22 jun. 2017

How to check the cooling liquid - NIRS™ DS2500


Filter Replacement - NIRS™ DS2500


Lamp Replacement - NIRS™ DS2500


Instrument Calibration - NIRS™ DS2500


Checking Temperatures in DS2500 (Lamp)



 
In order that the performance of the instrument DS2500 be optimal, we have to attend the temperature of the lamp when running the diagnostics. I consider it is fine around 35ºC.
Sometimes we find high temperatures like the one in the picture, and even seeing that the report says that is OK, this temperature can affect to the instrument itself and the results.
One of the causes that this temperature increase is that the tank of the pump has lost water, so it is a good idea to check the level, and fill it in if necessary.

Checking pump level video
Check that the pump is pumping. We should see some turbulences in the water and a small noise in the pump.
Check if the water is to dirty, or with algae’s.
Check that the fan is working, its mission is to keep cold the water and see if the filter is clean so the fan performs better its mission.

Changing the filter

It is important also the temperature of the room or laboratory where the instrument is. A higher temperature will increase also the lamp temperature.

After checking all this points, and being sure that the lamp is fine, maybe is the moment to run an instrument calibration:

Instrument Calibration

 

19 jun. 2017

Comparing Residuals, GH and T when validating


When looking to the validation statistics is important to look at the same time to three values: Residual, GH and T value for every sample. From this data (fiber), we can check if our sample is extrapolating badly, it is not robust or any other issues.

In this case, as we can see there are samples with a very high GH and we can see that those samples have in common that the T statistic is negative (in the left tail of the Gaussian Bell) and the value is quite high also for the T.
These samples have also the highest residiual values.
 Something is telling us that this samples have something special and are not well represented by the equation. PCA is warking fine and is detecting these samples as outliers, but we need to know what makes tese samples special.

These samples are soy meal and have  highest fat value as the ones in the calibration so the Model did not learn enough about the interaction between the fiber bands and fat bands. So this samples are very interested to make the calibtration more robust.

After checking this, we can add these samples to the calibration to improve the results of the next validation.

 
Graphically in Excel we can se the interaction between the Residuals, GHs and T values:
 

22 may. 2017

Mosaic 7.12 is now available on our Europe server


Mosaic version 7.12 is now available on our Europe server.
Once you try to connect, you should be asked to automatically download and install the new client.
User accounts, passwords remain the same.

Ports used for NOVA:
 
Configure correctly the ports with your IT for a successful synchonization.

7 may. 2017

Easy way to check the eigen values with the T (scores) matrix

Other interesting Matrix multiplication is the product of the score matrix T by it´s transpose in this way:

Tt%*%T

This product give us a square matrix (a.a), being “a” the number of loadings or PCs chosen, and the diagonal has the eigenvalues which are related to the quantity of explained variance for every loading.

If we plot the diagonal we can see how the eigenvalue decrease by every loading. This plot can help us to decide how many loadings or PCs to choose.

Add caption
 

6 may. 2017

Checking the orthogonality of P (loadings) matrix

One of the values we got in the script of the post:"Tutorials with Resemble (Part 3 - orthoProjection) " was the loadings matrix (X.loadings), or what we called usually in this blog the P matrix.

One of the characteristics of the loadings “P” matrix, when we develop the PCA, is that if we multiply it by its transpose we get the Identity Matrix “I”

P<-X.loadings

Pt<-t(X.loadings)

 
P%*%Pt = I

 
In the “I” matrix, its diagonal is “1”, and “0” values for all the rest cells indicating that all the loadings are orthogonal between them.

Exercise:
  • Check it by yourself and take out the diagonal from the P matrix.
  • Represent in a graphic the first loadings:
    • 1 vs 2      : a plane
    • 1, 2 and 3: a cube
 

19 abr. 2017

How to load a REP file in a MOSAIC LOCAL Prediction Model

If we use the MONITOR in Win ISI or a LOCAL Prediction Model in ISI Scan, there is a field to load the REP file (is a ".nir" which include the variation we want to minimize in the model, like the temperature, differences between instruments, differences between the pathlengths of the gold reflectors,….). This way the LOCAL uses the REP file when developing the calibration.

In MOSAIC the REP file must be load in a different way.

As usual we load the ".RED" file, reduced with the appropriate math-treatment, we set the maximum and minimum number of factors and samples,...., but where I load the repeatability file (.NIR) .

😏...Easy but tricky.

Rename the extension from the repeatability file from ".NIR" to ".REP", and give to this file the same name than the ".RED" file; put them both in the same folder. Now when you import the ".RED" file to the LOCAL Prediction Model, the ".REP" file will go with it. Just check it on the Links tab of the LOCAL P.M.
 
As you know something similar happens when whe load a ".EQA" and load also the ".PCA" and ".LIB" files

Thanks to Montse for testing this feature...😉