Draft of Win ISI diagram

Working on the main diagram of Win ISI for a presentation. This is a draft and I have to add more tools from new versions.

 

Diagnostics : Peak to Peak (P2P)

Is the way we can see if we have extreme peaks on the noise spectra (like in this case due to encoder noise).

It is the absolute value between the absorbance in the highest peak and the absorbance in the lowest peak.

The manufacturers fix this value according to the  quality of the instrument components.

PUZZLE: Spectra Reconstruction

I use to explain the concept of the spectra reconstruction as trying to fix a puzzle. We have the pieces ( loadings) which once are multiplied by the scores have difference sizes, but the same pattern.





We fit all the pieces, but it can be that the puzzle does not fit correctly, that we have some gaps or spaces not filled,...., etc. is the concept of spectra reconstruction whe we have a error matrix which is the part of the puzzle not completed. It can be small, large,...

One application of this concept is used to define if the spectra belongs to a certain category.

In this blog you will find post about the spectra reconstruction.

Sub-sample and sub-scan concept

When we analyzed heterogeneous samples, it is normal to use large cups. The cups rotate and stops in certain places called sub-samples (suppose eight). At each sub-sample several sub-scans (normally  four) are acquired.

So we have eight sub-samples spectra composed of the average of four sub-scans each. In total we have thirty two scans.

We can get a prediction of each of the sub-samples to get the eight predictions and calculate the standard deviation for every constituent in order to see the heterogeneity of the sample composition.

We can export the average spectrum of all the sub-samples,  the eight spectra of the eight sub-samples or the thirty two total sub-scans for further study.

 

Thanks a lot (more than 250.000 visits to this blog)

Thanks to all of you who read and follow this blog. We have pass the 250.000 visits in this Blog Life and I really happy about that.

 

Of course these are the main countries who visit the Blog, but I appreciate visits from many other places.

                  thanks so much



Maximum Distance (Discriminate Method)

I wrote in other posts, about the Maximum Distance algorithm, in order to discriminate products. In resume is the spectra of a set of samples for training, where we apply a math treatment, and calculate the standard deviation at each wavelength (s), in order to fit some limits to the spectra (will be added to the average spectrum). Therefore, the new samples should come into the defined limits in order to be classify as a sample of this group.

Therefore, in the areas of the spectra where there are more variability, the limits will be higher than in the area of lower variability.

We can see first the spectra (gray ones) with the mat treatment applied and draw the average spectrum (red one):

 

 and to over plot  the standard deviation spectra at each wavelength (green one) with the average spectrum (red one), in order to imagine how the limit will fit.

 

I will try to work on it exporting in Excel the spectra to show you better in a new post.



 

How to load the Check Sample product in MOSAIC

On the DSs or DAs, the check sample comes with a USB pen with some files (DA1650, DS2500 and DS2500F) with the extension  "mcf". If we import a this files into Mosaic we will install the parameter, prediction model and check cell product at the same time, so it is not necessary to go step by step, so it is more quick to have the instrument ready to analyze the Check Sample.

 

Go  to your Network, right clic with the mouse and choose "Import instrument group configuration". Open in Explorer the adequate "msc" file on the USB pen drive and the configuration will be loaded and ready to work in NOVA if we use  Mosaic Solo, or after synchronization, if we use Mosaic Network.