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.
In this work, the photodetection performance of polyvinyl alcohol (PVA) nanofibers and its composite with yttrium oxide (Y2O3) at different concentrations (2.5, 5, 10) wt% are examined deposited on p-type Si with (111) orientation. Electrospinning technique was used to create nanofiber composites. Adding Y2O3 significantly impacts the PVA nanofibers where ultraviolet-visible (UV-Vis) spectroscopy optical absorption energy gap decreases with increased concentration (2.8, 2.6, and 2.3) eV. X-ray diffraction was used to investigate crystal structure, which is cubic structure. The chemical composition study was conducted using Fourier transform infrared spectroscopy (FTIR) spectra, which revealed the stretching vibrations related to the Y-O bon
... Show MoreSpin coating technique used to prepare ZnPc, CdS and ZnPc/CdS blend thin films, these films annealed at 423K for 1h, 2h and 3h. Optical behavior of these films were examined using UV-Vis. and PL. The absorption spectrum of ZnPc shows a decreasing in absorption with the increase of annealing time while CdS spectrum give a clearly absorption peak at~510 nm. Energy gap of ZnPc increases from 1.41 to 1.52 eV by increasing the annealing time. Eg of CdS decrease by increasing annealing time, from 2.3 eV to 2.2 eV. The intensities of the peaks obtained from PL spectra were strongly dependent on annealing time and confirmed the results obtained from UV-Vis. D.C. conductivity measurement showed that all the thin films have two differen
... Show MoreTitanium alloy (Ti-6Al-4V) samples were nitrided in low pressure (1.3, 3 mbar) dc-glow discharge plasmas of nitrogen. The treating time was 5, 10 and 15 hour and the temperatures range of the samples during the nitriding process was close to 800oC. The obtained microstructures of the nitride layers were studied by x-ray diffraction and optical microscopy. The ε –Ti2N, ζ-Ti3N3-x and η-Ti3N2-x.phases were formed and addition to the solid solution of nitrogen in titanium, α (Ti,N). Micro hardness measurements exhibit an increment for the Ti-alloy specimens which nitrided at 800oC for 10 and 15h.Corrosion measurements were obtained for the Ti-6Al-4V alloy in Ringer solution after plasma nitriding. The clear improving in the corrosion r
... Show MoreIn this study many specimen s were prepared from 2024-T3 Aluminum alloy for corrosion test by the dimensions of (15*15*3) mm according to ASTM G71-31 and then subjected to shot peening process at different time (15, 30, 45) minutes using steel ball having a diameter of 2.75 mm and Rockwell Hardness of 55RC to induce compressive residual stress which were measured using X-Ray diffraction method, surface roughness and hardness were tested before and after peening. Electrochemical corrosion test by Tafel extrapolation method was carried out in an environment of 3 .5% NaCl solutions (sea water) where Corrosion rate calculated using Tafle equation.
The obtained results show a favorable influence of SP treatment
... Show MorePreparation and Identification of some new Pyrazolopyrin derivatives and their Polymerizations study
As one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller
... Show MoreWhenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas
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