A Markov random field approach for modeling spatio-temporal evolution of microstructures
ثبت نشده
چکیده
The following problem is addressed: ‘Can one synthesize microstructure evolution over a large area given experimental movies measured over smaller regions?’ Our input is a movie of microstructure evolution over a small sample window. A Markov random field (MRF) algorithm is developed that uses this data to estimate the evolution of microstructure over a larger region. Unlike the standard microstructure reconstruction problem based on stationary images, the present algorithm is also able to reconstruct timeevolving phenomena such as grain growth. Such an algorithm would decrease the cost of full-scale microstructure measurements by coupling mathematical estimation with targeted small-scale spatiotemporal measurements. The grain size, shape and orientation distribution statistics of synthesized polycrystalline microstructures at different times are compared with the original movie to verify the method.
منابع مشابه
Context-aware Modeling for Spatio-temporal Data Transmitted from a Wireless Body Sensor Network
Context-aware systems must be interoperable and work across different platforms at any time and in any place. Context data collected from wireless body area networks (WBAN) may be heterogeneous and imperfect, which makes their design and implementation difficult. In this research, we introduce a model which takes the dynamic nature of a context-aware system into consideration. This model is con...
متن کاملEvaluation of Tests for Separability and Symmetry of Spatio-temporal Covariance Function
In recent years, some investigations have been carried out to examine the assumptions like stationarity, symmetry and separability of spatio-temporal covariance function which would considerably simplify fitting a valid covariance model to the data by parametric and nonparametric methods. In this article, assuming a Gaussian random field, we consider the likelihood ratio separability test, a va...
متن کاملAssessment of Neonate's Congenital Hypothyroidism Pattern Using Poisson Spatio-temporal Model in Disease Mapping under the Bayesian Paradigm during 2011-18 in Guilan, Iran
Background: Congenital Hypothyroidism (CH) is one of the reasons for mental retardation and defective growth in neonates. It can be treated if it is diagnosed early. The congenital hypothyroidism can be diagnosed using newborn screening in the first days after birth. Disease mapping helps to identify high-risk areas of the disease. This study aimed to evaluate the pattern of CH using the Poisso...
متن کاملSpatio-temporal analysis of diurnal air temperature parameterization in Weather Stations over Iran
Diurnal air temperature modeling is a beneficial experimental and mathematical approach which can be used in many fields related to Geosciences. The modeling and spatio-temporal analysis of air Diurnal Temperature Cycle (DTC) was conducted using data obtained from 105 synoptic stations in Iran during the years 2013-2014 for the first time; the key variable for controlling the cosine term i...
متن کاملSTCS-GAF: Spatio-Temporal Compressive Sensing in Wireless Sensor Networks- A GAF-Based Approach
Routing and data aggregation are two important techniques for reducing communication cost of wireless sensor networks (WSNs). To minimize communication cost, routing methods can be merged with data aggregation techniques. Compressive sensing (CS) is one of the effective techniques for aggregating network data, which can reduce the cost of communication by reducing the amount of routed data to t...
متن کامل