Sentence examples for approach by generating from inspiring English sources
A traffic simulation case study exemplifies this approach by generating a model for the SUMO traffic simulator from vehicular telemetry data.
We illustrate validity of our approach by generating a sliding mode control input function for stabilization of an inverted pendulum.
We further validated our approach by generating different batches of scCAT-seq profiles from two additional ENCODE cell lines: HeLa-S3 cervix adenocarcinoma and HCT116 colorectal carcinoma cell lines (Supplementary Data 1).
We compare the performance of our algorithm against that of a traditional Force-Directed Scheduling approach by generating architectures from algorithms selected from embedded computing and scientific computing.
The approach, by generating networks where the input data are fed via external inputs rather than initial conditions, enables multiple prototype patterns to be retrieved simultaneously.
In this study we suggest an alternative approach; by generating NCR-Ig fusion proteins we allow the NK receptors to bind to their preferred (and mostly unknown) tumor ligands and to selectively recruit, via the Ig domain, effector mechanisms against the malignant cells.
In the study presented here, we integrated the 2 approaches by generating adenoviral vectors that express both the HSV-TK gene from the adenoviral E4 promoter and, from a distinct expression unit, multiple copies of an amiRNA directed against the wt Ad5 pTP mRNA.
As noted in Section "Approach to police patrol districting" our approach begins by generating thousands of plans using randomized districting parameters.
The approach starts by generating the input/output data.
The first approach begins by generating a pooled M-estimator of scatter based on all the data, followed by a penalised M-estimator of scatter for each group, with the penalty term chosen so that the individual scatter matrices are shrunk towards the pooled scatter matrix.
We approach this by generating a set of synthetic trial outcomes and evaluate the loss associated with each of the algorithms across 100 repeated runs to minimize variability caused by the stochastic nature of the algorithms.
