FCH2-Artigos (em revistas ou actas indexadas)
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Percorrer FCH2-Artigos (em revistas ou actas indexadas) por Objetivos de Desenvolvimento Sustentável (ODS) "09:Indústria, Inovação e Infraestruturas"
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- Aprendizado por transferência para correção automática de redaçãoPublication . Silveira, Igor Cataneo; Ribeiro, Eugénio; Mamede, Nuno; Baptista, JorgeA tarefa de Correção Automática de Redação tem despertado crescente interesse na ´área de processamento de texto em português. Entre os conjuntos de dados disponíveis, destaca-se um corpus de redações narrativas produzidas por alunos do 5º ao 9º ano do ensino fundamental no Brasil. Essas redações são avaliadas segundo quatro competências: registro formal, coerência temática, estrutura retórica narrativa e coesão textual. Este trabalho explora a criação de um sistema baseado em conhecimentos derivados de outro dataste (desenvolvido com base em textos produzidos para o ENEM) e de outras tarefas (cálculo de complexidade textual e análise de legibilidade). O sistema desenvolvido combina modelos neurais, características (features) curadas calculadas por programas de análise textual e seleção de fatures em um modelo de Aprendizado em Dois Estágios. Com isso, foi possível elevar a performance em relação ao estado da-arte, nomeadamente, em 9% para a primeira competência, 5,5% para a terceira e 8,9% para a quarta.
- Coupling geometric morphometrics and machine learning for mandibular sex estimation in late pleistocene and late modern populationsPublication . Godinho, Ricardo Miguel; Crevecoeur, Isabelle; Garcia, Susana; Whiting, Rebecca; Aramendi, JuliaAccurate sex estimation is crucial for studying both modern and ancient human populations, yet methods are often limited to well-preserved skeletons. Here, we combine Geometric Morphometrics (GM) and Machine Learning (ML) to assess mandibular sexual dimorphism and classify sex across a wide chronological and geographic range to bracket the potential of this approach. Sixty-seven individuals from the modern, identified Luis Lopes collection (Portugal) and 18 Late Pleistocene individuals from Jebel Sahaba (Sudan) were surface scanned. Anatomical landmark coordinates were extracted and analyzed with GM, and ML models were trained on a subset of the modern sample to predict sex in both the remaining modern individuals and the Late Pleistocene specimens. GM revealed significant sexual dimorphism in all samples, and ML achieved high intrapopulation classification accuracy. However, predictions were less reliable when applied across the temporally and geographically distant Jebel Sahaba population, reflecting interpopulation differences in mandibular size and shape. These results demonstrate that while GM-ML approaches are powerful tools for sex estimation within populations, caution is required when extending models to other populations.
- A deep regression model with low-dimensional feature extraction for multi-parameter manufacturing quality predictionPublication . Deng, Jun; Bai, Yun; Li, ChuanManufacturing quality prediction can be used to design better parameters at an earlier production stage. However, in complex manufacturing processes, prediction performance is a_ected by multi-parameter inputs. To address this issue, a deep regression framework based on manifold learning (MDRN) is proposed in this paper. The multi-parameter inputs (i.e., high-dimensional information) were firstly analyzed using manifold learning (ML), which is an e_ective nonlinear technique for low-dimensional feature extraction that can enhance the representation of multi-parameter inputs and reduce calculation burdens. The features obtained through the ML were then learned by a deep learning architecture (DL). It can learn su_cient features of the pattern between manufacturing quality and the low-dimensional information in an unsupervised framework, which has been proven to be e_ective in many fields. Finally, the learned features were inputted into the regression network, and manufacturing quality predictions were made. One type (two cases) of machinery parts manufacturing system was investigated in order to estimate the performance of the proposed MDRN with three comparisons. The experiments showed that the MDRN overwhelmed all the peer methods in terms of mean absolute percentage error, root-mean-square error, and threshold statistics. Based on these results, we conclude that integrating the ML technique for dimension reduction and the DL technique for feature extraction can improve multi-parameter manufacturing quality predictions.
- Digital technologies and public policies applied to green citiesPublication . Sousa, Maria JoséDigital technologies and public policies are fundamental for cities in defining their urban greening strategies, and the main goal of this research is to identify the applied digital technologies and the public policy dimensions implemented at the national level by the member states to promote urban greening in the literature and official documents. The methodology used is a systematic literature review (based on international studies), a Delphi study with experts, and a policy analysis, aiming to understand how the Portuguese government has implemented policies and identify the main technologies applied to urban greening. The main findings regard (i) the focus on the interaction between actors in policymaking; (ii) interpretive approaches used to examine the application of technologies in urban greening problems; and (iii) how policies reflect the social construction of ‘problems’. The research focuses on how policy analysis provides a powerful tool that can be used to understand the technologies, actions, interests, and political contexts underpinning policy decisions. The main lessons learned from this research are that urban greening can benefit urban centers together with the non-urban environment on which they have a functional impact, such as agricultural hinterland areas, forest spaces around the cities, and the rural–urban interfaces. Initiatives for urban greening are designed to enhance cross-border coordination, complementarities, flexibility, productivity, and access to the main international markets and territories.
- Discovering entrepreneurship competencies through problem-based learning in higher education studentsPublication . Sousa, Maria José; Costa, Joana MartinhoThe increase in student engagement in the learning process has driven educators to use more dynamic pedagogical methodologies. Several studies have shown evidence of increased interest in learning when real-world problems are integrated into the learning environment. This paper presents the competencies developed by higher education students through application of the problem-based learning (PBL) methodology in higher education courses. The research begins with the identification of a set of competencies developed by higher education students in other studies developed and reported in the last five years and includes them in a survey to analyze the level of development of those competencies when problem-based learning is applied in university courses. To identify the competencies developed by applying the problem-based learning methodology, the research employed a document analysis and a survey of the students that participated in the experimental application. The research questions “What are the competencies developed by students in problem-based learning?” and “Are the competencies identified by the students sufficiently learned in universities?” guided the study. The competencies found by the students were identified through a questionnaire given as an online survey to 76 students. The key outcome of the research is the identification in the bachelor courses of the competencies perceived as essential by students participating in the application of PBL in terms of their advancement.
- Education and language on instagram: 1000 influencers in Spain and PortugalPublication . Domínguez Martín, Rosa; Novoa Fernández, OliviaEducation today involves leveraging virtual environments to eliminate spatiotemporal barriers, democratizing teaching and access to knowledge. Social media enhance the dissemination and interactive learning in various fields. This research focuses on educational profiles, examining those dedicated to languages. This study analyses the 1000 most influential profiles in the “education” category on the social media platform Instagram: 500 from Spain and 500 from Portugal. The results from the sample obtained for both countries are compared, analysing the findings and reflecting on the pedagogical implications they entail.
- Gamification on mathematics engagement and motivation in secondary school and higher education: a systematic review and meta-analysisPublication . Ratinho, Elias; Figueiredo, Mauro; Estêvão, Maria Dulce da Mota Antunes de Oliveira ; Faísca, Luís; Martins, CátiaThis systematic review and meta-analysis examined the effects of gamification on students’ motivation and engagement in mathematics at the secondary and higher education levels. A literature search (April 2025) followed by an updated search (November 2025) across ten databases identified 45 studies for qualitative synthesis and 11 for meta-analysis. The review followed PRISMA 2020 guidelines with a pre-registered protocol, and study quality was appraised with the Mixed Methods Appraisal Tool. Meta-analytic results using a three-level Correlated and Hierarchical Effects model with robust variance estimation showed a significant small-to-moderate positive effect on motivation (g = .383, 95% CI [.11, .66], p = .0218). Motivation was assessed more consistently than engagement that could not be included in the meta-analysis due to the lack of validated measures. The systematic review indicates that gamification supports motivation and engagement, with only four studies reporting negative effects. Most interventions used digital platforms (e.g., Kahoot!; Classcraft) and common game elements such as points, leaderboards and instant feedback. Overall, gamification appears promising for enhancing motivation and engagement in mathematics when designs are aligned with students’ needs, balancing competition with mastery and cooperation. Therefore, educators should limit excessive competition and prioritize personal progress and cooperative tasks that foster social interaction. Future studies should employ validated measures, larger samples, and examine both motivation and engagement to strengthen the evidence base and guide effective implementation in education.
- Special Issue: phenolic profiling and antioxidant capacity in agrifood productsPublication . Rodríguez Solana, Raquel; Pereira-Caro, Gema; Moreno-Rojas, José ManuelPhenolic compounds are secondary plant metabolites known to be one of the most important sources of natural antioxidants in the human diet. These compounds play important roles in long-term health and reducing the risks of chronic and degenerative diseases. Apart from the biological capacities shown by phenolics in in-vivo and in-vitro studies, they present protective effects against the deterioration of foods and beverages because of their intrinsic nature as antioxidants. For all these reasons, the search for new sources of natural antioxidants, nutraceuticals and functional foods have been the subject of many studies in recent years. However, such compounds are potentially vulnerable to different factors of plant processing (such as light, temperature, pH, oxygen, etc.) for obtaining different food and beverage products. Consequently, substantial modifications to their structure and concentration could occur, leading to changes in their potential biological activities. Recent endeavors have placed particular importance on finding plant-processing methods and techniques for stabilizing plant-based products that do not alter their phenolic content and therefore their antioxidant and other biological activities. This Special Issue aims to bring together the most recent work, on the one hand, on the development of new functional food and nutraceutical products with high phenolic content and antioxidant potential, and on the other hand, on the impact that conventional and advanced food processing technologies [e.g., pulsed electric fields (PEF), pulsed-light (PL), ultraviolet (UV)-light; high pressure processing or high hydrostatic pressure (HPP/HHP); ultrasound; extrusion technology, etc.] have on the phenolic and bioactivity characteristics of industrial foods.
- Spheritivity, a hybrid immersive VR Art collectionPublication . Olivero, Lucas FabianSpheritivity is a collection of handmade immersive art exploring the influence of hybrid (physical/digital) perspective artworks for boosting artists’ creativity. Spheritivity exposes applications of Hybrid Immersive Art and the wide range of possibilities that perspective (as knowledge) can offer to artists, from the mastering of geometries in space up to the creation of digital environments using the latest advancements in the field of graphic representation: spherical perspectives. Furthermore, Spheritivity is enhanced with visual paradoxes (intellectual component) and Spheri (interactive component). The visual paradoxes are Escher-like visual games, such as never-ending stairs, non-orientable surfaces, etc., which Spheritivity upgrade to a never-ending canvas (via digital technology) and considering all vanishing points around the observer (via spherical perspectives). In turn, the installation Spheri uses body tracking via the machine learning library MediaPipe, and it provides Spheritivity with an interactive framework for visitors and artists to discover the potential and applications of VR environments created from spherical perspectives.