— In order for humanoid robots to perform skillful tasks, a reliable and scalable computing system that supports hard real-time processing is required. This paper describes a fiv...
This paper proposes a diagnosis architecture that integrates consistency based diagnosis with induced time series classifiers, trying to combine the advantages of both methods. Co...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
—This paper proposes the energy function of a power system with a Static Synchronous Series Compensator (SSSC). They make it possible for the direct method to acquire the transie...
This paper is concerned with workload minimization in re-entrant lines with exponential service times and preemptive control policies. Using a numerical algorithm called the power...