Abstract: Health of a person plays a vital role in the collective
health of his community and hence the well-being of the society as a
whole. But, in today’s fast paced technology driven world, health
issues are increasingly being associated with human behaviors – their
lifestyle. Social networks have tremendous impact on the health
behavior of individuals. Many researchers have used social network
analysis to understand human behavior that implicates their social
and economic environments. It would be interesting to use a similar
analysis to understand human behaviors that have health
implications. This paper focuses on concepts of those behavioural
analyses that have health implications using social networks analysis
and provides possible algorithmic approaches. The results of these
approaches can be used by the governing authorities for rolling out
health plans, benefits and take preventive measures, while the
pharmaceutical companies can target specific markets, helping health
insurance companies to better model their insurance plans.
Abstract: In this paper, the decomposition-aggregation method
is used to carry out connective stability criteria for general linear
composite system via aggregation. The large scale system is
decomposed into a number of subsystems. By associating directed
graphs with dynamic systems in an essential way, we define the
relation between system structure and stability in the sense of
Lyapunov. The stability criteria is then associated with the stability
and system matrices of subsystems as well as those interconnected
terms among subsystems using the concepts of vector differential
inequalities and vector Lyapunov functions. Then, we show that the
stability of each subsystem and stability of the aggregate model
imply connective stability of the overall system. An example is
reported, showing the efficiency of the proposed technique.