UAV - based imagery processing using structure from motion and remote sensing technology

With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

Mining protein structure data

The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database. In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%. In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem. In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models. The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work. The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.

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.

Liderança e estratégia em contexto de inovação nas organizações de saúde : estudos de caso

RESUMO - A presente investigação procura descrever e compreender como a estratégia influencia a liderança e como esta por sua vez interage nos processos de inovação e mudança, em organizações de saúde. Desconhecem-se estudos anteriores, em Portugal, sobre este problema de investigação e da respectiva problemática teórica. Trata-se de um estudo exploratório e descritivo que envolveu 5 organizações de saúde, 4 portuguesas e 1 espanhola, 4 hospitais (dois privados e uma unidade local de saúde). Utilizou-se uma abordagem mista de investigação (qualitativa e quantitativa), que permitiu compreender, através do estudo de caso, como se articulam a estratégia, a liderança e a inovação nessas cinco organizações de saúde. Os resultados do estudo empírico foram provenientes da recolha de dados efectuada através de observação directa e estruturada, entrevistas com actores-chave, documentos em suporte de papel e digital, e ainda inquérito por questionário de auto-resposta a uma amostra (n=165) de actores do line e do staff (Administradores, Directores de Serviço/Departamento, Enfermeiros Chefe e Técnicos Coordenadores) das cinco organizações de saúde. Tanto o modelo de Miles & Snow (estratégia organizacional), como o modelo dos valores contrastantes de Quinn (cultura organizacional e liderança), devidamente adaptados, mostram-se heurísticos e provam poder aplicar-se às organizações de saúde, apesar a sua complexidade e especificidade. Tanto as organizações do sector público como do sector privado e organizações públicas concessionadas (parcerias público privadas) podem ser acompanhadas e monitorizadas nos seus processos de inovação e mudança, associados aos tipos de cultura, liderança ou estratégia organizacionais adoptadas. As organizações de saúde coabitam num continuum, onde o ambiente (quer interno quer externo) e o tempo são factores decisivos que condicionam a estratégia a adoptar. Também aqui, em função da realidade dinâmica e complexa onde a organização se move, não há tipologias puras. Há, sim, uma grande plasticidade e flexibilidade organizacionais. Quanto aos líderes, exercem habitualmente a autoridade formal, pela via da circular normativa. Não são pares (nem primi inter pares), colocam-se por vezes numa posição de superioridade, quando o mais adequado seria a relação de parceria, cooperação e procura de consensos, com todos os colaboradores, afim de serem eles os verdadeiros protagonistas e facilitadores da mudança e das inovações. Como factores facilitadores da inovação e da mudança, encontrámos nas organizações de saúde estudadas o seguinte: facilidade de aprender; visão/missão adequadas; ausência de medo de falhar; e como factores inibidores: falta de articulação entre serviços/departamentos; estrutura organizacional (no sector público muito verticalizada e no sector privado mais horizontalizada); resistência à mudança; falta de tempo; falha no tempo de reacção (o tempo útil para a tomada de decisão é, por vezes, ultrapassado). --------ABSTRACT - The present research seeks to describe and understand how strategy influences leadership and how this in turn interacts in the process of innovation and change in health organizations. Previous studies on these topics are unknown in Portugal, about this research problem and its theoretical problem. This is an exploratory and descriptive study that involved 5 health organizations, 4 Portuguese and 1 Spanish. We used a mixed approach of research (qualitative and quantitative), which enabled us to understand, through case study, how strategy and leadership were articulated with innovation in these five health organizations. The results of the empirical study came from data collection through direct observation, interviews with key actors, documents and survey questionnaire answered by 165 participants of line and staff (Administrators, Medical Directors of Service /Department, Head Nurses and Technical Coordinators) of the five health organizations. Despite their complexity and specificity, both the model of Miles & Snow (organizational strategy) and the model of the Competing Values Framework of Quinn (organizational culture and leadership), suitably adapted, have proven heuristic power and able to be apply to healthcare organizations. Both public sector organizations, private and public organizations licensed (public-private partnerships) can be tracked and monitored in their processes of innovation and change in order to understand its kind of culture, leadership or organizational strategy adopted. Health organizations coexist in a continuum, where the environment (internal and external) and time are key factors which determine the strategy to adopt. Here too depending on the dynamic and complex reality where the organization moves, there are no pure types. There is indeed a great organizational plasticity and flexibility. Leaders usually carry the formal authority by circular normative. They are not pairs (or primi inter pares). Instead they are, sometimes, in a position of superiority, when the best thing is partnership, collaboration, cooperation, building consensus and cooperation with all stakeholders, in order that they are the real protagonists and facilitators of change and innovation. As factors that facilitate innovation and change, we found in health organizations studied, the following: ease of learning; vision / mission appropriate; absence of fear of failure, and as inhibiting factors: lack of coordination between agencies / departments; organizational structure (in the public sector it is too vertical and in the private sector it is more horizontal); resistance to change; lack of time and failure in the reaction time (the time for decision making is sometimes exceeded).

The national physics and chemistry exams and the learning of sciences

Dissertação apresentada para obtenção do Grau de Doutor em Ciências da Educação, pela Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa

Machine learning Gaussian short rate

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

Garland, since 1776- a unique ownership structure

The case is based on Garland, a 240 years old Portuguese family business, now owned by the Dawson family. It focuses on a decision made 50 years ago, aligned with what had been the company’s history, about the ownership rules for family members, which influences the ownership structure of the firm. It addresses the main issues about ownership in family businesses, and tackles the problem of succession planning and fair process. It contains a teaching note to support the utilization of the case in a classroom context, with learning objectives, target audience, a teaching plan, questions and proposed answers, and theory that relates to the case. It is also complemented with an epilogue and an overview of the case.

Does the existing Corporate Governance structure and strict Legal Framework, affect the strategic decisionmaking of CEOs?

This thesis is a case study on Corporate Governance and Business Ethics, using the Portuguese Corporate Law as a general setting. The thesis was conducted in Portugal with illustrations on past cases under the Business Judgment Rule of the State of Delaware, U.SA along with illustrations on current cases in Portugal under the Portuguese Judicial setting, along with a comparative analysis between both. A debate is being considered among scholars and executives; a debate on best practices within corporate governance and corporate law, associated with recent discoveries of unlawful investments that lead to the bankruptcy of leading institutions and an aggravation of the crisis in Portugal. The study aimed at learning possible reasons and causes for the current situation of the country’s corporations along with attempts to discover the best way to move forward. From the interviews and analysis conducted, this paper concluded that the corporate governance structure and legal frameworks in Portugal were not the sole influencers behind the actions and decisions of Corporate Executives, nor were they the main triggers for the recent corporate mishaps. But it is rather a combination of different factors that played a significant role, such as cultural and ethical aspects, individual personalities, and others all of which created gray areas beyond the legal structure, which in turn accelerated and aggravated the corporate governance crisis in the country.