Bøger i Data Handling in Science and Technology serien

Data Fusion Methodology and Applications explores the data-driven discovery paradigm in science and the need to handle large amounts of diverse data. Drivers of this change include the increased availability and accessibility of hyphenated analytical platforms, imaging techniques, the explosion of omics data, and the development of information technology. As data-driven research deals with an inductive attitude that aims to extract information and build models capable of inferring the underlying phenomena from the data itself, this book explores the challenges and methodologies used to integrate data from multiple sources, analytical platforms, different modalities, and varying timescales.Presents the first comprehensive textbook on data fusion, focusing on all aspects of data-driven discoveryIncludes comprehensible, theoretical chapters written for large and diverse audiencesProvides a wealth of selected application to the topics included

Presents basic mathematical aspects of the ranking methods using a didactical approach. This book covers a wide range of applications, from the environment and toxicology to DNA sequencing. It can be applied in several different fields, such as decision support, toxicology, EU priority lists of toxic chemicals, and environmental problems.

Genetic Algorithms (GA) and Artificial Neural Networks (ANN) have progressively increased in importance amongst the techniques routinely used in chemometrics. Divided into two sections (GA and ANN), this book contains contributions from experts in the field and is of use to those who are using or are interested in GA and ANN.

As such the book provides the means to approach and solve analytical problems strategically and systematically, without the need for the reader to become a fully-fledged chemometrician. The authors' aim was to write a tutorial book which would be useful to readers at every level in this field.

Analyzing observed or measured data is an important step in applied sciences. This book provides not only definitions and short descriptions, but also offers an overview of the different topics. It gives 1700 entries in alphabetical order grouped into 20 topics and each topic is organized in a hierarchical fashion.

Introduces the fundamentals of experimental design. This book discusses the effects of different experimental designs and different models on the variance-covariance matrix and on the analysis of variance. It includes applications and topics such as confidence bands, rotatability, and confounding.

Concentrating on theoretical aspects, this book is written in a tutorial-like manner, with simple numerical examples. It presents applications of wavelets from many branches of chemistry which is aimed at chemists to further exploration of this subject. It explains all basic terms and pinpoints all properties of wavelets.

Gives an overview of the numerical data analysis and signal treatment techniques that are used in chromatography and related separation techniques. This book emphasises the description of the symmetrical and asymmetrical chromatographic peak shape models. It discusses both theoretical and empirical models.

Useful to researchers and professionals in chemometrics, this book provides 106 exercises with answers to accompany the study of theoretical principles. It presents 42 cases studies with real data showing designs and the complete statistical analyses for problems in the areas chromatography, electroanalytical and electrochemistry, and calibration.

Describes multivariate analysis in sensory science and both methods for aggregated and individual sensory profiles are discussed. This title presents processes and results in such a way that they can be understood not only by statisticians but also by experienced sensory panel leaders and users of sensory analysis.

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. It 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.