Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
The study aimed at identifying the strategic gaps in the actual reality of the management of public organizations investigated to determine the strategy used based on the study model. The study relied on the variable of the general organization strategy in its dimensions (the general organization strategy, the organization's political strategy and the defense strategy of the organization) The sample of the study was (General Directorate of Traffic, Civil Status Directorate and Civil Defense Directorate), formations affiliated to the Ministry of the Interior, for the importance of the activity carried out by these public organizations by providing them In order to translate the answers into a quantitative expression in the analysi
... Show MoreIn this publication, several six coordinate Co(III)-complexes are reported. The reaction of 2,3-butanedione monoxime with ethylenediamine or o-phenylenediamine in mole ratios of 2:1 gave the tetradentate imine-oxime ligands diaminoethane-N,N`-bis(2-butylidine-3-onedioxime) H2L1 and o-phenylenediamine-N,N`-bis(2-butylidine-3-onedioxime), respectively. The reaction of H2L1 and H2L2 with Co(NO3)2, and the amino acid co-ligands (glycine or serine) resulted in the formation of the required complexes. Upon complex formation, the ligands behave as a neutral tetradantate species, while the amino acid co-ligand acts as a monobasic species. The mode of bonding and overall geometry of the complexes were determined through physico-chemical and spectro
... Show MoreWith the study of synthesizing new organic compounds and exploring biological potency. Aryldiazenyl derivatives (2-5) were carried out by coupling of diazonium salt of 4-aminoacetophenone (1) and miscellaneous active methylene compounds such as: acetylacetone, ethyl cyanoacetate, dimedone or methyl acetoacetate. Moreover substituted 1,2,3-triazole (7-9) were synthesized by the cyclization of 1-(4-azidophenyl) ethanone (6); (which was obtained by coupling of diazonium salt (1) with sodium azid); with acetylacetone, methyl acetoacetate or methyl cyanoacetate, respectively. The structures of the prepared compounds were promoted by IR, H1NMR and UV/Visible spectra. Further, they were examined in vetro for antibacterial activity against five str
... Show MoreIn this work, ZnO quantum dots (Q.dots) and nanorods were prepared. ZnO quantum dots were prepared by self-assembly method of zinc acetate solution with KOH solution, while ZnO nanorods were prepared by hydrothermal method of zinc nitrate hexahydrate Zn (NO3)2.6H2O with hexamethy lenetetramin (HMT) C6H12N4. The optical , structural and spectroscopic properties of the product quantum dot were studied. The results show the dependence of the optical properties on the crystal dimension and the formation of the trap states in the energy band gap. The deep levels emission was studied for n-ZnO and p-ZnO. The preparation ZnO nanorods show semiconductor behavior of p-type, which is a difficult process by doping because native defects.
The preparation of the phenanthridine derivative compound was achieved by adopting an efficient one-pot synthetic approach. The condensation of an ethanolic mixture of benzaldehyde, cyclohexanone and ammonium acetate in a 2:1:1 mole ratio resulted in the formation of the title compound. Analytical and spectroscopic techniques were used to confirm the nature of the new compound. A mechanism for the formation of the phenanthridine moiety that is based on three steps has been suggested
In this work, composite materials were prepared by mixing different concentrations of ferrites with polyacrylonitrile (PAN) polymer. Using the electrospinning technique, these composites were deposited on a p-type silicon wafer. The prepared samples demonstrated nanofibers in both pure PAN polymers and their composites with ferrite. Prior to examining the humidity sensing effectiveness with a percentage of relative humidity at a frequency of 10 kHz, based on ambient temperature and a relative humidity range of 50–100%, the composite nanofibers demonstrated stronger humidity sensing compared to the pure PAN nanofibers, which demonstrated a powerful resistance response. More precisely, the PAN@ferrite nanocomposite showed a broad adsorption
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