A neural network system for control of pH

J.S. Torrecilla , J.M. Aragon , M.C. Palancar
American Institute of Chemical Engineers, New York, NY (United States)

1996
Extraction Methods of Biophenols

F. Rodriguez , M. Gonzalez-Miquel , J.S. Torrecilla , Maria Gonzalez Miquel
In: Torrecilla, J.S, editor(s). The Role of Ionic Liquids in the Chemical Industry. Nova Science Publishers ; 2012..

2012
Comparative Evaluation of [imidazolium][tf2n] and [pyridinium][tf2n] Ionic Liquids for the Liquid-liquid Extraction of Aromatics

F. Rodriguez , J. Garcia , M. Larriba , J.S. Torrecilla
Chemical engineering transactions 24 805 -810

5
2011
SYNERGISTIC LIQUID-LIQUID EXTRACTION OF TOLUENE FROM HEPTANE WITH MIXTURES OF [bmim]BF4 AND [omim]BF4 IONIC LIQUIDS

F. Rodriguez , J. Garcia , J.S. Torrecilla , S. Garcia
Chemical engineering transactions 17 1579 -1584

2009
Artificial neural networks : a promising tool to design and optimize high-pressure food processes

J.S. Torrecilla , L. Otero , P.D. Sanz
Journal of Food Engineering 69 ( 3) 299 -306

82
2005
Optimization of an artificial neural network for thermal/pressure food processing: Evaluation of training algorithms

J.S. Torrecilla , L. Otero , P.D. Sanz
Computers and Electronics in Agriculture 56 ( 2) 101 -110

36
2007
A neural network approach for thermal/pressure food processing

J.S Torrecilla , L Otero , P.D Sanz
Journal of Food Engineering 62 ( 1) 89 -95

153
2004
Modelling of High-Pressure Treatments of Foods by an Artificial Neural Network

Bérengère Guignon , Laura Otero , A. Ramos , J. S. Torrecilla
Process Engineering Publisher

2006
The Initial Freezing Temperature of Foods at High Pressure

B. Guignon , J. S. Torrecilla , L. Otero , A. M. Ramos
Critical Reviews in Food Science and Nutrition 48 ( 4) 328 -340

15
2008
A quantum-chemical-based guide to analyze/quantify the cytotoxicity of ionic liquids

J. S. Torrecilla , J. Palomar , J. Lemus , F. Rodríguez
Green Chemistry 12 ( 1) 123 -134

95
2010
Application of artificial neural networks as a tool for moisture prediction in microbially colonized halite in the Atacama Desert

K. Wierzchos , J. C. Cancilla , J. S. Torrecilla , P. Díaz-Rodríguez
Journal of Geophysical Research 120 ( 6) 1018 -1026

1
2015
Solving the spectroscopy interference effects of β-carotene and lycopene by neural networks

José S Torrecilla , Montaña Cámara , Virginia Fernández-Ruiz , Guiomar Piera
Journal of agricultural and food chemistry 56 ( 15) 6261 -6266

27
2008
Rebuttal to “Comments on “Boiling Points of Ternary Azeotropic Mixtures Modeled with the Use of the Universal Solvation Equation and Neural Networks’”

Alexander A Oliferenko , Polina V Oliferenko , José S Torrecilla , Alan R Katritzky
Industrial & Engineering Chemistry Research 52 ( 1) 545 -546

10
2013
o 11A? Artificial neural networks in the determination of different types of cancer

John C Cancilla , Kacper Wierzchoś , Nisreen Shehadeh , Hossam Haick

1
2015
Artificial Neural Networks Aiding in Breath-Based Early Cancer Diagnosis

John C Cancilla , Inese Polaka , Arnis Kirsners , Hossam Haick

Phenolic compounds in olive oil mill wastewater

José S Torrecilla , John C Cancilla
Academic Press 693 -700

24
2021
Is my food safe?–AI-based classification of lentil flour samples with trace levels of gluten or nuts

Sandra Pradana-López , Ana M Pérez-Calabuig , Laura Otero , John C Cancilla
Food Chemistry 386 132832 -132832

10
2022
Convolutional capture of the expansion of extra virgin olive oil droplets to quantify adulteration

Sandra Pradana-Lopez , Ana M Perez-Calabuig , John C Cancilla , Yolanda Garcia-Rodriguez
Food Chemistry 368 130765 -130765

8
2022
Deep quantification of a refined adulterant blended into pure avocado oil

Ana M Pérez-Calabuig , Sandra Pradana-López , Andrea Ramayo-Muñoz , John C Cancilla
Food Chemistry 404 134474 -134474

5
2023
Distinct thermal patterns to detect and quantify trace levels of wheat flour mixed into ground chickpeas

John C Cancilla , Sandra Pradana-López , Ana M Pérez-Calabuig , Sandra López-Ortega
Food Chemistry 384 132468 -132468

4
2022