Geodupa - a geography-driven partial membership algorithm

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Biogenic amines in wine: gene transcription as a tool for selection of Oenococcus oeni starter strains

Dissertation presented to obtain the Ph.D degree in Biology

Segregated modeling and selection of populations for polyhydroxyalkanoate production by mixed microbial cultures

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Química e Bioquímica

Selection of a co-operation agreement between EMOVE – Innovative Technologies and WavEC – Wave Energy Center

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Market selection and market entry recommendations for a non-profit organization's first international venture

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Food waste valorization through the production of polyhydroxyalkanoates by mixed microbial cultures

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Production of polyhydroxyalkanoates from cheese whey - pH effect on the acidogenic fermentation stage and nutrient needs of the culture selection stage

Dissertação para obtenção do Grau de Mestre em Biotecnologia

2D position system for a mobile robot in unstructured environments

Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.

Return Migration, Self-Selection and Entrepreneurship in Mozambique

Does return migration affect entrepreneurship? This question has important implications for the debate on the economic development effects of migration for origin countries. The existing literature has, however, not addressed how the estimation of the impact of return migration on entrepreneurship is affected by double unobservable migrant self-selection, both at the initial outward migration and at the final inward return migration stages. This paper uses a representative household survey conducted in Mozambique in order to address this research question. We exploit variation provided by displacement caused by civil war in Mozambique, as well as social unrest and other shocks in migrant destination countries. The results lend support to negative unobservable self-selection at both and each of the initial and return stages of migration, which results in an under-estimation of the effects of return migration on entrepreneurial outcomes when using a ‘naïve’ estimator not controlling for self-selection. Indeed, ‘naïve’ estimates point to a 13 pp increase in the probability of owning a business when there is a return migrant in the household relative to non-migrants only, whereas excluding the double effect of unobservable self-selection, this effect becomes significantly larger - between 24 pp and 29 pp, depending on the method of estimation and source of variation used.

Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

Internationalization strategy for MyHelpster.com with a focus on international market selection

International Market Selection is an important step towards a successful internationalization strategy. This is no different for startup companies like MyHelpster. This work project was intended to help MyHelpster with their internationalization process by completing the IMS portion of it. The IMS process presented in this paper lead to the conclusion that MyHelpster’s next market for expansion should be the USA. In order to find as much success as possible the author suggests being patient and only expanding when the company has the necessary capital, experience and credibility. Both primary and secondary data were used to compile the qualitative and quantitative analyses.

International market selection of Carrefour

Carrefour has been internationalizing into many countries and would like to continue growing. This study focuses on the potential future international market selection of Car-refour, comparing countries from the EU and South America, in a quantitative and qual-itative analysis. The purpose of the project is to help Carrefour to find the right market and the right mode to entry. Through semi-structured interviews and a literature research we found out that Sweden has the highest potential to entry with a Venture (Marketing), followed by Austria

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

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