81
TITLE: Discussion: Process data streams aggregation versus product samples aggregation
AUTHORS: Reis, MS;
PUBLISHED: 2019, SOURCE: JOURNAL OF QUALITY TECHNOLOGY, VOLUME: 53, ISSUE: 1
INDEXED IN: Scopus WOS CrossRef: 3
IN MY: ORCID
82
TITLE: An Advanced Data-Centric Multi-Granularity Platform for Industrial Data Analysis
AUTHORS: Reis, MS; Rato, TJ;
PUBLISHED: 2019, SOURCE: 29th European Symposium on Computer-Aided Process Engineering (ESCAPE) in 29TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT B, VOLUME: 46
INDEXED IN: Scopus WOS CrossRef: 1
IN MY: ORCID
83
TITLE: Optimal fusion of industrial data streams with different granularities
AUTHORS: Rato, TJ; Reis, MS;
PUBLISHED: 2019, SOURCE: COMPUTERS & CHEMICAL ENGINEERING, VOLUME: 130
INDEXED IN: Scopus WOS CrossRef: 5
IN MY: ORCID
84
TITLE: Mechanistic Modeling and Simulation for Process Data Generation
AUTHORS: Fernandes, NCP; Romanenko, A; Reis, MS;
PUBLISHED: 2019, SOURCE: Industrial and Engineering Chemistry Research, VOLUME: 58, ISSUE: 38
INDEXED IN: Scopus CrossRef: 4
IN MY: ORCID
85
TITLE: Finding the optimal time resolution for batch-end quality prediction: MRQP - A framework for multi-resolution quality prediction
AUTHORS: Gins, G; Van Impe, JFM; Reis, MS;
PUBLISHED: 2018, SOURCE: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, VOLUME: 172
INDEXED IN: Scopus WOS CrossRef: 19
IN MY: ORCID
86
TITLE: A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part II - Assessing Detection Speed
AUTHORS: Rato, TJ; Rendall, R; Gomes, V; Saraiva, PM; Reis, MS;
PUBLISHED: 2018, SOURCE: Industrial and Engineering Chemistry Research, VOLUME: 57, ISSUE: 15
INDEXED IN: Scopus CrossRef: 7
IN MY: ORCID
87
TITLE: Distribution models for nitrophenols in a liquid-liquid system  Full Text
AUTHORS: Lopes, ALCV; Ribeiro, AFG; Reis, MPS; Silva, DCM; Portugal, I; Baptista, CMSG;
PUBLISHED: 2018, SOURCE: CHEMICAL ENGINEERING SCIENCE, VOLUME: 189
INDEXED IN: Scopus WOS CrossRef: 4
IN MY: ORCID
88
TITLE: Image-based manufacturing analytics: Improving the accuracy of an industrial pellet classification system using deep neural networks
AUTHORS: Rendall, R; Castillo, I; Lu, B; Colegrove, B; Broadway, M; Chiang, LH; Reis, MS;
PUBLISHED: 2018, SOURCE: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, VOLUME: 180
INDEXED IN: Scopus WOS CrossRef: 18
IN MY: ORCID
89
TITLE: Definitive Screening Designs and latent variable modelling for the optimization of solid phase microextraction (SPME): Case study - Quantification of volatile fatty acids in wines  Full Text
AUTHORS: Ana C Pereira; Reis, MS; Leca, JM; Rodrigues, PM; Marques, JC;
PUBLISHED: 2018, SOURCE: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, VOLUME: 179
INDEXED IN: Scopus WOS CrossRef: 13
IN MY: ORCID
90
TITLE: Building Optimal Multiresolution Soft Sensors for Continuous Processes
AUTHORS: Rato, TJ; Reis, MS;
PUBLISHED: 2018, SOURCE: 27th European Symposium on Computer-Aided Process Engineering (ESCAPE) in INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, VOLUME: 57, ISSUE: 30
INDEXED IN: Scopus WOS CrossRef: 18
IN MY: ORCID
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