An experimental study of the incipient bed shear stress partition in mobile bed channels filled with emergent rigid vegetation

This paper investigates the bed shear stress based on the condition of the incipient motion of sediment in a uniform-flow flume covered with emergent rigid vegetation,which is represented by arrays of circular cylinders arranged in a regular pattern.A total of 148 tests are performed to observe the influence of the vegetation density,bed slope,flow depth and sediment size on the bed shear stress.The tests reveal that when the sediment is in incipient motion,the resistances acting on the flow passing the rigid vegetation contain the vegetation resistance and the bed shear stress.This shear stress could be divided into two parts:the grain shear stress and the shear stress caused by sand dunes,which are the deformed bedform with the sediment incipient motion.An empirical relationship between the shear stress of the sand dune and vegetation density,the Froude number,the apparent vegetation layer velocity is developed.     

Determination of the dynamic recrystallization kinetics model for SCM435 steel

The flow stress behavior of SCM435 steel was studied by using a MMS-200 thermal simulation machine, under the conditions with deformation temperatures of 1023–1323 K and strain rate of 0.01–10 s^?1. The experimental results indicated that the critical strain would get smaller with the increment in temperature and the decrement in strain rate, leaving the dynamic recrystallization easier to occur. The peak stress constitutive equation of SCM435 steel under high temperatures was established by the form of hyperbolic sine, and the activation energy of deformation under high temperature was obtained by regression equation. The critical strain ? _c for dynamic recrystallization was accurately derived from the θ-σ curve containing strain hardening rate θ and flow stress σ. Then the correlation between peak stress, peak strain, critical stress, critical strain and the parameter Z was further obtained. The Avrami kinetic equation of dynamic recrystallization for SCM435 steel was developed from stress-strain curve, and the Avrami exponent m was abstracted. Observations also indicated that the Avrami constants would decrease with increments in temperature, but increase with increments in strain rate. The Avrami constant took small influence from the deforming temperature, but significant influence from strain rate, and the correlation between Avrami constant and the strain rate was obtained by regression equation.     

氧化铌掺杂PbO2电极的制备及降解分散蓝B

采用电沉积法制备氧化铌掺杂的钛基PbO2电极,通过X射线衍射、扫描电镜和电化学工作站进行表征.结果表明,掺杂氧化铌改变了沉积PbO2的晶型分布,电极表面出现α-PbO2晶型,提高了镀层与基体的结合度及电子传递效率;同时晶体尺寸略有增大,排列规整均匀.氧化铌最佳掺杂质量浓度为3.5 g/L,改性电极的析氧电位上升到1.523 V,阶跃氧化电流达到0.155 9 A,强化寿命延长到702 min,电催化性能和稳定性均有明显提升.利用所制备改性电极降解分散蓝B的最佳降解条件:溶液pH值为2,电解质NaC1浓度为0.7 mol/L,电流密度为40 mA/cm2,1h后脱色率可达89％,脱色动力学可用拟2级反应描述.     

Effect of nucleating agents and heat treatments on the crystallization of magnesium aluminosilicate transparent glass-ceramics

The crystallization behavior and transparent property of MgO-Al2O3-SiO2 (MAS) glasses with TiO2 and TiO2+ZrO2 as nucleating agents were discussed by differential thermal analysis, X-ray diffraction, field emission-environment scanning electron microscope, energy dispersive spectrum and UV-VIS-NIR scanning spectrophotometer. It was found that the glass crystallized at 950 ℃ with ZrO2 less than 3% could obtain transparent glass ceramic, which presented purple to colorless. With the nucleating agent additives (5% TiO2+3% ZrO2), the colorless transparent glass-ceramics with spinel as the main crystal phase could be prepared, and the transmittance reached about 80% . As the crystallized temperature increase to 1 000 ℃, besides spinel(MgAl2O4), sapphirine (Mg3.5Al9Si1.5O20) and ZrTiO4 precipitated from matrix glass, and the transmitance of glass-ceramic decreased.     

耦合Schrodinger-KdV方程的行波解

为了得到Schrodinger-KdV方程的行波解,运用平面动力系统理论方法,对其动力学行为进行研究,证明了该方程光滑孤立波解和光滑周期波解的存在性,并在不同的参数条件下,给出了各类解存在的充分条件,求出了所有显式精确行波解。     

一种功能可配置的业务中间件软件产品及其应用

探讨一种功能可配置的业务中间件软件产品及其在业务系统开发中的应用.阐述该系统实现的原理,分析系统体系结构与主要组成,研究系统实现方法及其特点.以国土资源电子政务信息系统为例,说明该软件产品的应用及效果.该研究为众多领域的业务信息系统的高效研发提供了一种新的技术与工具支持.     

一种新的频繁子树挖掘算法研究与实现

为提高频繁子树挖掘算法效率,结合原有频繁子树挖掘算法FSubtreeM的相关技术提出了新的全局树引导结构及其相关引理,并证明了其正确性.最后提出了新的频繁子树挖掘算法FSM_CGTG,并通过实验证明了该算法在现实数据集上的有效性且比现有频繁子树挖掘算法FSubtreeM性能优越.     

Preface

Recently, there has been a dramatic increase in research on data mining on social networks and social media. Theubiquitous nature of Web-enabled devices, including desktops,     

A tunable support vector machine assembly classifier for epileptic seizure detection

Automating the detection of epileptic seizures could reduce the significant human resources necessary for the care of patients suffering from intractable epilepsy and offer improved solutions for closed-loop therapeutic devices such as implantable electrical stimulation systems. While numerous detection algorithms have been published, an effective detector in the clinical setting remains elusive. There are significant challenges facing seizure detection algorithms. The epilepsy EEG morphology can vary widely among the patient population. EEG recordings from the same patient can change over time. EEG recordings can be contaminated with artifacts that often resemble epileptic seizure activity. In order for an epileptic seizure detector to be successful, it must be able to adapt to these different challenges. In this study, a novel detector is proposed based on a support vector machine assembly classifier (SVMA). The SVMA consists of a group of SVMs each trained with a different set of weights between the seizure and non-seizure data and the user can selectively control the output of the SVMA classifier. The algorithm can improve the detection performance compared to traditional methods by providing an effective tuning strategy for specific patients. The proposed algorithm also demonstrates a clear advantage over threshold tuning. When compared with the detection performances reported by other studies using the publicly available epilepsy dataset hosted by the University of BONN, the proposed SVMA detector achieved the best total accuracy of 98.72%. These results demonstrate the efficacy of the proposed SVMA detector and its potential in the clinical setting.     

一种改进的多机器人协作实时FastSLAM算法

针对FastSLAM1.0中机器人缺乏自身定位测量修正引起的累积误差和FastSLAM2.0引入测量修正引起算法复杂度增加的问题,提出一种改进的基于辅助测量的多机器人协作实时FastSLAM算法,使用双机器人协同工作,领头机器人负责完成同时定位与地图构建任务,辅助机器人通过静态相对位置测量为领头机器人提供实时定位测量修正.该辅助测量方法不仅为SLAM任务执行机器人提供较准确的定位测量值,同时也避免了FastSLAM2.0算法中额外的算法复杂度问题.实验结果表明算法既可以获得较高的精度,而且方便可行,具有较高实用价值.