Prediction performance of various numerical model training algorithms in solidification process of A356 matrix composites

129-134This paper reports the microstructural and mechanical properties of casting Al matrix composite such as porosity, hardness and tensile strength. The numerical model and finite element method are applied to simulate the solidification of the composites. The finite element analysis involves a number of steps such as finite-element discretization, imposition of boundary conditions and solution of assembled equations. The mathematical formulation of this solidification problem is given. The neural network predictions are directly compared with the experimentally obtained data to evaluate the learning performance. In this investigation the MAPE is used to evaluate the performance of model. The results show that Levenberg-Marquardt learning algorithm give the best prediction for UTS, hardness and porosity of A356 composite reinforced with B4C particulates

Multifocal electroretinogram in diabetic macular edema; Correlation with visual acuity and optical coherence tomography

Purpose: To evaluate multifocal electroretinogram (mfERG) changes in eyes with diabetic macular edema (DME) and investigate any possible correlation with optical coherence tomography (OCT) features and visual acuity (VA). Methods: Twenty-nine right eyes of 29 subjects with DME due to non-proliferative diabetic retinopathy and 30 eyes of 30 normal subjects were evaluated. All patients underwent a complete ophthalmic examination. Sixty-one scaled hexagon mfERG responses were recorded. Components of thefirst order kernel of N1, N2, and P1 in five concentric rings centered on the fovea, were measured in both groups. Correlation and regression analyses were performed among VA, central macular thickness (CMT) based on OCT, mfERG amplitude, and latency of the N1, N2 and P1 waves. Results: Significant differences were observed in all mfERG parameters in five-ring regions of the retina between eyes with DME versus controls (P < 0.05). There were significant correlations among VA with N2 (P = 0,001, b = 0.73) and P1 amplitudes (P = 0.001, b = −0.84) in the central macular area, and there was a borderline association between VA and CMT (P = 0.042, b = 0.392). Conclusion: Amplitudes of mfERG components (N1, P1, and N2) are significantly reduced and their latencies are delayed in eyes with DME indicating functional impairment in the outer retina. The mfERG total amplitude was significantly correlated with VA even more than CMT, therefore the combined use of OCT and mfERG for macular evaluation may better evaluate visual status in DME patients