Parallel Optimization of the Crystal-KMC on Tianhe-2

The Kinetic Monte Carlo(KMC) is one of the commonly used methods for simulating radiation damage of materials. Our team develops a parallel KMC software named Crystal-KMC, which supports the Embedded Atom Method(EAM) potential energy and utilizes the Message Passing Interface(MPI) technology to simulate the vacancy transition of the Copper(Cu) element under neutron radiation. To make better use of the computing power of modern supercomputers, we develop the parallel efficiency optimization model for the Crystal-KMC on Tianhe-2, to achieve a larger simulation of the damage process of materials under irradiation environment. Firstly, we analyze the performance bottleneck of the Crystal-KMC software and use the MIC offload statement to implement the operation of key modules of the software on the MIC coprocessor. We use Open MP to develop parallel optimization for the Crystal-KMC, combined with existing MPI inter-process communication optimization, finally achieving hybrid parallel optimization. The experimental results show that in the single-node CPU and MIC collaborative parallel mode, the speedup of the calculation hotspot reaches 30.1, and the speedup of the overall software reaches 7.43.     

一类三元离散神经网络的收敛性

利用Lyapunov函数对在一条直线上的3个神经元构成的离散神经网络的收敛性进行了讨论,得到了一系列的结论.     

Strong association of de novo copy number mutations with sporadic schizophrenia

Schizophrenia is an etiologically heterogeneous psychiatric disease, which exists in familial and nonfamilial (sporadic) forms. Here, we examine the possibility that rare de novo copy number (CN) mutations with relatively high penetrance contribute to the genetic component of schizophrenia. We carried out a whole-genome scan and implemented a number of steps for finding and confirming CN mutations. Confirmed de novo mutations were significantly associated with schizophrenia (P = 0.00078) and were collectively approximately 8 times more frequent in sporadic (but not familial) cases with schizophrenia than in unaffected controls. In comparison, rare inherited CN mutations were only modestly enriched in sporadic cases. Our results suggest that rare de novo germline mutations contribute to schizophrenia vulnerability in sporadic cases and that rare genetic lesions at many different loci can account, at least in part, for the genetic heterogeneity of this disease.     

基于运动信息和相位一致性的运动目标提取

提出一种新的时空结合的运动目标分割方法。该算法首先在累积帧差图像上使用改进的高阶统计(HOS)算法检测出运动区域,用最大连通区域表示初始运动目标模板,利用基于Log-Gabor复小波变换的相位一致性边缘检测算法提取出每一帧的单边缘信息,结合初始运动模板与空域边缘图像得到更精确的运动目标模板,最后结合原图像分割出运动对象。实验结果表明该算法能从对比度较小和噪声较大的视频序列中精确地提取出运动目标,且不受光照变化的影响。     

基于离散正则模型的时变信道盲辨识算法

以CDMA时变信道离散正则模型为基础,提出了基于改进的矩阵外积分解的时变信道盲辨识算法。算法对传统的矩阵外积分解算法进行修正,使其适应离散正则模型两级盲辨识,并引入了精确的时延阶数估计,克服了现有算法需要预先知道信道时延实际阶数的局限,使其在仅知道信道阶数上界的条件下完成盲辨识。仿真结果表明了该算法的有效性。     

基于Agent的集卡调度建模与仿真研究

日益大型化的集装箱船舶对集装箱码头的生产调度提出了较以往更加严格的要求.集装箱码头中的集卡调度是否合理对于提高整个码头的装卸效率具有重要意义.利用agent和哈佛体系结构对集卡动态调度进行建模,以AnyLogic仿真平台为实现工具,基于数据库中实际的生产数据,融合黑板系统和消息通讯形成多agent之间的协同机制,引入操作系统中的资源分配算法调度集卡.最后仿真了具体的港口生产实例,其结果优于以往文献的仿真结果,充分验证了上述建模仿真思想的可行性和可信性.     

基于元胞自动机的企业员工行为-激励传播效应模拟

企业激励的现有研究方法过于概念化,不能从理论上说明具体激励措施的运用过程及效果.在一般激励理论的基础上,结合企业激励可传递的特点,提出激励传播理论,考虑时间延迟、信息失真和行为突变等因素改进元胞自动机模型,对企业员工激励传播过程进行元胞自动机建模并开发模拟系统,就该过程及其对企业内部群体的影响进行模拟实验,模拟结果证明了企业员工群体激励传播效应的存在,并说明如何通过模拟实验来制定相应的激励措施以改善企业员工激励的效果.     

基于非线性自适应观测器的故障诊断

将自适应控制的思想和状态观测器方法相结合研究了一类非线性控制系统的故障诊断问题。针对一类满足Lipschitz条件的带有未知参数的非线性系统,提出了一种非线性自适应状态观测器的设计方法,并将其应用到控制系统的故障诊断中。通过设置未知故障向量的自适应调整律,保证了状态观测器的渐近稳定。数字仿真证明了该方法的有效性,系统渐近稳定,状态向量和故障向量的估计值均趋近于实际值。     

基于三维目标建模的需求分析方法

面向目标的需求分析方法是需求工程领域研究的热点问题之一.在深入研究目前有代表性的目标分类方法基础上,提出一种不依赖于具体应用领域的、较为系统和完整的目标分类框架和建模方法.该框架从三个角度对目标进行划分,分别将其归类为操作性或非操作性目标,硬目标或软目标以及实现型或维持型目标.这三种分类虽然相互独立,但在实际建模时可以相互补充,形成一个完整的体系,为目标建模提供不同的帮助.在此基础上,还提供了一种目标建模的具体算法,可以较好地完成目标建模任务.     

Data association based on target signal classification information

In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy.