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With these matrices we were finally able to calculate the real position of the objects in the arena from the pixel coordinates derived from the recordings.
We demonstrated in this study that, using the PCA subspace based on typical existing matrices, we were able to obtain a sensitive novel matrix, MIQS, empirically.
Because the same scale for intensity was used in both matrices, we were able to sum the exposures to these agents across the full job history for each individual.
Using these matrices, we were able to find orthologs for rhomboid proteases of P. berghei, P. falciparum & P. vivax and large subunit of U2 snRNP auxiliary factor of Cryptosporidium parvum in Arabidopsis thaliana.
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Therefore, with the common hidden variables and the trained weight matrices we are able to build an auto-encoder machine to reconstruct the input dynamic networks.
By using effective canonical labeling and adopting weighted adjacency matrices, we are able to perform graph isomorphism test in polynomial running time.
By checking against this matrix, we were able to determine boundaries corresponding to real-world positioning.
Based on this miRNA influence matrix we were able to group patients into aggressive and low risk cancer patients.
By using the Curriculum Alignment Matrix, we were able to analyze our curriculum and the way that we teach particular concepts in both the prerequisite course and the advanced courses.
In other words, viewing r i j s as a similarity matrix, we were looking for rows with a small value on the diagonal, but with some large off-diagonal element in that row.
So this is the matrix we're going to use to analyze the first stage of the game in the case where the equilibrium we're playing tomorrow is (Fight, quit).
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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