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The theory for sample surveys has been developed using two theoretical frameworks: design-based and model-based.
In addition, it explains about a new IDS which has been developed using two proposed algorithms namely intelligent rule-based attribute selection algorithm and intelligent rule-based enhanced multiclass support vector machine (IREMSVM).
These tools have been developed using two distinct algorithms that initially identify (Gapfind) what the authors have called a "no production" or "no consumption" metabolites [ 46] through analyzing the production or consumption fluxes in the metabolic model.
To compare the results with those obtained by the conventional competitive radioimmunoassay (RIA) using a polyclonal antibody, a new immunoradiometric assay (IRMA) method was used which has recently been developed using two monoclonal antibodies raised to different epitopes of TA-4.
Since then, other prognostic predictors such as the Rotterdam 76-gene signature (ROT76) [ 8, 9] and the risk of relapse (ROR) score based on the PAM50 subtype assay [ 10] have been developed using two different node-negative and adjuvant treatment-naive populations.
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Within the DSSITP (Decision Support System for Intermodal Transport Policy) project, an assessment framework has been developed using three different models that are capable of assessing policies intended to enhance the growth of intermodal inland waterway and rail transport.
A chelate scale for Fe(III)[47] has been developed using seven natural ligands (Table 2 and Fig. 9) which react with Fe III) to form complexes spanning 20 log Ktherm units.
Here, phylogenetic tree has been developed using sixty proteins (n = 60) and it is an interactive tree with the orthologs and paralogs of the seed sequences.
Since the 1980s, a number of new immunoassay techniques has been developed using three labeling techniques (fluorescein, radioisotopes, and enzymes) [ 4].
An SVM-based classifier has been developed, using four dimensions of vector, one for each domain; this achieved 61.41% sensitivity, 90.65% specificity, 76.08% accuracy and 0.54 MCC.
The applications are developed using two different software development languages; C and COBOL.
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