373 research outputs found
Monthly progress report no. 6, apr. 10 - may 10, 1965
Leak testing and welding gold plated Kovar covers to precision flat pack
Intelligent tutoring systems for space applications
Artificial Intelligence has been used in many space applications. Intelligent tutoring systems (ITSs) have only recently been developed for assisting training of space operations and skills. An ITS at Southwest Research Institute is described as an example of an ITS application for space operations, specifically, training console operations at mission control. A distinction is made between critical skills and knowledge versus routine skills. Other ITSs for space are also discussed and future training requirements and potential ITS solutions are described
Development of an energy dissipation system based on metal extrusion
Energy dissipation system based on metal extrusio
A fundamental effect in computations on real numbers
AbstractFor several elementary constructions which often occur in computations on real numbers we prove that they possess unavoidable intensionalities. Our examples give sharp bounds for constructive extensional choices and Skolem functors in theories of order ⩾2
Benjamini-Schramm Convergence of Normalized Characteristic Numbers of Riemannian Manifolds
We study a weak form of Gromov-Hausdorff convergence
of Riemannian manifolds, also known as
Benjamini-Schramm convergence. This concept
is also applicable to other areas and has widely
been studied in the context of graphs.
The main result is the continuity of characteristic
numbers normalized by the volume with respect
to the Benjamini-Schramm topology on the class
of Riemannian manifolds with a uniform lower
bound on injectivity radius and Ricci curvature.
An immediate consequence is a comparison theorem
that gives for any characteristic number a
linear bound in terms of the volume on the entire
class of manifolds mentioned. We give another
interpretation of the result showing that characteristic
numbers can be reconstructed with some
accuracy from local random information
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