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Aiming at improving the identification and judgment on objectives of unmanned weapon system in the battlefield, this paper puts forward a new efficient method to infuse conflict evidence orienting towards shortcomings existing in the Dempster-Shafter (D-S) evidence theory when fusing conflict evidence. This paper is to improve the D-S Evidence Theory, by firstly conducting research on the influence of a certain operational environment on the sensors precision in the unmanned weapon system, and by secondly establishing sensors weight values based on fixed basic probability assignment by exploiting AHP. The improved approach can enhance the reliability of identification result, which has been proved via simulation experiments, and it improves the performance of target recognition system to a certain extent.

Aiming at the invisibility of the electromagnetic environment (EME), this paper presents the method to visualize the weapon equipments EME. The visualization can be divided into two steps. Firstly, we can model the weapon equipments EME to get the electromagnetic data by the finite difference time domain(FDTD) and the transformation from the near field to the far field. Secondly, we can render the electromagnetic data by the data field visualization. The experiment shows that this way is feasible and effective.

Spare parts inventory is one of the most important contents in supportability analysis of aircrafts. Considering that scrap of spare parts was not taken into account in traditional analysis methods, an optimized model of resupply process was built aiming at maximizing the availability of spare parts. During such procedure, the initial supply and resupply are analyzed considering spare parts scrap and cost restrictions. It is assumed that once the scrap of spare parts exists, extra parts will be purchased immediately in the strategy of the analysis model. We obtained the solution method of top limit to availability at the end of each year. And relations among spare parts shortage costs, procurement costs and demand costs in queuing process are explicated in a formulation. Then the model is solved with an iterative algorithm. The optimized model is proved to be rational and validated by a comparison of numerical examples.

This paper presents a computer-based adaptive control system for left ventricular bypass assist devices consisting of air driven diaphragm pumps. The system provides for 1) synchronization of pumping with ECG signals and 2) control of atrial pressure at desired levels. The system design includes an adaptive control algorithm which is a self-tuning PID-controller based on pole placement. The performance of the system has been demonstrated by in vitro experiments_ on a mock circulatory system. When there is an increase in atrial pressure, the system responds with an increase in stroke volume. Following major changes in the circulatory system, the control algorithm retunes itself and restores the system to the desired state.