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356 results on '"Ribeiro, Angela"'

1. Qualitative and quantitative analysis of student's perceptions in the use of generative AI in educational environments

Author

Altares-López, Sergio, Bengochea-Guevara, José M., Ranz, Carlos, Montes, Héctor, and Ribeiro, Angela

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

The effective integration of generative artificial intelligence in education is a fundamental aspect to prepare future generations. The objective of this study is to analyze from a quantitative and qualitative point of view the perception of controlled student-IA interaction within the classroom. This analysis includes assessing the ethical implications and everyday use of AI tools, as well as understanding whether AI tools encourage students to pursue STEM careers. Several points for improvement in education are found, such as the challenge of getting teachers to engage with new technologies and adapt their methods in all subjects, not just those related to technologies., Comment: 17 pages, 7 figures, 4 tables

Published
2024

2. AutoQML: Automatic Generation and Training of Robust Quantum-Inspired Classifiers by Using Genetic Algorithms on Grayscale Images

Author

Altares-López, Sergio, García-Ripoll, Juan José, and Ribeiro, Angela

Subjects
Quantum Physics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

We propose a new hybrid system for automatically generating and training quantum-inspired classifiers on grayscale images by using multiobjective genetic algorithms. We define a dynamic fitness function to obtain the smallest possible circuit and highest accuracy on unseen data, ensuring that the proposed technique is generalizable and robust. We minimize the complexity of the generated circuits in terms of the number of entanglement gates by penalizing their appearance. We reduce the size of the images with two dimensionality reduction approaches: principal component analysis (PCA), which is encoded in the individual for optimization purpose, and a small convolutional autoencoder (CAE). These two methods are compared with one another and with a classical nonlinear approach to understand their behaviors and to ensure that the classification ability is due to the quantum circuit and not the preprocessing technique used for dimensionality reduction., Comment: Submitted for review on the 7th of June 2022

Published
2022
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6. Automatic design of quantum feature maps

Author

Altares-López, Sergio, Ribeiro, Angela, and García-Ripoll, Juan José

Subjects
Quantum Physics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We propose a new technique for the automatic generation of optimal ad-hoc ans\"atze for classification by using quantum support vector machine (QSVM). This efficient method is based on NSGA-II multiobjective genetic algorithms which allow both maximize the accuracy and minimize the ansatz size. It is demonstrated the validity of the technique by a practical example with a non-linear dataset, interpreting the resulting circuit and its outputs. We also show other application fields of the technique that reinforce the validity of the method, and a comparison with classical classifiers in order to understand the advantages of using quantum machine learning.

Published
2021
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9. Collaborative Harvest Robot

Author

Conejero, Maria Nuria, Montes, Hector, Andujar, Dionisio, Bengochea-Guevara, Jose Maria, Ribeiro, Angela, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Tardioli, Danilo, editor, Matellán, Vicente, editor, Heredia, Guillermo, editor, Silva, Manuel F., editor, and Marques, Lino, editor

Published
2023
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12. Collaborative Harvest Robot

Author

Conejero, Maria Nuria, primary, Montes, Hector, additional, Andujar, Dionisio, additional, Bengochea-Guevara, Jose Maria, additional, and Ribeiro, Angela, additional

Published
2022
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14. An Autonomous Guided Field Inspection Vehicle for 3D Woody Crops Monitoring

Author

Bengochea-Guevara, José M., Andújar, Dionisio, Cantuña, Karla, Garijo-Del-Río, Celia, Ribeiro, Angela, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Silva, Manuel F., editor, Luís Lima, José, editor, Reis, Luís Paulo, editor, Sanfeliu, Alberto, editor, and Tardioli, Danilo, editor

Published
2020
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15. AutoQML: Automatic generation and training of robust quantum-inspired classifiers by using evolutionary algorithms on grayscale images[Formula presented]

Author

Ministerio de Asuntos Económicos y Transformación Digital (España), Altares-López, Sergio, García-Ripoll, Juan José, Ribeiro, Angela, Ministerio de Asuntos Económicos y Transformación Digital (España), Altares-López, Sergio, García-Ripoll, Juan José, and Ribeiro, Angela

Abstract

A new hybrid system is proposed for automatically generating and training quantum-inspired classifiers on grayscale images by using multiobjective genetic algorithms. It is defined a dynamic fitness function to obtain the smallest circuit complexity and highest accuracy on unseen data, ensuring that the proposed technique is generalizable and robust. At the same time, it is minimized the complexity of the generated circuits in terms of the number of entangling operators by penalizing their appearance and number of gates. The size of the images is reduced by using two dimensionality reduction approaches: principal component analysis (PCA), which is encoded within the individual and genetically optimized by the system, and a small convolutional autoencoder (CAE). These two methods are compared with one another and with a classical nonlinear approach to understand their behaviors and to ensure that the classification ability is due to the quantum circuit and not the preprocessing technique used for dimensionality reduction.

Published
2024

16. Generative AI: The power of the new education

Author

Altares-López, Sergio, Bengochea-Guevara, José M., Ranz, Carlos, Montes, Héctor, Ribeiro, Angela, Altares-López, Sergio, Bengochea-Guevara, José M., Ranz, Carlos, Montes, Héctor, and Ribeiro, Angela

Abstract

The effective integration of generative artificial intelligence in education is a fundamental aspect to prepare future generations. This study proposes an accelerated learning methodology in artificial intelligence, focused on its generative capacity, as a way to achieve this goal. It recognizes the challenge of getting teachers to engage with new technologies and adapt their methods in all subjects, not just those related to AI. This methodology not only promotes interest in science, technology, engineering and mathematics, but also facilitates student understanding of the ethical uses and risks associated with AI. Students' perceptions of generative AI are examined, addressing their emotions towards its evolution, evaluation of its ethical implications, and everyday use of AI tools. In addition, AI applications commonly used by students and their integration into other disciplines are investigated. The study aims to provide educators with a deeper understanding of students' perceptions of AI and its relevance in society and in their future career paths., Comment: 14 pages, 7 figures, 4 tables

Published
2024

17. Effect of tetanic stimulation prior to train-of-four monitoring on the time to muscle response stabilization with neuromuscular blockade with rocuronium in patients aged 60 to 80 years: A prospective randomized controlled trial.

Author

Henrique Silva Ribeiro, Angela, Verçosa, Nubia, Braga, Estêvão Luiz Carvalho, Micuci, Angelo Jorge Queiroz Rangel, Germano-Filho, Paulo Alípio, and Cavalcanti, Ismar Lima

Subjects
*NEUROMUSCULAR blockade, *RANDOMIZED controlled trials, *NEUROMUSCULAR blocking agents, *ROCURONIUM bromide, *NEUROMUSCULAR diseases, *SURGERY
Abstract

Purpose: To determine the effect of tetanic stimulation on the time to achieve stabilization of the T1 height, by acceleromyography train-of-four (TOF) ratio monitoring, in patients aged 60 to 80 years. Methods: Randomized, prospective, single-blind, controlled trial in patients aged 60 to 80 years undergoing elective surgery under general anesthesia in two university hospitals in Brazil between December 2019 and March 2022. This trial was performed in accordance with the principles of the Helsinki Declaration and the guidelines for good clinical research practice in pharmacodynamic studies of neuromuscular blocking agents II. Participants were randomly allocated by computer-generated numbers to receive tetanic stimulation (intervention group, n = 25) or not receive tetanic stimulation (control group, n = 25) to achieve T1 height stabilization on TOF ratio monitoring. The primary endpoint was to evaluate the effect of tetanic stimulation on the time to achieve stabilization of the T1 height. We also evaluated the effect on the onset time of rocuronium and time to recover from neuromuscular blockade with a single dose of rocuronium 0.6 mg.kg-1 with spontaneous recovery. Results: There was no statistically significant difference between the groups in the time to T1 height stabilization (intervention: 4.3 [2.0–8.0] min; control: 5.8 [2.0–10.5] min; p = 0.202), onset time of the neuromuscular blocking agent (intervention: 1.9 [±0.7] min; control: 2.2 [±1.0] min; p = 0.219), or neuromuscular blockade recovery times to normalized TOF values of 0.7 (intervention: 106.1 [±37.2] min; control: 91.7 [±27.5] min; p = 0.295), 0.8 (intervention: 114.3 [±40.1] min; control: 97.8 [±28.9] min; p = 0.225), 0.9 (intervention: 126.5 [±44.0] min; control: 106.9 [±30.6] min; p = 0.153), and 1.0 (intervention: 138.3 [±43.4] min; control: 123.8 [±43.5] min; p = 0.425). Conclusion: The results of this study suggest that the recommendation to use tetanic stimulation to shorten the time to T1 height stabilization in neuromuscular monitoring did not alter the stabilization time of the T1 twitch or the pharmacodynamics of neuromuscular blockade with rocuronium in patients aged 60 to 80 years. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Thiamine Deficiency and Poverty

Author

Dias, Fernando Machado Vilhena, Oliveira, Aline Sanches, da Silva, Danilo Jorge, Ribeiro, Angela Maria, Preedy, Victor R., editor, and Patel, Vinood B., editor

Published
2019
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21. 3D Monitoring of Woody Crops Using a Medium-Sized Field Inspection Vehicle

Author

Bengochea-Guevara, José M., Andújar, Dionisio, Sanchez-Sardana, Francisco L., Cantuña, Karla, Ribeiro, Angela, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Ollero, Anibal, editor, Sanfeliu, Alberto, editor, Montano, Luis, editor, Lau, Nuno, editor, and Cardeira, Carlos, editor

Published
2018
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25. No sex-biased dispersal in a primate with an uncommon social system-cooperative polyandry.

Author

Díaz-Muñoz, Samuel L and Ribeiro, Angela M

Subjects
Inbreeding avoidance, Kin cooperation, Local mate competition, Local resource enhancement, Mating systems, Polyandry, Population structure, Sex-biased dispersal, Social behavior, Biological Sciences, Medical and Health Sciences
Abstract

An influential hypothesis proposed by Greenwood (1980) suggests that different mating systems result in female and male-biased dispersal, respectively, in birds and mammals. However, other aspects of social structure and behavior can also shape sex-biased dispersal. Although sex-specific patterns of kin cooperation are expected to affect the benefits of philopatry and dispersal patterns, empirical evidence is scarce. Unlike many mammals, Saguinus geoffroyi (Geoffroy's tamarin) has a breeding system in which typically multiple males mate with a single breeding female. Males typically form cooperative reproductive partnerships between relatives, whereas females generally compete for reproductive opportunities. This system of cooperative polyandry is predicted to result in female-biased dispersal, providing an opportunity to test the current hypotheses of sex-biased dispersal. Here we test for evidence of sex-biased dispersal in S. geoffroyi using demographic and genetic data from three populations. We find no sex bias in natal dispersal, contrary to the prediction based on the mating patterns. This pattern was consistent after controlling for the effects of historical population structure. Limited breeding opportunities within social groups likely drive both males and females to disperse, suggesting that dispersal is intimately related to the social context. The integration of genetic and field data revealed that tamarins are another exception to the presumed pattern of male-biased dispersal in mammals. A shift in focus from mating systems to social behavior, which plays a role in most all processes expected to influence sex-bias in dispersal, will be a fruitful target for research both within species and across taxa.

Published
2014

30. Identification of Plant Textures in Agricultural Images by Principal Component Analysis

Author

Montalvo, Martín, Guijarro, María, Guerrero, José Miguel, Ribeiro, Ángela, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Martínez-Álvarez, Francisco, editor, Troncoso, Alicia, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2016
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31. Marine genomics: News and views

Author

Ribeiro, Ângela M., Foote, Andrew D., Kupczok, Anne, Frazão, Bárbara, Limborg, Morten T., Piñeiro, Rosalía, Abalde, Samuel, Rocha, Sara, and da Fonseca, Rute R.

Published
2017
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35. NeRFLight: Fast and Light Neural Radiance Fields using a Shared Feature Grid

Author

European Commission, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Rivas-Manzaneque, Fernando, Sierra-Acosta, Jorge, Penate-Sanchez, Adrian, Moreno-Noguer, Francesc, Ribeiro, Angela, European Commission, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Rivas-Manzaneque, Fernando, Sierra-Acosta, Jorge, Penate-Sanchez, Adrian, Moreno-Noguer, Francesc, and Ribeiro, Angela

Abstract

While original Neural Radiance Fields (NeRF) have shown impressive results in modeling the appearance of a scene with compact MLP architectures, they are not able to achieve real-time rendering. This has been recently addressed by either baking the outputs of NeRF into a data structure or arranging trainable parameters in an explicit feature grid. These strategies, however, significantly increase the memory footprint of the model which prevents their deployment on bandwidth-constrained applications. In this paper, we extend the grid-based approach to achieve real-time view synthesis at more than 150 FPS using a lightweight model. Our main contribution is a novel architecture in which the density field of NeRF-based representations is split into N regions and the density is modeled using N different decoders which reuse the same feature grid. This results in a smaller grid where each feature is located in more than one spatial position, forcing them to learn a compact representation that is valid for different parts of the scene. We further reduce the size of the final model by disposing of the features symmetrically on each region, which favors feature pruning after training while also allowing smooth gradient transitions between neighboring voxels. An exhaustive evaluation demonstrates that our method achieves real-time performance and quality metrics on a pair with state-of-the-art with an improvement of more than 2× in the FPS/MB ratio.

Published
2023

46. Fleets of robots for environmentally-safe pest control in agriculture

Author

Gonzalez-de-Santos, Pablo, Ribeiro, Angela, Fernandez-Quintanilla, Cesar, Lopez-Granados, Francisca, Brandstoetter, Michael, Tomic, Slobodanka, Pedrazzi, Stefania, Peruzzi, Andrea, Pajares, Gonzalo, Kaplanis, George, Perez-Ruiz, Manuel, Valero, Constantino, del Cerro, Jaime, Vieri, Marco, Rabatel, Gilles, and Debilde, Benoit

Published
2017
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50. Perception and Tracking of Dynamic Objects for Optimization of Avoidance Strategies in Autonomous Piloting of Vehicles

Author

García-Pérez, Lía, García-Alegre, María C., Ribeiro, Ángela, Guinea, Domingo, Cañas, Jose María, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Freksa, Christian, editor, Knauff, Markus, editor, Krieg-Brückner, Bernd, editor, Nebel, Bernhard, editor, and Barkowsky, Thomas, editor

Published
2005
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