971 resultados para refinement calculus


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National Natural Science Foundation of China; Public Administration and Civil Service Bureau of Macau SAR; Companhia de Telecomunicacoes de Macau S.A.R.L.; Macau SAR Government Tourist Office

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Knowledge Systems Institute Graduate School

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National Natural Science Foundation of China [40771205]; National Science Fund for Distinguished Young Scholars [40625002]; Chinese Academy of Sciences [KZCX2-YW-315]

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A refined version of the edge-to-edge matching model is described here. In the original model, the matching directions were obtained from the planes with all the atomic centers that were exactly in the plane, or the distance from the atomic center to the plane which was less than the atomic radius. The direction-matching pairs were the match of straight rows-straight rows and zigzag rows-zigzag rows. In the refined model, the matching directions were obtained from the planes with all the atomic centers that were exactly in the plane.

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A program was written to solve calculus word problems. The program, CARPS (CALculus Rate Problem Solver), is restricted to rate problems. The overall plan of the program is similar to Bobrow's STUDENT, the primary difference being the introduction of "structures" as the internal model in CARPS. Structures are stored internally as trees. Each structure is designed to hold the information gathered about one object. A description of CARPS is given by working through two problems, one in great detail. Also included is a critical analysis of STUDENT.

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Gough, John, 'Quantum Stratonovich Stochastic Calculus and the Quantum Wong-Zakai Theorem', Journal of Mathematical Physics. 47, 113509, (2006)

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Greaves, George; Jenkins, T.E.; Landron, C.; Hennet, L., (2001) 'Liquid alumina: detailed atomic coordination determined from neutron diffraction data using empirical potential structure refinement', Physical Review Letters 86 pp.4839-4842 RAE2008

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We consider the problems of typability[1] and type checking[2] in the Girard/Reynolds second-order polymorphic typed λ-calculus, for which we use the short name "System F" and which we use in the "Curry style" where types are assigned to pure λ -terms. These problems have been considered and proven to be decidable or undecidable for various restrictions and extensions of System F and other related systems, and lower-bound complexity results for System F have been achieved, but they have remained "embarrassing open problems"[3] for System F itself. We first prove that type checking in System F is undecidable by a reduction from semi-unification. We then prove typability in System F is undecidable by a reduction from type checking. Since the reverse reduction is already known, this implies the two problems are equivalent. The second reduction uses a novel method of constructing λ-terms such that in all type derivations, specific bound variables must always be assigned a specific type. Using this technique, we can require that specific subterms must be typable using a specific, fixed type assignment in order for the entire term to be typable at all. Any desired type assignment may be simulated. We develop this method, which we call "constants for free", for both the λK and λI calculi.

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We study the problem of type inference for a family of polymorphic type disciplines containing the power of Core-ML. This family comprises all levels of the stratification of the second-order lambda-calculus by "rank" of types. We show that typability is an undecidable problem at every rank k ≥ 3 of this stratification. While it was already known that typability is decidable at rank ≤ 2, no direct and easy-to-implement algorithm was available. To design such an algorithm, we develop a new notion of reduction and show how to use it to reduce the problem of typability at rank 2 to the problem of acyclic semi-unification. A by-product of our analysis is the publication of a simple solution procedure for acyclic semi-unification.

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An iterative method for reconstructing a 3D polygonal mesh and color texture map from multiple views of an object is presented. In each iteration, the method first estimates a texture map given the current shape estimate. The texture map and its associated residual error image are obtained via maximum a posteriori estimation and reprojection of the multiple views into texture space. Next, the surface shape is adjusted to minimize residual error in texture space. The surface is deformed towards a photometrically-consistent solution via a series of 1D epipolar searches at randomly selected surface points. The texture space formulation has improved computational complexity over standard image-based error approaches, and allows computation of the reprojection error and uncertainty for any point on the surface. Moreover, shape adjustments can be constrained such that the recovered model's silhouette matches those of the input images. Experiments with real world imagery demonstrate the validity of the approach.