Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks

Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of human's physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (facebook, coauthor and email social networks), we find that the excitable senor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods

The numerical operator method to the real time dynamics of currents through the nanostructures with different topologies

We present the numerical operator method designed for the real time dynamics of currents through nanostructures beyond the linear response regime. We apply this method to the transient and stationary currents through nanostructures with different topologies, e.g., the flakes of square and honeycomb lattices. We find a quasi-stationary stage with a life proportional to the flake size in the transient currents through the square flakes, but this quasi-stationary stage is destroyed in the presence of disorder. However, there is no quasi-stationary stage in the transient currents through the honeycomb flakes, showing that the transient current depends strongly upon the topologies of the nanostructures. We also study the stationary current by taking the limit of the current at long times. We find that the stationary current through a square flake increases smoothly as the voltage bias increasing. In contrast, we find a threshold voltage in the current-voltage curve through a honeycomb flake, indicating a gap at the Fermi energy of a honeycomb flake.Comment: 13 pages, 4 figure

Investigating the effect of construction management strategies on project greenhouse gas emissions using interactive simulation

The challenges posed by global climate change are motivating the investigation of strategies that can reduce the life cycle greenhouse gas (GHG) emissions of products and processes. While new construction materials and technologies have received significant attention, there has been limited emphasis on understanding how construction processes can be best managed to reduce GHG emissions. Unexpected disruptive events tend to adversely impact construction costs and delay project completion. They also tend to increase project GHG emissions. The objective of this paper is to investigate ways in which project GHG emissions can be reduced by appropriate management of disruptive events. First, an empirical analysis of construction data from a specific highway construction project is used to illustrate the impact of unexpected schedule delays in increasing project GHG emissions. Next, a simulation based methodology is described to assess the effectiveness of alternative project management strategies in reducing GHG emissions. The contribution of this paper is that it explicitly considers projects emissions, in addition to cost and project duration, in developing project management strategies. Practical application of the method discussed in this paper will help construction firms reduce their project emissions through strategic project management, and without significant investment in new technology. In effect, this paper lays the foundation for best practices in construction management that will optimize project cost and duration, while minimizing GHG emissions