.  The effect of flow shear on turbulent transport in tokamaks is studied numerically in the experimentally relevant limit of zero magnetic shear. It is found that the plasma is linearly stable for all nonzero flow shear values, but that subcritical turbulence can be sustained nonlinearly at a wide range of temperature gradients. Flow shear increases the nonlinear temperature gradient threshold for turbulence but also increases the sensitivity of the heat flux to changes in the temperature gradient, except over a small range near the threshold where the sensitivity is decreased. A bifurcation in the equilibrium gradients is found: for a given input of heat, it is possible, by varying the applied torque, to trigger a transition to significantly higher temperature and flow gradients.  The achievement of long duration, alternating current discharges on the tokamak IST-TOK requires a real-time plasma position control system. The plasma position determination based on magnetic probes system has been found to be inadequate during the current inversion due to the reduced plasma current. A tomography diagnostic has been therefore installed to supply the required feedback to the control system. Several tomographic methods are available for soft X-ray or bolo-metric tomography, among which the Cormack and Neural networks methods stand out due to their inherent speed of up to 0000 reconstructions per second, with currently available technology. This paper discusses the application of these algorithms on fusion devices while comparing performance and reliability of the results. It has been found that although the Cormack based inversion proved to be faster, the neural networks reconstruction has fewer artifacts and is more accurate.  