劝导技术及其设计评估的分析

劝导技术是利用计算机、设备及应用软件来影响人类想法及行为的技术。该文对劝导技术的发展及其现状进行了综述,并着重对劝导技术的可信度及其三类劝导技术应用结果通过心理学的角度进行了分析。系统生命周期是现代设计方法理念的一个重要概念,该文介绍了系统生命周期,并介绍了基于系统生命周期中的劝导技术的设计评估行为。该文为劝导技术产品研究设计分析提供了系统的理论的指导。     

基于8邻域编码逐像素跟踪法的指纹细节特征提取算法

研究并实现基于8邻域编码逐像素跟踪法的细节特征提取算法。该算法能有效提取细化后指纹图像中的端点和分叉点,通过回朔跟踪法,能有效去除图像中的伪特征点。实验结果表明该算法较大幅度提高了特征提取的速度,并能够较准确的滤除伪特征点,缩短了图像后处理时间,可以满足实际应用的需要。     

一种新的鼠标器结构探讨

作为计算机指点式输入设备,目前已有的器械包括:机械式鼠标、光学鼠标、轨迹球、电子笔等。鼠标的应用无疑给人们使用计算机带来了极大便利,但是,由于工作原理的缺陷使得传统鼠标无法应对日益提升的系统应用,比如在三维图形界面下光标定位、控制的实现。本文提出一种新的鼠标器结构,以较小的代价克服了上述传统鼠标器缺点,还实现了三维空间的定位。     

门禁系统的RS422/RS485总线解决方案

目前各种工业场合诸如门禁考勤系统、自动收费系统、数据远传系统（如三表的数据采集传输）等中,远距离串行数据通信的可靠性显得非常重要。RS232串行总线的接口电平比TTL电平大,使得抗干扰能力增强;但RS232规定了其最大负载为2500pF的电容,通信距离也被限制,通常适合于20m以内的数据通信,且是单端通信,必然存在不可消除的共地噪声和共模干扰问题。     

Convergence analysis of convex incremental neural networks

Recently, a convex incremental algorithm (CI-ELM) has been proposed in Huang and Chen (Neurocomputing 70:3056–3062, 2007), which randomly chooses hidden neurons and then analytically determines the output weights connecting with the hidden layer and the output layer. Though hidden neurons are generated randomly, the network constructed by CI-ELM is still based on the principle of universal approximation. The random approximation theory breaks through the limitation of most conventional theories, eliminating the need for tuning hidden neurons. However, due to the random characteristic, some of the neurons contribute little to decrease the residual error, which eventually increase the complexity and computation of neural networks. Thus, CI-ELM cannot precisely give out its convergence rate. Based on Lee’s results (Lee et al., IEEE Trans Inf Theory 42(6):2118–2132, 1996), we first show the convergence rate of a maximum CI-ELM, and then systematically analyze the convergence rate of an enhanced CI-ELM. Different from CI-ELM, the hidden neurons of the two algorithms are chosen by following the maximum or optimality principle under the same structure as CI-ELM. Further, the proof process also demonstrates that our algorithms achieve smaller residual errors than CI-ELM. Since the proposed neural networks remove these “useless” neurons, they improve the efficiency of neural networks. The experimental results on benchmark regression problems will support our conclusions. The work is under the funding of Singapore MOE AcRF Tier 1 grant WBS No: R 252-000-221-112.     

Characteristics of an electron source of a surface‐conduction electron‐emitter display

Abstract— The electron source is an essential part of a surface‐conduction electron‐emitter display (SED). An electron source for an SED was obtained after certain procedures were performed. By introducing a carbon atmosphere, the electron‐emission characteristics of a SED were studied experimentally. The electron‐emission characteristic curves were drawn after comparing the experimental data of the electron source obtained in a vacuum environment with the data obtained in a carbon atmosphere, from which it had proved that a carbon atmosphere could significantly improve the electron‐emission characteristics of a SED. As a result, both the device current and the emission current had become stronger and the efficiency of surface‐conduction electron emission had been improved significantly. The possible reasons were analyzed: more carbon, which could possibly form the electron‐emission region of a SED, was produced from the carbon atmosphere during the electrical activation process.     

The application of a proportional difference type iterative learning control in active vibration control

Active vibration control is used to instead passive solutions in order to increase the performance at low frequencies, in a variety of different engineering systems. This method has improved the performance specifically. The paper will propose a proportional difference type iterative learning control algorithm to deal with the periodic sources and to investigate the active solution as the three degrees of freedom ＂mass spring damping＂ mount. Simulation shows that this method could get a better tracking performance, also the displacement could converge to zero with a fast speed.     

An algorithm of file encryption based on sum function sequences

An algorithm of file encryption based on sum function sequences is discussed in this paper. A file is encrypted by applying sum function sequences, bits with exclusive-or operation, and circular cryptographic key. Comparing with traditional algorithms and others, it is harder to decode, and the system cost is lower. New encryption algorithms can be made by transforming source codes with sum function sequences, and it can be used to encrypt different files.     

基于灰色神经网络算法的煤矿瓦斯涌出量预测模型的研究

文章提出了一种采用灰色神经网络对煤矿瓦斯涌出量进行预测的方法,并在此基础上详细介绍了灰色神经网络瓦斯预测模型的构建过程,给出了应用实例。仿真结果表明,该模型具有预测精度高、所需样本少、计算简便等优点。