Modeling of the lung impedance using a fractional order ladder network with constant phase elements

The self similar branching arrangement of the airways makes the respiratory system an ideal candidate for the application of fractional calculus theory. The fractal geometry is typically characterized by a recurrent structure. This study investigates the identification of a model for the respiratory tree by means of its electrical equivalent based on intrinsic morphology. Measurements were obtained from seven volunteers, in terms of their respiratory impedance by means of its complex representation for frequencies below 5 Hz. A parametric modeling is then applied to the complex valued data points. Since at low-frequency range the inertance is negligible, each airway branch is modeled by using gamma cell resistance and capacitance, the latter having a fractional-order constant phase element (CPE), which is identified from measurements. In addition, the complex impedance is also approximated by means of a model consisting of a lumped series resistance and a lumped fractional-order capacitance. The results reveal that both models characterize the data well, whereas the averaged CPE values are supraunitary and subunitary for the ladder network and the lumped model, respectively.

Spatial data infrastructures model for developing countries: A case study of Nigeria

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

Visualization of clusters in geo-referenced data using three-dimensional self-organizing maps

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

Web GIS to support irrigation management: a prototype for SAGRA network, Alentejo Portugal

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

Social network analysis applied to knowledge creation and transfer in the portuguese agricultural R&D field: an exploratory study

Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm

Enterprise information portals: potential for evaluating research for knowledge management and human capital assets using social network analysis

Paper presented at the ECKM 2010 – 11th European Conference on Knowledge Management, 2-3 September, 2010, Famalicão, Portugal. URL: http://www.academic-conferences.org/eckm/eckm2010/eckm10-home.htm

Avaliação do potencial eólico para geração de energia eléctrica

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

On the applicability of joint inversion of gravity and resistivity data to the study of a tectonic sedimentary basin in Northern Portugal

The Chaves basin is a pull-apart tectonic depression implanted on granites, schists, and graywackes, and filled with a sedimentary sequence of variable thickness. It is a rather complex structure, as it includes an intricate network of faults and hydrogeological systems. The topography of the basement of the Chaves basin still remains unclear, as no drill hole has ever intersected the bottom of the sediments, and resistivity surveys suffer from severe equivalence issues resulting from the geological setting. In this work, a joint inversion approach of 1D resistivity and gravity data designed for layered environments is used to combine the consistent spatial distribution of the gravity data with the depth sensitivity of the resistivity data. A comparison between the results from the inversion of each data set individually and the results from the joint inversion show that although the joint inversion has more difficulty adjusting to the observed data, it provides more realistic and geologically meaningful models than the ones calculated by the inversion of each data set individually. This work provides a contribution for a better understanding of the Chaves basin, while using the opportunity to study further both the advantages and difficulties comprising the application of the method of joint inversion of gravity and resistivity data.

Building a person home behavior model based on data from smart house sensors 2015

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

4Sensing - decentralized processing for participatory sensing data

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática.

Comparing wind generation profiles: A circular data approach

The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.

Deteção de avarias na caixa de engrenagens de aerogeradores

Ao longo dos últimos anos tem-se assistido a um forte desenvolvimento e crescimento do número de parques eólicos instalados no mundo, o que leva a que seja necessário o incremento de ferramentas que permitam aperfeiçoar os sistemas de monitorização e controlo atualmente existentes. Por outro lado, não se deve deixar de ter em conta os custos elevados de operação e manutenção dos sistemas eólicos bem como o facto de os aerogeradores estarem localizadas em locais remotos ou offshore, o que faz aumentar os custos associados à sua exploração. A dissertação nasce da intenção clara do mercado em apostar na supervisão e previsão de avarias graves, de forma a minimizar os encargos subjacentes. Este trabalho de dissertação visa a utilização de redes neuronais para criar uma ferramenta informática de previsão de avarias em caixas de engrenagens em aerogeradores. As redes neuronais são ferramentas informáticas ideais para trabalhar com muita informação, sendo que a sua aplicação depende da qualidade e quantidade dos dados. Para tal irá ser efetuado um estudo em um parque eólico, no qual se analisará as principais avarias detetadas bem como as grandezas que deverão integrar a construção desta rede neuronal. Assim sendo, a informação relativa às diversas máquinas existentes num parque, é de enorme importância para a definição e otimização da rede neuronal a construir. Os resultados obtidos neste trabalho com a aplicação de redes neuronais para a previsão de avarias em caixas de engrenagens do parque eólico de estudo, provam que é possível realizar uma deteção da avaria bem como uma constatação de que a reparação possa ter sido bem efetuada ou mal sucedida, podendo assim ser ajustados os programas de manutenção a efetuar e uma verificação das ações de reparação para sua validação.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Replication vs erasure coding in data centric storage for wireless sensor networks

In-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability.