Extraction automatique d´associations lexicales à partir de corpora

The automatic acquisition of lexical associations from corpora is a crucial issue for Natural Language Processing. A lexical association is a recurrent combination of words that co-occur together more often than expected by chance in a given domain. In fact, lexical associations define linguistic phenomena such as idiomes, collocations or compound words. Due to the fact that the sense of a lexical association is not compositionnal, their identification is fundamental for the realization of analysis and synthesis that take into account all the subtilities of the language. In this report, we introduce a new statistically-based architecture that extracts from naturally occurring texts contiguous and non contiguous. For that purpose, three new concepts have been defined : the positional N-gram models, the Mutual Expectation and the GenLocalMaxs algorithm. Thus, the initial text is fisrtly transformed in a set of positionnal N-grams i.e ordered vectors of simple lexical units. Then, an association measure, the Mutual Expectation, evaluates the degree of cohesion of each positional N-grams based on the identification of local maximum values of Mutual Expectation. Great efforts have also been carried out to evaluate our metodology. For that purpose, we have proposed the normalisation of five well-known association measures and shown that both the Mutual Expectation and the GenLocalMaxs algorithm evidence significant improvements comparing to existent metodologies.

Sentiment analysis on twitter for the portuguese language

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Testing native speakers of German and Portuguese on the understanding of topological operators-line-region relations in gvSIG

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Geospatial database generation from digital newspapers: use case for risk and disaster domains.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

A framework for supporting knowledge representation – an ontological based approach

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Cognitive assessment of topological movement Patterns and direction turns: An influence of scale

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Quality of process modeling using BPMN: a model-driven approach

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

Development of new membranes based on ionic liquid materials for gas separation

In the field of energy, natural gas is an essential bridge to a clean, low carbon, renewable energy era. However, natural gas processing and transportation regulation require the removal of contaminant compounds such as carbon dioxide (CO2). Regarding clean air, the increasing atmospheric concentrations of greenhouse gases, specifically CO2, is of particular concern. Therefore, new costeffective, high performance technologies for carbon capture have been researched and the design of materials with the ability to efficiently separate CO2 from other gases is of vital importance.(...)

A tradução de textos económico-financeiros de português para inglês: potencialidades da Plataforma ISTRION

Este Trabalho de Projeto tem como objetivo primordial analisar a tradução, de português para inglês, de textos económico-financeiros, utilizando a plataforma de Tradução Automática (TA) ISTRION. A tradução de conteúdos selecionados da Newsletter Económico-Financeira Maximus Report é efetuada com base na referida plataforma, complementada com outras ferramentas de apoio ao processamento linguístico que sejam consideradas relevantes. Visa-se igualmente com este Trabalho de Projeto analisar as potencialidades desta plataforma, bem como medir os resultados da tradução. Por último pretende-se enquadrar, testar, estudar e medir quais os critérios em que se poderá tornar mais eficiente a tradução destes textos.

About using serious games to teach (Portuguese) sign language

Sign language is the form of communication used by Deaf people, which, in most cases have been learned since childhood. The problem arises when a non-Deaf tries to contact with a Deaf. For example, when non-Deaf parents try to communicate with their Deaf child. In most cases, this situation tends to happen when the parents did not have time to properly learn sign language. This dissertation proposes the teaching of sign language through the usage of serious games. Currently, similar solutions to this proposal do exist, however, those solutions are scarce and limited. For this reason, the proposed solution is composed of a natural user interface that is intended to create a new concept on this field. The validation of this work, consisted on the implementation of a serious game prototype, which can be used as a source for learning (Portuguese) sign language. On this validation, it was first implemented a module responsible for recognizing sign language. This first stage, allowed the increase of interaction and the construction of an algorithm capable of accurately recognizing sign language. On a second stage of the validation, the proposal was studied so that the pros and cons can be determined and considered on future works.

How human schematization and systematic errors take effect on sketch map formalizations

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Evaluation of neuroprotective effects of natural extracts obtained from portuguese agro-food residues

Countries are currently faced with problems derived from changes in lifespan and an increase in lifestyle-related diseases. Neurodegenerative disorders such Parkinson’s (PD) and Alzheimer’s (AD) diseases are an increasing problem in aged societies. Data from World Alzheimer Report 2011 indicate that 36 million people worldwide are living with dementia. Oxidative stress has been associated with the development of AD and PD. Therefore there is interest to search for effective compounds or therapies to combat the oxidative damage in these diseases. Current evidence strongly supports a contribution of phenolic compounds present in fruits and vegetables to the prevention of neurodegenerative diseases such AD and PD. The industrial processing of a wide variety of fruits results in the accumulation of by-products without commercial value. Opuntia ficus-indica (cactus pear) is consumed fresh and processed like in juice. Prunnus avium (sweet cherry) is consumed fresh but the organoleptics characteristics of the fruits leads to the smaller and ragged fruits have no commercial value. Fruit extracts of both species has described to be rich in phenolic compounds and to have high antioxidant activities due to its composition. The aim of this work was assessing the efficacy of O. ficus-indica and P. avium by-products extracts obtained with conventional solvent extraction and pressurized liquid extraction in a neurodegeneration cell model. All extracts have protected neuroblastoma cells from H2O2-induced death at low, non-toxic levels, which approach to physiologically-relevant serum concentration. However, cherry extract has a slighter neuroprotective activity. The protective effect of Opuntia extracts are not conducted by a direct antioxidant activity since there are not decreases in intracellular ROS levels in cell treated with extracts and challenged with H2O2, while cherry extract neuroprotection seems to be due to a direct scavenging activity. Extracts from different biological matrixes seems to protect neuronal cells trough different cellular mechanisms.