Design and implementation of light-weight mobile multicast for fast MIPv6

Mobile multicast is a research hotspot and can provide many applications. Some mobile multicast schemes have been proposed, but most of them introduce new entities and study construction algorithms of the dynamic multicast delivery structure which is heavyweight for wireless devices. In this paper, we propose a light-weight mobile multicast (LMM) scheme for Fast Mobile IPv6 which reduces the redundant operational overhead by simplifying multicast listener discovery (MLD) proxying. The LMM scheme implements simplified MLD proxying function on home agent to reduce the complicated multicast routing protocol and modifies MLD host part function on mobile node to reduce the multicast membership messages interaction. In order to solve the tunnel convergence problem, LMM also introduces a multicast tunnel combination and reconstruction algorithm. We set up a test-bed to evaluate the performance of LMM, and compare it with other mobile multicast schemes. The experimental results show that LMM reduces the multicast disruption time at handover. Based on the experimental results, we analyze the cost of LMM, and the results show that it has lower protocol cost than other schemes.     

Combined MCDM techniques for exploring stock selection based on Gordon model

Basing on the Gordon model perspective and applying multiple criteria decision making (MCDM), this research explores the influential factors and relative weight of dividend, discount rate, and dividend growth rate. The purpose is to establish an investment decision model and provides investors with a reference/selection of stocks most suitable for investing effects to achieve the greatest returns. Taking full consideration of the interrelation effect among variables of the decision model, this paper introduced analytical network process (ANP) and examined leading electronics companies spanning the hottest sectors of lens, solar, and handset by experts. Empirical findings indicated that dividend was affected by industry outlook, earnings, operating cash flow, and dividend payout rate; discount rate was affected by market β and risk-free rate; and dividend growth rate was affected by earnings growth rate and dividend payout growth rate. Also, according to literatures, discount rate possessed a self-effect relationship. Among the eight evaluation criteria, market β was the most important factor influencing investment decisions, followed by dividend growth rate and risk-free rate. In stock evaluations, leadership companies in the solar industry outperformed those in handset and lens, becoming investors’ favorite stock group at the time that this research was conducted.     

冷床区钢坯自动跟踪系统关键技术的研发

安钢中板厂的炉号跟踪系统中,冷金属检测器CMD用来检测冷床区钢坯的运动,但是CMD只能检测出辊道上是否有钢坯经过,而不能判断钢坯在冷床区具体上到哪个冷床,因此,目前冷床部分的钢坯跟踪是靠人工手动完成的.针对该问题,提出一种新的运用数字图像处理技术完成冷床区钢坯自动跟踪的方法.该方法利用运动目标检测方法检测出辊道上有钢坯运动,然后经过最佳阈值分割、改进的区域生长算法、质心标记、数据库程序等步骤完成钢坯运动轨迹的标记,实现自动跟踪.     

基于群决策的多Agent资源管理模型

在大部分系统中,资源都是有限供给的.因此,为了提高系统的性能,保证资源使用的效率与公平,必须对资源进行有效的管理.而合理分配资源和解决资源使用冲突是系统资源管理的核心问题.基于群决策方法提出了一个多Agent资源管理模型,以动态优先级的方式灵活地解决了系统资源分配与使用冲突问题.     

Controllability of heterogeneous multi-agent systems under directed and weighted topology

This paper considers the controllability problem for both continuous- and discrete-time linear heterogeneous multi-agent systems with directed and weighted communication topology. First, two kinds of neighbour-based control protocols based on the distributed protocol of first-order and second-order multi-agent systems are proposed, under which it is shown that a heterogeneous multi-agent system is controllable if the underlying communication topology is controllable. Then, under special leader selection, the result shows that the controllability of a heterogeneous multi-agent system is solely decided by its communication topology graph. Furthermore, some necessary and/or sufficient conditions are derived for controllability of communication topology from algebraic and graphical perspectives. Finally, simulation examples are presented to demonstrate the effectiveness of the theoretical results.     

Optimal replacement policy for a two-dissimilar-component cold standby system with different repair actions

In this paper, a cold standby repairable system consisting of two dissimilar components and one repairman is studied. When failures occur, the repair of both component 1 and component 2 are not ‘as good as new’. The consecutive operating times of component 1 after repair constitute a decreasing geometric process, while the repair times of component 1 are independent and identically distributed. For component 2, its failure is rectified by minimal repair, and the repair time is negligible. Component 1 has priority in use when both components are good. The replacement policy N is based on the failure number of component 1. Under policy N, we derive the explicit expression of the long-run average cost rate C(N) as well as the average number of repairs of component 2 before the system replaced. The optimal replacement policy N*, which minimises the long-run average cost rate C(N), is obtained theoretically. If the failure rate r(t) of component 2 is increasing, the existence and uniqueness of the optimal policy N* is also proved. Finally, a numerical example is given to validate the developed theoretical model. Some sensitivity analyses are provided to show the influence of some parameters, such as the costs for replacement and repair, and the parameters of the lifetime and repair time distributions of both components, to the optimal replacement policy N* and corresponding average cost rate C(N*).     

Modeling of the hot metal silicon content in blast furnace using support vector machine optimized by an improved particle swarm optimizer

As a highly complex multi-input and multi-output system, blast furnace plays an important role in industrial development. Although much research has been done in the past few decades, there still exist many problems to be solved, such as the modeling problem. This paper adopts support vector regression (SVR) to construct the prediction model of blast furnace silicon content. To ensure a good generalization performance for the given datasets, it is important to select proper parameters for SVR. In view of this problem, a new particle swarm optimizer called DMS-PSO-CLS is presented to optimize the parameters of SVR. In DMS-PSO-CLS, a new cooperative learning strategy is hybridized with DMS-PSO, which makes particle information be used more effectively for generating better-quality solutions. DMS-PSO-CLS takes merits of the DMS-PSO and the cooperative learning strategy so that both the convergence speed and the convergence precision can be improved. Experimental results show that DMS-PSO-CLS can find the optimal parameters of SVR with high speed and the SVR model optimized by DMS-PSO-CLS can achieve a good regression precision on the predictive problem of blast furnace.     

On the tag localization of web video

Nowadays, numerous social videos have pervaded on the web. Social web videos are characterized with the accompanying rich contextual information which describe the content of videos and thus greatly facilitate video search and browsing. Generally, those contextual data such as tags are provided at the whole video level, without temporal indication of when they actually appear in the video, let alone the spatial annotation of object related tags in the video frames. However, many tags only describe parts of the video content. Therefore, tag localization, the process of assigning tags to the underlying relevant video segments or frames even regions in frames is gaining increasing research interests and a benchmark dataset for the fair evaluation of tag localization algorithms is highly desirable. In this paper, we describe and release a dataset called DUT-WEBV, which contains about 4,000 videos collected from YouTube portal by issuing 50 concepts as queries. These concepts cover a wide range of semantic aspects including scenes like “mountain”, events like “flood”, objects like “cows”, sites like “gas station”, and activities like “handshaking”, offering great challenges to the tag (i.e., concept) localization task. For each video of a tag, we carefully annotate the time durations when the tag appears in the video and also label the spatial location of object with mask in frames for object related tag. Besides the video itself, the contextual information, such as thumbnail images, titles, and YouTube categories, is also provided. Together with this benchmark dataset, we present a baseline for tag localization using multiple instance learning approach. Finally, we discuss some open research issues for tag localization in web videos.     

Joint design of clustering and in-cluster data route for heterogeneous wireless sensor networks

A heterogeneous wireless sensor network comprises a number of inexpensive energy constrained wireless sensor nodes which collect data from the sensing environment and transmit them toward the improved cluster head in a coordinated way. Employing clustering techniques in such networks can achieve balanced energy consumption of member nodes and prolong the network lifetimes. In classical clustering techniques, clustering and in-cluster data routes are usually separated into independent operations. Although separate considerations of these two issues simplify the system design, it is often the non-optimal lifetime expectancy for wireless sensor networks. This paper proposes an integral framework that integrates these two correlated items in an interactive entirety. For that, we develop the clustering problems using nonlinear programming. Evolution process of clustering is provided in simulations. Results show that our joint-design proposal reaches the near optimal match between member nodes and cluster heads.     

Flocking of multi‐agent nonholonomic systems with unknown leader dynamics and relative measurements

In this paper, we consider the distributed flocking control problem of multi‐agent nonholonomic systems with a virtual leader whose dynamics is unknown; state information is time varying and not available to all agents under both fixed and switching topologies. On the basis of the relative velocity and orientation information of neighboring agents, two distributed discontinuous control protocols are designed for fixed and switching topologies, respectively. By using tools from algebraic graph theory and nonsmooth analysis, the proposed distributed discontinuous control protocols guarantee that the velocities and orientations of the agents exponentially converge to the velocity and orientation of the virtual leader, respectively, while ensuring collision avoidance of the whole group, if the interaction graph among agents is undirected and the virtual leader with bounded time‐varying velocity has directed paths to other agents. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2017 John Wiley & Sons, Ltd.