Browsing Technology Innovation and Engineering Education Unit by Publisher "Elsevier"
Now showing items 1-6 of 6
-
Deep learning techniques for liver and liver tumor segmentation: A review
( Elsevier , 2022 , Article)Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the medical image processing domain for the last few decades. The existence of other organs such as the heart, spleen, stomach, ... -
Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection
( Elsevier , 2024 , Article)Zinc oxide (ZnO) nanocomposite sensors decorated with various dopants are popular tools for detecting even low hydrogen (H2) concentrations. The nanocomposite's chemistry, temperature, and H2 concentration impact the success ... -
Modeling of permeability impairment dynamics in porous media: A machine learning approach
( Elsevier , 2023 , Article)The prediction of clogging and permeability impairment dynamics in porous media is crucial for the optimization of various industrial and natural processes. This paper presents a novel machine learning-based approach for ... -
Novel and robust machine learning approach for estimating the fouling factor in heat exchangers
( Elsevier , 2022 , Article)The fouling factor (Rf) is an operating index for measuring an undesirable effect of solids’ deposition on the heat transfer ability of heat exchangers. Accurate prediction of the fouling factor helps appropriate scheduling ... -
Perspectives on food waste management: Prevention and social innovations
( Elsevier , 2022 , Article Review)Food waste is one of the challenging issues humans are facing. A third of the food produced in the world is wasted at various points along the food supply chain. Food waste can be reduced by developing technology that can ... -
A time–frequency based approach for generalized phase synchrony assessment in nonstationary multivariate signals
( Elsevier , 2013 , Article)This paper proposes a new approach to estimate the phase synchrony among nonstationary multivariate signals using the linear relationships between their instantaneous frequency (IF) laws. For cases where nonstationary ...
