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Results: 26
Short- and long-term predictions of chaotic flows and extreme events
NAK Doan, W Polifke, L Magri
Sep 01, 2021
We propose a physics-constrained machine learning method-based on reservoir computing-to time-accurately predict extreme events and long-term velocity statistics in a model of chaotic flow. The method leverages the strengths of...
Published by:
Large-Scale Software-Defined IoT Platform for Provisioning IoT Services on Demand
Internet of things (IoT) has developed into an interconnected platform infrastructure for providing everyday services. Emerging end-to-end IoT services are being developed for local and multiple distributed regions. To realize...
Membrane fouling remediation in ultrafiltration of latex contaminated water and wastewater
The goal of the present study was to remediate membrane fouling of latex effluent by altering the membrane surface charge or the ionic strength of simulated latex effluent either through the pH change or using anionic...
Membrane fouling remediation in ultrafiltration of latex contaminated water and wastewater
The goal of the present study was to remediate membrane fouling of latex effluent by altering the membrane surface charge or the ionic strength of simulated latex effluent either through the pH change or using anionic...
Filtered Reaction Rate Modelling in Moderate and High Karlovitz Number Flames
Abstract: Direct numerical simulations (DNS) of statistically planar flames at moderate and high Karlovitz number (Ka) have been used to perform an a priori evaluation of a presumed-PDF model approach for filtered reaction rate...
Published by: Springer Netherlands
A comparison study of dental pulp stem cells derived from healthy and orthodontically intruded human permanent teeth for mesenchymal stem cell characterisation.
The objective of this study was to compare the characteristics of Dental Pulp Stem Cells (DPSCs) derived from healthy human permanent teeth with those that were orthodontically-intruded to serve as potential Mesenchymal Stem...
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Constrained Density Peak Clustering
Clustering is a commonly used tool for discovering knowledge in data mining. Density peak clustering (DPC) has recently gained attention for its ability to detect clusters with various shapes and noise, using just one parameter....

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