A modified genetic algorithm (MGA) optimization procedure, alongside time series machine learning (ML) classifiers, is proposed to minimize handovers in a digital twin-based visible light communication (VLC) system. Frequent handovers have a direct impact on the overall performance of the VLC system …

Objective: To evaluate psychometrics of wearable devices measuring physical activity (PA) in ambulant children with gait abnormalities due to neuromuscular conditions.  Data Sources: We searched PubMed, Embase, PsycINFO, CINAHL, and SPORTDiscus in March 2023.  Study Selection: We included studies if …

Knowledge on the biodiversity and abundance of phytoplankton is key for many ecological and societal (e.g., blue growth) questions. Gathering temporal variation and spatial patterns on key indicators requires reliable and standardized protocols on sampling, species identification and counting. Numerous …

RTK-GNSS (Real Time Kinematic - Global Navigation Satellite System) is based on a ‘rover’ GNSS antenna that receives error correction information from a ‘base’ GNSS antenna. While the rover can be placed on a robot to move around, the base station has the additional ‘knowledge’ of being stationary. …

This study presents a methodology designed to optimize various parameters of each access point within a Multiple-Input Single-Output (MISO) Visible Light Communication (VLC) system. The primary objective is to enhance both power and spectral efficiencies. A MISO-VLC model is presented based on experimental …

Designing lead-free piezoelectric ceramics with tailored electrical properties remains a critical challenge for various applications. In this paper we present a novel methodology integrating Machine Learning (ML) and optimization procedures to fine-tune electrical properties in lead-free (1-x) Na0.5 …

Purpose This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations …

Accurate assessment of rolling resistance is important for wheelchair propulsion analyses. However, the commonly used drag and deceleration tests are reported to underestimate rolling resistance up to 6% due to the (neglected) influence of trunk motion. The first aim of this study was to investigate …

This study proposes a novel loss function for neural network models that explores the topological structure of stock realized volatility (RV) data by adding Wasserstein Distance (WD). The study shows that the proposed loss statistically significantly improves the forecast accuracy of neural network models …