Fundamentals and Applications of Multiway Data Analysis

Alejandro Olivieri, Graciela M. Escandar, Héctor C. Goicoechea, Arsenio Muñoz de la Peña, Alejandro Olivieri, Graciela M. Escandar, Héctor C. Goicoechea, Arsenio Muñoz de la Peña

• Publisher: Elsevier
• Year: 2024
• Print ISBN:
  9780443132612
• eBook ISBN:
  9780443132629
• Topic: Technology & Engineering
• Subtopic: Materials Science
• Index: Technology & Engineering

Fundamentals and Applications of Multiway Data Analysis provides comprehensive coverage of the main aspects of multiway analysis, including selected applications that can resolve complex analytical chemistry problems. This book follows on from Fundamentals and Analytical Applications of Multiway Calibration, (2015) by addressing new theoretical analysis and applications on subjects beyond multiway calibration and devoted to the analysis of multiway data for other purposes. Specifically, this new volume presents researchers a set of effective tools they can use to obtain the maximum information from instrumental data.  This book includes the most advanced techniques, methods and algorithms related to multiway modelling for solving calibration and classification tasks, and the way they can be applied.  This book collects contributions from a selected number of well-known and active chemometric research groups across the world, each covering one or more subjects where their expertise is recognized and appreciated.  - Includes chapters written by renowned international authors, all currently active in the subject field - Presents coverage of all the main aspects of multi-way analytical data analysis, concerning the two main areas of interest: data generation and algorithmic models for data processing - Provides up-to-date material with reference to current literature on the subject

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• Preface
• Chapter 1: Effects of different constraints on range of feasible solutions in self-modeling curve resolution methods
• Chapter 2: Custom-made optical platforms for high-throughput acquisition of multilinear high-order data in dynamic systems
• Chapter 3: Fusion of multiway data with classical spectroscopy for the study of natural waters
• Chapter 4: Replicate analysis for uncertainty estimation in PARAFAC and PARAFASCA analyses of factorial metabolomics data
• Chapter 5: Fluorescence developments for the nondestructive analysis of forensic fiber evidence
• Chapter 6: Multiset analysis by multivariate curve resolution: The unmixing methodology to handle hyperspectral image fusion scenarios
• Chapter 7: Multiway analysis of electrochemical data
• Chapter 8: Fluorescence spectroscopy and second-order methods in monitoring aquatic environments
• Chapter 9: Recent advances in multiway data modeling for classification issues
• Chapter 10: Multiway calibration using spectral data modulated by pH
• Chapter 11: Multiway analyses in biological interactions
• Chapter 12: Recent applications of multiway data modeling for protein analysis by IR spectroscopy
• Chapter 13: Hard modeling of multiway data
• Chapter 14: Multiway data analysis applied to excitation–emission fluorescence matrices acquired from semiconductor/carbon quantum dots-based sensing nanoplatforms
• Chapter 15: Recent applications of third-order/four-way and fourth-order/five-way data analysis
• Chapter 16: Recent advances in multiway analytical figures of merit
• Chapter 17: Suitability of multiway methods to ensure food safety
• Chapter 18: Multiway data analysis applied to miniaturized spectroscopy
• Chapter 19: Multiway analysis in process analytical chemistry
• Chapter 20: Recent advances in comparative analysis for comprehensive two-dimensional gas chromatography–mass spectrometry data
• Chapter 21: Multiway data processing of hyphenated chromatographic data for targeted and nontargeted analysis of environmental samples
• Chapter 22: New application of trilinear decomposition model: Theory, data processing, and classical quantitative applications
• Chapter 23: New application of trilinear decomposition model: New quantitative and qualitative applications
• Index