The optimum separators operating pressure is determined by using flash calculations and equilibrium ratios. In this study, the optimum separator size for Jambur field is calculated by using equations introduced by Arnold and Stewart and API12J Specification [1]. Because Jambur field has a high production rate two conditions are taken in the study to determine separator size, first based on production rate 80,000 bbl/day and second based on split the production between two banks A and B (40,000 bbl/day for each bank). The calculation resulted in optimum separator pressure for the first stage of 700 psi, and the second stage of 300 psi, and the third stage of 120 psi. The results show that as the number of stages increased above three

This study synthesized zeolite 4A, and hierarchical composite structure consisting of zeolite 4A- carbon were successfully prepared. Hydrothermal method was used to grow a layer of zeolite 4A over porous carbon surfaces to enhance mass transfer and increase surface area of zeolite. The products then were used to remove radioactive cesium¹³⁷Cs from liquid wastewater. Iraqi dates leaves midribs (DM) were used as locally available agricultural waste to prepare low- cost porous carbon, using carbonization method in tubular furnace at 900C for two hours. Hierarchical porous structures including zeolite are prepared by mechanically activating the carbon surface via Ultrasonicating nanoparticles suspension of ground zeolite type 4A.F

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

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

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

This work reports the development of an analytical method for the simultaneous analysis of three fluoroquinolones; ciprofloxacin (CIP), norfloxacin (NOR) and ofloxacin (OFL) in soil matrix. The proposed method was performed by using microwave-assisted extraction (MAE), solid-phase extraction (SPE) for samples purification, and finally the pre-concentrated samples were analyzed by HPLC detector. In this study, various organic solvents were tested to extract the test compounds, and the extraction performance was evaluated by testing various parameters including extraction solvent, solvent volume, extraction time, temperature and number of the extraction cycles. The current method showed a good linearity over the concentration ranging from

Formation of emulsions during oil production is a costly problem, and decreased water content in emulsions leads to increases productivity and reduces the potential for pipeline corrosion and equipment used. The chemical demulsification process of crude oil emulsions is one of the methods used for reducing water content. The demulsifier presence causes the film layer between water droplets and the crude oil emulsion that to become unstable, leading to the accelerated of water coalescence. This research was performed to study the performance of a chemical demulsifier Chimec2439 (commercial) a blend of non-ionic oil-soluble surfactants. The crude oils used in these experiments were Basrah and Kirkuk Iraqi crude oil. These

The current trend worldwide is searching plant extracts towards prevention of neurodegenerative disorders. This study aimed to investigate the neuroprotective effect of Alpinia galanga leaves (ALE), Alpinia galanga rhizomes (ARE), Vitis vinifera seeds (VSE), Moringa oleifera leaves (MLE), Panax ginseng leaves (PLE) and Panax ginseng rhizomes (PRE) ethanolic extracts on human neuroblastoma (SHSY5Y) cells. The 1‐diphenyl‐1‐picrylhydrazyl (DPPH) radical scavenging of VSE and MLE were 81% and 58%, respectively. Ferric‐reducing antioxidant power (FRAP) of ALE and MLE (33.57 ± 0.20 and 26.76 ± 0.30 μmol Fe(ΙΙ)/g dry wt., respectively) were higher than for the other extracts. Liquid chromatography coupled to quadrupole time‐of‐fli

The acidity of spent lubricant was treated using sodium hydroxide solution. The effect of three variables on the treatment have been studied . These are mixing time rangingfrom 5-35 minutes, NaOH to lubricant weight ratio ranging from  0.25-1.25 and weight percentage  of NaOH ranging from  2-6 % .

The experimental design of Box-Wilson method is adopted to find a useful relationship between the three controllable variables and the lowering in the acidity of the spent lubricant. Then the effective variables and interactions are identified using the statistical analysis(F-test) of  three variable fractional design. The mathematical model is well represented  by a second order polynomial.

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