Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

Deadline division-based heuristic for cost optimization in workflow scheduling

Cost optimization for workflow applications described by Directed Acyclic Graph (DAG) with deadline constraints is a fundamental and intractable problem on Grids. In this paper, an effective and efficient heuristic called DET (Deadline Early Tree) is proposed. An early feasible schedule for a workflow application is defined as an Early Tree. According to the Early Tree, all tasks are grouped and the Critical Path is given. For critical activities, the optimal cost solution under the deadline constraint can be obtained by a dynamic programming strategy, and the whole deadline is segmented into time windows according to the slack time float. For non-critical activities, an iterative procedure is proposed to maximize time windows while maintaining the precedence constraints among activities. In terms of the time window allocations, a local optimization method is developed to minimize execution costs. The two local cost optimization methods can lead to a global near-optimal solution. Experimental results show that DET outperforms two other recent leveling algorithms. Moreover, the deadline division strategy adopted by DET can be applied to all feasible deadlines.     

A sensitive and selective sensor for dopamine determination based on a molecularly imprinted electropolymer of o-aminophenol

A simple and reliable method was proposed for preparing a selective dopamine (DA) sensor based on a molecularly imprinted electropolymer of o-aminophenol. The sensor is selective for the determination of DA in the presence of high concentrations of ascorbic acid (AA), with a maximum molar ratio of 1/1000. The molecular imprinted (MIP) sensor was tested by cyclic voltammetry (CV) as well as differential pulse voltammetry (DPV) to verify the changes in oxidative currents of ferricyanide. In optimized conditions, DA at concentrations of 2 × 10⁻⁸ to 0.25 × 10⁻⁶ mol/L could be determined with a detection limit of 1.98 × 10⁻⁹ mol/L (S/N = 3). The MIP sensor showed high selectivity, sensitivity, and reproducibility. Determination of DA in simulated samples of dopamine hydrochloride showed good recovery.     

Micromachining of passive planar micromixer on poly (methyl methacrylate) substrate with excimer laser ablation

Excimer laser ablation technique was introduced into this work to fabricate a passive planar micromixer on the PMMA substrate. T-junction shaped and width-changed S-shaped microchannels were both designed in this micromixer to enhance mixing effect. The mixing experiment of distilled water and Rhodamine B with injection flow rate of 500 and 1,500 μm/s validates the mixing effectivity of this micromixer, and indicates the feasibility of excimer laser ablation in the microfabrication of μ-TAS device.     

A cross-junction channel valveless-micropump with PZT actuation

A gas-jet micro pump with novel cross-junction channel has been designed and fabricated using a Si micromachining process. The valveless micro pump is composed of a piezoelectric lead zirconate titanate (PZT) diaphragm actuator and fluidic network. The design of the valveless pump focuses on a cross-junction formed by the neck of the pump chamber and one outlet and two opposite inlet channels. The structure of cross-junction allows differences in fluidic resistance and fluidic momentum inside the channels during each PZT diaphragm vibration cycle, which leads to the gas flow being rectified without valves. The flow channels were easily fabricated by using silicon etching process. To investigate the effects of the structure of the cross-junction on the gas flow rate, two types of pump with different cross-junction were studied. The design and simulation were done using ANSYS-Fluent software. The simulations and experimental data revealed that the step-nozzle structure is much more advantageous than the planar structure. A flow rate of 5.2 ml/min was obtained for the pump with step structure when the pump was driven at its resonant frequency of 7.9 kHz by a sinusoidal voltage of 50 V_p–p.     

基于Python的实时嵌入式软件测试脚本

基于Python语言设计一种实时测试脚本,开发扩展模块,实现测试脚本与嵌入式软件仿真测试环境（ESSTE）的接口。该测试脚本使用简便,实时性高、描述能力强、具有良好的可复用性,目前已成功应用到ESSTE中。对多个实时嵌入式软件进行测试,结果验证了该测试脚本的正确性和实时性。     

基于色度坐标高斯混合模型的步态检测

针对传统的基于RGB通道的高斯混合模型低对比度像素点检测效果较差的问题,提出一种基于色度坐标的高斯混合模型,使之更好地用于步态检测。该算法将RGB色彩值转换到色度坐标上,以强调色彩对比度,提高低对比度像素点的检测率,并增加亮度信息以减小阴影的影响,在前景提取部分,加入噪声抑制机制。实验结果表明,改进后的算法在相同对比度下,误检测率最多可减小一半。     

基于推理信息量的BN参数学习变量离散化方法

提出推理信息量的概念,将其作为贝叶斯网络连续变量离散化评价标准。在连续变量离散化的过程中,采用遗传算法寻求最优解,设计个体编码方式、交叉算子和变异算子,将推理信息量作为衡量个体适应度的标准。实例分析证明,通过该方法对变量进行离散化后学习得到的贝叶斯网络在推理时能得到更大的推理信息量。     

基于Radon变换的抗旋转攻击零水印算法

针对大多数基于变换域的零水印算法无法抵抗几何攻击（RST变换）的缺陷,提出一种基于Radon变换的抗旋转攻击零水印算法。通过Radon变换检测算法对发生旋转几何攻击后的图像进行几何校正并提取水印。仿真实验结果证明,该算法可以获得良好的图像视觉效果,对旋转几何攻击及加噪、滤波、JPEG压缩、剪切攻击有较好的鲁棒性。     

基于直方图规定化的抗几何攻击数字水印算法

提出一种基于严格直方图规定化的抗几何攻击数字水印算法。该算法基于图像块信息熵与边缘检测结果,选择图像最大的平坦区域,利用严格直方图规定化将图像平坦区域的直方图规定化为特定形状,为了提高水印检测精度与嵌入图像的保真度,选择锯齿状直方图作为水印信息。实验表明,该算法嵌入水印后的图像具有很好的保真度,对几何攻击、噪声污染、JPEG压缩、线性和非线性滤波有较好的鲁棒性。