Géneros textuais e práticas de sucesso no 1º ciclo do ensino básico

Tese de Doutoramento em Estudos da Criança (Área do Conhecimento em Estudos da Língua Portuguesa)

Text mining na análise de sentimentos em contextos de big data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

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)

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

Companies' OHS internal structures: Types and theoretical foundations

An organization manages to regulate, standardize and optimize its operations in a way that places health and safety first by considering Health, Safety, Environment and Ergonomics (HSEE). In order to provide a theoretical foundation for Companies’ Occupational Health and Safety Internal Structures (COHSIS) allowing the focus on safety, COHSIS and its fundamentals were reviewed and described based on a brief literature review, which have included both papers published in journals, as well as works made available by selected organizations with mature safety culture. Three COHSIS were defined for description of its fundamentals, enabling improve the usability of its terminologies and provide the mentioned theoretical foundation.

Using a new developed die and different types of thermosetting resins to produce U200 profiles by pultrusion

In this work, a new steel heated pultrusion die was designed, developed and manufactured to produce U200 glass fibre reinforced thermosetting matrix (GRP) profiles. The finite element analysis (FEA) was used to predict and optimise the developed die heating by using cylindrical electrical powered cartridges. To assess the new die performance it was mounted in the 120 kN pultrusion line of the Portuguese company Vidropol SA and used to produce continuously U200 profiles able to meet all requirements specified for the E23 grade accordingly to the European Standard EN 13706: 2002. After setting up the type, orientation and sequence of layers in the U 200 laminate, different types of thermosetting resins were used in its production. Orthophthalic, isophthalic and bisphenolic unsaturated polyester as well as vinylester resins were used to produce glass fibre reinforced U 200 composite profiles. All applied resins were submitted to SPI gel tests in order to select the more appropriated catalyst system and optimise the processing variables to be used in each case, namely, pultrusion pull-speed and die temperature. The best pultrusion operational conditions were selected by varying and monitoring the pull-speed and die temperature and, at the same time, measuring the temperature on the manufactured U 200 profile during processing. Finally, the produced U200 profiles were submitted to visual inspection, calcination and mechanical tests, namely, flexural, tensional and interlaminar shear strength (ILSS) tests, to assess their accomplishment with the EN 13706 requirements.

Reconstructing transcriptional regulatory networks using data integration and text mining

Transcriptional Regulatory Networks (TRNs) are powerful tool for representing several interactions that occur within a cell. Recent studies have provided information to help researchers in the tasks of building and understanding these networks. One of the major sources of information to build TRNs is biomedical literature. However, due to the rapidly increasing number of scientific papers, it is quite difficult to analyse the large amount of papers that have been published about this subject. This fact has heightened the importance of Biomedical Text Mining approaches in this task. Also, owing to the lack of adequate standards, as the number of databases increases, several inconsistencies concerning gene and protein names and identifiers are common. In this work, we developed an integrated approach for the reconstruction of TRNs that retrieve the relevant information from important biological databases and insert it into a unique repository, named KREN. Also, we applied text mining techniques over this integrated repository to build TRNs. However, was necessary to create a dictionary of names and synonyms associated with these entities and also develop an approach that retrieves all the abstracts from the related scientific papers stored on PubMed, in order to create a corpora of data about genes. Furthermore, these tasks were integrated into @Note, a software system that allows to use some methods from the Biomedical Text Mining field, including an algorithms for Named Entity Recognition (NER), extraction of all relevant terms from publication abstracts, extraction relationships between biological entities (genes, proteins and transcription factors). And finally, extended this tool to allow the reconstruction Transcriptional Regulatory Networks through using scientific literature.

Pervasive patient timeline

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Automatic distinction of Fernando Pessoas’ heteronyms

Text Mining has opened a vast array of possibilities concerning automatic information retrieval from large amounts of text documents. A variety of themes and types of documents can be easily analyzed. More complex features such as those used in Forensic Linguistics can gather deeper understanding from the documents, making possible performing di cult tasks such as author identi cation. In this work we explore the capabilities of simpler Text Mining approaches to author identification of unstructured documents, in particular the ability to distinguish poetic works from two of Fernando Pessoas' heteronyms: Alvaro de Campos and Ricardo Reis. Several processing options were tested and accuracies of 97% were reached, which encourage further developments.

Evaluation of inflammatory response induced by different types of daily contact lenses

Dissertação de mestrado em Genética Molecular

Escrever para aprender através dos textos literários e não literários

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico