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among a wide class of list maintenance rules. Other natural heuristics, such as the transpose and frequency count rules, da not share this property. We generalize our results to show that move-to-front is within a constant factor of optimum as long as the access cost is a convex function. We also study

CLAIMS ® /REFERENCE (File 124) is a dictionary index to the two subject classifications which are searchable in the CLAIMS family of patent databases (File 340, 341, 942). File 124 describes these two distinct systems of indexing: (1) U.S. Patent Classification codes from the U.S. Patent and Trademark Office and (2) the UNITERM and CDB indexing system developed by IFI CLAIMS Patent Services. The description of the U.S. Patent Classification corresponds to the Manual of Classification and the Index to the U.S. Patent Classification issued by the U.S. Patent and Trademark Office. The UNITERM and CDB indexing terms correspond to the IFI/CLAIMS Vocabulary and Thesaurus for use in the CLAIMS ® /UNITERM (File 341) and CLAIMS ® /COMPREHENSIVE (File 942) databases.

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CLAIMS ® /REFERENCE (File 124) is a dictionary index to the two subject classifications which are searchable in the CLAIMS family of patent databases (File 340, 341, 942). File 124 describes these two distinct systems of indexing: (1) U.S. Patent Classification codes from the U.S. Patent and Trademark Office and (2) the UNITERM and CDB indexing system developed by IFI CLAIMS Patent Services. The description of the U.S. Patent Classification corresponds to the Manual of Classification and the Index to the U.S. Patent Classification issued by the U.S. Patent and Trademark Office. The UNITERM and CDB indexing terms correspond to the IFI/CLAIMS Vocabulary and Thesaurus for use in the CLAIMS ® /UNITERM (File 341) and CLAIMS ® /COMPREHENSIVE (File 942) databases.

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7 � No integrity or consistency checks � Redundant schemata � Typos, transmission errors, incorrect calculations � Variants

. In this system sources select transmission rates that maximize their own benefits, utility minus bandwidth cost, and network links adjust bandwidth prices to coordinate the sources' decisions. We allow feedback delays to be different, substantial and time-varying, and links and sources to update

Abstract not found

This paper proposes a method for estimating the number of iterations required until convergence of a feed-forward neural network for any weight update frequency. The NETtalk neural application has been used to get data on convergence and the best learning rate. Our results show that less frequent