Many applications rely heavily on large amounts of data in the distributed storages collected over time or produced by large scale scientific experiments or simulations. The key co...
Many image processing and computer vision applications have difficulty dealing with a nonstatic background such as water waves, but this particular dynamic scene actually contains...
In this study, we propose the use of specialized influence models to capture the dynamic behavior of a Network-onChip (NoC). Our goal is to construct a versatile modeling framewor...
Collapsed Gibbs sampling is a frequently applied method to approximate intractable integrals in probabilistic generative models such as latent Dirichlet allocation. This sampling ...
Transmitting compressed data can reduce inter-processor communication traffic and create new opportunities for DVS (dynamic voltage scaling) in distributed embedded systems. Howe...