Automatic robotic tasks in unstructured environments using an image path tracker

This paper describes a new method to perform automatic tasks with a robot in an unstructured environment. A task to replace a blown light bulb in a streetlamp is described to show that this method works properly. In order to perform this task correctly, the robot is positioned by tracking secure previously defined paths. The robot, using an eye-in-hand configuration on a visual servoing scheme and a force sensor, is able to interact with its environment due to the fact that the path tracking is performed with time-independent behaviour. The desired path is expressed in the image space. However, the proposed method obtains a correct tracking not only in the image, but also in the 3D space. This method solves the problems of the previously proposed time-independent tracking systems based on visual servoing, such as the specification of the desired tracking velocity, less oscillating behaviour and a correct tracking in the 3D space when high velocities are used. The experiments shown in this paper demonstrate the necessity of time-independent behaviour in tracking and the correct performance of the system.     

Social networks and genetic algorithms to choose committees with independent members

Choosing committees with independent members in social networks can be regarded as a group selection problem where independence, as the main selection criterion, can be measured by the social distance between group members. Although there are many solutions for the group selection problem in social networks, such as target set selection or community detection, none of them have proposed an approach to select committee members based on independence as group performance measure. In this work, we propose a novel approach for independent node group selection in social networks. This approach defines an independence group function and a genetic algorithm in order to optimize it. We present a case study where we build a real social network with on-line available data extracted from a Research and Development (R&D) public agency, and then we compare selected groups with existing committees of the same agency. Results show that the proposed approach can generate committees that improve group independence compared with existing committees.     

An integrated package for drought monitoring,prediction and analysis to aid drought modeling and assessment

Due to severe drought events and disastrous impacts in recent decades, substantial efforts have been devoted recently to drought monitoring, prediction and risk analysis for aiding drought preparedness plans and mitigation measures. Providing an overview of these aspects of drought research, this study presents an integrated R package and illustrates a wide range of its applications for drought modeling and assessment based on univariate and multivariate drought indices for both operational and research purposes. The package also includes statistical prediction of drought in a probabilistic manner based on multiple drought indicators, which serves as a baseline for drought prediction. The univariate and multivariate drought risk analysis of drought properties and indices is also presented. Finally, potential extensions of this package are also discussed. The package is provided freely to public to aid drought early warning and management.     

基于概念格的数据挖掘方法在库存管理中的应用*

库存管理是物流系统优化的一个重要内容,利用概念格的数据挖掘方法来实现多目标优化过程中,给出了库存模型向概念格模型转换的方法,提出了一种具体的概念格的渐进式构造算法;对于概念格的数据挖掘方法,具体定义了概念格中的关联规则,并提取了库存模型中的隐藏知识,进而为实现库存模型的多目标优化提供了决策支持。     

A Piecewise Grey System Model for Study the Effects of Anthropogenic Activities on Karst Hydrological Processes

Sustainable groundwater development must rely on a good understanding of hydrological processes, especially under effects of anthropogenic activities. This paper develops a piecewise analysis based on grey system model for study effects of anthropogenic activities on hydrological processes. The time series of precipitation and spring discharge were segmented into three time periods depending on whether variations are due to climate variation: the predevelopment stage, the transition stage, and the new equilibrium stage. Then we modeled hydrological process of the predevelopment stage and new equilibrium stage by the grey system model. By comparing the model results, we can quantify the effects of human activities on hydrological processes. We applied the model to Liulin Springs China. The results indicated that the hydraulic response time of the spring discharge to precipitation from the predevelopment stage to the new equilibrium stage, ranges from less than 1 year to up to 4 years. The results revealed that human activities slow the groundwater flow. GM (1,N) models of Liulin Springs discharge showed that the driving coefficients of precipitation to the spring discharge decreased from 0.012272 in the predevelopment stage to 0.007753 in the new equilibrium stage, which means that groundwater recharge ability has reduced about 36.82 %. Human activities in Liulin Springs have drastically changed the groundwater system. Piecewise grey system model is a robust method for hydrological process simulation.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

基于数字图像处理的混凝土细观有限元建模

将混凝土看成由水泥砂浆、粗骨料及两者之间的界面组成的三相复合材料。采用MATLAB图像处理工具,选取窗口大小为5×5的像素矩阵对二值图像进行中值滤波处理,然后以结构元素形状为disk、结构半径为2的像素矩阵进行图像形态学处理,最后对图像进行边缘检测以提取二维混凝土骨料边界。基于8连通区域的图像轮廓跟踪算法,运用几何矢量转换技术得到混凝土细观结构图,并在有限元软件ANSYS中对细观数值模型进行了加载试验。结果表明,用该方法得到的细观数值模型与原图像吻合好,可真实地研究混凝土在宏、细观方面的力学性能。     

胶黏钢-混凝土组合梁的界面行为数值分析

根据推出的试验测试数据,将黏胶/混凝土界面的剪切-滑移行为用具备损伤本构关系的弹簧单元来模拟,建立胶黏钢-混凝土组合梁的三维非线性有限元模型.基于模拟结果,揭示了组合梁黏胶/混凝土界面的黏结应力分布规律及脱胶剥离过程.分析结果表明:弹性模量小的黏胶剂更有利于界面的剪力均匀传递,但会引起混凝土板和钢梁间产生大的相对滑动,导致结构整体承载力降低.胶黏组合梁的界面脱胶剥离是一个突发的典型脆性破坏过程,会产生灾难性后果,在设计过程中需引起足够重视.     

振荡电压的计算

电路由一种状态变为另一种状态,会出现高频振荡的过渡过程。文章推求振荡电压的计算公式。