Comunicaciones y ponencias de congresos - Biltzarrak eta Argitalpenak

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Open Access
Additively generated (a,b)-implication functions*
(IEEE, 2023) Santos, Helida; Pereira Dimuro, Graçaliz; Bedregal, Benjamin; Paiva, Rui; Lucca, Giancarlo; Moura, Bruno; Cruz, Anderson; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Some problems involving classification through neural networks are known to use inputs out of the scope of the unit interval. Therefore, defining operations on arbitrary closed real intervals may be an interesting strategy to tackle this issue and enhance those application environments. In this paper we follow the ideas already discussed in the literature regarding (a,b)-fusion functions, and (a,b)-negations, to provide a new way to construct implication functions. The main idea is to construct an operator using additively generated functions that preserve the properties required by implication functions.
Open Access
Addressing the issue of trust in elementary teachers' maths-specific education: ANFoMAM project
(Charles University (Chequia), 2019) Celi, Valentina; Cogolludo, José Ignacio; Gil Clemente, Elena; Lizasoain Iriso, María Inmaculada; Millán Gasca, Ana; Moler Cuiral, José Antonio; Regoliosi, Luigi; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
To improve primary school teachers' maths-specific education at university, our project will develop a series of workshops, as ready-to-use instruments, which closely consider children's way of learning and their relationship with mathematics. Thus, the interest of participants in children is exploited in sessions which take into account both their professional work as teachers and their own childhood experiences. The aim is to help participants to evolve in the key aspect of trust. The paper describes the objectives and first results of the ANFoMAM project, supported by the Erasmus Plus Programme in the area of strategic partnerships for innovation in higher education in Europe.
Open Access
Agent-based simulation improves e-grocery deliveries using horizontal cooperation
(IEEE, 2020) Serrano Hernández, Adrián; Faulín Fajardo, Javier; Torre Martínez, Rocío de la; Cadarso, Luis; Estatistika, Informatika eta Matematika; Enpresen Kudeaketa; Institute of Smart Cities - ISC; Institute for Advanced Research in Business and Economics - INARBE; Estadística, Informática y Matemáticas; Gestión de Empresas
E-commerce has increased tremendously in recent decades because of improvements in the information and telecommunications technology along with changes in societal lifestyles. More recently, e-grocery (groceries purchased online) including fresh vegetables and fruit, is gaining importance as the most-efficient delivery system in terms of cost and time. In this respect, we evaluate the effect of cooperation-based policies on service quality among different supermarkets in Pamplona, Spain. Concerning the methodology, we deploy, firstly, a detailed survey in Pamplona in order to model e-grocery demand patterns. Secondly, we develop an agent-based simulation model for generating scenarios in cooperative and non-cooperative settings, considering the real data obtained from the survey analysis. Thus, a Vehicle Routing Problem is dynamically generated and solved within the simulation framework using a biased-randomization algorithm. Finally, the results show significant reductions in lead times and better customer satisfaction when employing horizontal cooperation in e-grocery distribution.
Open Access
Aggregation functions based on the Choquet integral applied to image resizing
(Atlantis Press, 2019) Bueno, Jéssica C. S.; Dias, Camila A.; Pereira Dimuro, Graçaliz; Santos, Helida; Bustince Sola, Humberto; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas
The rising volume of data and its high complexity has brought the need of developing increasingly efficient knowledge extraction techniques, which demands efficiency both in computational cost and in accuracy. Most of problems that are handled by these techniques has complex information to be identified. So, machine learning methods are frequently used, where a variety of functions can be applied in the different steps that are employed in their architecture. One of them is the use of aggregation functions aiming at resizing images. In this context, we introduce a study of aggregation functions based on the Choquet integral, whose main characteristic in comparison with other aggregation functions is that it considers, through fuzzy measure, the interaction between the elements to be aggregated. Thus, our main goal is to present an evaluation study of the performance of the standard Choquet integral the and copula-based generalization of the Choquet integral in relation to the maximum and mean functions, looking for results that may be better than the aggregation functions commonly applied. The results of such comparisons are promising, when evaluated through image quality metrics.
Open Access
Aggregation of deep features for image retrieval based on object detection
(Springer, 2019-09-22) Forcén Carvalho, Juan Ignacio; Pagola Barrio, Miguel; Barrenechea Tartas, Edurne; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Image retrieval can be tackled using deep features from pretrained Convolutional Neural Networks (CNN). The feature map from the last convolutional layer of a CNN encodes descriptive information from which a discriminative global descriptor can be obtained. However, this global descriptors combine all of the information of the image, giving equal importance to the background and the object of the query. We propose to use an object detection based on saliency models to identify relevant regions in the image and therefore obtain better image descriptors. We extend our proposal to multi-regional image representation and we combine our proposal with other spatial weighting measures. The descriptors derived from the salient regions improve the performance in three well known image retrieval datasets as we show in the experiments.
Open Access
Análisis de los cambios en los patrones de temperatura mediante técnicas de stream clustering
(CAEPIA, 2024) Urío Larrea, Asier; Pereira Dimuro, Graçaliz; Andreu-Pérez, Javier; Camargo, Heloisa A.; Aguirre Eraso, Javier; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
El cambio climático afecta a las condiciones medioambientales de las distintas regiones. La capacidad de constatar estos cambios es una eficaz herramienta para adaptarse a la evolución de las condiciones. Los datos meteorológicos se generan continuamente en múltiples estaciones de todo el mundo, proporcionando una valiosa información sobre la variabilidad en el tiempo de los patrones climáticos. El estudio de este flujo de datos nos permite comprender mejor los nuevos patrones climáticos. Este trabajo explora, mediante un algoritmo de agrupamiento de flujos de datos (stream clustering), el potencial de emplear datos meteorológicos obtenidos en diferentes localizaciones geográficas para rastrear el cambio en los patrones climáticos en la Comunidad Foral de Navarra durante los últimos 20 años. El estudio de caso mostró la aplicabilidad de los métodos de flujos de datos a la segmentación incremental de regiones geográficas en función de sus factores climatológicos.
Open Access
Análisis de redes sociales basado en las conquistas de César Borgia
(Universidad de Málaga, 2021) Fumanal Idocin, Javier; Cordón, Óscar; Alonso Betanzos, Amparo; Bustince Sola, Humberto; Fernández Fernández, Francisco Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
En este trabajo presentamos el modelado de redes sociales y detección de comunidades utilizando como base un evento histórico real, las conquistas de César Borgia en el siglo XV. Para ello, proponemos un nuevo conjunto de funciones, llamadas funciones de afinidad, disenadas para capturar la 'naturaleza de las interacciones locales entre cada par de actores en una red. Utilizando estas funciones, desarrollamos un nuevo algoritmo de detección de comunidades, el Borgia Clustering, donde las comunidades surgen naturalmente de un proceso de simulación de interacción de múltiples agentes en la red. También discutimos los efectos del tamaño y la escala de cada comunidad, y como pueden ser tomadas en cuenta en el proceso de simulación. Finalmente, comparamos nuestra detección de comunidades con otros algoritmos representativos, encontrando resultados favorables a nuestra propuesta.
Open Access
Analysing capacity challenges in the Multi-Airport System of Mexico City
(Dime University of Genoa, 2022) Mújica Mota, Miguel; Faulín Fajardo, Javier; Izco Berastegui, Irene; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
The relentless growth in Mexico City’s aviation traffic has inevitably strained capacity development of its airport, raising the dilemma between the possible solutions. In the present study, Mexico’s Multi-Airport System is subjected to analysis by means of multi-model simulation, focusing on the capacity-demand problem of the system. The methodology combines phases of modelling, data collection, simulation, experimental design, and analysis. Drawing a distinction from previous works involving two-airport systems. It also explores the challenges raised by the Covid-19 pandemic in Mexico City airport operations, with a discrete-event simulation model of a multi-airport system composed by three airports (MEX, TLC, and the new airport NLU). The study is including the latest data of flights, infrastructures, and layout collected in 2021. Therefore, the paper aims to answer to the question of whether the system will be able to cope with the expected demand in a short-, medium-, and long term by simulating three future scenarios based on aviation forecasts. The study reveals potential limitations of the system as time evolves and the feasibility of a joint operation to absorb the demand in such a big region like Mexico City
Open Access
Analysis of inter-train wireless connectivity to enable context aware rail applications
(Springer, 2021) Picallo Guembe, Imanol; López Iturri, Peio; Celaya Echarri, Mikel; Azpilicueta Fernández de las Heras, Leyre; Astrain Escola, José Javier; Falcone Lanas, Francisco; Estadística, Informática y Matemáticas; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Estatistika, Informatika eta Matematika; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Train systems are fundamental players within multi-modal transit systems, providing efficient transportation means for passengers and goods. In the framework of Smart Cities and Smart Regions, providing context aware environments is compulsory in order to take full advantage of system integration, with updated information exchange among Intelligent Transportation system deployments. In this work, inter-train wireless system connectivity is analyzed with the aid of deterministic 3D wireless channel approximations, with the aim of obtaining estimations of frequency/power volumetric channel distributions, as well as time domain characteristics, for different frequency bands. The results show the impact of the complex inter-train scenario conditions, which require precise channel modelling in order to perform optimal network design, planning and optimization tasks.
Open Access
Analysis of interaction mechanisms and intercomparison of raytracing tools for optimizing THz simulations
(IEEE, 2025-03-11) Aksoy, Enes; Schultze, Alper; Fazli, Abdolvakil; Raschkowski, Leszek; Azpilicueta Fernández de las Heras, Leyre; Celaya Echarri, Mikel; Navarro Cía, Miguel; Stanczak, Slawomir; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
This paper quantifies the weight of the different physical mechanisms (reflection, diffraction, and scattering) in a typical indoor THz wireless communication environment and provides an intercomparison of raytracing tools. Two state-of-the-art raytracing tools - Wireless InSite and Sionna - are utilized to analyze the capabilities of currently available open-source and commercial raytracing engines for THz simulations. A channel sounder measurement campaign at 300 GHz was conducted in a conference room at Fraunhofer HHI, which is used to validate the raytracing simulations. Additionally, the measurements are compared to a proprietary raytracer, optimized for THz simulations. This paper presents a guideline to increase the capabilities of state-of-the-art raytracing tools, to obtain good results for high frequency simulations. The comparisons show, that currently used raytracing tools are not sufficiently accurate for THz simulations. However, these inaccuracies can be mitigated by the implementation of new features, such as the inclusion of different scattering mechanisms and the incorporation of atmospheric attenuation, while utilizing precise geometry and accurate material parameter models.
Open Access
Analyzing the determinant characteristics for a good performance at enade brazilian exam stratified by teaching modality: face-to-face versus online
(SciTePress, 2022) Gondran, Eric; Lucca, Giancarlo; Berri, Rafael A.; Santos, Helida; Borges, Eduardo N.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
The National Student Performance Exam (ENADE) annually evaluates different Brazilian higher education courses. This exam considers both face-to-face and distance learning courses. Distance learning is growing increasingly, especially during the coronavirus (COVID-19) pandemic. This study applies different techniques for selecting ENADE 2018 database characteristics, like information gain, gain rate, symmetric uncertainty, Pearson correlation, and relief F. The objective of the work is to discover which personal and socioeconomic characteristics are decisive for the student's performance at ENADE, whether the student is in the context of Distance Education or face-to-face. It can be concluded, among other results, that: the father's level of education directly influences performance; the higher the income, the better the performance; and white students have better performance than black and brown-skinned ones. Thus, the results obtained in this study may initiate analyzes of public policies towards improving performance at ENADE.
Open Access
Application and comparison of CC-integrals in business group decision making
(Springer, 2022) Wieczynski, Jonata; Lucca, Giancarlo; Borges, Eduardo N.; Pereira Dimuro, Graçaliz; Lourenzutti, Rodolfo; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Optimized decisions is required by businesses (analysts) if they want to stay open. Even thought some of these are from the knowhow of the managers/executives, most of them can be described mathematically and solved (semi)-optimally by computers. The Group Modular Choquet Random Technique for Order of Preference by Similarity to Ideal Solution (GMC-RTOPSIS) is a Multi-Criteria Decision Making (MCDM) that was developed as a method to optimize the later types of problems, by being able to work with multiple heterogeneous data types and interaction among different criteria. On the other hand the Choquet integral is widely used in various fields, such as brain-computer interfaces and classification problems. With the introduction of the CC-integrals, this study presents the GMC-RTOPSIS method with CC-integrals. We applied 30 different CC-integrals in the method and analyzed its results using 3 different methods. We found that by modifying the decisionmaking method we allow for more flexibility and certainty in the choosing process.
Open Access
Application of the Sugeno integral in fuzzy rule-based classification
(Springer, 2022) Wieczynski, Jonata; Lucca, Giancarlo; Borges, Eduardo N.; Pereira Dimuro, Graçaliz; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Fuzzy Rule-Based Classification System (FRBCS) is a well known technique to deal with classification problems. Recent studies have considered the usage of the Choquet integral and its generalizations to enhance the quality of such systems. Precisely, it was applied to the Fuzzy Reasoning Method (FRM) to aggregate the fired fuzzy rules when classify new data. On the other side, the Sugeno integral, another well known aggregation operator, obtained good results when applied to brain-computer interfaces. Those facts led to the present study in which we consider the Sugeno integral in classification problems. That is, the Sugeno integral is applied in the FRM of a widely used FRBCS and its performance is analyzed over 33 different datasets from the literature. In order to show the efficiency of this new approach, the obtained results are also compared to past studies involving the application of different aggregation functions. Finally, we perform a statistical analysis of the application.
Open Access
Aprender matemáticas: ¿qué enseñan los niños con discapacidad intelectual a los maestros en formación?
(Universidad de Zaragoza, 2019-05-14) Cogolludo, José Ignacio; García Catalán, Olga Raquel; Gil Clemente, Elena; Lizasoain Iriso, María Inmaculada; Millán Gasca, Ana; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2
La actitud con la que los maestros de Primaria afrontan su tarea como profesores de matemáticas tiene más que ver con sus experiencias previas como alumnos de la disciplina que con los contenidos que han aprendido durante las asignaturas de didáctica de las matemáticas en los Grados de Educación. Esta cuestión tiene un impacto sobre la instrucción matemática posterior de los niños, que se amplifica en el caso de los que tienen necesidades educativas especiales y conduce a emprender vías poco eficaces. Nuestro objetivo es trasladar a los estudiantes prácticas positivas, en forma de experiencia, llevadas a cabo con niños con discapacidad intelectual que puedan iluminarles sobre la forma de aprender de cualquier niño. Prácticas basadas por una parte en un enfoque histórico que propone una integración de aritmética y geometría elementales y por otra parte en el modelo desarrollado en Singapur para la resolución de problemas.
Open Access
Assessing the impact of physicians' behavior variability on performance indicators in emergency departments: an agent-based model
(IEEE, 2025-01-20) Baigorri Iguzquiaguirre, Miguel; Cildoz Esquíroz, Marta; Mallor Giménez, Fermín; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
In emergency departments (EDs), traditional simulation models often overlook the variability in physician practice, assuming uniform service provision. Our study introduces a hybrid agent-based discrete-event simulation (AB-DES) model to capture this variability. Through simulation scenarios based on real ED data, we assess the impact of physician behavior on key performance indicators such as patient waiting times and physician stress levels. Results show significant variability in both individual physician performance and average metrics across scenarios. By integrating physician agent modeling, informed by literature from medical and workplace psychology, our approach offers a more nuanced representation of ED dynamics. This model serves as a foundation for future developments towards digital twins, facilitating real-time ED management. Our findings emphasize the importance of considering physician behavior for accurate performance assessment and optimization.
Open Access
Automatic detection of high-voltage power lines in LiDAR surveys using data mining techniques
(Springer, 2020) Chasco Hernández, Daniel; Sanz Delgado, José Antonio; García Morales, Víctor; Álvarez-Mozos, Jesús; Ingeniería; Estadística, Informática y Matemáticas; Ingeniaritza; Estatistika, Informatika eta Matematika
The correct classification of power lines in LiDAR point clouds has attracted the interest of the mapping community in the last years. The objective of this research is the detection and automatic extraction of high-voltage transmission lines from LiDAR data using data mining techniques. With this aim, a Single Photon LiDAR (SPL) survey acquired over the region of Navarre (Spain) in 2017 was used, with a mean point density of 14 pt/m2. Different data mining techniques were evaluated, including decision trees (C4.5 and CART) and ensemble learning algorithms (Random Forests, Bagging and AdaBoost). Fifteen test sites were studied corresponding to areas with high-voltage power lines over different conditions regarding the underlying vegetation and topography. For these sites 92,104 LiDAR points were identified as power lines and more than 4M points as not power lines using existing cartography. This dataset was randomly split in train and test sets and then balanced two obtain a similar amount of data for the two classes. The results obtained show the importance of balancing the training data with improvements in accuracy of ~10% with respect to the imbalanced case. Accuracies higher than 87% were obtained in all balanced cases, with particularly successful results for ensemble learning techniques, being AdaBoost the technique with the highest accuracy 91%. These results suggest that the combination of SPL surveys and data mining tools can be successfully used for the operational mapping of high voltage power lines.
Open Access
Autonomous robot for construction stake out
(2021) Zaratiegui Fernández, Javier ignacio; Dios Ursúa, Carlos Juan de; Marzo Pérez, Asier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Gobierno de Navarra / Nafarroako Gobernua
Design, develop and commercial deployment of an autonomous marking device for construction stake out.
Open Access
Avatarians: playing with your friends' data
(Association for Computing Machinery, 2012) Marzo Pérez, Asier; Ardaiz Villanueva, Óscar; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Gobierno de Navarra / Nafarroako Gobernua
This article describes a new game mechanic called Game Entity Social Mapping (GESM) based on using social networking data fetched from a remote site about the player and his contacts to create characters, items or scenarios. A preliminary evaluation consisting of applying this mechanic to three different games was conducted. A small number of users tested those games to measure the enjoyment and learning about their contacts information.
Open Access
Bargaining for the last mile cost and environmental preferences of stakeholders: an economic experiment
(Elsevier, 2025-01-09) Denant-Boemont, Laurent; Faulín Fajardo, Javier; Hammiche, Sabrina; Serrano Hernández, Adrián; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
We aim at studying how environmental preferences matter when consumers negotiate with sellers in order to contract for delivery at home. To do that, we build an economic laboratory experiment where pairs of participants bargain for choosing either the click-and-collect option, which is free for consumer but implies for him private transportation costs, or the delivery-at-home option, which is pricey for him, but externalize transportation cost to the seller. In addition, in our game, transportation triggers environmental costs that are borne by both partners. We have 4 different treatments: The first one, as a benchmark, corresponds to an ultimatum bargaining game about the last mile cost with environmental costs. In the second one, we deliver a message about environmental impacts of transportation to the buyer, whereas, in the third one, the same message is delivered to the seller. The last one is a control where the message is delivered to both partners. The preliminary results (which included 178 participants) show that the average delivery price proposed by sellers is below Nash equilibrium price but above the "behavioral price" and that acceptance rates of seller's proposals by buyers are quite high.
Open Access
Bayesian modeling approach in Big Data contexts: an application in spatial epidemiology
(IEEE, 2020) Orozco Acosta, Erick; Adin Urtasun, Aritz; Ugarte Martínez, María Dolores; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Estadística, Informática y Matemáticas
In this work we propose a novel scalable Bayesian modeling approach to smooth mortality risks borrowing information from neighbouring regions in high-dimensional spatial disease mapping contexts. The method is based on the well-known divide and conquer approach, so that the spatial domain is divided into D subregions where local spatial models can be fitted simultaneously. Model fitting and inference has been carried out using the integrated nested Laplace approximation (INLA) technique. Male colorectal cancer mortality data in the municipalities of continental Spain have been analyzed using the new model proposals. Results show that the new modeling approach is very competitive in terms of model fitting criteria when compared with a global spatial model, and it is computationally much more efficient.