Artificial Neural Networks for Prediction of COVID-19 in Saudi Arabia

In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. The performance of the proposed model has been analyzed by the root mean squared error (RMSE) function, and correlation coefficient (R). Furthermore, we tested the proposed model using other existing data recorded in Saudi Arabia (testing data). It is demonstrated that the MLPNN-PPA model has the highest performance in predicting the number of infected and recovering in Saudi Arabia. The results reveal that the number of infected persons will increase in the coming days and become a minimum of 9789. The number of recoveries will be 2000 to 4000 per day.     

Window flow control in computer communication networks

Computer communication networks are basically resource sharing systems and are used for an efficient exchange of information among remote users. Performance (throughput, delay and power) of a computer network depends upon the intensity of data and/or information traffic. If a network's traffic is allowed to increase beyond certain limits, its performance rapidly degrades. In order to keep data traffic under control, some restrictions are applied at various levels of computer communication networks. These restrictions are usually referred to as flow control techniques.

This paper deals with window (also called end-to-end or entry-to-exit) flow control in computer communication networks. In this method, a source node is allowed to have only a limited number of unacknowledged messages, usually termed as “window size”, at a time. Flow control, in this paper, is discussed in the context of three computer communication switching techniques: packet switching, virtual cut-through switching and quasi cut-through switching. The analysis of window flow control is based upon simulation of a typical store-and-forward computer network. Several simulation results are presented to illustrate the effects of window flow control on various computer communication switching techniques.     

Liquid‐Phase Aerobic Oxidation of Benzyl Alcohol Catalyzed by Pt/ZrO2

The oxidation of benzyl alcohol by molecular oxygen in the liquid phase and catalyzed by Pt/ZrO2 using n‐heptane as the solvent was studied. Pt/ZrO₂ was very active and 100 % selective for benzyl alcohol conversion to benzaldehyde. The catalyst can be separated by filtration and reused. No leaching of Pt or Zr into the solution was observed. Typical batch reactor kinetic data were obtained and fitted to the Langmuir‐Hinshelwood, Eley‐Rideal and Mars‐van Krevelen models of heterogeneously catalyzed reactions. The Langmuir‐Hinshelwood model was found to give a better fit. The rate‐determining step was proposed to involve direct interaction of an adsorbed oxidizing species with the adsorbed reactant or an intermediate product of the reactant. H₂O₂ was also proposed to be an intermediate product. n‐Heptane was found to be an appropriate solvent in this reaction system.     

Glyceride studies. V. The distribution of unsaturated acyl groups in vegetable triglycerides

The distribution of oleic, linoleic, linolenic, petroselinic, hexadec-9 and 11-enoic, sterculic, four conjugated octadecatrienoic acids, isolinolenic, and octadeca-6,9,12,15-tetraenoic acid in vegetable triglycerides has been studied by hydrolysis with pancreatic lipase. The results, discussed in terms of a selectivity factor, indicate that these unsaturated acids do not compete equally for the secondary hydroxyl group.     

Advanced Friction–Wear Behavior of Organic Brake Pads Using a Newly Developed System

The objective of this study was to investigate the influence of an advanced performance system on the tribological behavior of brake pad material using a specially designed brake pad tester system following standard SAE J-661. The tribological behavior and friction and wear characteristics of the organic brake pad samples were evaluated. During braking tests, the samples, in contact with a cast iron disk, were studied at different disc speeds, temperatures, and braking cycles under a constant pressure. In order to understand the friction and wear behavior, the unworn surfaces, worn surfaces, and wear debris were characterized by means of scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). Furthermore, the surface characteristics and differences in the wear modes of the brake pad samples were examined. Wear debris was permitted to deform the brake pad surfaces, leading to friction layers and enabling the estimation of the friction behavior of the brake pads. The results showed that the best friction–wear behavior was obtained with lower braking cycles at low speeds and temperature. Thus, the newly developed brake pad tester system proved very effective in evaluating the performance of the brake pad samples.     

Novel Analytical Thermal Performance Rate Analysis in ZnO-SAE50 Nanolubricant: Nonlinear Mathematical Model

The investigation of local thermal transport rate in the nanolubricants is significant. These lubricants are broadly used in environmental pollution, mechanical engineering and in the paint industry due to high thermal performance rate. Therefore, thermal transport in ZnO-SAE50 nanolubricant under the impacts of heat generation/absorption is conducted. The colloidal suspension is flowing between parallel stretching disks in which the lower disk is positioned at z = 0 and upper disk apart from distance d. The problem is transformed in dimensionless version via described similarity transforms. In the next stage, an analytical technique (VPM) is implemented for the solution purpose. The graphical results against multiple flow parameters were furnished over the region of interest and explained comprehensively. It is imperative to mention that the results are plotted for ZnO-SAE50 and conventional liquid as well. Further, rapid motion of the fluid is perceived against high Reynolds and γ parameters. The wall shear stresses at the upper end rises for multiple Reynolds and γ while; decrement is detected at the lower end. The significant contribution of an internal heat source is noted for thermal performance rate at the upper end. Foremost, the local heat transport rate declines at the lower disk. By altering Reynolds number, prompt heat transfer rate is gained at the upper disk and increasing behavior of the local heat transport rate is slow at the lower disk. From the study, it is concluded that the nanolubricants have high thermal characteristics. Therefore, such fluids are reliable to use in above stated areas.     

Analysis of Silver Nanoparticles in Engine Oil: Atangana–Baleanu Fractional Model

The present article aims to examine the heat and mass distribution in a free convection flow of electrically conducted, generalized Jeffrey nanofluid in a heated rotatory system. The flow analysis is considered in the presence of thermal radiation and the transverse magnetic field of strength B₀. The medium is porous accepting generalized Darcy’s law. The motion of the fluid is due to the cosine oscillations of the plate. Nanofluid has been formed by the uniform dispersing of the Silver nanoparticles in regular engine oil. The problem has been modeled in the form of classical partial differential equations and then generalized by replacing time derivative with Atangana–Baleanu (AB) time-fractional derivative. Upon taking the Laplace transform technique (LTT) and using physical boundary conditions, exact expressions have been obtained for momentum, energy, and concentration distributions. The impact of a number of parameters on fluid flow is shown graphically. The numerical tables have been computed for variation in the rate of heat and mass transfer with respect to rooted parameters. Finally, the classical solution is recovered by taking the fractional parameter approaching unity. It is worth noting that by adding silver nanoparticles in regular engine oil, its heat transfer rate increased by 14.59%, which will improve the life and workability of the engine.     

Dual Branches of MHD Three-Dimensional Rotating Flow of Hybrid Nanofluid on Nonlinear Shrinking Sheet

In this study, magnetohydrodynamic (MHD) three-dimensional (3D) flow of alumina (Al₂O₃) and copper (Cu) nanoparticles of an electrically conducting incompressible fluid in a rotating frame has been investigated. The shrinking surface generates the flow that also has been examined. The single-phase (i.e., Tiwari and Das) model is implemented for the hybrid nanofluid transport phenomena. Results for alumina and copper nanomaterials in the water base fluid are achieved. Boundary layer approximations are used to reduce governing partial differential (PDEs) system into the system of the ordinary differential equations (ODEs). The three-stage Lobatto IIIa method in bvp4c solver is applied for solutions of the governing model. Graphical results have been shown to examine how velocity and temperature fields are influenced by various applied parameters. It has been found that there are two branches for certain values of the suction/injection parameter b: The rise in copper volumetric concentration improved the velocity of hybrid nanofluid in the upper branch. The heat transfer rate improved for the case of hybrid nanofluid as compared to the viscous fluid and simple nanofluid.