3C理论视角下项目管理合规风险预警机制浅探

合规管理是加快项目顺利推进的重要举措.建立健全项目管理过程中的合规管理机制,可以有效防范项目合规风险,保障项目持续健康有序推进.本文基于3C理论视角,结合实际情况,从分类、协调、协作角度来分析、识别合规风险,探讨项目管理合规风险预警机制的有效办法,构建合规管理闭环,持续提升合规管理实践.     

浅谈三层体系结构应用系统

通过对二种应用系统的编程模型,即两层体系结构与三层体系结构的比较,以本人之前在企业完成的工程项目—"某市社会保险信息管理系统"为例介绍了三层体系结构的工作流程、特点及优越性。     

基于LM3914的酒精浓度检测仪的设计

本文介绍了一种酒精浓度检测仪的设计方法,主要利用MQ一3酒精传感器检测酒精浓度,通过分压式电路将电阻转换为成比例的电压,再再利用线性显示驱动器LM3914驱动不同颜色的发光二极管和蜂鸣器提示检测得到的酒精浓度大小,并详细介绍了其调试方法。     

CTCS-2级及CTCS-3级列控系统方案优化探讨

CTCS-2级及CTCS-3级列控系统已广泛应用于我国高速铁路项目中,对保证高速铁路运行安全起到重要作用。在分析现有安全措施的基础上,针对一些意外情况、特殊场景等提出以下方案优化思路供研讨。     

移动IP技术应用前景探析

从介绍移动IP技术的概念入手,阐述了移动IP技术发展的客观必然性,讨论了3G时代移动IP技术的发展及其应用情况,并预示未来的4G时代,移动IP技术将成为应用极其普及的主流技术。     

三维地震勘探在高庄煤矿的应用效果分析

三维地震勘探对解决水域煤层构造和埋藏范围有精度高、成本低、见效快的特点。近年来随着数字地震水平的发展,尤其是野外数据仪器工作效率和勘探精度的提高,三维地震在煤田勘探和石油勘探等领域得到了广泛的应用。通过野外实际检验,该方法在高庄煤矿的实际应用中起到了很好的地质效果。     

移动IPv6技术及应用

快速增长的移动数据业务需求推动着IPv6(尤其是移动IPv6)和3G不断向前发展。文中对移动IPv6的关键技术——切换技术及QoS进行了描述,并在此基础上对移动IPv6在3G网络中的实现进行了探讨。     

Short and long run causality measures: Theory and inference

The concept of causality introduced by Wiener [Wiener, N., 1956. The theory of prediction, In: E.F. Beckenback, ed., The Theory of Prediction, McGraw-Hill, New York (Chapter 8)] and Granger [Granger, C. W.J., 1969. Investigating causal relations by econometric models and cross-spectral methods, Econometrica 37, 424–459] is defined in terms of predictability one period ahead. This concept can be generalized by considering causality at any given horizon h$h$ as well as tests for the corresponding non-causality [Dufour, J.-M., Renault, E., 1998. Short-run and long-run causality in time series: Theory. Econometrica 66, 1099–1125; Dufour, J.-M., Pelletier, D., Renault, É., 2006. Short run and long run causality in time series: Inference, Journal of Econometrics 132 (2), 337–362]. Instead of tests for non-causality at a given horizon, we study the problem of measuring causality between two vector processes. Existing causality measures have been defined only for the horizon 1, and they fail to capture indirect causality. We propose generalizations to any horizon h$h$ of the measures introduced by Geweke [Geweke, J., 1982. Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association 77, 304–313]. Nonparametric and parametric measures of unidirectional causality and instantaneous effects are considered. On noting that the causality measures typically involve complex functions of model parameters in VAR and VARMA models, we propose a simple simulation-based method to evaluate these measures for any VARMA model. We also describe asymptotically valid nonparametric confidence intervals, based on a bootstrap technique. Finally, the proposed measures are applied to study causality relations at different horizons between macroeconomic, monetary and financial variables in the US.