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.

Results of a study of alloys and films with various Pb content have been reported and discussed. Films of of thickness 1.5 μm have been deposited on glass substrates by flash thermal evaporation method at room temperature, under vacuum at constant deposition rate. These films were annealed under vacuum around 10⁻⁶Torr at different temperatures up to 523 K. The composition of the elements in alloys was determined by standard surfaces techniques such as atomic absorption spectroscopy (AAS) and X-ray fluorescence (XRF), and the results were found of high accuracy and in very good agreement with the theoretical values. The structure for alloys and films is determined by using X-ray

A progression of Polyaniline (PANI) and Titanium dioxide (TiO₂) nanoparticles (NPs) were prepared by an in-situ polymerization strategy within the sight of TiO₂ NPs. The subsequent nanocomposites were analyzed using Fourier-transform infrared spectra (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-Ray Analysis (EDX) taken for the prepared samples. PANI/TiO₂ nanocomposites were prepared by various compound materials (with H₂SO₄ 0.3 M and without it, to compare the outcome of it) by the compound oxidation technique using ammonium persulfate (APS) as oxidant within the sight of ultrafine grade powder of TiO₂ cooled in an ice bath.

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

Roller-Compacted Concrete (RCC) is a zero-slump concrete, with no forms, no reinforcing steel, no finishing and is wet enough to support compaction by vibratory rollers. Because the effectiveness of curing on properties and durability, the primary scope of this research is to study the effect of various curing methods (air curing, emulsified asphalt(flan coat) curing, 7 days water curing and permanent water curing) and different porcelanite (local material used as an Internal Curing agent) replacement percentages (volumetric replacement) of fine aggregate on some properties of RCC and to explore the possibility of introducing more practical RCC for road pavement with minimum requirement of curing. Cubes specimens were sawed from the slab

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

Concrete pavements are essential to modern infrastructure, but their low tensile and flexural strengths can cause cracking and shrinkage. This study evaluates fiber reinforcement with steel and carbon fibers in various combinations to improve rigid pavement performance. Six concrete mixes were tested: a control mix with no fiber, a mix with 1% steel fiber (SF1%), a mix with 1% carbon fiber (CF1%), and three hybrid mixes with 1% fiber content: 0.75% steel /0.25% carbon fiber (SF0.75CF0.25), 0.25% steel /0.75% carbon fiber (SF0.25CF0.75), and 0.5% steel /0.5% carbon fiber ((SF0.5CF0.5). Laboratory experiments including compressive, flexural, and splitting tensile strength tests were conducted at 7, 28, and 90 days, while Finite Element Analys