Data Science & Engineering into Food Science: A novel Big Data Platform for Low Molecular Weight Gelators’ Behavioral Analysis

Data Science & Engineering into Food Science: A novel Big Data Platform for Low Molecular Weight Gelators’ Behavioral Analysis

The objective of this article is to introduce a comprehensive end-to-end solution aimed at enabling the application of state-of-the-art Data Science and Analytic methodologies to a food science related problem. The problem refers to the automation of load, homogenization, complex processing and real...

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Bibliographic Details
Main Authors: Verónica Cuello, Gonzalo Zarza, Maria Corradini, Michael Rogers
Format: Article
Language:English
Published: Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2020-10-01
Series:Journal of Computer Science and Technology
Subjects:
big data
data science
food science
coloidal science
low molecular weight gelators
self assembly
Online Access:https://journal.info.unlp.edu.ar/JCST/article/view/1435

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