A Phenomenological Expression for Deuteron Electromagnetic Form Factors Based on Perturbative QCD Predictions

For deuteron electromagnetic form factors,perturbative QCD(pQCD) predicts that $G^{+}_{00}$ becomes the dominate helicity amplitude and that $G^{+}_{+0}$ and $G^{+}_{+-}$ are suppressed by factors $\Lambda_{\rm QCD}/Q$ and $\Lambda_{\rm QCD}^2/Q^2$ at large $Q^2$,respectively. We try to discuss the higher order corrections beyond the pQCD asymptotic predictions by interpolating an analytical form to the intermediate energy region. From fitting the data,our results show that the helicity-zero to zero matrix element $G^{+}_{00}$ dominates the gross structure function $A(Q^2)$ in both of the large and intermediate energy regions; it is a good approximation for $G^{+}_{+-}$ to ignore the higher order contributions and the higher order corrections to $G^{+}_{+0}$ should be taken into account due to sizeable contributions in the intermediate energy region.Comment: 9 pages,3 figure

The development of test action bank for active robot learning

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Master of Science by researchIn the rapidly expanding service robotics research area, interactions between robots and humans become increasingly cornmon as more and more jobs will require cooperation between the robots and their human users. It is important to address cooperation between a robot and its user. ARL is a promising approach which facilitates a robot to develop high-order beliefs by actively performing test actions in order to obtain its user's intention from his responses to the actions. Test actions are crucial to ARL. This study carried out primary research on developing a Test Action Bank (TAB) to provide test actions for ARL. In this study, a verb-based task classifier was developed to extract tasks from user's commands. Taught tasks and their corresponding test actions were proposed and stored in database to establish the TAB. A backward test actions retrieval method was used to locate a task in a task tree and retrieve its test actions from TAB. A simulation environment was set up with a service robot model and a user model to test TAB and demonstrate some test actions. Simulations were also perfonned in this study, the simulation results proved TAB can successfully provide test actions according to different tasks and the proposed service robot model can demonstrate test actions