The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
This study was conducted to identify the impact of germination in the ratio Almaah of Chemical Constituents of Homs and in the organoleptic properties of the Biskt plant it and compare the results with the treatment control (seeds Almnepth) Adhrt results for a significant increase in the percentage of crude protein with the progress of the process of germination, reaching 24.5% in percentage of crude protein with the progress of the germination process Krbu hydrate college during the germination period, reaching 59.2% in the fourth day
The presence of residual antibiotics in water results in the development of antibiotics resistant genes. The available wastewater treatment systems are not capable of removing such antibiotics from sewage. Thus, antibiotics need to be removed before the discharge of wastewater. Adsorption is among the promising techniques for the wastewater treatment to aid the removal of a wide range of organic and inorganic pollutants. The present work is a contribution to the search for an economical method for the removal of low concentrations of amoxicillin (AMX) from water by adsorption on water treatment residue, WTR, taken from a local drinking water facility. The chemical composition and the adsorptive characteristics of the material were first
... Show MoreThe effect of mixed corrosion inhibitors in cooling system was evaluated by using carbon steel specimens and weight loss analysis. The carbon steel specimens immersed in mixture of sodium phosphate (Na2 HPO4) used as corrosion inhibitor and sodium glocunate (C6 H11 NaO7) as a scale dispersant at different concentrations (20,40, 60, 80 ppm) and at different temperature (25,50,75 and 100)ºC for (1-5) days. The corrosion inhibitors efficiency was calculated by using uninhibited and inhibited water to give 98.1%. The result of these investigations indicate that the corrosion rate decreases with the increase the corrosion inhibitors concentration at 80 ppm and at 100ºC for 5 days, (i.e,
... Show MoreThe present study aimed to identify the extent to which the content of social and national studies courses was included in interactive thinking maps in the educational stages in the Kingdom of Saudi Arabia, and to achieve the goal of the study, the researcher used the descriptive and analytical approach, and the study tool used consisted of a content analysis card; Where it included a list of the types of thinking maps, where the study sample consisted of all social and national studies courses at the elementary and intermediate levels, and it is (12) books for the student in its first and second parts, and after verifying the validity and reliability of the tool, it was applied to the study sample, and the study reached conclusions, inc
... Show MoreExperimental model was done for pile model of L / D = 25 installed into a laminar shear box contains different saturation soil densities (loose and dense sand) to evaluate the variation of pore water pressure before and after apply seismic loading. Two pore water pressure transducers placed at position near the middle and bottom of pile model to evaluate the pore water pressure during pullout tests. Seismic loading applied by uniaxial shaking table device, while the pullout tests were conducted through pullout device. The results of changing pore water pressure showed that the variation of pore water pressure near the bottom of pile is more than variation near the middle of pile in all tests. The variation of pore water
... Show MoreA new benzylidene derivative, namely N-benzylidene-5-phenyl-1,3,4-thiadiazol-2-amine (BPTA), has been synthesized and instrumentally confirmed with Elemental Analysis (CHN), Nuclear Magnetic Resonance (NMR), and Fourier Transform Infrared Spectroscopy (FT-IR). Titanium Dioxide (TiO2) nanoparticles (NPs) were synthesized and characterized by X-ray. The mutualistic complementary dependence of BPTA with TiO2 nanoparticles as anti-corrosive inhibitor on mild steel (MS) in 1.0 M hydrochloric acid has been tested at various concentrations and various temperatures. The methodological work was achieved by gravimetric measurement methods complemented with surface analysis. The synthesized inhibitor concentrations were 0.1 mM to 0.5 mM and the temper
... 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
... 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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