15,932 research outputs found

    Liberate your avatar; the revolution will be social networked

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    This paper brings together the practice-based creative research of artists Charlotte Gould and Paul Sermon, culminating in a collaborative interactive installation that investigates new forms of social and political narrative in multi-user virtual environments. The authors' artistic projects deal with the ironies and stereotypes that are found within Second Life in particular. Paul Sermon’s current creative practice looks specifically at the concepts of presence and performance within Second Life and 'first life', and attempts to bridge these two spaces through mixed reality techniques and interfaces. Charlotte Gould’s Ludic Second Life Narrative radically questions the way that users embody themselves in on-line virtual environments and identifies a counter-aesthetic that challenges the conventions of digital realism and consumerism. These research activities and outcomes come together within a collaborative site-specific public installation entitled Urban Intersections for ISEA09, focusing on contested virtual spaces that mirror the social and political history of Belfast. The authors' current collaborative practice critically investigates social, cultural and creative interactions in Second Life. Through these practice-based experiments the authors' argue that an enhanced social and cultural discourse within multi-user virtual environments will inevitably lead to growth, cohesion and public empowerment, and like all social networking platforms, contribute to greater social and political change in first life

    Slow‐Wave Structures Utilizing Superconducting Thin‐Film Transmission Lines

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    Slow‐wave propagation of electromagnetic waves in transmission lines formed of thin‐film superconductors has been studied theoretically and experimentally. Previous theoretical analyses have been extended to include nonlocal theories. Strong dependence of phase velocity is found on film thickness and interfilm spacing when these become less than a few penetration depths. Velocity is also modified by coherence length, mean free path, nature of reflection of electrons at the film surfaces, and by temperature and magnetic field. Experimental measurements were made to verify the dependence on thickness, spacing, and temperature by means of a resonance technique. Agreement with theory was excellent in the case of temperature. Data taken for varying thickness and spacing verified the general trend of theoretical predictions. They indicate a nonlocal behavior with some specular reflection, but scatter of the data taken for different films prevents precise comparison of theory and experiment. Estimates of bulk penetration depths were made for indium, λ_In = 648±130 Å. For tantalum a rough estimate could be made of λTa = 580 Å. Data were consistent with the estimate of coherence length for indium of Ο_0 ≈ 3000 Å. Velocity was found to be independent of frequency in the range 50–500 MHz, while losses increased as the square. Pulse measurements indicated that delays of several microseconds and storage of several thousand pulses on a single line are feasible

    A second derivative SQP method: theoretical issues

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    Sequential quadratic programming (SQP) methods form a class of highly efficient algorithms for solving nonlinearly constrained optimization problems. Although second derivative information may often be calculated, there is little practical theory that justifies exact-Hessian SQP methods. In particular, the resulting quadratic programming (QP) subproblems are often nonconvex, and thus finding their global solutions may be computationally nonviable. This paper presents a second-derivative SQP method based on quadratic subproblems that are either convex, and thus may be solved efficiently, or need not be solved globally. Additionally, an explicit descent-constraint is imposed on certain QP subproblems, which “guides” the iterates through areas in which nonconvexity is a concern. Global convergence of the resulting algorithm is established

    A second derivative SQP method: local convergence

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    In [19], we gave global convergence results for a second-derivative SQP method for minimizing the exact ℓ1-merit function for a fixed value of the penalty parameter. To establish this result, we used the properties of the so-called Cauchy step, which was itself computed from the so-called predictor step. In addition, we allowed for the computation of a variety of (optional) SQP steps that were intended to improve the efficiency of the algorithm. \ud \ud Although we established global convergence of the algorithm, we did not discuss certain aspects that are critical when developing software capable of solving general optimization problems. In particular, we must have strategies for updating the penalty parameter and better techniques for defining the positive-definite matrix Bk used in computing the predictor step. In this paper we address both of these issues. We consider two techniques for defining the positive-definite matrix Bk—a simple diagonal approximation and a more sophisticated limited-memory BFGS update. We also analyze a strategy for updating the penalty paramter based on approximately minimizing the ℓ1-penalty function over a sequence of increasing values of the penalty parameter.\ud \ud Algorithms based on exact penalty functions have certain desirable properties. To be practical, however, these algorithms must be guaranteed to avoid the so-called Maratos effect. We show that a nonmonotone varient of our algorithm avoids this phenomenon and, therefore, results in asymptotically superlinear local convergence; this is verified by preliminary numerical results on the Hock and Shittkowski test set

    A second-derivative trust-region SQP method with a "trust-region-free" predictor step

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    In (NAR 08/18 and 08/21, Oxford University Computing Laboratory, 2008) we introduced a second-derivative SQP method (S2QP) for solving nonlinear nonconvex optimization problems. We proved that the method is globally convergent and locally superlinearly convergent under standard assumptions. A critical component of the algorithm is the so-called predictor step, which is computed from a strictly convex quadratic program with a trust-region constraint. This step is essential for proving global convergence, but its propensity to identify the optimal active set is Paramount for recovering fast local convergence. Thus the global and local efficiency of the method is intimately coupled with the quality of the predictor step.\ud \ud In this paper we study the effects of removing the trust-region constraint from the computation of the predictor step; this is reasonable since the resulting problem is still strictly convex and thus well-defined. Although this is an interesting theoretical question, our motivation is based on practicality. Our preliminary numerical experience with S2QP indicates that the trust-region constraint occasionally degrades the quality of the predictor step and diminishes its ability to correctly identify the optimal active set. Moreover, removal of the trust-region constraint allows for re-use of the predictor step over a sequence of failed iterations thus reducing computation. We show that the modified algorithm remains globally convergent and preserves local superlinear convergence provided a nonmonotone strategy is incorporated

    A Second Method to Photometrically Align Multi-Site Microlensing Light Curves: Source Color in Planetary Event MOA-2007-BLG-192

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    At present, microlensing light curves from different telescopes and filters are photometrically aligned by fitting them to a common model. We present a second method based on photometry of common field stars. If two spectral responses are similar (or the color of the source is known) then this technique can resolve important ambiguities that frequently arise when predicting the future course of the event, and that occasionally persist even when the event is over. Or if the spectral responses are different, it can be used to derive the color of the source when that is unknown. We present the essential elements of this technique and apply it to the case of MOA-2007-BLG-192, an important planetary event for which the system may be a terrestrial planet orbiting a brown dwarf or very low mass star. The refined estimate of the source color that we derive here, V-I=2.36 +- 0.03, will aid in making the estimate of the lens mass more precise.Comment: 16 pages including 3 figures. Submitted to Ap

    New battery model and state-of-health determination through subspace parameter estimation and state-observer techniques

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    This paper describes a novel adaptive battery model based on a remapped variant of the well-known Randles' lead-acid model. Remapping of the model is shown to allow improved modeling capabilities and accurate estimates of dynamic circuit parameters when used with subspace parameter-estimation techniques. The performance of the proposed methodology is demonstrated by application to batteries for an all-electric personal rapid transit vehicle from the Urban Light TRAnsport (ULTRA) program, which is designated for use at Heathrow Airport, U. K. The advantages of the proposed model over the Randles' circuit are demonstrated by comparisons with alternative observer/estimator techniques, such as the basic Utkin observer and the Kalman estimator. These techniques correctly identify and converge on voltages associated with the battery state-of-charge (SoC), despite erroneous initial conditions, thereby overcoming problems attributed to SoC drift (incurred by Coulomb-counting methods due to overcharging or ambient temperature fluctuations). Observation of these voltages, as well as online monitoring of the degradation of the estimated dynamic model parameters, allows battery aging (state-of-health) to also be assessed and, thereby, cell failure to be predicted. Due to the adaptive nature of the proposed algorithms, the techniques are suitable for applications over a wide range of operating environments, including large ambient temperature variations. Moreover, alternative battery topologies may also be accommodated by the automatic adjustment of the underlying state-space models used in both the parameter-estimation and observer/estimator stages
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