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In allusion to the problem that Q-Learning,which was used discount reward as the evaluation criterion,could not show the affect of the action to the next situation,AR-Q-Learning was put forward based on the average reward and Q-Learning.In allusion to the curse of dimensionality,which meant that the computational requirement grew exponen-tially with the number of the state variable.Minimum state method was put forward.AR-Q-Learning and minimum state method were used in reinforcement learning for Blocks World,and the result of the experiment shows that the method has the characteristic of aftereffect and converges more faster than Q-Learning,and at the same time,solve the curse of di-mensionality in a certain extent in Blocks World.

In order to improve the performance of Deep Web crawler in discovering and searching data sources interfaces,a new method was raised to parallel processing the mass data within the Deep Web compromising MapReduce program-ming model and virtualization technology.The new crawling architecture was designed with three producers,the link classified MapReduce,the page classified MapReduce and the form classified MapReduce.Server virtualization was adopted to simulate the cluster environment in order to test the performance.Experiment results indicate that this method is capable for large-scale data parallel computing,can improve the crawling efficiency and avoid wasteful expenditure,which prove the feasibility of applying cloudy technologies into Deep Web data mining field.

The efficient data transmission problem through cooperative communication was studied,a network coding was designed with random binning implements for wireless sensor networks,a cooperative data transmission scheme combined with the network coding was proposed,analyzed the end-to-end outage probability was analyzed.the usefulness of relaying was evaluated,and an ACK-less data transmission method based on the cooperative mechanism was developed.The theoretical analysis and experimental simulations show that they allowing for a more efficient use of resources.

Medical image visualization is an important field of scientific computing visualization. Three-dimensional segmentation plays a very important role in three-dimensional reconstruction of human tissues and region of interest. In order to observe the information of human internal tissues better and provide reliable basis for clinical diagnosis, pathological analysis and treatment, it is indispensable to do cutting on volume data. Virtual cutting is usually carried out with the user's interactive operations after three-dimensional reconstruction. This paper does research on the algorithms of cutting volume data, and proposes a series of solutions including plane cutting, bounding box cutting, ball cutting and contour surface cutting. Experiment results indicate that the algorithms are practical and efficient, which can reach favorable virtual cutting effect. By this meaning, doctors can know the internal information of volume data more clearly. Meanwhile, the amount of computation reduced.

Titanium (Ti) and its alloys are widely used in clinical practice as preferred materials for bone tissue repair and replacement because of their good mechanical properties; however, as Ti lacks biological activity, clinical application has been limited. Herein, we prepared a manganese–titanium dioxide (Mn–TiO2) microporous biotic coating on Ti surfaces by micro-arc oxidation (MAO). The coating showed good surface topography and was uniformly doped with Mn, and the Mn ions were slowly released. In vitro, the Mn–TiO2 microporous biotic coating promoted the adhesion, proliferation, differentiation, and mineralization of MC3T3-E1 osteoblasts. Moreover, in vivo experiments showed that the coating promoted early osseointegration. We also conducted a preliminary investigation to explore the molecular mechanism underlying the regulation of the function of osteoblasts by the coating. Furthermore, we found that the coating could inhibit the growth of Escherichia coli in vitro, demonstrating reliable antibacterial ability. To conclude, Mn–TiO2 microporous biotic coating can improve the biological activity of Ti implants, which can potentially improve their clinical applications. [ABSTRACT FROM AUTHOR]