Influência das condições de trabalho na exposição aos fumos de soldadura e efeitos na saúde

Mestrado em Segurança e Higiene do Trabalho.

Análise da resistência à fadiga de tubos de aço API 5CT N80 Tipo Q soldados via processo de indução magnética de alta frequência (HFIW)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Exposição a fumo de soldaduras: quais os factores de risco?

Mestrado em Segurança e Higiene no Trabalho.

Notice on a methodology for characterizing emissions of ultrafine particles/nanoparticles in microenvironments

Bearing in mind the potential adverse health effects of ultrafine particles, it is of paramount importance to perform effective monitoring of nanosized particles in several microenvironments, which may include ambient air, indoor air, and also occupational environments. In fact, effective and accurate monitoring is the first step to obtaining a set of data that could be used further on to perform subsequent evaluations such as risk assessment and epidemiologic studies, thus proposing good working practices such as containment measures in order to reduce occupational exposure. This paper presents a useful methodology for monitoring ultrafine particles/nanoparticles in several microenvironments, using online analyzers and also sampling systems that allow further characterization on collected nanoparticles. This methodology was validated in three case studies presented in the paper, which assess monitoring of nanosized particles in the outdoor atmosphere, during cooking operations, and in a welding workshop.

Towards an Academic Social Network for Bologna Process

The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.

Concepção e instalação de tabelas multifunções para recintos desportivos cobertos

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Desperdícios na cadeia logística no âmbito industrial

Projecto apresentado ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientada por Prof. Doutor Gouveia

Comportamento à fadiga de juntas soldadas de aços tipo 460M com fios fluxados

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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.

Global and local detection of liver steatosis from ultrasound

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. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Projecto dum laboratório remoto para automação de processos industriais

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Comando de ondulador de tensão trifásico por PWM e técnica U/F com implementação por microcontrolador

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Contribuição para a caracterização da emissão de nanopartículas em processos de soldadura e avaliação de riscos decorrentes do processo

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica Ramo de processos químicos

Conceção e construção de um simulador de controlo de vibrações

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Regularização de barras e soldaduras aluminotérmicas

Relatório de Estágio para obtenção do grau de Mestre em Engenharia Civil