概率最大受限路径相容算法

研究了可用于求解约束满足问题的最大受限路径相容算法(maxRPC).maxRPC算法执行过程中有大量无效的寻找路径相容证明(PC-witness)的操作,有效地识别和避免这些无效的寻找PC-witness的操作,可以提高maxRPC算法的求解效率.首先,提出了在一条约束上任意两个相容的值在任意路径上存在PC-witness的概率;然后,基于这一概率提出了一种概率最大受限路径相容算法(PmaxRPC),并将新算法成功应用于求解约束满足问题的回溯搜索.实验结果显示:PmaxRPC可以避免一部分无效的寻找PC-witness的操作,在求解约束满足问题时,PmaxRPC效率高于maxRPC.在某些测试用例上,PmaxRPC比maxRPC和最流行的弧相容算法效率更高.     

空间约束混合高斯运动目标检测

目的 针对传统混合高斯模型前景检测运算量过大问题,提出一种基于空间约束的混合高斯前景检测算法。方法 通过快速初始化缩短模型的初始建立过程;采用双重背景模型机制,以自适应背景减法的前景检测结果作为混合高斯前景检测的空间约束条件,降低模型在背景区域的冗余运算;运用多策略自适应模型更新,提高前景检测的准确性。结果 在各种测试场景下,与传统混合高斯法、CodeBook、GMG、偏差均值混合高斯模型(MODGMM)等算法相比,该算法具有更好的准确率以及4倍以上的处理速度。结论 在固定相机场景下的运动目标检测中,算法能有效提高传统混合高斯法的准确性且具有极高的实时性。     

交互更新模式的量子遗传算法的几何约束求解

目的针对传统量子遗传算法无法充分利用种群中未成熟个体信息的不足,提出了基于交互更新模式的量子遗传算法(IUMQGA)并应用于几何约束求解中。方法几何约束问题的约束方程组可转化为优化模型,因此约束求解问题可以转化为优化问题。采用将遗传算法与量子理论相结合的量子遗传算法,使用双串量子染色体结构,使用交互更新策略将遗传算法中的交叉操作利用量子门变换来实现,根据不同情况采用不同的交互更新策略。这里的交互,指的是两个个体进行信息交换的过程,该过程用以产生新的个体。这不仅增加了个体间信息的交换而且充分利用了种群中未成熟个体的信息,提高了算法的收敛速度。结果通过非线性方程实例和几何约束实例测试并与其他方法比较表明,基于交互更新模式的量子遗传算法求解几何约束问题具有更好的求解精度和求解速率。双圆外公切线问题实例中,IUMQGA算法比QGA算法稳定;单圆填充问题和双圆外公切线问题实例中,通过实验求得各变量的最优值与其相应的精确值的误差在1E-2以下。结论采用交互更新模式的量子遗传算法可以很好地求解几何约束问题。     

Robust Input Covariance Constraint Control for Uncertain Polytopic Systems

In this paper, the robust input covariance constraint (ICC) control problem with polytopic uncertainty is solved using convex optimization with linear matrix inequality (LMI) approach. The ICC control problem is an optimal control problem that optimizes the output performance subjected to multiple constraints on the input covariance matrices. This control problem has significant practical implications when hard constraints need to be satisfied on control actuators. The contribution of this paper is the characterization of the control synthesis LMIs used to solve the robust ICC control problem for polytopic uncertain systems. Both continuous‐ and discrete‐time systems are considered. Parameter‐dependent and independent Lyapunov functions have been used for robust ICC controller synthesis. Numerical design examples are presented to illustrate the effectiveness of the proposed approach.     

Adaptive Fuzzy PD+ Control for Attitude Maneuver of Rigid Spacecraft

In this paper, an adaptive fuzzy PD+ controller is proposed for the attitude maneuver of rigid spacecraft. The novel controller adjusts the gains of the PD+ attitude controller online according to attitude errors and angular velocity errors during the maneuver procedure. Therefore, quick response and avoidance of actuator saturation can be achieved simultaneously. Furthermore, the adaptation mechanism is designed, based on Lyapunov theory, to guarantee the stability of the closed‐loop system. To achieve good performance of the closed‐loop system under the constraint of actuator saturation, controller parameter optimization is developed on the basis of a genetic algorithm. Simulation results show that the transient performance and robustness against parametric uncertainty and environmental disturbance of the adaptive fuzzy PD+ controller are better than those of a constant PD+ controller.     

Particle swarm algorithm with adaptive constraint handling and integrated surrogate model for the management of petroleum fields

This paper deals with the development of effective techniques to automatically obtain the optimum management of petroleum fields aiming to increase the oil production during a given concession period of exploration. The optimization formulations of such a problem turn out to be highly multimodal, and may involve constraints. In this paper, we develop a robust particle swarm algorithm coupled with a novel adaptive constraint-handling technique to search for the global optimum of these formulations. However, this is a population-based method, which therefore requires a high number of evaluations of an objective function. Since the performance evaluation of a given management scheme requires a computationally expensive high-fidelity simulation, it is not practicable to use it directly to guide the search. In order to overcome this drawback, a Kriging surrogate model is used, which is trained offline via evaluations of a High-Fidelity simulator on a number of sample points. The optimizer then seeks the optimum of the surrogate model.     

Code Analysis for Software and System Security Using Open Source Tools

ABSTRACT

Software security helps in identifying and managing risks. One of the effective ways to identify software vulnerabilities is to analyze its code. Code analysis (Chess & West, 2007 Chess, B. and West, J. 2007. Secure programming with static analysis, Boston, MA: Addison-Wesley.  [Google Scholar]) helps in catching common coding mistakes such as buffer overflow, unused variables, memory leaks, and various race conditions, which in turn optimizes computer programs, both in storage and computation aspects. Software developers use either open source tools or commercial tools for verification and validation of software. Without proper validation of a software/system using some standard guidelines, potential attackers can find ways to exploit vulnerabilities and bugs and then can gain control over a system, if they are successful. In this paper, we discuss some of the open source static code analysis and dynamic analysis tools, their merits, and limitations with respect to some target codes that contain possible threats. We consider C/C++ and Java programming languages for our experiments. For static code analyzers, we consider Flawfinder, Splint, and Cppcheck; PMD, Findbugs, and Valgrind for dynamic code analysis, and its plug-in, Memcheck, to perform dynamic analysis on executables. We provide our observations in a comparison table, highlighting these tools strengths and weaknesses.     

Segmentation of the left ventricle in cardiac cine MRI using a shape-constrained snake model

Segmentation of the left ventricle (LV) is a hot topic in cardiac magnetic resonance (MR) images analysis. In this paper, we present an automatic LV myocardial boundary segmentation method using the parametric active contour model (or snake model). By convolving the gradient map of an image, a fast external force named gradient vector convolution (GVC) is presented for the snake model. A circle-based energy is incorporated into the GVC snake model to extract the endocardium. With this prior constraint, the snake contour can conquer the unexpected local minimum stemming from artifacts and papillary muscle, etc. After the endocardium is detected, the original edge map around and within the endocardium is directly set to zero. This modified edge map is used to generate a new GVC force filed, which automatically pushes the snake contour directly to the epicardium by employing the endocardium result as initialization. Meanwhile, a novel shape-similarity based energy is proposed to prevent the snake contour from being strapped in faulty edges and to preserve weak boundaries. Both qualitative and quantitative evaluations on our dataset and the publicly available database (e.g. MICCAI 2009) demonstrate the good performance of our algorithm.     

采用随机有限断层法生成最大可信地震

本文依据基于地震学理论合成地震动的随机方法和能够细致描述震源复杂性的有限断层模型,采用随机有限断层法直接生成最大可信地震。重点比较了随机有限断层法的静拐角频率和动拐角频率理论,开发基于静拐角频率方法的Fortran程序SFFMSIM,作为对比,引进了动拐角频率程序EXSIM。选用1994年Northridge地震数据检验本文采用的随机有限断层模拟方法和程序。最后以大岗山水电站工程为例,采用随机有限断层法生成磨西断裂发震时工程场址可能产生的最大可信地震的加速度时程曲线。结果显示：随机有限断层法合成时程的放大系数谱均值与80条基岩记录平均谱的一致性较好。预测震源位错分布形式未知的地震时,动拐角频率和静拐角频率方法的模拟结果有差异。     

水下粉细砂土体在超高频机械振动荷载作用下液化特性的试验研究

为了量化高频机械振动对土壤液化的具体效果,在试验室泥槽中对不同性质的水下粉细砂沉积物开展了诸如不同振动作用时间及不同工况下的液化试验,利用静力触探仪测量了振动作用前后其承载力变化情况,基于试验数据分析讨论了振动作用时间、振动作用距离、振动频率对于液化效果的影响.