Part I : Comparing derivatization methods for amino acids – one and two-step procedures using gas chromatography – flame ion detector (GC-FID) Part II: Story of an icon from its execution until its conservation

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Conservação e Restauro

New strategies to detect and understand genotype-by-environment interactions and QTL-by-environment interactions

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco, especialidade em Estatística

Emergência e declínio do piano na vida quotidiana madeirense (1821‐1930)

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Ciências Musicais

A CMMI-compliant requirements management and development process

Requirements Engineering has been acknowledged an essential discipline for Software Quality. Poorly-defined processes for eliciting, analyzing, specifying and validating requirements can lead to unclear issues or misunderstandings on business needs and project’s scope. These typically result in customers’ non-satisfaction with either the products’ quality or the increase of the project’s budget and duration. Maturity models allow an organization to measure the quality of its processes and improve them according to an evolutionary path based on levels. The Capability Maturity Model Integration (CMMI) addresses the aforementioned Requirements Engineering issues. CMMI defines a set of best practices for process improvement that are divided into several process areas. Requirements Management and Requirements Development are the process areas concerned with Requirements Engineering maturity. Altran Portugal is a consulting company concerned with the quality of its software. In 2012, the Solution Center department has developed and applied successfully a set of processes aligned with CMMI-DEV v1.3, what granted them a Level 2 maturity certification. For 2015, they defined an organizational goal of addressing CMMI-DEV maturity level 3. This MSc dissertation is part of this organization effort. In particular, it is concerned with the required process areas that address the activities of Requirements Engineering. Our main goal is to contribute for the development of Altran’s internal engineering processes to conform to the guidelines of the Requirements Development process area. Throughout this dissertation, we started with an evaluation method based on CMMI and conducted a compliance assessment of Altran’s current processes. This allowed demonstrating their alignment with the CMMI Requirements Management process area and to highlight the improvements needed to conform to the Requirements Development process area. Based on the study of alternative solutions for the gaps found, we proposed a new Requirements Management and Development process that was later validated using three different approaches. The main contribution of this dissertation is the new process developed for Altran Portugal. However, given that studies on these topics are not abundant in the literature, we also expect to contribute with useful evidences to the existing body of knowledge with a survey on CMMI and requirements engineering trends. Most importantly, we hope that the implementation of the proposed processes’ improvements will minimize the risks of mishandled requirements, increasing Altran’s performance and taking them one step further to the desired maturity level.

Customer relationship management at Siemens Healthcare – a diagnosis and proposal for strategy and market segmentation

Towards a holistic perspective of CRM, this project aims to diagnose and propose a strategy and market segmentation for Siemens Healthcare. The main underlying principle is to apply a full customer-centric outlook taking own business properties into consideration while preserving Siemens Healthcare’s culture and vision. Mainly focused on market segmentation, this project goes beyond established boundaries by employing an unbiased perspective of CRM while challenging current strategy, goals, processes, tools, initiatives and KPIs. In order to promote a sustainable business excellence strategy, this project aspires to streamline CRM strategic importance and driving the company one step forward.

Research study for an entrepreneurship practical guide

This thesis is a research study, which is aimed to be published later, in the form of a practical guide for those who have an idea and plan to go one step forward on the creation of a brand and/or a business. The main questions addressed are regarding the main concerns of an entrepreneur, identifiying the main topics that an entrepreneur's practical guide must approach. This work aims to provide relevant and important insights for those who want to start a business, taking in consideration some best practices, advises from entrepreneurs that have already started their own businesses and shared their experience. It means to provide a strong contribution to the Portuguese ecosystem, more specifically, startups, small companies, projects or ideas at seed or startup stage, brands, clubs, and every initiative which is starting from nothing, or almost nothing. Apart from books and online researches, primary information and testimonials were collected through an online survey, from a target audience of entrepreneurs, leading to the main findings of this study. The conclusion of this thesis is the gross index of the future startuper's practical guide, which will be divided in 4 different stages: Preparation, Implementation, Leverage and Closure.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Designing market-based instruments for biodiversity conservation: learning with the Australian experience and evaluating Portugal's potential

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão de Sistemas Ambientais

Aprendizagem autónoma (self-directed learning): relatório de um atelier pedagógico

Educação Médica. 1994, 5(3):178-181.

Learning to manage in knowledge-based organizations: the role of learning logs or portfolios

Paper presented at the 8th European Conference on Knowledge Management, Barcelona, 6-7 Sep. 2008 URL: http://www.academic-conferences.org/eckm/eckm2007/eckm07-home.htm

Portuguese entrepreneurial women – fostering learning communities

This article repports findings on a project - DONA EMPRESA - that the Portuguese Association of Women Entrepreneurs has been promoting for four years now. The project aims at supporting unemployed women, having a business idea, to create their own employment. So far about one hundred enterprises have been created in the scope of this project, their surviving rate being very high after one year of business running.

Recommending media content based on machine learning methods

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A learning approach to swarm-based path detection and tracking

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

Analysis of the progress of lifelong learning strategies of Portuguese Economics and Management Schools

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

Machine learning Gaussian short rate

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco