Category: 7. Maths

This section provides a detailed description of the datasets utilized to evaluate the proposed method’s performance, specifying the metrics employed to assess its effectiveness and showcasing the results obtained from the implemented approach.

To validate the presented approach, all stages were developed and simulated in MATLAB. This simulation displays the results of an emotion recognition algorithm applied to the speaker’s speech. It also enables the comparison of these results to…

3D jumper models

To conduct aerodynamic simulations, a three-dimensional geometric model of the athlete–ski system during the straight-line descent of the in-run phase was established. The model was constructed using anthropometric data obtained…

In this section, we revisit the work of Herrmann et al.⁷, which focuses on maximizing small root bounds for RSA with a small secret exponent. In their approach, they introduced a novel technique known as the method of unravelled linearization….

The mesoscopic scale is the state between macroscopic and microscopic, and its scale is generally between micrometers and millimeters. It has been shown that the RFC mesoscale range is in the millimeter level^2,22,23. This section introduces a 3D…

M.C. Escher’s artwork is a gateway into a world of depth-defying optical illusions, featuring “impossible objects” that break the laws of physics with convoluted geometries. What you perceive his illustrations to be…

The numerical investigation of nonlinear irreversible biochemical reaction (NIBR) model is carried out using an advanced computational numerical solver called intelligent backpropagated by the Levenberg–Marquardt artificial neural networks…

CN to MCI progression

As we mentioned in the proposed method, the first phase of the proposed method is MCI progression prediction. In this phase, MRI images of the baseline as well as Demographic features (including Age, Gender, Marital Status,…

Theory

A recurrent neural net is a general term for any neural net designed to analyze sequences or streams of data, one element at a time. The Elman Recurrent Neural Network¹¹, henceforward abbreviated as RNN, is a particularly simple design,…

Overview

In this work, we leverage inverse rendering and generative object priors to infer and track 3D multi-object scenes by jointly optimizing object pose, geometry and appearance. Our approach focuses on scenarios where an accurate scene…