This search reports the synthesis of some new series of Schiff base compounds for trimetheprim derivatives which known high been known as a medicinal effectiveness. Trimetheprim was condensed with several substituted aldehydes compounds.(4-dimethyl amine benzaldehyde , propanal , salicaldehyde, 2.4 dimethoxy benzaldehyde and 4- methyl benzaldehyde) to obtain Schiff base products(1a-5a) and several substituted ketones compound (4-aminoacetophenone,4-chloroacetophenone, isobutyleketone, acetylacetone and acetophenone) to obtain Schiff base products(6b-10b) in ethanol in the presence of concentrated sulphuric acid as a catalyst to yield the Schiff base. The structure of synthesized compounds has been established on the basis of their Chemical

Derivatives of Schiff-bases possess a great importance in pharmaceutical chemistry. They can be used for synthesizing different types of bioactive compounds. In this paper, derivatives of new Schiff bases have been synthesized from several serial steps. The acid (I) was synthesized from the reaction of dichloroethanoic acid with 2 moles of p-aminoacetanilide. New acid (I) converted to its ester (II) via the reaction of (I) with dimethyl sulphate in the present of anhydrous of sodium carbonate and dry acetone. Acid hydrazide (III) has been synthesized by adding 80% of hydrazine hydrate  to the new ester using ethanol as a solvent. The last step included the preparation of new Schiff-bases (IV-VIII) by the reaction of acid hydrazide with

 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

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

KE Sharquie, AA Noaimi, MS Abass, American Journal of Dermatology and Venereology, 2019 - Cited by 4

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