technique that can be integrated into long-term, standardized survey protocols of aquatic species. It can considerably benefit the monitoring of inaccessible regions, such as the Amazonian freshwater systems, which are facing immediate threats from increased hydropower construction.This research is part of Project Providence (http://www.projectprovidence.org/) funded through the Sense of Silence Foundation (http://www.thesenseofsilencefoundation.com/) by the Gordon and Betty Moore Foundation. Additional funding was provided by the Rolex Institute and the Fondation Prince Albert II de Monaco.Peer ReviewedPostprint (published version