新疆高校大学生生活价值观及应对方式的相关研究

本研究对新疆在校大学生生活价值观现状及应对方式进行调研,经分析得出：新疆高校大学生生活价值观各维度与积极应对呈线性相关,不向学生的生活价值观在年级、专业、性别变量上存在显著差异和多样性,农学专业学生在生活价值观各维度和压力应对上需要进一步引导和关注。     

随机共振在微弱信号检测中的数值仿真

对基于非线性双稳系统随机共振的微弱信号检测技术进行数值研究,利用随机共振机制,浸入在噪声中的微弱信号可以得到有效的放大与增强。给出了基于Runge Kutta算法的双稳系统随机共振模型的求解方法,提出了利用随机共振检测微弱非周期信号的一种新思路。数值仿真结果表明,该方法不仅可以检测出强噪声极低频的微弱周期信号,而且可以对非周期信号进行有效的检测。     

高校学生宿舍楼初期火灾的扑救与逃生

高校学生公寓、宿舍是学生休息、生活、学习的综合场所,由于当前学生数量成倍增长、电脑电视进入宿舍,学生生活学习用品增多,使得楼内可燃物随之增多,加之一些学生违反宿舍安全管理规定,不安全隐患急剧增多,火灾发生的几率明显增大。阐明了高校学生宿舍楼初期火灾的扑救办法和火灾中的逃生技巧,以期最大限度的减少财产损失和人员伤亡。     

基于全寿命周期的消防装备管理系统化组织体系建立

目前消防装备管理存在着管理环节分离,管理决策缺乏科学性,经费使用效益低下等问题。以全寿命周期管理理念,推进消防装备管理创新,建立消防装备管理系统化组织体系,是解决问题的关键。     

具有变时滞的离散型随机BAM神经网络的稳定性

研究一类具有变时滞的离散型随机BAM神经网络。通过构造Lyapunov泛函以及线性矩阵不等式（LMI）,得出了离散系统全局渐近稳定的充分条件。     

基于加速寿命试验的晶体管静电放电潜在性失效的研究

对高频小功率硅双极结型晶体管2SC3356进行静电放电试验,并利用加速寿命试验原理对两组器件进行加速寿命试验。采用Arrhenius模型对试验结果进行计算分析,发现低于损伤阈值的ESD注入可以使器件的寿命缩短,得出ESD可以在高频小功率硅双极结型晶体管内部造成潜在性失效,使得器件寿命缩短。     

基于随机网络的平均维修保障服务时间分析

利用随机网络建模方法在随机工程项目分析中的优越性,建立了不同保障方式下的维修保障过程模型。重点对网络活动中的维修等待时间和维修等待概率进行了分析,利用随机网络的解析算法,确定了维修力量的平均维修保障服务时间分析模型。最后将该方法应用于伴随修理过程,对其平均维修保障服务时间进行了案例分析。     

武器装备全寿命费用宏观控制的系统动力学模型

以武器装备作战能力差距为牵引,以全寿命周期阶段对作战能力的影响为主要依据,建立了基于系统动力学的武器装备全寿命费用控制分析模型,客观、合理地描述了全寿命周期各阶段之间的相互影响,并对武器装备全寿命费用宏观费用控制问题进行了仿真实验分析。     

Approximating nondominated sets in continuous multiobjective optimization problems

Many important problems in Operations Research and Statistics require the computation of nondominated (or Pareto or efficient) sets. This task may be currently undertaken efficiently for discrete sets of alternatives or for continuous sets under special and fairly tight structural conditions. Under more general continuous settings, parametric characterisations of the nondominated set, for example through convex combinations of the objective functions or ε‐constrained problems, or discretizations‐based approaches, pose several problems. In this paper, the lack of a general approach to approximate the nondominated set in continuous multiobjective problems is addressed. Our simulation‐based procedure only requires to sample from the set of alternatives and check whether an alternative dominates another. Stopping rules, efficient sampling schemes, and procedures to check for dominance are proposed. A continuous approximation to the nondominated set is obtained by fitting a surface through the points of a discrete approximation, using a local (robust) regression method. Other actions like clustering and projecting points onto the frontier are required in nonconvex feasible regions and nonconnected Pareto sets. In a sense, our method may be seen as an evolutionary algorithm with a variable population size. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

A generalization of the weighted set covering problem

We study a generalization of the weighted set covering problem where every element needs to be covered multiple times. When no set contains more than two elements, we can solve the problem in polynomial time by solving a corresponding weighted perfect b‐matching problem. In general, we may use a polynomial‐time greedy heuristic similar to the one for the classical weighted set covering problem studied by D.S. Johnson [Approximation algorithms for combinatorial problems, J Comput Syst Sci 9 (1974), 256–278], L. Lovasz [On the ratio of optimal integral and fractional covers, Discrete Math 13 (1975), 383–390], and V. Chvatal [A greedy heuristic for the set‐covering problem, Math Oper Res 4(3) (1979), 233–235] to get an approximate solution for the problem. We find a worst‐case bound for the heuristic similar to that for the classical problem. In addition, we introduce a general type of probability distribution for the population of the problem instances and prove that the greedy heuristic is asymptotically optimal for instances drawn from such a distribution. We also conduct computational studies to compare solutions resulting from running the heuristic and from running the commercial integer programming solver CPLEX on problem instances drawn from a more specific type of distribution. The results clearly exemplify benefits of using the greedy heuristic when problem instances are large. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2005