RemoteLabs Platform

This paper reports on a first step towards the implementation of a framework for remote experimentation of electric machines ? the RemoteLabs platform. This project was focused on the development of two main modules: the user Web-based and the electric machines interfaces. The Web application provides the user with a front-end and interacts with the back-end ? the user and experiment persistent data. The electric machines interface is implemented as a distributed client server application where the clients, launched by the Web application, interact with the server modules located in platforms physically connected the electric machines drives. Users can register and authenticate, schedule, specify and run experiments and obtain results in the form of CSV, XML and PDF files. These functionalities were successfully tested with real data, but still without including the electric machines. This inclusion is part of another project scheduled to start soon.

Implementation of a Campus wide DGPS Data Server

Although the Navigation Satellite Timing and Ranging (NAVSTAR) Global Positioning System (GPS) is, de facto, the standard positioning system used in outdoor navigation, it does not provide, per se, all the features required to perform many outdoor navigational tasks. The accuracy of the GPS measurements is the most critical issue. The quest for higher position readings accuracy led to the development, in the late nineties, of the Differential Global Positioning System (DGPS). The differential GPS method detects the range errors of the GPS satellites received and broadcasts them. The DGPS/GPS receivers correlate the DGPS data with the GPS satellite data they are receiving, granting users increased accuracy. DGPS data is broadcasted using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to have access, within the ISEP campus, to DGPS correction data. To achieve this objective we designed and implemented a distributed system composed of two main modules which are interconnected: a distributed application responsible for the establishment of the data link over the Internet between the remote DGPS stations and the campus, and the campus-wide DGPS data server application. The DGPS data Internet link is provided by a two-tier client/server distributed application where the server-side is connected to the DGPS station and the client-side is located at the campus. The second unit, the campus DGPS data server application, diffuses DGPS data received at the campus via the Intranet and via a wireless data link. The wireless broadcast is intended for DGPS/GPS portable receivers equipped with an air interface and the Intranet link is provided for DGPS/GPS receivers with just a RS232 DGPS data interface. While the DGPS data Internet link servers receive the DGPS data from the DGPS base stations and forward it to the DGPS data Internet link client, the DGPS data Internet link client outputs the received DGPS data to the campus DGPS data server application. The distributed system is expected to provide adequate support for accurate (sub-metric) outdoor campus navigation tasks. This paper describes in detail the overall distributed application.

Integrated Management of IaaS Resources

This paper proposes and reports the development of an open source solution for the integrated management of Infrastructure as a Service (IaaS) cloud computing resources, through the use of a common API taxonomy, to incorporate open source and proprietary platforms. This research included two surveys on open source IaaS platforms (OpenNebula, OpenStack and CloudStack) and a proprietary platform (Parallels Automation for Cloud Infrastructure - PACI) as well as on IaaS abstraction solutions (jClouds, Libcloud and Deltacloud), followed by a thorough comparison to determine the best approach. The adopted implementation reuses the Apache Deltacloud open source abstraction framework, which relies on the development of software driver modules to interface with different IaaS platforms, and involved the development of a new Deltacloud driver for PACI. The resulting interoperable solution successfully incorporates OpenNebula, OpenStack (reuses pre-existing drivers) and PACI (includes the developed Deltacloud PACI driver) nodes and provides a Web dashboard and a Representational State Transfer (REST) interface library. The results of the exchanged data payload and time response tests performed are presented and discussed. The conclusions show that open source abstraction tools like Deltacloud allow the modular and integrated management of IaaS platforms (open source and proprietary), introduce relevant time and negligible data overheads and, as a result, can be adopted by Small and Medium-sized Enterprise (SME) cloud providers to circumvent the vendor lock-in problem whenever service response time is not critical.

Relatório de estágio em marketing corporativo na empresa Insite IT GmbH

Relatório de estágio apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

Inferência de percursos dos utentes de um transporte coletivo

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicações e Multimédia

Diagnosis of an EPS module

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

Autoconsumo fotovoltaico, um elemento de eficiência energética. Caso de estudo: ISEP

Mestrado em Energias Sustentáveis

System-on-chip field-programmable gate array design for onboard real-time hyperspectral unmixing

Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Coluna de som utilizando array de transdutores de ultrasons

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Integração de aplicações Web 2.0 e sistemas de gestão de conteúdos em ambientes pessoais de aprendizagem

A utilização de aplicações Web 2.0 no processo ensino/aprendizagem tem vindo a intensificar-se nos últimos tempos, mais por iniciativas individuais de docentes e estudantes do que por estratégia das Instituições de Ensino. Este artigo apresenta um projecto já em curso que consiste na implementação de uma plataforma de criação de ambientes de aprendizagem controlados pelos estudantes, integrando aplicações Web 2.0 e sistemas de gestão de conteúdos. A plataforma permitirá a utilização segura de conteúdos criados em aplicações Web 2.0, no processo de avaliação, possibilitando a sua publicação na infra-estrutura controlada pela Instituição de Ensino Superior, contribuindo assim para a adequação do binómio ensino/aprendizagem ao novo paradigma implicado no processo de Bolonha.

Uma aplicação Web para apoio a laboratórios remotos reconfiguráveis baseados na norma IEEE 1451.0

Nos últimos anos, o processo de ensino e aprendizagem tem sofrido significativas alterações graças ao aparecimento da Internet. Novas ferramentas para apoio ao ensino têm surgido, nas quais se destacam os laboratórios remotos. Atualmente, muitas instituições de ensino disponibilizam laboratórios remotos nos seus cursos, que permitem, a professores e alunos, a realização de experiências reais através da Internet. Estes são implementados por diferentes arquiteturas e infraestruturas, suportados por vários módulos de laboratório acessíveis remotamente (e.g. instrumentos de medição). No entanto, a sua inclusão no ensino é ainda deficitária, devido: i) à falta de meios e competências técnicas das instituições de ensino para os desenvolverem, ii) à dificuldade na partilha dos módulos de laboratório por diferentes infraestruturas e, iii) à reduzida capacidade de os reconfigurar com esses módulos. Para ultrapassar estas limitações, foi idealizado e desenvolvido no âmbito de um trabalho de doutoramento [1] um protótipo, cuja arquitetura é baseada na norma IEEE 1451.0 e na tecnologia de FPGAs. Para além de garantir o desenvolvimento e o acesso de forma normalizada a um laboratório remoto, este protótipo promove ainda a partilha de módulos de laboratório por diferentes infraestruturas. Nesse trabalho explorou-se a capacidade de reconfiguração de FPGAs para embutir na infraestrutura do laboratório vários módulos, todos descritos em ficheiros, utilizando linguagens de descrição de hardware estruturados de acordo com a norma IEEE 1451.0. A definição desses módulos obriga à criação de estruturas de dados binárias (Transducer Electronic Data Sheets, TEDSs), bem como de outros ficheiros que possibilitam a sua interligação com a infraestrutura do laboratório. No entanto, a criação destes ficheiros é bastante complexa, uma vez que exige a realização de vários cálculos e conversões. Tendo em consideração essa mesma complexidade, esta dissertação descreve o desenvolvimento de uma aplicação Web para leitura e escrita dos TEDSs. Para além de um estudo sobre os laboratórios remotos, é efetuada uma descrição da norma IEEE 1451.0, com particular atenção para a sua arquitetura e para a estrutura dos diferentes TEDSs. Com o objetivo de enquadrar a aplicação desenvolvida, efetua-se ainda uma breve apresentação de um protótipo de um laboratório remoto reconfigurável, cuja reconfiguração é apoiada por esta aplicação. Por fim, é descrita a verificação da aplicação Web, de forma a tirar conclusões sobre o seu contributo para a simplificação dessa reconfiguração.

A comparative study between centralization and decentralization of diagnostic reasoning in EPS

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa de Lisboa para obtenção do grau de mestre em Engenharia Electrotécnica e de Computadores

Combate à fraude em jogos de casino, assistida por computador

No decorrer dos últimos anos tem-se verificado um acréscimo do número de sistemas de videovigilância presentes nos mais diversos ambientes, sendo que estes se encontram cada vez mais sofisticados. Os casinos são um exemplo bastante popular da utilização destes sistemas sofisticados, sendo que vários casinos, hoje em dia, utilizam câmeras para controlo automático das suas operações de jogo. No entanto, atualmente existem vários tipos de jogos em que o controlo automático ainda não se encontra disponível, sendo um destes, o jogo Banca Francesa. A presente dissertação tem como objetivo propor um conjunto de algoritmos idealizados para um sistema de controlo e gestão do jogo de casino Banca Francesa através do auxílio de componentes pertencentes à área da computação visual, tendo em conta os contributos mais relevantes e existentes na área, elaborados por investigadores e entidades relacionadas. No decorrer desta dissertação são apresentados quatro módulos distintos, os quais têm como objetivo auxiliar os casinos a prevenir o acontecimento de fraudes durante o decorrer das suas operações, assim como auxiliar na recolha automática de resultados de jogo. Os quatro módulos apresentados são os seguintes: Dice Sample Generator – Módulo proposto para criação de casos de teste em grande escala; Dice Sample Analyzer – Módulo proposto para a deteção de resultados de jogo; Dice Calibration – Módulo proposto para calibração automática do sistema; Motion Detection – Módulo proposto para a deteção de fraude no jogo. Por fim, para cada um dos módulos, é apresentado um conjunto de testes e análises de modo a verificar se é possível provar o conceito para cada uma das propostas apresentadas.

Integrated Management of Cloud Computing Resources

Lunacloud is a cloud service provider with offices in Portugal, Spain, France and UK that focus on delivering reliable, elastic and low cost cloud Infrastructure as a Service (IaaS) solutions. The company currently relies on a proprietary IaaS platform - the Parallels Automation for Cloud Infrastructure (PACI) - and wishes to expand and integrate other IaaS solutions seamlessly, namely open source solutions. This is the challenge addressed in this thesis. This proposal, which was fostered by Eurocloud Portugal Association, contributes to the promotion of interoperability and standardisation in Cloud Computing. The goal is to investigate, propose and develop an interoperable open source solution with standard interfaces for the integrated management of IaaS Cloud Computing resources based on new as well as existing abstraction libraries or frameworks. The solution should provide bothWeb and application programming interfaces. The research conducted consisted of two surveys covering existing open source IaaS platforms and PACI (features and API) and open source IaaS abstraction solutions. The first study was focussed on the characteristics of most popular open source IaaS platforms, namely OpenNebula, OpenStack, CloudStack and Eucalyptus, as well as PACI and included a thorough inventory of the provided Application Programming Interfaces (API), i.e., offered operations, followed by a comparison of these platforms in order to establish their similarities and dissimilarities. The second study on existing open source interoperability solutions included the analysis of existing abstraction libraries and frameworks and their comparison. The approach proposed and adopted, which was supported on the conclusions of the carried surveys, reuses an existing open source abstraction solution – the Apache Deltacloud framework. Deltacloud relies on the development of software driver modules to interface with different IaaS platforms, officially provides and supports drivers to sixteen IaaS platform, including OpenNebula and OpenStack, and allows the development of new provider drivers. The latter functionality was used to develop a new Deltacloud driver for PACI. Furthermore, Deltacloud provides a Web dashboard and REpresentational State Transfer (REST) API interfaces. To evaluate the adopted solution, a test bed integrating OpenNebula, Open- Stack and PACI nodes was assembled and deployed. The tests conducted involved time elapsed and data payload measurements via the Deltacloud framework as well as via the pre-existing IaaS platform API. The Deltacloud framework behaved as expected, i.e., introduced additional delays, but no substantial overheads. Both the Web and the REST interfaces were tested and showed identical measurements. The developed interoperable solution for the seamless integration and provision of IaaS resources from PACI, OpenNebula and OpenStack IaaS platforms fulfils the specified requirements, i.e., provides Lunacloud with the ability to expand the range of adopted IaaS platforms and offers a Web dashboard and REST API for the integrated management. The contributions of this work include the surveys and comparisons made, the selection of the abstraction framework and, last, but not the least, the PACI driver developed.