具有并行约束目标的多主体系统动态角色分配

多主体系统已成为建模和开发大型复杂分布式信息系统的一种理想范型.很多基于主体技术的系统要求支持动态角色分配,而已有动态角色分配算法忽略了目标之间的约束对角色分配的影响.首先,提出一个具有并行约束目标的多主体系统动态角色分配模型,引入多个角色分配管理者主体共同承担角色分配的计算任务,避免因单个主体可能造成的计算瓶颈.然后,基于并行约束目标结构图,给出目标集划分算法.并设计实现了角色分配算法,分析了该算法的时间复杂度.最后,实验研究了角色分配算法的执行时间,表明理论分析与实验结果一致.基于目标集合划分对角色分配的计算任务进行分割,使得各个角色分配管理者主体的计算结果无需进行合并再进行并行约束检查.     

基于Petri-net的机器人足球角色转换研究

文章在分析机器人足球的角色的基础上,提出了用Petri-net来描述角色转换的原理,该方法简洁明了,完全适用于机器人足球多协调决策系统。     

Autonomous sub-image matching for two-dimensional electrophoresis gels using MaxRST algorithm

Matching two-dimensional electrophoresis (2-DE) gel images typically generates a bottleneck in the automated protein analysis, and image distortion and experimental variation, which reduce the matching accuracy. However, conventional matching schemes only compare two complete images, and landmark selection and registration procedures are rather time-consuming. This work presents a novel and robust Maximum Relation Spanning Tree (MaxRST) algorithm, in which an autonomous sub-image matching method does not require registering or manual selection of landmarks. The 2D gel images are represented graphically. Image features are then quantitatively extracted regardless of image size. Similarity between a sub-image and large image is then determined based on Gaussian similarity measurement inspired by fuzzy method, thereby increasing the accuracy of fractional matching. The proposed autonomous matching algorithm achieves an accuracy of up to 97.29% when matching 627 2-DE gel test images. In addition to accommodating image rotation, reversals, shape deformation and intensity changes, the proposed algorithm effectively addresses the sub-image mapping problem and was analyzed thoroughly using a large dataset containing 4629 images. The contributions of this work are twofold. First, this work presents a novel MaxRST strategy and autonomous matching method that does not require manual landmark selection. Second, the proposed method, which extends 2-DE gel matching to query sub-image and a database containing large sets of images, can be adopted for mapping and locating, and to compare small gel images with large gel images with robustness and efficiency.     

Adaptive Matrix Completion for Fast Visibility Computations with Many Lights Rendering

Several fast global illumination algorithms rely on the Virtual Point Lights framework. This framework separates illumination into two steps: first, propagate radiance in the scene and store it in virtual lights, then gather illumination from these virtual lights. To accelerate the second step, virtual lights and receiving points are grouped hierarchically, for example using Multi-Dimensional Lightcuts. Computing visibility between clusters of virtual lights and receiving points is a bottleneck. Separately, matrix completion algorithms reconstruct completely a low-rank matrix from an incomplete set of sampled elements. In this paper, we use adaptive matrix completion to approximate visibility information after an initial clustering step. We reconstruct visibility information using as little as 10 % to 20 % samples for most scenes, and combine it with shading information computed separately, in parallel on the GPU. Overall, our method computes global illumination 3 or more times faster than previous state-of-the-art methods.     

Autonomous feature following for visual surveillance using a small unmanned aerial vehicle with gimbaled camera system

This paper represents the development of feature following control and distributed navigation algorithms for visual surveillance using a small unmanned aerial vehicle equipped with a low-cost imaging sensor unit. An efficient map-based feature generation and following control algorithm is developed to make an onboard imaging sensor to track a target. An efficient navigation system is also designed for real-time position and velocity estimates of the unmanned aircraft, which is used as inputs for the path following controller. The performance of the proposed autonomous path following capability with a stabilized gimbaled camera onboard a small unmanned aerial robot is demonstrated through flight tests with application to target tracking for real-time visual surveillance.     

基于样本分布不平衡的近似支持向量机

针对标准的近似支持向量机（PSVM）没有考虑样本分布不平衡的问题,提出了一种新的PSVM算法-BPSVM,根据训练样本数量的不平衡对正负样本集分别分配了不同的惩罚因子,并将原始优化问题的惩罚因子由数值变更为一个对角阵,最后推导出了线性和非线性BPSVM的决策函数,实验结果表明：BPSVM的性能优于PSVM与SVM方法相比效率更高.     

Difference intensity distance group pattern for recognizing actions in video using Support Vector Machines

Recognition of human actions is a very important, task in many applications such as Human Computer Interaction, Content based video retrieval and indexing, Intelligent video surveillance, Gesture Recognition, Robot learning and control, etc. An efficient action recognition system using Difference Intensity Distance Group Pattern (DIDGP) method and recognition using Support Vector Machines (SVM) classifier is presented. Initially, Region of Interest (ROI) is extracted from the difference frame, where it represents the motion information. The extracted ROI is divided into two blocks B1 and B2. The proposed DIDGP feature is applied on the maximum intensity block of the ROI to discriminate the each action from video sequences. The feature vectors obtained from the DIDGP are recognized using SVM with polynomial and RBF kernel. The proposed work has been evaluated on KTH action dataset which consists of actions like walking, running, jogging, hand waving, clapping and boxing. The proposed method has been experimentally tested on KTH dataset and an overall accuracy of 94.67% for RBF kernel.     

CONFIDANT: Collaborative Object Notification Framework for Insider Defense using Autonomous Network Transactions

File Integrity Analyzers serve as a component of an Intrusion Detection environment by performing filesystem inspections to verify the content of security-critical files in order to detect suspicious modification. Existing file integrity frameworks exhibit single point-of-failure exposures. The Collaborative Object Notification Framework for Insider Defense using Autonomous Network Transactions (CONFIDANT) framework aims at fail-safe and trusted detection of unauthorized modifications to executable, data, and configuration files. In this paper, an IDS architecture taxonomy is proposed to classify and compare CONFIDANT with existing frameworks. The CONFIDANT file integrity verification framework is then defined and evaluated. CONFIDANT utilizes three echelons of agent interaction and four autonomous behaviors. Sensor agents in the lowest echelon comprise the sensor level to generate an assured report to companion agents of computed MD5 file digests. At the control level, beacon agents verify file integrity based on the digests from sensor-level agents assembled over time. Upper echelon transactions occur at the response level. Here watchdog behavior agents dispatch probe agents to implement the alarm signaling protocol. CONFIDANT has been implemented in the Concordia agent environment to evaluate and refine its agent behaviors. Evaluation shows that CONFIDANT mitigates single point-of-failure exposures that are present in existing frameworks. Supported in-part by National Security Agency subcontract MDA904-99-C-2642     

一种稀疏波长转换光网络中的波长分配算法

研究了具有波长转换功能的WDM光网络的分类以及已有的几种波长分配算法，分析了波长分配算法的一般流程。文中以波长变换次数最少做为所提出的波长分配算法的主要优化目标，根据WDM光网络中的节点是否具有波长转换的功能，结合等价光路由替换的思想，提出了在稀疏有限波长转换光网络中的一种启发式的波长分配算法。仿真实验表明，当光网络中的连接请求量较大时，该算法的阻塞率低于已有的一些波长分配算法，连接能力有了较大提高。     

一种模拟电路的支持向量机故障诊断方法

系统地提出了模拟电路的最小二乘小波支持向量机故障诊断方法。从测试点得到各种故障状态下的输出电压信号，对输出电压信号进行小波去噪，对信号进行小波分解获取多尺度的低频系数和高频系数，并对小波系数进行处理从而提取出故障特征量，以此作为学习样本来训练最小二乘小波支持向量机，确定其模拟电路故障诊断的模型。雷达系统电路仿真结果表明了模拟电路的小波变换和最小二乘小波支持向量机故障诊断方法取得了较好的效果。     

Autonomous real-time landing site selection for Venus and Titan using Evolutionary Fuzzy Cognitive Maps

Future science-driven landing missions, conceived to collect in situ data on regions of planetary bodies that have the highest potential to yield important scientific discoveries, will require a higher degree of autonomy. The latter includes the ability of the spacecraft to autonomously select the landing site using real-time data acquired during the descent phase. This paper presents the development of an Evolutionary Fuzzy Cognitive Map (E-FCM) model that implements an artificial intelligence system capable of autonomously selecting a landing site with the highest potential for scientific discoveries constrained by the requirement of soft landing in a region with safe terrains. The proposed E-FCM evolves its internal states and interconnections as a function of real-time data collected during the descent phase, therefore improving the decision process as more accurate information becomes available. The E-FCM is constructed using knowledge accumulated by planetary experts and it is tested on scenarios that simulate the decision process during the descent phase toward the Hyndla Regio on Venus. The E-FCM is shown to quickly reach conclusions that are consistent with what would be the choice of a planetary expert if the scientist were presented with the same information. The proposed methodology is fast and efficient and may be suitable for on-board spacecraft implementation and real-time decision making during the course of robotic exploration of the Solar System.     

Autonomous weld seam identification and localisation using eye-in-hand stereo vision for robotic arc welding

One of the main difficulties in using robotic welding in low to medium volume manufacturing or repair work is the time taken to programme the robot to weld a new part. It is often cheaper and more efficient to weld the parts manually. This paper presents a method for the automatic identification and location of welding seams for robotic welding using computer vision. The use of computer vision in welding faces some difficult challenges such as poor contrast, textureless images, reflections and imperfections on the surface of the steel such as scratches. The methods developed in the paper enables the robust identification of narrow weld seams for ferrous materials combined with reliable image matching and triangulation through the use of 2D homography. The proposed algorithms are validated through experiments using an industrial welding robot in a workshop environment. The results show that this method can provide a 3D Cartesian accuracy of within ±1 mm which is acceptable in most robotic arc welding applications.     

Enhancement of Self-adaptive real-coded genetic algorithm using Taguchi method for Economic dispatch problem

In this paper, a new optimization algorithm, namely Taguchi self-adaptive real-coded genetic algorithm (TSARGA) is proposed and implemented to solve economic dispatch (ED) problem with valve-point loading. The TSARGA combines the self-adaptive real-coded genetic algorithm with Taguchi method which can exploit the potential offspring. The self-adaptation is achieved by means of simulated binary crossover (SBX). Moreover, powerful exploration capability is achieved through tournament selection by creating tournaments between two solutions. The better solution is chosen and placed in the mating pool leading to better convergence and reduced computational burden. The systematic reasoning ability of the Taguchi method is incorporated after SBX operations to select the potential genes to achieve polynomial mutation, and consequently, enhance the robustness of the solution. The proposed TSARGA is effectively applied to solve the ED problem with valve-point loading with 6, 13 and 40-generator systems. The proposed method yields solutions towards global optimum and it compares far better with other methods in terms of solution quality, handling constraints and computation time.     

Framework for Autonomous On-board Navigation with the AR.Drone

We present a framework for autonomous flying using the AR.Drone low cost quadrotor. The system performs all sensing and computations on-board, making the system independent of any base station or remote control. High level navigation, computer vision and control tasks are carried out in an external processing unit that steers the vehicle to a desired location. We experimentally demonstrate the properties and capabilities of three systems to autonomously following several trajectory patterns, visually estimate its position and detecting and following a person and evaluate the performance of the systems.     

基于周期时间限制的多机器人自主委托协作模型

提出一种基于周期时间限制的多机器人自主委托协作模型,目的是解决传统算法在任务撤销、失效限 制方面的欠缺,并在灵活性和可控性之间寻求平衡．它可以有效地对委派任务的机器人进行控制,但又不会因为执 行过于严格的委托约束而造成策略定义和模型构造方面的困难．该多机器人协作模型解决了现有多机器人分工协作 模型中对时间限制缺少支持的问题,并给出了一个支持临时性限制、时序依赖限制和传播限制的委托协作模型．使 用周期时间、使用次数、有效期限来控制临时协同,用推导规则来控制协作间的时序依赖,用委托深度来限制委托 权限的传播．给出了模型的形式化描述．     

Multiclass Support Vector Machines for Classification of ECG Data with Missing Values

The article presents an experimental study on multiclass Support Vector Machine (SVM) methods over a cardiac arrhythmia dataset that has missing attribute values for electrocardiogram (ECG) diagnostic application. The presence of an incomplete dataset and high data dimensionality can affect the performance of classifiers. Imputation of missing data and discriminant analysis are commonly used as preprocessing techniques in such large datasets. The article proposes experiments to evaluate performance of One-Against-All (OAA) and One-Against-One (OAO) approaches in kernel multiclass SVM for a heartbeat classification problem with imputation and dimension reduction techniques. The results indicate that the OAA approach has superiority over OAO in multiclass SVM for ECG data analysis with missing values.     

Certified Reduced Basis Methods for Parametrized Elliptic Optimal Control Problems with Distributed Controls

In this paper, we consider the efficient and reliable solution of distributed optimal control problems governed by parametrized elliptic partial differential equations. The reduced basis method is used as a low-dimensional surrogate model to solve the optimal control problem. To this end, we introduce reduced basis spaces not only for the state and adjoint variable but also for the distributed control variable. We also propose two different error estimation procedures that provide rigorous bounds for the error in the optimal control and the associated cost functional. The reduced basis optimal control problem and associated a posteriori error bounds can be efficiently evaluated in an offline–online computational procedure, thus making our approach relevant in the many-query or real-time context. We compare our bounds with a previously proposed bound based on the Banach–Ne?as–Babu?ka theory and present numerical results for two model problems: a Graetz flow problem and a heat transfer problem. Finally, we also apply and test the performance of our newly proposed bound on a hyperthermia treatment planning problem.     

时变时滞极点配置最优预报自校正PID控制器

对于时变时滞过程．本文论述了一种新的极点配置最优预报自校正ＰＩＤ控制器．仿真实例说明了本文结果的有效性。     

一种增益可调的极点配置自校正调节器的显式和隐式算法

本文提出一种新颖的极点配置自校正调节器算法。在配置闭环极点的同时,对调节器的高频增益加以限制,以减弱控制信号的高频振荡。文中给出了显式和隐式算法。算法简单、直观、易于实现。计算机仿真结果表明,采用本文提出的算法,控制信号的方差明显降低。     

Multilayer Minimum Projection Method with Singular Point Assignment for Nonsmooth Control Lyapunov Function Design

Control Lyapunov function (CLF) design on a manifold is a difficult problem in control theory. To address this problem, we have proposed the multilayer minimum projection method. The method requires CLFs on different manifolds from the manifold where the control problem is defined. In this paper, we relax the requirement by desingularization of the functions on the manifolds. The paper focuses on the problem of desingularization in the multilayer minimum projection method. We show that the functions on other manifolds need not be CLFs by consideration of desingularization. Moreover, we propose a CLF design method by singular point assignment based on the advantage of desingularization. The method enables us to merge local CLFs into the global CLF. This paper proposes two CLF design methods: desingularization and singular point assignment. A CLF design example is provided for each method; the advantages of the proposed methods are confirmed by those two examples.