Integrated approach to assess vulnerability of the Coastal Region of Bangladesh due to climate change

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

A conceptual model to approach the scaling process of social entreprises: The case of Cozinha com Alma

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Promoting Portuguese exports to Germany: A hand-on approach for the machinery and equipment sector

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Noise traders, rational traders, and the rest: A new approach to efficient financial markets

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

Microbiology of membrane bioreactors for wastewater treatment: a molecular approach

Dissertation presented to obtain the Ph.D degree in Engineering and Technology Sciences, Biotechnology.

From a project to an organisation: a Strategic Communication’s approach

Relatório de Estágio apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ciências da Comunicação, área de especialização em Comunicação Estratégica

Quality of process modeling using BPMN: a model-driven approach

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A clustering approach for vehicle routing problems with hard time windows

Dissertação para obtenção do Grau de Mestre em Logica Computicional

A semi-automatic approach to code smells detection

Eradication of code smells is often pointed out as a way to improve readability, extensibility and design in existing software. However, code smell detection remains time consuming and error-prone, partly due to the inherent subjectivity of the detection processes presently available. In view of mitigating the subjectivity problem, this dissertation presents a tool that automates a technique for the detection and assessment of code smells in Java source code, developed as an Eclipse plugin. The technique is based upon a Binary Logistic Regression model that uses complexity metrics as independent variables and is calibrated by expert‟s knowledge. An overview of the technique is provided, the tool is described and validated by an example case study.

Studies towards modified chitooligosaccharides: a new approach to NAG-NAM moiety

Dissertação para obtenção do Grau de Mestre em Bioorgânica

Development of an integrative approach for the characterization of ecological risk on marine transition ecosystems: the Sado Estuary as a case study

Estuaries and other transitional waters are complex ecosystems critically important as nursery and shelter areas for organisms. Also, humans depend on estuaries for multiple socio-economical activities such as urbanism, tourism, heavy industry, (taking advantage of shipping), fisheries and aquaculture, the development of which led to strong historical pressures, with emphasis on pollution. The degradation of estuarine environmental quality implies ecologic, economic and social prejudice, hence the importance of evaluating environmental quality through the identification of stressors and impacts. The Sado Estuary (SW Portugal) holds the characteristics of industrialized estuaries, which results in multiple adverse impacts. Still, it has recently been considered moderately contaminated. In fact, many studies were conducted in the past few years, albeit scattered due to the absence of true biomonitoring programmes. As such, there is a need to integrate the information, in order to obtain a holistic perspective of the area able to assist management and decision-making. As such, a geographical information system (GIS) was created based on sediment contamination and biomarker data collected from a decade-long time-series of publications. Four impacted and a reference areas were identified, characterized by distinct sediment contamination patterns related to different hot spots and diffuse sources of toxicants. The potential risk of sediment-bound toxicants was determined by contrasting the levels of pollutants with available sediment quality guidelines, followed by their integration through the Sediment Quality guideline Quotient (SQG-Q). The SQG-Q estimates per toxicant or class was then subjected to georreferencing and statistical analyses between the five distinct areas and seasons. Biomarker responses were integrated through the Biomarkers Consistency Indice and georreferenced as well through GIS. Overall, in spite of the multiple biological traits surveyed, the biomarker data (from several organisms) are accordant with sediment contamination. The most impacted areas were the shipyard area and adjacent industrial belt, followed by urban and agricultural grounds. It is evident that the estuary, although globally moderately impacted, is very heterogeneous and affected by a cocktail of contaminants, especially metals and polycyclic aromatic hydrocarbon. Although elements (like copper, zinc and even arsenic) may originate from the geology of the hydrographic basin of the Sado River, the majority of the remaining contaminants results from human activities. The present work revealed that the estuary should be divided into distinct biogeographic units, in order to implement effective measures to safeguard environmental quality.

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

Proteomics based approach to understand tissue regeneration

Dissertation presented to obtain the PhD degree in Biochemistry

Wound Healing: a genetic approach in Drosophila

The wound healing response is an essential mechanism to maintain the integrity of epithelia and protect all organisms from the surrounding milieu. In the “purse-string” mechanism of wound closure, an injured epithelial sheet cinches its hole closed via an intercellular contractile actomyosin cable.(...)