Ontology-based representation and generation of workflows for micro-task human-machine computation

Doctoral Program in Computer Science

Mapping numbers onto space in preschool children and adults

Tese de Doutoramento em Psicologia - Especialidade em Psicologia Experimental e Ciências Cognitivas

Relação entre regulação das ordens profissionais e gestão jurisdicional dos profissionais de contabilidade: estudo comparado entre Portugal e o Brasil

Tese de Doutoramento em Ciência da Administração

Arquitecturas imaginárias. Espaço real e ilusório no Barroco português

Tese de Doutoramento em Arquitectura / Cultura Arquitectónica.

3D representation of the urban evolution of Braga using the cityengine tool

The morphological evolution of the city of Braga has been the subject of several studies focusing on different urban areas in different periods. Using the accumulated knowledge provided by the available archaeological, historical and iconographic data of Braga, from the Roman times to the nineteenth century, we intend to present a working methodology for 3D representation of urban areas and its evolution, using the CityEngine ESRI tool. Different types of graphic and cartographic data will be integrated in an archaeological information system for the characterization of urban buildings. Linking this information system to the rules of characterization of urban spaces through the CityEngine tool, we can create the 3D urban spaces and their changes. The building characterization rules include several parameters of architectural elements that can be dynamically changed according the latest information. This methodology will be applied to the best known areas within of the city allowing the creation of different and dynamic layouts. Considerations about the concepts, challenges and constraints of using the CityEngine tool for recording and representing urban evolution knowledge will be discussed.

Aplicação da linha de equilíbrio no planeamento e controlo da construção

Dissertação de mestrado integrado em Engenharia Civil

Automatically estimating iSAX parameters

The Symbolic Aggregate Approximation (iSAX) is widely used in time series data mining. Its popularity arises from the fact that it largely reduces time series size, it is symbolic, allows lower bounding and is space efficient. However, it requires setting two parameters: the symbolic length and alphabet size, which limits the applicability of the technique. The optimal parameter values are highly application dependent. Typically, they are either set to a fixed value or experimentally probed for the best configuration. In this work we propose an approach to automatically estimate iSAX’s parameters. The approach – AutoiSAX – not only discovers the best parameter setting for each time series in the database, but also finds the alphabet size for each iSAX symbol within the same word. It is based on simple and intuitive ideas from time series complexity and statistics. The technique can be smoothly embedded in existing data mining tasks as an efficient sub-routine. We analyze its impact in visualization interpretability, classification accuracy and motif mining. Our contribution aims to make iSAX a more general approach as it evolves towards a parameter-free method.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)