669 research outputs found
Complexity of Problems of Commutative Grammars
We consider commutative regular and context-free grammars, or, in other
words, Parikh images of regular and context-free languages. By using linear
algebra and a branching analog of the classic Euler theorem, we show that,
under an assumption that the terminal alphabet is fixed, the membership problem
for regular grammars (given v in binary and a regular commutative grammar G,
does G generate v?) is P, and that the equivalence problem for context free
grammars (do G_1 and G_2 generate the same language?) is in
Using the Expectation Maximization Algorithm with Heterogeneous Mixture Components for the Analysis of Spectrometry Data
Coupling a multi-capillary column (MCC) with an ion mobility (IM)
spectrometer (IMS) opened a multitude of new application areas for gas
analysis, especially in a medical context, as volatile organic compounds (VOCs)
in exhaled breath can hint at a person's state of health. To obtain a potential
diagnosis from a raw MCC/IMS measurement, several computational steps are
necessary, which so far have required manual interaction, e.g., human
evaluation of discovered peaks. We have recently proposed an automated pipeline
for this task that does not require human intervention during the analysis.
Nevertheless, there is a need for improved methods for each computational step.
In comparison to gas chromatography / mass spectrometry (GC/MS) data, MCC/IMS
data is easier and less expensive to obtain, but peaks are more diffuse and
there is a higher noise level. MCC/IMS measurements can be described as samples
of mixture models (i.e., of convex combinations) of two-dimensional probability
distributions. So we use the expectation-maximization (EM) algorithm to
deconvolute mixtures in order to develop methods that improve data processing
in three computational steps: denoising, baseline correction and peak
clustering. A common theme of these methods is that mixture components within
one model are not homogeneous (e.g., all Gaussian), but of different types.
Evaluation shows that the novel methods outperform the existing ones. We
provide Python software implementing all three methods and make our evaluation
data available at http://www.rahmannlab.de/research/ims
Sarasota Performing Arts Research Coalition Community Report
Presents findings from a 2002 Urban Institute survey of Sarasota residents' perceptions of and attitudes toward the performing arts
Washington, D.C. Performing Arts Research Coalition Community Report
Presents findings from a 2002 Urban Institute survey of Washington-area residents' perceptions of and attitudes toward the performing arts
A note on first-order spectra with binary relations
The spectrum of a first-order sentence is the set of the cardinalities of its
finite models. In this paper, we consider the spectra of sentences over binary
relations that use at least three variables. We show that for every such
sentence , there is a sentence that uses the same number of
variables, but only one symmetric binary relation, such that its spectrum is
linearly proportional to the spectrum of . Moreover, the models of
are all bipartite graphs. As a corollary, we obtain that to settle
Asser's conjecture, i.e., whether the class of spectra is closed under
complement, it is sufficient to consider only sentences using only three
variables whose models are restricted to undirected bipartite graphs
Seattle Performing Arts Research Coalition Community Report 2002
Presents findings from a 2002 Urban Institute survey of Seattle residents' perceptions of and attitudes toward the performing arts
Washington, D.C. Performing Arts Research Coalition Community Report
Presents findings from a 2002 Urban Institute survey of Washington-area residents' perceptions of and attitudes toward the performing arts
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