Guitar solo tracker

A motivação para este trabalho vem da necessidade que o autor tem em poder registar as notas tocadas na guitarra durante o processo de improviso. Quando o músico está a improvisar na guitarra, muitas vezes não se recorda das notas tocadas no momento, este trabalho trata o desenvolvimento de uma aplicação para guitarristas, que permita registar as notas tocadas na guitarra eléctrica ou clássica. O sinal é adquirido a partir da guitarra e processado com requisitos de tempo real na captura do sinal. As notas produzidas pela guitarra eléctrica, ligada ao computador, são representadas no formato de tablatura e/ou partitura. Para este efeito a aplicação capta o sinal proveniente da guitarra eléctrica a partir da placa de som do computador e utiliza algoritmos de detecção de frequência e algoritmos de estimação de duração de cada sinal para construir o registo das notas tocadas. A aplicação é desenvolvida numa perspectiva multi-plataforma, podendo ser executada em diferentes sistemas operativos Windows e Linux, usando ferramentas e bibliotecas de domínio público. Os resultados obtidos mostram a possibilidade de afinar a guitarra com valores de erro na ordem de 2 Hz em relação às frequências de afinação standard. A escrita da tablatura apresenta resultados satisfatórios, mas que podem ser melhorados. Para tal será necessário melhorar a implementação de técnicas de processamento do sinal bem como a comunicação entre processos para resolver os problemas encontrados nos testes efectuados.

Lanczos algorithm on the grassmann manifold

5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)

Avaliação da caracterização de lesões em mamografia com recurso a sistemas CAD (Diagnóstico Assistido por Computador)

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Imagem Digital com Radiação X.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

Projeto de estruturas e fundações de um edifício de serviços

O presente trabalho é o culminar de um percurso académico cheio de aprendizagens que me preencheu por completo. A realização de um projeto de estruturas como trabalho final de mestrado (TFM) foi uma escolha fácil, pois, na minha opinião, permite fazer a transição entre os conceitos adquiridos durante o curso e os métodos utilizados no ambiente não académico. O objetivo do trabalho é realizar o projeto de estruturas e fundações de um edifício destinado a serviços. Foram aplicados os conhecimentos adquiridos ao longo de todo o curso de Engenharia Civil, em especial das Unidades Curriculares de dimensionamento de estruturas. Foi elaborado um modelo da estrutura num programa de cálculo automático: SAP2000. Assim, de acordo com os resultados fornecidos pelo programa e através da consulta dos regulamentos nacionais (REBAP e RSA) e internacionais (Eurocódigos), foi possível dimensionar todos os elementos estruturais. Os diferentes aspetos condicionantes no projeto foram devidamente analisados e discutidos, por forma a encontrar a solução que mais se adequa ao pretendido. Todas as opções tomadas são devidamente justificadas, procurando-se elaborar um trabalho detalhado e, acima de tudo, correto. É importante dizer ainda que, a permanente troca de ideias e conhecimentos entre colegas e, como é óbvio, com o orientador do trabalho, foi muito relevante na realização deste trabalho. Uma parte essencial de um projeto são, sem dúvida, as peças desenhadas. Nesse capítulo tentou-se atingir um nível de detalhe e simplicidade que permita uma interpretação inequívoca dos mesmos.

Processamento de imagem para determinação de distribuições granulométricas de gotas numa suspensão

Mestrado em Engenharia Electrotécnica e de Computadores

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Comparison of different breast planning techniques and algorithms for radiation therapy treatment

This work aims at investigating the impact of treating breast cancer using different radiation therapy (RT) techniques – forwardly-planned intensity-modulated, f-IMRT, inversely-planned IMRT and dynamic conformal arc (DCART) RT – and their effects on the whole-breast irradiation and in the undesirable irradiation of the surrounding healthy tissues. Two algorithms of iPlan BrainLAB treatment planning system were compared: Pencil Beam Convolution (PBC) and commercial Monte Carlo (iMC). Seven left-sided breast patients submitted to breast-conserving surgery were enrolled in the study. For each patient, four RT techniques – f-IMRT, IMRT using 2-fields and 5-fields (IMRT2 and IMRT5, respectively) and DCART – were applied. The dose distributions in the planned target volume (PTV) and the dose to the organs at risk (OAR) were compared analyzing dose–volume histograms; further statistical analysis was performed using IBM SPSS v20 software. For PBC, all techniques provided adequate coverage of the PTV. However, statistically significant dose differences were observed between the techniques, in the PTV, OAR and also in the pattern of dose distribution spreading into normal tissues. IMRT5 and DCART spread low doses into greater volumes of normal tissue, right breast, right lung and heart than tangential techniques. However, IMRT5 plans improved distributions for the PTV, exhibiting better conformity and homogeneity in target and reduced high dose percentages in ipsilateral OAR. DCART did not present advantages over any of the techniques investigated. Differences were also found comparing the calculation algorithms: PBC estimated higher doses for the PTV, ipsilateral lung and heart than the iMC algorithm predicted.

Image upsampling algorithms applied on Nuclear Medicine: comparision of hqnx and nxSaI algorithms families with two interpolation algorithms - nearest neighbour and bicubic interpolation

Introduction: Image resizing is a normal feature incorporated into the Nuclear Medicine digital imaging. Upsampling is done by manufacturers to adequately fit more the acquired images on the display screen and it is applied when there is a need to increase - or decrease - the total number of pixels. This paper pretends to compare the “hqnx” and the “nxSaI” magnification algorithms with two interpolation algorithms – “nearest neighbor” and “bicubic interpolation” – in the image upsampling operations. Material and Methods: Three distinct Nuclear Medicine images were enlarged 2 and 4 times with the different digital image resizing algorithms (nearest neighbor, bicubic interpolation nxSaI and hqnx). To evaluate the pixel’s changes between the different output images, 3D whole image plot profiles and surface plots were used as an addition to the visual approach in the 4x upsampled images. Results: In the 2x enlarged images the visual differences were not so noteworthy. Although, it was clearly noticed that bicubic interpolation presented the best results. In the 4x enlarged images the differences were significant, with the bicubic interpolated images presenting the best results. Hqnx resized images presented better quality than 4xSaI and nearest neighbor interpolated images, however, its intense “halo effect” affects greatly the definition and boundaries of the image contents. Conclusion: The hqnx and the nxSaI algorithms were designed for images with clear edges and so its use in Nuclear Medicine images is obviously inadequate. Bicubic interpolation seems, from the algorithms studied, the most suitable and its each day wider applications seem to show it, being assumed as a multi-image type efficient algorithm.

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.

Projeto de estrutura variante de um edifício de escritórios em Lisboa

Trabalho de Projecto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas