Periodic ripples in suspended graphene

We study the mechanism of wrinkling of suspended graphene, by means of atomistic simulations. We argue that the structural instability under edge compression is the essential physical reason for the formation of periodic ripples in graphene. The ripple wavelength and out-of-plane amplitude are found to obey 1/4-power scaling laws with respect to edge compression. Our results also show that parallel displacement of the clamped boundaries can induce periodic ripples, with oscillation amplitude roughly proportional to the 1/4 power of edge displacement. The results are fundamental to graphene's applications in electronics.Comment: 5 Figure

Strange Particles and Neutron Stars - Experiments at Gsi

Experiments on strangeness production in nucleus-nucleus collisions at SIS energies address fundamental aspects of modern nuclear physics: the determination of the nuclear equation-of-state at high baryon densities and the properties of hadrons in dense nuclear matter. Experimental data and theoretical results will be reviewed. Future experiments at the FAIR accelerator aim at the exploration of the QCD phase diagram at highest baryon densities.Comment: %Invited talk given at the International Invited talk given at the International Symposium on Heavy Ion Physics (ISHIP 2006) April 3-6 2006, FIAS, Frankfurt, Germany Frankfurt, German

Robust variance-constrained filtering for a class of nonlinear stochastic systems with missing measurements

The official published version of the article can be found at the link below.This paper is concerned with the robust filtering problem for a class of nonlinear stochastic systems with missing measurements and parameter uncertainties. The missing measurements are described by a binary switching sequence satisfying a conditional probability distribution, and the nonlinearities are expressed by the statistical means. The purpose of the filtering problem is to design a filter such that, for all admissible uncertainties and possible measurements missing, the dynamics of the filtering error is exponentially mean-square stable, and the individual steady-state error variance is not more than prescribed upper bound. A sufficient condition for the exponential mean-square stability of the filtering error system is first derived and an upper bound of the state estimation error variance is then obtained. In terms of certain linear matrix inequalities (LMIs), the solvability of the addressed problem is discussed and the explicit expression of the desired filters is also parameterized. Finally, a simulation example is provided to demonstrate the effectiveness and applicability of the proposed design approach.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK and the Alexander von Humboldt Foundation of Germany

Image tag completion by local learning

The problem of tag completion is to learn the missing tags of an image. In this paper, we propose to learn a tag scoring vector for each image by local linear learning. A local linear function is used in the neighborhood of each image to predict the tag scoring vectors of its neighboring images. We construct a unified objective function for the learning of both tag scoring vectors and local linear function parame- ters. In the objective, we impose the learned tag scoring vectors to be consistent with the known associations to the tags of each image, and also minimize the prediction error of each local linear function, while reducing the complexity of each local function. The objective function is optimized by an alternate optimization strategy and gradient descent methods in an iterative algorithm. We compare the proposed algorithm against different state-of-the-art tag completion methods, and the results show its advantages

To mesh or not to mesh: flexible wireless indoor communication among mobile robots in industrial environments

Mobile robots such as automated guided vehicles become increasingly important in industry as they can greatly increase efficiency. For their operation such robots must rely on wireless communication, typically realized by connecting them to an existing enterprise network. In this paper we motivate that such an approach is not always economically viable or might result in performance issues. Therefore we propose a flexible and configurable mixed architecture that leverages on mesh capabilities whenever appropriate. Through experiments on a wireless testbed for a variety of scenarios, we analyse the impact of roaming, mobility and traffic separation and demonstrate the potential of our approach