Making the ‘MOST’ out of RFID technology: a research agenda for the study of the adoption,usage and impact of RFID

Radio frequency identification (RFID) technology dramatically increases the ability of the organization to acquire a vast array of data about the location and properties of any entity that can be physically tagged and wirelessly scanned within certain technical limitations. RFID can be applied to a variety of tasks, structures, work systems and contexts along the value chain, including business-to-business logistics, internal operations, business-to-consumer marketing, and after-sales service applications. As industry adoption of RFID increases there is an emerging interest by academic researchers to engage in scholarly investigation to understand how RFID relates to mobility, organizational and systems technologies (MOST). In this paper, we explore RFID and propose a research agenda to address a series of broad research questions related to how RFID technology: (1) is developed, adopted, and implemented by organizations; (2) is used, supported, and evolved within organizations and alliances; and (3) impacts individuals, business processes, organizations, and markets. As with many technological innovations, as the technical problems associated with implementing and using RFID are addressed and resolved, the managerial and organizational issues will emerge as critical areas for IS research.

Common model analysis and improvement of particle swarm optimizer

Particle swarm optimizer (PSO), a new evolutionary computation algorithm, exhibits good performance for optimization problems, although PSO can not guarantee convergence of a global minimum, even a local minimum. However, there are some adjustable parameters and restrictive conditions which can affect performance of the algorithm. In this paper, the algorithm are analyzed as a time-varying dynamic system, and the sufficient conditions for asymptotic stability of acceleration factors, increment of acceleration factors and inertia weight are deduced. The value of the inertia weight is enhanced to (?1, 1). Based on the deduced principle of acceleration factors, a new adaptive PSO algorithmharmonious PSO (HPSO) is proposed. Furthermore it is proved that HPSO is a global search algorithm. In the experiments, HPSO are used to the model identification of a linear motor driving servo system. An Akaike information criteria based fitness function is designed and the algorithms can not only estimate the parameters, but also determine the order of the model simultaneously. The results demonstrate the effectiveness of HPSO.     

基于笔迹的身份鉴别

提出了一种鉴别笔迹的新方法.现有的笔迹识别方法大多需要进行分割或关联部分的分析,都是与内容相关的方法.在新方法里,把手写笔迹作为一种纹理来看待,将笔迹鉴别的问题转化为纹理识别来处理,这是一种与内容无关的方法.使用多通道二维Gabor滤波器来提取这些纹理的特征,并使用加权欧氏距离分类器来完成匹配工作.在实验中,使用了17个人的不同笔迹,取得了很好的结果.     

pH中和系统辨识中的人工神经网络应用

pH中和作为化工、生物、发电和污水处理中的一个重要过程,具有极强的非线性和不确定性,很难对其进行精确建模,因此,pH值的控制一直是工业过程控制中的一个难题。本文借鉴了计算机领域中神经网络(NN)在非线性系统建模中的显著作用,结合对pH中和过程机理的分析,建立了基于BP神经网络的辨识模型,对典型的pH中和过程系统辨识进行了仿真研究,并进行了相关试验。试验结果表明:神经网络在pH中和过程辨识中具有较高的辨识精度,有着广阔的应用前景。     

论指纹识别技术及在银行身份验证中的应用

介绍真皮指纹识别的原理,并以实例介绍了基于IC卡的银行脱机式指纹系统的结构、硬件组成、软件流程等。该系统可以广泛应用于银行的身份验证。     

Web日志挖掘的数据预处理研究

分析了Web日志挖掘的数据预处理过程,提出了基于日志引用页的用户识别算法,并对其性能进行分析,最后给出了应用实例。     

基于期望最大化算法的自适应噪声交互多模型滤波

A novel method under the interactive multiple model (IMM) filtering framework is presented in this paper, in which the expectation-maximization (EM) algorithm is used to identify the process noise covariance Q online. For the existing IMM filtering theory, the matrix Q is determined by means of design experience, but Q is actually changed with the state of the maneuvering target. Meanwhile it is severely influenced by the environment around the target, i.e., it is a variable of time. Therefore, the experiential covariance Q can not represent the influence of state noise in the maneuvering process exactly. Firstly, it is assumed that the evolved state and the initial conditions of the system can be modeled by using Gaussian distribution, although the dynamic system is of a nonlinear measurement equation, and furthermore the EM algorithm based on IMM filtering with the Q identification online is proposed. Secondly, the truncated error analysis is performed. Finally, the Monte Carlo simulation results are given to show that the proposed algorithm outperforms the existing algorithms and the tracking precision for the maneuvering targets is improved efficiently.     

一种隐藏和提取版权控制数据的技术方案

研究了数字内容的版权控制问题，提出了一种隐藏和提取版权控制数据的技术方案．此方案基于整形小波变换，通过对部分小波系数的特殊量化来隐藏数字许可和版权标识，其提取不需要知道原始数字内容．隐藏版权标识用于证明内容的版权归属，隐藏数字许可用于限制用户的播放行为．文章在讨论版权控制框架和模型的基础上。对版权控制数据的隐藏和提取过程进行了算法描述，并且说明了在低频部分隐藏数字许可增加鲁棒性，在所有频带隐藏版权标识监测完整性。     

森林树种高光谱波段的选择

高光谱是遥感技术发展的一个重要方向，也是地物识别的重要手段。本研究利用地物光谱仪对杉木、雪松、小叶樟树和桂花树4个树种进行高光谱数据测量，探索不同树种在不同波段上的识别能力。研究采用了逐步判别分析法和分层聚类法对实验数据进行数据分析。结果表明：逐步判别分析法选择的波段主要位于红、绿、蓝、和近红外区；分层聚类法选择的波段除了红、绿、蓝、和近红外波段外，还增加了蓝-绿边缘、绿-红边缘和红边区的波段。所选择的波段比原始波段在树种识别时具有更高的精度，最高识别精度达96．77％；边缘区波段对树种的识别有重要作用；用对数-微分变换处理较其他方法处理对树种识别有更好的效果。     

一种加权模糊推理网络模型及其应用

提出了一种加权模糊推理网络的结构模型和学习算法,该网络的基本信息处理单元为模糊推理神经元,融合了模糊逻辑能够较完整地表达领域规则和先验知识,以及神经网络自适应环境的优点。根据模糊推理规则的量化表示形式和微分方程数值解的动力学思想推导出了该网络模型的学习算法。该算法具有稳定、收敛速度快,且能较好地避免网络学习陷入局部极值点。以油田生产复杂水淹层识别问题为例,验证了模型和算法的有效性。