A new Azo‐Schiff base ligand L was prepared by reaction of m‐hydroxy benzoic acid with (Schiff base B) of 3‐[2‐(1H–indol‐3‐yl)‐ethylimino]‐1.5‐dimethyl‐2‐phenyl‐2,3‐dihydro‐1H‐pyrazol‐4‐ylamine. This synthesized ligand was used for complexation with different metal ions like Ni(II), Co(II), Pd(II) and Pt(IV) by using a molar ratio of ligand: metal as 1:1. Resulted compounds were characterized by NMR (¹H and ¹³C), UV–vis spectroscopy, TGA, FT‐IR, MS, elemental analysis, magnetic moment and molar conductivity studies. The activation thermodynamic parameters, such as ΔE*, ΔH^*, ΔS^*, ΔG^*and

Diazotization reaction between 1-(2,4,6-Trihydroxy-phenyl)-ethanone and diazonium salts was carried out resulting in ligand 4-(3-Acetyl-2,4,6-trihydroxy-phenylazo)-N-(5-methyl-isoxazol-3-yl)-benzenesulfonamide, this in turn reacted with the next metal ions (V4+ , Cr3+ , Mn2+ and Cu2+) forming stable complexes with unique geometries such as (Octahedral for both Cr3+ , Mn2+ and Cu2+ ,squar pyramidal for V4+). The creation of such complexes was detected by employing spectroscopic means involving ultraviolet-visible which proved the obtained geometries, fourier transfer proved the formation of azo group and and the coordination with metal ion through it. Pyrolysis (TGA & DSC) studies proved the coordination of water residues with me

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

This paper is summarized with one of the applications of adsorption behavior; A UV-Vis method has been applied to survey the isotherm of adsorption. Results for experimental showed the applicability of Langmuir equation. The effect of temperature on the adsorption of cobalt (II) Complex by bentonite surface was studied. The results shown that the amount of adsorption was formed to increase, such as the temperature increase (Endothermic process). Cobalt (II) Complex has adsorption studies by bentonite surface at different pH values (1.6-10); these studies displayed an increase in adsorption with increasing pH. ∆G, ∆H, and ∆S thermodynamic functions of the cobalt (II) Complex for their adsorption have been calculated

In the theoretical part, removal of direct yellow 8 (DY8) from water solution was accomplished using Bentonite Clay as an adsorbent. Under batch adsorption, the adsorption was observed as a function of contact time, adsorbent dosage, pH, and temperature. The equilibrium data were fitted with the Langmuir and Freundlich adsorption models, and the linear regression coefficient R2 was used to determine the best fitting isotherm model. thermodynamic parameters of the ongoing adsorption mechanism, such as Gibb's free energy, enthalpy, and entropy, have also been measured. The batch method was also used for the kinetic calculations, and the day's adsorption assumes first-order rate kinetics. The kinetic studies also show that the intrapar

Steganography is defined as hiding confidential information in some other chosen media without leaving any clear evidence of changing the media's features. Most traditional hiding methods hide the message directly in the covered media like (text, image, audio, and video). Some hiding techniques leave a negative effect on the cover image, so sometimes the change in the carrier medium can be detected by human and machine. The purpose of suggesting hiding information is to make this change undetectable. The current research focuses on using complex method to prevent the detection of hiding information by human and machine based on spiral search method, the Structural Similarity Index Metrics measures are used to get the accuracy and quality

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

Wind energy is one of the most common and natural resources that play a huge role in energy sector, and due to the increasing demand to improve the efficiency of wind turbines and the development of the energy field, improvements have been made to design a suitable wind turbine and obtain the most energy efficiency possible from wind. In this paper, a horizontal wind turbine blade operating under low wind speed was designed using the (BEM) theory, where the design of the turbine rotor blade is a difficult task due to the calculations involved in the design process. To understand the behavior of the turbine blade, the QBlade program was used to design and simulate the turbine rotor blade during working conditions. The design variables suc

2- amino -5- thiol-1,3,4- thiadiazole (S1) was prepared by cyclic locking of thiosemicarbazide in the presence of anhydrous sodium carbonate and CS2. diazotization of (S1) compound gave diazonium salt (S2) that reacts with different activated aromatic compounds to get the following azo compounds ,2 [(4- aminophenyl) diazenyl ] 1,3,4- thiazdiazole-5- thiol (S3) ,2-[4-amino- 1-naphthyl diazenyl] -1,3,4 – thiazdiazole-5-thiol (S4) , 3-amino-4-[(5- mercapto -1,3,4- thiadiazole -2-yl) diazenyl ] phenol(S5) ,1-[(5-mercapto-1,3,4-thiadiazole-2-yl) diazenyl] -2-naphthol (S6) , 5-{[4-(dimethylamino) phenyl] diazenyl}-1,3,4-thiadiazole-2- thiol(S7) ,5-{[4-(diethylamino) phenyl] diazenyl}-1,3,4- thiadiazole-2- thiol(S8) ,2- amino-5-[(5-mercapto-1,3