Dimensionality reduction methods are very common in the field of high dimensional data analysis, where the classical analysis methods are inadequate. Typically, algorithms for dimensionality reduction are computationally expensive. Therefore, their applications to process data warehouses are impractical. It is visible even more when the data is accumulated non-stop. In this paper, an out-of-sam...

Many algorithms for graph layout have been devised over the last 30 years spanning both the graph drawing and information visualisation communities. This article first reviews the advances made in the field of graph drawing that have then often been applied by the information visualisation community. There then follows a discussion of a range of techniques developed specifically for graph visua...

With the increasing availability of data from various domains such as health care, finance, social networks, etc. there is a need to provide analytic tools that are more accessible to lay people. In this paper, we present a software tool which can be used to aid inexperienced users in understanding high dimensional data. To facilitate the understanding of such data, we place special emphasis on...

We describe the dimensional reduction of IIB B-fields in F-theory using a conjectured description normalizable terms perverse sheaves. Computations are facilitated Decomposition Theorem. Many our descriptions new, and all results consistent with known physics. also conjecture physical framework for show consistency mathematics.