The simultaneous generation of dust during the deposition of semiconducting thin films by radio frequency plasma enhanced chemical vapor deposition has so far been regarded as a troublesome by-product. However, we present results from recent microstructural investigations of carbonaceous dust particles from a methane precursor that demonstrate that the technique may be suited to generating full...

This paper presents work done to improve the representation in European decision support tools of physico-chemical forms of radiocontaminants released to the atmosphere from a major nuclear power plant accident. The task is to accommodate those types of scenarios where fuel particles are at play. A methodology with associated parameters has been developed to improve modelling of the aerodynamic...

Linear discriminant analysis (LDA) is a classical statistical approach for dimensionality reduction and classification. In many cases, the projection direction of the classical and extended LDA methods is not considered optimal for special applications. Herein we combine the Partial Least Squares (PLS) method with LDA algorithm, and then propose two improved methods, named LDA-PLS and ex-LDA-PL...

Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) problem in traditional LDA. When applied to face recognition under varying lighting conditions and different facial expressions, neither method may work robustly due to limited number of training samples for each class in the train...