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To analyze the performance of parameter estimation methods with a time series dataset at a higher noise level, we generated only a single time series data sample and used this as the observed dataset in the experiments with model.
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First, clustering start with the input dataset at a high identity threshold (≥ 90%).
It can cluster a PDB-sized dataset in ∼20 min. In the hierarchical clustering process, the program first performs clustering on the original input dataset at a high identity threshold, and the representatives of each previous clustering step will be the input of the following clustering run at a lower identity threshold.
Virtual monoenergetic datasets reconstructed at a high kV can help reduce blooming artefact, allowing improved assessment of vascular stent patency [39], and of heavily calcified vessels [40].
High density ALS elevation point clouds and large scale datasets allowed model development at a higher resolution (2 m) but the decision tree model at 10 m resolution performed better than the rest.
This dataset was acquired at a high spatial resolution of 20 μm, requiring the use of HCCA matrix, which forms relatively small crystals.
Thus, it is important to have access to datasets that are at a high geographic resolution with pertinent GP workload information.
The main conclusion is that if one set of classification rules for a specific landscape was determined for a high-resolution dataset at a small subset, it could be applied for larger areas even if only coarser digital elevation model information were available.
We recently collected a new dataset at higher resolutions.
At a higher level, those datasets allow to consider whole populations from a God-eye point of view.
Similar results are obtained with cultures at a higher growth rate (datasets B1-B3), B1 and B2 are highly consistent, while protein producing B3 shows similar behaviour to A3-A4.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com