对高校人事档案管理工作的探讨

阐述了高校人事档案的作用,分析了高校人事档案管理中存在的问题,通过对问题产生的原因进行分析,提出了加强高校人事档案管理工作的对策。     

中学学习型教师团队建设探索——以华山中学为例

学习型组织具有五个要素,即自我超越、改善心智模式、建立共同愿景、团队学习、系统思考,学习型教师团队同样要符合这些特征。为此,华山中学开展了积极探索,提出创建学习型教师团队的关键是:建立共同愿景,提升生命力;改变学习方式,增强学习力;变革管理模式,培养创造力。初步营造出了凝心聚力实现又好又快发展的良好教育氛围,促进了学校教育实践的全面开展。     

浅谈高中班级管理三步走

面对竞争激烈的高考,如何让学生健康向上的成长,班级氛围至关重要。氛围的形成,关键在班主任管理。本文明确了高一、高二、高三三个阶段管理的重点,并谈及到多种合理有效的做法,指出班级管理需用心更需用情。     

Choosing arrival process models for service systems: Tests of a nonhomogeneous Poisson process

Service systems such as call centers and hospital emergency rooms typically have strongly time‐varying arrival rates. Thus, a nonhomogeneous Poisson process (NHPP) is a natural model for the arrival process in a queueing model for performance analysis. Nevertheless, it is important to perform statistical tests with service system data to confirm that an NHPP is actually appropriate, as emphasized by Brown et al. [8]. They suggested a specific statistical test based on the Kolmogorov–Smirnov (KS) statistic after exploiting the conditional‐uniform (CU) property to transform the NHPP into a sequence of i.i.d. random variables uniformly distributed on [0,1] and then performing a logarithmic transformation of the data. We investigate why it is important to perform the final data transformation and consider what form it should take. We conduct extensive simulation experiments to study the power of these alternative statistical tests. We conclude that the general approach of Brown et al. [8] is excellent, but that an alternative data transformation proposed by Lewis [22], drawing upon Durbin [10], produces a test of an NHPP test with consistently greater power. We also conclude that the KS test after the CU transformation, without any additional data transformation, tends to be best to test against alternative hypotheses that primarily differ from an NHPP only through stochastic and time dependence. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 66–90, 2014     

Power series expansions for the distribution and mean value function of a geometric process with Weibull interarrival times

The geometric process is considered when the distribution of the first interarrival time is assumed to be Weibull. Its one‐dimensional probability distribution is derived as a power series expansion of the convolution of the Weibull distributions. Further, the mean value function is expanded into a power series using an integral equation. © 2014 Wiley Periodicals, Inc. Naval Research Logistics, 61: 599–603, 2014     

面向大型机构的统一身份管理方法

通过借鉴自由联盟组织提出的Liberty框架,并针对该框架的结构以及身份提供者之间信任关系的建立模式进行改造,提出一种面向大型机构的新型身份管理联盟。新型的身份管理联盟比Liberty框架更加适用于具有分布性、自治性、全局性和协同性的大型机构。新型的身份管理联盟在物理结构上可看作由多个身份提供者节点组成的一棵树,其中每个身份提供者节点必须并且只能与其父节点和子节点建立信任关系,这与现实中各个大型机构的树状层级结构是完全相符的。在系统实现过程中,依托新型身份管理联盟的树状结构,并采用LDAP实现了用户认证数据的分级存储。此外还通过安全认证网关在网络层对用户的接入进行控制,从而能够同时支持B/S和C/S两类应用系统的单点登录。     

基于数据站场的系统效能评估决策支持方法

随着信息技术的发展,系统信息量的提升给军事系统效能评估带来了新的问题。针对系统效能分析数据非线性、高维数、强耦合的特点,提出了一种基于数据站场技术的效能评估决策支持方法。通过数据恢复、约减、求精与重构操作,对评估数据进行了处理,并搭建了数据站场立方体,降低了数据间的依赖性,满足了不同层面系统分析的需求。以面向任务的网络化火控系统的为例,进行了系统效能评估、时效性评估和指标分析,从三个层次验证了方法的有效性与可行性。将数据挖掘技术应用到仿真系统效能评估决策中,获得了更广泛的应用。     

用非概率理论分析混合不确定性结构的可靠性

针对不确定性结构可靠性分析中的输入变量分布参数具有不确定性和输入变量为区间模型的混合不确定性结构展开研究。考虑到可用信息最少的情况,将分布参数的不确定性描述为区间模型。通过等概率转换方法将随机变量与其分布参数进行分离,使问题转化为随机与区间变量混合的可靠性问题,建立了混合不确定性问题的可靠性分析模型。基于非概率可靠性理论,建立混合不确定结构分析模型的二级极限状态函数并结合Kriging代理模型建立了高效的求解方法。将所建立的混合不确定模型应用于飞行器结构的不确定性分析中,验证了所建模型的合理性和所提方法的高效性和准确性。     

机动发射条件下助推滑翔导弹射击诸元快速解算

针对机动发射条件下助推滑翔导弹对全程弹道快速生成的迫切需求,在弹道设计中选取7个关键性控制量参数作为全程弹道射击诸元,并提出与之相对应的诸元解算算法。将全程弹道分为助推段、初始下降段、滑翔段和俯冲攻击段,在统一化运动模型描述的基础上,运用参数化迭代的思路,依次对不同飞行阶段诸元进行了快速求解,满足多种复杂约束条件。在全程诸元迭代解算模式的基础上,提出助推段沿用中心弹道诸元,仅对其他射击诸元进行重计算的部分诸元迭代解算模式。仿真结果表明:采用所提助推滑翔导弹射击诸元快速解算方法,可在大范围机动条件下对远距离地面固定目标进行快速精确打击。     

Bivariate models from univariate life distributions: A characterization cum modeling approach

Bivariate life distribution models are of importance for studying interdependent components. We present a generic approach by introducing a new concept of characterized model in stead of a characterized distribution. It strikes a balance between characterization and modeling approaches to eliminate their individual limitations and incorporate their respective strengths. The proposed model, being a characterized one, admits many important properties irrespective of the choice of marginal distributions. The retention of univariate IFR, DFR, IFRA, DFRA, NBU, and NWU class properties in the bivariate setup has been ensured along with some results on series combinations and convolution. No other models, available in the literature, can ensure simultaneous retention of these fundamental and extremely important class properties. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004