Sentence examples for build and validate a from inspiring English sources

SIIL subsequently decided to design, build, and validate a new building dedicated to the production of 2 conjugate vaccines MenAfriVac and Haemophilus influenzae type b conjugate – to ensure sufficient production capacity to deliver the agreed 25 million doses of MenAfriVac per year.

Fig. 4 a Active (1 3) and inactive (4 5) benzothiazole derivatives used to build and validate a pharmacophore model.

Amazon wanted to simplify this process and allow any developer to quickly build and validate a model and process millions or even billions of predictions in real time.

Furthermore, Partial Least Squares-regression (PLS-regression) was trained to correlate VE-tongue data with the reference measurement in order to build and validate a prediction model for UCC determination.

The non-destructive parameters extracted from the gripper finger accelerometers were used to build and validate a partial least square model, with a calibration regression coefficient of r = 0.87 and a high prediction performance (r = 0.90).

In this study we aimed to build and validate a PBPK model for the characterization of infant exposure to POPs through placental transfer and breast-feeding.

This study aimed to design, build and validate an ohmic heating apparatus in bench scale and evaluate its performance on liquid food processing.

The aim of this paper is to propose, build and validate an architecture based on the analysis of visual characteristics by using computer vision techniques and machine learning to detect both distraction and drowsiness in drivers.

The data has been used to build and validate an IDA ICE simulation model in order to study possible improvements in energy consumption by changing the thermal mass and the ventilation strategies.

We designed, built, and validated a phantom that allows for accurate, sensitive, fast, and inexpensive daily QA procedures in proton therapy with PBS.

It builds and validates a statistical model that predicts the correctness of next incoming read transaction on a data object or attribute, at any instant of time t (thereby CI) with known number of replicas (Rp) and the time gap (tg) between the observed read and preceding latest update using logistic regression and radial basis function artificial neural network (RBFNN).