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This paper proposed an environmental RF energy acquisition system based on GSM-1800 and WiFi frequency bands. The system consists of a dual-frequency circularly polarized antenna, a dual-frequency rectifier circuit and a load. The impedance bandwidth of the circular polarization antenna is 1 GHz～2.6 GHz, and the axial ratio bandwidth is 1.78 GHz～1.96 GHz and 2.37 GHz～2.59 GHz. The designed dual-frequency rectifier has a maximum RF-DC efficiency of 44% when the 1.825 GHz single-frequency input is 10 dBm. In the case of 2.45 GHz input power of 8 dBm, the highest RF-DC efficiency is 49%. When the dual-frequency input power is 7.5 dBm, the maximum RF-DC conversion efficiency is 53% and the DC voltage is 1.73 V. Placing the designed dual-band energy harvesting system near the router and the phone being called, an LED light can be lit to realize its energy harvesting function.

Domain modeling is a crucial step from natural language requirements to precise specifications, and an essential support for the development of automation system design tools. The existing domain model extraction methods are not accurate enough to be applied into specific fields. In this paper, we present a method for extracting the requirement domain model of airborne display and control system based on Natural Language Processing (NLP). Firstly, the domain model template is defined on the basis of the detailed study of the existing rules. Then in the requirement statement, the parse tree generated from Stanford Parser is utilized to preprocess the requirements for special symbols and conjunctions. Finally, we conduct the comparative experiment and the results indicate that the precision of domain model extraction is 20.01% higher than the existing approaches without preprocessing.