Segmentation of striatal brain structures from high resolution pet images

Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers

Optimization of multi-stage amplifiers in deep-submicron CMOS using a distributed/parallel genetic algorithm

IEEE International Symposium on Circuits and Systems, pp. 724 – 727, Seattle, EUA

Including context in a routing algorithm for the internet of things

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

A lightweight distributed super peer election algorithm for unstructured dynamic P2P systems

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

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

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

Development of principle culture medium formulations for Saccharomyces cerevisiae

Saccharomyces cerevisiae as well as other microorganisms are frequently used in industry with the purpose of obtain different kind of products that can be applied in several areas (research investigation, pharmaceutical compounds, etc.). In order to obtain high yields for the desired product, it is necessary to make an adequate medium supplementation during the growth of the microorganisms. The higher yields are typically reached by using complex media, however the exact formulation of these media is not known. Moreover, it is difficult to control the exact composition of complex media, leading to batch-to-batch variations. So, to overcome this problem, some industries choose to use defined media, with a defined and known chemical composition. However these kind of media, many times, do not reach the same high yields that are obtained by using complex media. In order to obtain similar yield with defined media the addition of many different compounds has to be tested experimentally. Therefore, the industries use a set of empirical methods with which it is tried to formulate defined media that can reach the same high yields as complex media. In this thesis, a defined medium for Saccharomyces cerevisiae was developed using a rational design approach. In this approach a given metabolic network of Saccharomyces cerevisiae is divided into a several unique and not further decomposable sub networks of metabolic reactions that work coherently in steady state, so called elementary flux modes. The EFMtool algorithm was used in order to calculate the EFM’s for two Saccharomyces cerevisiae metabolic networks (amino acids supplemented metabolic network; amino acids non-supplemented metabolic network). For the supplemented metabolic network 1352172 EFM’s were calculated and then divided into: 1306854 EFM’s producing biomass, and 18582 EFM’s exclusively producing CO2 (cellular respiration). For the non-supplemented network 635 EFM’s were calculated and then divided into: 215 EFM’s producing biomass; 420 EFM’s producing exclusively CO2. The EFM’s of each group were normalized by the respective glucose consumption value. After that, the EFMs’ of the supplemented network were grouped again into: 30 clusters for the 1306854 EFMs producing biomass and, 20 clusters for the 18582 EFM’s producing CO2. For the non-supplemented metabolic network the respective EFM’s of each metabolic function were grouped into 10 clusters. After the clustering step, the concentrations of the other medium compounds were calculated by considering a reasonable glucose amount and by accounting for the proportionality between the compounds concentrations and the glucose ratios. The approach adopted/developed in this thesis may allow a faster and more economical way for media development.

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

Contém resumo

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.