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She combines theory with longitudinal large-sample data (e.g., robotics, biomedical, multi-industry datasets), background fieldwork, and state-of-the-art quantitative methods.
An analysis of the background fractal dimension distributions obtained using TTE and DISCSC data (143 and 110 background regions, respectively), indicates that for both datasets background fractal dimensions 〈Dbgr〉 = 1.5 that the fractal dimension distributions obtained by using these data can be processed simultaneously.
A period of steady state during the methane surrogate experiments was reevaluated by linear regression and statistical analysis methods suggested by Yum and Peirce (1997), then distributions of two datasets, background data and steady state data, were compared to investigate possible surrogates that could detect shifts of methane concentrations in water.
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A list is returned containing tumour label, the number of tumour type samples within the sample set (hits), the number of tumour type samples within the ExpO dataset, foreground), the number of non tumour type samples within the ExpO dataset (background), the number of samples selected on expression (sample.size) and the p-value (p. value) associated with enrichment.
The BEVTFILE keyword is added to HRC-I datasets when background subtraction is used; it contains the name of the background event file used.
We used the binding peak summits in each dataset, provided in the original publications, as the data owners might have a better understanding of their datasets for background subtraction and normalization.
To provide a fair comparison, we invested extensive effort into ensuring that we evaluated all methods under identical conditions with the same reference sequences, test datasets and background taxonomies, using their recommended settings.
Finally, experimental results on a large-scale dataset called Background Models Challenge (BMC 2012) show the comparative performance of 32 different robust subspace learning/tracking methods.
In the abovementioned experiments, we use images in the ImageNet dataset as background images, as shown in Fig. 2.
The whole annotated microarray was used as the reference dataset (ie, background) for pathway analysis.
These sample groups were tested for enrichment of malignant tissue type when compared to the complete dataset as background.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com