During this decade, it has been observed that many realworld graphs, like the web and some social and metabolic networks, have a scale-free structure. These graphs are characterized by a big variability in the arity of nodes, that seems to follow a power-law distribution. This came as a big surprise to researchers steeped in the tradition of classical random networks. SAT instances can also be ...

We propose a new statistical approach for characterizing the class separability degree in . This approach is based on a nonparametric statistic called “the Cut Edge Weight”. We show in this paper the principle and the experimental applications of this statistic. First, we build a geometrical connected graph like Toussaint’s Relative Neighbourhood Graph on all examples of the learning set. Secon...

Let G be a graph. Assume that l and k are two natural numbers. An l-sum flow on a graph G is an assignment of non-zero real numbers to the edges of G such that for every vertex v of G the sum of values of all edges incident with v equals l. An l-sum k-flow is an l-sum flow with values from the set {±1, . . . ,±(k − 1)}. Recently, it was proved that for every r, r > 3, r 6= 5, every r-regular gr...

We present an analytical approach to calculating the distribution of shortest paths lengths (also called intervertex distances, or geodesic paths) between nodes in unweighted undirected networks. We obtain very accurate results for synthetic random networks with specified degree distribution (the so-called configuration model networks). Our method allows us to accurately predict the distributio...

We consider the problem that on large random geometric graphs, random walk-based distances between nodes do not carry global information such as cluster structure. Instead, as the graphs become larger, the distances contain mainly the obsolete information of local density of the nodes. Many distances or similarity measures between nodes on a graph have been proposed but none are both proved to ...

Visualization technology has been extensive used in various fields which makes the information presented in a visual way. Visualization directly improves the cognitive efficiency of information, greatly reduces the complexity of data understanding, and breaks through the limitation of the traditional statistical analysis method. The automatic placement of nodes and edges in the network graph ha...

The proliferation of business intelligence applications moves most organizations into an era where data becomes an essential part of the success factors. More and more business focus has thus been added to the integration and processing of data in the enterprise environment. Developing and maintaining Extraction-Transform-Load (ETL) processes becomes critical in most data-driven organizations. ...

In this paper signal flow graph non-linear modeling of cascade buck converters is presented. Unified signal flow graph model of the converter is developed and then deduction of large, small-signal and steadystate models from the unified graph is demonstrated. Converter performance expressions are derived. Largesignal model is developed and programmed in TUTSIM simulator. Large-signal responses ...