Electrospinning is a novel technique that can be used to produce highly porous fibers with highly tunable properties. In this research, this technique is adopted to prepare the electrospun nanofiber membrane for membrane distillation application. A custom-built electrospinning setup was made to prepare the nanofibers membrane. Polyvinylidene fluoride (PVDF) polymer was used in the electrospinning process due to its high hydrophobicity. Electrospun (PVDF) nanofibers were tested in direct contact membrane distillation (DCMD) process using 0.6 M sodium chloride as a feed solution. The resulting nanofiber membrane exhibited high performance in DCMD (i.e. relatively high water flux and high salt rejection). It has been found that the prepared membrane has a uniform and fibrous structure as indicated by the scanning electron microscopy (SEM). Relatively thin fibers with a diameter of 250 nm were produced during the Electrospinning process.
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Investigation of the adsorption of acid fuchsin dye (AFD) on Zeolite 5A is carried out using batch scale experiments according to statistical design. Adsorption isotherms, kinetics and thermodynamics were demonstrated. Results showed that the maximum removal efficiency was using zeolite at a temperature of 93.68751 mg/g. Experimental data was found to fit the Langmuir isotherm and pseudo second order kinetics with maximum removal of about 95%. Thermodynamic analysis showed an endothermic adsorption. Optimization was made for the most affecting operating variables and a model equation for the predicted efficiency was suggested.
With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. T
... Show MoreAlthough the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t
... Show MoreThe purpose of this paper to discriminate between the poetic poems of each poet depending on the characteristics and attribute of the Arabic letters. Four categories used for the Arabic letters, letters frequency have been included in a multidimensional contingency table and each dimension has two or more levels, then contingency coefficient calculated.
The paper sample consists of six poets from different historical ages, and each poet has five poems. The method was programmed using the MATLAB program, the efficiency of the proposed method is 53% for the whole sample, and between 90% and 95% for each poet's poems.
XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.