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1. Study of Long-term Spectral Evolution and X-Ray and γ-Ray Correlation of Blazars Seen by HAWC

Author

R. Alfaro, C. Alvarez, A. Andrés, J.C. Arteaga-Velázquez, D. Avila Rojas, H.A. Ayala Solares, R. Babu, E. Belmont-Moreno, A. Bernal, K.S. Caballero-Mora, T. Capistrán, A. Carramiñana, F. Carreón, S. Casanova, U. Cotti, J. Cotzomi, S. Coutiño de León, E. De la Fuente, D. Depaoli, N. Di Lalla, R. Diaz Hernandez, B.L. Dingus, M.A. DuVernois, M. Durocher, J.C. Díaz-Vélez, K. Engel, C. Espinoza, K.L. Fan, N. Fraija, S. Fraija, J.A. García-González, F. Garfias, A. Gonzalez Muñoz, M.M. González, J.A. Goodman, S. Groetsch, J.P. Harding, S. Hernández-Cadena, I. Herzog, D. Huang, F. Hueyotl-Zahuantitla, A. Iriarte, V. Joshi, S. Kaufmann, D. Kieda, A. Lara, W.H. Lee, J. Lee, H. León Vargas, J.T. Linnemann, A.L. Longinotti, G. Luis-Raya, K. Malone, O. Martinez, I. Martinez-Castellanos, J. Martínez-Castro, J.A. Matthews, P. Miranda-Romagnoli, J.A. Montes, E. Moreno, M. Mostafá, A. Nayerhoda, L. Nellen, M.U. Nisa, R. Noriega-Papaqui, N. Omodei, M. Osorio, Y. Pérez Araujo, E.G. Pérez-Pérez, C.D. Rho, D. Rosa-González, E. Ruiz-Velasco, H. Salazar, D. Salazar-Gallegos, A. Sandoval, M. Schneider, J. Serna-Franco, A.J. Smith, Y. Son, R.W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Ureña-Mena, E. Varela, L. Villaseñor, X. Wang, I.J. Watson, K. Whitaker, E. Willox, S. Yun-Cárcamo, H. Zhou, C. de León, HAWC collaboration, Abraham D. Falcone, and Fredric Hancock

Subjects
Active galactic nuclei, High energy astrophysics, Blazars, Gamma-ray astronomy, Gamma-ray detectors, Gamma-ray observatories, Astrophysics, QB460-466
Abstract

The HAWC Observatory collected 6 yr of extensive data, providing an ideal platform for long-term monitoring of blazars in the very high energy (VHE) band, without bias toward specific flux states. HAWC continuously monitors blazar activity at TeV energies, focusing on sources with a redshift of z ≤ 0.3, based on the Third Fermi-LAT Catalog of High-Energy sources. We specifically focused our analysis on Mrk 421 and Mrk 501, as they are the brightest blazars observed by the HAWC Observatory. With a data set of 2143 days, this work significantly extends the monitoring previously published, which was based on 511 days of observation. By utilizing HAWC data for the VHE γ -ray emission in the 300 GeV–100 TeV energy range, in conjunction with Swift-XRT data for the 0.3–10 keV X-ray emission, we aim to explore potential correlations between these two bands. For Mrk 501, we found evidence of a long-term correlation. Additionally, we identified a period in the light curve where the flux was very low for more than 2 yr. On the other hand, our analysis of Mrk 421 measured a strong linear correlation for quasi-simultaneous observations collected by HAWC and Swift-XRT. This result is consistent with a linear dependence and a multiple-zone synchrotron self-Compton model to explain the X-ray and γ -ray emission. Finally, as suggested by previous findings, we confirm a harder-when-brighter behavior in the spectral evolution of the flux properties for Mrk 421. These findings contribute to the understanding of blazar emissions and their underlying mechanisms.

Published
2025
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2. Enhancing healthcare infrastructure resilience through agent-based simulation methods

Author

Carramiñana, David, Bernardos, Ana M., Besada, Juan A., and Casar, José R.

Subjects
Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Systems and Control
Abstract

Critical infrastructures face demanding challenges due to natural and human-generated threats, such as pandemics, workforce shortages or cyber-attacks, which might severely compromise service quality. To improve system resilience, decision-makers would need intelligent tools for quick and efficient resource allocation. This article explores an agent-based simulation model that intends to capture a part of the complexity of critical infrastructure systems, particularly considering the interdependencies of healthcare systems with information and telecommunication systems. Such a model enables to implement a simulation-based optimization approach in which the exposure of critical systems to risks is evaluated, while comparing the mitigation effects of multiple tactical and strategical decision alternatives to enhance their resilience. The proposed model is designed to be parameterizable, to enable adapting it to risk scenarios with different severity, and it facilitates the compilation of relevant performance indicators enabling monitoring at both agent level and system level. To validate the agent-based model, a literature-supported methodology has been used to perform cross-validation, sensitivity analysis and test the usefulness of the proposed model through a use case. The use case analyzes the impact of a concurrent pandemic and a cyber-attack on a hospital and compares different resiliency-enhancing countermeasures using contingency tables. Overall, the use case illustrates the feasibility and versatility of the proposed approach to enhance resiliency.

Published
2025
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3. A Performance Analysis of You Only Look Once Models for Deployment on Constrained Computational Edge Devices in Drone Applications

Author

Rey, Lucas, Bernardos, Ana M., Dobrzycki, Andrzej D., Carramiñana, David, Bergesio, Luca, Besada, Juan A., and Casar, José Ramón

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, I.2.10, C.3, C.1.3
Abstract

Advancements in embedded systems and Artificial Intelligence (AI) have enhanced the capabilities of Unmanned Aircraft Vehicles (UAVs) in computer vision. However, the integration of AI techniques o-nboard drones is constrained by their processing capabilities. In this sense, this study evaluates the deployment of object detection models (YOLOv8n and YOLOv8s) on both resource-constrained edge devices and cloud environments. The objective is to carry out a comparative performance analysis using a representative real-time UAV image processing pipeline. Specifically, the NVIDIA Jetson Orin Nano, Orin NX, and Raspberry Pi 5 (RPI5) devices have been tested to measure their detection accuracy, inference speed, and energy consumption, and the effects of post-training quantization (PTQ). The results show that YOLOv8n surpasses YOLOv8s in its inference speed, achieving 52 FPS on the Jetson Orin NX and 65 fps with INT8 quantization. Conversely, the RPI5 failed to satisfy the real-time processing needs in spite of its suitability for low-energy consumption applications. An analysis of both the cloud-based and edge-based end-to-end processing times showed that increased communication latencies hindered real-time applications, revealing trade-offs between edge (low latency) and cloud processing (quick processing). Overall, these findings contribute to providing recommendations and optimization strategies for the deployment of AI models on UAVs., Comment: This manuscript consists of 24 pages, 7 figures, and 7 tables

Published
2025
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4. Study of long-term spectral evolution and X-ray and Gamma-ray correlation of blazars seen by HAWC

Author

Alfaro, R., Alvarez, C., Andrés, A., Arteaga-Velázquez, J. C., Rojas, D. Avila, Solares, H. A. Ayala, Babu, R., Belmont-Moreno, E., Bernal, A., Caballero-Mora, K. S., Capistrán, T., Carramiñana, A., Carreón, F., Casanova, S., Cotti, U., Cotzomi, J., de León, S. Coutiño, De la Fuente, E., Depaoli, D., Di Lalla, N., Hernandez, R. Diaz, Dingus, B. L., DuVernois, M. A., Durocher, M., Díaz-Vélez, J. C., Engel, K., Espinoza, C., Fan, K. L., Fraija, N., Fraija, S., García-González, J. A., Garfias, F., Muñoz, A. Gonzalez, González, M. M., Goodman, J. A., Groetsch, S., Harding, J. P., Hernández-Cadena, S., Herzog, I., Huang, D., Hueyotl-Zahuantitla, F., Iriarte, A., Joshi, V., Kaufmann, S., Kieda, D., Lara, A., Lee, W. H., Lee, J., Vargas, H. León, Linnemann, J. T., Longinotti, A. L., Luis-Raya, G., Malone, K., Martinez, O., Martinez-Castellanos, I., Martínez-Castro, J., Matthews, J. A., Miranda-Romagnoli, P., Montes, J. A., Moreno, E., Mostafá, M., Nayerhoda, A., Nellen, L., Nisa, M. U., Noriega-Papaqui, R., Omodei, N., Osorio, M., Araujo, Y. Pérez, Pérez-Pérez, E. G., Rho, C. D., Rosa-González, D., Ruiz-Velasco, E., Salazar, H., Salazar-Gallegos, D., Sandoval, A., Schneider, M., Serna-Franco, J., Smith, A. J., Son, Y., Springer, R. W., Tibolla, O., Tollefson, K., Torres, I., Torres-Escobedo, R., Turner, R., Ureña-Mena, F., Varela, E., Villaseñor, L., Wang, X., Watson, I. J., Whitaker, K., Willox, E., Yun-Cárcamo, S., Zhou, H., de León, C., Falcone, Abraham D., and Hancock, Fredric

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The HAWC Observatory collected 6 years of extensive data, providing an ideal platform for long-term monitoring of blazars in the Very High Energy (VHE) band, without bias towards specific flux states. HAWC continuously monitors blazar activity at TeV energies, focusing on sources with a redshift of {z \lt 0.3}, based on the Third Fermi-LAT Catalog of High-Energy sources. We specifically focused our analysis on Mrk 421 and Mrk 501, as they are the brightest blazars observed by the HAWC Observatory. With a dataset of 2143 days, this work significantly extends the monitoring previously published, which was based on 511 days of observation. By utilizing HAWC data for the VHE {\gamma}-ray emission in the 300 GeV to 100 TeV energy range, in conjunction with Swift-XRT data for the 0.3 to 10 keV X-ray emission, we aim to explore potential correlations between these two bands. For Mrk 501, we found evidence of a long-term correlation. Additionally, we identified a period in the light curve where the flux was very low for more than two years. On the other hand, our analysis of Mrk 421 measured a strong linear correlation for quasi-simultaneous observations collected by HAWC and Swift-XRT. This result is consistent with a linear dependence and a multiple-zone synchrotron self-Compton model to explain the X-ray and the {\gamma}-ray emission. Finally, as suggested by previous findings, we confirm a harder-when-brighter behavior in the spectral evolution of the flux properties for Mrk 421. These findings contribute to the understanding of blazar emissions and their underlying mechanisms.

Published
2025

5. Study of the IC 443 region with the HAWC observatory

Author

Alfaro, R., Alvarez, C., Araya, M., Arteaga-Velázquez, J. C., Rojas, D. Avila, Solares, H. A. Ayala, Babu, R., Bernal, A., Caballero-Mora, K. S., Capistran, T., Carramiñana, A., Casanova, S., Cotti, U., Cotzomi, J., de León, S. Coutiño, De la Fuente, E., Depaoli, D., Desiati, P., Di Lalla, N., Hernandez, R. Diaz, Dingus, B. L., DuVernois, M. A., Díaz-Vélez, J. C., Ergin, T., Espinoza, C., Fang, K., Fraija, N., Fraija, S., García-González, J. A., Goksu, H., González-Cervera, J. A., González, M. M., Goodman, J. A., Groetsch, S., Harding, J. P., Hernández-Cadena, S., Herzog, I., Hinton, J., Huang, D., Hueyotl-Zahuantitla, F., Hüntemeyer, P., Kaufmann, S., Lara, A., Lee, J., Vargas, H. León, Linnemann, J. T., Longinotti, A. L., Luis-Raya, G., Malone, K., Martinez, O., Martínez-Castro, J., Matthews, J. A., Miranda-Romagnoli, P., Montes, J. A., Morales-Soto, J. A., Moreno, E., Mostafá, M., Najafi, M., Nellen, L., Nisa, M. U., Noriega-Papaqui, R., Olivera-Nieto, L., Omodei, N., Osorio, M., Ponce, E., Araujo, Y. Pérez, Pérez-Pérez, E. G., Rho, C. D., Rosa-González, D., Roth, M., Ruiz-Velasco, E., Salazar, H., Sandoval, A., Schneider, M., Schwefer, G., Serna-Franco, J., Smith, A. J., Son, Y., Springer, R. W., Tibolla, O., Tollefson, K., Torres, I., Torres-Escobedo, R., Turner, R., Wang, X., Wang, Z., Watson, I. J., Wu, H., Yu, S., Yun-Cárcamo, S., Zhou, H., and de León, C.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Context. Supernova remnants are one potential source class considered a PeVatron (i.e. capable of accelerating cosmic rays above PeV energies). The shock fronts produced after the explosion of the supernova are ideal regions for particle acceleration. IC 443 is a supernova remnant that has been studied extensively at different wavelengths. We study this region using very-high-energy gamma-ray data. Aims. We explore the region of IC 443 using 2966 days of gamma-ray data from the HAWC observatory. We study the emission of this supernova remnant and search for signatures that would show acceleration of (hadronic) cosmic rays at the PeV range. Methods. We use the maximum likelihood estimation and a likelihood ratio test to perform a multi-source fitting search. We find the best-fit morphology and spectrum of the IC 443 region above $\sim$300 GeV that best describes the HAWC data. Results. We observe a point source located at ($\alpha$=94.42$^{\circ}$, $\delta$=22.35$^{\circ}$) that we associate with IC 443. The measured spectrum is a simple power law with an index of -3.14$\pm$0.18, which is consistent with previous TeV observations. We also find a new extended component in the region whose emission is described by a simple power law with an index of -2.49$\pm$0.08 and which we call HAWC J0615+2213. Conclusions. Although we cannot confirm that IC 443 is a hadronic PeVatron, we do not find any sign that the spectrum has a cut off at tens of TeV energies, with the spectrum extending to $\sim$30 TeV. Furthermore, we find a new extended source in the region. While we show evidence that this new source might be a new TeV halo, we defer a detailed analysis of this new source to another publication.

Published
2025

6. Application of Deep Reinforcement Learning to UAV Swarming for Ground Surveillance

Author

Arranz, Raúl, Carramiñana, David, de Miguel, Gonzalo, Besada, Juan A., and Bernardos, Ana M.

Subjects
Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract

This paper summarizes in depth the state of the art of aerial swarms, covering both classical and new reinforcement-learning-based approaches for their management. Then, it proposes a hybrid AI system, integrating deep reinforcement learning in a multi-agent centralized swarm architecture. The proposed system is tailored to perform surveillance of a specific area, searching and tracking ground targets, for security and law enforcement applications. The swarm is governed by a central swarm controller responsible for distributing different search and tracking tasks among the cooperating UAVs. Each UAV agent is then controlled by a collection of cooperative sub-agents, whose behaviors have been trained using different deep reinforcement learning models, tailored for the different task types proposed by the swarm controller. More specifically, proximal policy optimization (PPO) algorithms were used to train the agents' behavior. In addition, several metrics to assess the performance of the swarm in this application were defined. The results obtained through simulation show that our system searches the operation area effectively, acquires the targets in a reasonable time, and is capable of tracking them continuously and consistently.

Published
2025
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7. Towards resilient cities: A hybrid simulation framework for risk mitigation through data driven decision making

Author

Carraminana, David, Bernardos, Ana M., Besada, Juan A., and Casar, Jose R.

Subjects
Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Systems and Control
Abstract

Providing a comprehensive view of the city operation and offering useful metrics for decision making is a well known challenge for urban risk analysis systems. Existing systems are, in many cases, generalizations of previous domain specific tools and or methodologies that may not cover all urban interdependencies and makes it difficult to have homogeneous indicators. In order to overcome this limitation while seeking for effective support to decision makers, this article introduces a novel hybrid simulation framework for risk mitigation. The framework is built on a proposed city concept that considers urban space as a Complex Adaptive System composed by interconnected Critical Infrastructures. In this concept, a Social System, which models daily patterns and social interactions of the citizens in the Urban Landscape, drives the CIs demand to configure the full city picture. The frameworks hybrid design integrates agent based and network based modeling by breaking down city agents into system dependent subagents, to enable both inter and intra system interaction simulation, respectively. A layered structure of indicators at different aggregation levels is also developed, to ensure that decisions are not only data driven but also explainable. Therefore, the proposed simulation framework can serve as a DSS tool that allows the quantitative analysis of the impact of threats at different levels. First, system level metrics can be used to get a broad view on the city resilience. Then, agent level metrics back those figures and provide better explainability. On implementation, the proposed framework enables component reusability (for eased coding), simulation federation (enabling the integration of existing system oriented simulators), discrete simulation in accelerated time (for rapid scenario simulation) and decision oriented visualization (for informed outputs)., Comment: 24 pages

Published
2025
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8. Hybrid Artificial Intelligence Strategies for Drone Navigation

Author

San-Segundo, Rubén, Angulo, Lucía, Gil-Martín, Manuel, Carramiñana, David, and Bernardos, Ana M.

Subjects
Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract

Objective: This paper describes the development of hybrid artificial intelligence strategies for drone navigation. Methods: The navigation module combines a deep learning model with a rule-based engine depending on the agent state. The deep learning model has been trained using reinforcement learning. The rule-based engine uses expert knowledge to deal with specific situations. The navigation module incorporates several strategies to explain the drone decision based on its observation space, and different mechanisms for including human decisions in the navigation process. Finally, this paper proposes an evaluation methodology based on defining several scenarios and analyzing the performance of the different strategies according to metrics adapted to each scenario. Results: Two main navigation problems have been studied. For the first scenario (reaching known targets), it has been possible to obtain a 90% task completion rate, reducing significantly the number of collisions thanks to the rule-based engine. For the second scenario, it has been possible to reduce 20% of the time required to locate all the targets using the reinforcement learning model. Conclusions: Reinforcement learning is a very good strategy to learn policies for drone navigation, but in critical situations, it is necessary to complement it with a rule-based module to increase task success rate.

Published
2025
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13. High Positive End-expiratory Pressure (PEEP) with Recruitment Maneuvers versus Low PEEP during General Anesthesia for Surgery: A Bayesian Individual Patient Data Meta-analysis of Three Randomized Clinical Trials

Author

Mazzinari, Guido, Zampieri, Fernando G., Ball, Lorenzo, Campos, Niklas S., Bluth, Thomas, Hemmes, Sabrine N. T., Ferrando, Carlos, Librero, Julian, Soro, Marina, Pelosi, Paolo, Gama de Abreu, Marcelo, Schultz, Marcus J., Serpa Neto, Ary, Campos, Niklas S., Bluth, Thomas, Hemmes, Sabrine N.T., Ferrando, Carlos, Pelosi, Paolo, de Abreu, Marcelo Gama, Schultz, Marcus J., Neto, Ary Serpa, Campos, Niklas S., Bluth, Thomas, Hemmes, Sabrine N.T., Librero, Julian, Pozo, Natividad, Ferrando, Carlos, Ball, Lorenzo, Mazzinari, Guido, Pelosi, Paolo, de Abreu, Marcelo Gama, Schultz, Marcus J., Neto, Ary Serpa, Hemmes, Sabrine N.T., Gama de Abreu, Marcelo, Severgnini, Paolo, Hollmann, Markus W., Binnekade, Jan M., Wrigge, Hermann, Canet, Jaume, Hiesmayr, Michael, Schmid, Werner, Tschernko, Edda, Jaber, Samir, Hedenstierna, Göran, Putensen, Christian, Pelosi, Paolo, Schultz, Marcus J., Marti, Agnes, Bacuzzi, Alessandro, Brodhun, Alexander, Molin, Alexandre, Merten, Alfred, Parera, Ana, Brunelli, Andrea, Cortegiani, Andrea, Güldner, Andreas, Reske, Andreas W., Gratarola, Angelo, Giarratano, Antonino, Bastin, Bea, Heyse, Bjorn, Mazul-Sunko, Branka, Amantea, Bruno, Barberis, Bruno, Putensen, Christian, Uhlig, Christopher, Minguez Marín, Conrado, Celentano, Cristian, La Bella, Daniela, D’Antini, David, Velghe, David, Sulemanji, Demet, De Robertis, Edoardo, Hartmann, Eric, Montalto, Francesca, Tropea, Francesco, Mills, Gary H., Cinnella, Gilda, Rocca, Giorgio Della, Caggianelli, Girolamo, Pellerano, Giulia, Mollica, Giuseppina, Bugedo, Guillermo, Wrigge, Hermann, Mulier, Jan-Paul, Vandenbrande, Jeroen, Geib, Johann, Yaqub, Jonathan, Florez, Jorge, Mayoral, Juan F., Sprung, Juraj, Van Limmen, Jurgen, Bos, Lieuwe D.J., de Baerdemaeker, Luc, Jamaer, Luc, Spagnolo, Luigi, Strys, Lydia, Granell Gil, Manuel, de Abreu, Marcelo Gama, Vidal Melo, Marcos F., Schultz, Marcus J., Unzueta, Maria Carmen, Moral, Maria Victoria, Ferner, Marion, Hollmann, Markus W., Weiss, Martin, Vanoni, Massimo, Schaefer, Maximilian S., Prieto, Mercè, Grio, Michele, Severgnini, Paolo, Spieth, Peter Markus, Simon, Philipp, Bodger, Phoebe, Sierra, Pilar, Laufenberg-Feldmann, Rita, Rusca, Roberta, Proietti, Rodolfo, Hemmes, Sabrine N.T., Raineri, Santi Maurizio, Caroleo, Santo, Sabaté, Sergi, De Hert, Stefan, Pezzato, Stefano, Treschan, Tanja A., Goranovic, Tatjana, Koch, Thea, Bluth, Thomas, Kiss, Thomas, Perilli, Valter, Cegarra, Virginia, Schmid, Werner, Ferrando, Carlos, Belda, Javier, Soro, Marina, Canet, Jaume, Unzueta, Carmen, Suarez-Sipmann, Fernando, Librero, Julián, Llombart, Alicia, Rovira, Lucas, Granell, Manuel, Aldecoa, César, Diaz-Cambronero, Oscar, Balust, Jaume, Garutti, Ignacio, Gonzalez, Rafael, Gallego, Lucia, del Valle, Santiago Garcia, Redondo, Javier, Pestaña, David, Rodríguez, Aurelio, García, Javier, de la Matta, Manuel, Ibáñez, Maite, Barrios, Francisco, Hernández, Samuel, Torres, Vicente, Peiró, Salvador, Pozo, Natividad, Villena, Abigail, Carramiñana, Albert, Gallego-Casilda, Alberto, Duca, Alejandro, Alcón, Amalia, Miñana, Amanda, Asensio, Ana, Colás, Ana, Isabel Galve, Ana, Izquierdo, Ana, Jurado, Ana, María Pérez, Ana, Mugarra, Ana, Parera, Ana, Brunelli, Andrea, Gutierrez, Andrea, De Miguel, Ángeles, Lozano, Angels, Katime, Antonio, Romero, Antonio, Garrigues, Beatriz, Ayas, Begoña, Arocas, Blanca, Delgado, Carlos, Fernández, Carmen, Romero, Carolina, Gallego, Clara, Garcés, Cristina, Lisbona, Cristina, Parrilla, Cristina, López-Herrera, Daniel, González, Domingo, Llamazares, Eduardo, Del Rio, Elena, Lozano, Elena, Pastor, Ernesto, Chamorro, Estefanía, Gracia, Estefanía, Sánchez, Ester, Romero, Esther, Díez, Fernando, Serralta, Ferran, Daviu, Francisco, Sandín, Francisco, Aguilar, Gerardo, Tusman, Gerardo, Azparren, Gonzalo, Martínez-Pallí, Graciela, Mazzinari, Guido, Benítez, Inmaculada, Hernandéz, Inmaculada, India, Inmaculada, León, Irene, Fuentes, Isabel, Ruiz, Isabel, Puig, Jaume, Ignacio Román, Javie, Acosta, Jesús, Rico, Jesús, Olmedo, Jonathan, Carbonell, Jose A., Alonso, Jose M., María Pérez, Jose, Miguel Marcos, Jose, Navarro, Jose, Valdivia, Jose, Carrizo, Juan, Piqueras, Laura, Soriano, Laura, Vaquero, Laura, Miguel, Lisset, Muñoz, Lorena, Valencia, Lucia, Olmedilla, Luis, Etulain, Ma Justina, Tisner, Manuel, Barrio, María, Dolores Alonso, María, García, María, Hernández, María J., José Alberola, María, Parra, María, Pilar Argente, María, Vila, María, De Fez, Mario, Agilaga, Marta, Gine, Marta, Ayuso, Mercedes, García, Mercedes, Bejarano, Natalia, Peña, Natalia, Ojeda, Nazario, Martínez, Nilda, García, Nuria, Padrón, Oto, García, Pablo, Valls, Paola, Cruz, Patricia, Piñeiro, Patricia, Charco, Pedro, Anaya, Rafael, López, Ramiro, Rodríguez, Rayco, Martínez, Rocío, Pujol, Roger, Dosdá, Rosa, Lardies, Rosa, Díaz, Ruben, Villazala, Rubén, Zapatero, Sara, Cabrera, Sergio, Sánchez, Sergio, Martin, Silvia, Diaz, Suzana, Franco, Tania, Moreno, Tania, Socorro, Tania, Gilabert, Vicente, Balandrón, Victor, Moral, Victoria, Cegarra, Virgina, Varón, Viviana, Bluth, Thomas, Serpa Neto, Ary, Bobek, Ilona, Canet, Jaume, Cinnella, Gilda, de Baerdemaeker, Luc, Gregoretti, Cesare, Hedenstierna, Göran, Hemmes, Sabrine N.T., Hiesmayr, Michael, Hollmann, Markus W., Jaber, Samir, Laffey, John, Licker, Marc-Joseph, Markstaller, Klaus, Matot, Idit, Mills, Gary H., Mulier, Jan Paul, Putensen, Christian, Rossaint, Rolf, Schmitt, Jochen, Senturk, Mert, Severgnini, Paolo, Sprung, Juraj, Vidal Melo, Marcos F., Wrigge, Hermann, Schultz, Marcus J., Pelosi, Paolo, de Abreu, Marcelo Gama, Abelha, Fernando, Abitağaoğlu, Sühayla, Achilles, Marc, Adebesin, Afeez, Adriaensens, Ine, Ahene, Charles, Akbar, Fatima, Al Harbi, Mohammed, Al Khoury al Kallab, Rita, Albanel, Xavier, Aldenkortt, Florence, Alfouzan, Rawan Abdullah Saleh, Alruqaie, Reef, Altermatt, Fernando, Araujo, Bruno Luís de Castro, Arbesú, Genaro, Artsi, Hanna, Aurilio, Caterina, Ayanoglu, Omer Hilmi, Bacuzzi, Alessandro, Baig, Harris, Baird, Yolanda, Balonov, Konstantin, Balust, Jaume, Banks, Samantha, Bao, Xiaodong, Baumgartner, Mélanie, Belda Tortosa, Isabel, Bergamaschi, Alice, Bergmann, Lars, Bigatello, Luca, Biosca Pérez, Elena, Birr, Katja, Bluth, Thomas, Bojaxhi, Elird, Bonenti, Chiara, Bonney, Iwona, Bos, Elke M.E., Bowman, Sara, Braz, Leandro Gobbo, Brugnoni, Elisa, Brull, Sorin J., Brunetti, Iole, Bruni, Andrea, Buenvenida, Shonie L., Busch, Cornelius Johannes, Camerini, Giovanni, Canet, Jaume, Capatti, Beatrice, Carmona, Javiera, Carungcong, Jaime, Carvalho, Marta, Cattan, Anat, Cavaleiro, Carla, Chiumello, Davide, Ciardo, Stefano, Coburn, Mark, Colella, Umberto, Contreras, Victor, Corman Dincer, Pelin, Cotter, Elizabeth, Crovetto, Marcia, Darrah, William, Davies, Simon, de Baerdemaeker, Luc, De Hert, Stefan, Del Cojo Peces, Enrique, Delphin, Ellise, Diaper, John, do Nascimento, Paulo, Jr., Donatiello, Valerio, Dong, Jing, Dourado, Maria do Socorro, Dullenkopf, Alexander, Ebner, Felix, Elgendy, Hamed, Ellenberger, Christoph, Erdoğan Ari, Dilek, Ermert, Thomas, Farah, Fadi, Fernandez-Bustamante, Ana, Ferreira, Cristina, Fiore, Marco, Fonte, Ana, Fortià Palahí, Christina, Galimberti, Andrea, Gama de Abreu, Marcelo, Garofano, Najia, Giaccari, Luca Gregorio, Gilsanz, Fernando, Girrbach, Felix, Gobbi, Luca, Godfried, Marc Bernard, Goettel, Nicolai, Goldstein, Peter A., Goren, Or, Gorlin, Andrew, Granell Gil, Manuel, Gratarola, Angelo, Graterol, Juan, Guyon, Pierre, Haire, Kevin, Harou, Philippe, Helf, Antonia, Hemmes, Sabrine N.T., Hempel, Gunther, Hernández Cádiz, María José, Heyse, Björn, Hollmann, Markus W., Huercio, Ivan, Ilievska, Jasmina, Jakus, Lien, Jeganath, Vijay, Jelting, Yvonne, Jung, Minoa, Kabon, Barbara, Kacha, Aalok, Karaman Ilić, Maja, Karuppiah, Arunthevaraja, Kavas, Ayse Duygu, Keli Barcelos, Gleicy, Kellogg, Todd A., Kemper, Johann, Kerbrat, Romain, Khodr, Suraya, Kienbaum, Peter, Kir, Bunyamin, Kiss, Thomas, Kivrak, Selin, Klarić, Vlasta, Koch, Thea, Köksal, Ceren, Kowark, Ana, Kranke, Peter, Kuvaki, Bahar, Kuzmanovska, Biljana, Laffey, John, Lange, Mirko, Lemos, Marília Freitas de, Licker, Marc-Joseph, López-Baamonde, Manuel, López-Hernández, Antonio, Lopez-Martinez, Mercedes, Luise, Stéphane, MacGregor, Mark, Machado, Humberto S., Magalhães, Danielle, Maillard, Julien, Malerbi, Patrizia, Manimekalai, Natesan, Margarson, Michael, Markstaller, Klaus, Martin, Archer K, Martin, David P., Martin, Yvette N., Martínez-Ocon, Julia, Martin-Loeches, Ignacio, Maseda, Emilio, Matot, Idit, McAuliffe, Niamh, McKenzie, Travis J., Medina, Paulina, Meersch, Melanie, Menzen, Angelika, Mertens, Els, Meurer, Bernd, Meyer-Treschan, Tanja, Miao, Changhong, Micalizzi, Camilla, Milić, Morena, Módolo, Norma Sueli Pinheiro, Moine, Pierre, Mölders, Patrick, Montero-Feijoo, Ana, Moret, Enrique, Muller, Markus K, Murphy, Zoe, Nalwaya, Pramod, Filip, Naumovski, Navalesi, Paolo, Navarro e Lima, Lais Helena, Nesek Adam, Višnja, Neumann, Claudia, Newell, Christopher, Nisnevitch, Zoulfira, Nizamuddin, Junaid, Novazzi, Cecilia, Nunes, Catarina S, O’Connor, Michael, Oprea, Günther, Orhan Sungur, Mukadder, Özbilgin, Şule, Pace, Maria Caterina, Pacheco, Marcos, Packianathaswamy, Balaji, Palma Gonzalez, Estefania, Papaspyros, Fotios, Paredes, Sebastián, Passavanti, Maria Beatrice, Pedemonte, Juan Cristobal, Pelosi, Paolo, Peremin, Sanja, Philipsenburg, Christoph, Pinho, Daniela, Pinho, Silvia, Posthuma, Linda M., Pota, Vincenzo, Preckel, Benedikt, Priani, Paolo, Putensen, Christian, Rached, Mohamed Aymen, Radoeshki, Aleksandar, Ragazzi, Riccardo, Rajamanickam, Tamilselvan, Rajamohan, Arthi, Ramakrishna, Harish, Rangarajan, Desikan, Reiterer, Christian, Renew, J. Ross, Reynaud, Thomas, Rhys, Rhidian, Rivas, Eva, Robitzky, Luisa, Rossaint, Rolf, Rubulotta, Francesca, Sabbatini, Giovanni, Samuels, Jon D, Sanahuja, Josep Martí, Sansone, Pasquale, Santos, Alice, Sayedalahl, Mohamed, Schaefer, Maximilian S., Scharffenberg, Martin, Schiffer, Eduardo, Schliewe, Nadja, Schorer, Raoul, Schultz, Marcus J., Schumann, Roman, Selmo, Gabriele, Sendra, Mar, Senturk, Mert, Severgnini, Paolo, Shaw, Kate, Shosholcheva, Mirjana, Sibai, Abdulrazak, Simon, Philipp, Simonassi, Francesca, Sinno, Claudia, Sivrikoz, Nukhet, Skandalou, Vasiliki, Smith, Neil, Soares, Maria, Socorro Artiles, Tania, Sousa Castro, Diogo, Sousa, Miguel, Spadaro, Savino, Sprung, Juraj, Stamatakis, Emmanouil, Steiner, Luzius A., Stevenazzi, Andrea, Suarez-de-la-Rica, Alejandro, Suppan, Mélanie, Teichmann, Robert, Tena Guerrero, José Maria, Thiel, Bram, Tolós, Raquel, Tucci, Michelle, Turnbull, Zachary A., Turudić, Žana, Unterberg, Matthias, Van Limmen, Jurgen, Van Nieuwenhove, Yves, Van Waesberghe, Julia, Vidal Melo, Marcos Francisco, Vitković, Bibiana, Vivona, Luigi, Vizcaychipi, Marcela, Volta, Carlo Alberto, Weber, Anne, Weingarten, Toby N., Wittenstein, Jakob, Wrigge, Hermann, Wyffels, Piet, Yagüe, Julio, Yates, David, Yavru, Ayşen, Zac, Lilach, and Zhong, Jing

Published
2025
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14. Evaluating Active Learning: The Role of Non-Presential Workload Monitoring in Academic Achievement and Student Satisfaction in Architecture Programs Within the European Higher Education Area.

Author

Sirvent-Pérez, César Daniel, Pérez-Carramiñana, Carlos, Saura-Gómez, Pascual, González-Avilés, Ángel Benigno, and Ruiz-Cáceres, José Ángel

Subjects
STUDENT exchange programs, AUTODIDACTICISM, BACHELOR'S degree, SELF-managed learning (Personnel management), ACTIVE learning
Abstract

The European Higher Education Area (EHEA) university learning framework, structured around the European Credit Transfer and Accumulation System (ECTS), integrates classroom hours with independent, non-classroom workloads outside the university, where students engage in self-directed learning. This study aimed to develop a standardized protocol to monitor and quantify non-presential study hours to identify and adjust anomalous workload values. Over a two-year period, data were gathered from two distinct student groups (local Spanish students and international exchange students) enrolled in the same fourth-year architecture course at the University of Alicante. The data analysis allowed for an exploration of correlations among three key variables: non-presential study hours, final grades, and student satisfaction (self-assessed course perceptions). The results reveal a direct proportional relationship among these variables, whereby an increase in weekly study hours corresponds with both higher final grades and improved student satisfaction with the course. [ABSTRACT FROM AUTHOR]

Published
2025
Full Text
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15. Evaluating Active Learning: The Role of Non-Presential Workload Monitoring in Academic Achievement and Student Satisfaction in Architecture Programs Within the European Higher Education Area

Author

César Daniel Sirvent-Pérez, Carlos Pérez-Carramiñana, Pascual Saura-Gómez, Ángel Benigno González-Avilés, and José Ángel Ruiz-Cáceres

Subjects
workload, non-presential, ECTS credits, final grades, student satisfaction, bachelor’s degree, Education
Abstract

The European Higher Education Area (EHEA) university learning framework, structured around the European Credit Transfer and Accumulation System (ECTS), integrates classroom hours with independent, non-classroom workloads outside the university, where students engage in self-directed learning. This study aimed to develop a standardized protocol to monitor and quantify non-presential study hours to identify and adjust anomalous workload values. Over a two-year period, data were gathered from two distinct student groups (local Spanish students and international exchange students) enrolled in the same fourth-year architecture course at the University of Alicante. The data analysis allowed for an exploration of correlations among three key variables: non-presential study hours, final grades, and student satisfaction (self-assessed course perceptions). The results reveal a direct proportional relationship among these variables, whereby an increase in weekly study hours corresponds with both higher final grades and improved student satisfaction with the course.

Published
2025
Full Text
View/download PDF

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