Locating whiteness in the academic production of "I Philosophy" in and of time and place

This review will critically evaluate two recent texts by white academics working across disciplines of cultural studies, history and anthropology and published by UNSW Press, which share a focus on the relationship between Aboriginality, Philosophy, Place and Time in Australia. I write from the position of a queer white academic committed to engaging politically and intellectually with the challenge of Indigenous sovereignties in this place while also aware that my position as a middle class white woman and intellectual imposes limits on what it is possible for me to know about Indigenous epistemologies (see Moreton-Robinson, 2000). In the course of this review I will demonstrate how anthropology's tendency to fix its objects of study within a circumscribed space of 'difference' limits the capacity of texts produced within this discipline to account for racialized struggles over sovereignty. While these struggles are equally embedded in the ethnographic context and the nation's constitution and political institutions, we will see that Muecke and Bird Rose confront problems in analysing the relationship between the intimate space of the 'field', in which one's research subjects quickly become one's 'friends' and/or 'classificatory kin'—on one hand—and the public space of the nation within which statements about Aboriginality by white academics circulate and are vested with an authority that escapes individual intentions and control—on the other.

Space efficient quantile summary for constrained sliding windows on a data stream

In many online applications, we need to maintain quantile statistics for a sliding window on a data stream. The sliding windows in natural form are defined as the most recent N data items. In this paper, we study the problem of estimating quantiles over other types of sliding windows. We present a uniform framework to process quantile queries for time constrained and filter based sliding windows. Our algorithm makes one pass on the data stream and maintains an E-approximate summary. It uses O((1)/(epsilon2) log(2) epsilonN) space where N is the number of data items in the window. We extend this framework to further process generalized constrained sliding window queries and proved that our technique is applicable for flexible window settings. Our performance study indicates that the space required in practice is much less than the given theoretical bound and the algorithm supports high speed data streams.