@article{rabiei_thomas_jin_narayan_cuomo_yang_ong_2006, title={A study on functionally graded HA coatings processed using ion beam assisted deposition with in situ heat treatment}, volume={200}, ISSN={["0257-8972"]}, DOI={10.1016/j.surfcoat.2005.09.027}, abstractNote={A new generation of calcium phosphate coatings with less than 1 μm thickness and graded crystallinity through the thickness of the film has been processed using ion beam assisted deposition (IBAD) and in situ heat treatment. Microstructural analysis of the film confirmed a gradual decrease of the grain size and crystallinity towards the surface, leading to nano-scale grains and eventually amorphous layer at the surface. The mechanical properties and adhesion bonding of the film have been evaluated using microscratch and nanoindentation tests and, in general, functionally graded HA films deposited using our IBAD system together with in situ heat treatment demonstrated higher modulus and hardness values than sputter-deposited films with the same thickness as well as those appearing in the literature for sintered HA. Scratch test results of both sets of samples revealed that crack formation is more common in sputter-deposited HA film than in the functionally graded HA film deposited using IBAD and in situ heat treatment. We anticipate that the functionally graded hydroxyapatite films will provide improved tissue–implant interfaces for orthopedic and dental implants.}, number={20-21}, journal={SURFACE & COATINGS TECHNOLOGY}, author={Rabiei, A and Thomas, B and Jin, C and Narayan, R and Cuomo, J and Yang, Y and Ong, JL}, year={2006}, month={May}, pages={6111–6116} }
 @article{bishr_yang_lee_2000, title={Self-tuning PID control using an adaptive network-based fuzzy inference system}, volume={6}, ISSN={["1079-8587"]}, DOI={10.1080/10798587.2000.10642795}, abstractNote={Abstract This paper presents a self-tuning PID control algorithm using an adaptive network-based fuzzy inference structure (ANFIS). In particular, the design of a self-tuning PID learning-based optimum controller is introduced which can be applied to nonlinear as well as linear systems. A recursive adaptation scheme is employed for on-line implementation of the self-tuning PID controller in which an exponential forgetting factor is used to weigh old data and both an error and control rate cost are used in the backwards pass. Results show that the method is a viable approach for tuning the parameters of a PID controller.}, number={4}, journal={INTELLIGENT AUTOMATION AND SOFT COMPUTING}, author={Bishr, M and Yang, YG and Lee, G}, year={2000}, pages={271–280} }