Application of Soft Power Strategy on Asian Civilization Spaces

While increasing contact between peoples and cultures,globalization does not weaken the diversity of world's civilizations.Soft power can serve as a lubricant to prevent the clash of civilizations and enhance dialogues between civilizations.The article summarizes the three components of China's soft power:cultural promoting,foreign assistance and the thought of"a harmonious world."Taking Uzbekistan as an example,the author also illustrates the path of the Islamic nations to implement"soft power"strategy.

Optimal confrontation position selecting games model and its application to one-on-one air combat

In the air combat process,confrontation position is the critical factor to determine the confrontation situation,attack effect and escape probability of UAVs.Therefore,selecting the optimal confrontation position becomes the primary goal of maneuver decision-making.By taking the position as the UAV’s maneuver strategy,this paper constructs the optimal confrontation position selecting games(OCPSGs)model.In the OCPSGs model,the payoff function of each UAV is defined by the difference between the comprehensive advantages of both sides,and the strategy space of each UAV at every step is defined by its accessible space determined by the maneuverability.Then we design the limit approximation of mixed strategy Nash equilibrium(LAMSNQ)algorithm,which provides a method to determine the optimal probability distribution of positions in the strategy space.In the simulation phase,we assume the motions on three directions are independent and the strategy space is a cuboid to simplify the model.Several simulations are performed to verify the feasibility,effectiveness and stability of the algorithm.

Space Enterprise Strategy Guiding-Based Study on Project Portfolio Management and Flow Optimization

Project portfolio management(PPM) is the centralized management method, process and technology in multiple projects. When multiple projects in the space industry are implemented, it provides an effective methodology to resolve the problems at the same time such as conflicts among models, decrease in design efficiency,and increase in target deviation. Hence, a PPM dedicated to multiple projects management in space enterprise is presented in this paper. Firstly, an analysis of features and contents in space enterprise portfolio management mode is performed by using PPM based on its specific strategic characteristics. Then, the principle and selection methods of PPM are provided as a reference for the future development of an enterprise. Finally, a multiple-level organization architecture including decision making layers, function management layers and project execution layers is proposed so as to adapt to possible changes in the multiple projects and correspond to the strategic development. As a consequence, a perfect matching mechanism to fit the changes in PPM modes is reached. In addition, the flow chart of PPM is designed and optimized by analyzing the implementation procedure of strategic target and project portfolio life-cycle, which is expected to realize the purpose of improving space enterprise management efficiency, project management capacity, innovation development and economic benefits.

分割氢键有机框架的孔道空间提升光催化CO_(2)还原效率

氢键有机框架材料(HOFs)在催化领域具有巨大的潜力,但其孔道空间在去除溶剂后易塌陷,限制了其在光催化能源转换和存储方面的应用.本研究采用孔道分割策略成功设计并合成了一种稳定孔道结构、高效光催化CO_(2)还原活性的HOF催化剂.H4TBAPy分子通过与HOF孔道中大量的CH…π相互作用锚定自身,并将HOF的大孔道分隔成多个小空间,显著增加了HOF框架的稳定性.同时,富电子属性的H4TBAPy分子提升了HOF体系中电子的传输速率,从而提高了催化活性.这项研究为设计稳定、高性能的HOFs光催化剂提供了新策略.

Variable-fidelity optimization with design space reduction

Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity （LF） model provides physics-based approximation of the high-fidelity （HF） model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.