Long-term biosignals visualization and processing

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

Parallel programming in biomedical signal processing

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Chagas' disease: an algorithm for donor screening and positive donor counseling

Classical serological screening assays for Chagas' disease are time consuming and subjective. The objective of the present work is to evaluate the enzyme immuno-assay (ELISA) methodology and to propose an algorithm for blood banks to be applied to Chagas' disease. Seven thousand, nine hundred and ninety nine blood donor samples were screened by both reverse passive hemagglutination (RPHA) and indirect immunofluorescence assay (IFA). Samples reactive on RPHA and/or IFA were submitted to supplementary RPHA, IFA and complement fixation (CFA) tests. This strategy allowed us to create a panel of 60 samples to evaluate the ELISA methodology from 3 different manufacturers. The sensitivity of the screening by IFA and the 3 different ELISA's was 100%. The specificity was better on ELISA methodology. For Chagas disease, ELISA seems to be the best test for blood donor screening, because it showed high sensitivity and specificity, it is not subjective and can be automated. Therefore, it was possible to propose an algorithm to screen samples and confirm donor results at the blood bank.

Fast screening for diagnostic of heart ischemic episodes

Dissertação para obtenção do Grau de Doutor em Química Sustentável

Comparação entre os métodos de Ziehl-Neelsen modificado e Acid-Fast-Trichrome para a pesquisa fecal de Cryptosporidium parvum e Isospora belli

Devido a crescente importância dos coccídios intestinais (Cryptosporidium, Isospora e Cyclospora) como parasitos oportunistas, é fundamental para os laboratórios diferenciar morfologicamente estes protozoários; a técnica de Ziehl-Neelsen modificada (ZNm) é amplamente utilizada para este fim; recentemente, foi proposto um novo procedimento, a coloração combinada do ácido tricrômico (Acid-Fast-Trichrome - AFT). O objetivo do presente estudo foi comparar os processos AFT e ZNm para a detecção destes coccídios em amostras fecais de pacientes portadores do vírus VIH. Foram selecionados dois grupos de indivíduos, para inclusão no estudo, segundo a presença (n=60) ou ausência de diarréia (n=60). As amostras de fezes foram coletadas em solução de formalina 10% e os esfregaços fecais preparados i) diretamente das fezes e ii) após concentração prévia a 500xg (10 minutos), foram submetidos aos diferentes processos de coloração. Considerando-se a positividade por técnica (AFT e ZNm), verificou-se a superioridade do procedimento de ZNm (n=19; 100% dos casos positivos) sobre o de AFT (n=8; 42,1%). Ambos possibilitaram a identificação dos 101 casos verdadeiramente negativos. Coccidiose intestinal foi mais frequente entre os pacientes que apresentaram diarréia (26,6%) em comparação à positividade observada entre os indíviduos assintomáticos (5%) sendo que C. cayetanensis não foi detectada em ambos os grupos. Foi de nosso interesse avaliar a aplicabilidade da técnica AFT para a coloração deste protozoário. Devido à sensibilidade e especificidade obtida neste estudo (100%), conclui-se que o método de ZNm continua sendo o mais indicado para o diagnóstico da criptosporidiose e isosporose, principalmente quando associado ao procedimento de centrífugo-concentração (500xg, 10 minutos). Embora a coloração AFT tenha baixo custo, faz-se necessário o seu aperfeiçoamento pois este procedimento permite o diagnóstico simultâneo dos coccídios intestinais (C. parvum, I. belli e C. cayetanensis) e dos microsporídios.

Automated quantitative analysis of MCC-IMS spectra

Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.

Zara: Marketing in Fast Fashion: A case-study

Zara was founded in 1975 by Amancio Ortega Gaona, soon becoming the largest and most successful chain of the Galician group Inditex (Industria de Diseño Textil) and a pioneer of the rising fashion category of Fast Fashion. Its innovative vertically-integrated strategies, combined with its emphasis on quality and demand-based offer have shaped the world of fashion and brought forth many questions on its future sustainability and growth. Zara has always relied on its store network for advertising its product offer; allowing its garments to “speak for themselves”. With the continued pressure felt in the industry, management has pressed some concerns about future company growth and creative, innovating solutions must be implemented to guarantee Zara’s future growth. The case-study narrative focuses on these issues and leaves readers with an open question regarding what decision to implement.

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.

Comprehensive comparison of a current-source and a voltage-source converter for three-phase EV fast battery chargers

This paper presents a comprehensive comparison of a current-source converter and a voltage-source converter for three-phase electric vehicle (EV) fast battery chargers. Taking into account that the current-source converter (CSC) is a natural buck-type converter, the output voltage can assume a wide range of values, which varies between zero and the maximum instantaneous value of the power grid phase-to-phase voltage. On the other hand, taking into account that the voltage-source converter (VSC) is a natural boost-type converter, the output voltage is always greater than the maximum instantaneous value of the power grid phase-to-phase voltage, and consequently, it is necessary to use a dc-dc buck-type converter for applications as EV fast battery chargers. Along the paper is described in detail the principle of operation of both the CSC and the VSC for EV fast chargers, as well as the main equations of the power theory and current control strategies. The comparison between both converters is mainly established in terms of the total harmonic distortion of the grid current and the estimated efficiency for a range of operation between 10 kW and 50 kW.

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.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.