Giant panda pedigree data is an important data base for studying the population dynamics of giant pandas. Therefore, it is of great significance for data modeling of giant panda ecosystems from the perspective of panda conservation. Focused on this issue, a data modeling method of giant panda ecosystem based on population dynamics P system was proposed. Based on the giant panda pedigree data released by Chinese Association of Zoological Gardens, the population characteristics of captive pandas were simulated and researched in China Giant Panda Conservation Research Center from individual behavior. The change rules of reproductive parameters were analyzed in detail, and added to the field released module. Eventually, a population dynamic P system for giant panda was designed releasing-to-the-wild with a two-layer nested membrane structure, a collection of objects and a series of evolution rules which is inline with the characteristics of giant panda. For all giant panda, the maximum relative error between the simulation results and the actual data was within ±4.13% and basically controlled within ±2.7% of P system. The experimental results verify the effectiveness and soundness of the proposed model. It can simulate the population dynamic change trend of giant panda and provide the basis for management decision-making.

Concerning the problems of designing and modeling the process of Point-Of-Care Testing (POCT) system, a method for concurrence system modeling and analyzing based on Time-Petri Net (TPN) was proposed which built more accurate information model for the process designing of POCT system. The activity holding duration was introduced into classical TPN, and the TPN modeling method for POCT control process was proposed. The scheduling simulator embedded in Petri net model was also designed for assisting the analysis, and optimization of the POCT control process. The simulation results show that the proposed modeling method for TPN can satisfy the practical requirement of process modeling of the parallel multi-class POCT control system in the fields such as reachable nodes and running time and provide powerful tool for process simulation and analysis. Furthermore, the proposed TPN can assist the system designer for the optimization of POCT system.