This research includes synthesis of some new thiourea derivatives by two route, the first route include synthesis of 1-aroyl-3-aryl thiourea derivatives (1-17) by a reaction of substituted carboxylic acids with thionyl chloride then the resultant compounds treated the result with potassium thiocyanate to afford the corresponding 1-aroyl isothiocyanate which react directly with primary and secondary aryl amines. The second route, bromo benzene was allowed to react with potassium thiocyanate to afford the corresponding phenylisothiocyanate which was directly reacted with primary and secondary aryl amines to yield 1-phenyl-3-aryl thiourea derivatives (18- 28).The purity of the synthesized compounds were checked by measuring the melting point,Thin Layer Chromatography (TLC) and their structure, were identified by spectral methods [FTIR,1 H-NMR and 13C-NMR].furthermore, these compounds were investigated as corrosion inhibitors for carbon steel at 303 K in 1M H2SO4 solution by using weight loss method, the results showed that maximum inhibition efficiency of some 1-aroyl-3-aryl thiourea derivatives and 1-phenyl-3-aryl thiourea derivatives are ranging between (83-94) %.
Hand-lay up method was used to prepare the samples made of epoxy (EP) as a matrix reinforced with chopped carbon fibers (CCF). The fatigue behavior of epoxy resin /chopped carbon fiber composites was studied with different weight percentage of chopped carbon fibers (2.5%,5%,7.5%,10%,12.5%). The fatigue test was carried out under alternate bending method, which was made by applying sinusoidal wave with constant displacement (15mm), stress ratio R=-1,and loading frequency 10Hz, which is believed to give a negligible temperature rise during the test. The results of the maximum stress, fatigue strength, fatigue limit and fatigue life of the tested composites are calculated from stress(S)-number of cycles(N) (S-N) curves.
It was shown that
This paper is mainly concerned with the study of the moral aspects that prompts William Shakespeare to attempt a romance in which he has embedded the epitome of his thought, experience, and philosophy concerning certain significant aspects of human life whose absence or negligence may threaten human existence, peace, and stability. From the beginning of history man realizes the importance of prosperity on the many and various levels that touch and address his needs and desires—natural, material, and spiritual. The Tempest, due to the dramatist's awareness of the aforementioned values, reflects the dramatist's duty as to projecting and unfolding these important aspects, rec
... Show MoreThis paper is mainly concerned with the study of the moral aspects that prompts William Shakespeare to attempt a romance in which he has embedded the epitome of his thought, experience, and philosophy concerning certain significant aspects of human life whose absence or negligence may threaten human existence, peace, and stability. From the beginning of history man realizes the importance of prosperity on the many and various levels that touch and address his needs and desires—natural, material, and spiritual. The Tempest, due to the dramatist's awareness of the aforementioned values, reflects the dramatist's duty as to projecting and unfolding these important aspects, reconciliation and forgiveness, that promote prosperity which is th
... Show MoreImage 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
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
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The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita
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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
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This study includes adding chemicals to gypseous soil to improve its collapse characteristics. The collapse behavior of gypseous soil brought from the north of Iraq (Salah El-Deen governorate) with a gypsum content of 59% was investigated using five types of additions (cement dust, powder sodium meta-silicate, powder activated carbon, sodium silicate solution, and granular activated carbon). The soil was mixed by weight with cement dust (10, 20, and 30%), powder sodium meta-silicate (6%), powder activated carbon (10%), sodium silicate solution (3, 6, and 9%), and granular activated carbon (5, 10, and 15%). The collapse potential is reduced by 86, 71, 43, 37, and 35% when 30% cement dust, 6% powder sodium meta-silicate, 10% powder activated
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The nonlinear refractive (NLR) index and third order susceptibility (X3) of carbon quantum dots (CQDs) have been studied using two laser wavelengths (473 and 532 nm). The z-scan technique was used to examine the nonlinearity. Results showed that all concentrations have negative NLR indices in the order of 10−10 cm2/W at two laser wavelengths. Moreover, the nonlinearity of CQDs was improved by increasing the concentration of CQDs. The highest value of third order susceptibility was found to be 3.32*10−8 (esu) for CQDs with a concentration of 70 mA at 473 nm wavelength.