Automatic identification of landmarks for standard slice positioning in brain MRI.

Purpose: To demonstrate a novel automatic slice-positioning technique based on three new anatomical landmarks and to standardize prospective scans by lowering rotational and translational variances.

Materials And Methods: After defining the interpeduncular fossa corner and the eyeball centers as landmarks, they are manually labeled on 25 different T1 MRI scans. New scans are produced according to the Eyeball centers-Mesencephalon (EM) plane.

Nonlinear predictive control of a drying process using genetic algorithms.

A nonlinear predictive control technique is developed to determine the optimal drying profile for a drying process. A complete nonlinear model of the baker's yeast drying process is used for predicting the future control actions. To minimize the difference between the model predictions and the desired trajectory throughout finite horizon, an objective function is described.

Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases.

Direct descent curvature optimal control with a modification algorithm and its application to nonlinear process.

This paper presents a direct descent second order or direct descent curvature algorithm with some modifications for the optimal control computations. This algorithm is compared with Hamiltonian methods in the literature. The proposed algorithm has generated numerically robust solutions with respect to conjugate points.

Trajectory priming with dynamic fuzzy networks in nonlinear optimal control.

Fuzzy logic systems have been recognized as a robust and attractive alternative to some classical control methods. The application of classical fuzzy logic (FL) technology to dynamic system control has been constrained by the nondynamic nature of popular FL architectures. Many difficulties include large rule bases (i.

Intelligent optimal control with dynamic neural networks.

The application of neural networks technology to dynamic system control has been constrained by the non-dynamic nature of popular network architectures. Many of difficulties are-large network sizes (i.e.