Project List

The AgroPro project aspires to provide the agriculture professionals acquaintance with the available airborne technology & software as well as with UAV international legislation & regulations. The acquaintance with mission planning & the available open source and commercial tools.

The aim of the SmartVitiNet project is to (a) scale-up, pilot and bring to the market an innovative holistic phytosanitary and plant protection system based on the use of unmanned aerial vehicles, new observational platforms and new ready to use sensors, and (b) establish a Competence Center for Precision Viticulture. The proposed research will utilize complementary knowledge, experiences and infrastructure of all partners to achieve the proposed innovative results. The sustainability of the undertaking will be ensured thanks to the establishment of the Competence Centre for Precision Viticulture which aims to upskill sector professionals, create expert networks, facilitate permanent flows of knowledge transfer between academia, innovative SMEs, viticulture professionals and regional authorities to increase sector competitiveness, while enacting EU environmental policies, reducing sector health impact and risks of food pollution.

EMPOWER will focus on education for children with neurodevelopmental disorders (NDDs). Children with NDDs can experience difficulties with language and speech, motor skills, behaviour, memory, learning, or other neurological functions. Technological solutions that can respond to such individual needs have the potential to both improve the quality and inclusiveness of the education of these children and support teachers in carrying out their educational vocation. From a technological perspective, the challenge is not only to deliver the resulting educational program but also to do so accurately and to the benefit of the child. From an ethical perspective, several challenges come together in the trade-off between the potential educational benefits and the necessity to process relevant information regarding the children via measurements and algorithms that shape the educational program. In the proposed AI regulations of the EU (Artificial Intelligence Act, EC/2021), this is a high- risk endeavour. Together, this application domain is therefore a challenging one in that it unites sensitive cases of the obstacles one is likely to encounter in digitizing education. Addressing these challenges is therefore also an opportunity to shed more light on the future of technology and AI in education as the ability to address these challenges in their extreme form will lead to insights that are relevant more generally.

Bayesian structural equation modeling (BSEM) is receiving increasing interest mainly due to its capability of solving some of the issues found in the mainstream frequentist approach (e.g., nonconvergence, Heywood cases, sample size, inadmissible solutions) and because it allows fitting complex models that classical maximum likelihood methods might struggle to fit (Merkle & Rosseel, 2018). However, BSEM can be computationally intensive. In fact, the computational cost of the Bayesian analysis harmed the more frequent use of Bayesian statistics. The use of Bayesian methods has improved, mainly due to the computational advances, presenting researchers with more flexible, and powerful tools. Nowadays, Bayesian analysis is an established branch of methodology for model estimation (van de Schoot et al., 2021). In part, this is due to two aspects: the increased popularity of Bayesian methodology, and the advent of Markov chain Monte Carlo (MCMC) methods (Depaoli, 2021). Bayesian statistics benefit from MCMC methods since Bayesian analysis heavily relies on multidimensional integration. MCMC comprises a set of computational algorithms that can help to solve high‐dimensional, and complex modeling situations (South et al., 2022). MCMC can help Bayesian statistics by — for example — reconstructing the posterior distribution (Depaoli, 2021). MCMC can benefit greatly from a parallel computing environment, which allows to perform extensive calculations simultaneously. The advances in consumer computer hardware make parallel computing widely available to most users. Many computer video graphic cards support parallel computing. The use of the graphics processing units (GPU) usually provide meaningful gains in terms of performance (Češnovar et al., 2019). There is no doubt that parallel computing is of deep importance, the use of this technology can greatly improve several fields of statistics. One of those fields is BSEM, as so, the objective of this project is to understand th...

Despite the Union’s effort to fight against online hate speech (OHS), several reports showed an increase in OHS during 2020-21. The current pandemic provided a context for increased scapegoating and stigmatization, and minority groups are disproportionally targets of hatred discourse. OHS is a persistent threat to the Union’s values and there is a need for more knowledge on its content, detection and countering, as highlighted in the current Call. Portugal, as other member states, has seen an escalation of hate speech against immigrants, racial/ethnic groups, and LGBTIQ communities. However, there is no systematized knowledge nor tools designed to detect, monitor and prevent OHS against these communities. Our project aims at addressing this need, offering a comprehensive, participatory and culturally sensitive approach to analyse, detect, and counter, direct and indirect OHS in Portuguese language.