Sentence examples for traffic behavior in from inspiring English sources

More research is needed to find effective behavioral change techniques (other than increasing risk awareness) for promoting safe traffic behavior in adolescents.

This article focuses on the modeling and simulation of microscopic traffic behavior in virtual reality system using multi-agent technology, a hierarchical modular modeling methodology and distributed simulation.

A good traffic assignment model can be a powerful tool to describe the characteristics of traffic behavior in a road network.

In this study, the traffic informer program – designed to promote safe traffic behavior in the pre-driver population – was experimentally evaluated, with a specific focus on bicycle use.

Therefore, we propose a RCM based on stochastic principle to understand the traffic behavior in a better way.

M Szmit, A Szmit (2012) [18] Computer networks Holt-Winters method is used to understand the traffic behavior in a computer network with the aim to perform intrusion detection.

This was also described for the antigen 85A-deficient mutant of Mtb (ΔfbpA), a candidate vaccine with an enhanced immunogenicity profile presenting an altered intracellular trafficking behavior in macrophages, as ΔfbpA containing phagosomes were able to fuse with late endosomes but failed to acquire rab7 and CD63 markers, avoiding lysosomal fusion [45].

In the two examples targeted, the functional activity of the labeled molecules was comparable in the human and mouse systems to that displayed by the unlabeled molecules, which should allow us to use these labeled analogues to study their trafficking behavior in vivo.

The LC matches with the data from Mallikarjuna et al. [3] as well as Gunay [8], due to similarity in traffic behavior of studied traffic in these researches to that studied in this paper.

Elastic optical networks (EONs) have emerged as a promising solution for future high speed networks because of their ability to efficiently manage network resources and provide better spectrum utilization to cope with the recent rapid change in traffic behavior and the tremendous growth in bandwidth demand.

It is composed of three components, a machine learning rule discovery, a threat prediction model builder and tools to ensure timely reaction to rules violation and un-standardized and ongoing changes in traffic behavior.