80 research outputs found
DataWarp: Building Applications which Make Progress in an Inconsistent World
The usual approach to dealing with imperfections in data is to attempt to eliminate them. However, the nature of modern systems means this is often futile. This paper describes an approach which permits applications to operate notwithstanding inconsistent data. Instead of attempting to extract a single, correct view of the world from its data, a DataWarp application constructs a collection of interpretations. It adopts one of these and continues work. Since it acts on assumptions, the DataWarp application considers its recent work to be provisional, expecting eventually most of these actions will become definitive. Should the application decide to adopt an alternative data view, it may then need to void provisional actions before resuming work. We describe the DataWarp architecture, discuss its implementation and describe an experiment in which a DataWarp application in an environment containing inconsistent data achieves better results than its conventional counterpart
A Study on the Parallelization of Terrain-Covering Ant Robots Simulations
Agent-based simulation is used as a tool for supporting (time-critical) decision making in differentiated contexts. Hence, techniques for speeding up the execution of agent-based models, such as Parallel Discrete Event Simulation (PDES), are of great relevance/benefit. On the other hand, parallelism entails that the final output provided by the simulator should closely match the one provided by a traditional sequential run. This is not obvious given that, for performance and efficiency reasons, parallel simulation engines do not allow the evaluation of global predicates on the simulation model evolution with arbitrary time-granularity along the simulation time-Axis. In this article we present a study on the effects of parallelization of agent-based simulations, focusing on complementary aspects such as performance and reliability of the provided simulation output. We target Terrain Covering Ant Robots (TCAR) simulations, which are useful in rescue scenarios to determine how many agents (i.e., robots) should be used to completely explore a certain terrain for possible victims within a given time. © 2014 Springer-Verlag Berlin Heidelberg
Mesonic Form Factors
We have started a program to compute the electromagnetic form factors of
mesons. We discuss the techniques used to compute the pion form factor and
present preliminary results computed with domain wall valence fermions on MILC
asqtad lattices, as well as Wilson fermions on quenched lattices. These methods
can easily be extended to rho-to-gamma-pi transition form factors.Comment: 7 pages, 6 figures, Workshop on Lattice Hadron Physics 2003 (LHP2003
Anatomia do cone medular aplicada à via epidural de administração de fármacos em macacos-prego ( Sapajus libidinosus )
- …