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In this paper we propose a new approach to design of DRT models which considers DRT as a multi-agent system (MAS) where various autonomous agents represent interests of system's stakeholders.
Study-specific RRs were combined using the DerSimonian and Laird (1986) random-effects models, which considers both within- and between-study variations.
This leads to the expanding vision for fair monetary and non-monetary incentive models, which considers innovative approaches to monetary compensation, and much more purposeful investment in human resources, including continuing education, skills-training, and career ladders that honour the individual's desire to grow in their role, and move into other forms of employment.
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Most of the models are reduced-form models, which consider only one or two parameters.
The existing literature lacks such models, which consider all of these stakeholders in a single model.
We have used mathematical models which consider susceptible, exposed, infectious, and removed people.
The review revealed that there are only few models, which consider logistics hubs in general.
These models, which considered stress sensitivity, were based on fractal theory and the mechanics of materials.
The works in [3 5] propose models which consider fluid torques, where drag forces and torques are evaluated numerically.
The additive interference models, which consider the sum of interferences, are more accurate but require more computational effort.
Finally, the described control strategy may be extended to more complex epidemical models which consider more population categories than the presented SIRS model.
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