The nonlinear regression estimation issues are solved by successful application of a novel
neural network technique termed as support vector machines (SVMs). Evaluation of …

The existing machine-vision surface roughness measurement technique extracts relevant
evaluation indices from grayscale images without using the strong sensitivity of color …

Color image indices used to characterize surface roughness are more sensitive than
grayscale images or spectral indices owing to the rich information contained in color images …

Prediction of the chronological age based on neuroimaging data is important for brain
development analysis and brain disease diagnosis. Although many researches have been …

This study develops explainable machine learning (ML) models to predict the ultimate
bending capacity of cold-formed steel (CFS) beams with staggered slotted perforations …

Non-stationarity due to climate change and/or variability can reduce the capabilities of
drought prediction models. The objective of this study is to improve drought prediction by …

Surface roughness is one of the key characteristics of machined components as it affects the
surface quality and, consequently, the lifetime of the components themselves. The most …

In this research, an efficient thermal-stress coupling design method for a Chiplet-based
system with a coaxial through silicon via (CTSV) array is developed by combining the …

We generalize a support vector machine to a support spinor machine by using the
mathematical structure of wedge product over vector machine in order to extend field from …

Non-stationary systems are found throughout the world, from climate patterns under the
influence of variation in carbon dioxide concentration to brain dynamics driven by ascending …