基于数字图像处理的纺织物辅助设计模拟系统开发

文章研究并设计了一种基于数字图像处理技术( DIP)的纺织物辅助设计模拟系统。该系统通过将极大化思想、 K-means聚类以及形态学开闭运算有机结合,成功实现了从实际织物组织图中自动提取组织形态学结构,并提出了一种 全新的组织纱线色彩替换算法,将各种组织结构模拟到纺织物设计图样中。实验证明,该系统能够实现很好的组织模拟 效果。     

新一代信息技术驱动的产品适应性创新机制

现有产品创新研究多从用户、产品以及技术单一视角出发,然而,进入数字经济时代,在新一代信息技术驱动下,产品以用户、企业、环境多维互动的方式进行创新,呈现出特有的适应性创新特征。本文采取多案例研究方法,探讨在新一代信息技术驱动下产品适应性创新的特征和实现机制。研究发现:产品适应创新具有高频互动、即时反馈、快速适应性和用户主导创新四个显著特征,形成用户、企业、产品多方互动的适应性创新实现机制。与此同时,通过案例论证以产品、场景、用户为核心特征的产品适应创新实现机制的存在性,指出其本质是深入挖掘用户需求并实现用户需求的快速匹配。     

“信息处理”专业课程群建设研究

本文分析了电子信息工程专业信息处理专业课程群建设的必要性和可行性,并讨论了信息处理专业课程群研究与建设的内容和方法。     

记录纵向输出中的汉字处理

本文针对中文管理系统中记录纵向输出的特点，提出了记录纵向输出中的通用汉字处理方法，给出了实现算法。     

基于视觉传感的焊缝跟踪系统研究现状

视觉传感技术在焊接机器人上的应用,大大提高了机器人的焊接效率和焊接质量。文中介绍了基于视觉传感的 焊缝跟踪系统的分类及主动视觉和被动视觉技术的基本原理;分析了图像处理技术的滤波去噪、图像分割与边缘检测和 特征分析等研究方法;分析了焊缝跟踪系统的控制结构和智能控制技术的应用现状。最后提出根据视觉传感系统测得 焊缝的信息,实时调节焊接参数以及焊枪角度等工艺参数进行自动化和智能化焊接是未来发展方向。     

A simple two-stage design for quantitative responses with application to a study in diabetic neuropathic pain

Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to be stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase II and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail.     

Approximating the risk score for disease diagnosis using MARS

In disease screening and diagnosis, often multiple markers are measured and combined to improve the accuracy of diagnosis. McIntosh and Pepe [Combining several screening tests: optimality of the risk score, Biometrics 58 (2002), pp. 657–664] showed that the risk score, defined as the probability of disease conditional on multiple markers, is the optimal function for classification based on the Neyman–Pearson lemma. They proposed a two-step procedure to approximate the risk score. However, the resulting receiver operating characteristic (ROC) curve is only defined in a subrange (L, h) of false-positive rates in (0,1) and the determination of the lower limit L needs extra prior information. In practice, most diagnostic tests are not perfect, and it is usually rare that a single marker is uniformly better than the other tests. Using simulation, I show that multivariate adaptive regression spline is a useful tool to approximate the risk score when combining multiple markers, especially when ROC curves from multiple tests cross. The resulting ROC is defined in the whole range of (0,1) and is easy to implement and has intuitive interpretation. The sample code of the application is shown in the appendix.     

Doubly adaptive biased coin designs with heterogeneous responses

Doubly adaptive biased coin design (DBCD) is an important family of response-adaptive randomization procedures for clinical trials. It uses sequentially updated estimation to skew the allocation probability to favor the treatment that has performed better thus far. An important assumption for the DBCD is the homogeneity assumption for the patient responses. However, this assumption may be violated in many sequential experiments. Here we prove the robustness of the DBCD against certain time trends in patient responses. Strong consistency and asymptotic normality of the design are obtained under some widely satisfied conditions. Also, we propose a general weighted likelihood method to reduce the bias caused by the heterogeneity in the inference after a trial. Some numerical studies are also presented to illustrate the finite sample properties of DBCD.     

C2C网上交易中信号机制的有效性分析

本文应用Berry等(1995)^[2]提出的离散选择需求模型和差异产品的伯川德竞争模型,并利用淘宝网上的交易数据,对声誉、消费者保障计划、保修服务及信息披露四种信号策略在网上交易中的作用进行了实证研究。需求估计结果表明消费者保障计划中的"7天无理由退换货"计划以及保修服务可以作为产品质量的信号;而在其他有效信号策略存在的情况下,消费者保障计划中的"先行赔付"计划以及卖家声誉作为质量信号的作用则被削弱。成本分析表明,信息披露虽然可以提高消费者购买的可能性,但是由于发出信号的成本太低,容易被低质量卖家所模仿,因此并不能作为有效的质量信号。本文首次从供给和需求两个方面分析了信号机制在信息不对称情况下的效应及其作用机制。     

Trend estimation of multivariate time series with controlled smoothness

This paper extends the univariate time series smoothing approach provided by penalized least squares to a multivariate setting, thus allowing for joint estimation of several time series trends. The theoretical results are valid for the general multivariate case, but particular emphasis is placed on the bivariate situation from an applied point of view. The proposal is based on a vector signal-plus-noise representation of the observed data that requires the first two sample moments and specifying only one smoothing constant. A measure of the amount of smoothness of an estimated trend is introduced so that an analyst can set in advance a desired percentage of smoothness to be achieved by the trend estimate. The required smoothing constant is determined by the chosen percentage of smoothness. Closed form expressions for the smoothed estimated vector and its variance-covariance matrix are derived from a straightforward application of generalized least squares, thus providing best linear unbiased estimates for the trends. A detailed algorithm applicable for estimating bivariate time series trends is also presented and justified. The theoretical results are supported by a simulation study and two real applications. One corresponds to Mexican and US macroeconomic data within the context of business cycle analysis, and the other one to environmental data pertaining to a monitored site in Scotland.