Cosmopolitan speakers and their cultural cartographies

Language learners' increased mobility and the ubiquity of virtual intercultural encounters has challenged traditional ideas of ‘cultures’. Moreover, representations of cultures as consumable life-choices has meant that learners are no longer locked into standard and static cultural identities. Language learners are better defined as cosmopolitan individuals with subjective and complex socio-political and historical identities. Such models push the boundaries of current concepts in language pedagogy to new understandings of who the language learner is and a refashioning of the cultural maps they inhabit. This article presents a model for cultural understanding that draws on the theoretical framework of Beck's Cosmopolitan Vision and its related concepts of ‘Banal Cosmopolitanism’ and ‘Cosmopolitan Empathy’. Narrative accounts are used to illustrate the experience of a group of students of Arabic and Serbian/Croatian and their use of the cultural resources at their disposal to construct their own subjective cosmopolitan life-worlds. Through the analysis of learners' everyday cultural practices inside and outside the educational environment, the scope of the intercultural experience is revisited and a new paradigm for the language learner is presented. The Cosmopolitan Speaker (CS) described in this article is a subject who adopts a flâneur-like disposition to reflect on and scrutinise the target culture. Armed with this highly personal interpretation of reality, CSs will be able to take part in their own cultural trajectories and imagine and ‘figure’ their own cartography of the world

Hitting probabilities for non-linear systems of stochastic waves

We consider a $d$-dimensional random field $u = \{u(t,x)\}$ that solves a non-linear system of stochastic wave equations in spatial dimensions $k \in \{1,2,3\}$, driven by a spatially homogeneous Gaussian noise that is white in time. We mainly consider the case where the spatial covariance is given by a Riesz kernel with exponent $\beta$. Using Malliavin calculus, we establish upper and lower bounds on the probabilities that the random field visits a deterministic subset of \IR^d, in terms, respectively, of Hausdorff measure and Newtonian capacity of this set. The dimension that appears in the Hausdorff measure is close to optimal, and shows that when $d(2-\beta) > 2(k+1)$, points are polar for $u$. Conversely, in low dimensions $d$, points are not polar. There is however an interval in which the question of polarity of points remains open.Comment: 85 page

Criteria for hitting probabilities with applications to systems of stochastic wave equations

We develop several results on hitting probabilities of random fields which highlight the role of the dimension of the parameter space. This yields upper and lower bounds in terms of Hausdorff measure and Bessel--Riesz capacity, respectively. We apply these results to a system of stochastic wave equations in spatial dimension $k\ge1$ driven by a $d$-dimensional spatially homogeneous additive Gaussian noise that is white in time and colored in space.Comment: Published in at http://dx.doi.org/10.3150/09-BEJ247 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

A Robust Multiple Feature Approach To Endpoint Detection In Car Environment Based On Advanced Classifiers

In this paper we propose an endpoint detection system based on the use of several features extracted from each speech frame, followed by a robust classifier (i.e Adaboost and Bagging of decision trees, and a multilayer perceptron) and a finite state automata (FSA). We present results for four different classifiers. The FSA module consisted of a 4-state decision logic that filtered false alarms and false positives. We compare the use of four different classifiers in this task. The look ahead of the method that we propose was of 7 frames, which are the number of frames that maximized the accuracy of the system. The system was tested with real signals recorded inside a car, with signal to noise ratio that ranged from 6 dB to 30dB. Finally we present experimental results demonstrating that the system yields robust endpoint detection

Red Queen Coevolution on Fitness Landscapes

Species do not merely evolve, they also coevolve with other organisms. Coevolution is a major force driving interacting species to continuously evolve ex- ploring their fitness landscapes. Coevolution involves the coupling of species fit- ness landscapes, linking species genetic changes with their inter-specific ecological interactions. Here we first introduce the Red Queen hypothesis of evolution com- menting on some theoretical aspects and empirical evidences. As an introduction to the fitness landscape concept, we review key issues on evolution on simple and rugged fitness landscapes. Then we present key modeling examples of coevolution on different fitness landscapes at different scales, from RNA viruses to complex ecosystems and macroevolution.Comment: 40 pages, 12 figures. To appear in "Recent Advances in the Theory and Application of Fitness Landscapes" (H. Richter and A. Engelbrecht, eds.). Springer Series in Emergence, Complexity, and Computation, 201