Abstract. This paper underscores the potency of invariant character tensor and its derivative concepts accentuate synergy between isotropic other tensors corresponding vector operations. The equivalence covariant in a curvilinear coordinates system embedded with non-constant field partial an affine ingrained constant is interrogated. role Christofell symbols as connector vectors their derivativ...

in this paper we present some results about subgroup which is generalization of the subgroup $r_{2}^{otimes}(g)={ain g|[a,g]otimes g=1_{otimes},forall gin g}$ of right $2_{otimes}$-engel elements of a given group $g$. if $p$ is an odd prime, then with the help of these results, we obtain the results about tensor squares of p-groups satisfying the law $[x,g,y]otimes g=1_{otimes}$, for all $x, g,...

This paper establishes some perturbation analysis for the tensor inverse, Moore-Penrose and system based on t-product. In settings of structured perturbations, we generalize Sherman-Morrison-Woodbury (SMW) formula to t-product scenarios. The SMW can be used perform sensitivity a multilinear equations.

hydrogen bonding of dppe with water that surrounded of membrane, plays an important role in permeability ofmembrane that we were presented this matter with analysis of bond angles and torsion angles before and after ofadded water molecules.interaction with water molecules causes some changes in the geometry of dppe which were explained bythe contribution of zwitterionic form of dppe molecule, a...

We propose a method for visualizing two-dimensional symmetric positive definite tensor fields using the Heat Kernel Signature (HKS). The HKS is derived from the heat kernel and was originally introduced as an isometry invariant shape signature. Each positive definite tensor field defines a Riemannian manifold by considering the tensor field as a Riemannian metric. On this Riemmanian manifold we...

a new and significant source of information on earthquake studies has been provided by space geodesy. the data which are gathered by various techniques of space geodesy, can quantify potential of seismic activity in the region of interest. to achieve this goal, the main advantage of extra-terrestrial geodetic data in comparison with the conventional data from geology and seismology is the abili...

unlike the classical deformation analysis of the earth crust, which derives the planar and vertical strains separately, in this study, we have offered a method for 3-d deformation study based on intrinsic geometry of the manifolds on the topographic surface of the earth. in this way, our method would be based on the 2-d metric tensor of horizontal deformation and 2-d curvature tensor of vertica...

Tensor decomposition is a powerful tool for multiway data analysis. Many popular tensor decomposition approaches—such as the Tucker decomposition and CANDECOMP/PARAFAC (CP)—conduct multi-linear factorization. They are insufficient to model (i) complex interactions between data entities, (ii) various data types (e.g. missing data and binary data), and (iii) noisy observations and outliers. To ad...

The moving objectives’ images are in tensor format in reality. That using for reference the thought of tensor space dimension reduction to gain the optimal gait characters with low dimension inaugurate a new gait recognition way. A novel gait expression and recognition algorithm based on the tensor space is introduced here. It is a tensor space learning algorithm that could investigate the inhe...