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"An intelligent decision support system for warranty claims forecasting" by Ali Nikseresht, Sajjad Shokouhyar et al.

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, complexit...
Machine Learning Quality Function Deployment Deep Ensemble Random Vector Functional Link Root Mean Square Error Deep Learning Quality Function Deployment
Source: uow.edu.au

Analyzing GNSS Radio Frequency Interference Events in Canada - Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design

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
British Columbia Anurag Raghuvanshi Broadsense Datasets Sunil Bisnath Spirent Datasets Jason Bond

"Micro-displacement and Profile Measurement Using a Selfmixing Interfer" by Han Wang

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...
Fast Fourier Transform Self Mixing Interferometry Semiconductor Laser Diode Micro Displacement Sensing Profile Measurement Time Frequency Analysis
Source: uow.edu.au

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