The atom-bond connectivity index of graph is a topological index proposed by Estrada et al. as ABC (G)  uvE (G ) (du dv  2) / dudv , where the summation goes over all edges of G, du and dv are the degrees of the terminal vertices u and v of edge uv. In the present paper, some upper bounds for the second type of atom-bond connectivity index are computed.

– We use a Gaussian radial basis kernel function to map pairs of feature vectors from a sample into a fuzzy connectivity matrix whose entries are fuzzy truths that the vector pairs belong to the same classes. To reduce the matrix size when the data set is large, we obtain a smaller set of representative vectors to form a smaller matrix. To this end we first group the feature vectors into many s...

We proposed a watermarking for 3D polygonal meshes using normal vector distribution of each patch. The distribution of norm vector for 3D polygonal mesh is a consistent factor to be robust against various attacks such as af£ne transform and mesh connectivity altering. Therefore, the proposed algorithm embedded watermark into these consistent normal vectors and equal watermark bit was embedded i...

let $g=(v,e)$ be a connected graph. the eccentric connectivity index of $g$, $xi^{c}(g)$, is defined as $xi^{c}(g)=sum_{vin v(g)}deg(v)ec(v)$, where $deg(v)$ is the degree of a vertex $v$ and $ec(v)$ is its eccentricity. the eccentric distance sum of $g$ is defined as $xi^{d}(g)=sum_{vin v(g)}ec(v)d(v)$, where $d(v)=sum_{uin v(g)}d_{g}(u,v)$ and $d_{g}(u,v)$ is the distance between $u$ and $v$ ...

if we think of the graph as modeling a network, the vulnerability measure the resistance of the network to disruption of operation after the failure of certain stations or communication links. many graph theoretical parameters have been used to describe the vulnerability of communication networks, including connectivity, integrity, toughness, binding number and tenacity.in this paper we discuss...

Using directed transfer function (DTF) and partial coherence (PDC) in the information version, this paper extends theoretical framework to incorporate instantaneous Granger causality (iGC) frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC’s repercussions associated with connectivity, where interactions mediate...

Functional connectivity using resting-state fMRI has emerged as an important research tool for understanding normal brain function as well as changes occurring during brain development and in various brain disorders. Most prior work has examined changes in pairwise functional connectivity values using a multi-variate classification approach, such as Support Vector Machines (SVM). While it is po...

Recently there has been an increased interest in using fMRI data to study the dynamic nature of brain connectivity. In this setting, the activity in a set of regions of interest (ROIs) is often modeled using a multivariate Gaussian distribution, with a mean vector and covariance matrix that are allowed to vary as the experiment progresses, representing changing brain states. In this work, we in...