灌装包装生产线效率评估系统的设计

针对国内一部分食品企业灌装包装生产线难以量化生产线效率的现状,提出了一套切实有效的生产线效率评估系统。通过评估设备速度V-曲线,以现代信息化技术为基础,提取出关键设备的停机记录,其中包含了停机的起始时间、终止时间、时长、分类、机台和原因等几大关键项内容,然后对内外部因素造成的各类时间损失进行准确量化评估,从而构建以总资产利用率、线毛产出率、设备综合利用率和线效率4项指标为衡量标准的一套生产线效率评估系统。本系统实现了灌装包装生产线数字化过程,整体透视出企业的综合管理能力、部门之间的协调配合能力、设备运行能力和故障处理能力。基于此数字化效率评估系统,可以分析停机成因,识别出影响生产线效率的核心要素,通过针对性的优化手段,达到提高效率的目的,实现降低成本和提高利润的业务目标。     

Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence

Most existing reduced-form macroeconomic multivariate time series models employ elliptical disturbances, so that the forecast densities produced are symmetric. In this article, we use a copula model with asymmetric margins to produce forecast densities with the scope for severe departures from symmetry. Empirical and skew t distributions are employed for the margins, and a high-dimensional Gaussian copula is used to jointly capture cross-sectional and (multivariate) serial dependence. The copula parameter matrix is given by the correlation matrix of a latent stationary and Markov vector autoregression (VAR). We show that the likelihood can be evaluated efficiently using the unique partial correlations, and estimate the copula using Bayesian methods. We examine the forecasting performance of the model for four U.S. macroeconomic variables between 1975:Q1 and 2011:Q2 using quarterly real-time data. We find that the point and density forecasts from the copula model are competitive with those from a Bayesian VAR. During the recent recession the forecast densities exhibit substantial asymmetry, avoiding some of the pitfalls of the symmetric forecast densities from the Bayesian VAR. We show that the asymmetries in the predictive distributions of GDP growth and inflation are similar to those found in the probabilistic forecasts from the Survey of Professional Forecasters. Last, we find that unlike the linear VAR model, our fitted Gaussian copula models exhibit nonlinear dependencies between some macroeconomic variables. This article has online supplementary material.     

Conditional VAR and Expected Shortfall: A New Functional Approach

We estimate two well-known risk measures, the value-at-risk (VAR) and the expected shortfall, conditionally to a functional variable (i.e., a random variable valued in some semi(pseudo)-metric space). We use nonparametric kernel estimation for constructing estimators of these quantities, under general dependence conditions. Theoretical properties are stated whereas practical aspects are illustrated on simulated data: nonlinear functional and GARCH(1,1) models. Some ideas on bandwidth selection using bootstrap are introduced. Finally, an empirical example is given through data of the S&P 500 time series.     

Robust Inference for Near-Unit Root Processes with Time-Varying Error Variances

The autoregressive Cauchy estimator uses the sign of the first lag as instrumental variable (IV); under independent and identically distributed (i.i.d.) errors, the resulting IV t-type statistic is known to have a standard normal limiting distribution in the unit root case. With unconditional heteroskedasticity, the ordinary least squares (OLS) t statistic is affected in the unit root case; but the paper shows that, by using some nonlinear transformation behaving asymptotically like the sign as instrument, limiting normality of the IV t-type statistic is maintained when the series to be tested has no deterministic trends. Neither estimation of the so-called variance profile nor bootstrap procedures are required to this end. The Cauchy unit root test has power in the same 1/T neighborhoods as the usual unit root tests, also for a wide range of magnitudes for the initial value. It is furthermore shown to be competitive with other, bootstrap-based, robust tests. When the series exhibit a linear trend, however, the null distribution of the Cauchy test for a unit root becomes nonstandard, reminiscent of the Dickey-Fuller distribution. In this case, inference robust to nonstationary volatility is obtained via the wild bootstrap.     

Unified multivariate survival model with a surviving fraction: an application to a Brazilian customer churn data

In this paper we propose a new lifetime model for multivariate survival data in presence of surviving fractions and examine some of its properties. Its genesis is based on situations in which there are m types of unobservable competing causes, where each cause is related to a time of occurrence of an event of interest. Our model is a multivariate extension of the univariate survival cure rate model proposed by Rodrigues et al. [37 J. Rodrigues, V.G. Cancho, M. de Castro, and F. Louzada-Neto, On the unification of long-term survival models, Statist. Probab. Lett. 79 (2009), pp. 753–759. doi: 10.1016/j.spl.2008.10.029[Crossref], [Web of Science ®] , [Google Scholar]]. The inferential approach exploits the maximum likelihood tools. We perform a simulation study in order to verify the asymptotic properties of the maximum likelihood estimators. The simulation study also focus on size and power of the likelihood ratio test. The methodology is illustrated on a real data set on customer churn data.     

基于CAN总线的隧道通风监测系统设计

为了实现隧道通风监测系统的高安全可靠性、远距离信息传输、多节点网络监测等要求,提出了基于CAN总线 技术的隧道通风监控系统。设计了基于CAN总线技术的控制系统硬件结构,介绍了烟雾和温度检测原理;设计了基于 CAN总线的通风系统监测节点;设计了工控机与CAN总线通信接口适配卡;设计了系统主程序、事件检查和处理子程序 的流程图。应用结果表明该系统具有传输距离远、监测网络节点多等特点,大大提高了系统的实时性和可靠性。     

“镇改市”过程中的制约因素与改革进路

“镇改市”是我国基层行政体制改革的试验,也是在新型城镇化过程中对基层行政区划改革做出的有益尝试。以构建大中小城市和小城镇协调发展的城镇化空间格局为目标指向,通过激活中小城市的发展“命脉”,改变单纯依靠经济推动乡镇发展的路径依赖,实现“农民城”向新型城镇的跨越,是中国经济发展的新探索。然而,随着改革的推进,缺位的行政规划设计、有限的乡镇管理能力、被异化的政绩观念、社会组织发育不成熟以及市民文化普及不到位等,对“镇改市”的推进造成一定程度的制约,成为“镇改市”过程中难以回避的现实问题。问题的化解离不开政策的引导、技术的支持和法治的保障,这三个维度相互联系、缺一不可,共同为“镇改市”改革的顺利实施“保驾护航”。     

协商民主与政治参与——一种重要的扩大公民有序政治参与的民主形式

协商民主是一种重要的扩大有序政治参与的民主形式。其主要体现为：协商民主有利于整合政治过程中的利益冲突;有利完善政治系统的结构与功能;有利于形成科学和民主的公共决策;有利于促进参与型政治文化的形成。