This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

Heavy metals contamination in aquatic ecosystems is considered one of the most important threats of aquatic life. Submerge aquatic plants Ceratophyllum demersum in its non living form used for the removal of trace elements. This article studied the ability of the fine powder of C.demersum for the removal of some heavy metals (HM) like copper, cadmium, lead and chrome from aqueous solution with in variable experimental factors. The study occupy two treatments the first included different hydrogen ions pH within a range of 4, 5,6and 8 with a constant HM concentration (1000 ppm).While the second treatment represented by using variable HM concentrations within a range of (250,500,750and 1000 ppm) with a constant pH=7.In both treatments the a

The snthesis and characterization of cobalt(II), nickel(II), copper(II) and zinc(II) complexes of azo ligand 4-[(5-acetyl-2-aminophenyl)- diazenyl]-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one derived from 4-aminoantipyrine and 4-aminoacetophenone are reported. The nature of the compounds have been studied followed by mole ratio and methods of continuous contrast, Beer′s law followed during a condensation rate (1 × 10-4 – 3 × 10-4 M). The analytical data showed that all the complexes are in 1:2 metal-ligand ratio. An octahedral geometry have been suggested for all the compounds and biological studies of all the complexes were evaluated against different types of antimicrobial strains.

The effect of ozone gas with temperatures 35. 40 and 45 Celsius to control on larval and adult stages of Tribolium castaneum was tested and at time of exposure 1.0, 3.0, 7.0, 9.0, 11.0, 13.0 hours and the level of relative humidity prevailing during the test 45 ± 1%. Results showed significant differences between the exposure times, when the percentage of mortality 100% between larvae (primary, intermediate and advanced) in the treatment effect at a temperature of 35 Celsius with ozone gas at exposure time to 9.0, 11.0, 11.0 hours for the three ages respectively, and adult (male and female) in the same treatment when the three heat degrees had given ratios the total mortality reached 100% of both males at exposure time to 7.0 ,3