An efficient and secure approach for a cloud collaborative editing

The demand for cloud-based collaborative editing service is rising along with the tremendously increased popularity in cloud computing. In the cloud-based collaborative editing environment, the data are stored in the cloud and able to be accessed from everywhere through every compatible device with the Internet. The information is shared with every accredited user in a group. In other words, multiple authorized users of the group are able to work on the same document and edit the document collaboratively and synchronously online. Meanwhile, during the whole collaborative editing process, the encryption technique is eventually applied to protect and secure the data. The encryption for the collaborative editing, however, could require much time to operate. To elevate the efficiency of the encryption, this study first analyzes the text editing in the collaborative service and presents a framework of the Red–Black tree, named as rbTree-Doc. The rbTree-Doc can reduce the amount of data to be encrypted. Although the trade-off for creating the Red–Black tree introduces extra cost, the experimental results of using rbTree-Doc in text editing operations, such as insertion and removal, show improved efficiency compared with other whole-document encryption strategy. Using rbTree-Doc, the efficiency is improved by 31.04% compared to that 3DES encryption is applied and by 23.94% compared to that AES encryption is applied.     

Parametric modeling of microwave passive components using combined neural networks and transfer functions in the time and frequency

A novel parametric modeling technique is proposed to develop combined neural network and transfer function models for both time and frequency (TF) domain applications of passive components, where the neural network is trained to map geometrical variables to the coefficients of transfer functions. Built on our previous work, a new order‐changing module is developed to enforce stability of transfer functions and simultaneously guarantee continuity of coefficients. A constrained optimization strategy is introduced to enforce passivity of transfer functions through a neural network training process. A general equivalent circuit for two‐port passive components is generated directly from coefficients of arbitrary‐order transfer functions. Once trained, the parametric model can provide accurate and fast prediction of the electromagnetic behavior of passive components with geometrical parameters as variables. Compared to our previous work, the proposed method enables models to work well in the time domain providing good accuracy in challenging modeling applications. Two parametric modeling examples of spiral inductors and interdigital capacitors, and their application in both time and frequency domain simulations of a power amplifier are examined to demonstrate the validity of the proposed technique. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2013.     

组合型材参数化快速设计的方法研究

为了满足大型工程系统对组合型材的快速参数化设计要求,本文设计开发了一套针对组合型材的参数化绘图系统。系统在天喻参数化零件库的基础上,以其参数化和数据库技术做支撑,通过其参数化驱动的技术来绘制单个型材的截面图形,并通过一系列的变换矩阵对截面图形进行变换,以达到相互组合的目的;并根据组合后的图形数据,在特定的消隐算法的基础上,完成组合型材的水平与竖直方向的投影视图。文中分析了此系统的框架结构,并对所涉及到的关键技术,如型材的组合运算、方位视图的生成以及对型材视图的投影所涉及到的消隐算法进行了介绍,最后给出了此系统在某锅炉企业中的应用实例。     

机场视景模型参数化建模方法研究

随着计算机虚拟现实和视景仿真技术的发展与完善,用于提高视景的逼真度和视觉效果的技术在飞行模拟机视景仿真中已得到广泛的应用。但是,基于Multigen Creator等3D建模软件构建机场模型的缺点日益凸显:人工收集机场数据、手工绘制机场拓扑图的建模方法耗时、费力、效率低、缺乏灵活性和可复用性。针对这些问题,结合机场路网结构的特点,将参数化的思想引入到机场路网三维建模过程中,提出了一种基于交通拓扑约束的机场路网参数化三维建模方法,设计并实现了基于该方法的用于视景的机场路网模型参数化建模系统。该系统已成功应用到机场模型建模工作中,建模速度较之传统方法有了显著的提高,而且制作出来的模型可以复用,系统在稳定性、可扩展性和可移植性方面表现出色,并具有很强的真实感和沉浸感。     

基于Pro／E的机械产品设计

基于Pro／E特征建模、参数化、全数据相关的特点,不仅能实现零部件的参数化实体建模,也可以方便地建立从三维模型到二维工程图的转换,有效地缩短设计时间,提高设计效率与质量。通过对Pro／E特点的讨论,结合台式钻床产品设计实例,论述了Pro／E在机械产品设计中的应用。     

具有区间峰值的曲面伸缩因子及其实验

为了改进参数曲面自由变形方法,构造了一种新的伸缩因子函数,它不仅具有以往文献所引入的伸缩因子的特性,还可以在区域上达到峰值,从而克服现有的伸缩因子仅在一点达到峰值的不足。使用新的伸缩因子去作用待变形的曲面方程,从而使曲面发生形变,通过交互改变控制参数来控制曲面的形状,使其能够更好地表示一些实体的外型。实验表明,该方法数学背景简单,易于控制,重复使用可获得丰富的变形效果。适用于几何造型、计算机动画、CAD/CAM等领域。     

一类非线性参数化系统自适应重复学习控制

针对一类高阶非线性参数化系统, 利用分段积分机制, 提出了一种新的自适应重复学习控制方法. 该方法结合反馈线性化, 可以处理参数在一个未知紧集内周期性快时变的非线性系统, 通过引进微分-差分混合型参数自适应律, 设计了一种自适应控制策略, 使广义跟踪误差在误差平方范数意义下渐近收敛于零, 通过构造Lyapunov泛函, 给出闭环系统收敛的一个充分条件. 实例仿真结果说明了该方法的可行性.     

不规则网格上的曲面设计方法

提出一种在不规则网格上构造曲面的方法.其基本思想是,通过均匀双三次B样条基函数的分解和子基函数的分类,将B样条曲面方法推广到任意四边形网格.给定一个任意四边形控制网格,首先对每个控制点构造一个基函数;所有控制点加权组合形成整体曲面.构造的曲面是分片双三次有理参数多项式曲面.此方法可以看成是均匀B样条曲面构造方法的扩展,如果控制网格是规则四边形网格,那么构造得到的曲面与均匀双三次B样条曲面是一致的.最后,实例证明此方法能够有效地构造曲面.     

声学参量换能器阵及其测试系统设计

根据声学参量阵原理,设计了一个3×3的九元矩形换能器阵及其测试系统,并在空气进行验证性实验;系统包括正弦信号产生电路、信号控制电路、功率放大电路以及回波信号接收电路等,辅以LabVIEW平台,实现正弦信号和脉冲控制信号的产生,发射信号时间长度控制以及功率放大,并最终驱动换能器阵;实验表明,当有85kHz和90kHz的正弦信号产生时,系统各部分均能正常工作,能够听到天花板处有声响,且回波信号中含有5kHz的频率成分,即证明换能器阵及其系统的设计均是可行的.     

基于间歇控制的不确定主从Lur’e系统的指数同步

研究了不确定主从Lur’e系统的问歇控制同步问题．运用Lyapunov稳定性理论和S-过程,首先推导出保证标称主从Lur’e系统指数同步的一个充分条件．在此基础上进一步得到了具有范数有界不确定性主从Lur’e系统鲁棒指数同步的结果．这些同步判据以矩阵不等式的形式给出．另外我们还提出了一种最小化性能指标的优化策略．最后,通过两个数值例子验证了结果的有效性．