3499 research outputs found
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A lumped mass beam model for the wave propagation in anti-tetrachiral periodic lattices
No full textThe engineered class of periodic anti-tetrachiral materials is mainly characterized by
the unusual macroscopic property of a negative Poisson’s ratio. The auxetic behavior of the material
depends on the geometric and elastic features of the microstructure. In particular, the material symmetries
of the periodic cell govern the quadratic or orthotropic symmetry of the first-order elastic
tensor (i.e. auxetic quadratic or auxetic orthotropy). Under the assumption of uniform mass density
and elastic properties, one or the other case can be realized by a square or rectangular microstructure,
respectively. A beam lattice model with lumped masses is employed to analyse the effects
of different, usually small-valued, geometric and elastic parameters of the high- and low-frequency
dispersion curves and band gaps characterizing the free wave propagation
Statistical Analysis of Probabilistic Models of Software Product Lines with Quantitative Constraints
No full textWe investigate the suitability of statistical model checking for the analysis of probabilistic models of software product lines with complex quantitative constraints and advanced feature installation options. Such models are specified in the feature-oriented language QFLan, a rich process algebra whose operational behaviour interacts with a store of constraints, neatly separating product configuration from product behaviour. The resulting probabilistic configurations and behaviour converge seamlessly in a semantics based on DTMCs, thus enabling quantitative analyses ranging from the likelihood of certain behaviour to the expected average cost of products. This is supported by a Maude implementation of QFLan, integrated with the SMT solver Z3 and the distributed statistical model checker MultiVeStA. Our approach is illustrated with a bikes product line case study
Replicating Data for Better Performances in X10
No full textLinguistic primitives for replica-aware coordination offer suitable solutions to the challenging problems of data distribution and locality in large-scale high-performance computing. The data replication mechanisms that had previously been designed to extend Klaim with replicated tuples are now used to experiment with X10, a parallel programming language primarily targeting clusters of multi-core processors linked in a large-scale system via high-performance networks. Our approach aims at allowing the programmer to specify and coordinate the replication of shared data items by taking into account the desired consistency properties. The programmer can hence exploit such flexible mechanisms to adapt data distribution and locality to the needs of the application, in order to improve performance in terms of concurrency and data access. We investigate issues related to replica consistency and provide a performance analysis, which includes scenarios where replica-based specifications and relaxed consistency provide significant performance gains
Replica-Based High-Performance Tuple Space Computing
No full textWe present the tuple-based coordination language RepliKlaim, which enriches Klaim with primitives for replica-aware coordination. Our overall goal is to offer suitable solutions to the challenging problems of data distribution and locality in large-scale high performance computing. In particular, RepliKlaim allows the programmer to specify and coordinate the replication of shared data items and the desired consistency properties. The programmer can hence exploit such flexible mechanisms to adapt data distribution and locality to the needs of the application, so to improve performance in terms of concurrency and data access. We investigate issues related to replica consistency, provide an operational semantics that guides the implementation of the language, and discuss the main synchronization mechanisms of our prototypical run-time framework. Finally, we provide a performance analysis, which includes scenarios where replica-based specifications and relaxed consistency provide significant performance gains
A Theory of Political Entrenchment
No full textCan an incumbent political party increase its chances at re-election by implementing inefficient policies that harm its constituency? This paper studies the possibility of such a phenomenon, which we label political entrenchment. We use a two-party dynamic model of redistribution with probabilistic voting. Political entrenchment by the Left occurs only if incumbency rents are sufficiently high. Low-skill citizens may vote for this party even though they rationally expect the adoption of these policies. We discuss: the possibility of entrenchment by the Right; the scope for commitment to avoid entrenchment policies; and the effect of state capacity, income inequality and party popularity on the likelihood of entrenchment. We illustrate our theory with a number of historical examples
(edited by) Proceedings 8th Interaction and Concurrency Experience, ICE 2015, Grenoble, France, 4-5th June 2015
No full textThis volume contains the proceedings of ICE 2015, the 8th Interaction and Concurrency Experience, which was held in Grenoble, France on the 4th and 5th of June 2015 as a satellite event of DisCoTec 2015. The ICE procedure for paper selection allows PC members to interact, anonymously, with authors. During the review phase, each submitted paper is published on a discussion forum with access restricted to the authors and to all the PC members not declaring a conflict of interest. The PC members post comments and questions to which the authors reply. Each paper was reviewed by three PC members, and altogether 9 papers, including 1 short paper, were accepted for publication (the workshop also featured 4 brief announcements which are not part of this volume). We were proud to host three invited talks, by Leslie Lamport (shared with the FRIDA workshop), Joseph Sifakis and Steve Ross-Talbot. The abstracts of the last two talks are included in this volume together with the regular papers
Structural patterns of the occupy movement on Facebook
No full textIn this work we study a peculiar example of social organization on Facebook: the Occupy Movement -- i.e., an international protest movement against social and economic inequality organized online at a city level. We consider 179 US Facebook public pages during the time period between September 2011 and February 2013. The dataset includes 618K active users and 753K posts that received about 5.2M likes and 1.1M comments. By labeling user according to their interaction patterns on pages -- e.g., a user is considered to be polarized if she has at least the 95% of her likes on a specific page -- we find that activities are not locally coordinated by geographically close pages, but are driven by pages linked to major US cities that act as hubs within the various groups. Such a pattern is verified even by extracting the backbone structure -- i.e., filtering statistically relevant weight heterogeneities -- for both the pages-reshares and the pages-common users networks
LPV system identification under noise corrupted scheduling and output signal observations
No full textMost of the approaches available in the literature for the identification of Linear Parameter-Varying (LPV) systems rely on the assumption that only the measurements of the output signal are corrupted by the noise, while the observations of the scheduling variable are considered to be noise free. However, in practice, this turns out to be an unrealistic assumption in most of the cases, as the scheduling variable is often related to a measured signal and, thus, it is inherently affected by a measurement noise. In this paper, it is shown that neglecting the noise on the scheduling signal, which corresponds to an error-invariables
problem, can lead to a significant bias on the estimated parameters. Consequently, in order to overcome this corruptive phenomenon affecting practical use of data-driven LPV modeling, we present an identification scheme to compute a consistent estimate of LPV Input/Output (IO) models from noisy output and scheduling signal observations. A simulation example is provided to prove the effectiveness
of the proposed methodology
Green power grids: how energy from renewable sources affects network and markets
No full textThe increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources, fundamentally changing the configuration of energy management and introducing new criticalities that are only partly understood. In particular, renewable energies introduce fluctuations causing an increased request of conventional energy sources oriented to balance energy requests on short notices. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and the forecast of short time fluctuations related to renewable sources and to their effects on the electricity market. To account for the inter-dependencies among the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations on the power system and an agent based approach for the prediction of the market players behavior. Our model is a data-driven; it builds on one day ahead real market transactions to train agents behaviour and allows to infer the market share of different energy sources. We benchmark our approach on the Italian market finding a good accordance with real data