Browsing by Subject "ARTIFICIAL NEURAL NETWORKS"
Now showing items 1-8 of 8
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3D deformation and strain fields in drying kaolinite obtained from tracking internal bubbles using X-ray CT and ANN
(2024)Drying fine-grained sediments experience shrinkage and desiccation cracking that may dramatically alter their mechanical and hydraulic properties. This study adopts X-ray computed tomography (CT) to monitor the three-dimensional ... -
ANN-based bubble tracking algorithm for clay slurries containing large gas bubbles using X-ray CT
(Civil Engineering Research Association of Ireland, 2022)Gassy clay is a widely-distributed natural composite material consisting of a saturated clay matrix incorporating large gas bubbles. This study aims to develop a novel method to non-destructively monitor the strain field ... -
A GIS model for personal exposure to PM10 for Dublin commuters
(Trinity College Dublin, 2012)The project has focused on a number of scientific issues in the development of the GIS air quality model for the Dublin Area and its Satellite Towns . Firstly, how to model air quality by integrating existing and ... -
IMEC: A Memory-Efficient Convolution Algorithm For Quantised Neural Network Accelerators
(IEEE, 2022)Quantised convolution neural networks (QCNNs) on FPGAs have shown tremendous potential for deploying deep learning on resource constrained devices closer to the data source or in embedded applications. An essential building ... -
A Lightweight FPGA-based IDS-ECU Architecture for Automotive CAN
(IEEE, 2022)Recent years have seen an exponential rise in complex software-driven functionality in vehicles, leading to a rising number of electronic control units (ECUs), network capabilities, and interfaces. These expanded ... -
Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation
(2024)This paper proposes the use of Artificial Neural Networks (ANNs), specifically Physics-Informed Neural Networks (PINNs), for dynamic surrogate modelling of wind turbines. PINNs offer the flexibility to model complex ... -
Prediction of indoor air exposure from outdoor air quality using an artificial neural network model for inner city commercial buildings
(2015)NO 2 and particulate matter are the air pollutants of most concern in Ireland , with possible links to the high er respiratory and cardiovascular mortality and morbidity rates found in the ... -
Reverse extrusion test for fine-grained soil characterisation: internal flow pattern with ANN-enhanced particle tracking
(2023)The reverse extrusion test involves one-dimensionally (1D) compressing a fine-grained soil sample contained in a cup container of cross-sectional area A. The force Fe applied by the loading platen causes extrusion of the ...