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R.C. McDowall is the principle of McDowall Consulting and director of R.D. McDowall Limited, and "Questions of Quality" column editor for LCGC Europe, Spectroscopy's sister magazine.

Articles

“SneakerNet,” or the manual transfer of data using a disk or USB stick from one computer system to another, should be long dead, but this noncompliant transfer process still survives.

Consigning SneakerNet to the Graveyard of Technology

The details of applying deep learning algorithms and FT-IR spectra are described for classification research using the spectra of strawberries as an example.

Combining the WGAN and ResNeXt Networks to Achieve Data Augmentation and Classification of the FT-IR Spectra of Strawberries

Howard Mark serves on the Editorial Advisory Board of 

 and runs a consulting service, Mark Electronics that provides assistance, training, and consultation in near-IR spectroscopy as well as custom hardware and software design and development.

Jerome Workman Jr. serves on the Editorial Advisory Board of Spectroscopy and is currently with Unity Scientific LLC. He is also an adjunct professor at Liberty University and U.S. National University. He can be reached at jworkman04@gsb.columbia.edu.

Mathematics is a formal logic system, perhaps the ultimate formal logic system. Here we describe the elegance of the foundations of the mathematics that chemometrics is based on.

Why Does -1 x -1 = 1?

We explore how different algorithms and different numbers of factors affect the results.

Classical Least Squares (CLS), Part 3: Expanding the Analysis to Include Concentration Information on Principal Component Regression (PCR) and Partial Least Squares (PLS) Algorithms

Spreadsheets are often used to perform GMP-related calculations, but can lead to serious problems and unnecessary risk. We explain why the use of spreadsheets is heavily discouraged in a regulated laboratory environment.

Spreadsheets: A Sound Foundation for a Lack of Data Integrity?

We provide a scorecard of chemometric techniques used in spectroscopy. The tables and lists of reference sources given here provide an indispensable resource for anyone seeking guidance on understanding chemometric methods or choosing the most suitable approach for a given analysis problem.

A Survey of Chemometric Methods Used in Spectroscopy

Chemometrics in Spectroscopy is a collection of column articles that the authors published in Spectroscopy over a period spanning more than two decades. Each article is generally arranged as a chapter in the book, and chapters dealing with the same or similar topics are arranged closely as a section block rather than following the original sequence in the magazine. Although each article or series of articles only discusses one specific topic, collectively, the articles form a comprehensive reference that is a valuable source for readers wanting to learn chemometrics, especially with its applications in spectroscopy. 


Book Review: Chemometrics in Spectroscopy, 2nd Edition, by Howard Mark and Jerry Workman, Jr.

A newly discovered effect can introduce large errors in many multivariate
spectroscopic calibration results. The CLS algorithm can be used to explain this effect. Having found this new effect that can introduce large errors in calibration results, an investigation of the effects of this phenomenon to calibrations using principal component regression (PCR) and partial least squares (PLS) is examined.

More About CLS, Part 1: Expanding the Concept

Calibration transfer involves multiple strategies and mathematical techniques for applying a single calibration database to two or more instruments. Here, we explain the methods to modify the spectra or regression vectors to correct differences between instruments.

Calibration Transfer Chemometrics, Part I: Review of the Subject

The archnemesis of calibration modeling and the routine use of multivariate models for quantitative analysis in spectroscopy is the confounded bias or slope adjustments that must be continually implemented to maintain calibration prediction accuracy over time. A perfectly developed calibration model that predicted well on day one suddenly has to be bias adjusted on a regular basis to pass a simple bias test when predicted values are compared to reference values at a later date. Why does this problem continue to plague researchers and users of chemometrics and spectroscopy?

Data Analysis, Statistics, and Chemometrics