Lightweight monitoring of transactional memory programs

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Functional monolithic platforms for antibody purification

Dissertação para obtenção do Grau de Doutor em Química Sustentável

Service-oriented infrastructure to support the control, monitoring and management of a shop floor system

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Monitoring and modelling of membrane bioreactors for wastewater treatment incorporating 2D fluorescence spectroscopy

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica, Especialidade em Engenharia Bioquímica

Implementação e validação de um método de pesquisa e quantificação de Vitamina E por HPLC

As vitaminas são substâncias orgânicas presentes em muitos alimentos, em pequenas quantidades e indispensáveis ao funcionamento do organismo. A ausência sistemática destas resulta, quase sempre, em crescimento e desenvolvimento deficientes e em casos extremos pode conduzir a doenças graves, como por exemplo, a demência (vitaminas do complexo B), o raquitismo (vitamina D), o escorbuto (vitamina C). Em 1968 a American Food and Nutrition Board reconheceu oficialmente a vitamina E como um nutriente essencial para os seres humanos, pois possui uma importante função no organismo, como antioxidante, ao inibir a oxidação de lípidos insaturados e ao prevenir o dano oxidativo celular pela inativação de radicais livres e espécies reativas de oxigênio. O interesse nesta vitamina é cada vez maior, devido às funções que desempenha no organismo como agente antioxidante, envolvido no retardamento do envelhecimento e na proteção de doenças crônicas não transmissíveis, como Parkinson, Alzheimer, cancro e doenças cardiovasculares. O presente trabalho tem como objetivo a implementação e validação de um método de pesquisa e quantificação da vitamina E na manteiga por cromatografia líquida de alta eficiência, no laboratório de Química da empresa SGS, expandindo desta forma, as capacidades da empresa nesta área. Para tal foram avaliados parâmetros como linearidade, limites de deteção e quantificação, repetibilidade, precisão intermédia e exatidão. Os resultados mostram que o método é linear para uma gama de trabalho entre 5,00 e 50,00 mg/L com um limite de deteção e quantificação de 1,27 mg/L e 3,84 mg/L, respetivamente. O método apresentou repetibilidade e precisão intermédia aceitáveis, com coeficientes de variação inferiores a 5%, limite de repetibilidade de 1,37 mg/kg e variabilidade de resultados associados ao método de 0,19 mg/L. A exatidão do método foi aferida recorrendo a ensaios de recuperação, tendo-se obtido percentagens de recuperação médias superiores a 80%.

Wearable monitoring system for assistance dogs

Despite the recent progresses in robotics, autonomous robots still have too many limitations to reliably help people with disabilities. On the other hand, animals, and especially dogs, have already demonstrated great skills in assisting people in many daily situations. However, dogs also have their own set of limitations. For example, they need to rest periodically, to be healthy (physically and psychologically), and it is difficult to control them remotely. This project aims to “augment” the Assistance dog, by developing a system that compensates some of the dog weaknesses through a robotic device mounted on the dog harness. This specific study, involved in the COCHISE project, focuses on the development of a system for the monitoring of dogs activity and physiological parameters.

Social-media monitoring for cold-start recommendations

Generating personalized movie recommendations to users is a problem that most commonly relies on user-movie ratings. These ratings are generally used either to understand the user preferences or to recommend movies that users with similar rating patterns have rated highly. However, movie recommenders are often subject to the Cold-Start problem: new movies have not been rated by anyone, so, they will not be recommended to anyone; likewise, the preferences of new users who have not rated any movie cannot be learned. In parallel, Social-Media platforms, such as Twitter, collect great amounts of user feedback on movies, as these are very popular nowadays. This thesis proposes to explore feedback shared on Twitter to predict the popularity of new movies and show how it can be used to tackle the Cold-Start problem. It also proposes, at a finer grain, to explore the reputation of directors and actors on IMDb to tackle the Cold-Start problem. To assess these aspects, a Reputation-enhanced Recommendation Algorithm is implemented and evaluated on a crawled IMDb dataset with previous user ratings of old movies,together with Twitter data crawled from January 2014 to March 2014, to recommend 60 movies affected by the Cold-Start problem. Twitter revealed to be a strong reputation predictor, and the Reputation-enhanced Recommendation Algorithm improved over several baseline methods. Additionally, the algorithm also proved to be useful when recommending movies in an extreme Cold-Start scenario, where both new movies and users are affected by the Cold-Start problem.

Improving the early diagnostic of prostate cancer by multiple biomarker detection with new biosensing devices

Prostate cancer (PCa) is the most common form of cancer in men, in Europe (World Health Organization data). The most recent statistics, in Portuguese territory, confirm this scenario, which states that about 50% of Portuguese men may suffer from prostate cancer and 15% of these will die from this condition. Its early detection is therefore fundamental. This is currently being done by Prostate Specific Antigen (PSA) screening in urine but false positive and negative results are quite often obtained and many patients are sent to unnecessary biopsy procedures. This early detection protocol may be improved, by the development of point-of-care cancer detection devices, not only to PSA but also to other biomarkers recently identified. Thus, the present work aims to screen several biomarkers in cultured human prostate cell lines, serum and urine samples, developing low cost sensors based on new synthetic biomaterials. Biomarkers considered in this study are the following: prostate specific antigen (PSA), annexin A3 (ANXA3), microseminoprotein-beta (MSMB) and sarcosine (SAR). The biomarker recognition may occurs by means of molecularly imprinted polymers (MIP), which are a kind of plastic antibodies, and enzymatic approaches. The growth of a rigid polymer, chemically stable, using the biomarker as a template allows the synthesis of the plastic antibody. MIPs show high sensitivity/selectivity and present much longer stability and much lower price than natural antibodies. This nanostructured material was prepared on a carbon solid. The interaction between the biomarker and the sensing-material produces electrical signals generating quantitative or semi-quantitative data. These devices allow inexpensive and portable detection in point-of-care testing.

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Monitoring liquidity risk at BPI GA

Field lab: Business project

Implementação de método em HPLC para a determinação de PAH´s em óleos vegetais

Os Hidrocarbonetos Policíclicos Aromáticos (HPA’s), doravante designados PAH’s são considerados poluentes prioritários, devido às suas características tóxicas, cancerígenas e mutagénicas. No entanto, apenas 16 destes compostos são referidos na lista de compostos orgânicos prioritários, na qual estão inseridos os 4 PAH’s estudados neste trabalho - Benzo[a]antraceno, Benzo[a]Pireno, Benzo[b]fluoranteno e o criseno. A origem dos PAH’s no ambiente provém de fontes naturais e antropogénicas. Vários processos têm sido desenvolvidos para remover e/ou reduzir estes contaminantes no ambiente. A sua maioria passa por reduzir a poluição causada por fontes antropogénicas. No entanto, devido à dificuldade de remover totalmente estes contaminantes é necessário controlar a concentração destes compostos durante o processo de fabrico de alimentos. Os PAH’s podem ser encontrados em diferentes géneros alimentícios tais como óleos vegetais. Sendo a Sovena produtora destes surge como objectivo deste trabalho implementar e validar um método analítico para a quantificação dos 4 PAH’s nos óleos crus e refinados de forma a garantir que o contaminante é eliminado ou reduzido até níveis aceitáveis. Esta quantificação foi feita em HPLC com detector de fluorescência (FLD), utilizando-se o método da adição de padrão interno, neste caso o Benzo[b]Criseno. Para avaliar a linearidade do método procedeu-se à representação gráfica da função Área=f (concentração), obtendo – se uma função linear na gama de 1 a 50μg/kg. A média da precisão medida através do coeficiente de variação variou entre 1,63 e 7,49%, a exactidão obtida pela média da percentagem de recuperação variou entre 65,0 e 107,5% sem matriz e entre 59,2 e 87,8% com matriz (óleo alimentar). O limite de detecção obtido foi de 0,5 μg/kg e o limite de quantificação 1 μg/kg. Através da comparação de resultados com laboratórios externos foi possível um constante desenvolvimento no sentido de melhorar os resultados.

A indústria de defesa na cooperação Brasil-Portugal

The global dynamics of alliances are strongly determined by the level of cooperation among states. This cooperation can be embodied in various aspects, but the level of defense and security cooperation becomes usually more doctrinal and lasting. By the nature of sovereignty that instills in the bilateral relationship, cooperation at defense and security level can leverages other forms of cooperation. The circumstances and relational balance between Brazil and Portugal seem to evolve towards distancing opportunities, despite they are culturally and institutionally untainted. The economic dynamics, the strategic projection in global sustainability terms, the scale and ambition of Brazilian regional leadership, contrasts with the actual context of Portugal, distancing himself both on the stage where they operate. On the other hand, the historical and cultural roots, the language, the affinity of the peoples of CPLP and some opportunities for economic niches, trend to attract both countries. The condition of Portugal in NATO and Europe, coupled with the ability to export technical and human resources to value-added for Brazil, seems also to become approaching factors. On the balance of these dynamics, there is a set of exogenous factors (economic, external global relations matrix, regional stability, among others), which are not always controlled by any of both countries. These factors call for strong capacity for foresight analysis and decision making, with the inherent risk. There is cooperation vectors that are not apparently penalized by geographic distance, or by the difference of realities. Among these vectors we shall highlight synergies in technological niches, highly tradable goods and, mostly, using the domain of dual technologies. The thirteen niches herein identified are: Monitoring, Navigation, Command and Control, Electronics, Optoelectronics, Communication and remote sensing, Information Technologies, Flight Simulation, Specialized Training, Fiber Optic Sensors, Materials Engineering, Nanotechnology and Communications. Cumulating with identified opportunities in traditional relational framework, both countries are growing (in geography and economic terms) into the Atlantic, making it a central element in the bilateral approach. By being at the same time a growing stage of disputes and which stability tends to be threatened, it will be done an analysis of these synergistic vectors, superimposed on the impact on Atlantic securitization process.

A new credit monitoring framework for agents' networks

The purpose of this work is to develop a practicable approach for Telecom firms to manage the credit risk exposition to their commercial agents’ network. Particularly it will try to approach the problem of credit concession to clients’ from a corporation perspective and explore the particular scenario of agents that are part of the commercial chain of the corporation and therefore are not end-users. The agents’ network that served as a model for the presented study is composed by companies that, at the same time, are both clients and suppliers of the Telecommunication Company. In that sense the credit exposition analysis must took into consideration all financial fluxes, both inbound and outbound. The current strain on the Financial Sector in Portugal, and other peripheral European economies, combined with the high leverage situation of most companies, generates an environment prone to credit default risk. Due to these circumstances managing credit risk exposure is becoming increasingly a critical function for every company Financial Department. The approach designed in the current study combined two traditional risk monitoring tools: credit risk scoring and credit limitation policies. The objective was to design a new credit monitoring framework that is more flexible, uses both external and internal relationship history to assess risk and takes into consideration commercial objectives inside the agents’ network. Although not explored at length, the blueprint of a Credit Governance model was created for implementing the new credit monitoring framework inside the telecom firm. The Telecom Company that served as a model for the present work decided to implement the new Credit Monitoring framework after this was presented to its Executive Commission.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.