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Physical Sciences and Mathematics Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Everyone Is A Curator: Human-Assisted Preservation For Ore Aggregations, Frank Mccown, Michael L. Nelson, Herbert Van De Sompel
Everyone Is A Curator: Human-Assisted Preservation For Ore Aggregations, Frank Mccown, Michael L. Nelson, Herbert Van De Sompel
Computer Science Faculty Publications
The Open Archives Initiative (OAI) has recently created the Object Reuse and Exchange (ORE) project that defines Resource Maps (ReMs) for describing aggregations of web resources. These aggregations are susceptible to many of the same preservation challenges that face other web resources. In this paper, we investigate how the aggregations of web resources can be preserved outside of the typical repository environment and instead rely on the thousands of interactive users in the web community and the Web Infrastructure (the collection of web archives, search engines, and personal archiving services) to facilitate preservation. Inspired by Web 2.0 services such as …
Correlation Of Music Charts And Search Engine Rankings, Martin Klein, Olena Hunsicker, Michael Nelson
Correlation Of Music Charts And Search Engine Rankings, Martin Klein, Olena Hunsicker, Michael Nelson
Computer Science Faculty Publications
We investigate the question whether expert rankings of real-world entities correlate with search engine (SE) rankings of corresponding web resources. We compare Billboards "Hot 100 Airplay" music charts with SE rankings of associated web resources. Out of nine comparisons we found two strong, two moderate, two weak and one negative correlation. The remaining two comparisons were inconclusive.
Evaluating Multicore Algorithms On The Unified Memory Model, John E. Savage, Mohammad Zubair
Evaluating Multicore Algorithms On The Unified Memory Model, John E. Savage, Mohammad Zubair
Computer Science Faculty Publications
One of the challenges to achieving good performance on multicore architectures is the effective utilization of the underlying memory hierarchy. While this is an issue for single-core architectures, it is a critical problem for multicore chips. In this paper, we formulate the unified multicore model (UMM) to help understand the fundamental limits on cache performance on these architectures. The UMM seamlessly handles different types of multiple-core processors with varying degrees of cache sharing at different levels. We demonstrate that our model can be used to study a variety of multicore architectures on a variety of applications. In particular, we use …