38 resultados para complexity in spatiotemporal evolution


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Process simulation programs are valuable in generating accurate impurity profiles. Apart from accuracy the programs should also be efficient so as not to consume vast computer memory. This is especially true for devices and circuits of VLSI complexity. In this paper a remeshing scheme to make the finite element based solution of the non-linear diffusion equation more efficient is proposed. A remeshing scheme based on comparing the concentration values of adjacent node was then implemented and found to remove the problems of oscillation.

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Using an entropy argument, it is shown that stochastic context-free grammars (SCFG's) can model sources with hidden branching processes more efficiently than stochastic regular grammars (or equivalently HMM's). However, the automatic estimation of SCFG's using the Inside-Outside algorithm is limited in practice by its O(n3) complexity. In this paper, a novel pre-training algorithm is described which can give significant computational savings. Also, the need for controlling the way that non-terminals are allocated to hidden processes is discussed and a solution is presented in the form of a grammar minimization procedure. © 1990.

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Successful product development, especially in motorsport, increasingly depends not just on the ability to simulate aero-thermal behavior of complex geometrical configurations, but also the ability to automate these simulations within a workflow and perform as many simulations as possible within constrained time frames. The core of these aero-thermal simulations - and usually the main bottleneck - is generating the computational mesh. This paper describes recent work aimed at developing a mesh generator which can reliably produce meshes for geometries of essentially arbitrary complexity in an automated manner and fast enough to keep up with the pace of an engineering development program. Our goal is to be able to script the mesh generation within an automated workflow - and forget it. © 2011 SAE International.

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Driven by the need for more responsive manufacturing processes and as a consequence of increasing complexity in products and production systems, this short paper introduces a number of developments in the area of modular, distributed manufacturing systems. Requirements for the development of such systems are addressed and, in particular, the relevance to current and future integrated control systems is examined. One of the key issues for integrated control systems in the future is the need to provide support for distributed decision-making in addition to existing distributed control capabilities.

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The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space and on scalability to high-dimensional problems. The mathematical developments rely on the theory of gradient descent algorithms adapted to the Riemannian geometry that underlies the set of fixedrank positive semidefinite matrices. In contrast with previous contributions in the literature, no restrictions are imposed on the range space of the learned matrix. The resulting algorithms maintain a linear complexity in the problem size and enjoy important invariance properties. We apply the proposed algorithms to the problem of learning a distance function parameterized by a positive semidefinite matrix. Good performance is observed on classical benchmarks. © 2011 Gilles Meyer, Silvere Bonnabel and Rodolphe Sepulchre.

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The capability of extending body structures is one of the most significant challenges in the robotics research and it has been partially explored in self-reconfigurable robotics. By using such a capability, a robot is able to adaptively change its structure from, for example, a wheel like body shape to a legged one to deal with complexity in the environment. Despite their expectations, the existing mechanisms for extending body structures are still highly complex and the flexibility in self-reconfiguration is still very limited. In order to account for the problems, this paper investigates a novel approach to robotic body extension by employing an unconventional material called Hot Melt Adhesives (HMAs). Because of its thermo-plastic and thermo-adhesive characteristics, this material can be used for additive fabrication based on a simple robotic manipulator while the established structures can be integrated into the robot's own body to accomplish a task which could not have been achieved otherwise. This paper first investigates the HMA material properties and its handling techniques, then evaluates performances of the proposed robotic body extension approach through a case study of a "water scooping" task. © 2012 IEEE.