A graph homomorphism is an edge preserving vertex mapping between two graphs. Locally constrained homomorphisms are those that behave well on the neighborhoods of vertices — if the neighborhood of any vertex of the source graph is mapped bijectively (injectively, surjectively) to the neighborhood of its image in the target graph, the homomorphism is called locally bijective (injective, surjecti...

the growing population and increasing socio-economic necessitiescreates a pressure on land use/land cover. nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. this study investigates the land use changes in part of hableh rood watershed of iran using landsat 7 and 8 (sensor etm+ and oli) i...

Graph homomorphism has been studied intensively. Given an m ×m symmetric matrix A, the graph homomorphism function is defined as

The growing population and increasing socio-economic necessities creates a pressure on land use/land cover. Nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. This study investigates the land use changes in part of Hableh Rood Watershed of Iran using Landsat 7 and 8 (Sensor ETM+ and OLI) ...

this paper continues the investigation of the rst author begun in part one. the hereditary properties of n-homomorphism amenability for banach algebras are investigated and the relations between n-homomorphism amenability of a banach algebra and its ide- als are found. analogous to the character amenability, it is shown that the tensor product of two unital banach algebras is n-homomorphism am...

This paper addresses the problem of segmenting dense range data containing curved surfaces. Segmentation is a crucial step in the processing of range data for applications in object recognition, measurement, reengineering and modeling. We propose a two stage process using model-based curvature classification as an initial grouping. Features based on differential geometry, mainly curvature featu...

We address the problem of automating the processing of dense range data, specifically the automated interpretation of such data containing curved surfaces. This is a crucial step in the automated processing of range data for applications in object recognition, measurement, re-engineering and modeling. We propose a two stage process using model-based curvature classification as the first step. F...

Bounds on the range of random graph homomorphism into Z, and the maximal height difference of the Gaussian random field, are presented.