The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

In this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.

A new series of metal ions complexes of VO(II), Cr(III), Mn(II), Zn(II), Cd(II) and Ce(III) have been synthesized from the Schiff bases (4-chlorobenzylidene)-urea amine (L1) and (4-bromobenzylidene)-urea amine (L2). Structural features were obtained from their elemental microanalyses, magnetic susceptibility, molar conductance, FT-IR, UV–Vis, LC-Mass and 1HNMR spectral studies. The UV–Vis, magnetic susceptibility and molar conductance data of the complexes suggest a tetrahedral geometry around the central metal ion except, VOII complexes that has square pyramidal geometry, but CrIII and CeIII octahedral geometry. The biological activity for the ligand (L1) and its Vanadium and Cadmium complexes were studied. Structural geometries of com

     Cupressus sempervirens L., Cupressaceae, that is known as evergreen cypress, Mediterranean cypress and in Arabic called “al -Sarw. It is an evergreen, medium sized, longevity, and wide distributed over all the world. The plant represents an important member of conifer plants which characterized with aromatic leaves and cones. Cupressus sempervirens have been ethnobotanical uses as an antiseptic, relief of cough, astringent, antispasmodic, wound healing and anti-inflammatory. Aims of this work are phytochemical analysis, isolation and structural identification of Quercitroside (quercitrin) and essential oil in Iraqi C. sempervirens. Isolation of quercitrin was