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Full-Text Articles in Engineering
Optical Processors For Smart Structures, Barry G. Grossman, Howard Hou, Ramzi H. Nassar
Optical Processors For Smart Structures, Barry G. Grossman, Howard Hou, Ramzi H. Nassar
Electrical Engineering and Computer Science Faculty Publications
For underwater fiber-optic sensor arrays containing hundreds of sensors as well as smart aerospace structures and skins using fiber-optic strain sensor arrays, the output of the sensors are optical signals that are a function of the measurand. We are also employing optical signals to energize smart-structure actuators (shape-memory alloys). An all-optical processor would thus seem to be logical choice for the processor since we must simultaneously process, in real time, multiple optical input (sensor) signals and generate multiple output (actuator) signals. In addition, with an all-optical processor, there would be no reduction in processor performance due to converting between optical …
Neural Networks In Manufacturing: Possible Impacts On Cutting Stock Problems, Cihan H. Dagli
Neural Networks In Manufacturing: Possible Impacts On Cutting Stock Problems, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The potential of neural networks is examined, and the effect of parallel processing on the solution of the stock-cutting problem is assessed. The conceptual model proposed integrates a feature-recognition network and a simulated annealing approach. The model uses a neocognitron neural network paradigm to generate data for assessing the degree of match between two irregular patterns. The information generated through the feature recognition network is passed to an energy function, and the optimal configuration of patterns is computed using a simulated annealing algorithm. Basics of the approach are demonstrated with an example.