A model for heterogeneous networks management and Performance evaluation

In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.

A Model to Evaluate Vertical Handovers on JRRM

In a heterogeneous cellular networks environment, users behaviour and network deployment configuration parameters have an impact on the overall Quality of Service. This paper proposes a new and simple model that, on the one hand, explores the users behaviour impact on the network by having mobility, multi-service usage and traffic generation profiles as inputs, and on the other, enables the network setup configuration evaluation impact on the Joint Radio Resource Management (JRRM), assessing some basic JRRM performance indicators, like Vertical Handover (VHO) probabilities, average bit rates, and number of active users, among others. VHO plays an important role in fulfilling seamless users sessions transfer when mobile terminals cross different Radio Access Technologies (RATs) boundaries. Results show that high bit rate RATs suffer and generate more influence from/on other RATs, by producing additional signalling traffic to a JRRM entity. Results also show that the VHOs probability can range from 5 up to 65%, depending on RATs cluster radius and users mobility profile.

An Efficient Long Distance Echo Canceller

This paper describes an implementation of a long distance echo canceller, operating on full-duplex with hands-free and in real-time with a single Digital Signal Processor (DSP). The proposed solution is based on short length adaptive filters centered on the positions of the most significant echoes, which are tracked by time delay estimators, for which we use a new approach. To deal with double talking situations a speech detector is employed. The floating-point DSP TMS320C6713 from Texas Instruments is used with software written in C++, with compiler optimizations for fast execution. The resulting algorithm enables long distance echo cancellation with low computational requirements, suited for embbeded systems. It reaches greater echo return loss enhancement and shows faster convergence speed when compared to the conventional approach. The experimental results approach the CCITT G.165 recommendation levels.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Design and performance of a novel low-density parity-check code for distributed video coding

Low-density parity-check (LDPC) codes are nowadays one of the hottest topics in coding theory, notably due to their advantages in terms of bit error rate performance and low complexity. In order to exploit the potential of the Wyner-Ziv coding paradigm, practical distributed video coding (DVC) schemes should use powerful error correcting codes with near-capacity performance. In this paper, new ways to design LDPC codes for the DVC paradigm are proposed and studied. The new LDPC solutions rely on merging parity-check nodes, which corresponds to reduce the number of rows in the parity-check matrix. This allows to change gracefully the compression ratio of the source (DCT coefficient bitplane) according to the correlation between the original and the side information. The proposed LDPC codes reach a good performance for a wide range of source correlations and achieve a better RD performance when compared to the popular turbo codes.

Directional Moving Target Indication for Civil Traffic Monitoring Using Single Channel SAR

This paper presents a novel moving target indicator which is selective with respect to a direction of interest. Preliminary results indicate that the obtained selectivity may have high interest in civil traffic monitoring using single channel SAR data.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.

GuideMe: service for consulting, publication and recommendation of touristic locations

Trabalho de Projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Modelos de simulação em MATSim aplicados à análise de sistemas de transporte

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

Cooperative framework for open real-time systems

Actualmente, os sistemas embebidos estão presentes em toda a parte. Embora grande parte da população que os utiliza não tenha a noção da sua presença, na realidade, se repentinamente estes sistemas deixassem de existir, a sociedade iria sentir a sua falta. A sua utilização massiva deve-se ao facto de estarem practicamente incorporados em quase os todos dispositivos electrónicos de consumo, telecomunicações, automação industrial e automóvel. Influenciada por este crescimento, a comunidade científica foi confrontada com novos problemas distribuídos por vários domínios científicos, dos quais são destacados a gestão da qualidade de serviço e gestão de recursos - domínio encarregue de resolver problemas relacionados com a alocação óptima de recursos físicos, tais como rede, memória e CPU. Existe na literatura um vasto conjunto de modelos que propõem soluções para vários problemas apresentados no contexto destes domínios científicos. No entanto, não é possível encontrar modelos que lidem com a gestão de recursos em ambientes de execução cooperativos e abertos com restrições temporais utilizando coligações entre diferentes nós, de forma a satisfazer os requisitos não funcionais das aplicações. Devido ao facto de estes sistemas serem dinâmicos por natureza, apresentam a característica de não ser possível conhecer, a priori, a quantidade de recursos necessários que uma aplicação irá requerer do sistema no qual irá ser executada. Este conhecimento só é adquirido aquando da execução da aplicação. De modo a garantir uma gestão eficiente dos recursos disponíveis, em sistemas que apresentam um grande dinamismo na execução de tarefas com e sem restrições temporais, é necessário garantir dois aspectos fundamentais. O primeiro está relacionado com a obtenção de garantias na execução de tarefas de tempo-real. Estas devem sempre ser executadas dentro da janela temporal requirida. O segundo aspecto refere a necessidade de garantir que todos os recursos necessários à execução das tarefas são fornecidos, com o objectivo de manter os níveis de performance quer das aplicações, quer do próprio sistema. Tendo em conta os dois aspectos acima mencionados, o projecto CooperatES foi especificado com o objectivo de permitir a dispositivos com poucos recursos uma execução colectiva de serviços com os seus vizinhos, de modo a cumprir com as complexas restrições de qualidade de serviço impostas pelos utilizadores ou pelas aplicações. Decorrendo no contexto do projecto CooperatES, o trabalho resultante desta tese tem como principal objectivo avaliar a practicabilidade dos conceitos principais propostos no âmbito do projecto. O trabalho em causa implicou a escolha e análise de uma plataforma, a análise de requisitos, a implementação e avaliação de uma framework que permite a execução cooperativa de aplicações e serviços que apresentem requisitos de qualidade de serviço. Do trabalho desenvolvido resultaram as seguintes contribuições: Análise das plataformas de código aberto que possam ser utilizadas na implementação dos conceitos relacionados com o projecto CooperatES; Critérios que influenciaram a escolha da plataforma Android e um estudo focado na análise da plataforma sob uma perspectiva de sistemas de tempo-real; Experiências na implementação dos conceitos do projecto na plataforma Android; Avaliação da practicabilidade dos conceitos propostos no projecto CooperatES; Proposta de extensões que permitam incorporar características de sistemas de tempo real abertos na plataforma Android.

Framework de controlo de acessos para Triple-stores com interface Sail API

Grande parte dos triples-stores são open source e desenvolvidos em Java, disponibilizando interfaces standards e privadas de acesso. A grande maioria destes sistemas não dispõe de mecanismos de controlo de acessos nativos, o que dificulta ou impossibilita a sua adopção em ambientes em que a segurança dos factos é importante (e.g. ambiente empresarial). Complementarmente observa-se que o modelo de controlo de acesso a triplos e em particular a triplos descritos por ontologias não está standardizado nem sequer estabilizado, havendo diversos modelos de descrição e algoritmos de avaliação de permissões de acesso. O trabalho desenvolvido nesta tese/dissertação propõe um modelo e interface de controlo de acesso que permite e facilite a sua adopção por diferentes triple-stores já existentes e a integração dos triples-stores com outros sistemas já existentes na organização. Complementarmente, a plataforma de controlo de acesso não impõe qualquer modelo ou algoritmo de avaliação de permissões, mas pelo contrário permite a adopção de modelos e algoritmos distintos em função das necessidades ou desejos. Finalmente demonstra-se a aplicabilidade e validade do modelo e interface propostos, através da sua implementação e adopção ao triple-store SwiftOWLIM já existente, que não dispõe de mecanismo de controlo de acessos nativo.