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Release modelling of nanoencapsulated food ingredients by probabilistic models: cellular automata and Monte Carlo methods

Bezbradica, Marija ORCID: 0000-0001-9366-5113, Crane, Martin ORCID: 0000-0001-7598-3126 and Ruskin, Heather J. (2020) Release modelling of nanoencapsulated food ingredients by probabilistic models: cellular automata and Monte Carlo methods. In: Jafari, Seid ORCID: 0000-0001-6877-9549, (ed.) Nanoencapsulation in the Food Industry. Academic Press, Cambridge, Massachusetts, pp. 273-309. ISBN 9780128156667

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Abstract

Probabilistic modeling methods have found increasing importance in recent years, driven by concurrent growth in computing power with applications in the modeling of many fields of science, engineering, and medicine. This has been due not just to method scope and flexibility, but also in no small part to advance in computing capacity and interconnection speed and commensurate decreases in the costs of these. In this chapter, we review the literature on probabilistic methods with their different and varied forms, and describe the theory of the methods, together with practical applications in the fields of drug delivery systems in the pharmaceutical industry and nanoencapsulation within the food industry.

Item Type:Book Section
Refereed:Yes
Uncontrolled Keywords:Probabilistic models; Monte Carlo simulation; Cellular automata models; Agent-based models
Subjects:Computer Science > Computer simulation
Mathematics > Mathematical models
Mathematics > Stochastic analysis
Mathematics > Statistics
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Academic Press
Official URL:https://www.sciencedirect.com/science/article/pii/B9780128156650000084
Copyright Information:© 2020 Academic Press
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:26158
Deposited On:06 Sep 2021 14:27 by Marija Bezbradica . Last Modified 02 Dec 2021 04:30

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