2019
Autores
Carneiro, D; Novais, P; Duraes, D; Pego, JM; Sousa, N;
Publicação
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
Abstract
For the majority of students, assessment moments are associated with significant levels of stress and anxiety. While a certain amount of stress motivates the individual and improves performance, too much stress will have the contrary effect. Stress has therefore a fundamental role on student performance. It should be the educational organizations' mission to understand the underlying mechanisms that lead to performance anxiety and provide their students with the best coping tools and strategies. In the present study we analyze student behavior during e-assessment in terms of mouse dynamics. Two major behavioral patterns can be identified, based on ten features that quantify the performance of the student's interaction with the computer: (1) students who are able to sustain performance during the exam and (2) students whose performance varies significantly. Data shows that the behavior of each student during the exam correlates strongly with the time it takes the student to complete it. Several classifiers were trained that predict the completion time of each exam based on the students' interaction patterns. Two of them do it with an average error of around twelve minutes. Results show that there are still mechanisms that can be explored to better understand the complex relationship between stress, performance and human behavior, that can be used for the implementation of better stress detection, monitoring and coping strategies.
2019
Autores
Quintela, H; Carneiro, D; Ferreira, L;
Publicação
Business Intelligence and Analytics in Small and Medium Enterprises
Abstract
2019
Autores
Cunha, I; Simoes, J; Alves, A; Gomes, R; Ribeiro, A;
Publicação
AMBIENT INTELLIGENCE (AMI 2019)
Abstract
Demand for leisure activities has increased due to some reasons such as increasing wealth, ageing populations and changing lifestyles, however, the efficiency of public transport system relies on solid demand levels and well-established mobility patterns and, so, providing quality public transportation is extremely expensive in low, variable and unpredictable demand scenarios, as it is the case of non-routine trips. Better prediction estimations about the trip purpose helps to anticipate the transport demand and consequently improve its planning. This paper addresses the contribution in comparing the traditional approach of considering municipality division to study such trips against a proposed approach based on clustering of dense concentration of services in the urban space. In our case, POIs (Points of Interest) collected from social networks (e.g. Foursquare) represent these services. These trips were associated with the territory using two different approaches: 'municipalities' and 'clusters' and then related with the likelihood of choosing a POI category (Points-of-Interest). The results obtained for both geographical approaches are then compared considering a multinomial model to check for differences in destination choice. The variables of distance travelled, travel time and whether the trip was made on a weekday or a weekend had a significant contribution in the choice of destination using municipalities approach. Using clusters approach, the results are similar but the accuracy is improved and due to more significant results to more categories of destinations, more conclusions can be drawn. These results lead us to believe that a cluster-based analysis using georeferenced data from social media can contribute significantly better than a territorial-based analysis to the study of non-routine mobility. We also contribute to the knowledge of patterns of this type of travel, a type of trips that is still poorly valued and difficult to study. Nevertheless, it would be worth a more extensive analysis, such as analysing more variables or even during a larger period.
2019
Autores
Simões, J; Gomes, R; Alves, A; Bernardino, J;
Publicação
Advances in Intelligent Systems and Computing
Abstract
Mobility has become one of the most difficult challenges that cities must face. More than half of world’s population resides in urban areas and with the continuously growing population it is imperative that cities use their resources more efficiently. Obtaining and gathering data from different sources can be extremely important to support new solutions that will help building a better mobility for the citizens. Crowdsensing has become a popular way to share data collected by sensing devices with the goal to achieve a common interest. Data collected by crowdsensing applications can be a promising way to obtain valuable mobility information from each citizen. In this paper, we study the current work on the integrated mobility services exploring the crowdsensing applications that were used to extract and provide valuable mobility data. Also, we analyze the main current techniques used to characterize urban mobility. © Springer Nature Switzerland AG 2019.
2019
Autores
Lourenco, EJ; Oliva, M; Estrela, MA; Baptista, AJ;
Publicação
Proceedings - 2019 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2019
Abstract
This manuscript presents a novel framework, the Multidimensional Design Assessment Model, which encompasses a multi-criteria approach to efficiency, eco-efficiency and costs assessment for a given design system in aeronautical industry production. The framework is established by adopting Design-for-X and Multi-Layer Stream Mapping approaches, based on Lean Thinking, for efficiency assessment and adopting modules of ecoPROSYS to eco-efficiency assessment. A real case study from aeronautical sector is given to demonstrate the approach, for the assembly of aircraft structure Horizontal Tale Plane, where different results are presented and discussed for each dimension of analysis and how improvement strategies can be designed. © 2019 IEEE.
2019
Autores
Lezak, E; Ferrera, E; Rossini, R; Masluszczak, Z; Fialkowska-Filipek, M; Hovest, GG; Schneider, A; Lourenço, EJ; Baptista, AJ; Cardeal, G; Estrela, M; Rato, R; Holgado, M; Evans, S;
Publicação
Technological Developments in Industry 4.0 for Business Applications - Advances in Logistics, Operations, and Management Science
Abstract
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