Hypertension prediction in adolescents using anthropometric measurements: do machine learning models perform equally well?

SS Chai, KL Goh, WL Cheah, YHR Chang, GW Ng - Applied Sciences, 2022 - mdpi.com
The use of anthropometric measurements in machine learning algorithms for hypertension
prediction enables the development of simple, non-invasive prediction models. However …

Surface roughness analysis: A comprehensive review of measurement techniques, methodologies, and modeling

K Sushil, J Ramkumar… - Journal of …, 2025 - journals.sagepub.com
The scale and value of surface roughness affect the wetting, fatigue, dam**, emissivity,
heat transfer, and aesthetic characteristics leading to applications in food, chemical …

Exploring the impact of feature data normalization and standardization on regression models for smartphone price prediction

M Bonamutial, SY Prasetyo - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Smartphone has become a necessity and the most accessible for every individual and is
mainly used for communication. Smartphone price is higher than the previous years …

[HTML][HTML] Comparison of Data Fusion Methods in Fusing Satellite Products and Model Simulations for Estimating Soil Moisture on Semi-Arid Grasslands

Y Zhu, L Zhang, F Li, J Xu, C He - Remote Sensing, 2023 - mdpi.com
In arid and semi-arid areas, soil moisture (SM) plays a crucial role in land-atmosphere
interactions, hydrological processes, and ecosystem sustainability. SM data at large scales …

Bidirectional long short-term memory-based empirical wavelet transform: A new hybrid artificial intelligence model for robust prediction of soil moisture content

S Heddam, S Kim, A Elbeltagi, O Kisi - Current Directions in Water Scarcity …, 2022 - Elsevier
This study uses the empirical wavelet transform (EWT) for improving the estimation of soil
moisture. We used the bidirectional long short-term memory (BiLSTM), the support vector …