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Number of items: 47.
Article
Adame-Siles, JA;
Fearn, T;
Guerrero-Ginel, JE;
Garrido-Varo, A;
Maroto-Molina, F;
Perez-Marin, D;
(2016)
Near-infrared spectroscopy and geostatistical analysis for modeling spatial distribution of analytical constituents in bulk animal by-product protein meals.
Applied Spectroscopy
, 71
pp. 520-532.
10.1177/0003702816683958.
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Adame-Siles, JA;
Guerrero-Ginel, JE;
Fearn, T;
Garrido-Varo, A;
Pérez-Marín, D;
(2020)
Performance comparison of sampling designs for quality and safety control of raw materials in bulk: a simulation study based on NIR spectral data and geostatistical analysis.
Chemometrics and Intelligent Laboratory Systems
, 198
, Article 103940. 10.1016/j.chemolab.2020.103940.
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Adame-Siles, JA;
Guerrero-Ginel, JE;
Fearn, T;
Garrido-Varo, A;
Pérez-Marín, D;
(2019)
Multistage and adaptive sampling protocols combined with near-infrared spectral sensors for automated monitoring of raw materials in bulk.
Biosystems Engineering
, 188
pp. 82-95.
10.1016/j.biosystemseng.2019.10.008.
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Allen, JL;
Sandberg, S;
Chhoa, C;
Fearn, T;
Rapee, R;
(2017)
Parent-Dependent Stressors and the Onset of Anxiety Disorders in Children: Links with Parental Psychopathology.
European Child and Adolescent Psychiatry
pp. 1-11.
10.1007/s00787-017-1038-3.
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Au, J;
Youngentob, KN;
Foley, WJ;
Moore, BD;
Fearn, T;
(2020)
Sample selection, calibration and validation of models developed from a large dataset of near infrared spectra of tree leaves.
Journal of Near Infrared Spectroscopy
, 28
(4)
pp. 186-203.
10.1177/0967033520902536.
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Brown, N;
Lichtblau, D;
Fearn, T;
Strlic, M;
(2017)
Characterisation of 19th and 20th century Chinese paper.
Heritage Science
, 5
, Article 47. 10.1186/s40494-017-0158-x.
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Chisholm, S;
Stein, AB;
Jordan, NR;
Hubel, TM;
Shawe-Taylor, J;
Fearn, T;
McNutt, JW;
... Hailes, S; + view all
(2019)
Parsimonious test of dynamic interaction.
Ecology and Evolution
, 9
(4)
pp. 1654-1664.
10.1002/ece3.4805.
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Cui, Chenhao;
Caporaso, Nicola;
Chen, Jiawei;
Fearn, Tom;
(2023)
Farinograph characteristics of wheat flour predicted by near infrared spectroscopy with an ensemble modelling method.
Journal of Food Engineering
, 359
, Article 111689. 10.1016/j.jfoodeng.2023.111689.
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Cui, C;
Fearn, T;
(2018)
Modern practical convolutional neural networks for multivariate regression: Applications to NIR calibration.
Chemometrics and Intelligent Laboratory Systems
, 182
pp. 9-20.
10.1016/j.chemolab.2018.07.008.
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Cui, C;
Fearn, T;
(2018)
Hierarchical mixture of linear regressions for multivariate spectroscopic calibration: An application for NIR calibration.
Chemometrics and Intelligent Laboratory Systems
, 174
pp. 1-14.
10.1016/j.chemolab.2017.12.013.
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Cui, C;
Fearn, T;
(2017)
Comparison of partial least squares regression, least squares support vector machines, and Gaussian process regression for a near infrared calibration.
Journal of Near Infrared Spectroscopy
, 25
(1)
pp. 5-14.
10.1177/0967033516678515.
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Curran, K;
Underhill, M;
Grau-Bove, J;
Fearn, T;
Gibson, LT;
Strlic, M;
(2018)
Classifying degraded modern polymeric museum artefacts by their smell.
Angewandte Chemie
10.1002/anie.201712278.
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Curran, K;
Underhill, M;
Strlič, M;
Možir, A;
Gibson, LT;
Fearn, T;
(2014)
Cross-infection effect of polymers of historic and heritage significance on the degradation of a cellulose reference test material.
Polymer Degradation and Stability
, 107
pp. 294-306.
10.1016/j.polymdegradstab.2013.12.019.
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Drakos, I;
Kenny, P;
Fearn, T;
Speller, R;
(2017)
Multivariate analysis of energy dispersive X-ray diffraction data for the detection of illicit drugs in border control.
Crime Science
, 6
, Article 1. 10.1186/s40163-016-0062-9.
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Duran-Casablancas, C;
Grau-Bové, J;
Fearn, T;
Strlič, M;
(2019)
Accumulation of wear and tear in archival and library collections. Part II: an epidemiological study.
Heritage Science
, 7
(1)
, Article 11. 10.1186/s40494-019-0253-2.
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Fearn, T;
(2024)
Testing differences in predictive ability: A tutorial.
Journal of Chemometrics
, Article e3549. 10.1002/cem.3549.
(In press).
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Fearn, T;
Pérez Marín, D;
Garrido Varo, A;
Guerrero Ginel, JE;
(2019)
Classifying with confidence using Bayes rule and kernel density estimation.
Chemometrics and Intelligent Laboratory Systems
, 189
pp. 81-87.
10.1016/j.chemolab.2019.04.0004.
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Fenech, A;
Fearn, T;
Strlic, M;
(2012)
Use of Design-of-Experiment principles to develop a dose-response function for colour photographs.
Polymer Degradation and Stability
, 97
(4)
pp. 621-625.
10.1016/j.polymdegradstab.2012.01.012.
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Fernández-Cabanás, Víctor M;
Pérez-Marín, Dolores C;
Fearn, Tom;
Gonçalves de Abreu, Joadil;
(2023)
Optimisation of the predictive ability of NIR models to estimate nutritional parameters in elephant grass through LOCAL algorithms.
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
, 285
, Article 121922. 10.1016/j.saa.2022.121922.
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Garrido-Varo, A;
Garcia-Olmo, J;
Fearn, T;
(2019)
A note on Mahalanobis and related distance measures in WinISI and The Unscrambler.
Journal of Near Infrared Spectroscopy
, 27
(4)
253 -258.
10.1177/0967033519848296.
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Kenny, PS;
Crews, C;
Fearn, T;
Speller, RD;
(2021)
Determination of ingredients in packaged pharmaceutical tablets by energy dispersive X-ray diffraction and maximum likelihood principal component analysis multivariate curve resolution-alternating least squares with correlation constraint.
Journal of Chemometrics
10.1002/cem.3329.
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Kissi, N;
Curran, K;
Vlachou-Mogire, C;
Fearn, T;
McCullough, L;
(2017)
Developing a non-invasive tool to assess the impact of oxidation on the structural integrity of historic wool in Tudor tapestries.
Heritage Science
, 5
(49)
10.1186/s40494-017-0162-1.
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Liu, Y;
Fearn, T;
Strlič, M;
(2022)
Photodegradation of iron gall ink affected by oxygen, humidity and visible radiation.
Dyes and Pigments
, 198
, Article 109947. 10.1016/j.dyepig.2021.109947.
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Liu, Y;
Fearn, T;
Strlic, M;
(2021)
Factorial experimentation on photodegradation of historical paper by polychromatic visible radiation.
Heritage Science
, 9
, Article 130. 10.1186/s40494-021-00602-4.
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Liu, Y;
Fearn, T;
Strlič, M;
(2021)
Spectral sensitivity of the discoloration of Historical rag paper.
Talanta Open
, 4
, Article 100058. 10.1016/j.talo.2021.100058.
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Liu, Y;
Fearn, T;
Strlič, M;
(2021)
Quantitative NIR spectroscopy for determination of degree of polymerisation of historical paper.
Chemometrics and Intelligent Laboratory Systems
, 214
, Article 104337. 10.1016/j.chemolab.2021.104337.
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Mahgoub, H;
Bardon, T;
Lichtblau, D;
Fearn, T;
Strlič, M;
(2016)
Material properties of Islamic paper.
Heritage Science
, 4
, Article 34. 10.1186/s40494-016-0103-4.
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Perez-Marin, D;
Calero, L;
Fearn, T;
Torres, I;
Garrido-Varo, A;
Sanchez, M-T;
(2019)
A system using in situ NIRS sensors for the detection of product failing to meet quality standards and the prediction of optimal postharvest shelf-life in the case of oranges kept in cold storage.
Postharvest Biology and Technology
, 147
pp. 48-53.
10.1016/j.postharvbio.2018.09.009.
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Pérez-Marín, D;
Fearn, T;
Riccioli, C;
De Pedro, E;
Garrido, A;
(2021)
Probabilistic classification models for the in situ authentication of iberian pig carcasses using near infrared spectroscopy.
Talanta
, 222
, Article 121511. 10.1016/j.talanta.2020.121511.
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Pinotti, L;
Ottoboni, M;
Caprarulo, V;
Giromini, C;
Gottardo, D;
Cheli, F;
Fearn, T;
(2016)
Microscopy in combination with image analysis for characterization of fishmeal material in aquafeed.
Animal Feed Science and Technology
, 215
pp. 156-164.
10.1016/j.anifeedsci.2016.02.009.
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Piotrowski, C;
Garcia, R;
Garrido-Varo, A;
Pérez-Marín, D;
Riccioli, C;
Fearn, T;
(2019)
Short Communication: The potential of portable near infrared spectroscopy for assuring quality and authenticity in the food chain, using Iberian hams as an example.
Animal
, 13
(12)
pp. 3018-3021.
10.1017/S1751731119002003.
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Rostron, Peter D;
Fearn, Tom;
Ramsey, Michael H;
(2024)
Improved coverage factors for expanded measurement uncertainty calculated from two estimated variance components.
Accreditation and Quality Assurance
10.1007/s00769-024-01579-w.
(In press).
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Rostron, Peter D;
Fearn, Tom;
Ramsey, Michael H;
(2022)
Comparing uncertainties—Are they really different?
Accreditation and Quality Assurance
, 27
pp. 133-142.
10.1007/s00769-022-01501-2.
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Rostron, Peter D;
Fearn, Tom;
Ramsey, Michael H;
(2020)
Confidence intervals for robust estimates of measurement uncertainty.
Accreditation and Quality Assurance
, 25
pp. 107-119.
10.1007/s00769-019-01417-4.
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Rostron, PD;
Fearn, T;
Ramsey, MH;
(2021)
Confidence intervals for robust estimates of measurement uncertainty (vol 25, pg 107, 2020).
Accreditation and Quality Assurance
, 26
(59)
10.1007/s00769-021-01457-9.
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Wang, G;
Fearn, T;
Wang, T;
Choy, K-L;
(2021)
Machine Learning Approach for Predicting the Discharging Capacities of Doped lithium Nickel- Cobalt-Manganese Cathode Materials in Li-ion Batteries.
ACS Central Science
, 7
(9)
pp. 1551-1560.
10.1021/acscentsci.1c00611.
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Wang, G;
Fearn, T;
Wang, T;
Choy, KL;
(2021)
Insight Gained from Using Machine Learning Techniques to Predict the Discharge Capacities of Doped Spinel Cathode Materials for Lithium-Ion Batteries Applications.
Energy Technology
10.1002/ente.202100053.
(In press).
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Zhang, Y;
Fearn, T;
(2015)
A linearization method for partial least squares regression prediction uncertainty.
Chemometrics and Intelligent Laboratory Systems
, 140
10.1016/j.chemolab.2014.11.011.
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Zhu, Y;
Fearn, T;
Chicken, DW;
Austwick, MR;
Somasundaram, SK;
Mosse, CA;
Clark, B;
... Bown, SG; + view all
(2018)
Elastic scattering spectroscopy for early detection of breast cancer: partially supervised Bayesian image classification of scanned sentinel lymph nodes.
Journal of Biomedical Optics
, 23
(8)
, Article 085004. 10.1117/1.JBO.23.8.085004.
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Book chapter
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Wilson, HJ;
(2016)
Practical Analytical Methods for Partial Differential Equations.
In: Bullett, SR and Fearn, T and Smith, F, (eds.)
Advanced Techniques in Applied Mathematics.
World Scientific: Singapore, Singapore.
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Proceedings paper
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Duran Casablancas, C;
Grau-Bové, J;
Fearn, T;
Strlič, M;
(2017)
Data mining in collections: from epidemiology to demography.
In:
Proceedings of the 18th ICOM Comittee for Conservation Triennial Conference.
International Council of Museums (ICOM-CC): Copenhagen, Denmark.
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Foreman, L;
Kimber, JA;
Oliver, KV;
Brown, JM;
Janes, SM;
Fearn, T;
Kazarian, SG;
(2015)
Assessing Dysplasia of a Bronchial Biopsy with FTIR Spectroscopic Imaging.
In: Cote, GL, (ed.)
The Proceedings of Optical Diagnostics and Sensing XV: Toward Point-of-Care Diagnostics.
SPIE - The International Society for Optical Engineering
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Garrido-Varo, A;
Riccioli, C;
Fearn, T;
De Pedro, E;
Perez-Marin, D;
(2019)
Multivariate predictive models for the prediction of fatty acids in the EU high added-value "acorn Iberian pig ham" using a miniature near-infrared spectroscopy instrument.
In: Kim, MS and Chin, BA and Cho, BK, (eds.)
SENSING FOR AGRICULTURE AND FOOD QUALITY AND SAFETY XI.
SPIE: Baltimore, MD, United States.
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Garrido-Varo, A;
Riccioli, C;
Fearn, T;
De Pedro, E;
Perez-Marin, D;
(2018)
Miniature near infrared spectroscopy spectrometer and information and communication technologies to guarantee the integrity of the EU high added-value "acorn Iberian pig ham" (IP).
In: Kim, MS and Chao, K and Chin, BA and Cho, BK, (eds.)
(Proceedings) Conference on Sensing for Agriculture and Food Quality and Safety X.
SPIE - International Society of Optical Engineering
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Kotti, E;
Manolopoulou, I;
Fearn, T;
(2016)
Hierarchical Bayesian variable selection in the probit model with mixture of nominal and ordinal responses.
In:
(Proceedings) 2016 IEEE Workshop on Statistical Signal Processing (SSP).
IEEE
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Mahgoub, H;
Chen, H;
Gilchrist, J;
Fearn, T;
Strlic, M;
(2017)
Quantitative chemical near-infrared hyperspectral imaging of Islamic paper.
In: Bridgland, J, (ed.)
(Proceedings) ICOM-CC 18th Triennial Conference.
International Council of Museums: Paris.
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Mahgoub, H;
Gilchrist, J;
Fearn, T;
Strlic, M;
(2017)
Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization.
In:
Optics for Arts, Architecture, and Archaeology VI.
(pp. 103310P-1).
SPIE
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