Multi-scale vegetation classification using earth observation data of the Sundarban mangrove forest, Bangladesh.

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

Contract-program evaluation: Impact of the DRG classification system on hospitals' outputs

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

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.

Análise comparativa de sistemas de classificação de doentes de reabilitação

RESUMO - Caracterização do problema: A inadequação e ineficácia do sistema de financiamento ―por diária‖ dos cuidados de reabilitação resultaram na necessidade de criação de sistemas de classificação de doentes de reabilitação em regime de internamento, em muitos países. Também em Portugal é necessário implementar um sistema de financiamento, baseado num sistema de classificação de doentes, ajustado pela complexidade e necessidade de cuidados destes doentes. Objectivos: Caracterização dos cuidados de reabilitação em Portugal, e do actual sistema de financiamento destes doentes; realização de uma revisão de literatura dos sistemas de classificação de doentes de reabilitação já existentes, de modo a compreender quais as variáveis de agrupamento utilizadas e qual a capacidade de previsão dos custos destes mesmos sistemas; perceber a importância da implementação de um dos sistemas de classificação em Portugal, e quais as suas vantagens. Metodologia: Da revisão de literatura efectuada, foram encontrados quatro sistemas de classificação de doentes implementados e/ou em vias de serem implementados como base para um sistema de financiamento, nos EUA, Austrália e Canadá. Foi efectuada uma extensa caracterização e análise crítica dos mesmos. Conclusões: Podemos concluir, que dos poucos sistemas de classificação de doentes de reabilitação existentes, optou-se pelo estudo de uma possível adopção do sistema norte-americano para a realidade portuguesa, por ser o único sistema de classificação já utilizado para fins de financiamento para todos os doentes de reabilitação desde 2002, o que inclui mais variáveis de decisão na classificação dos doentes, e o que permite a maior previsão dos custos dos doentes em termos percentuais.

A variabilidade no consumo de recursos nos traumatismos crânio-encefálicos

RESUMO - Portugal atravessa um contexto socioeconómico conturbado onde se têm imposto várias reformas, nomeadamente ao nível da Saúde. Atualmente, o financiamento do internamento hospitalar é feito por grupos de diagnóstico homogéneo com base num sistema prospetivo, reunindo os episódios em grupos clinicamente coerentes e homogéneos, de acordo com o consumo de recursos necessário para o seu tratamento, tendo em conta as suas características clínicas. Apesar do objetivo deste sistema de classificação de doentes, é aceite que existe variabilidade no consumo de recursos entre episódios semelhantes, sendo que a mesma variabilidade pode representar uma diferença significativa nos custos de tratamento. Os Traumatismos Cranio-encefálicos são considerados um problema de saúde pública, pelo que os episódios selecionados para este estudo tiveram por base os diagnósticos mais comuns relacionados com esta problemática. Procurou-se estudar a relação entre o consumo esperado e o observado bem como, a forma em que esta relação é influenciada por diferentes variáveis. Para verificar a existência de variabilidade no consumo de recursos, bem como as variáveis mais influentes, foi utilizada a regressão linear e constatou-se que variáveis como a idade, o destino pós-alta e o distrito têm poder explicativo sobre esta relação. Verificou-se igualmente que na sua generalidade as instituições hospitalares são eficientes na prestação de cuidados. Compreender a variabilidade do consumo de recursos e as suas implicações no financiamento poderá suscitar a dúvida se a utilização de GDH será o mais adequado à realidade portuguesa, de forma a ajustar as políticas de saúde, mantendo a eficiência e a qualidade dos cuidados.

Development of novel active pharmaceutical ionic liquids and salts based on antibiotics and anti-fungal drugs

Ionic Liquids (ILs) are class of compounds, which have become popular since the mid-1990s. Despite the fact that ILs are defined by one physical property (melting point), many of the potential applications are now related to their biological properties. The use of a drug as a liquid can avoid some problems related to polymorphism which can influence a drug´s solubility and thus its dosages. Also, the arrangement of the anion or cation with a specific drug might be relevant in order to: a) change the correspondent biopharmaceutical drug classification system; b) for the drug formulation process and c) the change the Active Pharmaceutical Ingredients’ (APIs). The main goal of this Thesis is the synthesis and study of physicochemical and biological properties of ILs as APIs from beta-lactam antibiotics (ampicillin, penicillin G and amoxicillin) and from the anti-fungal Amphotericin B. All the APIs used here were neutralized in a buffer appropriate hydroxide cations. The cation hydroxide was obtained on Amberlite resin (in the OH form) in order to exchange halides. The biological studies of these new compounds were made using techniques like the micro dilution and colorimetric methods. Overall a total of 19 new ILs were synthesised (6 ILs based on ampicillin, 4 ILs, based on amoxicillin, 6 ILs based on penicillin G and 4 ILs based on amphotericin B) and characterized by spectroscopic and analytical methods in order to confirm their structure and purity. The study of the biological properties of the synthesised ILs showed that some have antimicrobial activity against bacteria and yeast cells, even in resistant bacteria. Also this work allowed to show that ILs based on ampicillin could be used as anti-tumour agents. This proves that with a careful selection of the organic cation, it is possible to provoke important physico-chemical and biological alteration in the properties of ILs-APIs with great impact, having in mind their applications.

Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam

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

Automatic sleep apnea detection and sleep classification using the ECG and the SpO2 signals

Dissertation for a Masters Degree in Computer and Electronic Engineering

The contribution of multitemporal information from multispectral satellite images for automatic land cover classification at the national scale

Thesis submitted to the Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management – Geographic Information Systems

Land cover dynamics in Savanna Ecosystem of Borena Ethiopia

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

Recent droughts and the impact of North Atlantic Oscillation in Iberia; a spatiotemporal analysis based on vegetation temperature condition Index (VTCI)

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

Fluvial system restoration – case study: river Tua

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, Perfil de Engenharia de Sistemas Ambientais

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.