Model selection for covariance structures analysis in nursing research

Covariance structures analysis is often used in nursing research to appraise statistical models reflecting complex human health processes. The model selection approach in covariance structures analysis is designed to select the "best" model from a specified set of theoretically defensible, competing alternatives, all of which are viewed as approximations. Model selection criteria explicitly incorporate both model misfit in the population and sampling error to evaluate the set of models. The result is that interpretability of model parameters and goodness-of-fit are enhanced simultaneously. Relative merits of the model selection approach are identified in light of technical concerns, parsimony, and use of scientific theory in nursing.     

车辆四轮转向系统的控制方法

系统地评述了车辆四轮转向系统的原理及其控制方法的发展,在此基础上指出四轮转向系统的研究必须以闭环综合评价为出发点,并与其它主动安全技术相结合才能真正达到实用阶段。     

Super connectivity of Kronecker products of graphs

Let G₁ and G₂ be two connected graphs. The Kronecker product G₁×G₂ has vertex set V(G₁×G₂)=V(G₁)×V(G₂) and the edge set . In this paper, we show that if G is a bipartite graph with κ(G)=δ(G), then G×Kn(n?3) is super-κ.     

Scalable multi-variate analytics of seismic and satellite-based observational data

Over the past few years, large human populations around the world have been affected by an increase in significant seismic activities. For both conducting basic scientific research and for setting critical government policies, it is crucial to be able to explore and understand seismic and geographical information obtained through all scientific instruments. In this work, we present a visual analytics system that enables explorative visualization of seismic data together with satellite-based observational data, and introduce a suite of visual analytical tools. Seismic and satellite data are integrated temporally and spatially. Users can select temporal ;and spatial ranges to zoom in on specific seismic events, as well as to inspect changes both during and after the events. Tools for designing high dimensional transfer functions have been developed to enable efficient and intuitive comprehension of the multi-modal data. Spread-sheet style comparisons are used for data drill-down as well as presentation. Comparisons between distinct seismic events are also provided for characterizing event-wise differences. Our system has been designed for scalability in terms of data size, complexity (i.e. number of modalities), and varying form factors of display environments.     

斩拌滚揉机控制策略的研究与实现

针对斩拌滚揉机在滚揉过程中必须保持低温、真空的特点,首先在滚筒夹层设计带有制冷剂流动的蓄冷层以实现温度控制,其次采用PLC和变频器对滚筒和真空泵进行闭环控制,实现滚揉过程中螺旋桨叶的匀渐变速度调节,从而解决滚揉不足或滚揉过度造成的产品蛋白严重变性或保水性都较差的问题;实际运行结果表明,该控制系统具有精度高、运行稳定可靠、监控能力强、操作简便等特点,能够满足斩拌滚揉机的控制要求.     

Using jump-diffusion modeling for valuing real options in infrastructure projects

In infrastructure financed projects, in order to attract private investors, host governments often provide some guarantees. This paper develops a value model of minimum revenue guarantee with multiple-exercise real options under the impact of the emergency incident. The model is applied to infrastructure financed projects using the minimum revenue guarantee under simulation. The simulation results indicate that, before quantifying the value of the minimum revenue guarantee, it is necessary to forecast the jump degree and intensity of the emergency incident, as well as prevent and control risks arising from such emergencies. Otherwise, underestimation of the guarantee value will occur and the government will have to bear huge debt in this condition. We also analyze the dependence of the guaranteed value on the minimum guaranteed revenue level, initial revenue and number of exercise rights. For various conditions, the diagrams of the guaranteed value are also presented.     

A belief-rule-based inventory control method under nonstationary and uncertain demand

This paper is devoted to investigating inventory control problems under nonstationary and uncertain demand. A belief-rule-based inventory control (BRB-IC) method is developed, which can be applied in situations where demand and demand-forecast-error (DFE) do not follow certain stochastic distribution and forecasting demand is given in single-point or interval styles. The method can assist decision-making through a belief-rule structure that can be constructed, initialized and adjusted using both manager’s knowledge and operational data. An extended optimal base stock (EOBS) policy is proved for initializing the belief-rule-base (BRB), and a BRB-IC inference approach with interval inputs is proposed. A numerical example and a case study are examined to demonstrate potential applications of the BRB-IC method. These studies show that the belief-rule-based expert system is flexible and valid for inventory control. The case study also shows that the BRB-IC method can compensate DFE by training BRB using historical demand data for generating reliable ordering policy.     

污水处理厂工程自动控制系统

根据唐山市玉田县当地污水水质情况,针对奥贝尔氧化沟污水处理工艺的特点及其处理过程对控制的要求,采用PLC以及其它控制元件,完成对污水处理装置中的粗处理装置、排污泵的启停,氧化沟及沉淀池的控制,以及回流污泥处理系统、除磷加药系统等过程的顺序控制.并对安全系统的紧急停车进行PLC控制处理,从而实现了安全、稳定、高效、低耗的目的.     

选择重传ARQ结合自适应调制系统的跨层分析和设计

提出一种针对选择自动重传(SR-ARQ)技术结合自适应调制系统(AMS)的跨层分析和设计方法.该方法采用有限状态马尔可夫链(FSMC),同时对物理层和链路层进行建模,然后用更新报酬(renewal-reward)理论对系统的有效吞吐量进行精确分析,并根据分析结果设计系统中所使用的参数.计算机仿真结果验证了该跨层分析方法的精确性,并可以从中看出本方法对系统参数选取的指导意义.