Modelo SIG para apoio à análise de sistemas de transportes e usos do solo

Dissertação de natureza científica para obtenção do grau de Mestre em Engenharia Civil

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

A checkpointing-enabled and resource-aware Java Virtual Machine for efficient and robust e-Science applications in grid environments

Object-oriented programming languages presently are the dominant paradigm of application development (e. g., Java,. NET). Lately, increasingly more Java applications have long (or very long) execution times and manipulate large amounts of data/information, gaining relevance in fields related with e-Science (with Grid and Cloud computing). Significant examples include Chemistry, Computational Biology and Bio-informatics, with many available Java-based APIs (e. g., Neobio). Often, when the execution of such an application is terminated abruptly because of a failure (regardless of the cause being a hardware of software fault, lack of available resources, etc.), all of its work already performed is simply lost, and when the application is later re-initiated, it has to restart all its work from scratch, wasting resources and time, while also being prone to another failure and may delay its completion with no deadline guarantees. Our proposed solution to address these issues is through incorporating mechanisms for checkpointing and migration in a JVM. These make applications more robust and flexible by being able to move to other nodes, without any intervention from the programmer. This article provides a solution to Java applications with long execution times, by extending a JVM (Jikes research virtual machine) with such mechanisms. Copyright (C) 2011 John Wiley & Sons, Ltd.

Study on influence of the new CoDeSys V3.0 on the existing CoDeSys discipline of the Mind8 Engineering Center

CoDeSys "Controller Development Systems" is a development environment for programming in the area of automation controllers. It is an open source solution completely in line with the international industrial standard IEC 61131-3. All five programming languages for application programming as defined in IEC 61131-3 are available in the development environment. These features give professionals greater flexibility with regard to programming and allow control engineers have the ability to program for many different applications in the languages in which they feel most comfortable. Over 200 manufacturers of devices from different industrial sectors offer intelligent automation devices with a CoDeSys programming interface. In 2006, version 3 was released with new updates and tools. One of the great innovations of the new version of CoDeSys is object oriented programming. Object oriented programming (OOP) offers great advantages to the user for example when wanting to reuse existing parts of the application or when working on one application with several developers. For this reuse can be prepared a source code with several well known parts and this is automatically generated where necessary in a project, users can improve then the time/cost/quality management. Until now in version 2 it was necessary to have hardware interface called “Eni-Server” to have access to the generated XML code. Another of the novelties of the new version is a tool called Export PLCopenXML. This tool makes it possible to export the open XML code without the need of specific hardware. This type of code has own requisites to be able to comply with the standard described above. With XML code and with the knowledge how it works it is possible to do component-oriented development of machines with modular programming in an easy way. Eplan Engineering Center (EEC) is a software tool developed by Mind8 GmbH & Co. KG that allows configuring and generating automation projects. Therefore it uses modules of PLC code. The EEC already has a library to generate code for CoDeSys version 2. For version 3 and the constant innovation of drivers by manufacturers, it is necessary to implement a new library in this software. Therefore it is important to study the XML export to be then able to design any type of machine. The purpose of this master thesis is to study the new version of the CoDeSys XML taking into account all aspects and impact on the existing CoDeSys V2 models and libraries in the company Harro Höfliger Verpackungsmaschinen GmbH. For achieve this goal a small sample named “Traffic light” in CoDeSys version 2 will be done and then, using the tools of the new version it there will be a project with version 3 and also the EEC implementation for the automatically generated code.

Materiais estruturados: qual o seu papel na aprendizágem dos primeiros números?

Dissertação apresentada para obtenção do grau de Mestre em Educação Matemática na Educação Pré-Escolar e no 1.º e 2.º Ciclos do Ensino Básico

Twin Peaks como alegoria daimónica cinematográfica

For a long time the allegorical activity was considered dogmatic and equated with artistic fossilization, archaic religious propensity and lack of creativity. However, Walter Benjamin (1928) and Paul De Man (1969), among other illustrious thinkers, came to its defense, exalting, instead, its cryptic, hybrid and abstract nature, which, incidentally, are the main characteristics of modern art. “Twin Peaks – Fire Walk with Me” (David Lynch, 1992) is a wonderful object of analysis, despite being one of the most misunderstood films in the history of cinema. The fact that its narrative is a prequel to the cult television series “Twin Peaks” and incorporates many of the characters of that show, explicitly denigrating the moral image of the protagonist, Laura Palmer, brought about an intense rejection by the fans of the series, as well as the indifference of the cinephilic community in general. However, one must go deeper, in order to understand Lynch’s brave accomplishment and its artfulness. Indeed, the opus is a powerful cinematic allegory because it contains a double layer of metaphorical meaning, one of them being explicitly metacinematic. Thus, besides assuming itself as a filmic daimonic allegory, occurring in a spiritual universe of Good versus Evil, the film is also an authorial discourse on cinema itself. More specifically, it is an allegory of spectatorship, according to Robert Stam’s definition, where the existence and crossing over to “another side” duplicates the architecture of movie theatres and the psychic processes involved in film viewing.

A magnanimidade da teoria: interpretar a ética em teoria da literatura

Tese de doutoramento, Teoria da Literatura, Universidade de Lisboa, Faculdade de Letras, 2003

As representações da escola face ao trabalho para casa, no 1.º ciclo do ensino básico

Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e 2.º Ciclo do Ensino Básico

Estudo da qualidade organizacional da unidade de rastreio da retinopatia diabética do Alentejo central: projecto de intervenção comunitária em saúde

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Gestão e Administração dos Serviços de Saúde.

On the analysis of compensation correctness

One fundamental idea of service-oriented computing is that applications should be developed by composing already available services. Due to the long running nature of service interactions, a main challenge in service composition is ensuring correctness of transaction recovery. In this paper, we use a process calculus suitable for modelling long running transactions with a recovery mechanism based on compensations. Within this setting, we discuss and formally state correctness criteria for compensable processes compositions, assuming that each process is correct with respect to transaction recovery. Under our theory, we formally interpret self-healing compositions, that can detect and recover from faults, as correct compositions of compensable processes. Moreover, we develop an automated verification approach and we apply it to an illustrative case study.

Algorithm-oriented design of efficient many-core architectures applied to dense matrix multiplication

Recent integrated circuit technologies have opened the possibility to design parallel architectures with hundreds of cores on a single chip. The design space of these parallel architectures is huge with many architectural options. Exploring the design space gets even more difficult if, beyond performance and area, we also consider extra metrics like performance and area efficiency, where the designer tries to design the architecture with the best performance per chip area and the best sustainable performance. In this paper we present an algorithm-oriented approach to design a many-core architecture. Instead of doing the design space exploration of the many core architecture based on the experimental execution results of a particular benchmark of algorithms, our approach is to make a formal analysis of the algorithms considering the main architectural aspects and to determine how each particular architectural aspect is related to the performance of the architecture when running an algorithm or set of algorithms. The architectural aspects considered include the number of cores, the local memory available in each core, the communication bandwidth between the many-core architecture and the external memory and the memory hierarchy. To exemplify the approach we did a theoretical analysis of a dense matrix multiplication algorithm and determined an equation that relates the number of execution cycles with the architectural parameters. Based on this equation a many-core architecture has been designed. The results obtained indicate that a 100 mm(2) integrated circuit design of the proposed architecture, using a 65 nm technology, is able to achieve 464 GFLOPs (double precision floating-point) for a memory bandwidth of 16 GB/s. This corresponds to a performance efficiency of 71 %. Considering a 45 nm technology, a 100 mm(2) chip attains 833 GFLOPs which corresponds to 84 % of peak performance These figures are better than those obtained by previous many-core architectures, except for the area efficiency which is limited by the lower memory bandwidth considered. The results achieved are also better than those of previous state-of-the-art many-cores architectures designed specifically to achieve high performance for matrix multiplication.

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.