Projeto: “Olha um trator!”

Descobrir o meio significa ter oportunidade de o observar, de o sentir, de o viver, de o experienciar, em suma, de interagir com ele. As crianças pequenas, quando estimuladas a descobrir o meio que as rodeia, desenvolvem um conjunto de competências que lhes permite a construção de imagens sobre o mundo nas suas múltiplas dimensões. O projeto que apresentamos surgiu de um percurso rotineiro pela área envolvente ao Jardim de Infância. Tem a particularidade de se desenvolver em meio rural, num contexto facilitador de experiências vivas e plenas de significado para as crianças. Percorrendo de forma integrada diferentes áreas de conteúdo, mas privilegiando o Conhecimento do Mundo, a Expressão Dramática e o Desenvolvimento Pessoal e Social, este projeto, centrado na descoberta do trator agrícola, procura no meio e na comunidade envolvente os recursos que o fazem crescer e que o tornam tão significativo para as crianças que nele se envolvem: os espaços, onde se constrói e partilha o conhecimento; os profissionais, a quem se colocam todas as questões e onde se procura ajuda para a realização das tarefas mais difíceis; as famílias, com quem se vive diariamente todo o processo.

Formar o “leitor público”: contributos do teatro para o desenvolvimento da leitura em voz alta

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística, na especialização de Teatro na Educação

Desenvolvimento da autonomia dos alunos na aprendizagem de piano: relatório de estágio

Resumo I - O presente Relatório tem como objetivo dar a conhecer a experiência da estagiária, inserida no âmbito do Mestrado em Ensino da Música, da Escola Superior de Música de Lisboa – IPL. O Estágio decorreu no Instituto Gregoriano de Lisboa, no ano letivo de 2014/2015. Foram selecionados três alunos de níveis diferentes para avaliar a atividade da estagiária enquanto docente de piano. Com este intuito, foi feita a caraterização da escola e dos alunos envolvidos no Estágio, assim como a descrição das práticas educativas desenvolvidas. Para cada um dos alunos integrados no contexto deste Estágio foram elaborados planos de aulas semanais e planificações anuais. Por fim, foi elaborada uma análise crítica da atividade docente desenvolvida e a descrição das conclusões resultantes desta prática.

Forças Armadas portuguesas em Missões de Paz: comunicação e reconhecimento: relações públicas e diplomacia

Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Gestão Estratégica das Relações Públicas.

Definição dinâmica de personagens: trabalho de projecto

Trabalho de Projecto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Artes Performativas (Escritas de Cena)

Não sejas assim!: personagens - alter ego e encenação

Trabalho de Projecto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro – Especialização em Encenação.

As duas deusas: a partir da obra de vários autores: trabalho de projecto

Trabalho de Projeto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro, Artes Performativas – Especialização em Interpretação.

‘Thy love afar is spite at home' Emerson, Thoreau and Carey: an alternative perspective of communication in US

The conquest of the West by the stagecoaches and then by railway, Ford and the automobile civilization, the Moon landing by Apollo 11, Microsoft, Apple, CNN, Google and Facebook have appeared to us as celebratory examples of the willingness and ability of the US to overcome the distance and the absence through so-called modern progress of transportation and communication. Undoubtedly, the imaginary and the instrumental power associated to transports and communication of the last century and a half are identified with the mental images that the world has of the US. A world that has eagerly imported and copy their technology and technological culture. Beyond the illusions, this attempting, which has always been praised to transcende space and eclipse the time to get to places and peole increasingly distant and fast, has always a dark side: the political control of population, commercial advertising, the spread of the rumors, noise and gossip. However, since at least the nineteenth century, the political project incorporated in modern transportation and communication technologies was not shared by some of the most remarkable thinkers in the US not only in that century, but also in the 20th century. This paper begins by rescue Ralph W. Emerson and Henry D. Thoreau legacy regarding to communication. Emerson conceived communication as a give-and-take with no coordination between the two, and does not involve contact with the other. Thoreau, in turn, argued that modern trasnportation and communications inventions are but pretty toys which distract attention from serious things, nothing more than 'improved means to an end that is not perfected.' Secondly, we show that this skeptical view of the techological improvement of transport and communication was proceed in an original way with James W. Carey, a media studies thinker who became known for his criticism of the transmission view of communication.

GPU implementation of a hyperspectral coded aperture algorithm for compressive sensing

This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA) algorithm for compressive sensing on graphics processing units (GPUs). HYCA method combines the ideas of spectral unmixing and compressive sensing exploiting the high spatial correlation that can be observed in the data and the generally low number of endmembers needed in order to explain the data. The proposed implementation exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs using shared memory and coalesced accesses to memory. The proposed algorithm is evaluated not only in terms of reconstruction error but also in terms of computational performance using two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN. Experimental results using real data reveals signficant speedups up with regards to serial implementation.

GPU implementation of the simplex identification via split augmented Lagrangian

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Generation of high-affinity monoclonal antibodies of IgG class against native β-d-glucans from basidiomycete mushrooms

β-d-glucans from basidiomycete strains are powerful immunomodulatory agents in several clinical conditions. Therefore, their assay, purification and characterization are of great interest to understand their structure-function relationship. Hybridoma cell fusion was used to raise monoclonal antibodies (Mabs) against extracellular β-d-glucans (EBGs) from Pleurotus ostreatus. Two of the hybridoma clones (1E6-1E8-B5 and 3E8-3B4) secreting Mabs against EBGs were selected. This hybridoma cell line secreted Mabs of the IgG class which were then purified by hydroxyapatite chromatography to apparent homogeneity on native and SDS-PAGE. Mabs secreted by 1E6-1E8-B5 clone were found to recognize a common epitope on several β-d-glucans from different basidiomycete strains. This Mab exhibited high affinity constant (KA) for β-d-glucans from several mushroom strains in the range of 3.20 × 109 ± 3.32 × 103-1.51 × 1013 ± 3.58 × 107 L/mol. Moreover, they reacted to some heat-treated β-d-glucans in a different mode when compared with the native forms; these data suggest that this Mab binds to a conformational epitope on the β-d-glucan molecule. The epitope-binding studies of Mabs obtained from 1E6-1E8-B5 and 3E8-3B4 revealed that the Mabs bind to the same epitope on some β-d-glucans and to different epitopes in other antigen molecules. Therefore, these Mabs can be used to assay for β-d-glucan from basidiomycete mushrooms. © 2015 Elsevier Ltd. All rights reserved.

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.

A toolbox for hyperspectral image analysis

This paper introduces a new toolbox for hyperspectral imagery, developed under the MATLAB environment. This toolbox provides easy access to different supervised and unsupervised classification methods. This new application is also versatile and fully dynamic since the user can embody their own methods, that can be reused and shared. This toolbox, while extends the potentiality of MATLAB environment, it also provides a user-friendly platform to assess the results of different methodologies. In this paper it is also presented, under the new application, a study of several different supervised and unsupervised classification methods on real hyperspectral data.

Projeto de conceito e estrutura de website para o combate ao abandono animal em Portugal

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