In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
Modern embedded systems often require high degrees of instruction-level parallelism (ILP) within strict constraints on power consumption and chip cost. Unfortunately, a high-perfo...
We develop an architecture for a product master model that federates CAD systems with downstream application processes for dierent feature views that are part of the design proce...
Multi-core processors, with low communication costs and high availability of execution cores, will increase the use of execution and compilation models that use short threads to e...
Background: Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein ...