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Useful Calibration Acronyms

Useful ACRONYMS

This is a useful list of relevant acronyms related to our process analyzers and calibrations that are commonly encountered, and a short definition where relevant. The list below is in alphabetical order. This glossary represents the most popular data analysis terms you may use during your conversations about using process spectroscopy.

Calibration and Regression Methods Acronyms

  • ANN – Artificial Neural Networks An Artificial Neural Network (ANN) is an information processing method that is inspired by the way biological nervous systems process information. An ANN is composed of a large number of highly interconnected processing elements (neurons) working together to solve specific problems. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning involves adjustments to the connections that exist between the neurons. In more practical terms neural networks are non-linear statistical data
  • CLS – Classical Least Squares CLS (the K Matrix method) is a regression method that assumes Beer’s Law applies – i.e. that absorbance at each wavelength is proportional to component concentration. A model generated using CLS in its simplest form, requires that all interfering chemical components be known and included in the calibration data set.
  • ILS – Inverse Least Squares ILS (the P Matrix method) is a regression method that applies the inverse of Beer’s Law. It assumes that component concentration is a function of absorbance. An ILS model has a significant advantage over CLS in that it does not need to know and include all components in the calibration set.
  • kNN – k Nearest Neighbor kNN is a classification scheme where a Euclidian distance metric is used to determine the classification. The distance metric calculated for an unknown sample is an indication of the degree of similarity to other samples.
  • LWR – Locally Weighted Regression In locally weighted regression, sample points are weighted by their proximity to the current sample point in question. A regression model is then computed using the weighted points. In some cases, LWR models can produce better accuracy.
  • MCR – Multivariate Curve Resolution Multivariate Curve Resolution is a group of techniques that can be used to resolve mixtures by determining the number of constituents present and what their individual response profiles (spectra, pH profiles, time profiles, elution profiles) look like. It also provides an estimate of the concentrations. This can all be done with no prior information about the nature and composition of the mixtures.
  • MLR – Multiple Linear Regression MLR is a regression method for relating the variations in a response variable (concentrations or properties) to the variations of several predictors (spectral data). The goal is to be able to measure the spectral data on future samples and predict the concentrations or properties. One requirement for MLR is that the predictor variables (spectral data) must be linearly independent.

Instrument and Technology Acronyms

  • NIR-O – Our next generation spectrometer and an evolutionary step-up from the M412, NIR-O stands for Near InfraRed Online process analyzer. NIR-O is suitable for online analyses of most processes and process streams. Having the built-in capacity to add more sampling points (up to 12 total channels) within the same process or across processes, in any combination, gives users the flexibility to invest in exactly the capacity they require now. It also minimizes investment for any expansion users may want in the future. NIR-O operates in the xNIR range of 1000-2100nm, using process-proven TE-cooled InGaAs detector technology.
  • FT-NIR – An alternative to dispersive spectrometers, Fourier transform spectroscopy is an effective tool for lab analysis.
  • DG-NIR – Disperive grating technology was developed over 100 years ago and is the defacto standard for real time monitoring of in-situ process conditions.

Statistical and Mathematical Acronyms

  • OSC – Orthogonal Signal Correction Orthogonal signal correction is a technique originally developed and used for spectral data to remove variation that is orthogonal (non-correlated) to a particular parameter of interest. This is one way to remove interferences from spectral data prior to calibration.
  • PCA – Principal Component Analysis Principal component analysis (PCA) is a bi-linear modeling method that involves a mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible.
  • PCR – Principal Component Regression In PCR the PCA is taken one step further and a regression between the principal components and one or more response variables (concentrations or properties) is performed. A PCR model can then be used to predict concentrations or properties for unknown samples.
  • PLS – Partial Least Squares Partial Least Squares Regression is a bilinear modeling method where information in the original X variables (spectral data) is projected onto a small number of underlying “latent” variables called PLS components. The Y variables (concentrations or properties) are used in estimating the “latent” variables to ensure that the first components are those that are most relevant for predicting the Y-variables. Interpretation of the relationship between the X and Y variables is then simplified as this relationship is concentrated on the smallest possible number of components.
  • RMSEC – Root Mean Square Error of Calibration
  • RMSEP – Root Mean Square Error of Prediction
  • RMSEPcv – Root Mean Square Error of Prediction based on Cross Validation
  • SEC – Standard Error of Calibration
  • SEP – Standard Error of Prediction

These are all terms that are used to evaluate the performance of calibrations. The SEP terms are indications of how accurate a calibration model will be in predicting future samples. They are calculated using predicted results from true unknown samples. The RMSEP is an average expected prediction error. This differs slightly from the SEC terms that are providing the prediction error for the calibration samples used in developing the model. The relationship between RMSEP and SEP (RMSEC and SEC) is RMSEP2 = SEP2 + bias2

As the field of process spectroscopy grows, so does the number of acronyms associated with the calibration. The list below is in alphabetical order.

  • ANSI – American National Standards Institute
    The ANSI is a private nonprofit organization that oversees the development of voluntary consensus standards for products, services, processes, systems, and personnel in the United States. The organization also coordinates U.S. standards with international standards so that American products can be used worldwide. These standards ensure that the characteristics and performance of products are consistent, that people use the same definitions and terms, and that products are tested the same way.
  • ASTM – American Society for Testing and Materials
    ASTM International is one of the largest voluntary standards development organizations in the world. They are a source for technical standards for materials, products, systems, and services. ASTM International standards have an important role in the information infrastructure that guides design, manufacturing and trade in the global economy.
  • ATEX
    The European directive 94/9/EC requires that employers must protect employees from explosion risk in areas with explosive atmospheres. Manufacturers and importers must ensure that their products meet specific safety requirements. The goal of ATEX, which gets its name from the directive’s French title Appareils destinés á être utilisés en ATmosphères Explosibles, is to allow free trade of “ATEX” approved equipment within the EU by removing the need for separate testing and documentation for each member state.
  • CENELEC
    CENELEC is the European Committee for Electrotechnical Standardization. This is a non-profit technical organization set up under Belgian law and composed of the National Electrotechnical Committees of 30 European countries. CENELEC’s mission is to prepare voluntary electrotechnical standards that help develop the Single European Market/European Economic Area for electrical and electronic goods and services removing barriers to trade, creating new markets and cutting compliance costs.
  • FT-NIR
    Fourier transform spectroscopy is a measurement technique whereby spectra are collected based on time-domain measurements of the electromagnetic radiation. It can be applied to a variety of types of spectroscopy, including Near-Infrared spectroscopy (see NIR below).
  • ISO
    ISO is an international-standard-setting body composed of representatives from various national standards organizations. The organization promulgates world-wide proprietary industrial and commercial standards. ISO is a network of the national standards institutes of 157 countries, one member per country, with a Central Secretariat in Geneva, Switzerland, that coordinates the system.
  • NIR
    Near-Infrared or NIR is a region of the electromagnetic spectrum from about 750nm to 2600nm. Near Infrared Spectroscopy is the technique of using a sample’s NIR absorbance characteristics to predict parameters of interest. Molecules containing C-H, O-H, and N-H bonds absorb NIR radiation in specific regions or at specific wavelengths. These absorbance’s can then be used in a qualitative or quantitative measurement. NIR spectroscopy is widely used in both process and laboratory measurements across many industries (chemical, refining, pharmaceutical, polymer, semi- conductor, agricultural).
  • NIST
    The National Institute of Standards and Technology (NIST), previously known as the National Bureau of Standards (NBS), is a non-regulatory agency of the United States Department of Commerce. The institute’s mission is to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life.
  • PAT
    Process Analytical Technology (PAT) has been defined by the United States Food and Drug Administration (FDA) as a mechanism to design, analyze, and control pharmaceutical manufacturing processes through the measurement of critical process parameters and quality attributes. While this term was initially defined in relation to the pharmaceutical industry, the concepts and methods can be extended to other industries.
  • SST
    Our Single-Sided Transmission (SST) Probe is a rugged and reliable sample probe that is ideal for continuous process monitoring applications. SST means that light passes through the sample region only once. In contrast, transflectance probes pass twice, being reflected from the far end. The SST probe can be easily installed in a pipe or reactor through a single access port and works with any Guided Wave single-fiber spectrometer or photometer. Optional accessories make it easy to adapt the SST Probe to different kinds of process installations.
  • UV/VIS
    UV/VIS spectroscopy is the measurement of the wavelength and intensity of absorption of ultraviolet and visible light by a sample. Ultraviolet and visible light are energetic enough to promote outer electrons to higher energy levels. UV/VIS spectroscopy is usually applied to molecules and inorganic ions or complexes in solution. The spectra have broad features that are of limited use for sample identification but are very useful for quantitative measurements. The concentration of an analyte in solution can be determined by measuring the absorbance at some wavelength and applying the Beer-Lambert Law.

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