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» Learning from Highly Structured Data by Decomposition
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UBIMOB
2009
ACM
225views Management» more  UBIMOB 2009»
15 years 2 months ago
Historical data storage for large scale sensor networks
Wireless sensor networks are rapidly finding their way through a plethora of new applications like precision farming and forestry, with increasing network scale, system complexit...
Loïc Petit, Abdelhamid Nafaa, Raja Jurdak
BMCBI
2010
113views more  BMCBI 2010»
14 years 10 months ago
Use of historic metabolic biotransformation data as a means of anticipating metabolic sites using MetaPrint2D and Bioclipse
Background: Predicting metabolic sites is important in the drug discovery process to aid in rapid compound optimisation. No interactive tool exists and most of the useful tools ar...
Lars Carlsson, Ola Spjuth, Samuel Adams, Robert C....
CCGRID
2009
IEEE
15 years 2 months ago
Hierarchical Caches for Grid Workflows
From personal software to advanced systems, caching mechanisms have steadfastly been a ubiquitous means for reducing workloads. It is no surprise, then, that under the grid and clu...
David Chiu, Gagan Agrawal
IPPS
1999
IEEE
15 years 2 months ago
A Graph Based Framework to Detect Optimal Memory Layouts for Improving Data Locality
In order to extract high levels of performance from modern parallel architectures, the effective management of deep memory hierarchies is very important. While architectural advan...
Mahmut T. Kandemir, Alok N. Choudhary, J. Ramanuja...
CIKM
2006
Springer
15 years 5 days ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu