1,031 research outputs found
An Iterative Scheme for Leverage-based Approximate Aggregation
The current data explosion poses great challenges to the approximate
aggregation with an efficiency and accuracy. To address this problem, we
propose a novel approach to calculate the aggregation answers with a high
accuracy using only a small portion of the data. We introduce leverages to
reflect individual differences in the samples from a statistical perspective.
Two kinds of estimators, the leverage-based estimator, and the sketch estimator
(a "rough picture" of the aggregation answer), are in constraint relations and
iteratively improved according to the actual conditions until their difference
is below a threshold. Due to the iteration mechanism and the leverages, our
approach achieves a high accuracy. Moreover, some features, such as not
requiring recording the sampled data and easy to extend to various execution
modes (e.g., the online mode), make our approach well suited to deal with big
data. Experiments show that our approach has an extraordinary performance, and
when compared with the uniform sampling, our approach can achieve high-quality
answers with only 1/3 of the same sample size.Comment: 17 pages, 9 figure
Dual-Topology Hamiltonian-Replica-Exchange Overlap Histogramming Method to Calculate Relative Free Energy Difference in Rough Energy Landscape
A novel overlap histogramming method based on Dual-Topology
Hamiltonian-Replica-Exchange simulation technique is presented to efficiently
calculate relative free energy difference in rough energy landscape, in which
multiple conformers coexist and are separated by large energy barriers. The
proposed method is based on the realization that both DT-HERM exchange
efficiency and confidence of free energy determination in overlap histogramming
method depend on the same criteria: neighboring states' energy derivative
distribution overlap. In this paper, we demonstrate this new methodology by
calculating free energy difference between amino acids: Leucine and Asparagine,
which is an identified chanllenging system for free energy simulations.Comment: 14 pages with 4 figure
GXQuery: Extending XQuery for Querying Graph-structured XML Data
XML data can be naturally modeled as a graph. Existing query languages to XML can only express queries of matching XML document with a tree-structured schema with structural and value constraints without the consideration of graph features. The ability of such query languages cannot satisfy various requirements of querying graph-structured XML data. In this paper, GXQuery is presented as an extension of XQuery, an XML query language recommended byW3C, to express more flexible query on graph-structured XML. GXQuery expressions can match XML documentwith graph-structured schema with not only structural and value constraints, but also topological constraints
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