Sentence examples for resources simulation from inspiring English sources

Table 4 Cost-time analysis for locally provisioned resources Simulation memory Cost per simulation hour Max hours 3GB $0.576 53,568 40GB $2.30413,3922.

The paper also discusses current and future use of manufacturing resource simulation for design/configuration, operational planning and scheduling, and service and maintenance of manufacturing systems.

The paper discusses a software package that has been designed to enhance the efficiency of applying a range of hydrological and water resource simulation models.

At the system level, radio resource simulations are necessary to understand the benefits of the multiuser asynchronous approach.

Due to the lack of a systematic framework and supporting system between engineers and related manufacturing information resources, many simulation engineers have actually wasted time and cost with redundant tasks for simulation.

Utilizing current advanced HPC resources, the simulation rates achieved by our algorithms bring within reach performing complex multiscale simulations for solving vexing problems at the interface of biology and engineering, such as thrombosis in blood flow which combines millisecond-scale hematology with microscale blood flow at resolutions of micro-to-nanoscale cellular components of platelets.

In the last decades, with the advances in computational resources, numerical simulation approaches have become increasingly popular.

Wetlands are extremely valuable natural resources, the simulation of wetland landscape spatial-temporal evolution can reveal the mechanisms and laws of landscape succession, achieve the sustainable landscape use and provide wetland conservation and management decision support.

The aim of this review is to inform future educational strategies by synthesising research related to blended learning resources using simulation videos to teach clinical skills for health students.

Building and deploying successful big data smart city applications will require addressing the challenges and open issues, following rigorous design and development models, having well trained human resources, utilizing simulation models and being ell prepared and well supported by the governing entities.

However, limitations associated with up scaling conventional ash dispersal modelling methods include the computationally intensive nature of regional-scale applications that would require significant high-performance computing resources, long simulation times and could potentially constrain the spatial resolution, geographic extent and number of sources considered.