The work includes synthesis and characterization of some new heterocyclic compounds, as flow: The compound (3) (5-(4-chlorophenyl) -2-hydrazinyl-1,3,4-oxadiazole was synthesized by using two methods; the first method includes the direct reaction between hydrazine hydrate 80% and 5-(4-chlorophenyl)-2- (ethylthio) 1,3,4-oxadiazole (1), the second method involves converting 5-(4-chlorophenyl)-1,3,4-oxadiazol-2-amine (2) to diazonium salt then reducing this salt to compound (3) by stannous chloride. Compound (3) was used as starting material for synthesizing several fused heterocyclic compounds. The compound 6-(4- chlorophenyl)[1,2.4] triazolo [3,4,b][1,3,4] oxadiazole-3-(2H) thione (compound 4) was synthesized from the reaction of compound (3) with carbon disulfide in presence of potassium hydroxide. Compound 6-(4-chlorophenyl)-[1,2,4] triazolo [3,4-b][1,3,4] oxadiazole-3-amine (5) was synthesized from treatment of compound (3) with cyanogen bromide at room temperature in the presence of sodium hydrogen carbonate. Direct reaction between acetic acid and compound (3) in POCl3 affords 6-(4-chlorophenyl)-3-methyl-[1,2,4] triazolo [3,4,b][1,3,4] oxadiazole (compound 6). Five new fused rings derivatives (12-16) [6-(4- chlorophenyl)-3-(aryl)-[1,2,4] triazolo[3,4-b][1,3,4]oxadiazol] were synthesized by two steps. The first step was synthesized by corresponding Schiff bases (7-11) from reaction compound (3) with five aryl aldehyde. These Schiff bases were used as substrate to synthesize compounds (12-16) by treating these compounds with bromine in glacial acetic acid in dry sodium acetate.The synthesized compounds were characterized by FTIR,H-NMR,C-NMR and CHNS analysis.
Several azo dyes were synthesized through coupling reaetion of some substituted phenols and B.naphthol with diazonium salt of 2- amino-1,3-4- thiadiazol -5- thiol. All the synthesized compounds during this work were characterized using some speetral data (F.TIRand UV)andM.P . 2-[4 --Hydroxy napthyl-azo ] -1,3,4-Thiadiazol -5-Thiol • 2- [2-- hydroxy –4- NO2 – phenyl- azo]- 1,3,4 - Thiadiazol –5-Thiol. • 2- [3--Amino-4-Hydroxy phenyl –azo]-1,3,4 - Thiadiazol –5-Thiol. . • 2-[2--Amino-4-Hydroxy phenyl -azo]-1,3,4 - Thiadiazol –5-Thiol . • 2- [3--Amino-6- Hydroxy phenyl -azo]-1,3,4 - Thiadiazol –5-Thiol. • 2-[2-- Hydroxy- 5 – chloro – Pheny - azo]- 1,3,4 - Thiadiazol –5-Thiol . • 2- [4-- Hydroxy phenyl -azo] -1,
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WKAJ Khalifa E. Sharqui1,*, Adil A. Noaimi2, Ali R. Auda3, American Journal of Dermatology and Venereology, 2014 - Cited by 1
This work includes the synthesis and identification of ligand {3-((4-acetylphenyl)amino)-5,5-dimethylcyclohex2-en-1-one} (HL* ) by the treatment of 5,5-dimethylcyclohexane-1,3-dione with 4-aminoacetophenone under reflux. The ligand (HL* ) was identified via FTIR, Mass spectrum, elemental analysis (C.H.N.), 1H and 13C-NMR spectra, UV-Vis spectroscopy, TGA and melting point. The complexes were synthesized from ligand (HL* ) mixed with 3-aminophenol (A) and metal ion M(II), where M(II) = (Mn, Co, Ni, Cu, Zn and Cd) at alkaline medium to produce complexes of general formula [M(L* )(A)] with (1:1:1) molar ratio. These complexes were detected via FT-IR spectra, UV-Vis spectroscopy as well as elemental analysis (A.A) and melting point, conductivit
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor
... Show MoreSecure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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