We have studied the effect of applying an external magnetic field on the characteristics of iron oxide (IO) nanoparticles (NPs) synthesized by pulsed laser ablation in dimethylformamide (DMF). The NPs synthesized with and without applying of magnetic field were characterized by Fourier transformation infrared spectroscopy (FT-IR), UV–Vis absorption, scanning electron microscope (SEM), atomic force microscope (AFM), and X-ray diffraction (XRD). SEM results confirmed that the particle size was decreased after applying magnetic field.

TiO2 thin films were deposited by reactive d.c magnetron sputtering method on a glass substrate with various ratio of gas flow (Oxygen /Argon) (50/50, 100/50 and 150/50) at substrate temperature 573K. It can be observe that the optical energy gap of TiO2 thin films dependent on the ratio of gas flow (oxygen/argon), it varies between (3.45eV-3.57eV) also it is seen that the optical constants (α, n, K, εr and εi ) has been varied with the change of the ratio of gas flow (Oxygen /Argon).

Heavy metal consider as major environmental pollutants. Many of industrial wastewater effluents contain a wide range of these heavy metals. The adsorption of Cd2+ and Pb2+ metal ions from aqueous solution by activated carbon was studied. The results showed that maximum adsorption capacity occurred at 486.9×10-3 mg/kg for Pb2+ ion and 548.8×10-3 mg/kg for Cd2+ ion. The adsorption in a mixture of the metal ions had a balancing effect on the adsorption capacity of the activated carbon. The adsorption capacity of each metal ion was affected by the presence of other metal ions rather than its presence individually. The study showed the presence of other heavy metals attribute to the reduction in the activated carbon capacity, and the adsorp

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a