Accurate video text detection through classification of low and high contrast images

Detection of both scene text and graphic text in video images is gaining popularity in the area of information retrieval for efficient indexing and understanding the video. In this paper, we explore a new idea of classifying low contrast and high contrast video images in order to detect accurate boundary of the text lines in video images. In this work, high contrast refers to sharpness while low contrast refers to dim intensity values in the video images. The method introduces heuristic rules based on combination of filters and edge analysis for the classification purpose. The heuristic rules are derived based on the fact that the number of Sobel edge components is more than the number of Canny edge components in the case of high contrast video images, and vice versa for low contrast video images. In order to demonstrate the use of this classification on video text detection, we implement a method based on Sobel edges and texture features for detecting text in video images. Experiments are conducted using video images containing both graphic text and scene text with different fonts, sizes, languages, backgrounds. The results show that the proposed method outperforms existing methods in terms of detection rate, false alarm rate, misdetection rate and inaccurate boundary rate.     

Computational investigation of interactions between human H2 receptor and its agonists

Type 2 histamine receptor (H(2)R) is widely distributed in the body. Its main function is modulating the secretion of gastric acid. Most gastric acid-related diseases are closely associated with it. In this study, a combination of pharmacophore modeling, homology modeling, molecular docking and molecular dynamics methods were performed on human H(2)R and its agonists to investigate interaction details between them. At first, a pharmacophore model of H(2)R agonists was developed, which was then validated by QSAR and database searching. Afterwards, a model of the H(2)R was built utilizing homology modeling method. Then, a reference agonist was docked into the receptor model by induced fit docking. The 'induced' model can dramatically improve the recovery ratio from 46.8% to 69.5% among top 10% of the ranked database in the simulated virtual screening. The pharmocophore model and the receptor model matched very well each other, which provided valuable information for future studies. Asp98, Asp186 and Tyr190 played key roles in the binding of H(2)R agonists, and direct interactions were observed between the three residues and agonists. Residue Tyr250 could also form a hydrogen bond with H(2)R agonists. These findings would be very useful for the discovery of novel and potent H(2)R agonists.     

基于BP神经网络的石化过程在线故障监测系统

针对石化生产过程的高危性,开发了石化过程在线故障监测系统.通过OPC(OLE for process control)接口从生产现场采集实时数据,采用BP神经网络(back-propagation artificial neural network,BPNN)的模式识别方法,对生产过程进行实时故障监测,及时发现故障工况并提示操作人员采取相应措施,以减小系统运行的风险.BP神经网络的训练数据来自历史数据库,用户根据已发生过的故障工况确定训练数据的时间范围.BP网络模型的各项参数根据多次试验得到.对某工段的10个故障,其故障诊断准确率达到90%以上,具有较高的实时性和准确性.     

Quantizer design for interconnected feedback control systems

In this paper, we consider the design of interconnected H-infinity feedback control systems with quantized signals. We assume that a decentralized static output feedback has been designed for an interconnected continuous-time LTI system so that the closed-loop system is stable and a desired H-infinity disturbance attenuation level is achieved, and that the subsystems’ measurement outputs are quantized before they are passed to the local controller. We propose a localoutput- dependent strategy for updating the quantizers’ parameters, so that the overall closed-loop system is asymptotically stable and achieves the same H-infinity disturbance attenuation level. Both the pre-designed controllers and the quantizers’ parameters are constructed in a decentralized manner, depending on local information.     

Predictive control and scheduling codesign in network control systems

A codesign approach combining predictive control compensation and network scheduling is presented in this paper to overcome the adverse influences of stochastic time delays and packet losses encountered in network-based real-time control systems. The state estimation and control prediction compensation algorithms are used for the random network delays in the feedback and forward channels, and the stability criteria are analyzed. The proper sampling rate is given with network scheduling to meet the desired system performance, while the network-induced delay is tolerated. Simulations show that the codesign approach works well with the bounded network delay.     

Numerical analysis and physical simulations for the time fractional radial diffusion equation

We do the numerical analysis and simulations for the time fractional radial diffusion equation used to describe the anomalous subdiffusive transport processes on the symmetric diffusive field. Based on rewriting the equation in a new form, we first present two kinds of implicit finite difference schemes for numerically solving the equation. Then we strictly establish the stability and convergence results. We prove that the two schemes are both unconditionally stable and second order convergent with respect to the maximum norm. Some numerical results are presented to confirm the rates of convergence and the robustness of the numerical schemes. Finally, we do the physical simulations. Some interesting physical phenomena are revealed; we verify that the long time asymptotic survival probability ∝t^−α, but independent of the dimension, where α is the anomalous diffusion exponent.     

球杆网络化控制系统的延时分析与控制方法研究

对球杆系统进行了机理建模,并针对球杆网络化控制系统网络负载小、节点少、带宽冗余等特点,从网络通信原理的角度分析了网络延时的不确定性,结合测试结果提出了具有时变性、分段保持性延时特征的网络环境的假设.在这个前提下,将网络分布时延转换为前向通道上的单一时延.在此基础上提出了球杆网络化控制系统的根据延时分段补偿控制的策略及在...     

基于黑板Agent结构的应用模块工作流通用模板设计

分析了基于黑板Ａｇｅｎｔ结构的工作流管理体系,提出了面向产品协同设计的应用模块模型化管理方法,最后介绍了基于黑板Ａｇｅｎｔ结构的应用模块工作流通用模板的设计与实现方法。     

基于模糊算法的炉料粒级分布优化系统

本文在深入研究鼓风炉铅锌熔炼过程的基础上,分析了入炉炉料的粒级分布和透气性指数之间关系,提出了用模糊控制方法来计算鼓风炉入炉炉料的粒级分布,提出了基于专家规则的模糊控制算法,采用参数自修正自寻优的方法,不断对模型进行在线修正,仿真结果表明,采用该模型控制的透气性波动较小,趋势趋于平衡。     

基于视觉的水下管线识别与定位系统

论述了在水环境下如何通过视觉识别管线并给以精确的定位。提出了水下视觉系统的总体设计方案。在识别目标时,以目标的颜色为特征,并将颜色从ＲＧＢ窨转换到ＨＳＩ空间,使图象处理的速度和特征抽取的鲁棒性得到提高。对水下环境中点和线的精确定位进行了详细的分析,给出定位算法。最后的实验结果证明了算法的有效性。