Real‐Time Forecasts of Inflation: The Role of Financial Variables

We present a mixed‐frequency model for daily forecasts of euro area inflation. The model combines a monthly index of core inflation with daily data from financial markets; estimates are carried out with the MIDAS regression approach. The forecasting ability of the model in real time is compared with that of standard VARs and of daily quotes of economic derivatives on euro area inflation. We find that the inclusion of daily variables helps to reduce forecast errors with respect to models that consider only monthly variables. The mixed‐frequency model also displays superior predictive performance with respect to forecasts solely based on economic derivatives. Copyright © 2012 John Wiley & Sons, Ltd.     

Virtual reality mobility model for wireless ad hoc networks

For wireless ad hoc networks simulation, node＇s mobility pattern and traffic pattern are two key elements. A new simulation model is presented based on the virtual reality collision detection algorithm in obstacle environment, and the model uses the path planning method to avoid obstacles and to compute the node＇s moving path. Obstacles also affect node＇s signal propagation. Considering these factors, this study implements the mobility model for wireless ad hoc networks. Simulation results show that the model has a significant impact on the performance of protocols.     

多阶段任务系统任务持续能力仿真模型研究

多阶段任务系统(PMS)是一种典型的复杂系统,它包括多个在时间上连续且无相互重叠的阶段任务,执行作战与使用任务的武器装备多数属于这种复杂系统。分析了PMS及任务可靠度、可信度和任务效能等任务持续能力评价参数。结合实际装备系统大都属于可用马尔可夫过程进行描述的可修复系统的特点,为简化模型复杂程度提出了一些合理的假设条件。在此基础上,结合多阶段任务系统自身特点,通过分析多阶段任务系统任务持续能力建模仿真步骤,多阶段任务系统任务效能仿真方法,建立了基于Petri网的多阶段任务系统任务效能多层仿真模型。最后结合常见的"靶场打靶"任务进行了实例验证,并对仿真结果进行了分析。     

A linear benchmark for forecasting GDP growth and inflation?

Predicting the future evolution of GDP growth and inflation is a central concern in economics. Forecasts are typically produced either from economic theory‐based models or from simple linear time series models. While a time series model can provide a reasonable benchmark to evaluate the value added of economic theory relative to the pure explanatory power of the past behavior of the variable, recent developments in time series analysis suggest that more sophisticated time series models could provide more serious benchmarks for economic models. In this paper we evaluate whether these complicated time series models can outperform standard linear models for forecasting GDP growth and inflation. We consider a large variety of models and evaluation criteria, using a bootstrap algorithm to evaluate the statistical significance of our results. Our main conclusion is that in general linear time series models can hardly be beaten if they are carefully specified. However, we also identify some important cases where the adoption of a more complicated benchmark can alter the conclusions of economic analyses about the driving forces of GDP growth and inflation. Copyright © 2008 John Wiley & Sons, Ltd.     

The neurotrophic receptor TrkB: a drug target in anti-cancer therapy?

Increasing evidence implies altered signaling through the neurotrophic receptor tyrosine kinase TrkB in promoting tumor formation and metastasis. TrkB, sometimes in conjunction with its primary ligand BDNF, is often overexpressed in a variety of human cancers, ranging from neuroblastomas to pancreatic ductal adenocarcinomas, in which it may allow tumor expansion and contribute to resistance to anti-tumor agents. In vitro, TrkB acts as a potent suppressor of anoikis (detachment-induced apoptosis), which is associated with the acquisition of an aggressive tumorigenic and metastatic phenotype in vivo. In view of its predicted contribution to tumorigenicity and metastasis in humans, TrkB corresponds to a potential drug target, and preclinical models have already been established. The encouraging results of pharmacological Trk inhibitors in tumor xenograft models suggest that TrkB inhibition may represent a promising novel anti-tumor therapeutic strategy. This hypothesis is currently being evaluated in clinical trials. Here, we will discuss the latest developments on TrkB in these contexts as well as highlight some critical questions that remain to be addressed for evaluating TrkB as a therapeutic target in cancer. Received 12 October 2005; received after revision 19 December 2005; accepted 11 January 2006     

一类应力——强度干涉模型的Bayes可靠性分析

在应力—强度干涉模型中，当应力服从指数分布，强度服从伽玛分布情况下讨论了给定验前分布情况下可靠度的Bayes估计。并给出了数值例子，通过分析表明，Bayes模拟结果较好。     

内燃机工作过程多维模型计算机仿真平台设计与实现

设计了内燃机工作过程仿真集成化PC平台.以缸内流体动力学为基础,耦合反映缸内工作过程的喷射、燃烧和碳烟生成等子模型构建了平台的多维模型;通过设置Compaq Visual Fortran软件的双精度运行环境,在PC微机上成功编译了KIVA-3V源代码;然后通过设计可视化模块,实现了平台计算与可视的集成化功能.试验分析表明:仿真平台能模拟内燃机缸内工作过程,准确反映客观物理因素对工作过程的影响,仿真误差小于5%,可以在内燃机行业推广.     

一种不完全微分PID的多环Smith预估控制

提出一种不完全微分PID控制器组态,代替理想的PID控制器进行控制.对于系统外扰的影响,采用一种多环Smith预估器系统,利用MATLAB进行仿真.结果表明,该控制系统具有良好的抗外扰性能,可改善系统的调节品质.     

用微分方程方法研究红绿灯控制下的交通流模型

红绿灯模型是交通流动力学模型研究中一个重要而困难的问题,首先给出交通流模型,然后给出红绿灯交通流模型与特征线的求解,根据红绿灯模型与特征线意义,对交通流的红绿灯转换周期的设置具有重要意义．     

一种模糊高斯混合说话人识别模型

为了研究模糊聚类算法在高斯混合模型（GMM）参数获取方面的应用,采用模糊C均值算法（FCM）进行语音特征矢量的聚类,并结合Tabu搜索算法得到全局最优的聚类结果,进一步用EM算法得到GMM模型参数.使用TIMIT数据库中的语音进行测试,开集和闭集说话人辨认实验都表明,该方法获取的GMM参数比普通EM算法获得的GMM模型参数性能更优,能有效降低说话人辨认系统的误识率.