The Hubble telescope is characterized by the accuracy of the image formed in it, as a result of the fact that the surrounding environment is free of optical pollutants. Such as atmospheric gases and dust, in addition to light pollution emanating from industrial and natural light sources on the earth's surface. The Hubble telescope has a relatively large objective lens that provides appropriate light to enter the telescope to get a good image. Because of the nature of astronomical observation, which requires sufficient light intensity emanating from celestial objects (galaxies, stars, planets, etc.). The Hubble telescope is classified as type of the Cassegrain reflecting telescopes, which gives it the advantage of eliminating chromat

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

Evaluating the behavior of a ring foundation resting on multi-layered soil is one of the important issues facing civil engineers. Many researchers have studied the behavior of ring foundation rests on multi-layered soil with vertical loads acting on the foundation. In real life ring foundation can be subjected to both vertical and horizontal loads at the same time due to wind or the presence of soil. In this research, the behavior of ring footing subjected to inclined load has been studied using PLAXIS software. Furthermore, the effect of multi-layered soil has been simulated in the model. The results showed that both vertical and horizontal stresses are mainly affected when the inclination angle of the load exceeded 45 degrees with a reduc

     A partial temporary immunity SIR epidemic model involv nonlinear treatment rate is proposed and studied. The basic reproduction number  is determined. The local and global stability of all equilibria of the model are analyzed. The conditions for occurrence of local bifurcation in the proposed epidemic model are established. Finally, numerical simulation is used to confirm our obtained analytical results and specify the control set of parameters that affect the dynamics of the model.

Rapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could be one of the possible ways to offset the aggregate shortage problem and reduce environmental pollution. This paper reports an experimental study of unbound granular material using recycled concrete aggregate for pavement subbase construction. Five percentages of recycled concrete aggregate obtained from two different sources with an originally designed compressive strength of 20–30 MPa as well as 31–40 MPa at three particle size levels, i.e., coarse, fine, and extra fine, were test

The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a