receiver driven and requires no per-receiver status at the sender, in order to scale to large numbers of receivers. It relies on standard functionalities of multicast routers, and is suitable for continuous stream and reliable bulk data transfer. In the paper we illustrate the algorithm, characterize its

A framework for skill acquisition is proposed that includes two major stages in the development of a cognitive skill: a declarative stage in which facts about the skill domain are interpreted and a procedural stage in which the domain knowledge is directly embodied in procedures for performing the skill. This general framework has been instantiated in the ACT system in which facts are encoded in a propositional network and procedures are encoded as productions. Knowledge compilation is the process by which the skill transits from the declarative stage to the procedural stage. It consists of the subprocesses of composition, which collapses sequences of productions into single productions, and proceduralization, which embeds factual knowledge into productions. Once proceduralized, further learning processes operate on the skill to make the productions more selective in their range of applications. These processes include generalization, discrimination, and strengthening of productions. Comparisons are made to similar concepts from past learning theories. How these learning mechanisms apply to produce the power law speedup in processing time with practice is discussed. It requires at least 100 hours of learning and practice to acquire any significant cognitive skill to a reasonable degree of proficiency. For instance, after 100 hours a student learning to program a computer has achieved only a very modest facility in the skill. Learning one's primary language takes tens of thousands of hours. The psychology of human learning has been very thin in ideas about what happens to skills under the impact of this amount of learning—and for obvious reasons. This article presents a theory about the changes in the nature of a skill over such large time scales and about the basic learning processes that are responsible.

surprisingly good results for a wide range of textures. Second, we extend the algorithm to perform texture transfer -- rendering an object with a texture taken from a different object. More generally, we demonstrate how an image can be re-rendered in the style of a different image. The method works directly

extension of its request methods. A feature of HTTP is the typing and negotiation of data representation, allowing systems to be built independently of the data being transferred. HTTP has been in use by the World-Wide Web global information initiative since 1990. This specification defines the protocol

The rising abuse of computers and increasing threat to personal privacy through data banks have stimulated much interest m the techmcal safeguards for data. There are four kinds of safeguards, each related to but distract from the others. Access controls regulate which users may enter the system

In this paper we address the issue of privacy preserving data mining. Specifically, we consider a scenario in which two parties owning confidential databases wish to run a data mining algorithm on the union of their databases, without revealing any unnecessary information. Our work is motivated

The term Linked Data refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions

This paper presents the design and implementation of DOT, a flexible architecture for data transfer. This architecture separates content negotiation from the data transfer itself. Applications determine what data they need to send and then use a new transfer service to send it. This transfer

The central proposal of this article is that verbal reports are data. Accounting for verbal reports, as for other kinds of data, requires explication of the mech-anisms by which the reports are generated, and the ways in which they are sensitive to experimental factors (instructions, tasks, etc

Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications