The Persistence of Memory

This paper analyzes several natural and man-made complex phenomena in the perspective of dynamical systems. Such phenomena are often characterized by the absence of a characteristic length-scale, long range correlations and persistent memory, which are features also associated to fractional order systems. For each system, the output, interpreted as a manifestation of the system dynamics, is analyzed by means of the Fourier transform. The amplitude spectrum is approximated by a power law function and the parameters are interpreted as an underlying signature of the system dynamics. The complex systems under analysis are then compared in a global perspective in order to unveil and visualize hidden relationships among them.

Fazer uma história da própria vida. Narrativa pessoal e memória comunicativa em Paul Schatz im uhrenkasten

This essay offers a reflection on the concepts of identity and personal narrative, a line of argument that is closely interlaced with a subject‘s capacity to self-representation. As self-representation is necessarily composed upon remembrance processes, the question of memory as an element that directly influences the formation of an individual‘s identity becomes an emergent topic. Bearing this objective in mind, I shall highlight the notion of biographic continuity, the ability to elaborate a personal narrative, as an essential prerogative to attain a sense of identitary cohesion and coherence. On the other hand, I will argue that not only experienced memories play a key role in this process; intermediated, received narratives from the past, memories transmitted either symbolically or by elder members of the group or, what has been meanwhile termed ―postmemory‖, also influence the development of an individual‘s identitary map. This theoretical framework will be illustrated with the novel Paul Schatz im Uhrenkasten, written by German post-Holocaust author Jan Koneffke.

A Tradução reinventada em The Invention of Solitude de Paul Auster

A leitura da obra de Paul Auster, desde os primeiros poemas e ensaios até à mais recente ficção, revela uma constante reflexão metalinguística e metaficcional sobre o trabalho da escrita. Auster equaciona o problema da escrita enquanto acto, permitindo ao leitor acompanhar e participar desse processo de construção. A narrativa e a linguagem intelectualizam-se, tornam-se conscientes, o que possibilita uma aproximação privilegiada ao ensino da tradução de textos literários através da própria literatura. The Invention of Solitude é como uma arte poética inspirada na experiência efectiva do sujeito, enquanto escritor e tradutor. Podemos considerá-lo um romance-manifesto em duas partes (Portrait of an Invisible Man e The Book of Memory), com especial incidência na exploração analítica da cena da escrita, utilizando a personagem-escritor e suas vivências como cobaia neste processo de auto e heteroconhecimento. A partir da análise aplicada de The Invention of Solitude, este artigo irá remeter também para os ensaios de Ernest Gellner sobre Wittgenstein em Language and Solitude, entre outros escritores que se debruçaram igualmente sobre questões ligadas à tradução literária, como Dryden, Goethe, Nietzsche, Benjamin, Ortega y Gasset e Octávio Paz.

A framework for memory contention analysis in multi-core platforms

The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.

Inteligência artificial aplicada na previsão de mercados financeiros

Neste documento, são investigados vários métodos usados na inteligência artificial, com o objetivo de obter previsões precisas da evolução dos mercados financeiros. O uso de ferramentas lineares como os modelos AR, MA, ARMA e GARCH têm muitas limitações, pois torna-se muito difícil adaptá-los às não linearidades dos fenómenos que ocorrem nos mercados. Pelas razões anteriormente referidas, os algoritmos como as redes neuronais dinâmicas (TDNN, NARX e ESN), mostram uma maior capacidade de adaptação a estas não linearidades, pois não fazem qualquer pressuposto sobre as distribuições de probabilidade que caracterizam estes mercados. O facto destas redes neuronais serem dinâmicas, faz com que estas exibam um desempenho superior em relação às redes neuronais estáticas, ou outros algoritmos que não possuem qualquer tipo de memória. Apesar das vantagens reveladas pelas redes neuronais, estas são um sistema do tipo black box, o que torna muito difícil extrair informação dos pesos da rede. Isto significa que estes algoritmos devem ser usados com precaução, pois podem tornar-se instáveis.