Kinematics, pattern recognition, and motion control of mask-panel alignment system

Kinematics, pattern recognition, and motion control methods are investigated as an integrated approach for a mask-panel visual alignment system, which consists of the vision system to extract the mask-panel misalignment and the stage control system to compensate for it. First, a 4PPR alignment mechanism is considered and the inverse kinematic solution is found out to define the relationship between the mask-panel misalignment and the displacements of active joints. Then, a fast alignment mark recognition algorithm is proposed in terms of the geometric template matching (GTM), which is specific to simply shaped patterns but computationally much efficient compared with general correlation-based matchings. Finally, the kinematic solution and the developed vision algorithm are incorporated to implement a two-stage position-based visual servo, where both original fine images and reduced coarse ones are utilized together and the GTM plays a crucial role in achieving a near real-time visual feedback. Experimental results are shown to demonstrate the effectiveness of the GTM-based two-stage alignment control.     

The Laplace transform in discrete fractional calculus

We develop properties of the Laplace Transform in a discrete, fractional calculus setting, giving a precise treatment to convergence along the way. The end goal is to apply the Laplace Transform Method to solve a fractional initial value problem.     

Face recognition based on extreme learning machine

Extreme learning machine (ELM) is an efficient learning algorithm for generalized single hidden layer feedforward networks (SLFNs), which performs well in both regression and classification applications. It has recently been shown that from the optimization point of view ELM and support vector machine (SVM) are equivalent but ELM has less stringent optimization constraints. Due to the mild optimization constraints ELM can be easy of implementation and usually obtains better generalization performance. In this paper we study the performance of the one-against-all (OAA) and one-against-one (OAO) ELM for classification in multi-label face recognition applications. The performance is verified through four benchmarking face image data sets.     

基于主动漂移矫正的运动目标跟踪算法

针对传统的图像仿射配准(Affine image alignment, AIA)算法无法有效兼顾算法效率和鲁棒性的问题, 提出了一种快速鲁棒的新仿射配准算法---主动漂移矫正(Active drift correction, ADC)算法用于跟踪视频运动目标. 该算法的基本思想是: 通过引入一个漂移矫正项, 来改进传统算法的目标能量函数, 使算法具备抗漂移的能力, 从而提高算法的鲁棒性. 改进后的算法不需要传统算法中为增强鲁棒性而采用的许多复杂措施(如: 被动漂移矫正). 实验结果表明: 本文提出的算法简单、有效, 在不必牺牲算法效率和复杂度的条件下, 可以获得比传统算法更好的鲁棒性.     

Stable local dimensionality reduction approaches

Dimensionality reduction is a big challenge in many areas. A large number of local approaches, stemming from statistics or geometry, have been developed. However, in practice these local approaches are often in lack of robustness, since in contrast to maximum variance unfolding (MVU), which explicitly unfolds the manifold, they merely characterize local geometry structure. Moreover, the eigenproblems that they encounter, are hard to solve. We propose a unified framework that explicitly unfolds the manifold and reformulate local approaches as the semi-definite programs instead of the above-mentioned eigenproblems. Three well-known algorithms, locally linear embedding (LLE), laplacian eigenmaps (LE) and local tangent space alignment (LTSA) are reinterpreted and improved within this framework. Several experiments are presented to demonstrate the potential of our framework and the improvements of these local algorithms.     

混沌敏感性在图像加密中的2种应用

混沌系统的结构参数敏感性、初值敏感性和以同一分布遍历各态的特性较好地对应密码系统的一些基本特性。分析结构参数和初始值变化对混沌序列敏感性影响,得到混沌序列敏感性效应是一个积累过程。将混沌序列按照敏感性划分为混沌敏感性前后期序列并给出界定原则。探究混沌序列敏感性在图像加密时的2种不同应用。     

Higher order dispersive and dissipative hybrid method for the numerical solution of oscillatory problems

In this paper, an improved explicit two-step hybrid method with fifth algebraic order is derived. The new method possesses dispersion of order 10 and dissipation of order seven, which is first of its kind in the literature. Numerical experiment reveals the superiority of the new method for solving oscillatory or periodic problems over several methods of the same algebraic order.     

Board-Level Information Technology Governance Effects on Organizational Performance: The Roles of Strategic Alignment and Authoritarian Governance Style

ABSTRACT

We report on two empirical studies that explore key factors that help translate information technology governance by the board of directors into organizational performance. The first study shows that strategic alignment partially mediates the effect of board-level information technology governance on performance. The second study demonstrates that authoritarian governance style negatively moderates the effect of board-level information technology governance on performance. Together, these studies open up the black box between board-level information technology governance and organizational performance.     

垂线偏差对空中对准航向误差的影响研究

针对性分析了垂线偏差变化对空中对准航向精度的影响.首先给出了常用空中对准降阶滤波模型,分析了垂线偏差变化影响空中对准航向误差的机理.然后通过实测离线数据测试验证了垂线偏差对空中对准航向误差的影响.最后通过误差协方差分析方法仿真了降阶滤波模型在真实世界中的滤波性能.离线测试及仿真结果表明:在给定条件下垂线偏差变化率对航向误差的影响相对其他未建模惯性测量组件误差是主要的,对航向对准误差影响较大,可达0.15°.在中高精度应用中为保证在不同空域内空中对准航向精度考虑采用高精度重力场模型对垂线偏差进行补偿是必要的.     

基于初始磁导率的铁氧体裂纹检测

铁氧体是电子电路中广泛使用的抗干扰元件,生产中应力引发的内部缺陷裂纹严重影响其电气性能。其传统检测方法准确率低、速度慢,难以满足产品的快速检测需求。将基于初始磁导率的缺陷检测方法运用于铁氧体工件的检测,对检测传感器进行优化,使之能够在微小激励下获得准确的输出响应。对改进前后的传感器进行了对比实验,分别就其结构、尺寸、磁导率等参数进行了针对性分析,证明了该检测方法和参数优化的有效性。