Sitka Spruce Quality Estimation using Neural Networks
This paper describes an automated classifier for the 
identification of good wood and knotty wood from 
computer tomography (CT) images of logs. Such a 
system is intended to allow better assessment of saw 
logs before being cut into timber. We describe a new empirical model for the growth of Sitka Spruce (Picea 
Stichensis (Bong, Carr)) whose operation is adapted to 
Irish conditions. The use of Hopfield networks for 2D 
cross-section image reconstruction from CT data 
obtained from the model is investigated. We also used 
a multi-layer feedforward neural network trained with 
fast-backpropagation to identify good wood from 
knotty wood. The Hopfield approach to image 
reconstruction was seen as being unsuitable for 
application with the wood industry. However, the use 
of a feedforward neural network for wood classification produced very promising results when trained on our tree model. It is expected that results from real wood data would be even more accurate.
Geon theory as an account of shape recognition in mind and brain
In a fraction of a second humans are able to comprehend novel images of objects and scenes. Indeed, the human represents the only existence proof that a general shape recognizer is even possible. G...
Numerical Simulation of Induction Heating Process of Continuous Casting Slab
Compared with traditional blazing furnace, the Continuous Casting-Direct Rolling is an advanced manufacturing steel technology, which can reduce energy waste, decrease pollution and enhance efficiency. The characteristics of steels during induction heating are complex, the change of material properties with temperature makes exact analysis methods very difficult to implement. Therefore, a powerful computer aided numerical tool (i.e., finite difference analysis) is selected to numerically model the induction heating process in this paper. The mathematic model coupling with electromagnetic field and thermal field was established, and it was solved by finite difference method (FDM), thus the slab temperature distribution and its variation with time were obtained, and the characteristics in whole induction heating process were studied. To validate the program feasible, the results were evaluated and compared with experiment results, which showed that the simulation results are reliable and effective. The skin effect in heating process from the two results was studied and demonstrated, the temperature change caused by different parameters such as the induced power intensity and the corner radian were also presented, which indicate that the slab temperature can be heated uniformly through adjusting these parameters, thus the continuous casting slab can meet the rolling requirement.