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.
Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.
This paper proposed a new approach for an underwater visible light communication (UVLC) system using MIMO (2Tx/2Rx) technology. The BER performance, Q-factor, and data rate of the UVLC system are looked at in coastal waters of the Jerov type (J1C, J3C, J5C, J7C, and J9C). The applied system takes into account the angles ranging from 0 to 15° and 45°. The results indicated that 32-PPM outperformed other modulation techniques.
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A factor group is a mathematical group obtained by aggregating similar elements of a larger group using an equivalence relation that preserves some of the group structure. In this paper, the factor groups K(SL(2,121)) and K(SL(2,169)) computed for each group from the character table of rational representations.
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The method of operational matrices is based on the Bernoulli and Shifted Legendre polynomials which is used to solve the Falkner-Skan equation. The nonlinear differential equation converting to a system of nonlinear equations is solved using Mathematica®12, and the approximate solutions are obtained. The efficiency of these methods was studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as increases. Moreover, the obtained approximate solutions are compared with the numerical solution obtained by the fourth-order Runge-Kutta method (RK4), which gives a good agreement.
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Background The Transportation Problem (TP) is a detailed model in operations study with applications in logistics, supply chain management, and resource allocation. The classical IBFS methods including North-West Corner, Least Cost and Vogel’s Approximation have competitive computational efficiency, but they are very sensitive to the structure of the problem and usually lead to a solution that is far from the global optimum. Classic enhancement strategies like the Generalized Distribution (MODI) and Stepping-Stone (SS) approaches have low computational complexity but may fall into a local optimum quickly, which makes them ineffective in large-scale or unbalanced problems. Methods We propose the first generic hybrid algorithm, calle
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