Abstract Characterization of surface wettability plays an integral role in physical, chemical,
and biological processes. However, the conventional fitting algorithms are not suitable for …

Feature selection (FS) may improve the performance, cost-efficiency, and understandability
of supervised machine learning models. In this paper, FS for the recently introduced …

Since the outbreak of the COVID-19 pandemic, computer vision researchers have been
working on automatic identification of this disease using radiological images. The results …

Bearing fault diagnosis is vital for ensuring reliability and safety of high-speed trains and
wind turbines. Therefore, a minimum unscented Kalman filter-aided deep belief network is …

Fiber-reinforced nano-silica concrete (FrRNSC) was applied to a concrete sculpture to
address the issue of brittle fracture, and the primary objective of this study was to explore the …

Evolutionary algorithms (EAs) have shown their competitiveness in solving the problem of
feature selection (FS). However, in most of the existing EA-based FS methods, one bit in the …

Feature selection (FS) can increase the accuracy of forest aboveground biomass (AGB)
prediction from multiple satellite data and identify important predictors, but the role of FS in …

This paper proposes a novel framework for simulating the dynamics of beams on elastic
foundations. Specifically, partial differential equations modeling Euler–Bernoulli and …

Building-damage mapping using remote sensing images plays a critical role in providing
quick and accurate information for the first responders after major earthquakes. In recent …

Most pavement crack detection methods based on deep learning rely too much on pixel-
wise labels, and are facing with sample imbalance problem. This paper proposes a three …