Sentence examples for erosion to predict from inspiring English sources

The primary objective of this study was to determine the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of an MRI erosion to predict a new radiographic erosion in the same joint at a subsequent time point.

This paper presents a new frequency estimator algorithm for electric power systems that uses the Mathematical Morphology operators of dilation and erosion to predict the Clarke Components from voltage signals of three phases of the system.

The PPV of MRI erosions to predict subsequent radiographic erosions was low.

The question was whether one can apply a wind erosion model to predict the effect of wind erosion on the initial soil and landscape development.

The proposal of erosion models to predict the jet footprint during abrasive waterjet machining is a key element for the development of this technology, but it is very challenging because of the inherent fluctuations of the process.

The purpose of this study was to determine the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of a metatarsophalangeal (MTP) erosion on MRI to predict a subsequent radiographic erosion in the same joint.

In this context, the present work focuses on the use of advanced finite element (FE) methods to study the erosion mechanisms and to predict the coating behaviour in simulated erosion conditions.

An empirical erosion model is employed to predict the erosion rate of bend, and a fluid structure interaction (FSI) model is adopted to calculate the displacement of relief line.

The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies.

Understanding the factors that effect erosion makes it possible to predict the extent and consequences of onsite erosion.[5].

A basic difficulty with modelling soil loss is that the different forms of erosion have different causes and are influenced by different factors, so a model to predict erosion from arable land uses one group of parameters, but a model for gully erosion would use a very different set.