Nonparametric bayesian lifetime data analysis using dirichlet process lognormal mixture model

We propose a nonparametric Bayesian lifetime data analysis method using the Dirichlet process mixture model with a lognormal kernel. A simulation‐based algorithm that implements the Gibbs sampling is developed to fit the Dirichlet process lognormal mixture (DPLNM) model using rightly censored failure time data. Five examples are used to illustrate the proposed method, and the DPLNM model is compared to the Dirichlet process Weibull mixture (DPWM) model. Results indicate that the DPLNM model is capable of estimating different lifetime distributions. The DPLNM model outperforms the DPWM model in all the examples, and the DPLNM model shows promising potential to be applied to analyze failure time data when an appropriate parametric model for the data cannot be specified. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Why did Sudan Lose a small war in Southern Sudan?

ABSTRACT

When on the wrong end of an asymmetry in the projection of hard power, weaker sides countenance the grim arithmetic of avoiding direct and massed confrontations. Invariably, insurgents have over the ages tended to employ indirect tactical methods to render their stronger opponents ineffective. Ultimately – interest asymmetry, regime type, asymmetries of strategy, and external intervention – combine in a complex interplay and pattern, to militate against a strong side. In Sudan, these factors interacted throughout the civil wars to produce regional autonomy and finally an independent South Sudan in 2011. Similar strategic logic had confronted many large African states battling insurgencies in Ethiopia, Angola, Nigeria, Zaire, and apartheid-era South Africa. Oftentimes, weakening public resolve has caused these governments to accommodate, capitulate or withdraw even if they try not to blink. Notwithstanding the regime type, it can be concluded that the majority of strong actors are prone to fail in a protracted, asymmetric conflict. Hence, the notion of linking victory in counterinsurgency to the degree of openness (democratic polyarchies); or closeness (totalitarianism) – is still valid but highly contestable in the case of Africa’s large dysfunctional states.     

Colonial violence and its ‘Small Wars’: fighting the Kuki ‘guerillas’ during the Great War in Northeast India, 1917–1919

ABSTRACT

This paper concerns the lesser known British counterinsurgency (COIN) operations in Northeast frontier of India during the First World War. Officially known as the ‘Kuki Operations’, it was considered as part of the Great War. Carried out in isolation from press and public, and shelved in colonial archives, the event remained invisible until today. Yet, it registers a critical case of colonial COIN doctrine where the ‘moral effect’ doctrine was employed without being questioned. It unleashed enormous amount of organized violence, ranging from shoot at sight to indiscriminate burning of villages, wholesale destruction of property and livestock, prevention of cultivation and rebuilding of villages, forced mass displacement in jungles or in ‘concentration camps’, and collective punishment (communal penal labour and payment of compensation) after the war. This paper argues that the theory of ‘minimum force’ and the practicability of the ‘moral effect’ doctrine as applied by the Empire, sit oddly with each other at the frontier, where violence was seen both as a natural and moral orders. Violence as an ‘imperatively necessary’ method to bring order in a disorderly frontier, in the opinion of colonial state, informs and registers Northeast India as geography of violence.     

基于CPU-GPU混合计算平台的RNA二级结构预测算法并行化研究

RNA二级结构预测是生物信息学领域重要的研究方向,基于最小自由能模型的Zuker算法是目前该领域最典型使用最广泛的算法之一。本文基于CPU GPU的混合计算平台实现了对Zuker算法的并行和加速。根据CPU和GPU计算性能的差异,通过合理的任务分配策略,实现二者之间的并行协作计算和处理单元间的负载平衡;针对CPU和GPU的不同硬件特性,对Zuker算法在CPU和GPU上的实现分别采取了不同的并行优化方法,提高了混合加速系统的计算性能。实验结果表明,CPU处理单元在混合系统中承担了14%以上的计算任务,与传统的多核CPU并行方案相比,采用混合并行加速方法可获得15.93的全局加速比;与最优的单纯GPU加速方案相比,可获得16%的性能提升,并且该混合计算方案可用于对其它生物信息学序列分析应用的并行和加速。     

战时装备维修保障资源优化模型

维修资源在抢修过程中的分配决定了抢修活动的平均处理时间和等待时间,针对抢修实施时维修资源的分配,研究资源的优化配置使抢修时间最小的问题.在抢修过程中使抢修时间最小的目标和约束条件下,提出了资源配置优化的排队模型,并结合遗传算法给出了求解最优配置模型的方法,通过实例分析说明了模型和方法的应用情况.资源配置优化模型和算法已成功应用于集群装备保障决策系统的开发.     

业务流程建模中流程校验的研究与实现

随着计算机网络技术的迅速发展,企业的信息化程度不断提高,以自动化流程为核心理念的工作流管理系统应用越来越普及,对工作流管理系统的可靠性和正确性要求也越来越高.提出了一种工作流建模时的验证方法:在工作流管理系统的工作流建模环境中加入流程验证模块,对建模过程中可能产生的错误进行验证,进而建立简洁实用的流程;通过分析流程中的异常和失败的类型,增强系统的纠错能力,减少引擎处理的压力;对有着特殊应用的建模过程,能够方便地添加自定义的验证条件,为流程的正确运行提供有效的保障;向基于规则化的工作流系统提供建模完整性的方案,获得系统工作流的稳健性.     

基于行为建模的移动代理性能评估

针对移动代理的分布式应用性能评估需求,建立了移动代理生命周期中主要行为的网络负载模型和时间消耗模型.在3种典型分布式应用想定下,分析了基于C＼S模式和移动代理模式的应用实现基本过程,对两种模式下的网络负载和执行时间进行了仿真比较,结果证明了在访问节点数量较多,网络传输速率较低时,移动代理模式的具有更好性能.     

云模型和特征辐射源信息的平台目标识别

平台目标识别一般分为两个步骤,首先是对平台上辐射源的识别,然后通过辐射源和平台的关联进行平台识别.在辐射源识别阶段提出利用云模型描述和处理参数存在区间模糊和观测具有噪声的数据,较好地解决了对于带有复杂调制信号的辐射源识别问题.在平台识别阶段,就辐射源和平台关联的各种结果给出了新的计算样本和模板间匹配度的方法,并且提出利用平台的特征辐射源信息对平台识别结果进行进一步的筛选,以提高识别率.最后用仿真验证了该方法的有效性.     

TOT培训模式对我国警务硕士培养的几点启示

TOT培训是对培训者的培训,是欧盟开展成人教育的一种创新模式.通过浅析TOT培训模式,结合我国警务硕士培养目标和要求,从警务硕士培养理念、培养方法、管理与评估等方面提出了开展警务硕士专业学位研究生培养工作的几点思考.     

基于信息流的中枢疲劳脑电分析

为充分利用多导脑电信息,首次提出运用有向传递函数（DTF）方法,对不同中枢疲劳状态下导联间信息流的强度和方向的变化进行分析。研究结果表明,脑电功能耦合中额一到一顶方向的信息流是大脑皮层联系的一个固有特征,可以有效地刻画安静清醒和疲劳两个状态,长时间脑力劳动任务引起中枢疲劳的增加,进而导致整个频率段占优势的信息流的方向发生了反转,信息流占优势的方向从实验前的顶一到一额方向,转变为实验后的额一到一顶方向。