视觉导航机器人三维场景重建研究

针对自主导航机器人在室外中的立体视觉,应用了一种基于置信点扩展的三维重建的方法。该方法改进了归一化交叉相关算法,由视差空间图寻找视差空间中的置信点并进行表面跟踪,并用计算亚象素视差和中值滤波的办法得到视差图,最后使用滚球算法对从视差图中得到的点云数据进行三角化从而进行地形重建。实验结果表明,所使用匹配方法优于单一的归一化交叉相关方法,有着较强的鲁棒性,重建的地形效果较为理想。     

基于非量测相机的大坝三维模型的建立

以肖岭水库为例,探索并实践了利用非量测相机获取影像,并研究了建立三维模型的方法.首先利用拓普康全站仪获取控制点的三维坐标,使用非量测相机拍摄具有一定重叠度的像片,并利用拓普康公司的PI-Calib软件进行相机标定;然后采用MapMatrix软件进行影像的数据处理,通过自动相对定向、绝对定向,自动生成DEM和DOM以及三维模型.试验结果表明,该方法是可行的.     

玉米秸秆生物质热裂解产物分析

采用流化床热解反应器,以玉米秸秆热裂解产物为研究对象,对生物油组分、密度、粘度、pH、含水量、热值等进行分析.结果表明生物油含水量在25%~43%之间,偏酸性.粘度、密度、热值随含水量增加而降低.同时对生物油的均匀性和稳定性进行了考察,对生物油性质的分析做了基础性研究.     

分数跳-扩散下外汇期权定价

用保险精算方法,在股票价格服从分数跳-扩散过程,且无风险利率、波动率和期望收益率为时间的非随机函数,给出了外汇期权定价公式.     

掺固硫灰干粉砂浆的性能研究

对掺固硫灰干粉砂浆的性能进行了研究。讨论了固硫灰细度、掺量及与粉煤灰复掺对干粉砂浆工作性能、力学性能和膨胀性的影响。结果表明：经预处理固硫灰可以应用于干粉砂浆中,且掺量为10%时效果最佳。固硫灰与粉煤灰等矿物掺合料复掺可以改善干粉砂浆性能。     

武汉城市圈高校教育资源共享机制的构建

武汉城市圈内高校教育资源十分丰富但分布极不平衡。为提高教育资源的使用效益,促进城市圈高校教育的一体化发展,必须以科学发展观为理论指导,从转变观念、创新体制和完善机制等方面构建武汉城市圈高等学校教育资源共享的平台,以便更好地发挥高等教育在推进武汉城市圈＂两型社会＂建设中的＂动力站＂和＂加速器＂作用。     

Electric-oxidation extraction of molybdenite concentrate in alkaline NaCl electrolyte

The dissolution of molybdenite concentrate in NaCl electrolyte was investigated. The results show that the dissolution rate increases with the increase in liquid-to-solid ratio, stirring speed, NaCl concentration and temperature. When the liquid-to-solid ratio is 30:1, stirring speed is 400 r/min, concentration of NaCl is 4 mol/L at pH=9 and room temperature, the leaching efficiency of molybdenite concentrate will reach 99.5% in 240 min. Molybdenite concentrate cannot be electro-oxidized directly on the anode. The kinetic studies show that the dissolution of molybdenite concentrate is represented by shrinking core model with diffusion through a porous product layer of element sulfur, and the apparent activation energy for the dissolution reaction is 8.56 kJ/mol.     

Dynamic surface control-backstepping based impedance control for 5-DOF flexible joint robots

A new impedance controller based on the dynamic surface control-backstepping technique to actualize the anticipant dynamic relationship between the motion of end-effector and the external torques was presented. Comparing with the traditional backstepping method that has “explosion of terms” problem, the new proposed control system is a combination of the dynamic surface control technique and the backstepping. The dynamic surface control (DSC) technique can resolve the “explosion of terms” problem that is caused by differential coefficient calculation in the model, and the problem can bring a complexity that will cause the backstepping method hardly to be applied to the practical application, especially to the multi-joint robot. Finally, the validity of the method was proved in the laboratory environment that was set up on the 5-DOF (degree of freedom) flexible joint robot. Tracking errors of DSC-backstepping impedance control that were 2.0 and 1.5 mm are better than those of backstepping impedance control which were 3.5 and 2.5 mm in directions X, Y in free space, respectively. And the anticipant Cartesian impedance behavior and compliant behavior were achieved successfully as depicted theoretically.     

Application of open-pit and underground mining technology for residual coal of end slopes

Given the conditions of residual coal from the boundary of a flat dipping open-pit mine,which uses strip areas mining and inner dumping with slope-covering,we propose an open-pit and underground integrated mining technology for residual coal of end slopes.In the proposal a conveyance road and ventilation conveyance near the slope are built,corresponding to the pit mining area and the surface coal mine dump,as well as an interval haulage tunnel and air-inlet tunnel.The outcome shows that such mining method may reduce the effect to slope stability from underground mining,it does not affect the dumping advance and has a high recovery rate of residual coal resources.The working face is timbered by single hydraulic props,transported by a scraper conveyor and supported by coal walls.This method of mining is one of layered top coal caving,with high resource recovery,low production cost where positive economic benefit can be realized.     

Multi-label dimensionality reduction based on semi-supervised discriminant analysis

Multi-label data with high dimensionality often occurs, which will produce large time and energy overheads when directly used in classification tasks. To solve this problem, a novel algorithm called multi-label dimensionality reduction via semi-supervised discriminant analysis (MSDA) was proposed. It was expected to derive an objective discriminant function as smooth as possible on the data manifold by multi-label learning and semi-supervised learning. By virtue of the latent imformation, which was provided by the graph weighted matrix of sample attributes and the similarity correlation matrix of partial sample labels, MSDA readily made the separability between different classes achieve maximization and estimated the intrinsic geometric structure in the lower manifold space by employing unlabeled data. Extensive experimental results on several real multi-label datasets show that after dimensionality reduction using MSDA, the average classification accuracy is about 9.71% higher than that of other algorithms, and several evaluation metrices like Hamming-loss are also superior to those of other dimensionality reduction methods.