Particle swarm optimization (PSO) has become universal due to its simplicity and effectiveness in solving many problems in various applications with low computational cost. This algorithm consumes ...time as dealing with large tasks programs. The main goal of this paper is to introduce a parallel particle swarm optimization (PPSO) on multi-core processing kernel to decrease the determination. In order to ease transfer information among particles of shared area and exchange information by switching randomly. Most of serial PSO algorithms allow updating information among particles which takes a long time during the implementation period. The algorithm was applied to the standard optimization test set CEC (Congress on Evolutionary Computation) 2014 and gave good results compared to the previous algorithm. The empirical results show the execution time of Shared-PSO is more efficient than the serial PSO's. The proposed algorithm using a multicore CPU technique to improve it via parallelization and enhanced the efficiency of an algorithm by increase the range of PSO application.
With a large scope and high degree of complexity, managing megaprojects is often a challenge to many project managers. Many projects fail miserably. Research has shown that success in managing ...megaprojects requires a great deal of coordination and collaboration which can be done through established processes, strong teams, and involvement of stakeholders. Even though these processes and approaches are known, effectively implementing them can be difficult. This study investigates the management of selected mega IS/IT projects in the US, UK, and Australia; identifies common problems; and discusses some lessons learned. Since the literature on megaprojects primarily focuses on major public infrastructure projects, the results of this study will provide significant contributions to the literature and implications to practitioners.
This systematic review and meta-analysis evaluated the extent of sleep disturbances during the COVID-19 pandemic. Eleven databases and six preprint repositories were searched for the period from ...November 1, 2019, to July 15, 2021. The DerSimonian and Laird method was used to develop random-effect meta-analyses. Two hundred and fifty studies comprising 493,475 participants from 49 countries were included. During COVID-19, the estimated global prevalence of sleep disturbances was 40.49% 37.56; 43.48%. Bayesian meta-analysis revealed an odds of 0.68 0.59; 0.77 which translates to a rate of approximately 41%. This provides reassurance that the estimated rate using classical meta-analysis is robust. Six major populations were identified; the estimated prevalence of sleep problem was 52.39% 41.69; 62.88% among patients infected with COVID-19, 45.96% 36.90; 55.30% among children and adolescents, 42.47% 37.95; 47.12% among healthcare workers, 41.50% 32.98; 50.56% among special populations with healthcare needs, 41.16% 28.76; 54.79% among university students, and 36.73% 32.32; 41.38% among the general population. Sleep disturbances were higher during lockdown compared to no lockdown, 42.49% versus 37.97%. Four in every ten individuals reported a sleep problem during the COVID-19 pandemic. Patients infected with the disease, children, and adolescents appeared to be the most affected groups.
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