Articles de revista
http://hdl.handle.net/2117/188416
2024-03-29T15:09:28Z
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Measuring motivation from the Virtual Learning Environment in secondary education
http://hdl.handle.net/2117/404684
Measuring motivation from the Virtual Learning Environment in secondary education
Aluja Banet, Tomàs; Sancho Samsó, María Ribera; Vukic, Ivan
The increase of student’s disengagement is a problem in many developed countries’ educational systems. This paper presents our approach on how the usage of VLEs (Virtual Learning Environments) can be traced and used to enhance the teaching quality so as to improve engagement. We focus our work on secondary education. The question is not to predict the performance of students, from the collected data, which is always controversial; or just define a set of pre-established metrics, obtained from the digital data contained into the VLE, and monitor them, indirectly inducing an assessment regime. The aim is to look beyond the traces left by students and to measure the motivation of a student in a particular task, of a given subject, and in a specific day. For this purpose, we rely on the psychometric theory of measurementto build a composite index of motivation and we embed itinto a Learning Analytics system. The ultimate goal of this system is to provide teachers and stakeholders with objective and accurate (quasi) real time information about students’ motivation for learning, and hence adequately adapt and personalize the teaching methodologies and strategies in classrooms. The approach is general and can also be used in tertiary education for training students and researchers in High Performance and Data Intensive Computing.
2024-03-15T09:23:02Z
Aluja Banet, Tomàs
Sancho Samsó, María Ribera
Vukic, Ivan
The increase of student’s disengagement is a problem in many developed countries’ educational systems. This paper presents our approach on how the usage of VLEs (Virtual Learning Environments) can be traced and used to enhance the teaching quality so as to improve engagement. We focus our work on secondary education. The question is not to predict the performance of students, from the collected data, which is always controversial; or just define a set of pre-established metrics, obtained from the digital data contained into the VLE, and monitor them, indirectly inducing an assessment regime. The aim is to look beyond the traces left by students and to measure the motivation of a student in a particular task, of a given subject, and in a specific day. For this purpose, we rely on the psychometric theory of measurementto build a composite index of motivation and we embed itinto a Learning Analytics system. The ultimate goal of this system is to provide teachers and stakeholders with objective and accurate (quasi) real time information about students’ motivation for learning, and hence adequately adapt and personalize the teaching methodologies and strategies in classrooms. The approach is general and can also be used in tertiary education for training students and researchers in High Performance and Data Intensive Computing.
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An efficient greedy heuristic for the real-time train platforming problem
http://hdl.handle.net/2117/400851
An efficient greedy heuristic for the real-time train platforming problem
García Ródenas, Ricardo; López García, Maria Luz; Cadarso Morga, Luis; Codina Sancho, Esteve
This paper focuses on a special class of real-time railway traffic management problem: efficiently reallocating trains to platforms at stations in case of slight schedule changes or major disruptions. The need for a real-time response with a high level of quality makes this problem particularly challenging.
To address this issue, the authors propose a mesoscopic approach that involves preprocessing the data to determine feasible routes and other disruption parameters. They develop a greedy interchange heuristic to solve the mesoscopic real-time train platforming problem, providing high-quality routing and timing decisions within the computational time constraints of real-time management problems.
The performance of the proposed heuristic is analyzed through case studies using both synthetic and realistic scenarios from the Spanish railway traffic system. For large instances of the Atocha-Cercanías station case study, the solutions are generated from 5 to 10 times faster by the heuristic algorithm than by the exact method. The authors conclude that the proposed heuristic is a promising solution for real-time train platforming problems.
© 2023 The Author(s). This is an open access article under the CC BY-NC license
2024-02-02T11:01:44Z
García Ródenas, Ricardo
López García, Maria Luz
Cadarso Morga, Luis
Codina Sancho, Esteve
This paper focuses on a special class of real-time railway traffic management problem: efficiently reallocating trains to platforms at stations in case of slight schedule changes or major disruptions. The need for a real-time response with a high level of quality makes this problem particularly challenging.
To address this issue, the authors propose a mesoscopic approach that involves preprocessing the data to determine feasible routes and other disruption parameters. They develop a greedy interchange heuristic to solve the mesoscopic real-time train platforming problem, providing high-quality routing and timing decisions within the computational time constraints of real-time management problems.
The performance of the proposed heuristic is analyzed through case studies using both synthetic and realistic scenarios from the Spanish railway traffic system. For large instances of the Atocha-Cercanías station case study, the solutions are generated from 5 to 10 times faster by the heuristic algorithm than by the exact method. The authors conclude that the proposed heuristic is a promising solution for real-time train platforming problems.
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Specification and description language models automatic execution in a high-performance environment
http://hdl.handle.net/2117/399767
Specification and description language models automatic execution in a high-performance environment
Fonseca Casas, Pau; Romanowska, Iza; Garcia Subirana, Joan
Specification and Description Language (SDL) is a language that can represent the behavior and structure of a model completely and unambiguously. It allows the creation of frameworks that can run a model without the need to code it in a specific programming language. This automatic process simplifies the key phases of model building: validation and verification. SDLPS is a simulator that enables the definition and execution of models using SDL. In this paper, we present a new library that enables the execution of SDL models defined on SDLPS infrastructure on a HPC platform, such as a supercomputer, thus significantly speeding up simulation runtime. Moreover, we apply the SDL language to a social science use case, thus opening a new avenue for facilitating the use of HPC power to new groups of users. The tools presented here have the potential to increase the robustness of modeling software by improving the documentation, verification, and validation of the models.
2024-01-18T08:08:46Z
Fonseca Casas, Pau
Romanowska, Iza
Garcia Subirana, Joan
Specification and Description Language (SDL) is a language that can represent the behavior and structure of a model completely and unambiguously. It allows the creation of frameworks that can run a model without the need to code it in a specific programming language. This automatic process simplifies the key phases of model building: validation and verification. SDLPS is a simulator that enables the definition and execution of models using SDL. In this paper, we present a new library that enables the execution of SDL models defined on SDLPS infrastructure on a HPC platform, such as a supercomputer, thus significantly speeding up simulation runtime. Moreover, we apply the SDL language to a social science use case, thus opening a new avenue for facilitating the use of HPC power to new groups of users. The tools presented here have the potential to increase the robustness of modeling software by improving the documentation, verification, and validation of the models.
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A mathematical model for the COVID-19 pandemic in Tokyo through changing point calculus
http://hdl.handle.net/2117/397150
A mathematical model for the COVID-19 pandemic in Tokyo through changing point calculus
Martínez Vázquez, Laura; Fonseca Casas, Pau
The great social and economic impact that the COVID-19 pandemic has had on a global level has encouraged the development of new mathematical models that make it possible to better manage this and future pandemics. Here, we propose an extension of the classical epidemiological compartmental model SIR, the SEIAMD model (Susceptible–Exposed–Identified–Asymptomatic–iMmunized–Deceased), which considers the appearance of new virus variants, the use of vaccines, the existence of nonidentified asymptomatic individuals, and the loss of immunity acquired by infection or vaccination. Using an optimization model coded in Python that allows us to determine the change points that represent different behaviors of infected people, the SEIAMD model calculates, from official data, the different effective contact rates that were observed during the first seven waves of the COVID-19 pandemic in Tokyo due to the application of Non-Pharmaceutical Interventions (NPIs) and social habits. The closeness of the results obtained with our model and the real data, as well as the accuracy of predictions and observations, confirm the suitability of our model for studying the evolution of the COVID-19 pandemic in Tokyo.
2023-11-28T12:49:49Z
Martínez Vázquez, Laura
Fonseca Casas, Pau
The great social and economic impact that the COVID-19 pandemic has had on a global level has encouraged the development of new mathematical models that make it possible to better manage this and future pandemics. Here, we propose an extension of the classical epidemiological compartmental model SIR, the SEIAMD model (Susceptible–Exposed–Identified–Asymptomatic–iMmunized–Deceased), which considers the appearance of new virus variants, the use of vaccines, the existence of nonidentified asymptomatic individuals, and the loss of immunity acquired by infection or vaccination. Using an optimization model coded in Python that allows us to determine the change points that represent different behaviors of infected people, the SEIAMD model calculates, from official data, the different effective contact rates that were observed during the first seven waves of the COVID-19 pandemic in Tokyo due to the application of Non-Pharmaceutical Interventions (NPIs) and social habits. The closeness of the results obtained with our model and the real data, as well as the accuracy of predictions and observations, confirm the suitability of our model for studying the evolution of the COVID-19 pandemic in Tokyo.
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Modelling influenza and SARS-CoV-2 interaction: analysis for Catalonia region
http://hdl.handle.net/2117/397140
Modelling influenza and SARS-CoV-2 interaction: analysis for Catalonia region
Fonseca Casas, Pau; García Carrasco, Víctor; Garcia Subirana, Joan
The aim is to analyse that, during the current pandemic situation, the reduction in the number of cases of influenza suggests that the non-pharmaceutical interventions (NPIs) applied to contain the expansion of SARS-CoV-2 also affect the influenza expansion. We analyse the interaction of influenza and SARS-CoV-2 spread based on an extended SEIRD model for the Catalonia region in Spain. We show that the dynamic evolution of the spread of SARS-CoV-2 and influenza generates a small interference. This interference causes a small reduction in the number of cases of seasonal influenza, reducing its expansion over the population. Other elements like the face mask mandates, social distancing and hand cleaning boost the reduction in both expansions. Influenza expansion will present a small reduction in the number of cases due to the interaction with SARS-CoV-2 expansion but mainly because the NPIs applied to the population.
The version of record is available online at: http://dx.doi.org/10.1177/17483026231186012
2023-11-28T11:46:41Z
Fonseca Casas, Pau
García Carrasco, Víctor
Garcia Subirana, Joan
The aim is to analyse that, during the current pandemic situation, the reduction in the number of cases of influenza suggests that the non-pharmaceutical interventions (NPIs) applied to contain the expansion of SARS-CoV-2 also affect the influenza expansion. We analyse the interaction of influenza and SARS-CoV-2 spread based on an extended SEIRD model for the Catalonia region in Spain. We show that the dynamic evolution of the spread of SARS-CoV-2 and influenza generates a small interference. This interference causes a small reduction in the number of cases of seasonal influenza, reducing its expansion over the population. Other elements like the face mask mandates, social distancing and hand cleaning boost the reduction in both expansions. Influenza expansion will present a small reduction in the number of cases due to the interaction with SARS-CoV-2 expansion but mainly because the NPIs applied to the population.
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Applying data analytics to analyze activity sequences for an assessment of fragmentation in daily travel patterns: a case study of the metropolitan region of Barcelona
http://hdl.handle.net/2117/394764
Applying data analytics to analyze activity sequences for an assessment of fragmentation in daily travel patterns: a case study of the metropolitan region of Barcelona
Montero Mercadé, Lídia; Mejía-Dorantes, Lucía; Barceló Bugeda, Jaime
Sequence analysis is a robust methodological approach that has gained popularity in various fields, including transportation research. It provides a comprehensive way to understand the dynamics and patterns of individual behaviors over time. In the context of the Metropolitan Region of Barcelona, applying sequence analysis to mobility surveys offers valuable insights into the sequencing of travel activities and modes, shedding light on the complex interrelationship between individuals and their travel choices and the built environment. Sequence analysis allows us to examine travel behaviors as dynamic processes and reveal the underlying structure and evolution of travel patterns over a day. Here, we describe a data analytics approach that enables the identification of common travel patterns and the exploration of variations across demographic groups or geographical regions. We propose a method for discovering similarities in travel behavior segments from diaries included in travel surveys in order to refine transport policies for selected segments. Unfortunately, the data collected by the authorities in the analyzed travel surveys do not include family structure, which seems critical in explaining the segmentation of travel sequences.
2023-10-10T07:30:16Z
Montero Mercadé, Lídia
Mejía-Dorantes, Lucía
Barceló Bugeda, Jaime
Sequence analysis is a robust methodological approach that has gained popularity in various fields, including transportation research. It provides a comprehensive way to understand the dynamics and patterns of individual behaviors over time. In the context of the Metropolitan Region of Barcelona, applying sequence analysis to mobility surveys offers valuable insights into the sequencing of travel activities and modes, shedding light on the complex interrelationship between individuals and their travel choices and the built environment. Sequence analysis allows us to examine travel behaviors as dynamic processes and reveal the underlying structure and evolution of travel patterns over a day. Here, we describe a data analytics approach that enables the identification of common travel patterns and the exploration of variations across demographic groups or geographical regions. We propose a method for discovering similarities in travel behavior segments from diaries included in travel surveys in order to refine transport policies for selected segments. Unfortunately, the data collected by the authorities in the analyzed travel surveys do not include family structure, which seems critical in explaining the segmentation of travel sequences.
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Axisymmetric smoothed particle magnetohydrodynamics
http://hdl.handle.net/2117/393845
Axisymmetric smoothed particle magnetohydrodynamics
García Senz, Domingo; Wissing, Robert; Cabezón Gómez, Rubén Martín; Vurgun, Eda; Linares Herreros, María Paz
Many astrophysical and terrestrial scenarios involving magnetic fields can be approached in axial geometry. Although the smoothed particle hydrodynamics (SPH) technique has been successfully extended to magneto-hydrodynamics (MHD), a well-verified, axisymmetric MHD scheme based on such technique does not exist yet. In this work we fill that gap in the scientific
literature and propose and check a novel axisymmetric MHD hydrodynamic code, that can be applied to physical problems which display the adequate geometry. We show that the hydrodynamic code built following these axisymmetric hypothesis is able to produce similar results than standard 3D-SPMHD codes with equivalent resolution but with much lesser computational load.
2023-09-21T12:59:37Z
García Senz, Domingo
Wissing, Robert
Cabezón Gómez, Rubén Martín
Vurgun, Eda
Linares Herreros, María Paz
Many astrophysical and terrestrial scenarios involving magnetic fields can be approached in axial geometry. Although the smoothed particle hydrodynamics (SPH) technique has been successfully extended to magneto-hydrodynamics (MHD), a well-verified, axisymmetric MHD scheme based on such technique does not exist yet. In this work we fill that gap in the scientific
literature and propose and check a novel axisymmetric MHD hydrodynamic code, that can be applied to physical problems which display the adequate geometry. We show that the hydrodynamic code built following these axisymmetric hypothesis is able to produce similar results than standard 3D-SPMHD codes with equivalent resolution but with much lesser computational load.
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Analysing gendered mobility patterns in Barcelona through spatiotemporal segmentation
http://hdl.handle.net/2117/393528
Analysing gendered mobility patterns in Barcelona through spatiotemporal segmentation
Montero Mercadé, Lídia; Mejía-Dorantes, Lucía; Barceló Bugeda, Jaime
Citizens take part in different activities to satisfy their needs, to invest in their socio-economic progress, participate in social and health activities that improve their well-being. However, activity participation is influenced by many factors in the built environment, but also individual’s attributes. Herein we analyze activity participation and travel through sequence analysis. This method explores sequences of daily activity and travel employing techniques from the sequencing of events in the life course of individuals. Studying sequences of daily episodes (each activity and each trip) considers the entire trajectory of a person’s activity during a day while at the same time considering the number of activities, order of activities in a day, and their durations jointly. We applied this method to a sample of residents in the Metropolitan Area of Barcelona (RMB) in the 2018, 2019 and 2020 EMEF Travel Surveys. The EMEF2020 deserves a particular analysis since activity patterns are expected to vary compared to pre-COVID19 spread. We have focused on that fragmentation in activity participation over the mean among persons in specific gender, age, activity and transportation mode.
2023-09-15T07:12:32Z
Montero Mercadé, Lídia
Mejía-Dorantes, Lucía
Barceló Bugeda, Jaime
Citizens take part in different activities to satisfy their needs, to invest in their socio-economic progress, participate in social and health activities that improve their well-being. However, activity participation is influenced by many factors in the built environment, but also individual’s attributes. Herein we analyze activity participation and travel through sequence analysis. This method explores sequences of daily activity and travel employing techniques from the sequencing of events in the life course of individuals. Studying sequences of daily episodes (each activity and each trip) considers the entire trajectory of a person’s activity during a day while at the same time considering the number of activities, order of activities in a day, and their durations jointly. We applied this method to a sample of residents in the Metropolitan Area of Barcelona (RMB) in the 2018, 2019 and 2020 EMEF Travel Surveys. The EMEF2020 deserves a particular analysis since activity patterns are expected to vary compared to pre-COVID19 spread. We have focused on that fragmentation in activity participation over the mean among persons in specific gender, age, activity and transportation mode.
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Modeling SARS-CoV-2 true infections in Catalonia through a digital twin
http://hdl.handle.net/2117/391910
Modeling SARS-CoV-2 true infections in Catalonia through a digital twin
Fonseca Casas, Pau; Garcia Subirana, Joan; García Carrasco, Víctor
A dynamic view of the evolution of the infections of SARS-CoV-2 in Cataloniausing a Digital Twin approach that forecasts the true infection curve ispresented. The forecast model incorporates the vaccination process, theconfinement, and the detection rate, and virtually allows to consider anynonpharmaceutical intervention, enabling to understand their effects on thedisease’s containment while forecasting the trend of the pandemic. Acontinuous validation process of the model is performed using real data andan optimization model that automatically provides information regarding theeffects of the containment actions on the population. To simplify thisvalidation process, a formal graphical language that simplifies the interactionwith the different specialists and an easy modification of the modelparameters are used. The Digital Twin of the pandemic in Catalonia provides aforecast of the future trend of the SARS-CoV-2 spread and informationregarding the true cases and effectiveness of the NPIs to control theSARS-CoV-2 spread over the population. This approach can be applied easilyto other regions and can become an excellent tool for decision-making.
This is the peer reviewed version of the following article: Fonseca, P., Garcia, J. and Garcia, V., 2023. Modeling SARS-CoV-2 true infections in Catalonia through a digital twin. Advanced theory and simulations, (2200917), which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/adts.202200917. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
2023-07-21T08:55:52Z
Fonseca Casas, Pau
Garcia Subirana, Joan
García Carrasco, Víctor
A dynamic view of the evolution of the infections of SARS-CoV-2 in Cataloniausing a Digital Twin approach that forecasts the true infection curve ispresented. The forecast model incorporates the vaccination process, theconfinement, and the detection rate, and virtually allows to consider anynonpharmaceutical intervention, enabling to understand their effects on thedisease’s containment while forecasting the trend of the pandemic. Acontinuous validation process of the model is performed using real data andan optimization model that automatically provides information regarding theeffects of the containment actions on the population. To simplify thisvalidation process, a formal graphical language that simplifies the interactionwith the different specialists and an easy modification of the modelparameters are used. The Digital Twin of the pandemic in Catalonia provides aforecast of the future trend of the SARS-CoV-2 spread and informationregarding the true cases and effectiveness of the NPIs to control theSARS-CoV-2 spread over the population. This approach can be applied easilyto other regions and can become an excellent tool for decision-making.
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Critical infrastructure awareness based on IoT context data
http://hdl.handle.net/2117/390761
Critical infrastructure awareness based on IoT context data
Vila Gómez, Marc; Sancho Samsó, María Ribera; Teniente López, Ernest; Vilajosana Guillén, Xavier
The Internet of Things (IoT) represents a powerful new paradigm for connecting and communicating with the world around us. It has the potential to transform the way we live, work, and interact with our surroundings. IoT devices are transmitting information over the Internet, most of them with different data formats, despite they may be communicating similar concepts. This often leads to data incompatibilities and makes it difficult to extract the knowledge underlying that data. Because of the heterogeneity of IoT devices and data, interoperability is a challenge, and efforts are underway to overcome this through research and standardization. While data collection and monitoring in IoT systems are becoming more prevalent, contextualizing the data and taking appropriate actions to address issues in the monitored environment is still an ongoing concern. Context Awareness is a highly relevant topic in IoT, as it aims to provide a deeper understanding of the data collected and enable more informed decision-making. In this paper, we propose a semantic ontology designed to monitor global entities in the IoT. By leveraging semantic definitions, it enables end-users to model the entire process from detection to action, including context-aware rules for taking appropriate actions. The advantages of using semantic definitions include more accurate and consistent data interpretation, which improves the overall monitoring process and enables more effective decision-making based on the collected insights. Our proposal includes semantic models for defining the entities responsible for monitoring and executing actions, as well as the elements that need to be considered for an effective monitoring process. Additionally, we provide a new definition for the components known as gateways, which enable the connection and communication between devices and the Internet. Finally, we show the benefits of our ontology by applying it to a critical infrastructure domain where a rapid response is vital to prevent accidents and malfunction of the entities.
2023-07-13T09:48:19Z
Vila Gómez, Marc
Sancho Samsó, María Ribera
Teniente López, Ernest
Vilajosana Guillén, Xavier
The Internet of Things (IoT) represents a powerful new paradigm for connecting and communicating with the world around us. It has the potential to transform the way we live, work, and interact with our surroundings. IoT devices are transmitting information over the Internet, most of them with different data formats, despite they may be communicating similar concepts. This often leads to data incompatibilities and makes it difficult to extract the knowledge underlying that data. Because of the heterogeneity of IoT devices and data, interoperability is a challenge, and efforts are underway to overcome this through research and standardization. While data collection and monitoring in IoT systems are becoming more prevalent, contextualizing the data and taking appropriate actions to address issues in the monitored environment is still an ongoing concern. Context Awareness is a highly relevant topic in IoT, as it aims to provide a deeper understanding of the data collected and enable more informed decision-making. In this paper, we propose a semantic ontology designed to monitor global entities in the IoT. By leveraging semantic definitions, it enables end-users to model the entire process from detection to action, including context-aware rules for taking appropriate actions. The advantages of using semantic definitions include more accurate and consistent data interpretation, which improves the overall monitoring process and enables more effective decision-making based on the collected insights. Our proposal includes semantic models for defining the entities responsible for monitoring and executing actions, as well as the elements that need to be considered for an effective monitoring process. Additionally, we provide a new definition for the components known as gateways, which enable the connection and communication between devices and the Internet. Finally, we show the benefits of our ontology by applying it to a critical infrastructure domain where a rapid response is vital to prevent accidents and malfunction of the entities.