水下机器人软件可靠性及故障诊断方法研究

针对于智能水下机器人在软件系统故障诊断过程中广泛存在的不确定性和复杂关联性,采用改进的软件FMEA方法,对AUV智能规划决策控制系统进行了可靠性分析和研究,在总结了AUV主要软件故障模式的基础上,提出了一种基于FMEA的三层贝叶斯网络诊断模型。通过贝叶斯网络的推理机制,分别对单一故障和复合故障进行了推理实验。实验结果表明,采用上述方法能有效地提高水下机器人系统软件可靠性以及故障诊断能力。     

基于改进贝叶斯算法的文本广告邮件过滤

北方工业大学信息工程学院北京100041摘要：本文在分析朴素贝叶斯分类算法基础上提出了一种改进的贝叶斯算法,并将邮件视为句间有序,句内关键词无序的集合,用改进的贝叶斯算法模型设计了一种文本广告邮件过滤系统,通过实验证明了其有效性。     

指纹图像质量评估的研究与应用

指纹图像质量评估是自动指纹识别系统(AFIS)中重要的一个环节。指纹采集仪采集的指纹图像质量对预处理及指纹识别的效率有很大的影响。分析了现有的指纹采集细则,对有效面积、灰度变换、干湿、位置偏移等方面对指纹图像质量的影响进行了深入的探讨,并提出一种改进的基于边缘细节点信息的指纹图像质量评估方法,对采集到的指纹图像进行质量评测,为图像的预处理提供质量较高的指纹图像。实验证明,该方法对不合格的指纹图像有较好的过滤效果,有利于提高整个系统的效率。     

结合特征和非特征信息改进Nave Bayes及其应用*

朴素贝叶斯算法是一种常见的基于内容的垃圾邮件过滤算法,但是,传统朴素贝叶斯过滤存在判断内容的不确定性和邮件表示不完整性等问题。分析邮件信头各域在正常邮件和垃圾邮件中表现出的不同属性,提取非特征信息,结合特征信息和非特征信息改进朴素贝叶斯算法。实验结果表明,改进的朴素贝叶斯分类方法与单纯使用特征信息的方法相比,垃圾邮件的召回率和准确率更高,凸显了该方法涵盖邮件信息、克服内容判断缺陷的优势。     

基于LDA模型的博客垃圾评论发现

Blog(博客)作为一种新兴的网络媒体,在很大程度上增强了互联网的开放性,Blog已经成为互联网上的主要信息源之一,这也使得Blog空间中的垃圾评论成倍增长,因此如何识别垃圾评论成为面临的重要问题。该文首先借鉴处理垃圾邮件的方法,针对Blog本身的特点,使用规则初步过滤垃圾评论,然后对剩余评论,利用Latent Dirichlet Allocation(LDA) 这种能够提取文本隐含主题的产生式模型,对博客中的博文进行主题提取,并结合主题信息进行判断,从而识别Blog空间的垃圾评论。通过实验验证,该方法可以发现大多数垃圾评论,实验取得了较好的结果,使Blog信息更加准确、有效的为用户使用。     

基于模式的贝叶斯垃圾邮件过滤的研究与实现

运用TEIRESIAS算法从邮件中提取模式作为表示邮件的属性,在此基础上实现了一个贝叶斯垃圾邮件过滤实验系统。通过实验,比较分析了该过滤器的性能,并讨论了属性集大小、属性最少出现次数对基于模式的贝叶斯垃圾邮件过滤系统的影响。     

博客垃圾开始疯狂

继垃圾邮件之后,互联网将遇到新的“垃圾”,而它所带来的影响甚至会超过垃圾邮件小周用了整整一个月的时间,终于为一个行业网站写好了博客系统。把这个系统上传到服务器后的十天里,他和同事们注册了5个博客空间,并且各自放置了一些内容在博客里,之后他们的博客里出现了留言,但留言内容却是与博客主题毫无关联的广告。博客垃圾和垃圾博客同样受到侵扰的还有小周所服务的网站论坛,不断地有新的机器人前来注册,然后在论坛里发布广告信息。对于这些内容,小周毫不客气,发现便删除。但是对方是在用机器人发帖,而自己是手动删除,如此不对称的实力之…     

一种基于多贝叶斯算法的垃圾邮件过滤方法

贝叶斯算法在垃圾邮件过滤中应用广泛。针对算法提高精确率和召回率的矛盾,提出了一种新的基于多贝叶斯算法组合的垃圾邮件过滤方法,并给出了不同方法下中、英文垃圾邮件过滤实验数据对比。实验表明该方法显著提高了垃圾邮件的过滤性能。     

基于组合特征的动态垃圾博客过滤算法

近几年,垃圾博客过滤成为国际上新的热点研究领域。现有的过滤算法大多基于词频特征分类,特征冗余并缺乏关联性。为了解决此问题,提出一种基于组合特征的动态垃圾博客过滤算法(CFDSD),该算法采用作者属性和自相似特征来解决特征冗余和关联性低的问题,并应用贝叶斯分类算法优化词频特征分类。实验表明,该算法能适应博客随时间变化而动态更新的特点,同时提高了过滤效率。     

融合朴素贝叶斯和协同过滤的外卖推荐并行算法研究

为了提高个性化外卖推荐系统的准确率,结合传统的协同过滤算法中存在的数据稀疏性问题,提出一种融合朴素贝叶斯和协同过滤的外卖推荐并行算法。采用并行的朴素贝叶斯分类算法构建外卖评论文本情感分类器,量化评论文本情感值;结合评分数值构建外卖综合评分模型;将综合评分结果整合到推荐系统的训练集,利用优化的并行ALS算法进行推荐。实验结果表明,该推荐算法不仅在推荐准确率上有一定的提高,还具有良好的加速比。该算法应用于个性化外卖推荐是可行和有效的。     

无线传感器网络环境下基于粒子滤波的移动机器人SLAM算法

定位问题是移动机器人研究领域中最基本的问题,在Bayes的框架下研究了机器人与无线传感器网络(WSN)组成系统中的同时建图与定位问题(SLAM).针对该系统中只存在距离测量信息可用的情况提出了一种基于粒子滤波的SLAM算法.该方法将机器人状态和节点位置估计设置为一组全局估计粒子,通过对粒子及其权重的更新来计算整个系统的状态.算法将WSN节点的位置估计在机器人的路径上分解为相互独立的估计,从而将全局粒子的计算转化为使用一个机器人状态滤波器和对应于每个机器人粒子的节点位置滤波器进行计算.针对观测信息低维的特点,设计了处理低维观测信息的方法,使得观测信息可以在滤波阶段得到合理利用.并且详细介绍了提出的SLAM算法原理和计算过程,并通过仿真实验证明了算法的有效性和实用性.     

A blog article recommendation generating mechanism using an SBACPSO algorithm

In recent years blog-assisted learning has been used widely in higher education for improving writing and collaboratively sharing work online. However, methods for gathering useful information to be used as auxiliary-learning materials from the multitude of blog articles in the blogosphere has been seldom investigated. This paper proposes an individualized blog article recommendation mechanism to provide quality blog articles that accord with users’ learning topics. First, an IR-based technique was applied to extract and score index terms. The top three index terms were then entered into Google’s blog search engine to find the raw recommended blog articles. To avoid the situation where frequent topic-changing leads to a deficiency of article data on a specific learning topic, a forgetting rate was employed to simulate the phenomenon of changing learning topics. Subsequently, an extended Serial Blog Article Composition Particle Swarm Optimization (SBACPSO) algorithm was employed to provide optimal recommended materials to users. We evaluated the system’s performance to find the appropriate article population size. Finally, user satisfaction regarding both the system and recommended content were gauged to find the system’s limitations and possible improvements. This study is of importance in that it provides users with dynamic blog article recommendation, improved online information discovery skills and opportunities to socialize with other bloggers.     

基于改进Naïve Bayes的垃圾邮件过滤模型研究

分析了目前在垃圾邮件过滤中广泛应用的Naïve Bayes过滤模型（NBF）,指出了期望交叉熵（ECE）特征词选取方法的不足。提出了改进的Naïve Bayes垃圾邮件过滤模型（A-NBF）,用改进的期望交叉熵（AECE）选取垃圾邮件特征词,并在邮件分类过程中对特征词进行加权,从而提高对垃圾邮件过滤的精度。实验结果可以看出A-NBF比NBF在过滤精度方面有明显的提高。     

Bootstrapping a robot’s kinematic model

We present a system that is able to autonomously build a 3D model of a robot’s hand, along with a kinematic model of the robot’s arm, beginning with very little information. The system starts by using exploratory motions to locate and centre the robot’s hand in the middle of its field of view, and then progressively builds the 3D and kinematic models. The system is flexible, and easy to integrate with different robots, because the model building process does not require any fiducial markers to be attached to the robot’s hand. To validate the models built by the system we perform a number of experiments. The results of the experiments demonstrate that the hand model built by the system can be tracked with a precision in the order of 1 mm, and that the kinematic model is accurate enough to reliably position the hand of the robot in camera space.     

Bloggers’ Responses to the Snowden Affair: Combining Automated and Manual Methods in the Analysis of News Blogging

The Snowden affair gave rise to a huge public debate about not only the legitimacy of the secret surveillance programs he revealed but also about Snowden himself and about the accuracy of the information he leaked. In this paper we present an analysis of how the affair was discussed in the English language blogosphere, based on a corpus of 15,000 blog posts written about Snowden and published from June 2013 to June 2014, as a sub-corpus of a larger corpus of 100,000 blog posts on the topic of surveillance, written during the period 2006–2014. Automated tools are used to identify the topics that characterize the blogging about surveillance and the posts about the Snowden affair. Through an in-depth analysis of the blog posts that commented on Snowden’s revelations of the PRISM program for surveillance of social media users, we chart how bloggers responded to Snowden and his role in this disclosure, whether they found the information credible, and the extent to which they expressed criticism of the surveillance practices. The analysis is used as a basis for discussing the role of blogs in the civic engagement during the first phase of the Snowden affair.     

一种基于AIS和Bayes网络的垃圾邮件过滤算法

将人工免疫系统和贝叶斯网络相结合应用于垃圾邮件的过滤,设计了一个基于AIS和Bayes网络的垃圾邮件过滤算法,分析并解决了该算法实现过程中的关键问题,给出了亲和力的计算方法和抗原/抗体的结构定义。在PU1bare 语料的基础上与Carreras提出的AdaBoost方法进行对比实验,最后给出了实验结果。     

Updating workpiece geometry using robotic sensor information gathered during contact tasks

During robotic contact tasks, geometric information of the workpiece is used to specify the position of the robot’s hand on the workpiece and the direction of force control. This geometry is idealized in a typical CAD file, but due to manufacturing precision or wear, the actual workpiece geometry is inevitably deviated from the desired geometry. Furthermore, when the workpiece is mounted, position and orientation inaccuracies emerge. In this paper, we investigate two questions: (1) Can the workpiece geometry in the CAD file be used to control a robot in contact with an inaccurately placed workpiece?; and (2) Once the task is performed, how can the robot’s sensor information be used to update the geometry of the workpiece? A methodology is developed to solve robotic control problems with workpiece position and geometry inaccuracies. Once performed, the CAD file image is displaced to fit the sensed trajectory of the robot’s hand. Finally, the workpiece image geometry is modified using a least squares approximation to fit the sensed data more accurately. In the end, the robot performs the contact task while gathering information that is used to update the original CAD file geometry. The methodologies are demonstrated through a simulation experiment that requires a robot to shave a geometrically altered face that is inaccurately positioned.     

A human–robot interface for mobile manipulator

This paper presents a remote manipulation method for mobile manipulator through operator’s gesture. In particular, a track mobile robot is equipped with a 4-DOF robot arm to grasp objects. Operator uses one hand to control both the motion of mobile robot and the posture of robot arm via scheme of gesture polysemy method which is put forward in this paper. A sensor called leap motion (LM), which can obtain the position and posture data of hand, is employed in this system. Two filters were employed to estimate the position and posture of human hand so as to reduce the inherent noise of the sensor. Kalman filter was used to estimate the position, and particle filter was used to estimate the orientation. The advantage of the proposed method is that it is feasible to control a mobile manipulator through just one hand using a LM sensor. The effectiveness of the proposed human–robot interface was verified in laboratory with a series of experiments. And the results indicate that the proposed human–robot interface is able to track the movements of operator’s hand with high accuracy. It is found that the system can be employed by a non-professional operator for robot teleoperation.     

基于指纹识别技术的智能门禁系统研究

指纹识别门禁系统是基于生物识别技术的一项高科技安全设施,近年来在国内外得到广泛的应用,成为建筑智能化的一个重要标志。由于指纹具有无需携带、人人各异、终生不变等特点,因此利用指纹从身份识别依据,与钥匙、密码等传统手段相比,可大大提高安全性与可信度。以三星公司的S3C2440为控制核心,并采用富士通公司的MBF200指纹传感器芯片,对基于指纹识别技术的嵌入式门禁系统作分析研究。     

基于方向信息的指纹图像预处理

预处理是自动指纹识别技术的基础,它的好坏直接影响着指纹自动识别系统的效果。本文从方向图、滤波、二值化和细化等几个方面详细介绍了自动指纹识别系统中的预处理过程,并具体实现了指纹图像的预处理。该方法取得了良好的效果,保留了指纹纹线的关键信息,为下一步的特征提取工作打下了良好的基础。