Near infrared (NIR) spectroscopy is a non-destructive detection technology involving NIR
spectral data acquisition and chemometric treatment. The use of an NIR spectrometer is …

Deep convolution neural network (CNN) with one-dimensional (1D) convolution structure is
a potential and effective nonlinear method for near infrared (NIR) spectroscopy analysis …

To deal with the typically insufficiently labeled samples involved in practical spectroscopy
measurements, a conditional variational autoencoder (CVAE) is proposed to guide the …

Unfolding is a pretreating operation in most existing batch process modeling methods, but it
would destroy the essential structure of the raw data. Also, the number of estimated …

It is particularly important to test the quality of diesel oil. In order to improve the reliability and
rapidity of the determination, a novel CC-tSNE-SVR model combined with near infrared …

To measure the moisture content of granules during the industrial fluidized bed drying (FBD)
process, a semi-supervised calibration model is proposed for using the near-infrared (NIR) …

For using infrared spectroscopy to conduct in-situ measurement of slurry component
concentrations during batch crystallization or fermentation process in engineering practice, a …

For in-situ measurement of the granule moisture content (MC) during a fluidized bed drying
(FBD) process by using the near-infrared (NIR) spectroscopy, a novel spectral calibration …

Transferring an existing marketed pharmaceutical product from batch to continuous
manufacturing (CM) without changes in regulatory registration is a challenging task in the …

Real-time monitoring of critical quality attributes, such as residual water in granules after
drying which can be determined through loss-on-drying (LOD), during wet granulation and …