Metal insulator transitions in the triclinic reduced Molybdenum oxides.

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Log-Ratio and Parallel Factor Analysis: An Approach to Analyze Three-Way Compositional Data

For the exploratory analysis of three-way data, Parafac/Candecomp model (CP) is one of the most\ud applied models to study three-way arrays when the data are approximately trilinear. It is a three-way\ud generalization of PCA (Principal Component Analysis). CP model is a common name for low-rank\ud decomposition of three-way arrays. In this approach, the three-dimensional data are decomposed into a\ud series of factors, each relating to one of the three physical ways. When the data are particular ratios, as in\ud the case of compositional data, this model should consider the special problems that compositional data\ud pose. The principal aim of this paper is to describe how an analysis of compositional data by CP is possible\ud and how the results should be interpreted

Creation and collaboration: engaging new audiences for information visualization

In recent years we have seen information visualization technology move from an advanced research topic to mainstream adoption in both commercial and personal use. This move is in part due to many businesses recognizing the need for more effective tools for extracting knowledge from the data warehouses they are gathering. Increased mainstream interest is also a result of more exposure to advanced interfaces in contemporary online media. The adoption of information visualization technologies by lay users – as opposed to the traditional information visualization audience of scientists and analysts – has important implications for visualization research, design and development. Since we cannot expect each of these lay users to design their own visualizations, we have to provide them tools that make it easy to create and deploy visualizations of their datasets