Modern techniques for constraint solving the CASPER experience

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

Trypanosoma cruzi strains: behavior after passage into authoctonous or foreign species of triatomine (biological and biochemical patterns)

The behavior of T. cruzi strains from S. Felipe - BA (19 SF, 21 SF and 22 SF) classified as Type II Zymodeme 2, was investigated after passage through the authoctonous (P. megistus) and foreign vectors (T. infestans and R. prolixus). For each strain Swiss mice were infected: I - with blood forms (control); II - with metacyclic forms (MF) from P. megistus; III - with MF from T. infestans; IV - with MF from R. prolixus. Inocula: MF from the three species of triatomine, 60 to 120 days after feeding in infected mice, adjusted to 10 4. Biological behavior in mice (parasitemia, morphology, mortality, virulence and pathogenicity) after passage through triatomine was compared with data from the same strain in control mice. Isoenzymic electrophoresis (ASAT, ALAT, PGM, GPI) were also performed after culture into Warren medium. The three strains maintained the isoenzyme profiles (zymodeme 2), in the control groups and after passages through different species of triatomine. Biological characterization disclosed Type II strains patterns for all groups. An increased virulence was observed with the 22 SF strain isolated from P. megistus and T. infestans and higher levels of parasitemia and predominance of slender forms in mice inoculated with the 19 SF and 21 SF from these same species. Results indicate that the passage through the two species T. infestans and P. megistus had a positive influence on the virulence of the regional strains of S. Felipe, regardless of being autocthonous (P. megistus) or foreign to the area (T. infestans).

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Algorithms for time series clustering applied to biomedical signals

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

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Detection of mycoplasmas in urethral swabs from HIV-1 infected patients and control individuals using culture techniques and polymerase chain reaction

The objective of the present study was to determine the prevalence of certain mycoplasma species, i.e., Mycoplasma hominis, Ureaplasma urealyticum and Mycoplasma penetrans, in urethral swabs from HIV-1 infected patients compared to swabs from a control group. Mycoplasmas were detected by routine culture techniques and by the Polymerase Chain Reaction (PCR) technique, using 16SrRNA generic primers of conserved region and Mycoplasma penetrans specific primers. The positivity rates obtained with the two methods were comparable. Nevertheless, PCR was more sensitive, while the culture techniques allowed the quantification of the isolates. The results showed no significant difference (p < 0.05) in positivity rates between the methods used for mycoplasma detection.

PALEOPARASITOLOGY: PERSPECTIVES WITH NEW TECHNIQUES

Paleoparasitology is the study of parasites found in archaeological material. The development of this field of research began with histological identification of helminth eggs in mummy tissues, analysis of coprolites, and recently through molecular biology. An approach to the history of paleoparasitology is reviewed in this paper, with special reference to the studies of ancient DNA identified in archaeological material.

Análise de desempenho de algoritmos de otimização para extração de parâmetros em modelos semicondutores de potência

Apresenta-se nesta tese uma revisão da literatura sobre a modelação de semicondutores de potência baseada na física e posterior análise de desempenho de dois métodos estocásticos, Particle Swarm Optimizaton (PSO) e Simulated Annealing (SA), quando utilizado para identificação eficiente de parâmetros de modelos de dispositivos semicondutores de potência, baseado na física. O conhecimento dos valores destes parâmetros, para cada dispositivo, é fundamental para uma simulação precisa do comportamento dinâmico do semicondutor. Os parâmetros são extraídos passo-a-passo durante simulação transiente e desempenham um papel relevante. Uma outra abordagem interessante nesta tese relaciona-se com o facto de que nos últimos anos, os métodos de modelação para dispositivos de potência têm emergido, com alta precisão e baixo tempo de execução baseado na Equação de Difusão Ambipolar (EDA) para díodos de potência e implementação no MATLAB numa estratégia de optimização formal. A equação da EDA é resolvida numericamente sob várias condições de injeções e o modelo é desenvolvido e implementado como um subcircuito no simulador IsSpice. Larguras de camada de depleção, área total do dispositivo, nível de dopagem, entre outras, são alguns dos parâmetros extraídos do modelo. Extração de parâmetros é uma parte importante de desenvolvimento de modelo. O objectivo de extração de parâmetros e otimização é determinar tais valores de parâmetros de modelo de dispositivo que minimiza as diferenças entre um conjunto de características medidas e resultados obtidos pela simulação de modelo de dispositivo. Este processo de minimização é frequentemente chamado de ajuste de características de modelos para dados de medição. O algoritmo implementado, PSO é uma técnica de heurística de otimização promissora, eficiente e recentemente proposta por Kennedy e Eberhart, baseado no comportamento social. As técnicas propostas são encontradas para serem robustas e capazes de alcançar uma solução que é caracterizada para ser precisa e global. Comparada com algoritmo SA já realizada, o desempenho da técnica proposta tem sido testado utilizando dados experimentais para extrair parâmetros de dispositivos reais das características I-V medidas. Para validar o modelo, comparação entre resultados de modelo desenvolvido com um outro modelo já desenvolvido são apresentados.

Chlorella sp. coagulation‐flocculation by inducing a modification on the pH broth medium

Dissertação apresentada à Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Bioenergia

Evolutive behavior towards cardiomyopathy of treated (nifurtimox or benznidazole) and untreated chronic chagasic patients

The aim of this work was to compare the evolution of chronic chagasic untreated patients (UTPs) with that of benznidazole or nifurtimox-treated patients (TPs). A longitudinal study from a low endemic area (Santa Fe city, Argentina) was performed during an average period of 14 years. Serological and parasitological analyses with clinical exams, ECG and X-chest ray were carried out. At the onset, 19/198 infected patients showed chagasic cardiomyopathy (CrChM) while 179 were asymptomatic. In this latter group the frequency of CrChM during the follow-up was lower in TPs compared with UTPs (3.2% vs 7%). Within the CrChM group, 2/5 TPs showed aggravated myopathy whereas this happened in 9/14 UTPs. Comparing the clinical evolution of all patients, 5.9% of TPs and 13% of UTPs had unfavourable evolution, but the difference is not statistically relevant. Serological titers were assessed by IIF. Titers equal to or lower than 1/64 were obtained in 86% of the TPs, but only in 38% of UTPs. The differences were statistically significant (geometric mean: 49.36 vs. 98.2). Antiparasitic assessment of the drugs (xenodiagnosis) proved to be effective. The low sensitivity in chronic chagasic patients must be born in mind. Despite treated patients showed a better clinical evolution and lower antibody levels than untreated ones, it is necessary to carry on doing research in order to improve therapeutic guidelines, according to the risk/benefit equation and based on scientific and ethical principles.

Archaeological roman glasses: comparative characterisation by non-destructive analytical techniques

Dissertation presented in fulfilment of the requirements for the Master’s degree in Conservation and Restoration

Dimensionamento de pilares mistos aço-betão segundo a EN 1994-1-1 através de uma aplicação informática

O presente trabalho debruça-se sobre as estruturas mistas aço-betão, com foco nos pilares mistos e no seu dimensionamento segundo a norma europeia EN1994-1-1 (EC4) [1]. Um pilar misto aço-betão pode definir-se como um elemento de aço, laminado ou composto, que trabalha em conjunto com o betão, podendo as secções serem classificados como revestidas ou preenchidas. Com a crescente evolução das técnicas construtivas, as estruturas mistas aço-betão aparecem como soluções viáveis e seguras, tornando-se numa opção competitiva em relação às soluções tradicionais de betão armado e de aço estrutural. Isto, devido à grande capacidade de carga proporcionada por secções mais reduzidas, à boa relação de rigidez e bom comportamento perante os fenómenos de encurvadura. Com o surgimento da recente norma europeia EC4, não obstante a complexidade das metodologias de verificação da segurança propostas, há uma maior confiança na utilização deste tipo de estrutura por parte dos projetistas. É neste contexto que surge a necessidade de desenvolver ferramentas de cálculo expedito que possam ser utilizadas em gabinete de projeto, salvaguardando todos os aspectos regulamentares de verificação da segurança preconizados no EC4, de que é exemplo o dimensionamento de pilares mistos abordados no presente trabalho. De forma a validar a ferramenta desenvolvida é proposto um caso de estudo, com o objectivo de obter soluções de pilares mistos com dimensões otimizadas, fazendo as verificações previstas no EC4. Os resultados obtidos na ferramenta são comparados com os resultados obtidos através de cálculos analíticos.

Health care marketing: the theory of planned behavior applied to patients' choise between private and public providers in the portuguese health care system.

Dissertation submitted in partial fulfillment of the requirements for degree of Master in Statistics and Information Management.