突发事件中网络舆论的情报引导模式

随着信息化的日益普及,网络舆论已成为公众表达民情民意、讨论公共事务、进行舆论监督的一个开放的公共平台。突发事件发生后,该事件一旦成为互联网上的热门话题,往往能够在短时间内形成巨大的网络舆论场,吸引为数众多的网络受众参与其中。这些网络舆论一旦达到一定的传播强度,就可能转化为实际生活中的社会舆论,在整个社会范围中产生巨大影响。因此,有必要研究和讨论突发事件中的网络舆论引导问题,作者就是想把情报的概念引入到对突发事件中网络舆论的引导上,并建立起相应的情报引导模式,通过这一模式,可以实现对突发事件网络舆论的合理引导。     

MicroPort: A general simulation platform for seaport container terminals

Seaport container terminals are essential nodes in sea cargo transportation networks. As such, the operational efficiency of container terminals in handling containers passing through them plays a critical role in a globalized world economy. Many models and algorithms have been developed to address various decision problems in container terminals to help improve operational efficiency. These decision support tools are usually used separately for specific purposes. However, the problems they are trying to tackle are often interrelated. Therefore, in this regard, an evaluation tool which can capture as many operational conditions as possible for different decision problems is necessary. This paper introduces a general simulation platform, named MicroPort, which aims to provide an integrated and flexible modeling system for evaluating the operational capability and efficiency of different designs of seaport container terminals. The software structure of MicroPort comprises three programming layers: (1) the Functions layer; (2) the Applications layer; and (3) the Extensions layer. Different layers are bound by Application Programming Interfaces (APIs). Basic functions built in the Functions layer support the Applications layer in which major operation processes can be modeled by an agent-based method. External modules and decision support tools in the Extensions layer then use APIs to adjust the system to produce suitable simulation models for specific purposes.     

Efficient removal of boundary-divergence errors in time-splitting methods

A normal mode analysis is presented and numerical tests are performed to assess the effectiveness of a new time-splitting algorithm proposed recently in Karniadakiset al. (1990) for solving the incompressible Navier-Stokes equations. This new algorithm employs high-order explicit pressure boundary conditions and mixed explicit/implicit stiffly stable time-integration schemes, which can lead to arbitrarily high-order accuracy in time. In the current article we investigate both the time accuracy of the new scheme as well as the corresponding reduction in boundary-divergence errors for two model flow problems involving solid boundaries. The main finding is that time discretization errors, induced by the nondivergent splitting mode, scale with the order of the accuracy of the integration rule employed if a proper rotational form of the pressure boundary condition is used; otherwise a first-order accuracy in time similar to the classical splitting methods is achieved. In the former case the corresponding errors in divergence can be completely eliminated, while in the latter case they scale asO(vt)_1/2.     

职业教育计算机课新型教学模式与实训方法应用研究

随着时代的发展,信息化进程的加快,计算机在人们的日常生活中起到越来越重要的作用,因此,计算机教学也随之引起了人们的关注。计算机教学呼唤改变传统的教学模式,倡导灵活多元的教学模式。本文根据教学实践,从教学模式与实训方法应用做出分析与探讨。     

预测帧编码中基于场景信息的宏块模式跳过算法*

在对场景信息进行分析的基础上,提出了H.264/AVC中预测帧的一种快速算法.对于未发生场景切换的预测帧,采用INTRA模式跳过算法(IMSA),跳过该帧中所有的INTRA模式的决策过程.对于发生场景切换的预测帧,跳过INTER模式的决策过程(PMSA).仿真结果显示,与采用完整的率失真优化(RDO)决策过程相比,未发生场景切换时,所提方法能减少30%～60%的编码时间;发生场景切换时,能减少60%～70%的编码时间,并且未导致明显的图像质量下降和码率的增加.     

冲击荷载作用下热处理花岗岩动态力学特性研究

为研究冲击速度和热处理温度对黑云母花岗岩动态力学特性的影响,利用改进的霍普金森压杆系统对25~800 ℃共9个温度等级的热处理试样分别进行3种弹速下的冲击压缩试验。试验结果表明：随着冲击速度的增加,25~700 ℃热处理试样的应力—应变曲线由“Ⅱ型”转变为“Ⅰ型”,而800 ℃热处理试样均表现出“Ⅰ型”应力—应变曲线特征。同一温度热处理下试块的峰值应力、应变和平均应变均随动荷载的升高而增大。相同的冲击速度下,300 ℃热处理试样的动力学性能有所改善,500 ℃后试样的动力学性能开始逐渐劣化。同一温度热处理试样的破碎程度随冲击速度的增加而增加;相同冲击速度下,热处理试样的破碎程度随温度的升高先减弱后增强。     

Finite-time coordination in multiagent systems using sliding mode control approach

Finite-time stability in dynamical systems theory involves systems whose trajectories converge to an equilibrium state in finite time. In this paper, we use the notion of finite-time stability to apply it to the problem of coordinated motion in multiagent systems. Specifically, we consider a group of agents described by fully actuated Euler–Lagrange dynamics along with a leader agent with an objective to reach and maintain a desired formation characterized by steady-state distances between the neighboring agents in finite time. We use graph theoretic notions to characterize communication topology in the network determined by the information flow directions and captured by the graph Laplacian matrix. Furthermore, using sliding mode control approach, we design decentralized control inputs for individual agents that use only data from the neighboring agents which directly communicate their state information to the current agent in order to drive the current agent to the desired steady state. Sliding mode control is known to drive the system states to the sliding surface in finite time. The key feature of our approach is in the design of non-smooth sliding surfaces such that, while on the sliding surface, the error states converge to the origin in finite time, thus ensuring finite-time coordination among the agents in the network. In addition, we discuss the case of switching communication topologies in multiagent systems. Finally, we show the efficacy of our theoretical results using an example of a multiagent system involving planar double integrator agents.     

Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions

Epilepsy is a neurological disorder which is characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used signal for detection of epileptic seizures. This paper presents a new method for classification of ictal and seizure-free EEG signals. The proposed method is based on the empirical mode decomposition (EMD) and the second-order difference plot (SODP). The EMD method decomposes an EEG signal into a set of symmetric and band-limited signals termed as intrinsic mode functions (IMFs). The SODP of IMFs provides elliptical structure. The 95% confidence ellipse area measured from the SODP of IMFs has been used as a feature in order to discriminate seizure-free EEG signals from the epileptic seizure EEG signals. The feature space obtained from the ellipse area parameters of two IMFs has been used for classification of ictal and seizure-free EEG signals using the artificial neural network (ANN) classifier. It has been shown that the feature space formed using ellipse area parameters of first and second IMFs has given good classification performance. Experimental results on EEG database available by the University of Bonn, Germany, are included to illustrate the effectiveness of the proposed method.     

An analytical framework for integrated maritime terminal scheduling problems with time windows

Container transport, an integral part of intercontinental trade, has steadily increased over the past few decades. The productivity of such a system, in part, hinges on the efficient allocation of terminal resources such that the container transit time is minimized. This study provides an analytical framework, which entails efficient scheduling of quay and yard cranes, to minimize the time spent by containers at a terminal. A mixed-integer programming model is developed to capture the two-stage multi-processor characteristic of the problem, where each crane has specific time window availability. A genetic algorithm equipped with a novel decoding procedure is developed. The mixed-integer model is tested on a number of problem instances of varying sizes to gain managerial insights.