A modular designed bolt tightening shaft based on adaptive fuzzy backstepping control

This paper presents a modular designed autonomous bolt tightening shaft system with an adaptive fuzzy backstepping control approach developed for it. The bolt tightening shaft is designed for the autonomous bolt tightening operation, which has huge potential for industry application. Due to the inherent nonlinear and uncertain properties, the bolt tightening shaft and the bolt tightening process are mathematically modeled as an uncertain strict feedback system. With the adaptive backstepping and approximation property of fuzzy logic system, the controller is recursively designed. Based on the Lyapunov stability theorem, all signals in the closed-loop system are proved to be uniformly ultimately bounded and the torque tracking error exponentially converges to a small residue. And the effectiveness and performance of the proposed autonomous system are verified by the simulation and experiment results on the bolt tightening shaft system.     

新时期中职体育礼仪教育的实施策略

体育是文化的重要组成部分,不管是在世界,还是在国内,都已经成为了人们日常生活的一部分,也影响着人们的生活。中职的体育教学是培养人才的重要手段,蕴含着丰富的教育功能。在中职体育教学中,通过体育礼仪的教育可以提高中职学生的礼仪修养,进而促进学生整体思想水平和境界的提升。     

中央一号文件出台背景及政策要点

一、一号文件出台的背景1.兴水利除水害是治国安邦的头等大事在前不久一次会议上,一位中央领导同志指出,水的问题对中国来讲,历来都是一个大事。党的十五届三中全会决定中也有类似的论述。这次一号文件更是鲜明地提出,水旱     

Self-sensing active magnetic bearing using real-time duty cycle

In a self-sensing active magnetic bearing (AMB) system driven by pulse width modulation (PWM) switching power amplifiers, the rotor position information can be extracted from coil current and voltage signals by a specific signal demodulation process. In this study, to reduce the complexity of hardware, the coil voltage signal was not filtered but measured in the form of a duty cycle by the eCAP port of DSP (TMS320F28335). A mathematical model was established to provide the relationship between rotor position, current ripple, and duty cycle. Theoretical analysis of the amplitude-frequency characteristic of the coil current at the switching frequency was presented using Fourier series, Jacobi-Anger identity, and Bessel function. Experimental results showed that the time-varying duty cycle causes infinite side frequencies around the switching frequency. The side frequency interval depends on the varying frequency of the duty cycle. Rotor position can be calculated by measuring the duty cycle and demodulating the coil current ripple. With this self-sensing strategy, the rotor system supported by AMBs can steadily rotate at a speed of 3000 r/min.     

Testing the equality of proportions for correlated otolaryngologic data

In otolaryngologic (or ophthalmologic) studies, each subject usually contributes information for each of two ears (or eyes), and the values from the two ears (or eyes) are generally highly correlated. Statistical procedures that fail to take into account the correlation between responses from two ears could lead to incorrect results. On the other hand, asymptotic procedures that overlook small sample designs, sparse data structures, or the discrete nature of data could yield unacceptably high type I error rates even when the intraclass correlation is taken into consideration. In this article, we investigate eight procedures for testing the equality of proportions in such correlated data. These test procedures will be implemented via the asymptotic and approximate unconditional methods. Our empirical results show that tests based on the approximate unconditional method usually produce empirical type I error rates closer to the pre-chosen nominal level than their asymptotic tests. Amongst these, the approximate unconditional score test performs satisfactorily in general situations and is hence recommended. A data set from an otolaryngologic study is used to illustrate our proposed methods.     

Figure-ground separation by cue integration

This letter presents an improved cue integration approach to reliably separate coherent moving objects from their background scene in video sequences. The proposed method uses a probabilistic framework to unify bottom-up and top-down cues in a parallel, "democratic" fashion. The algorithm makes use of a modified Bayes rule where each pixel's posterior probabilities of figure or ground layer assignment are derived from likelihood models of three bottom-up cues and a prior model provided by a top-down cue. Each cue is treated as independent evidence for figure-ground separation. They compete with and complement each other dynamically by adjusting relative weights from frame to frame according to cue quality measured against the overall integration. At the same time, the likelihood or prior models of individual cues adapt toward the integrated result. These mechanisms enable the system to organize under the influence of visual scene structure without manual intervention. A novel contribution here is the incorporation of a top-down cue. It improves the system's robustness and accuracy and helps handle difficult and ambiguous situations, such as abrupt lighting changes or occlusion among multiple objects. Results on various video sequences are demonstrated and discussed. (Video demos are available at http://organic.usc.edu:8376/ approximately tangx/neco/index.html .).     

基于新型协调量化容差关系的不完备数据填补方法

提出一种基于新型协调量化容差关系的不完备数据补齐算法。首先求出属性值不完备对象的容差类,结合属性的重要度,将容差类里面的对象容差关系量化,再根据决策规则独立原则,在尽可能保持系统协调性的前提下对缺失属性值进行补齐。大量实验证明了本算法的有效性。     

基于LabVIEW 8.0测定纯液体蒸发焓的虚拟仪器

将常规的数字温度仪与压力计通过串行口和计算机连接,构建基于LabVIEW 8.0测定纯液体蒸发焓的虚拟仪器,实现实验数据的动态采集、实时显示、自动绘制p～T曲线并显示曲线方程、自动数据处理和写成结果报告等。应用结果表明:基于LabVIEW构建的测定纯液体蒸发焓的虚拟仪器,免除人工操作的繁琐和人为误差,测定乙醇和苯蒸发焓的相对误差分别为0.86%、-2.97%,提高了测量结果的准确度,且具有界面友好,操作简便和功能易扩展等诸多优点。     

A Multidimensional Paper Recommender: Experiments and Evaluations

Paper recommender systems in the e-learning domain must consider pedagogical factors, such as a paper's overall popularity and learner background knowledge — factors that are less important in commercial book or movie recommender systems. This article reports evaluations of a 6D paper recommender. Experimental results from a human subject study of learner preferences suggest that pedagogical factors help to overcome a serious cold-start problem (not having enough papers or learners to start the recommender system) and help the system more appropriately support users as they learn.