Power-aware design is one of the most important areas to be emphasized in multimedia mobile systems, in which data transfers dominate the power consumption. In this paper, we propose a new architecture for motion compensation (MC) of H.264/AVC with power reduction by decreasing the data transfers. For this purpose, a reconfigurable microarchitecture based on data type is proposed for interpolation and it is mapped onto the dedicated motion compensation IP (intellectual property) effectively without sacrificing the performance or the system latency. The original quarter-pel interpolation equation that consists of one or two half-pel interpolations and one averaging operation is designed to have different execution control modes, which result in decreasing memory accesses greatly and maintaining the system efficiency. The simulation result shows that the proposed method could reduce up to 87% of power consumption caused by data transfers over the conventional method in MC module.
We examine the optimal intervention of an influence designer in the presence of social learning in a network. Before learning begins, a designer implants opinions into the network to make agents' ultimate opinions as close as to target opinions. By decomposing the influence matrix, which summarizes the learning structure, we transform the designer's problem into one with an orthogonal basis: implanted opinions on one cluster of agents influence only another cluster's opinions with a multiplier effect. This transformation allows us to characterize the optimal intervention under both complete and incomplete information on the network structure.
We develop a model of strategic information transmission from an outside expert with informational superiority to a group of people who make a decision by voting on a proposal. An outside expert who observes the qualities of a proposal sends a cheap talk message to decision makers with limited information. A simple cheap talk strategy of the expert can be surprisingly effective in persuading decision makers by polarizing or unifying their opinions. When there is a significant informational gap, decision makers vote in the expert’s interest by focusing only on the expert’s message, even though they know she has her own bias.
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