Time‐Series Plots Integrated in Parallel‐Coordinates Displays

We present a natural extension of two‐dimensional parallel‐coordinates plots for revealing relationships in time‐dependent multi‐attribute data by building on the idea that time can be considered as the third dimension. A time slice through the visualization represents a certain point in time and can be viewed as a regular parallel‐coordinates display. A vertical slice through one of the axes of the parallel‐coordinates display would show a time‐series plot. For a focus‐and‐context Integration of both views, we embed time‐series plots between two adjacent axes of the parallel‐coordinates plot. Both time‐series plots are drawn using a pseudo three‐dimensional perspective with a single vanishing point. An independent parallel‐coordinates panel that connects the two perspectively displayed time‐series plots can move forward and backward in time to reveal changes in the relationship between the time‐dependent attributes. The visualization of time‐series plots in the context of the parallel‐coordinates plot facilitates the exploration of time‐related aspects of the data without the need to switch to a separate display. We provide a consistent set of tools for selecting and contrasting subsets of the data, which are important for various application domains.     

Crawl through Neighbors: A Simple Curve Reconstruction Algorithm

Given a planar point set sampled from an object boundary, the process of approximating the original shape is called curve reconstruction. In this paper, a novel non‐parametric curve reconstruction algorithm based on Delaunay triangulation has been proposed and it has been theoretically proved that the proposed method reconstructs the original curve under ε‐sampling. Starting from an initial Delaunay seed edge, the algorithm proceeds by finding an appropriate neighbouring point and adding an edge between them. Experimental results show that the proposed algorithm is capable of reconstructing curves with different features like sharp corners, outliers, multiple objects, objects with holes, etc. The proposed method also works for open curves. Based on a study by a few users, the paper also discusses an application of the proposed algorithm for reconstructing hand drawn skip stroke sketches, which will be useful in various sketch based interfaces.     

Reduced Aggregate Scattering Operators for Path Tracing

Aggregate scattering operators (ASOs) describe the overall scattering behavior of an asset (i.e., an object or volume, or collection thereof) accounting for all orders of its internal scattering. We propose a practical way to precompute and compactly store ASOs and demonstrate their ability to accelerate path tracing. Our approach is modular avoiding costly and inflexible scene‐dependent precomputation. This is achieved by decoupling light transport within and outside of each asset, and precomputing on a per‐asset level. We store the internal transport in a reduced‐dimensional subspace tailored to the structure of the asset geometry, its scattering behavior, and typical illumination conditions, allowing the ASOs to maintain good accuracy with modest memory requirements. The precomputed ASO can be reused across all instances of the asset and across multiple scenes. We augment ASOs with functionality enabling multi‐bounce importance sampling, fast short‐circuiting of complex light paths, and compact caching, while retaining rapid progressive preview rendering. We demonstrate the benefits of our ASOs by efficiently path tracing scenes containing many instances of objects with complex inter‐reflections or multiple scattering.     

Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.     

基于CNN的监控视频事件检测

复杂监控视频中事件检测是一个具有挑战性的难题, 而TRECVID-SED评测使用的数据集取自机场的实际监控视频,以高难度著称. 针对TRECVID-SED评测集, 提出了一种基于卷积神经网络(Convolutional neural network, CNN)级联网络和轨迹分析的监控视频事件检测综合方案. 在该方案中, 引入级联CNN网络在拥挤场景中准确地检测行人, 为跟踪行人奠定了基础; 采用CNN网络检测具有关键姿态的个体事件, 引入轨迹分析方法检测群体事件. 该方案在国际评测中取得了很好的评测排名: 在6个事件检测的评测中, 3个事件检测排名第一.     

Forecasting financial time series using a methodology based on autoregressive integrated moving average and Taylor expansion

Financial time series prediction is regarded as one of the most challenging job because of its inherent complexity, and the hybrid forecasting model incorporating autoregressive integrated moving average and support vector machine (SVM) has been implemented widely to deal with the both linear and nonlinear patterns in time series data. However, the SVM model does not take into consideration the time correlation knowledge between different data points in time series, which impacts the learning efficiency of the SVM in real application. To overcome this restriction, this paper proposes the Taylor Expansion Forecasting model as an alternative to the SVM and develops a novel hybrid methodology via combining autoregressive integrated moving average and Taylor Expansion Forecasting to exploit the comprehensive forecasting capacity to the financial time series data with noise. Both theoretical proof and empirical results obtained on several commodity future prices demonstrate that the proposed hybrid model improves greatly the forecasting accuracy.     

A hybrid approach for autonomous navigation of mobile robots in partially-known environments

We propose a hybrid approach specifically adapted to deal with the autonomous-navigation problem of a mobile robot which is subjected to perform an emergency task in a partially-known environment. Such a navigation problem requires a method that is able to yield a fast execution time, under constraints on the capacity of the robot and on known/unknown obstacles, and that is sufficiently flexible to deal with errors in the known parts of the environment (unexpected obstacles). Our proposal includes an off-line task-independent preprocessing phase, which is applied just once for a given robot in a given environment. Its purpose is to build, within the known zones, a roadmap of near-time-optimal reference trajectories. The actual execution of the task is an online process that combines reactive navigation with trajectory tracking and that includes smooth transitions between these two modes of navigation. Controllers used are fuzzy-inference systems. Both simulation and experimental results are presented to test the performance of the proposed hybrid approach. Obtained results demonstrate the ability of our proposal to handle unexpected obstacles and to accomplish navigation tasks in relatively complex environments. The results also show that, thanks to its time-optimal-trajectory planning, our proposal is well adapted to emergency tasks as it is able to achieve shorter execution times, compared to other waypoint-navigation methods that rely on optimal-path planning.     

基于STM32控制的仓储搬运机器人

针对实际工业生产过程对自动化的需求,阐明了实现精确搬运的智能机器人的设计.该机器人运用灰度、颜色传感器完成循迹、颜色识别的导向识别功能;通过STM32产生PMW波形控制伺服电机的转动,精确搬运物料;模拟真实厂区环境,规划高容错率行进路线.实验表明,机器人设计简单,易于实现与批量生产,实用可靠,可在自动化领域广泛推广.     

自底向上构建高效BVH的研究

光线追踪中,加速结构对于减少光线与几何体求交的计算量起到了不可或缺的作用,找到一种高效的加速结构仍然是本领域的研究热点之一.传统的加速结构如BVH,都是自顶向下的构建方式,由于其本身的限制,构造出的加速结构往往不是最优的.为了改进自顶向下的缺陷,提出了一种自底向上BVH的构建方式,它使用了BVH和空间划分的混合结构,并引入了一种改进的表面积启发代价函数和多个构建参数来优化最后的构建结果.最后实验表明,此文中提出的方式比传统的BVH与KD-Trees有更好的加速效果,可以实现对前两者5%-10%的提速.最后,文中还给出了一些加速方案来减少构建时间.     

关于并发系统分支互模拟关系发散性保持的研究

带发散性说明的分支互模拟是van Glabbeek和Weijland提出的一个概念,并被用来定义等价关系.该等价关系应该是最弱的一个发散性保持的并且满足分支互模拟性质的等价关系.然而在概念提出时并没有提供这些重要性质的证明,并且我们认为在原定义的基础上这个证明是不显然的.本文通过co-induction的手段利用染色迹的概念定义了着色完全迹等价,并证明该等价关系是最弱的一个保持发散的并且满足分支互模拟性质的等价关系.然后我们证明了着色完全迹等价关系和≈_b^△是相同的,因而补充了van Glabbeek和Weijland的工作,即证明了≈_b^△是最弱的一个保持发散的并且是满足分支互模拟性质的等价关系.