Developing accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …

Raman spectroscopy is increasingly being used in biology, forensics, diagnostics,
pharmaceutics and food science applications. This growth is triggered not only by …

Here, we present an improved water quality index (WQI) model for assessment of coastal
water quality using Cork Harbour, Ireland, as the case study. The model involves the usual …

Abstract Machine learning models have been shown to be useful for predicting and
assessing structural performance, identifying structural condition and informing preemptive …

Accurate assessment of undrained shear strength (USS) for soft sensitive clays is a great
concern in geotechnical engineering practice. This study applies novel data-driven extreme …

We show that a variety of modern deep learning tasks exhibit a'double-
descent'phenomenon where, as we increase model size, performance first gets worse and …

The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD)
are not well understood. Using a large neuroimaging dataset, we identified three latent …

Human Activity Recognition (HAR) employing inertial motion data has gained considerable
momentum in recent years, both in research and industrial applications. From the abstract …

Developing algorithmic approaches for the rational design and discovery of materials can
enable us to systematically find novel materials, which can have huge technological and …

Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …