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

Velocity estimation of moving ships using C-band SLC SAR data

A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.

RESTAVEC – from haitian slave child to middle-class american

Trabalho de Projeto apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Tradução e Interpretação Especializadas, sob orientação da Doutora Clara Sarmento

Performance Issues in Biped Walking Robots

This paper presents the dynamic analysis of robotic biped systems. The main goal is to gain insight into the phenomena of walking and to evaluate its performance. In this study, we propose three methods to quantitatively measure the dynamic efficiency of walking: energy analysis, perturbation analysis and lowpass frequency analysis. In order to accomplish this goal, the prescribed motion of the biped is completely characterised in terms of a set of locomotion variables, namely: step lenght, hip height, hip ripple, hip offset, foot clearance and link lenghts. based on these variables and their influence, the performance measures aer discussed and the results compared with those observed in nature.

Towards a classification scheme for musical sounds

Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2013

Visualizing control systems performance: A fractional perspective

This article presents a novel method for visualizing the control systems behavior. The proposed scheme uses the tools of fractional calculus and computes the signals propagating within the system structure as a time/frequency-space wave. Linear and nonlinear closed-loop control systems are analyzed, for both the time and frequency responses, under the action of a reference step input signal. Several nonlinearities, namely, Coulomb friction and backlash, are also tested. The numerical experiments demonstrate the feasibility of the proposed methodology as a visualization tool and motivate its extension for other systems and classes of nonlinearities.

Efficiency of strengthening techniques assessed for existing masonry buildings

The Azores archipelago is a zone with a vast cultural heritage, presenting a building stock mainly constructed in traditional stone masonry. It is known that this type of construction exhibits poor behaviour under seismic excitations; however it is extensively used in seismic prone areas, such as this case. The 9th of July of 1998 earthquake was the last seismic event in the islands, leaving many traditional stone constructions severely damaged or totally destroyed. This scenario led to an effort by the local government of improving the seismic resistance of these constructions, with the application of several reinforcement techniques. This work aims to study some of the most used reinforcement schemes after the 1998 earthquake, and to assess their effectiveness in the mitigation of the construction’s seismic vulnerability. A brief evaluation of the cost versus benefit of these retrofitting techniques is also made, seeking to identify those that are most suitable for each building typology. Thus, it was sought to analyze the case of real structures with different geometrical and physical characteristics, by establishing a comparison between the seismic performance of reinforced and non-reinforced structures. The first section contains the analysis of a total of six reinforcement scenarios for each building chosen. Using the recorded 1998 earthquake accelerograms, a linear time-history analysis was performed for each reinforcement scenario. A comparison was then established between the maximum displacements, inter-storey drift and maximum stress obtained, in order to evaluate the global seismic response of each reinforced structure. In the second part of the work, the examination of the performance obtained in the previous section, in relation to the cost of implementing each reinforcement technique, allowed to draw conclusions concerning the viability of implementing each reinforcement method, based on the book value of the buildings in study.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Quantification of the TMS-EEG response in epilepsy

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Sustainability of systems interoperability in dynamic business networks

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

Sistema de detecção de fogo e detecção e seguimento de objectos

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

Using GIS to map the spatial and temporal occurrence of cholera epidemic in Camaroon

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

Kinetics of IFN-gamma, TNF-alpha, IL-10 and IL-4 production by mononuclear cells stimulated with gp43 peptides, in patients cured of paracoccidioidomycosis

We analyzed the kinetics of cytokine production by mononuclear cells from 17 patients who had been treated for paracoccidioidomycosis, using the stimulus of gp43 peptide groups (43kDa glycoprotein of Paracoccidioides brasiliensis) at 0.1 and 1µM, gp43 (1µg/ml) and crude Paracoccidioides brasiliensis antigen (PbAg; 75µg/ml). IFN-gamma production was a maximum at 144 hours in relation to the G2 and G8 peptide groups at 1µM and was greatest at 144 hours when stimulated by gp43 and by PbAg. The maximum TNF-alpha production was at 144 hours for the G2 group (0.1µM) and for gp43. IL-10 production was highest after 48 and 72 hours for G7 and G6 at 1µM, respectively. We also suggest the best time for analysis of IL4 production. These results may contribute towards future studies with gp43 peptides and encourage further investigations with the aim of understanding the influence of these peptides on the production of inflammatory and regulatory cytokines.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.