探析产品设计中的“绿色设计”

由于环境的恶化、自然资源的有限和过度开采,倡导环境和资源保护的绿色设计必将成为今后产品设计的主流之一;社会的可持续发展的要求预示着"绿色设计"将成为现代产品设计的重要思想。然而多数人对绿色设计真正含义并不十分明确。本文就绿色设计的具体含义作了具体的分析,并把绿色设计的内容和趋势进行了新的总结和拓展。     

数据挖掘在电子商务中的应用研究

本文主要介绍数据挖掘在电子商务中的应用,文章从数据挖掘的定义、数据挖掘的常用方法出发,阐述了数据挖掘在海量信息中提取有效信息的作用,特别是数据挖掘与电子商务的结合可以给人们生活带来便利,给企业带来新的利润空间以及为企业提供决策支持。常用的数据挖掘技术主要包括支持向量机、朴素贝叶斯、聚类、决策树、神经网络和关联规则等,最后介绍了数据挖掘在电子商务的4个主要应用方面,说明了数据挖掘存在的必要性。     

对SQL Server数据库的安全和管理策略探讨

自微软公司推出SQL Server关系数据库管理系统以来,其在越来越多的电子商务网站和企业信息平台中得以广泛使用。然而与之相关的信息安全问题也日益凸现和受到用户的密切关注。因此,为了保护SQL Server数据库避免来自各种途径的安全威胁,保障信息的安全,本文对其安全机制、安全策略和保障其安全的管理策略进行了探讨,提出了相应的解决措施和办法,以供参考。     

基于RTLinux的开放式软件PLC的研究*

开放式控制技术是工业控制技术的发展趋势之一,软件PLC是开放式控制系统的重要组成部分。开放式控制系统实现的一条重要途径就是充分利用PC的软硬件资源,最大限度地利用软件实现控制功能。通过软件分层与数据开放相结合的方法,在RTLinux下设计的开放式软件PLC就是这种思想体现。     

Random-effects regression analysis of correlated grouped-time survival data

Random-effects regression modelling is proposed for analysis of correlated grouped-time survival data. Two analysis approaches are considered. The first treats survival time as an ordinal outcome, which is either right-censored or not. The second approach treats survival time as a set of dichotomous indicators of whether the event occurred for time periods up to the period of the event or censor. For either approach both proportional hazards and proportional odds versions of the random-effects model are developed, while partial proportional hazards and odds generalizations are described for the latter approach. For estimation, a full-information maximum marginal likelihood solution is implemented using numerical quadrature to integrate over the distribution of multiple random effects. The quadrature solution allows some flexibility in the choice of distributions for the random effects; both normal and rectangular distributions are considered in this article. An analysis of a dataset where students are clustered within schools is used to illustrate features of random-effects analysis of clustered grouped-time survival data.     

Adaptive tracking control of leader–follower systems with unknown dynamics and partial measurements

In this paper, a decentralized adaptive tracking control is developed for a second-order leader–follower system with unknown dynamics and relative position measurements. Linearly parameterized models are used to describe the unknown dynamics of a self-active leader and all followers. A new distributed system is obtained by using the relative position and velocity measurements as the state variables. By only using the relative position measurements, a dynamic output–feedback tracking control together with decentralized adaptive laws is designed for each follower. At the same time, the stability of the tracking error system and the parameter convergence are analyzed with the help of a common Lyapunov function method. Some simulation results are presented to validate the proposed adaptive tracking control.     

世界化纤发展趋势

对纤维的需求不断增长，天然纤维缺口将愈来愈大，均为化纤发展带来了机遇。化纤工业竞争激烈，主要趋势为扩大规模提高效率。无人化、环保化也是一种趋势。同时也发展了一些与下游名牌产品联系在一起的小型专业厂．高技术、高性能纤维发展较快．在技术方面，认为纤维超细化、废弃物回收重新纺制纤维，注意环保，设备增容、高效化，高性能纤维开发等是主要趋势．     

下河沉积型瓷石的工艺特性与开发应用的探讨

本文论述了新近在江西下河发现的沉积型瓷石的地质特点、矿石特征、精泥性能、成瓷工艺及其开发应用前景。     

一种适用于降压DC-DC的改进型电流检测电路

基于电流模式控制能够较好地改善DC-DC的性能,设计一种适用于降压DC-DC的改进型电流检测电路,所提出的电流检测电路提高了电流感应的速度和精度。通过对电路的理论分析与设计,采用SMIC 0.18μm CMOS工艺模型,利用Cadence工具对电路进行仿真验证,所提出的电流检测电路在负载电流为50 mA~500 mA时都能够达到96%的效率以及小于40 ns的建立时间。在开关频率为2 MHz时,输入电压范围为2.5 V~4.2 V,所需电感值为4.7μH,电容值为10μF,输出电压纹波小于18 mV。     

Interaction‐Feature Enhanced Multiuser Model Learning for a Home Environment Using Ambient Sensors

Activity recognition (AR) is a key enabler for a context‐aware smart home since knowing what the residents’ current activities helps a smart home provide more desirable services. This is why AR is often used in assistive technologies for cognitively impaired people to evaluate their abilities to undertake activities of daily living. In a real‐life scenario, multiple‐resident AR has been considered as a very challenging problem, primarily due to the complexity of data association. In addition, most prior research has not considered the potential interpersonal interactions among residents to simplify complexity, especially in an environment monitored by ambient sensors. In this study, we propose two types of multiuser activity models, both of which are derived from an interaction‐feature enhanced multiuser model learning framework. These two models consider interpersonal interactions and data association for multiuser AR using ambient sensors. We then compare their performance with the other two baseline models with or without consideration of data association and interpersonal interactions. The experimental results show that the derived models outperform other baseline classifiers. Therefore, the proposed approach can increase the opportunities for providing context‐aware services for a multiresident smart home.