Label-free electrochemical immunosensor for sensitive detection of kanamycin

A novel label-free electrochemical immunosensor for sensitive detection of kanamycin based on water-soluble graphene sheet (WGS)/prussian blue-chitosan (PB-CTS)/nanoporous gold (NPG) composited film has been reported. PB was selected as an electron transfer mediator, and was modified onto the electrode together with WGS through electrostatic adsorption. Then NPG was immobilized onto the as-prepared film for biomolecules anchoring. The electroactivity of PB was greatly enhanced in the presence of WGS and NPG. It could mainly be ascribed to the fact that the good conductivity of WGS and NPG promoted electron transfer and enhanced the sensitivity. kanamycin antibody, as a model, was immobilized onto the composite film for the detection of kanamycin. Under optimum conditions, the amperometric signal of PB decreased linearly with kanamycin concentration (0.02-14 ng mL⁻¹), a linear calibration plot (y = 1.3817 + 4.7544x, r = 0.9993), resulting in a low limit of detection (6.31 pg mL⁻¹). The novel immunosensor for the detection of kanamycin in real sample with satisfactory results has been proved. In addition, this method would be easily adapted for the detection of other residual antibiotics in animal derived foods.     

Process parameters selection of fluid industry based on flexible neural trees

Fluid industry＇s production takes on high complexity, strong association, non-linear and indeterminacy. To find important parameters which influence production process, provide theoretical basis for process control of fluid industry＇s production and make the production process control more exact, we propose a flexible neural tree model in this paper. The model can be created based on predeflned information set. The structure and parameters of flexible neural tree are optimized by probabilistic incremental program evolution and simulation annealing respectively. We take production process of decomposed kiln---one of important cement＇s processes---as an example. The result indicates that the proposed model is greatly efficient.     

Machinability of Metal Matrix Composites Reinforced by 3-D Network Structure

Metal matrix composites reinforced by three-dimensional (3-D) continuous network structure reinforcement (3DCNRMMC) are difficult to machine due to serious tool wear and poor surface roughness caused by the brittle and hard reinforcement which interpenetrate into ductile matrix. In order to achieve the approach of low cost of 3DCNRMMC, the machinability of it needs to be understood. The influences of three cutting parameters and volume fraction of reinforcement on cutting force were analyzed in detail. The results indicate that: (1) Due to the brittle phase(s) introduced into ductile matrix of composites, there is a large fluctuation of cutting force causing deterioration of machinability. The fluctuation ranges of cutting forces, initially increase rapidly with the increase of volume fraction of reinforcement and then decrease finally, are largest at the range of the volume fraction of 55–65%; (2) The influence of cutting parameters on cutting force is obvious. With the increases of cutting speed, cutting force decreases gradually unless cutting speed exceeds the value of 209 m/min. Cutting forces increase with increasing feed rate and depth of cut; (3) Owing to the large fluctuation of cutting force, there were some cratered surfaces caused by Si₃N₄ reinforcement pulling-out and flaking-off. Some brittle phase protruding from the machined surface caused the deterioration of machined surface.     

Optimal filtering for networked systems with Markovian communication delays

This paper is concerned with optimal filter problems for networked systems with random transmission delays, while the delay process is modeled as a multi-state Markov chain. By defining a delay-free observation sequence, the optimal filter problems are transformed into ones of the Markov jumping parameter system. We first present an optimal Kalman filter, which is with time-varying, path-dependent filter gains, and the number of the paths grows exponentially in time delay. Thus an alternative optimal Markov jump linear filter is presented, in which the filter gains just depend on the present value of the Markov chain. Further, an optimal filter with constant-gains is developed, the existence condition for the stabilizing solutions to the filter is given, and it can be shown that the proposed Markov jump linear filter converges to the constant-gain filter under appropriate assumptions.     

使用二次特征选择及核融合的语音情感识别

为提高语音情感识别精度,对基本声学特征构建的多维特征集合,采用二次特征选择方法综合考虑特征参数与情感类别之间的内在特性,从而建立优化的、具有有效情感可分性的特征子集;在语音情感识别阶段,设计二叉树结构的多分类器以综合考虑系统整体性能与复杂度,采用核融合方法改进SVM模型,使用多核SVM识别混淆度最大的情感。算法在Berlin情感语音库五种情感状态的样本上进行验证,实验结果表明二次特征选择与核融合相结合的方法在有效提高情感识别精度的同时,对噪声具有一定的鲁棒性。     

灰度累积投影直方图在胎冠缺陷检测中的应用

针对轮胎胎冠帘线搭接缺陷的自动检测问题,提出一种基于胎冠X射线图像的检测方法。首先,依据胎冠的X射线影像和投影角计算胎冠成像的灰度累积投影曲线;然后,计算曲线的局部峰值能量分布;其次,采用前n个最大峰值能量构造投影曲线的能量特征向量,并利用支持向量机(SVM)分类器进行最大投影曲线的判别;最后,利用位置反演计算对缺陷进行定位。仿真实验结果表明,所提方法可以对生产过程中采集的1000幅胎冠图像进行有效的缺陷检测,其最高检测正确率可达97.7%。     

基于虚拟导航线的农业机器人精确视觉导航方法

针对农田、野外环境中无人工标记情况下的导航问题,提出了一种基于虚拟导航线的农业机器人精确视觉导航方法。该方法不需要铺设导航线或者路标即可引导机器人行走直线。首先,根据需求确定需要跟踪的目标区域,之后控制机器人调整方向直到目标移至视野中央;其次,根据机器人和目标的位置确定参照目标,并依据两个目标的位置确定虚拟导航线;然后,动态更新导航线,并结合虚拟定标线和虚拟导航线确定偏移角度和偏移距离;最后,利用偏移参数构建模糊控制表,并以此实现对机器人旋转角度和行走速度的调整。实验结果表明,该算法能较为精确地实现对导航路线的识别,进而利用模糊控制策略使机器人沿直线向目标行走,且导航精度在10 cm以内。     

刀片加密服务器的文件加脱密技术

刀片加密服务器可以比较全面地解决从信息传输到信息存储全过程的信息安全问题。它主要应用在建立安全公用信息平台以及电子商务、电子政务等方面。利用刀片加密服务器建立的安全公用信息平台,将能逐步改变企业传统的建网观念,使企业由独立建网逐步转变为租用公网,计算机网络将真正走向公用化。本文主要介绍了刀片加密服务器的文件加脱密技术。     

面向分布式控制系统的实时SOA研究与应用

SOA(Service Oriented Architecture)已广泛应用于传统信息系统领域。如何将sOA思想应用于社会上广泛存在的分布式控制系统的构建,是服务计算领域的一个新的研究课题。针对分布式控制系统的特点及面向服务的思想,提出一种可有效解决消息可靠性传输、服务实时性处理的层次化实时SOA模型,给出各层次模型的详细思路与实现机制。基于该模型,设计并实现了电力配网自动化系统的底层多网络冗余实时消息总线原型系统,并给出了相关结 论。