Geometric Dilution of Precision (GDOP) is a coefficient for constellations of Global Positioning System (GPS) satellites. These satellites are organized geometrically. Traditionally, GPS GDOP computation is based on the inversion matrix with complicated measurement equations. A new strategy for calculation of GPS GDOP is construction of time series problem; it employs machine learning and artif...

Brain tumor is one of the major reasons of death among people. It is indication that the chances of survival can be greater than before if the tumor is detected correctly at its early stage. This paper classifies the type of tumor using Artificial Neural Network (ANN) in MRI images of different patients with Astrocytoma type of brain tumor. The extraction of texture features in the detected tum...

Therapies for corneal disease and injury often rely on artificial implants, but integrating cells into synthetic corneal materials remains a significant challenge. The electrochemically formed collagen-based matrix presented here is non-toxic to cells and controls the proliferation in the corneal fibroblasts seeded onto it. Histology and biomolecular studies show a behavior similar to corneal s...

In this paper, following a two-stage methodology, the differential quadrature element (DQE) model of a three-story frame structure is updated for the vibration analysis. In the first stage, the mass and stiffness matrices are updated using the experimental natural frequencies. Then, having the updated mass and stiffness matrices, the structural damping matrix is updated to minimize the error be...

This work present and demonstrated an applications of artificial neural network approach in optical sensing. The conventional matrix method used in simultaneous measurement of strain and temperature with optical Bragg gratings is compared with artificial neural network approach. The alternative method is proposed for reduced the error.

Compressive sensing takes advantage of the signals in some domain, allowing the entire signal to efficiently acquired and reconstructed from relatively few measurements. Toeplitz matrix has more advantages in the amount of data and computation over Gaussian random matrix, but its far from Gaussian matrix in the performance of signal reconstruction. In this paper, Toeplitz matrix is employed and...

ing symbolic matrices Special issue on artificial intelligence and symbolic computation Randa Almomen · Alan P. Sexton · Volker Sorge © Springer Science+Business Media B.V. 2012 Abstract We present a procedure that allows the abstraction of elements in concrete symbolic matrices to obtain a more compact representation employing ellipses in order to expose homogeneous regions present in a matrix...