36 resultados para Decision Tree


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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.

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Mycobacterium avium Complex (MAC) comprises microorganisms that affect a wide range of animals including humans. The most relevant are Mycobacterium avium subspecies hominissuis (Mah) with a high impact on public health affecting mainly immunocompromised individuals and Mycobacterium avium subspecies paratuberculosis (Map) causing paratuberculosis in animals with a high economic impact worldwide. In this work, we characterized 28 human and 67 porcine Mah isolates and evaluated the relationship among them by Multiple-Locus Variable number tandem repeat Analysis (MLVA). We concluded that Mah population presented a high genetic diversity and no correlations were inferred based on geographical origin, host or biological sample. For the first time in Portugal Map strains, from asymptomatic bovine faecal samples were isolated highlighting the need of more reliable and rapid diagnostic methods for Map direct detection. Therefore, we developed an IS900 nested real time PCR with high sensitivity and specificity associated with optimized DNA extraction methodologies for faecal and milk samples. We detected 83% of 155 faecal samples from goats, cattle and sheep, and 26% of 98 milk samples from cattle, positive for Map IS900 nested real time PCR. A novel SNPs (single nucleotide polymorphisms) assay to Map characterization based on a Whole Genome Sequencing analysis was developed to elucidate the genetic relationship between strains. Based on sequential detection of 14 SNPs and on a decision tree we were able to differentiate 14 phylogenetic groups with a higher discriminatory power compared to other typing methods. A pigmented Map strain was isolated and characterized evidencing for the first time to our knowledge the existence of pigmented Type C strains. With this work, we intended to improve the ante mortem direct molecular detection of Map, to conscientiously aware for the existence of Map animal infections widespread in Portugal and to contribute to the improvement of Map and Mah epidemiological studies.

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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.

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Impact Assessment and Project Appraisal, vol. 22, n.1, March 2004, p. 47–62

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Dissertação apresentada na faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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Over the last fifty years mobility practices have changed dramatically, improving the way travel takes place, the time it takes but also on matters like road safety and prevention. High mortality caused by high accident levels has reached untenable levels. But the research into road mortality stayed limited to comparative statistical exercises which go no further than defining accident types. In terms of sharing information and mapping accidents, little progress has been mad, aside from the normal publication of figures, either through simplistic tables or web pages. With considerable technological advances on geographical information technologies, research and development stayed rather static with only a few good examples on dynamic mapping. The use of Global Positioning System (GPS) devices as normal equipments on automobile industry resulted in a more dynamic mobility patterns but also with higher degrees of uncertainty on road traffic. This paper describes a road accident georeferencing project for the Lisbon District involving fatalities and serious injuries during 2007. In the initial phase, individual information summaries were compiled giving information on accidents and its majour characteristics, collected by the security forces: the Public Safety Police Force (Polícia de Segurança Pública - PSP) and the National Guard (Guarda Nacional Republicana - GNR). The Google Earth platform was used to georeference the information in order to inform the public and the authorities of the accident locations, the nature of the location, and the causes and consequences of the accidents. This paper also gives future insights about augmented reality technologies, considered crucial to advances to road safety and prevention studies. At the end, this exercise could be considered a success because of numerous consequences, as for stakeholders who decide what to do but also for the public awareness to the problem of road mortality.

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Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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World Transport Policy & Practice, Vol.6, nº2, (2000)

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Based on the report for Project III of the PhD programme on Technology Assessment and prepared for the Winter School that took place at Universidade Nova de Lisboa, Caparica Campus on the 6th and 7th of December 2010.

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Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering

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Based on the report for “Project IV” unit of the PhD programme on Technology Assessment. This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Manuel Laranja (ISEG-UTL). Other members of the thesis committee are Stefan Kuhlmann (Twente University), Leonhard Hennen (Karlsruhe Institute of Technology-ITAS), Tiago Santos Pereira (Universidade de Coimbra/CES) and Cristina Sousa (FCT-UNL).

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Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Michael Decker (Karlsruhe Institute of Technology-ITAS). Other members of the thesis committee are Carlos Alberto da Silva (University of Évora), José Maria de Albuquerque (Institute of Welding and Quality), Lotte Steuten (University of Twente), Mário Forjaz Secca (FCT-UNL) and Nelson Chibeles Martins (FCT-UNL).

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

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

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Submitted to the graduate faculty Universidade Nova de Lisboa – Faculdade de Ciências e Tecnologia in partial fulfillment of the requirements for the degree of Master in Industrial Engineering