This research aimed at identifying the factors that affecting in the recruitment of a teaching staff for the Massive Open Online Courses (MOOCs) in university teaching at the University of Khartoum. The descriptive method was followed. The questionnaire was used as a tool for data collection,, which was distributed directly to a sample of (181) respondent of the teaching staff members of the senate at University of Khartoum from those who were attend at the senate meeting No. (409) which was held on 22 August 2016 Of (272). The researcher followed for the distribution the chance method, where each questionnaire was distributed to each of a teaching staff from different faculties at the University of Khartoum, according to his willingness. The data were processed statistically by using appropriate statistical methods. The results showed that the general average of the degree of knowledge that held by teaching staff at Khartoum University on the importance of using. MOOCs in university teaching have reached a moderate agreement degree with an average of 3.39 . The general average of the attitudes of the sample towards the use of the MOOCs in university teaching have reached a moderate degree with an average of 3.44. There are challenges to the work of MOOCs in university teaching in at Khartoum University with a large degree and an average of 4.12.The research concluded with a number of recommendations, the most important are : It is necessary to possess teaching staff the technical skills in dealing with MOOCs. The accreditation of MOOCs as one of the most important techniques innovations in contemporary university educational practice to increase the effectiveness of university teaching as an alternative to traditional methods and indoctrination.
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This work investigates the effect of earthquakes on the stability of a collective pile subjected to seismic loads in the soil layer. Plaxis 3D 2020 finite element software modeled pile behavior in dry soils with sloping layers. The results showed a remarkable fluctuation between the earthquakes, where the three earthquakes (Halabja, El Centro, and Kobe) and the acceleration peak in the Kobe earthquake had a time of about 11 seconds. Different settlement results were shown, as different values were recorded for the three types of earthquakes. Settlement ratios were increased by increasing the seismic intensity; hence the maximum settlement was observed with the model under the effect of the Kobe earthquake (0.58 g), where
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Variation orders are an on-going phenomenon in construction and industry projects worldwide, particularly in the province of Sulaimani, where the project's damage from cost and schedule overrun because of variation orders. However, the effect on project costs and time overrun of variation order has yet to be identified. This study evaluates the impact of variation orders on the cost and time off in the Sulaimani governorate. Two hundred twenty-eight projects from various construction sectors built between 2007-2012 were adopted to calculate the contract cost and schedule overruns due to variation orders. Data analysis was applied in the study were descriptive statistics. One-way ANOVA was also applied to determine w
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Cyclophosphamide which acts as cytotoxic alkylating agent can induce a renal damage through the toxic metabolites which result from metabolic activation of Cyclophosphamide by cytochrome P-450 inside hepatocyte and develop renal toxicity by direct binding with cellular organelles in the urinary tract cells. Guggulsterone is a sterol derived from plant has ability to bind to farsenoid X receptor, mineral corticosteroid receptor, androgen receptor, glucocorticoid receptor and estrogen receptor.
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Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec
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Iron slag is a byproduct generated in huge quantities from recycled remnants of iron and steel factories; therefore, the possibility of using this waste in the removal of benzaldehyde from contaminated water offers an excellent topic in sustainability field. Results reveal that the removal efficiency was equal to 85% for the interaction of slag and water contaminated with benzaldehyde at the best operational conditions of 0.3 g/100 mL, 6, 180 min, and 250 rpm for the sorbent dosage, initial pH, agitation time, and speed, respectively with 300 mg/L initial concentration. The maximum uptake capacity of iron slag was 118.25 mg/g which was calculated by the Langmuir model. Physical sorption may be the major mechanism for the removal of
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The last decade has seen a variety of modifications of glass-ionomer cements (GICs), such as inclusion of bioactive glass particles and dispensing systems. Hence, the aim was to systematically evaluate effect of mixing modes and presence of reactive glass additives on the physical properties of several GICs.
The physical properties of eight commercial restorative GICs; Fuji IX GP Extra (C&H), KetacTM Fill Plus Applicap (C&H), Fuji II LC (C&H), Glass Carbomer Ce
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