基于群智感知的校园活动信息采集与分享系统

近年来,随着可内嵌多种传感器的智能手机的快速普及和应用,群智感知计算技术作为一种新的感知模式逐步发展起来。为了使大型社区的工作和生活变得更加丰富便捷,文章将群智感知计算技术应用于大学校园社区中。针对传统校园活动信息发布形式(如贴海报、布置展板)的相对闭塞性和不及时性(实时活动往往在事后报道)等问题,研究了基于群智感知的校园活动信息采集与分享系统FocusSense。该系统以校园内大量手机用户为移动传感节点,通过图像信息采集来共享用户关注的校园内活动信息(活动通知或实时活动),以此来帮助学生及时、高效而全面的获取校园内活动信息。     

融合多模信息感知的低功耗行为识别

行为识别在普适计算领域有着极大的应用前景,可广泛应用于医疗监护、智能家居/办公、商业服务等方面.其中基于传感器的行为识别因其分布范围广、不具侵扰性等优点,已成为目前的研究热点之一.采用机器学习理论和方法,提出了一种基于多模传感信息感知和融合的行为识别层次框架.该框架综合加速度和无线网络信号两种传感器信息、利用多种基于融合的识别方法,能同时解决“用户在哪里”、“用户在做什么”、“用户将要去做什么”等行为相关问题.采用智能手机作为实验平台,利用其内置的多种传感器收集用户的行为信息,更符合普适计算的发展趋势.最后通过实际采集的数据和大量的实验说明了各种方法的有效性.     

基于智能手机控制的家居服务机器人研发

针对我国智能家居服务机器人的发展现状与不足,设计了一种基于智能手机控制的家居服务机器人。主要涉及技术有:机器导航、机器视觉、信息融合、人机交互、嵌入式技术、语音识别技术等。实现了实时定位、远程控制、自主导航、手势识别、监控家庭环境、语音识别等功能。机器人配有一个单目摄像头,可以实时监控家庭环境;通过智能手机远程控制端可以在世界上任何一个可以上网的地方看到用户家里的状况;并且可以用手机控制机器人的行走路径,真正做到全方位无盲点的实时监控;基于ARM平台的嵌入式视觉处理系统实现手势识别并准确的控制机器人运动;机器人还配有烟雾感传感器、温湿度传感器,可以监测环境的空气质量。经过试验验证,该机器人符合家居服务的基本要求。     

集成社会化标签和用户背景信息的协同过滤推荐方法

针对传统的协同推荐算法存在数据稀疏和推荐精度低的问题,提出了一种集成社会化标签和用户背景信息的协同过滤(CF)推荐方法。首先,分别计算基于社会化标签和用户背景信息的用户间的相似度;然后,基于用户评分计算用户间的相似度;最后,集成上述3种相似性度量产生用户间综合相似度,并对目标用户进行项目推荐。实验结果表明,与传统的协同过滤推荐算法相比,所提方法在正常数据集和冷启动数据集下的平均绝对误差(MAE)平均降低了16%和22.6%。该方法不仅能有效地提高推荐算法的精度,而且能较好地解决数据稀疏和冷启动的问题。     

基于智能手机传感器与触摸屏的手势交互技术

由于以图像为手势信息载体的交互方式易受环境影响,设计实现了一种基于智能手机触摸屏与内置传感器的手势交互方案。首先通过手机内置MEMS传感器及触摸屏获取手势信息;然后分析手势的运动学特征,实时提取手势的信息(角速度、加速度、触摸屏数据),利用多变量决策树分类器完成对手势分类与识别;最后给出了一个原型系统。实验结果表明,该方案满足实时人机交互需求。     

基于两层社区混合计算的个性化推荐方法

社区发现在个性化推荐系统中有着良好的应用。考虑到具有联系的不同层次社区之间能够构成一种混合的计算模型(HCPR),将该混合计算模型从用户-项目关系图演化到三维立体混合计算模型中,采用不同的融合相似度分别构建项目层社区和用户层社区,并基于用户-项目之间关注-被关注关系定义混合计算层。提出了一种基于两层社区混合计算的个性化推荐方法,面对新用户、旧用户、新项目、旧项目的不同输入定义相应的计算,其能推荐较为精准、个性化的信息。在3种不同类型的数据集上进行了实验,结果表明该模型能够较好地表示用户之间、项目之间以及用户和项目之间的关系,与U-CF和I-CF的推荐方法相比,HCPR借助构建的混合计算层在保证推荐精确度的同时,推荐结果 更为 个性化。     

基于LBSN的个性化旅游包推荐系统

旅游是人们生活中的重要部分,但是制定旅游计划是一件繁杂的工作。基于位置的社交网络(LBSN)的发展,提供了大量关于位置和活动的信息。为辅助用户制订旅游计划,本文提出一个基于LBSN的个性化旅游包推荐系统。该系统利用采集自LBSN的数据,建立地点和用户偏好模型,根据用户需求,在时空约束下生成旅游路线,形成旅游包推荐给用户。本文实现的原型系统能交互地获取用户旅游意向,实时生成多个旅游包供用户选择,对游客制订旅游计划具有一定的参考价值。     

基于MEMS传感器数据拓扑分析的用户识别

随着科技的迅速发展,智能手机安全性的问题越来越受人们关注,用户识别认证在保证智能手机安全方面扮演着重要的角色.提出了一种基于微机电系统(Microelectro Mechanical Systems,MEMS)传感器步态信号持续同调的用户识别的新方法,MEMS传感器信号中的混沌不变量(伪周期性)可以由相空间中的拓扑特征来表示,通过持续同调提取相空间拓扑特征,建立不同用户的持续同调模型.利用持续同调特点,进一步简化持续同调为概率密度,并使用K-L散度度量不同用户模型间的差异,最终利用MEMS传感器信号实现无须用户主动参与的身份认证.为验证持续同调模型,采用十个不同用户,两种运动状态数据,通过仿真完成用户识别,结果表明识别的平均准确率达到95.3％.     

结合实时推荐与离线推荐的推荐系统

推荐系统是从大量信息中主动查找用户可能感兴趣的信息的工具.如何更好地贴近用户偏好,满足用户长期固有偏好的同时又能考虑到用户短期的兴趣焦点变化,是推荐系统长期研究的一个问题.此外,在对推荐系统进行设计时,为了提高推荐性能,除了专注于用户建模优化、推荐对象建模优化或推荐算法优化外,还需要将推荐系统作为一个整体进行系统性的研究,关注如系统流畅性、可伸缩能力等.针对这些问题,本文设计了一种实时推荐与离线推荐相结合的推荐系统,提出了采用待推荐池的方法保证系统的流畅性;在分析实时数据与历史数据的基础上,提供实时推荐与离线推荐,在贴合用户长期固有偏好的同时也能适应用户短时间内的兴趣焦点变化;采用控制模块对不同推荐结果数据进行控制调节,提高系统的可伸缩能力.基于该推荐系统,本文进行了对于微信文章的推荐实验,通过对待推荐池内数据进行分析来评价推荐效果,结果表明,推荐数据能够逐步贴近用户兴趣偏好.     

LiveData—基于智能手机传感器的用户数据采集系统

智能手机中各种内置传感器的出现使得用户能采集、分析和挖掘传感器数据中的有用信息。介绍了Android平台上用于采集传感器数据的应用LiveData,它可用于记录用户活动时的数据。针对应用LiveData采集的总量为28万条的传感器数据记录,提取了若干特征属性来识别用户的行为,并进一步分析了不同传感器以及不同数据采集环境对实验结果的影响。     

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.