Grout optimization for masonry consolidation

Tese apresentada para obtenção do Grau de Doutor em Engenharia Civil na especialidade de Reabilitação do Património Edificado, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Business model optimization of Prego Gourmet

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

Time series morphological analysis applied to biomedical signals events detection

Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

An RF LC Q-enhanced CMOS iter using integrated inductors with layout optimization

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Multi-GPU support on the marrow algorithmic skeleton framework

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Exopolysaccharide production by Enterobacter A47: optimization of cultivation conditions and study of polymer functional properties

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Optimization based design of LC voltage controlled oscilators

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

Optimization of ring oscillators

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

The optimization of the complaints management system

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

Optimization of investment promotion tools for Portugal: Specific recommendations to attract investments from Germany

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

Optimization of randomly amplified polymorphic DNA-polymerase chain reaction for molecular typing of Salmonella enterica serovar Typhi

Optimization of the RAPD reaction for characterizing Salmonella enterica serovar Typhi strains was studied in order to ensure the reproducibility and the discriminatory power of this technique. Eight Salmonella serovar Typhi strains isolated from various regions in Brazil were examined for the fragment patterns produced using different concentrations of DNA template, primer, MgCl2 and Taq DNA polymerase. Using two different low stringency thermal cycle profiles, the RAPD fingerprints obtained were compared. A set of sixteen primers was evaluated for their ability to produce a high number of distinct fragments. We found that variations associated to all of the tested parameters modified the fingerprinting patterns. For the strains of Salmonella enterica serovar Typhi used in this experiment, we have defined a set of conditions for RAPD-PCR reaction, which result in a simple, fast and reproducible typing method.

Controlling gene expression in enterobacteriaceae: studies on sRNAs and strategies for synthetic biology

Dissertation presented to obtain the Master Degree in Molecular, Genetics and Biomedicine

Evaluation and optimization of a session-based middleware for data management

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Development of a satellite based PM10 concentration product for urban areas

Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente

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.