The current research aims to reveal the reality of coping the scientific research in Omani universities in the Sultanate of Oman with the requirements of the Fourth Industrial Revolution in the light of Oman’s 2040 vision. It also aims derive some suggestions to develop the scientific research in these institutions. The study has adopted a qualitative approach in which interviews were conducted. The sample consisted of (16) leaders of governmental and private higher education institutions, as well as, some experts in the field of Fourth Industrial Revolution. The theoretical significance of the study is represented by its response to Oman’s vison in 2040. It is further in line with the previous international reports and educational s

This paper includes simulating an electron gun design to investigate the effect of the distance between the cathode and the Wehnelt cylinder bore on the quality of the ion beam emittance and to obtain the best distance of that geometrical factor. A study of a group of designs was conducted to find this distance. The SIMION8.0 program has been used to calculate the trajectories of the electrons with initial kinetic energy of (0.1 eV) and electron current of (1×10-12 A). The investigation also includes comparisons between the equipotential line trajectories for each design as well as the field distribution and the electron trajectories. The best emittance distance was concluded to be (3 mm).

Elastic electron scattering form factors, charge density distributions and charge,
neutron and matter root mean square (rms) radii for P
24
PMg, P
28
PSi and P
32
PS nuclei are
studied using the effect of occupation numbers. Single-particle radial wave functions
of harmonic-oscillators (HO) potential are used. In general, the results of elastic
charge form factors showed good agreement with experimental data. The occupation
numbers are taken to reproduce the quantities mentioned above. The inclusion of
occupation numbers enhances the form factors to become closer to the data. For the
calculated charge density distributions, the results show good agreement with
experimental data except the fail to

The influence of solar activity on the predicted ionospheric temperature parameters (electron Te, Ion Ti and neutral particle Tn) have been investigated over ionospheric Iraqi region by data generated using International Reference Ionosphere (IRI) and Madrigal models, the models result have been compared during the minimum and the maximum of solar cycle 24 for the years 2009 and 2016 respectively and for an altitudes ranged from 200-1000 km. The region under consideration spans over (latitude 29.1-37.2oN; longitude 38.9-47.7oE) within Iraq territory, the purpose of this paper is to determine the affection of the solar activity represented by the (sunspot number and solar flux) on the annual behavio

Spin 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. E_g 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

  This paper deals with proposing new lifting scheme (HYBRID Algorithm) that is capable of preventing images and documents which are fraud through decomposing there in to the real colors value arrays (red, blue and green) to create retrieval keys for its properties and store it in the database and then check the document originality by retrieve the query image or document through the decomposition described above and compare the predicted color values (retrieval keys)  of the query document with those stored in the database. The proposed algorithm has been developed from the two known lifting schemes (Haar and D4) by merging them to find out HYBRID lifting scheme. The validity and accuracy of the proposed algorithm have been ev

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121