COVID-19 requires crowded events to enforce restrictions, aimed to contain the spread of the virus. However, we have seen numerous events not observing these restrictions, thus becoming super spreader events. In order to contain the spread of a human to human communicable disease, a number of restrictions, including wearing face masks, maintaining social distancing, and adhering to regular cleaning and sanitization, are critical. These restrictions are absolutely essential for crowded events. Some crowded events can take place spontaneously, such as a political rally or a protest march or a funeral procession. Controlling spontaneous crowded events, like a protest march, political rally, celebration after a sporting event, or concert, can be quite difficult, especially during a crisis like the COVID-19 pandemic. In this article, we review some well-known crowded events that have taken place during the ongoing pandemic. Guided by our review, we provide a framework using machine learning to effectively organize crowded events during the ongoing and for future crises. We also provide details of metrics for the validation of some components in the proposed framework, and an extensive algorithm. Finally, we offer explanations of its various functions of the algorithm. The proposed framework can also be adapted in other crises.

Security of data has always been a contested issue since the internet became the way of life. The internet and Web 2.0 followed by Web 3.0 have enabled many applications for the use of the citizens. E-government is one of them. Questions have always been raised about the security of data in E-government applications and services. Saudi Arabia is one of the developing countries when it comes to the internet-based services. This paper attempts to review the effectiveness of security policies when dealing with threats and vulnerabilities. We shall study these aspects in the context of Saudi Arabian E-government. E-government, anywhere in the world is a very sensitive area when it comes to ensuring security of the users as well as the corporate data. Breach in security of user data may have catastrophic implications in some cases.

Load frequency control (LFC) is one of the most challenging problems in multi-area power systems. In this paper, we consider power system formed of distinct control areas with identical dynamics which are interconnected via weak tie-lines. We then formulate a disturbance rejection problem of power-load step variations for the interconnected network system. We follow a top-down method to approximate a centralized linear quadratic regulator (LQR) optimal controller by a distributed scheme. Overall network stability is guaranteed via a stability test applied to a convex combination of Hurwitz matrices, the validity of which leads to stable network operation for a class of network topologies. The efficiency of the proposed distributed load frequency controller is illustrated via simulation studies involving a six-area power system and three interconnection schemes. In the study, apart from the nominal parameters, significant parametric variations have been considered in each area. The obtained results suggest that the proposed approach can be extended to the non-identical case.

This article is concerned with modelling, controllability analysis and the design of aggressive robust controllers for interconnected electric power systems. The proposed Load Frequency Control (LFC), relying on $H_{\mathrm{\infty }}$ methodologies enhanced with integral action and pole clustering, can provide frequency regulation and fast transient response despite the presence of unknown disturbance load application. The inherent saturation constraints are handled by the combination of a controller gain minimization framework and an anti-windup enhanced controller design which provides stability guarantees, while avoiding frequency and tie-line power oscillations. For this scheme, particular attention should be paid on the modelling and controllability aspects of the power system, where it is shown that due to the singularity of the Laplacian matrix of the network's graph, a reduction of the state vector is necessary. Simulation studies are offered to illustrate the effectiveness of the suggested scheme.