Os contributos do texto literário para o ensino-aprendizagem de PLE: elaboração de uma proposta de didatização de um conto de Sophia de Mello Breyner Andresen

Dissertação de mestrado em Português Língua Não Materna (PLNM) – Português Língua Estrangeira (PLE) e Língua Segunda (PL2)

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Potencialidades de elementos pré-fabricados de madeira na reabilitação

Dissertação de mestrado em Construção e Reabilitação Sustentáveis

Otimização com restrições de complementaridade: algoritmos e aplicações

Tese de Doutoramento em Engenharia Industrial e de Sistemas (PDEIS)

Média digitais e lusofonia

É meu propósito, neste texto, discutir a Lusofonia através de um conjunto de conceitos ligados aos média digitais interativos, rompendo os limites da ligação entre produtores e recetores de conteúdos nas relações multi, inter e transculturais. Vou insistir na ideia de que os média digitais interativos significam novas práticas nas relações interculturais: por um lado, formas digitais interativas de comunicação intercultural e, por outro, textualidades multimodais (“hipertextualidades”) na produção do sentido lusófono. O percurso que proponho tem um cariz preponderantemente epistemológico. Tomando a Lusofonia como figura de interesse geoestratégico e cultural e os média digitais como objeto de análise, é minha preocupação fundamental interrogar a inovação, a hibridez e a interatividade digitais e verificar de que modo se articulam com as relações multi, inter e transculturais. Palavras-chave: Lusofonia, comunicação intercultural, média digitais interativos, comunicação multimodal, tecnologia da comunicação, Museu da Língua Portuguesa em São Paulo, Museu Virtual da Lusofonia.

Pointlike reducibility of pseudovarieties of the form V*D

In this paper, we investigate the reducibility property of semidirect products of the form V *D relatively to (pointlike) systems of equations of the form x1 =...= xn, where D denotes the pseudovariety of definite semigroups. We establish a connection between pointlike reducibility of V*D and the pointlike reducibility of the pseudovariety V. In particular, for the canonical signature consisting of the multiplication and the (omega-1)-power, we show that V*D is pointlike-reducible when V is pointlike-reducible.

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

Current Challenges in Modeling Cellular Metabolism

Mathematical and computational models play an essential role in understanding the cellular metabolism. They are used as platforms to integrate current knowledge on a biological system and to systematically test and predict the effect of manipulations to such systems. The recent advances in genome sequencing techniques have facilitated the reconstruction of genome-scale metabolic networks for a wide variety of organisms from microbes to human cells. These models have been successfully used in multiple biotechnological applications. Despite these advancements, modeling cellular metabolism still presents many challenges. The aim of this Research Topic is not only to expose and consolidate the state-of-the-art in metabolic modeling approaches, but also to push this frontier beyond the current edge through the introduction of innovative solutions. The articles presented in this e-book address some of the main challenges in the field, including the integration of different modeling formalisms, the integration of heterogeneous data sources into metabolic models, explicit representation of other biological processes during phenotype simulation, and standardization efforts in the representation of metabolic models and simulation results.

Mesenchymal stem cells secretome as a modulator of the neurogenic niche: Basic insights and therapeutic opportunities

Neural stem cells (NSCs) and mesenchymal stem cells (MSCs) share few characteristics apart from self-renewal and multipotency. In fact, the neurogenic and osteogenic stem cell niches derive from two distinct embryonary structures; while the later originates from the mesoderm, as all the connective tissues do, the first derives from the ectoderm. Therefore, it is highly unlikely that stem cells isolated from one niche could form terminally differentiated cells from the other. Additionally, these two niches are associated to tissues/systems (e.g., bone and central nervous system) that have markedly different needs and display diverse functions within the human body. Nevertheless they do share common features. For instance, the differentiation of both NSCs and MSCs is intimately associated with the bone morphogenetic protein family. Moreover, both NSCs and MSCs secrete a panel of common growth factors, such as nerve growth factor (NGF), glial derived neurotrophic factor (GDNF), and brain derived neurotrophic factor (BDNF), among others. But it is not the features they share but the interaction between them that seem most important, and worth exploring; namely, it has already been shown that there are mutually beneficially effects when these cell types are co-cultured in vitro. In fact the use of MSCs, and their secretome, become a strong candidate to be used as a therapeutic tool for CNS applications, namely by triggering the endogenous proliferation and differentiation of neural progenitors, among other mechanisms. Quite interestingly it was recently revealed that MSCs could be found in the human brain, in the vicinity of capillaries. In the present review we highlight how MSCs and NSCs in the neurogenic niches interact. Furthermore, we propose directions on this field and explore the future therapeutic possibilities that may arise from the combination/interaction of MSCs and NSCs.

FluidUM: análise de fluidos de um automóvel

Dissertação de mestrado integrado em Engenharia Mecânica