Linked Life Data

17477675

Source:http://linkedlifedata.com/resource/pubmed/id/17477675

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2007-5-4
pubmed:abstractText
We report on an adaptive binning approach designed for data visualization within scientific disciplines where counting statistics are expected to follow Poisson distributions. We envisage a wide range of applications stemming from astrophysics to the condensed matter sciences. Our main focus of interest concerns, however, neutron spectroscopy data from single-crystal samples where signals span a four-dimensional space defined by three spatial coordinates plus time. This makes widely used equal-width binning schemes inadequate since physically relevant information is often concentrated within rather small regions of such a space. Our aim is thus to generate optimally binned data sets from one-dimensional to three-dimensional volumes to provide the experimentalist with enhanced ability to carry out searches within a four-dimensional space. Several binning algorithms are then scrutinized against experimental as well as simulated data.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0034-6748
pubmed:author
pubmed:issnType
Print
pubmed:volume
78
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
043901
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Experimental neutron spectroscopy data visualization: adaptive tessellation algorithm.
pubmed:affiliation
CSIC, Instituto de Estructura de la Materia, Serrano 123, Madrid, Spain.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't