该文简要介绍了喷水推进器的基本原理和结构，分析了其发展历程、应用状况和存在的主要问题，总结了喷水推进装置的特点，对喷水推进器的未来发展趋势作了简要分析和探索。

In this study, a two-stage fuzzy robust integer programming (TFRIP) method has been developed for planning environmental management systems under uncertainty. This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming framework. It can facilitate dynamic analysis of capacity-expansion planning for waste management facilities within a multi-stage context. In the modeling formulation, uncertainties can be presented in terms of both possibilistic and probabilistic distributions, such that robustness of the optimization process could be enhanced. In its solution process, the fuzzy decision space is delimited into a more robust one by specifying the uncertainties through dimensional enlargement of the original fuzzy constraints. The TFRIP method is applied to a case study of long-term waste-management planning under uncertainty. The generated solutions for continuous and binary variables can provide desired waste-flow-allocation and capacity-expansion plans with a minimized system cost and a maximized system feasibility.

In this study, a dual-interval vertex analysis (DIVA) method is developed, through incorporating the vertex method within an interval-parameter programming framework. The developed DIVA method can tackle uncertainties presented as dual intervals that exist in the objective function and the left-and right-hand sides of the modeling constraints. An interactive algorithm and a vertex analysis approach are proposed for solving the DIVA model. Solutions under an associated a-cut level can be generated by solving a series of deterministic submodels. They can help quantify relationships between the objective function value and the membership grade, which is meaningful for supporting in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability. A management problem in terms of regional air pollution control is studied to illustrate applicability of the proposed approach. The results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers to identify desired pollution-abatement strategies with minimized costs and maximized environmental efficiencies.

针对目前在图形用户界面（graphic user interface, GUI）自动化测试方法中存在的手工依赖性和测试缺乏准确性等问题，提出了一种改进的GUI自动化测试算法。该算法包括两种基于事件流图的GUI自动化测试用例生成策略：基于蚁群算法的日常冒烟测试用例生成策略和基于宽度优先搜索生成树的深度回归测试用例生成策略。将这两种策略应用于没有考虑分层的GUI 事件流图模型中，得到标准GUI 的测试用例，然后再进行GUI测试。结合Microsoft UI Automation 框架和Visual Studio 2005 开发平台，对该算法进行了实验研究。研究表明：该算法可以提高GUI测试的自动化程度和准确性。

A more highly automated graphic user interface (GUI) test model, which is based on the event-flow graph, is proposed. In the model, an automation tool is first used to carry out reverse engineering for a GUI test sample so as to obtain the event-flow graph. Then an improved ant colony optimization algorithm and a goal-directed searching approach are adopted to create GUI test sample cases. Moreover, a corresponding prototype system based on Microsoft UI automation framework is developed.