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The work of Aljaafreh, Alshabatat, and Najim [76] that uses fuzzy logic inference for online identification of abnormal driving data was implemented using Fuzzylite [84], a free and open source fuzzy logic control engine for multiple platforms, including Android.
To estimate the genetic and environmental components of variance of the traits, twin model fitting of raw data was implemented using the statistical package Mx [ 37].
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All ESC and GCT mRNA array data were implemented using the Affymetrix Human Genome U133 Plus 2.0 chips.
Normalization and analysis of the microarray data were implemented using Bioconductor.
The user interface and modules to access the data were implemented using PHP.
In the present study, collection, storage, processing, and analysis of big-data-based biological and environmental information were implemented using cloud computing.
A prototype data warehouse was implemented using biological stream survey, hydrologic, and vegetation data to observe spatial patterns in biological community distributions.
Multiple imputation also used outcome data, and was implemented using chained equations through the ice command with parameter estimates combined across 20 imputed data sets using mi estimate in Stata.
The iPad data layer was implemented using a variety of built-in frameworks.
A case-cohort design was implemented using data from 10 US study sites participating in the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring Network.
The above scheme was implemented using simulated data in order to obtain sufficient sample size.
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