Advances in Nonlinear Complexity Analysis for Partial Differential Equations

1 p. -- [Editorial Material]

Biologically-inspired data decorrelation for hyper-spectral imaging

Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

Complexity of planning in design

Planning in design processes is modeled in terms of connectivities between product developments. Each product development comprises a network of processes. Similarity between processes is analysed by a layered classification ranging from common components to shared design knowledge. The connectivities between products arising from similarities among products are represented by a multidimensional network. Design planning is described by flows or 'traffic' on this network which represents a structural model of complexity. Comparison is made with information based measures of the complexity of designs and processes.

Development of new applications of inductively coupled plasma mass spectrometry (ICP-MS) hyphenated with different sample introduction systems

225 p. : il. Texto en español con conclusiones en inglés