Следене
Nicholas Watson
Nicholas Watson
Professor of Artificial Intelligence in Food, University of Leeds
Потвърден имейл адрес: leeds.ac.uk
Заглавие
Позовавания
Позовавания
Година
Cloud manufacturing as a sustainable process manufacturing route
O Fisher, N Watson, L Porcu, D Bacon, M Rigley, RL Gomes
Journal of manufacturing systems 47, 53-68, 2018
3352018
Effect of solvent composition and its interaction with ultrasonic energy on the ultrasound-assisted extraction of phenolic compounds from Mango peels (Mangifera indica L.)
T Martínez-Ramos, J Benedito-Fort, NJ Watson, II Ruiz-López, ...
Food and Bioproducts Processing 122, 41-54, 2020
1212020
A review of in-line and on-line measurement techniques to monitor industrial mixing processes
AL Bowler, S Bakalis, NJ Watson
Chemical Engineering Research and Design 153, 463-495, 2020
1122020
Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems
OJ Fisher, NJ Watson, JE Escrig, R Witt, L Porcu, D Bacon, M Rigley, ...
Computers & Chemical Engineering 140, 106881, 2020
1062020
Thin film thickness measurements in two phase annular flows using ultrasonic pulse echo techniques
YA Al-Aufia, BN Hewakandamby, G Dimitrakis, M Holmes, A Hasan, ...
Flow measurment and Instrumentation 66, 67-78, 2019
702019
Energy management for a net zero dairy supply chain under climate change
MI Malliaroudaki, NJ Watson, R Ferrari, LN Nchari, RL Gomes
Trends in Food Science & Technology 126, 153-167, 2022
662022
Monitoring mixing processes using ultrasonic sensors and machine learning
AL Bowler, S Bakalis, NJ Watson
Sensors 20 (7), 1813, 2020
522020
A review of ultrasonic sensing and machine learning methods to monitor industrial processes
AL Bowler, MP Pound, NJ Watson
Ultrasonics 124, 106776, 2022
512022
Advances in the ultrasound characterization of dry-cured meat products
E Corona, JV Garcia-Perez, TEG Alvarez-Arenas, N Watson, MJW Povey, ...
Journal of Food Engineering 119 (3), 464-470, 2013
492013
The effect of light intensity, sensor height, and spectral pre-processing methods when using NIR spectroscopy to identify different allergen-containing powdered foods
A Rady, J Fischer, S Reeves, B Logan, N James Watson
Sensors 20 (1), 230, 2019
452019
Near-infrared spectroscopy and machine learning for classification of food powders during a continuous process
S Ozturk, A Bowler, A Rady, NJ Watson
Journal of Food Engineering 341, 111339, 2023
442023
Near-infrared spectroscopy and hyperspectral imaging for sugar content evaluation in potatoes over multiple growing seasons
AM Rady, DE Guyer, NJ Watson
Food Analytical Methods 14, 581-595, 2021
382021
Clean-in-place monitoring of different food fouling materials using ultrasonic measurements
J Escrig, E Woolley, S Rangappa, A Simeone, NJ Watson
Food Control 104, 358-366, 2019
372019
A multi-sensor approach for fouling level assessment in clean-in-place processes
A Simeone, N Watson, I Sterritt, E Woolley
Procedia Cirp 55, 134-139, 2016
312016
Intelligent sensors for sustainable food and drink manufacturing
NJ Watson, AL Bowler, A Rady, OJ Fisher, A Simeone, J Escrig, ...
Frontiers in Sustainable Food Systems 5, 642786, 2021
302021
Monitoring the cleaning of food fouling in pipes using ultrasonic measurements and machine learning
J Escrig, E Woolley, A Simeone, NJ Watson
Food Control 116, 107309, 2020
292020
Ultrasonic measurements and machine learning for monitoring the removal of surface fouling during clean-in-place processes
JE Escrig, A Simeone, E Woolley, S Rangappa, A Rady, NJ Watson
Food and bioproducts processing 123, 1-13, 2020
262020
Intelligent industrial cleaning: A multi sensor approach utilising machine learning-based regression
A Simeone, E Woolley, J Escrig, NJ Watson
Loughborough University, 2020
262020
Intelligent resource use to deliver waste valorisation and process resilience in manufacturing environments: Moving towards sustainable process manufacturing
OJ Fisher, NJ Watson, JE Escrig, RL Gomes
Johnson Matthey Technology Review 64 (1), 93-99, 2020
252020
Enhanced clean-in-place monitoring using ultraviolet induced fluorescence and neural networks
A Simeone, B Deng, N Watson, E Woolley
Sensors 18 (11), 3742, 2018
252018
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