Air combat tactics decision-making is a procession which full of complexity and uncertainty. The decision-making is uncertainty fusion reasoning with multi-sensors system. Aim to deal with the uncertainty in a dynamic decision-making process of air combat, bayesian network model of air combat tactics decision-making has been brought out based on the merits of bayesian networks on uncertainty reasoning. Firstly, the air combat tactics of beyond visual range (BVR) was analyzed in detail as a typical air combat example based on the combat situation of both sides. Secondly, the decision-making variables and reasoning rules were selected based on the tactics control mathematics model. Lastly, according to the decisionmaking variables and the reasoning rules, the bayesian networks model of BVR combat tactics decision-making was given out. Then the optimal tactics decision-making can be selected applied with the bayesian network inference algorithm. The method has been tested with given conditions. The simulation results have showed that the tactics decisionmaking models could improve the decision-making accuracy and intelligent and the algorithm is simple, perspicuity and apt realization.

Language Related Episodes occur when speakers explicitly question lexical and grammatical aspects of the language they are using, resulting in collaborative discourse and assisted performance from peers. This paper demonstrates how such negotiation and repair may occur in relation to the gestural component of a speaker's expression, leading us to introduce the parallel term 'Gesture Related Episodes'. Our single case analysis reveals a range of issues that have received little attention, including the problems that people experience with gestures, what constitutes struggling in the gestural modality, and how people help each other to gesture more effectively in collaborative discourse. Our discussion links these issues to the L2 concerns and knowledge asymmetries in our data, as well as to conceptual and conventional features of gestures more generally.

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There are many problems in the layout of the railway freight stations, such as too many stations, the higher density of stations, and so on. So, it is necessary to adjust the layout of freight station and integrate the freight transport resources to raise the freight transport services level. According to the Sugarscape model and the analysis of advantages and disadvantages of Human Element model, a freight transport resources integration model is established based on multi-agent system and Human Element model, which can reflect the intelligent and autonomous of the station in the integrating process. The freight stations are regarded as autonomic Agents and the owners are regarded as resources in the model. The Agent energy can change during it seeks the resources, and its living or dying state is decided by its own energy. According to the set rules, a freight station concentration project in a definite scope is obtained through stimulation analysis. Finally, the freight transport resources integration project is obtained by the simulation for the model, which is meaningful to integrate the freight transport resources and optimize the layout of the railway freight stations and setup the strategic cargo-loading point and logistics center.