立体标签自动贴标机结构设计

为了减少在产品包装环节中的人员参与,提高包装环节的自动化程度,研制了一种用于立体标签的自动贴标机。 根据产品贴标的流程,采用Pro/E软件进行三维建模和零部件的优化设计,包括传送机构、标签推进机构和折弯机构。 折弯机构中采用了折弯翻板实现对标签的折弯控制;自动贴标机各机构均采用了独立的电机控制,控制系统采用PLC 技术和变频器调速控制,设计了电动机正反转的控制电路图。通过对机械结构和电气控制系统优化设计,得到了满足设 计要求的自动贴标机机构设计参数,实现了对厚度为0.5 mm纸质标签纸的2次折弯并实现贴标过程。该自动标签机的 使用实现了包装过程的自动化,提高产品的包装效率。     

虚拟机软件在中职网络教学和实训中的应用

随着全国中等职业学校计算机技能大赛的举办,中职学校网络实训环境发生了改变,虚拟机软件在网络教学中得到了广泛的应用.通过虚拟机软件可以建立虚拟化的实训环境,模拟真实的计算机系统.使用虚拟机软件既可以克服教学资源和设备不足的困难,又可以解决实训时长不足,完成真实环境难以实现的实训任务,保证网络教学和实训的顺利进行.     

采用汇文系统实现统编工作的探索

统一编目工作是促进图书馆业务工作自动化与标准化的重要技术,笔者从采用汇文系统进行统编工作的实践尝试中,探讨了统编工作中存在的一些实际问题,并提出了解决方案.     

Estimation with right‐censored observations under a semi‐Markov model

The semi‐Markov process often provides a better framework than the classical Markov process for the analysis of events with multiple states. The purpose of this paper is twofold. First, we show that in the presence of right censoring, when the right end‐point of the support of the censoring time is strictly less than the right end‐point of the support of the semi‐Markov kernel, the transition probability of the semi‐Markov process is nonidentifiable, and the estimators proposed in the literature are inconsistent in general. We derive the set of all attainable values for the transition probability based on the censored data, and we propose a nonparametric inference procedure for the transition probability using this set. Second, the conventional approach to constructing confidence bands is not applicable for the semi‐Markov kernel and the sojourn time distribution. We propose new perturbation resampling methods to construct these confidence bands. Different weights and transformations are explored in the construction. We use simulation to examine our proposals and illustrate them with hospitalization data from a recent cancer survivor study. The Canadian Journal of Statistics 41: 237–256; 2013 © 2013 Statistical Society of Canada     

聚酯聚合反应分层温度控制系统

介绍了聚合釜聚酯聚合反应温度过程控制系统及其设计方法。控制系统以高性能单片机系统为直控机（DDC）,PC机为上位机（MIS）,直控机负责聚合釜釜温及夹套温度采集、分析、控制,并将参数送上位机。上位机负责控制过程的时间及温度值设定、温度监测、工作过程监控。     

纸机传动控制系统的配置与控制原理

针对纸机日益高速化、大型化的发展趋势，设计了国内先进的全数字化通信网络传动控制系统。系统采用西门子全集成自动化解决方案，实现造纸生产过程的全线集成控制。高可靠的工业现场总线PROFIBUS—DP和工业以太网相结合的网络结构，有效地实现了数据共享，全面解决了整个工艺过程的控制。文章详细介绍了控制系统的配置和功能，重点阐述了速度链、负荷分配控制、张力控制等主要控制原理。     

Simultaneous confidence band for the difference of segmented linear models

Consider comparing between two treatments a response variable, whose expectation depends on the value of a continuous covariate in some nonlinear fashion. We fit separate segmented linear models to each treatment to approximate the nonlinear relationship. For this setting, we provide a simultaneous confidence band for the difference between treatments of the expected value functions. The treatments are said to differ significantly on intervals of the covariate where the simultaneous confidence band does not contain zero. We consider segmented linear models where the locations of the changepoints are both known and unknown. The band is obtained from asymptotic results.     

多层超高砖砌体房屋的抗震设计研究

本文根据“小震不坏,大震不倒”的抗震原则,对多层砖砌体房屋进行了强度分析,对构造柱和混凝土事本抗剪强度的影响进行了分析,提出了只要严格加强构造措施,砖砌体结构的高度超过规范规定的限值也能保证其安全性的观点。     

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously.

In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems.     

Machine gaming in Sydney clubs: characteristics of the supporting resident populations

This research provided background for surveys and interviews in later stages of a 3 part project. It aimed to identify, from secondary research, sociodemographic characteristics which tend to support registered clubs and their machine gaming activities in the Sydney Statistical Division. Using multiple methods including Pearson's Product Moment correlation, Principal Components factor analysis, and stepwise regression, the study profiled Sydney populations which spend highly on gaming machines. The most important sociodemographic predictors of Sydney statistical local areas where per capita gaming machine expenditure is high are large proportions of the adult resident population who were born in Malta, Greece, Lebanon, China, Italy, Vietnam, Yugoslavia, India or the Philippines; have no vocational or tertiary qualifications; or are unemployed.