基于可穿戴的老年康复护理生理指标监测装置设计

伴随着社会的发展,老年人的健康意识不断增强,康复护理成为当前老年人保健的重要途径,目前多采用生理指标监测装置帮助医护人员完成护理工作,但当前装置对于生理指标数据处理能力较差,导致医护人员无法获取到高精度的生理数据。针对此问题,设计基于可穿戴的老年康复护理生理指标监测装置。使用ARM Cortex-M4处理器作为中央控制芯片,并对老年康复护理生理指标监测装置整体参数进行优化。采集用户体温数据、心率数据以及血压数据,使用聚类分析法对其展开分析。对生理指标监测信息进行汇总,使用层次分析法分析用户生理指标变化风险,及时发出警报。至此,基于可穿戴的老年康复护理生理指标监测装置设计完成。构建应用测试可知,可穿戴装置的应用效果优于当前装置,可将其应用到老年人的康复护理中。     

中文微博客的垃圾用户检测

微博客的出现改变了我们获取信息的方式。然而,大量垃圾消息却此起彼伏,危害着微博的健康发展。该文研究了中文微博客中的垃圾用户检测问题。我们首先对垃圾用户的行为进行了分析,提出了基于用户图、用户资料、微博内容的3大类7种检测特征。随后,讨论了基于SVM分类器的垃圾用户检测方法。最后,我们对采集的微博数据进行了标注,并评价了分类器的效果。实验表明: 分类器具有较高的准确率和召回率,该文提出的特征具有较好的区分度。     

基于文本内容分析的微博广告过滤模型研究

针对新浪、腾讯等微博平台出现大量广告的问题,提出一个微博广告过滤模型。通过对数据的预处理,将采集到的微博原始数据转换成干净且计算机易处理的数据。在预处理阶段,根据微博文本的特点,对停用词表进行改进,以提高查准率,然后基于支持向量机构建一个训练分类器对数据进行训练,经过不断的学习和反馈,取得较好的分类效果。实验结果表明,该模型进行广告过滤时准确率超过90%,效果优于基于关键字的方法。     

一种基于用户商业行为的数据采集分析方案

为了有效利用用户在互联网上留下的痕迹数据,提高电子商务平台的购买转化率,提出一种基于用户商业行为的数据采集分析方案.该方案对痕迹数据进行分类采集,通过即定评价指标进行深层次挖掘,与关联规则库进行比对匹配,形戚满足用户需求的推荐内容.应用表明,痕迹数据的采集全面可靠,评价体系指标设定合理,推荐内容符合用户满意度.     

基于动态分类器集成的MEMS气体传感器阵列的气体定性识别方法

气体识别研究中,传感器的性能漂移问题始终是最具挑战的问题之一。为了减少漂移对气体识别的影响,本文利用动态分类器集成技术,针对基于MEMS技术的气体传感器阵列,提出了气体识别方法。本方法主要关注对气体样本在任意浓度下的定性分析。该方法基于支持向量机（SVM）分类器,首先利用在不同时间段采集的数据分别训练SVM分类器,再利用各分类器对不同时期数据的最优权值,估计拟合函数的参数;然后利用拟合函数,根据数据的采集时刻,预测各分类器的权值;最终利用预测的权值,对所有分类器的识别结果进行集成,得到最终识别结果。本文利用三年的测量数据,对该方法与已有类似方法的性能进行了比较。结果显示,该方法可以在较长时间内具有更高的准确率。而且,该方法可以通过选择更合理的拟合函数,提高识别性能。     

基于DSP的嵌入式在线振动信号分析系统

为监测机械设备的工作状态,对机械设备工作过程中产生的振动信号进行采集、处理和分析,从而实现系统的状态监测、故障诊断以及寿命预测等;但目前振动信号分析系统体积较大、不方便携带,多用于离线的振动信号处理,难以完成机械设备振动信号的在线实时分析;针对振动信号离线分析系统存在实时性低、体积大等不足,设计了基于TMS320C6713 DSP的嵌入式振动信号采集处理系统,以满足机械设备振动信号采集、处理和分析过程中对采集、处理实时性,系统便携性等需求;详细介绍了系统的软硬件设计原理和方法,利用美国凯斯西储大学的公开轴承测量数据集对系统的各项功能和技术指标进行实验验证;实验结果表明,该系统能够正常工作且可应用于实际工程中;另外,系统支持功能和算法扩展,以满足不同机械设备的振动信号采集、处理和分析需求。     

支持隐私保护的k近邻分类器

k近邻（k-nearest neighbor,简称kNN）分类器在生物信息学、股票预测、网页分类以及鸢尾花分类预测等方面都有着广泛的应用.随着用户隐私保护意识的日益提高,kNN分类器也需要对密文数据提供分类支持,进而保证用户数据的隐私性,即设计一种支持隐私保护的k近邻分类器（privacy-preserving k-nearest neighbor classifier,简称PP-kNN）.首先,对kNN分类器的操作进行分析,从中提取出一些基本操作,包括加法、乘法、比较、内积等.然后,选择两种同态加密方案和一种全同态加密方案对数据进行加密.在此基础上设计了针对基本操作的安全协议,其输出结果与在明文数据上执行同一方法的输出结果一致,且证明该协议在半诚实模型下是安全的.最后,通过将基本操作的安全协议进行模块化顺序组合的方式实现kNN分类器对密文数据处理的支持.通过实验,对所设计的PP-kNN分类器进行测试.结果表明,该分类器能够以较高效率实现对密文数据的分类,同时为用户数据提供隐私性保护.     

LabVIEW机械故障诊断系统的Web实现

本文针对机械设备远程故障诊断的振动数据分析问题,设计了一种在Web浏览器中进行机械设备振动数据实时显示和频谱分析的方法。首先,LabVIEW程序通过以太网从工业现场采集实时振动数据并以网络共享变量发布;然后,LabVIEW Web Service服务程序根据用户请求获取实时振动波形数据或对数据进行频谱分析,将数据以XML方式返回;最后,客户端的浏览器中分别采用Flex和Ajax对XML进行解析并显示实时波形和特征参数。该方法快速、稳定、可靠,很好地解决了远程故障诊断的问题。     

文本分类器性能评估指标

讨论了用传统性能评估指标(精度和错误率)评估文本分类器时面临的困难，分析了目前几种常用的文本分类器性能评估指标：查全率-查准率曲线、AUROC、Fi值以及BEP值的优点与不足，并提出了两种新的可用于文本分类器的性能评估指标。     

随机森林在滚动轴承故障诊断中的应用

针对不同轴承数据特征选择困难和单个分类器方法在滚动轴承故障诊断中精度较低的问题,提出了一种基于分类回归树（CART）的随机森林滚动轴承故障诊断算法。随机森林是包含了多种分类器的集成学习方法。通过随机森林的“集成”思想来提高滚动轴承故障诊断的精度。从滚动轴承的振动信号中提取时域统计指标,将其作为特征向量,利用随机森林（Random Forest）对滚动轴承故障进行诊断。利用SQI-MFS实验平台的轴承数据,与传统分类器（SVM、kNN和ANN）以及单个分类回归树的诊断结果相比,随机森林算法具有比较高的诊断精度。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.