Aplicação de um método de correlação de imagem para a determinação da tenacidade à fratura em corte de adesivos estruturais

Qualquer estrutura hoje em dia deve ser resistente, robusta e leve, o que aumentou o interesse industrial e investigação nas ligações adesivas, nomeadamente pela melhoria das propriedades de resistência e fratura dos materiais. Com esta técnica de união, o projeto de estruturas pode ser orientado para estruturas mais leves, não só em relação à economia direta de peso relativamente às juntas aparafusas ou soldadas, mas também por causa da flexibilidade para ligar materiais diferentes. Em qualquer área da indústria, a aplicação em larga escala de uma determinada técnica de ligação supõe que estão disponíveis ferramentas confiáveis para o projeto e previsão da rotura. Neste âmbito, Modelos de Dano Coesivo (MDC) são uma ferramenta essencial, embora seja necessário estimar as leis MDC do adesivo à tração e corte para entrada nos modelos numéricos. Este trabalho avalia o valor da tenacidade ao corte (GIIC) de juntas coladas para três adesivos com ductilidade distinta. O trabalho experimental consiste na caracterização à fratura ao corte da ligação adesiva por métodos convencionais e pelo Integral-J. Além disso, pelo integral-J, é possível definir a forma exata da lei coesiva. Para o integral-J, é utilizado um método de correlação de imagem digital anteriormente desenvolvido para a avaliação do deslocamento ao corte do adesivo na extremidade da fenda (δs) durante o ensaio, acoplado a uma sub-rotina em Matlab® para a extração automática de δs. É também apresentado um trabalho numérico para avaliar a adequabilidade de leis coesivas triangulares aproximadas em reproduzir as curvas força-deslocamento (P-δ) experimentais dos ensaios ENF. Também se apresenta uma análise de sensibilidade para compreender a influência dos parâmetros coesivos nas previsões numéricas. Como resultado deste trabalho, foram estimadas experimentalmente as leis coesivas de cada adesivo pelo método direto, e numericamente validadas, para posterior previsão de resistência em juntas adesivas. Em conjunto com a caraterização à tração destes adesivos, é possível a previsão da rotura em modo-misto.

A distributed platform for the volunteer execution of workflows on a local area network

Thesis submitted in fulfilment of the requirements for the Degree of Master of Science in Computer Science

Learning facial-expression models with crowdsourcing

The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

Epidemiological profile of meningococcal disease in the State of Minas Gerais and in the Central, North, and Triângulo Mineiro regions, Brazil, during 2000-2009

INTRODUCTION: Infection by Neisseria meningitidis, termed as meningococcal disease, can cause meningococcal meningitis and septicemia with or without meningitis. Meningococcal disease is endemic in Brazil and has a high potential to cause large-scale epidemics; therefore, it requires the immediate notification of cases to the Information System for Notifiable Diseases (SINAN) in Brazil. The aim of this study was to describe an epidemiological profile using data from notified and confirmed cases in the State of Minas Gerais, Brazil, from January 2000 to December 2009, obtained from the investigation records of individuals with meningitis registered with SINAN. METHODS: This was a retrospective, population-based study. Descriptive analysis of the data was made using the simple and relative frequencies of the categorical variables in the investigation records. RESULTS: There were 1,688 confirmed patients in Minas Gerais of which 45.5% lived in the Central, North, and Triângulo Mineiro regions. The highest frequencies of cases were in the 1-4-years age group (26.3%), males (54.7%), caucasian (36.4%), and lived in an urban area (80%). In the patients with specified education, 650 (60.9%) patients had secondary education. Serogrouping of meningococci had been performed in 500 (29.6%) patients by age and gender; 285 (57%) belonged to serogroup C, 67 (13.4%) were in the 1-to 4-years age group, and 168 (33.6%) were male. CONCLUSIONS: The epidemiological profiles of patients in the Central, North, and Triângulo Mineiro regions were not significantly different from the profile of patients in Minas Gerais.

The effectiveness of the “Processo Especial de Revitalização” as an instrument of corporate restructuring in the context of the current economic crisis

This work project intends to evaluate the effectiveness of the Portuguese Government’s strategy to promote the orderly deleveraging of the corporate sector in the context of the current economic crisis. The recommendations of the Troika and the commitments assumed under the Memorandum of Understanding signed by the Government in 2011 required the creation of formal processes to avoid disorderly deleveraging. Conclusions and recommendations were drawn based on past experiences of large-scale corporate restructuring strategies in other countries and on the analysis of financial and statistical data on companies applying for “Programa Especial de Revitalização”.

On project finance and the first road concession in Portugal

In broad sense, Project Financing1 as a mean of financing large scale infrastructural projects worldwide has had a steady growth in popularity for the last 20 years. This growth has been relatively unscathed from most economic cycles. However in the wake of the 2007 systemic Financial Crisis, Project Financing was also in trouble. The liquidity freeze and credit crunch that ensued affected all parties involved. Traditional Lenders, of this type of financial instrument, locked-in long-term contractual obligations, were severely hit with scarcity of funding compounded by rapidly increasing cost of funding. All the while, Banks were “rescued” by the concerted actions of Central Banks and other Multi-Lateral Agencies around the world but at the same time “stressed” by upcoming regulatory effort (Basel Committee). This impact resulted in specific changes to this type of long-term financing. Changes such as Commercial Banks’ increased risk aversion; pricing increase and maturities decrease of credit facilities; enforcement of Market Disruption Event clauses; partial responsibility for project risk by Multilateral Agencies; and adoption of utility-like availability payments in other industrial sectors such as transportation and even social infrastructure. To the extent possible, this report is then divided in three parts. First, it begins with a more instructional part, touching academic literature (theory) and giving the Banks perspective (practice), but mostly as an overview of Project Finance for awareness’ sake. The renowned Harvard Business School professor – Benjamin Esty, states2 that Project Finance is a “relatively unexplored territory for both empirical and theoretical research” which means that academic research efforts are lagging the practice of Project Finance. Second, the report presents a practical case regarding the first Road Concession in Portugal in 1998 ending with the lessons learned 10 years after Financial Close. Lastly, the report concludes with the analysis of the current trends and changes to the industry post Financial Crisis of the late 2000’s. To achieve this I’ll reference relevant papers, books on the subject, online articles and my own experience in the Project Finance Department at a major Portuguese Investment Bank. Regarding the latter, with the signing of a confidentiality agreement, I’m duly omitting sensitive and proprietary bank information.

Epidemic store for massive scale systems

The MAP-i doctoral program of the Universities of Minho, Aveiro and Porto

Human mobility patterns at the smallest scales

We present a study on human mobility at small spatial scales. Differently from large scale mobility, recently studied through dollar-bill tracking and mobile phone data sets within one big country or continent, we report Brownian features of human mobility at smaller scales. In particular, the scaling exponents found at the smallest scales is typically close to one-half, differently from the larger values for the exponent characterizing mobility at larger scales. We carefully analyze 12-month data of the Eduroam database within the Portuguese university of Minho. A full procedure is introduced with the aim of properly characterizing the human mobility within the network of access points composing the wireless system of the university. In particular, measures of flux are introduced for estimating a distance between access points. This distance is typically non-Euclidean, since the spatial constraints at such small scales distort the continuum space on which human mobility occurs. Since two different ex- ponents are found depending on the scale human motion takes place, we raise the question at which scale the transition from Brownian to non-Brownian motion takes place. In this context, we discuss how the numerical approach can be extended to larger scales, using the full Eduroam in Europe and in Asia, for uncovering the transi- tion between both dynamical regimes.

Cross-scale determinants of palm species distribution

We investigate palm species distribution, richness and abundance along the Mokoti, a seasonally-dry river of southeastern Amazon and compare it to the patterns observed at a large scale, comprising the entire Brazilian territory. A total of 694 palms belonging to 10 species were sampled at the Mokoti River basin. Although the species showed diverse distribution patterns, we found that local palm abundance, richness and tree basal area were significantly higher from the hills to the bottomlands of the study region, revealing a positive association of these measures with moisture. The analyses at the larger spatial scale also showed a strong influence of vapor pressure (a measure of moisture content of the air, in turn modulated by temperature) and seasonality in temperature: the richest regions were those where temperature and humidity were simultaneously high, and which also presented a lower degree of seasonality in temperature. These results indicate that the distribution of palms seems to be strongly associated with climatic variables, supporting the idea that, by 'putting all the eggs in one basket' (a consequence of survival depending on the preservation of a single irreplaceable bud), palms have become vulnerable to extreme environmental conditions. Hence, their distribution is concentrated in those tropical and sub-tropical regions with constant conditions of (mild to high) temperature and moisture all year round.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Benefits from energy related building renovation beyond costs, energy and emissions

The relevance of the building sector in the global energy use as well as in the global carbon emissions, both in the developed and developing countries, makes the improvement of the overall energy performance of existing buildings an important part of the actions to mitigate climate changes. Regardless of this potential for energy and emissions saving, large scale building renovation has been found hard to trigger, mainly because present standards are mainly focused on new buildings, not responding effectively to the numerous technical, functional and economic constraints of the existing ones. One of the common problems in the assessment of building renovation scenarios is that only energy savings and costs are normally considered, despite the fact that it has been long recognized that investment on energy efficiency and low carbon technologies yield several benefits beyond the value of saved energy which can be as important as the energy cost savings process. Based on the analysis of significant literature and several case studies, the relevance of co-benefits achieved in the renovation process is highlighted. These benefits can be felt at the building level by the owner or user (like increased user comfort, fewer problems with building physics, improved aesthetics) and should therefore be considered in the definition of the renovation measures, but also at the level of the society as a whole (like health effects, job creation, energy security, impact on climate change), and from this perspective, policy makers must be aware of the possible crossed impacts among different areas of the society for the development of public policies.

Nonlinear optimization for human-like synchronous movements of a dual arm-hand robotic system

In previous work we have presented a model capable of generating human-like movements for a dual arm-hand robot involved in human-robot cooperative tasks. However, the focus was on the generation of reach-to-grasp and reach-to-regrasp bimanual movements and no synchrony in timing was taken into account. In this paper we extend the previous model in order to accomplish bimanual manipulation tasks by synchronously moving both arms and hands of an anthropomorphic robotic system. Specifically, the new extended model has been designed for two different tasks with different degrees of difficulty. Numerical results were obtained by the implementation of the IPOPT solver embedded in our MATLAB simulator.

Towards human-like bimanual movements in anthropomorphic robots: a nonlinear optimization approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

Development of a methodology to incorporate risk and uncertainty in electricity power planning

Dissertação de mestrado em Engenharia Industrial

Redução de contaminações: um projeto de melhoria contínua em ambiente seis sigma

Dissertação de mestrado integrado em Engenharia e Gestão Industrial