Crossmodal content binding in information-processing architectures

Operating in a physical context, an intelligent robot faces two fundamental problems. First, it needs to combine information from its different sensors to form a representation of the environment that is more complete than any of its sensors on its own could provide. Second, it needs to combine high-level representations (such as those for planning and dialogue) with its sensory information, to ensure that the interpretations of these symbolic representations are grounded in the situated context. Previous approaches to this problem have used techniques such as (low-level) information fusion, ontological reasoning, and (high-level) concept learning. This paper presents a framework in which these, and other approaches, can be combined to form a shared representation of the current state of the robot in relation to its environment and other agents. Preliminary results from an implemented system are presented to illustrate how the framework supports behaviours commonly required of an intelligent robot

Reclaiming the borderlands : a relational and transnational feminist approach to the history and treatment of borderline personality disorder

This paper utilizes transnational feminist theory to both deconstruct the history of borderline personality disorder and to contextualize treatment within a relational psychodynamic frame. Using transnational feminist understandings of the borderland and splintering self-states, the concept of borderline personality disorder is reframed and explored through a historical perspective. Relational psychodynamic theory is considered as a response to this deconstruction, offering a contemporary perspective, which acknowledges the structural oppressions intrinsic in mental illness. Additionally this paper argues that this perspective highlights a path to engage authentically with intersections of self-states rather than at the poles of binary constructions of identity and self

Wind Loads on Transmission Line Structures in Simulated Downbursts

Downbursts pose a recognized threat to transmission line networks in South-east Queensland, and many other regions around the world. However, when assessing the structural adequacy of transmission line structures, design codes assume that an atmospheric boundary layer profile provide the basis of wind loading in the design process. Such assumptions may be leaving transmission networks exposed to an unquantified level of threat to a meteorological event that will likely cause the most severe loading on the structure during its lifetime. An analytical/stochastic method of simulating downburst winds has been used to explore the quasi-static loading conditions that occur during downbursts. These are presented in comparison to several existing transmission tower design codes, and the implications with regard to the structural adequacy of transmission line structures is discussed

Electromagnetic form factors of light vector mesons

The electromagnetic form factors G_E(q^2), G_M(q^2), and G_Q(q^2), charge radii, magnetic and quadrupole moments, and decay widths of the light vector mesons rho^+, K^{*+} and K^{*0} are calculated in a Lorentz-covariant, Dyson-Schwinger equation based model using algebraic quark propagators that incorporate confinement, asymptotic freedom, and dynamical chiral symmetry breaking, and vector meson Bethe-Salpeter amplitudes closely related to the pseudoscalar amplitudes obtained from phenomenological studies of pi and K mesons. Calculated static properties of vector mesons include the charge radii and magnetic moments: r_{rho+} = 0.61 fm, r_{K*+} = 0.54 fm, and r^2_{K*0} = -0.048 fm^2; mu_{rho+} = 2.69, mu_{K*+} = 2.37, and mu_{K*0} = -0.40. The calculated static limits of the rho-meson form factors are similar to those obtained from light-front quantum mechanical calculations, but begin to differ above q^2 = 1 GeV^2 due to the dynamical evolution of the quark propagators in our approach.Comment: 8 pages of RevTeX, 5 eps figure

Beta Residuals: Improving Fault-Tolerant Control for Sensory Faults via Bayesian Inference and Precision Learning

Model-based fault-tolerant control (FTC) often consists of two distinct steps: fault detection & isolation (FDI), and fault accommodation. In this work we investigate posing fault-tolerant control as a single Bayesian inference problem. Previous work showed that precision learning allows for stochastic FTC without an explicit fault detection step. While this leads to implicit fault recovery, information on sensor faults is not provided, which may be essential for triggering other impact-mitigation actions. In this paper, we introduce a precision-learning based Bayesian FTC approach and a novel beta residual for fault detection. Simulation results are presented, supporting the use of beta residual against competing approaches.Comment: 7 pages, 2 figures. Accepted at the 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes - SAFEPROCESS 202

A dynamical, confining model and hot quark stars

We explore the consequences of an equation of state (EOS) obtained in a confining Dyson-Schwinger equation model of QCD for the structure and stability of nonstrange quark stars at finite-T, and compare the results with those obtained using a bag-model EOS. Both models support a temperature profile that varies over the star's volume and the consequences of this are model independent. However, in our model the analogue of the bag pressure is (T,mu)-dependent, which is not the case in the bag model. This is a significant qualitative difference and comparing the results effects a primary goal of elucidating the sensitivity of quark star properties to the form of the EOS.Comment: 13 pages, 5 figures, epsfig.sty, elsart.sty. Shortened version to appear in Phys. Lett. B, qualitatively unmodifie