Denoising Vanilla Autoencoder for RGB and GS Images with Gaussian Noise.

Noise suppression algorithms have been used in various tasks such as computer vision, industrial inspection, and video surveillance, among others. The robust image processing systems need to be fed with images closer to a real scene; however, sometimes, due to external factors, the data that represent the image captured are altered, which is translated into a loss of information. In this way, there are required procedures to recover data information closest to the real scene. This research project proposes a Denoising Vanilla Autoencoding (DVA) architecture by means of unsupervised neural networks for Gaussian denoising in color and grayscale images. The methodology improves other state-of-the-art architectures by means of objective numerical results. Additionally, a validation set and a high-resolution noisy image set are used, which reveal that our proposal outperforms other types of neural networks responsible for suppressing noise in images.

Numerical Analysis of Zirconium and Titanium Implants under the Effect of Critical Masticatory Load.

Dental implants have become an alternative to replace the teeth of people suffering from edentulous and meet the physiological and morphological characteristics (recovering 95% of the chewing function). The evolution and innovation of biomaterials for dental implants have had a trajectory that dates back to prehistory, where dental pieces were replaced by ivory or seashells, to the present day, where they are replaced by metallic materials such as titanium or ceramics such as zirconium or fiberglass. The numerical evaluation focuses on comparing the stress distribution and general displacement between different dental implants and a healthy tooth when applying a force of 850 N. For the analysis, a model of the anatomical structure was developed of a healthy tooth considering three essential parts of the tooth (enamel, dentin, and pulp). The tooth biomodel was established through computed tomography. Three dental implant models were considered by changing the geometry of the abutment. A structural simulation was carried out by applying the finite element method (FEM). In addition, the material considered for the analyses was zirconium oxide (ZrO2), which was compared against titanium alloy (Ti6Al4V). The analyses were considered with linear, isotropic, and homogeneous properties. The variables included in the biomodeling were the modulus of elasticity, Poisson's ratio, density, and elastic limit. The results obtained from the study indicated a significant difference in the biomechanical behavior of the von Mises forces and the displacement between the healthy tooth and the titanium and zirconium implant models. However, the difference between the titanium implant and the zirconium implant is minimal because one is more rigid, and the other is more tenacious.