The research aims at measuring the impact of visual media on the development of the tourism services sector, which is a field study for the public. It aims at determining the impact of visual media on tourism sector development, clarifying the concept of visual media and its functions and studying the role of media in the development of tourism culture among the public. For a sample of the employees of the University of Baghdad, consisting of (120) male and female. A questionnaire was prepared for this purpose consisting of (21) questions distributed to the sample. The data were analyzed and the hypotheses were tested using the statistical program spss to unload the results and calculate the frequencies, percentages and correlation coefficients. The research reached several results, the most important of which is that the sample is influenced by the visual media, , And the presence of the intensity of the impact of visual media at the level of knowledge of the public, it is clear through the existence of high averages in the responses of the sample, and there is a very strong link between the follow-up media and tourism tourism decision to make tourism, The hypothesis of the existence of differences between the demographic variables of the sample and the impact of the visual media in the field of tourism, and prove the hypothesis that there are differences between the sample averages to the impact of media in the tourism sector.
In this study, a low-cost biosorbent, dead mushroom biomass (DMB) granules, was used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physicochemical parameters, such as initial metal ion concentration, equilibrium time, pH value, agitation speed, particles diameter, and adsorbent dosage, were studied. Five mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich-Peterson, Sips, and Khan models. The best fit to the Pb(II) and Ni(II) biosorption results was obtained by Langmuir model with maximum uptake capacities of 44.67 and 29.17 mg/g for these two ions, respectively, w
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A series of new Schiff bases and 1, 3-Oxazepine derivatives have been synthesised from condensation compound (1,1 -bis (4-aminophenyl) -4-phenyl cyclohexane [C1] with different aromatic aldehydes in the presence of catalytic glacial acetic acid to produce the Schiff bases [2-4]. These Schiff bases were reacted with maleic anhydride and phthalic anhydride in dry benzene to give seven-membered heterocyclic ring derivatives [5-10]. The structure formula of these compounds were confirmed by using FT-IR, (1H and 13C) NMR spectroscopy. The synthesized compounds were screened for their anti‐bacterial activity using ampicillin as a standard drug.
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ABSTRACT. A new three metal complexes of La(III), Ce(IV) and UO2(II) ions have been synthesized based on a Schiff base derived from the condensation of L-histidine and anisaldehyde. All prepared compounds were characterized by different spectroscopic techniques and Density-functional theory (DFT) calculations. The complexes were proposed to have an octahedral structure based on the investigated results. The optimized shape, numbering system, and dipole moment vector of Ligand and La, Ce, and UO2 (1:1) chelates were investigated. The Schiff base ligand and complexes exhibit moderate action against all of the bacteria tested, with P. aeruginosa, Klebsiella sp., and E. faecalis respectively being the order of inhibition.
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The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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