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This work develops a novel approach based on Machine Learning (ML)-assisted Quality Function Deployment (QFD) to sift the gold from the stone. It includes Time-Varying Filter-based Empirical Mode Decomposition (TVF-EMD), Deep Ensemble Random Vector Functional Link (DE-RVFL), and a Bayesian optimization algorithm for optimizing the shaped DE-RVFLTVF-EMD hyperparameters. This approach makes it possible for the proposed methods to be dynamic enough to deal with the data's volatility, complexity, uncertainty, and ambiguity. It is demonstrated that incorporating TVF-EMD to provide time-frequen...

This study examines the frequency, type and severity of interference events at specific locations in the country, providing valuable insights into the use of detectors, the nature of interference encountered, their potential sources and the impact on GNSS-derived positions.  NURAG RAGHUVANSHI, SUNIL

Aston University scientists have discovered a more accurate way of checking the blood flow in the feet of patients with type 2 diabetes.

Abstract Self-mixing interferometry (SMI) is a promising non-contact sensing technology, which has attracted much research attention in the last few decades. The SMI effect takes place when a small portion of laser is back-scattered from an external target and re-enters the laser diode (LD) internal cavity. A typical sensing system using an SMI configuration consists of an LD as the laser source, a target to reflect the laser, a photo diode (PD) to capture the optical signal. This configuration indicates the SMI-based sensing technology’s merits of minimum part-count scheme, low cost in imp...