武警院校“四位一体”心理服务模式探索与实践

武警院校“四位一体”心理服务模式的主要职能任务包括课堂教学、测试咨询、心理训练和部队服务,在制度保障机制、组织保障机制和物质保障机制下有效运行,能够增强院校心理课堂教学的效果,拓宽官兵维护心理健康的渠道,提升部队心理骨干的业务能力。     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

定向毫米波网络邻居发现协议

针对定向毫米波网络各节点间无波束方向先验信息导致邻居发现困难的问题,提出了一种基于盲交汇算法的邻居发现协议,推导了邻居发现过程中时隙长度、波束个数与邻居发现时间之间的理论关系。进一步,为了缩短邻居发现的时间,在盲交汇算法的邻居发现协议的基础上,提出了基于位置预测的邻居发现协议。仿真结果表明,基于盲交汇算法的邻居发现协议的最长邻居发现时间小于无协调的定向邻居发现协议,波束个数N接近2n(2n－1n,n>1,n∈Z)时,平均邻居发现时间低于无协调的定向邻居发现算法。此外,基于位置预测的邻居发现协议可以有效缩短邻居发现时间。     

基于算子空间的公式发现算法研究

在FDD提出的人工智能技术与曲线拟合技术结合的公式发现系统的基础上 ,提出了新的基于算子空间的公式发现算法 ,并在算法研究的基础上设计实现基于算子空间的可视化公式发现系统 ,该系统通过算子空间概念的引入 ,简化了算子空间的规则 ,同时引入导数规则、误差规则以及终止规则 ,丰富了知识库内容。通过以上改进 ,和BACON和FDD相比 ,公式发现的形式更广 ,复杂度更高。文章最后给出了应用实例以及公式发现的结果。     

Impacts of logistics information on sales: Evidence from Alibaba

Facing fierce competition from rivals, sellers in online marketplaces are eager to improve their sales by delivering items faster and more reliably. Because logistics quality can be known only after a transaction, sellers must identify effective ways to communicate logistics information to consumers. Drawing on the accessibility-diagnosticity framework, we theorize that the sales impacts of logistics information depend on its relative diagnostic value. Using data on 1493 items with 505,785 consumer reviews from an online marketplace, we examine how sales are affected by three information sources for logistics services: online word of mouth (WOM) about logistics, self-reported logistics services, and expected delivery time. We use an instrumental variable method to address the endogeneity issue between sales and WOM. We find that, ceteris paribus, consumers give more weight to WOM about logistics and delivery time when they make purchase decisions but less weight to self-reported logistics service. The effects of logistics information on sales are asymmetric for large and small sellers.     

一种完全分布式的空间服务及组合模型

针对服务组合中控制流和数据流的不同协调机制,可将组合模型分为4种类型,分别是控制流集中式且数据流集中式、控制流集中式且数据流分布式、控制流分布式且数据流集中式、控制流分布式且数据流分布式.空间服务组合流程需处理较大规模的数据流,采用控制流分布式和数据流分布式的协调机制能有效降低组合过程中系统整体通信规模并减少空间服务组合响应时间.通过对各种不同组合类型建模的定量分析对上述观点进行了正确性论证.模拟实验证明,定量分析结果可信.     

军事网络拓扑搜索

叙述了军用网络拓扑发现的特点和存在问题,军用网络拓扑发现的算法分两步:第一步,主干网络级,以路由器为主的网络主构架拓扑发现,给出了实现算法的数据结构和流程图;第二步,子网内拓扑发现,子网发现利用网桥管理对象组的信息,给出以交换机为骨架的子网拓扑,给出了子网拓扑发现算法。对开发网络拓扑发现软件有参考价值。     

混合模糊测试中混合符号执行优化策略评估与分析

针对传统混合模糊测试提升技术多聚焦于利用多种动静态分析手段辅助而忽略了混合符号执行自身性能的问题,提出一种混合模糊测试平衡点模型,并基于该模型对主流混合符号执行方案进行剖析,包括污点分析辅助模糊测试、混合模糊测试以及混合符号执行,归纳了6种符号执行方案,基于混合符号执行引擎Triton复现了6种符号执行方案,并通过10个典型真实程序进行了测试评估。从效率、内存、覆盖率三个维度对各个方案进行性能对比与影响因素分析。实验证明,优化方案都可以消除不必要的约束并减少时间和空间开销,但约束缩减会造成信息丢失,造成覆盖率降低。基于实验数据分析,提出了一个优化方案的性能序列,并提出三种针对不同测试需求的优化方案。     

基于依赖矩阵的Web服务组合故障诊断

为了保证指挥信息系统在动态环境下能够提供持续可靠的组合服务,提出一种利用依赖矩阵对Web服务组合故障原因进行诊断的模型,对依赖矩阵的建立进行了详细说明。然后,基于构造的依赖矩阵,提出改进的贪心算法对失效情况进行探测,并设计了基于二分查找的故障定位算法。实验模拟表明,提出的模型能够利用少量探测就能监测整个服务组合流程的运行情况,并定位找到错误源。     

The graph association problem: Mathematical models and a lagrangian heuristic

Graph association is the problem of merging many graphs that collectively describe a set of possibly repetitive entities and relationships into a single graph that contains unique entities and relationships. As a form of data association, graph association can be used to identify when two sensors are observing the same object so information from both sensors can be combined and analyzed in a meaningful and consistent way. Graph association between two graphs is related to the problem of graph matching, and between multiple graphs it is related to the common labeling of a graph set (also known as multiple graph matching) problem. This article contribution is to formulate graph association as a binary linear program and introduce a heuristic for solving multiple graph association using a Lagrangian relaxation approach to address issues with between‐graph transitivity requirements. The algorithms are tested on a representative dataset. The developed model formulation was found to accurately solve the graph association problem. Furthermore, the Lagrangian heuristic was found to solve the developed model within 3% of optimal on many problem instances, and found better solutions to large problems than is possible by directly using CPLEX. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013