Sentence examples for standardized data processing from inspiring English sources

Thus, automated and standardized data processing procedures, based on clearly defined criteria, such as statistical parameters and thresholds, are a prerequisite and highly desirable to guarantee the reproducibility and traceability of modeling results.

Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspectral data.

Deutsch, E. W. et al. Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

For the analysis of the iFCMRI data, a standardized data processing approach will be demonstrated on an item-by-item basis.

Since only one biological samples was sequenced, in order to avoid possible high false positive rates we first used trimmed mean of M values (TMM) to standardize data processing [ 48], then took advantage of DEGseq to analyze differentially expressed genes; the analysis conditions were qvalue <0.005 & log2 (foldchange) >1 [ 49– 51].

Clearly, aforementioned challenges can be solved in a more engineering manner, and a well-designed experiment system matching some systematic, standardizing data processing pipeline will be an important factor for a successful study.

Reporting on epoch length was fairly high, with 82%% of accelerometry articles reporting the preset epochs at which PA data were sampled.> Additional guidelines published by Ward et al. [ 6] recommended standardized data definitions and processing procedure.

The streamlined data processing and standardized data interpretation allows the comparison of the Mycobacterium tuberculosis MLPA results between different experiments.

The large sample size comprising data from eight European countries, the strictly standardized data assessment, documentation and data cleaning processing, guarantee the highest possible data quality.

(2) Standardization processing of data Because of the different orders of magnitude and dimension of feature indexes, for the convenience of analysis and comparison, the sample data needs to be standardized; data range is transferred to the domain [0, 1] (normalized processing).

Data extraction was performed by two trained research assistants independently following standardized data collection procedures.