In this research, a new 1, 3, 4-Thiadiazole derivatives have been synthesized by many heterocyclic reactions. Starting from (2, 5 – dimercapto -1, 3, 4-Thiadiazole) a variety of derivatives have been synthesis. Compound (1) was synthesized by the reaction of hydrazine hydrate with carbon disulphide in absolute ethanol. The compound (1) was reacted with 1, 2-dibromoethane in presence of alkali ethanol to give the compound (2). The compound (3) was formed from the reaction of compound (2) with hydrazine hydrate. Schiff base (4) was obtained by reacting of compound (3) with the compound (p-hydroxybenzaldehyde) in absolute ethanol. A variety of phenolic Schiff base (Methylolic, Etheric, and Epoxy) derivatives have been synthesized. Methylol

Synthesis of a new class of Schiff-base ligand with a tetrazole moiety to form polymeric metal complexes with Co^II, Ni^II, Zn^II, and Cd^II ions has been demonstrated. The ligand was synthesised by a multi-steps by treating 5-amino-2-chlorobenzonitrile and cyclohexane -1,3-dione, the 5,5'-(((1E,3E)-cyclohexane-1,3-diylidene)bis(azanylylidene))bis(2-chlorobenzonitrile) was obtained. The precursor (M) was prepared  from the reaction 5,5'-(((1E,3E)-cyclohexane-1,3-diylidene)bis(azanylylidene))bis(2-chlorobenzonitrile) with NaN₃ to obtained (1E,3E)-N¹,N³-bis(4-chloro-3-(1H-tetrazol-5-yl)phenyl)cyclohexane-1,3-diimine (N). By reacting the precursor (M) with CS₂

The synthesized ligand [4-chloro-5-(N-(5,5-dimethyl-3-oxocyclohex-1-en-1-yl)sulfamoyl)-2-((furan-2-ylmethyl)amino)benzoic acid] (H2L1) was identified utilizing Fourier transform infrared spectroscopy (FT-IR), 1 H, 13 C – NMR, (C.H.N), Mass spectra, UVVis methods based on spectroscopy. To detect mixed ligand complexes, analytical and spectroscopic approaches such as micro-analysis, conductance, UV-Visible, magnetic susceptibility, and FT-IR spectra were utilized. Its mixed ligand complexes [M(L1)(Q)Cl2] [ where M= Co(II), Ni(II) , and Cd(II)] and complexes [Pd(L1)(Q)] and [Pt(L1)(Q)Cl2]; [H2L1] =β-enaminone ligand =L1 and Q= 8-Hydroxyquinoline = L2]. The results showed that the complexes were synthesised utilizing the molar ratio M: L1

The aldol condensation of 2-acetylnaphthalene with 9-anthracene carboxaldehyde afforded α, β-unsaturated keton (1) . New heterocyclic compounds containing: cyclohexenone[2], indazole[3], pyrimidinethion [4], thiazolo fused pyrimidine[5], isoxazoline[6], substituted pyrazoline[7]a-d and pyrimidinone[8] rings system were synthesized from α, β-unsaturated keton[1]. Cyclization of [1] with ethylacetoacetate gave the mentioned heterocycle cyclohexanone [2]. The cyclo condensation of [2] with hydrazine gave the new indazole derivative [3]. furthermore, the reation of [1]with thiourea gives thiopyrmidine derivative [4]. The cyclo condensation of [4] with chloroacetic acid gave the fused rings [5]. Then reacted compound[1] with hydroxy

The research seeks to study the subject (Media separation: the Relationship of Arab Immigrants with the Media of the Countries of Diaspora/ Sweden as a model). Where this phenomenon, "problem" has not been subjected to an in-depth study to find out the causes of this media separation and its repercussions on the immigrant, whether in the problem of integration, or his opportunity to work, or adapt to live in the new society.

Separation is a kind of word that is rarely used in Arabic media studies, relevant, sometimes, to the meaning of “refraining from watching TV or listening to the radio or reading newspapers”. Sometimes, it means “not tuning to or using any form of media like radios or newspapers to be updated about what

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Recently, numerous the generalizations of Hurwitz-Lerch zeta functions are investigated and introduced. In this paper, by using the extended generalized Hurwitz-Lerch zeta function, a new Salagean’s differential operator is studied. Based on this new operator, a new geometric class and yielded coefficient bounds, growth and distortion result, radii of convexity, star-likeness, close-to-convexity, as well as extreme points are discussed.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class