Departamento de Ingeniería de Computadores, Automática y Robóticahttps://hdl.handle.net/10481/137052024-03-29T15:39:06Z2024-03-29T15:39:06ZInteractive simulations as a tool for logistics and maintenance of IFMIF-DONESBenito Fuentes, Andreahttps://hdl.handle.net/10481/899982024-03-15T07:47:17ZInteractive simulations as a tool for logistics and maintenance of IFMIF-DONES
Benito Fuentes, Andrea
Pre-configured virtual reality (VR) simulations of the logistics and maintenance processes have proven to be useful for identifying potential design issues as well as planning operations during an early design phase of facility. But VR simulations can also be used to deeply explore the feasibility of these procedures in a more interactive manner, so that we can identify potential risks and difficulty levels from early stages and study different maintenance strategies to assist the maintenance worker during these procedures. This article presents a framework to design and validate logistics and maintenance procedures in complex facilities, such as the International Fusion Materials Irradiation Facility DEMO Oriented Neutron Source (IFMIF-DONES). Our framework begins with a preparatory phase where essential information about the procedures and Computer-Aided Design (CAD) models is compiled into a comprehensive Virtualization Task Document (VTD). Differently from previous work, this VTD allows representation of parallel tasks. We implement the interactive version of the virtual environment, where the different maintenance and logistics equipment, as well as a virtual maintenance worker is controlled by the user (the person executing the interactive simulation). We have validated this interactive framework with two simulations for the installation process of the Superconducting Radio Frequency Linear accelerator (SRF Linac) modules in IFMIF-DONES. In one simulation (the automatic one), the procedures are reproduced as they are planned, while in the second simulation (the interactive one) the user freely controls the movements of the moving parts of the crane, grab and release plant equipment, move platforms, etc. Based on our simulations, the interactive version allows easier detection of potential points of collisions as well as more precise assessment of the difficulty of the tasks to be performed.
Formative evaluation and learning analytics for agile teachingMerelo Guervos, Juan Juliánhttps://hdl.handle.net/10481/898112024-03-06T07:39:35ZFormative evaluation and learning analytics for agile teaching
Merelo Guervos, Juan Julián
The agile manifesto provides a framework for software development in which customer comes first. Here we will describe a teaching experience based on agile principles that puts students at the center of a strategy that, through the use of fit learning analytics, is able to optimize the potential of a class and its individual students. We used project-based learning and formative evaluation as agile teaching best practices, evaluating student progress based on learning objectives submitted and evaluated asynchronously. The time when every objective is submitted and the time taken to pass it are the essential data points that will be leveraged to evaluate class progress, and the impact of specific measures taken to improve it, in-class or from one course to the next. Measures taken through three years with the same methodology prove that agile teaching can work, but it needs measurements for diagnosis and subsequent interventions to reach its full potential.
Low-Cost EEG Multi-Subject Recording Platform for the Assessment of Students’ Attention and the Estimation of Academic Performance in Secondary SchoolFuentes-Martínez, Víctor JuanRomero García, Samuel FranciscoLópez Gordo, Miguel ÁngelMinguillón Campos, JesúsRodríguez Álvarez, Manuelhttps://hdl.handle.net/10481/888152024-02-09T09:32:58ZLow-Cost EEG Multi-Subject Recording Platform for the Assessment of Students’ Attention and the Estimation of Academic Performance in Secondary School
Fuentes-Martínez, Víctor Juan; Romero García, Samuel Francisco; López Gordo, Miguel Ángel; Minguillón Campos, Jesús; Rodríguez Álvarez, Manuel
The level of student attention in class greatly affects their academic performance. Teachers
typically rely on visual inspection to react to students’ attention in time, but this subjective method
leads to inconsistencies across classes. Online education exacerbates the issue as students can turn off
cameras and microphones to keep their own privacy. To address this, we present a novel, low-cost
EEG-based platform for assessing students’ attention and estimating their academic performance. In a
study involving 34 secondary school students (aged 14 to 16), participants watched an academic video
and answered evaluation questions while their EEG activity was recorded using a commercial headset.
The results demonstrate a significant correlation (0.53, p-value = 0.003) between the power spectral
density (PSD) of the EEG beta band (12–30 Hz) and students’ academic performance. Additionally,
there was a notable difference in PSD-beta between high and low academic performers. These
findings encourage the use of PSD-beta for the immediate and objective assessment of both the
student attention and the subsequent academic performance. The platform offers valuable and
objective feedback to teachers, enhancing the effectiveness of both face-to-face and online teaching
and learning environments.
Intra-family links in the analysis of marital networksMerelo Guervos, Juan JuliánMolinari, M. Cristinahttps://hdl.handle.net/10481/873412024-01-26T09:34:12ZIntra-family links in the analysis of marital networks
Merelo Guervos, Juan Julián; Molinari, M. Cristina
Marriage networks, which represent the matrimonial connections between different families in a given historical and geographical milieu, rarely take into account one aspect of internal family dynamics, namely the existence of intra-family marriages. The inclusion of such marriages, represented in the graph by self-loops, is essential in order to compute more accurate measures of centrality. In this paper, we discuss various procedures for incorporating these links into the analysis, with the requirement that they be compatible with the use of already available social network analysis software. We then apply them to two historical marriage networks, one from the Republic of Venice and the other from Taiwan. By comparing centrality measures for the baseline and modified networks, we found that the most satisfactory of the proposed methods is the one that duplicates nodes of families with intra-family marriages and adds new edges that link these duplicated nodes to all the families to which the original node was connected. This procedure is computationally simple and conceptually sound, making it a useful tool for analysing marital networks.
Estimation of COVID-19 dynamics in the different states of the United States using Time-Series ClusteringRojas Ruiz, Fernando JoséValenzuela Cansino, OlgaRojas Ruiz, Ignaciohttps://hdl.handle.net/10481/872792024-01-25T11:02:45ZEstimation of COVID-19 dynamics in the different states of the United States using Time-Series Clustering
Rojas Ruiz, Fernando José; Valenzuela Cansino, Olga; Rojas Ruiz, Ignacio
Estimation of COVID-19 dynamics and its evolution is a multidisciplinary effort, which requires the unification of heterogeneous disciplines (scientific, mathematics, epidemiological, biological/bio-chemical, virologists and health disciplines to mention the most relevant) to work together in a better understanding of this pandemic. Time series analysis is of great importance to determine both the similarity in the behavior of COVID-19 in certain countries/states and the establishment of models that can analyze and predict the transmission process of this infectious disease. In this contribution, an analysis of the different states of the United States will be carried out to measure the similarity of COVID-19 time series, using dynamic time warping distance (DTW) as a distance metric. A parametric methodology is proposed to jointly analyze infected and deceased persons. This metric allows to compare time series that have a different time length, making it very appropriate for studying the United States, since the virus did not spread simultaneously in all the states/provinces. After a measure of the similarity between the time series of the states of United States was determined, a hierarchical cluster was created, which makes it possible to analyze the behavioral relationships of the pandemic between different states and to discover interesting patterns and correlations in the underlying data of COVID-19 in the United States. With the proposed methodology, nine different clusters were obtained, showing a different behavior in the eastern zone and western zone of the United States. Finally, to make a prediction of the evolution of COVID-19 in the states, Logistic, Gompertz and SIR model was computed. With these mathematical model it is possible to have a more precise knowledge of the evolution and forecast of the pandemic.