The study effect Graphene on optical and electrical properties of glass prepared on glass substrates using sol–gel dip-coating technique. The deposited film of about (60-100±5%) nm thick. Optical and electrical properties of the films were studied under different preparation conditions, such as graphene concentration of 2, 4, 6 and 8 wt%. The results show that the optical band gap for glass-graphene films decreasing after adding the graphene. Calculated optical constants, such as transmittance, extinction coefficient are changing after adding graphene. The structural morphology and composition of elements for the samples have been demonstrated using SEM and EDX. The electrical properties of films include DC electrical conductivity; we

The basic concepts of some near open subgraphs, near rough, near exact and near fuzzy graphs are introduced and sufficiently illustrated. The Gm-closure space induced by closure operators is used to generalize the basic rough graph concepts. We introduce the near exactness and near roughness by applying the near concepts to make more accuracy for definability of graphs. We give a new definition for a membership function to find near interior, near boundary and near exterior vertices. Moreover, proved results, examples and counter examples are provided. The Gm-closure structure which suggested in this paper opens up the way for applying rich amount of topological facts and methods in the process of granular computing.

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

Biodiversity, biological diversity, biological diversity, biological diversity, biological diversity, biological diversity, biological diversity (by developmental factors) environmental factors and environmental factors environmental factors and environmental factors and environmental factors Correlation between biology and the succession of geological and historical factors of living organisms and geological and historical factors to the site and what It is surrounded by natural and tourist attractions and the pursuit of scientific methods in order to advance the studies of biological diversity in the region .