3 resultados para Poetics of horizon

em Instituto Politécnico do Porto, Portugal


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Diane Arbus‘ photographs are mainly about difference. Most of the time she is trying ‗[…] to suppress, or at least reduce, moral and sensory queasiness‘ (Sontag 1977: 40) in order to represent a world where the subject of the photograph is not merely the ‗other‘ but also the I. Her technique does not coax her subjects into natural poses. Instead she encourages them to be strange and awkward. By posing for her, the revelation of the self is identified with what is odd. This paper aims at understanding the geography of difference that, at the same time, is also of resistance, since Diane Arbus reveals what was forcefully hidden by bringing it into light in such a way that it is impossible to ignore. Her photographs display a poetic beauty that is not only of the ‗I‘ but also of the ‗eye‘. The world that is depicted is one in which we are all the same. She ―atomizes‖ reality by separating each element and ‗Instead of showing identity between things which are different […] everybody is shown to look the same.‘ (Sontag 1977: 47). Furthermore, this paper analyses some of Arbus‘ photographs so as to explain this point of view, by trying to argue that between rejecting and reacting against what is standardized she does not forget the geography of the body which is also a geography of the self. While creating a new imagetic topos, where what is trivial becomes divine, she also presents the frailty of others as our own.

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The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

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The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indices. We analyze the Dow Jones Industrial Average ( ∧ DJI) and the NASDAQ Composite ( ∧ IXIC) indexes at a daily time horizon. The methods and algorithms that have been explored for description of physical phenomena become an effective background, and even inspiration, for very productive methods used in the analysis of economical data. We start by applying the classical concepts of signal analysis, Fourier transform, and methods of fractional calculus. In a second phase we adopt a pseudo phase plane approach.