Simplification of new fashion design methods

In this work, we introduce a new kind of perfect mappings, namely j-perfect mappings and j-ω-perfect mappings. Furthermore we devoted to study the relationship between j-perfect mappings and j-ω-perfect mappings. Finally, certain theorems and characterization concerning these concepts are studied; j = , δ, α, pre, b, β

Many of the elementary transformations of determinants which are used in their evaluation and in the solution of linear equations may by expressed in the notation of matrices. In this paper, some new interesting formulas of special matrices are introduced and proved that the determinants of these special matrices have the values zero. All formulation has been coded in MATLAB 7.

The crystal structures of a new polymorph and seven new derivatives of 2-(1-phenyl-1H-1,2,3-triazol-4-yl)pyridine have been characterized and examined along with three structures from the literature to identify trends in their intermolecular contact patterns and packing arrangements in order to develop an insight into the crystallization behaviour of this class of compound. Seven unique C-H...X contacts were identified in the structures and three of these are present in four or more structures, indicating that these are reliable supramolecular synthons. Analysis of the packing arrangements of the molecules using XPac identified two closely related supramolecular constructs that are present in eight of the 11 structures; in all cases, the st

New types of hydrodesulfurization (HDS) catalyst Re-Ni-Mo/ γ-Al2O3 was prepared and tested separately with two prepared conventional HDS catalysts (Ni-Mo/ γ-Al2O3 and Co-Mo//γ-Al2O3) by using a pilot plant hydrotreatment unit. Activities of three prepared hydrodesulfurization catalysts were examined in hydrodesulfurization (HDS) of atmospheric gas oil at different temperatures 275 to 350 °C and LHSV 1 to 4 h-1, the reactions conducted under constant pressure 40 bar and H2/HC ratio 500 ml/ml .Moreover, the hydrogenation of aromatic (HAD) in gas oil has been studied. HDS was much improved by adding promoter Re to the Ni-Mo/Al2O3 catalyst. The results showed that Re-Ni-Mo/ γ-Al2O3 have more activity in desulfurization than Ni-Mo//γ-Al2O3

The research addressed an analytical field investigation of the locality of meander, the factors responsible of the locality of the meander at certain points of the stream other than others, and the role sequence of these factors in the formation process.
The research revealed that the location of forming the meander was associated closely with the scale structural composition of the bank materials from which the first stage of forming the curved stream, for the inhomogeneous or non-identical opposite banks in their scale structural composition saw an activity of differential corrosion, while the homogeneous and identical opposite banks in their scale structural composition saw an identical corrosion activity in its intensity at both

New types of hydrodesulfurization (HDS) catalyst Re-Ni-Mo/ γ-Al₂O₃ was prepared and tested separately with two prepared conventional HDS catalysts (Ni-Mo/ γ-Al₂O₃ and Co-Mo//γ-Al₂O₃) by using a pilot plant hydrotreatment unit. Activities of three prepared hydrodesulfurization catalysts were examined in hydrodesulfurization (HDS) of atmospheric gas oil at different temperatures 275 to 350 °C and LHSV 1 to 4 h^-1, the reactions conducted under constant pressure 40 bar and H₂/HC ratio 500 ml/ml .Moreover, the hydrogenation of aromatic (HAD) in gas oil has been studied. HDS was much improved by adding promoter Re to the Ni-Mo/Al₂O₃

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number