Reviews:

Organic Process Research & Development
"..a useful introductory overview of a wide range of chemometric techniques.."

Book Description:

* Includes five chapters that cover the basic principles of chemometrics analysis.
* Provides two chapters on the use of Excel and MATLAB for chemometrics analysis.
* Contains 70 worked problems so that readers can gain a practical understanding of the use of chemometrics.

Synopsis:

Slow sand filtration is credited with being the first drinking water treatment process utilised to improve the quality of water in both modern Europe and the USA. Within the last 10 years, there has been a renaissance of interest in the potential use of enhanced processes of slow sand filtration throughout the world, especially for small and rural communities, and it continues to be the primary treatment process for many major European cities. The book deals with the latest research developments in slow sand and alternative biological filtration processes for drinking water treatment, including advances in the understanding of the fundamental mechanisms of the processes. In addition, progress in the techniques of operation and upgrading of the processes are described, with case studies from around the world. The principal themes of the book are: General overview; Removal of Natural Organic Matter (NOM), Biodegradable Organic Carbon (BOC) and Ozonation by-products; Biofilter media characteristics; Influence of process design variables and modifications; Modelling process performance; Pre-treatment applications; Operational experience and cleaning; and Upgrading treatment processes.

Table of Contents:

Preface.
1. INTRODUCTION.

Points of view.

Software and calculations.

Further reading.

References.

2. EXPERIMENTAL DESIGN.

Introduction.

Basic Principles.

Factorial designs.

Central composite or response surface designs.

Mixture designs.

Simplex optimisation.

Problems.

3. SIGNAL PROCESSING.

Sequential signals in chemistry.

Basics.

Linear filters.

Correlograms and time series analysis.

Fourier transform techniques.

Topical methods.

Poroblems.

4. PATTERN RECOGNITION.

Introduction.

The concept and need for principal components analysis.

Principal Components Analysis : the method.

Unsupervised Pattern Recognition : Cluster Analysis.

Supervised pattern recognition.

Multiway pattern recognition.

Problems.

5. CALIBRATION.

Introduction.

Univariate calibration.

Multiple linear regression.

Principal Components Regression.

Partial Least Squares.

Model validation.

Problems.

6. EVOLUTIONARY SIGNALS.

Introduction.

Exploratory data analysis and preprocessing.

Determining composition.

Resolution.

Problems.

Appendices

A.1 Vectors and Matrices.

A.2 Algorithms.

A.3 Basic Statistical Concepts.

A.4 Excel for Chemometrics.

A.5 Matlab for Chemometrics.

Index