A utilização das TIC em contexto de ensino - aprendizagem: potencialidades da Internet na promoção da expressão escrita

Relatório de estágio de mestrado em Ensino de Português no 3º Ciclo do Ensino Básico e no Ensino Secundário e de Espanhol nos Ensinos Básico e Secundário

Indústria Transformadora em Timor-Leste: uma proposta para um setor industrial

Dissertação de mestrado em Engenharia Industrial

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

Numerical simulation of the reflow soldering process

Dissertação de mestrado integrado em Mechanical Engineering

From software extensions to product lines of dataflow programs

Abstract Dataflow programs are widely used. Each program is a directed graph where nodes are computations and edges indicate the flow of data. In prior work, we reverse-engineered legacy dataflow programs by deriving their optimized implementations from a simple specification graph using graph transformations called refinements and optimizations. In MDE-speak, our derivations were PIM-to-PSM mappings. In this paper, we show how extensions complement refinements, optimizations, and PIM-to-PSM derivations to make the process of reverse engineering complex legacy dataflow programs tractable. We explain how optional functionality in transformations can be encoded, thereby enabling us to encode product lines of transformations as well as product lines of dataflow programs. We describe the implementation of extensions in the ReFlO tool and present two non-trivial case studies as evidence of our work’s generality

Dispositivo de avaliação externa ao ensino superior: um estudo exploratório sobre acreditação à Universidade Nacional Timor Lorosa'e, 2008 – 2013

Dissertação de mestrado em Ciências da Educação (área de especialização em Avaliação)

Beeswax organogels: Influence of gelator concentration and oil type in the gelation process

This work focused on how different types of oil phase, MCT (medium chain triglycerides) and LCT (long chain triglycerides), exert influence on the gelation process of beeswax and thus properties of the organogel produced thereof. Organogels were produced at different temperatures and qualitative phase diagrams were constructed to identify and classify the type of structure formed at various compositions. The microstructure of gelator crystals was studied by polarized light microscopy. Melting and crystallization were characterized by differential scanning calorimetry and rheology (flow and small amplitude oscillatory measurements) to understand organogels' behaviour under different mechanical and thermal conditions. FTIR analysis was employed for a further understanding of oil-gelator chemical interactions. Results showed that the increase of beeswax concentration led to higher values of storage and loss moduli (G, G) and complex modulus (G*) of organogels, which is associated to the strong network formed between the crystalline gelator structure and the oil phase. Crystallization occurred in two steps (well evidenced for higher concentrations of gelator) during temperature decreasing. Thermal analysis showed the occurrence of hysteresis between melting and crystallization. Small angle X-ray scattering (SAXS) analysis allowed a better understanding in terms of how crystal conformations were disposed for each type of organogel. The structuring process supported by medium or long-chain triglycerides oils was an important exploit to apprehend the impact of different carbon chain-size on the gelation process and on gels' properties.

Step towards to improve the voluntary interruption of pregnancy by means of business intelligence

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte, in particular the Voluntary Interruption of Pregnancy unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the KPIs evaluated as well as the benefits of this implementation are presented.

Real-Time models to predict the use of vasopressors in monitored patients

The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.