1. On-Line Prediction and Classification using The Unscrambler On-Line Predictor (OLUP) and Classifier (OLUC)

2. 1. On-Line Predictions

3. The Unscrambler On-Line Predictor (OLUP)
Loads your Unscrambler model(s) and performs full prediction
Using DDE (Dynamic Data Exchange) or function calls to a DLL (Dynamic Link Library)
Communicates with Excel, LabView, instrument control software, etc.

4. OLUP integration with Instrument Client Software (DLL Example)

5. OLUP integration with Instrument Client Software (DDE Example)

6. The Unscrambler On-Line Predictor (OLUP)
Specify the level of results you want
Automatic preprocessing (e.g. derivatives)
Program in C/C++, Visual Basic, Fortran, etc.
Documentation and code examples follow the software
Can be used in combination with The Unscrambler On-Line Classifier (OLUC)

7. Pretreatment / preprocessing
Baseline correction (offset & linear)
Derivatives
Multiplicative Scatter Correction
Shift (position) correction
Spectral matching/Standardization/ Calibration transfer
… and others
CHEMOmetrics means use of statistical methods within chemical analysis. Many people are provoked by this word, since they deal with economy (econometrics),psychlogy (psychometircs), bology (biometrics), etc. Therefore we prefer to call it CAMOmetrics, since our customers work witin many appication areas.
With CAMOmetrics (chemometrics) we also include startegies for collection and generation of informative data, handling om measurements and uncertainties and vaidaton (testing) of model, I.e. a complete strategy.

8. Results from full PLS Prediction^
Predicted Y-values ( Y )
Total Residual
Residuals for each x-variable
Scores
Leverages
Deviation in prediction
Here are some of the application areas where Camometrics and Unscrambler is much used. In spectroscopy calibration for example you use spectroscopy instruments and to make fast inexpensive measurements where you use The Unscrambler to make a model between spectroscopy measurements for example protein in wheat or fat in meat or octanenumber in gasolin or the concentration of alcohol in mixtures and so on. It is very much used in process analysis and optimalization for example to find out which product factors have result of result parameters or quality parameters and how should we run our process to get the best results. It is used in pharmaceutical industries for example to formulate new drugs to model the clinical activity or the reactions based on molecylstructure. It is very very much used in analytical chemistry to combine different kinds of measurements to find a analyzer which repleases costly measurements with cheaper ones. It is used in endline ??????? analysis to trace pollution for example or to measure the ???? of dioxines or to monitor the population of seals based on the kind of pollution that is stored in the bodies???? Very much used within food industry and consumer inustry within central valuation, where we try to describe the quality of a product parameters measured by human beings; smell, taste,taste of bitterness, sweetness ????? and so on. It is used for example in consumery research where you can use questionarie answers to try to find out relationships.

9. On-Line PLS Predictions

10. OLUP Syntax in Excel =Predict|Ypredicted!Data (Ypredicted)
=Predict|Tai!Data (scores)
=Predict|Hi!Data (leverage)
=Predict|Eix!Data (residual spectrum)

11. OLUP References Statoil Seagate Analytical Spectral Devices Monsanto
Nova Chemicals
Oji Paper company
Novo Nordisk
Unger Fabrics

12. 2. On-Line Classification

13. The Unscrambler On-Line Classifier (OLUC)
Loads your Unscrambler model(s) and performs classification
Using Dynamic Link Library (DLL)
Communicates with Excel, LabView, instrument control software, etc.
Automatic preprocessing (e.g. derivatives)
Program in C/C++, Visual Basic, Fortran, etc.
Can be used in combination with OLUP

14. OLUC Integration with Instrument Client Software DLL Example

15. Classification Results
For each sample:
Si, residual = Object to Model distance
Hi = Leverage
An object fits the class if Si and Hi are within membership limits
Between models: Model distance
For each variable: Discrimination power
Modeling power

16. 3. Combine Qualitative and Quantitative predictions

17. Combine Qualitative and Quantitative predictions OLUC/OLUP Integration with Instrument Client Software

18. Summary
For PCR and PLS-R models it is advised to use full prediction and get:
Outlier detection
Uncertainties in the predicted values
OLUP and OLUC give you flexibility in conveying results through DDE or function calls in DLL
There is a great potential in on-line NIR- spectroscopy e.g. for process monitoring!

19. Application examples
On-line quality control, automatically accepting or rejecting items
Process surveillance
Raw materials control based on multiple measurements or sensors (e.g. spectra)
On-Line estimation of parameters that are difficult, time-consuming or expensive to measure
Prediction of moisture, fat etc. in production lines