Academic & Scientific Publishing / PC Lab @ GEPSI –CIEPQPF


Books



• Reis, M.S., Estatística para a Melhoria de Processos – A Perspectiva Seis Sigma.
Coimbra: Imprensa da Universidade de Coimbra, 2016. (In Portuguese).

• Saraiva, P.M., J. d’Orey, P. Sampaio, M.S. Reis, C. Cardoso, J. Pinheiro, L. Tomé, O Futuro da Qualidade em Portugal.
Lisboa: APQ, 2010. ISBN: 978-972-9388-04-0. (In Portuguese).

Book Chapters

• Reis, M.S., Multivariate image analysis. Ed. by Granato, D., Ares, G. Mathematical and Statistical Methods in Food Science and Technology. Chichester: Wiley-Blackwell, 2014, p. 201-218. ISBN: 978-1-118-43368-3.

• Reis, M.S., B.R. Bakshi, P.M. Saraiva, Denoising and Signal to Noise Enhancement: Wavelet Transform and Fourier Transform. Editado por Brown, S.; Tauler, R.; Walczak, R.. Comprehensive Chemometrics: Chemical and Biochemical Data Analysis. Oxford: Elsevier, 2009, Vol. 2, p. 25-55.

• Reis, M.S., P.M. Saraiva, Multivariate and Multiscale Data Analysis. Editado por Coleman, S.; Greenfield, T.; Stewardson, D.; Montegomery, D.C.. Statistical Practice in Business and Industry, Statistics in Practice Series, Chichester: Wiley, 2008, p. 337-370.

Articles in peer reviewed journals and book series


/ 2017

• Campos, M., R. Sousa, A.C. Pereira, M.S. Reis, Advanced predictive methods for wine age prediction: Part II - A comparison study of multiblock regression approaches. Talanta. 171 (2017), p. 132-142. DOI: 10.1016/j.talanta.2017.04.064.

• Rendall, R., A.C. Pereira, M.S. Reis, Advanced predictive methods for wine age prediction: Part I - a comparison study of single-block regression approaches based on variable selection, penalized regression, latent variables and tree-based ensemble methods. Talanta. 171 (2017). DOI: 10.1016/j.talanta.2016.10.062.

• Rato, T.J., J. Blue, J. Pinaton, M.S. Reis, Translation Invariant Multiscale Energy-based PCA (TIME-PCA) for Monitoring Batch Processes in Semiconductor Manufacturing. IEEE – Transactions on Automation Science and Engineering. 14(2) (2017), p. 894-904. DOI: 10.1109/TASE.2016.2545744

• Lopes, A., A. Ribeiro, M.S. Reis, D.C.M. Silva, I. Portugal, C.M.S.G. Baptista, Modelling the Distribution of Nitrophenols in a Liquid-Liquid System Representative of an Industrial Nitration Process. Chemical Engineering Transactions. 57 (2017), p. 1033-1038.

• Lepore, A., B. Palumbo, C. Capezza, R. Rendall, M.S. Reis, A comparison of advanced regression techniques for predicting CO2 emissions in the ship industry. Quality and Reliability Engineering International. Accepted. (2017). DOI: 10.1002/qre.2171.

• Pinheiro, C.T., V. Ascensão, M.S. Reis, M.J. Quina, L. M. Gando-Ferreira, A data-driven approach for the study of coagulation phenomena in waste lubricant oils and its relevance in alkaline regeneration treatments. Science of the Total Environment. (2017). DOI: 10.1016/j.scitotenv.2017.05.124.

• Rato, T.J., M.S. Reis, Multiresolution Soft Sensors (MR-SS): A New Class of Model Structures for Handling Multiresolution Data. Industrial & Engineering Chemistry Research. 56(13) (2017), p. 3640-3654.

• Rato, T.J., M.S. Reis, Markovian and Non-Markovian Sensitivity Enhancing Transformations for Process Monitoring. Chemical Engineering Science. 163 (2017), p. 223-233.

• Pinheiro, C.T., R. Rendall, M.J. Quina, M.S. Reis, L. M. Gando-Ferreira, Assessment and Prediction of Lubricant Oil Properties Using Infrared Spectroscopy and Advanced Predictive Analytics. Energy & Fuels. 31(1) (2017), p. 179-187. DOI: 10.1021/acs.energyfuels.6b01958.

• Soares, M.A.R., M.J. Quina, M.S. Reis, R.M. Quinta-Ferreira, Assessment of co-composting process with high load of an inorganic industrial waste. Waste Management. 59 (2017), p. 90-89. DOI: 10.1016/j.wasman.2016.09.044.

/ 2016

• Fernández-Ramos, C., R. Rodríguez-Gómez, M.S. Reis, O. Ballesteros, A. Navalón, J.L. Vílchez, Sorption, degradation and transport phenomena of alcohol ethoxysulfates in agricultural soils. Laboratory studies. Chemosphere. 171 (2016), p.661-670. DOI: 10.1016/j.chemosphere.2016.12.091.

• Reis, M.S., R.S. Kenett, A Structured Overview on the Use of Computational Simulators for Teaching Statistical Methods. Quality Engineering. (2016), p. 1-16. DOI: 10.1080/08982112.2016.1272122.

• Reis, M.S., R.D. Braatz, L. Chiang, Big Data – Challenges and Future Research Directions. Chemical Engineering Progress (Special Section dedicated to big data). (March, 2016), p. 46-50.

• Rato, T.J., R. Rendall, V. Gomes, S.-T. Chin, L. Chiang, P.M. Saraiva, M.S. Reis, A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part I – Assessing detection strength. Industrial & Engineering Chemistry Research. 55(18) (2016), p. 5342-5358. DOI: 10.1021/acs.iecr.5b04851.

• Manco, G., S. Coleman, R. Goeb, A. Pievatolo, X. Tort-Martorell, M.S. Reis, How can SMEs benefit from Big Data? Challenges and a Path Forward. Quality and Reliability Engineering International. 32(6) (2016), p. 2151-2164.

• Pereira, A.C., M.J. Carvalho, A. Miranda, J.M. Leça, V, Pereira, F. Albuquerque, J.C. Marques, M.S. Reis, Modelling the ageing process: a novel strategy to analyze the wine evolution towards the expected features. Chemometrics and Intelligent Laboratory Systems. 154 (2016), p.176-184.

• Schmitt, E., T.J. Rato, M.S. Reis, B. de Ketelaere, M. Hubert, Parameter selection guidelines for adaptive PCA-based control. Journal of Chemometrics. 30(4) (2016), p. 163-176.

• Rato, T.J., E. Schmitt, B. de Ketelaere, M. Hubert, M.S. Reis, A Systematic Comparison of PCA-based Statistical Process Monitoring Methods for High-dimensional, Time-dependent Processes. AIChE Journal. 62(5) (2016), p. 1478-1493.

• Rendall, R., M.S. Reis, S.-T. Chin, L. Chiang, Managing Uncertainty Information for Improved Data-Driven Modelling. Computer-Aided Chemical Engineering, 38 (2016), p. 1575-1580

• Rendall, R., A. Pereira, M.S. Reis, An extended comparison study of large scale data-driven prediction methods based on variable selection, latent variables, penalized regression and machine learning. Computer-Aided Chemical Engineering, 38 (2016), p. 1629-1634.

/ 2015

• Schmitt, E., T.J. Rato, M.S. Reis, B. de Ketelaere, M. Hubert, Parameter selection guidelines for adaptive PCA-based control. Journal of Chemometrics. (2015).

• Rato, T.J., J. Blue, J. Pinaton, M.S. Reis, Translation Invariant Multiscale Energy-based PCA (TIME-PCA) for Monitoring Batch Processes in Semiconductor Manufacturing. IEEE – Transactions on Automation Science and Engineering. (2015).

• Rato, T.J., E. Schmitt, B. de Ketelaere, M. Hubert, M.S. Reis, A Systematic Comparison of PCA-based Statistical Process Monitoring Methods for High-dimensional, Time-dependent Processes. AIChE Journal. (2015). DOI: 10.1002/aic.15062.

• Reis, M.S., R. Rendall, S.-T. Chin, L. Chiang, Challenges in the Specification and Integration of Measurement Uncertainty in the Development of Data-Driven Models for the Chemical Processing Industry. Industrial & Engineering Chemistry Research. 54 (2015), p. 9159-9177.

• Leça, J.M., A.C. Pereira, A.C. Vieira, M.S. Reis, J.C. Marques, Optimal Design of Experiments Applied to Headspace Solid Phase Microextraction for the Quantification of Vicinal Diketones in Beer through Gas Chromatography-Mass Spectrometric detection. Analytica Chimica Acta. 887 (2015), p. 101-110.

• Oliver-Rodríguez, B., A. Zafra-Gómez, M.S. Reis, C. Verge, J.A. de Ferrer, M. Pérez-Pascual, J.L. Vílchez, Wide-range and Accurate Modeling of Linear Alkylbenzene Sulfonate (LAS) Adsorption/Desorption on Agricultural Soil. Chemosphere. 138 (2015), p. 148-155.

• Oliver-Rodríguez, B., A. Zafra-Gómez, M.S. Reis, B.P.M. Duarte, C. Verge, J.A. de Ferrer, M. Pérez-Pascual, J.L. Vílchez, Evaluation of Linear Alkylbenzene Sulfonate (LAS) Behaviour in Agricultural Soil Through Laboratory Continuous Studies. Chemosphere. 31 (2015), p. 1-8.

• Rato, T.J., M.S. Reis, On-line Process Monitoring using Local Measures of Association. Part I: Detection Performance. Chemometrics and Intelligent Laboratory Systems. 142 (2015), p. 255-264.

• Rato, T.J., M.S. Reis, On-line Process Monitoring using Local Measures of Association. Part II: Design Issues and Fault Diagnosis. Chemometrics and Intelligent Laboratory Systems. 142 (2015), p. 265-275.

• Reis, M.S., An Integrated Multiscale and Multivariate Image Analysis Framework for Process Monitoring of Colour Random Textures: MSMIA. Chemometrics and Intelligent Laboratory Systems. 142 (2015), p. 36-48.

• Rendall, R., M.S. Reis, A.C. Pereira, C. Pestana, V. Pereira, J.C. Marques, Chemometric Analysis of the Volatile Fraction Evolution of Portuguese Beer under Shelf Storage Conditions. Chemometrics and Intelligent Laboratory Systems. 142 (2015), p. 131-142.

• Rato, T.J., M.S. Reis, Multiscale and Megavariate Monitoring of the Process Networked Structure: M2NET. Journal of Chemometrics. 29(5) (2015), p. 309-322.

/ 2014

• Rato, T.J., M.S. Reis, Non-Causal Data-Driven Monitoring of the Process Correlation Structure: A Comparison Study with New Methods. Computers & Chemical Engineering. 71 (2014), p. 307-322.

• Rendall, R.R., M.S. Reis, A Comparison Study of Single-Scale and Multiscale Approaches for Data-Driven and Model-Based Online Denoising. Quality and Reliability Engineering International. 30(7) (2014), p. 935-950

• Rato, T.J., M.S. Reis, Sensitivity Enhancing Transformations for Large-Scale Process Monitoring. Computer-Aided Chemical Engineering. 34 (2014), p. 643-648.

• Moita, R.D., V.M. Gomes, P.M. Saraiva, M.S. Reis, An Extended Comparative Study of Two- and Three-Way Methodologies for the On-line Monitoring of Batch Processes. Computer-Aided Chemical Engineering. 34 (2014), p. 517-522.

• Rato, T.J., M.S. Reis, Sensitivity Enhancing Transformations for Monitoring the Process Correlation Structure. Journal of Process Control. 24 (2014), p. 905-915.

/ 2013

• G. Nogueira, Silva, D.C.M. Silva, M.S. Reis, C.M.S.G. Baptista, Prediction of the by-products formation in the adiabatic industrial benzene nitration process. Chemical Engineering Transactions. 32 (2013), p. 1249-1254.

• Reis, M.S., Applications of a new empirical modelling framework for balancing model interpretation and prediction accuracy through the incorporation of clusters of functionally related variables. Chemometrics and Intelligent Laboratory Systems. (2013), dx.doi.org/10.1016/j.chemolab.2013.05.007.

• Rato, T.J., M.S. Reis, Fault detection in the Tennessee Eastman benchmark process using dynamic principal components analysis based on decorrelated residuals (DPCA-DR). Chemometrics and Intelligent Laboratory Systems. 125 (2013), p. 101-108.

• Rato, T.J., M.S. Reis, Defining the structure of DPCA models and its impact on process monitoring and prediction activities. Chemometrics and Intelligent Laboratory Systems. 125 (2013), p. 74-86.

• Reis, M.S., Network-Induced Supervised Learning: Network-Induced Classification (NI-C) and Network-Induced Regression (NI-R). AIChE Journal. 59(5) (2013), p. 1570-1587.

• Pinheiro, I., P.J. Ferreira, F. A. Garcia, M.S. Reis, A.C. Pereira, C. Wandrey, H. Ahmadloo, J.L. Amaral, D. Hunkeler, M.G. Rasteiro, An experimental design methodology to evaluate the importance of different parameters on flocculation by polyelectrolytes. Powder Technology. 238 (2013), p. 2-13.

/ 2012

• Gomes, V.M., A.C. Pereira, P. M. Saraiva, M.S. Reis, Development of Generalized Platforms for the Analysis of Complex Datasets.Quality and Reliability Engineering International. 28 (2012), p. 508-523.

• Reis, M.S., P. M. Saraiva, Prediction of Profiles in the Process Industries.Industrial & Engineering Chemistry Research. 51 (2012), p. 4524-4266.

• Reis, M.S., P. Delgado, A large-scale statistical process control approach for the monitoring of electronic devices assemblage.Computers and Chemical Engineering. 39 (2012), p. 163-169.

/ 2011

• Pereira, A.C., M.S. Reis, P.M. Saraiva, J.C. Marques, Development of a fast and reliable method for long- and short-term wine age prediction. Talanta. 86 (2011), p. 293-304.

• Pereira, A.C., M.S. Reis, P.M. Saraiva, J.C. Marques, Madeira wine ageing prediction based on different analytical techniques: UV–vis, GC-MS, HPLC-DAD. Chemometrics and Intelligent Laboratory Systems. 105 (2011), p. 43-55.

• Cantarero, S., A. Zafra-Gómez, O. Ballesteros, A. Navalón, M.S. Reis, P.M. Saraiva, J.L. Vílchez, Environmental monitoring study of linear alkylbenzene sulfonates and insoluble soap in Spanish sewage sludge samples.Journal of Environmental Science and Health Part A. 46 (2011), p. 617-626.

• Rato, T.J., M.S. Reis, Statistical Process Control of Multivariate Systems with Autocorrelation. In Computer-Aided Chemical Engineering, vol. 29 – Parte A. Ed. by E.N. Pistikopoulos, M.C. Georgiadis and A. Kokossis. Amsterdam: Elsevier (2011). ISBN: 978-0-444-53711-9, p 497-501.

/ 2010

• Rato, T.J. M.S. Reis, Statistical Monitoring of Control Loops Performance: An Improved Historical-data Benchmark Index.Quality and Reliability Engineering International. 26:8 (2010), p. 831-844.

• Reis, M.S., A. Bauer, Image-based classification of paper surface quality using wavelet texture analysis.Computers and Chemical Engineering. 34 (2010), p. 2014-2021.

• Reis, M.S., P.M. Saraiva,Analysis and Classification of the Paper Surface. Industrial & Engineering Chemistry Research. 49:5 (2010), p. 2493–2502.

• Pereira, A.C., M.S. Reis, P.M. Saraiva, J.C. Marques, Analysis and assessment of Madeira wine ageing over an extended time period through GC–MS and chemometric analysis.Analytica Chimica Acta. 659 (2010), p. 93-101.

• Pereira, A.C., M.S. Reis, P.M. Saraiva, J.C. Marques, Aroma ageing trends in GC/MS profiles of liqueur wines.Analytica Chimica Acta. 660 (2010), p. 8-21.

• Reis, M.S., P. Delgado,“Mega”-Variate Statistical Process Control in Electronic Devices Assembling. In Computer-Aided Chemical Engineering, vol. 28. Ed. by S. Pierucci and G. Buzzi Ferraris. Amsterdam: Elsevier (2010). ISBN: 978-0-444-53569-6, p 523-528.

• Pereira, A.C., M.S. Reis, P.M. Saraiva, J.C. Marques, Multivariate Statistical Monitoring of Wine Ageing Processes. In Computer-Aided Chemical Engineering, vol. 28. Ed. by S. Pierucci and G. Buzzi Ferraris. Amsterdam: Elsevier (2010). ISBN: 978-0-444-53569-6, p 247-252.

/ 2009

• Reis, M.S., A. Bauer ⎯ Wavelet texture analysis of on-line acquired images for paper formation assessment and monitoring. Chemometrics and Intelligent Laboratory Systems. 95:2 (2009), p. 129-137.

• Reis, M.S., C.T. Abreu, M.J. Heitor, J. Ataíde, P.M. Saraiva, A new procedure for the routine assessment of paper diagonal curl. Tappi Journal. 8:10 (2009), p. 20-26.

• Reis, M.S., A multiscale empirical modeling framework for system identification. Journal of Process Control. 19:9 (2009), p. 1546-1557.

• Reis, M.S., A. Bauer, Using Wavelet Texture Analysis in Image-Based Classification and Statistical Process Control of Paper Surface Quality. In Computer-Aided Chemical Engineering, vol. 27. Ed. by Rita Maria de Brito Alves, Claudio Augusto Oller do Nascimento, Evaristo Chalbaud Biscaia, Jr.: Elsevier (2009). ISBN-13: 978-0-444-53472-9. p. 1209-1214.

• Paula A.G. Portugal, M.S. Reis, Cristina M.S.G. Baptista, Extending model prediction ability for the formation of nitrophenols in benzene nitration. Chemical Engineering Transactions. 17 (2009), p. 117-122.

• Pereira, A.C., M.S. Reis, and P.M. Saraiva ⎯ Quality control of food products using image analysis and multivariate statistical tools. Industrial & Engineering Chemistry Research. 48:2 (2009), p. 988-998.

• Saraiva, P.M., M.S. Reis, Ouvir e Interpretar Dados no Século XXI. Qualidade. Ano XXXVIII, nº 3, Outono (2009), p.28-38 (in Portuguese).

/ 2008

• Reis, M.S., C.T. Abreu, M. J. Heitor, P.M. Saraiva ⎯ Uma Nova Metodologia para Medição do “Curl” Diagonal do Papel. Pasta e Papel. Verão (2008), p.22-28 (in Portuguese).

• Reis, M.S., B.R. Bakshi, P.M. Saraiva ⎯ Multiscale Statistical Process Control Using Wavelet Packets. AIChE Journal. 54:9 (2008), p. 2366-2378.

/ 2006

• Reis, M.S., P.M. Saraiva, Generalized Multiresolution Decomposition Frameworks for the Analysis of Industrial Data with Uncertainty and Missing Values. Industrial & Engineering Chemistry Research. 45 (2006), p. 6330-6338.

• Reis, M.S., P.M. Saraiva, Multiscale Statistical Process Control with Multiresolution Data. AIChE Journal. 52:6 (2006), p. 2107-2119.

• Reis, M.S., P.M. Saraiva, Heteroscedastic Latent Variable Modelling with Applications to Multivariate Statistical Process Control. Chemometrics and Intelligent Laboratory Systems. 80 (2006), p. 57-66.

• Reis, M.S., P.M. Saraiva, Multiscale Statistical Process Control of Paper Surface. Quality Technology and Quantitative Management. 3:3 (2006), p. 263-282.

• Reis, M.S., P.M. Saraiva, Multiscale Analysis and Monitoring of Paper Surface. In Computer-Aided Chemical Engineering, vol. 21B. Ed. by Marquardt, W., C. Pantelides. Amsterdam: Elsevier (2006). ISBN 0-444-52257-3. p. 1173-1178.

• Reis, M.S., P.M. Saraiva, Multiscale SPC in the Presence of Multiresolution Data. In Computer-Aided Chemical Engineering, vol. 21B. Ed. by Marquardt, W., C. Pantelides. Amsterdam: Elsevier (2006). ISBN 0-444-52257-3. p. 1359-1364.

/ 2005

• Quadros, P.A., M.S. Reis, C. M. S. G. Baptista, Different Modelling Approaches for a Heterogeneous Liquid-Liquid Reaction Process. Industrial & Engineering Chemistry Research. 44 (2005), p. 9414-9421.

• Reis, M.S., P.M. Saraiva, Integration of Data Uncertainty in Linear Regression and Process Optimization. AIChE Journal. 51:11 (2005), p. 3007-3019.

• Costa, R., D. Angélico, M.S. Reis, J. Ataíde, P.M. Saraiva, Paper Superficial Waviness: Conception and Implementation of an Industrial Statistical Measurement System. Analytica Chimica Acta. 544 (2005), p. 135-142.

• Reis, M.S., P.M. Saraiva, Integrating Data Uncertainty in Multiresolution Analysis.In Computer-Aided Chemical Engineering, vol. 20B. Ed. by Puigjaner, L., A. Espuña. Amsterdam: Elsevier (2005). ISBN 0-444-51991-2. p. 1501-1506.

/ 2004

• Reis, M.S., P.M. Saraiva, A Comparative Study of Linear Regression Methods in Noisy Environments. Journal of Chemometrics. 18:12 (2004), p. 526-536.

• Reis, M.S., P.M. Saraiva, Accounting for Measurement Uncertainties in Industrial Data Analysis. In Computer-Aided Chemical Engineering, vol. 18. Ed. by Barbosa-Póvoa, A., H. Matos. Amsterdam: Elsevier (2004). ISBN 0-444-51694-8. p. 751-756.

• Dourado, C., A. Madrigal, M.S. Reis, Prediction of traqueal tube size in children using multiple variables. European Journal of Anaesthesiology. 21 (2004), p. 146-147.

/ 2003

• Reis, M.S., P.M. Saraiva, Multiscale Latent Variable Analysis of Industrial Data. In Computer-Aided Chemical Engineering, vol. 15B. Ed. by B. Chen, A.W. Westerberg. Amsterdam: Elsevier (2003). ISBN 0-444-51404-X. p. 1340-1345.