Forced consensus in networks of double integrator systems with delayed input

This communique presents forced second-order consensus protocols with communication time-delays for the network of agents with double integrator dynamics and gives a measure of the robustness of the protocols to the communication time-delays. By employing a frequency domain method, it is proven that the forced consensus is achieved asymptotically for appropriate time-delay if the network is connected. Particularly, the maximum fixed time-delay that can be tolerated by the network is found. The forced consensus protocols are distributed in the sense that each agent only needs information from its neighboring agents, which reduces the complexity of connections between agents significantly. Numerical simulation results are provided to demonstrate the effectiveness and the sharpness of the theoretical results.     

移动通讯及动态Web在原油计量中的应用

针对传统人工抄表计量方式存在的不足,利用先进的移动通讯技术和动态Web技术研制开发了新一代油田计量站原油分站计量系统,实现了计量数据的自动采集、无线远程传输和网络发布共享。     

Knowledge search and people with high epistemic curiosity

Porter sites have tried to increase their business potentials by helping users easily engage in diverse online activities such as search, entertainment, online communities, and others. Knowledge search engine is one of the most successful killer applications increasing user loyalty. However, most studies have independently focused on search engine technology such as search keyword algorithm, presentation of information and user characteristics such as cognitive style, search experiences, and skill levels. However, these previous studies lack an integrated understanding of causal links among critical factors predicting user motives and intention involving more situation-specific user characteristics. To fill these gaps in the literature, the present study focuses on whether knowledge characteristics such as specialization, preciseness, and diversity, and system characteristics such as interactivity, responsiveness, and communication richness are important in forming user motives and intention. The present study also identifies a moderating role of epistemic curiosity in the links between motives and intention. Two hundred and fifty-five data from Korean university students confirmed that knowledge and services characteristics such as specialty, preciseness, diversity, communication richness improve user motives, which have a positive impact on intention. Epistemic curiosity has a moderating effect on the links between motives and intention. Theoretical and practical implications are discussed in conclusion.     

网络工程专业通信类课程设置

网络工程专业与通信工程专业的课程体系既有共同点也有明显的区别。网络工程专业的通信类专业课程主要来源于通信工程专业的有关课程。如何根据网络工程专业的培养目标来进行取舍,是一个值得探讨的问题。本文在对网络工程专业和通信工程专业特点进行对比分析的基础上,给出网络工程专业开设通信类系列课程的建议。     

面向自动抄表系统的智能消息语言

针对传统自动抄表系统存在的多种计量设备相互通信困难的问题,提出了一种面向自动化抄表系统的智能消息语言(SML).分别阐述了SML的基本概念、结构及其在网络结构中的定位,分析了SML语言标准中的消息簇组成格式、封装和编码方式等.最后,结合电力抄表系统的应用实例,给出了SML语言在电力自动抄表系统中的各种数据传输格式.通过...     

配用电通信平台实现技术及应用

针对配用电领域的接入层通信特点,提出了融合多种通信方式的配用电通信平台实现技术.分析了通信接入平台的功能模型,实现不同通信类型终端的统一接入与管理.实践证明,采用该技术可灵活组建和部署通信接入方式,从而满足了配用电自动化系统的各种业务综合接入需求.     

FlexRay车载网络管理数据调度的研究

为确保汽车通信构架FlexRay的高效实时运行,需要尽可能地简化网络结构设计、降低通信复杂程度,良好的车载网络管理能够实现这些功能.简述了FlexRay通信协议和数据帧结构,在对比两种网络管理机制之后,提出了一种基于新规范的FlexRay网络管理方法.以其基本规范为依据,对网络管理数据的调度进行了分类,设计了数据的动态...     

On-demand minimum cost benchmarking for intermediate dataset storage in scientific cloud workflow systems

Many scientific workflows are data intensive: large volumes of intermediate datasets are generated during their execution. Some valuable intermediate datasets need to be stored for sharing or reuse. Traditionally, they are selectively stored according to the system storage capacity, determined manually. As doing science on clouds has become popular nowadays, more intermediate datasets in scientific cloud workflows can be stored by different storage strategies based on a pay-as-you-go model. In this paper, we build an intermediate data dependency graph (IDG) from the data provenances in scientific workflows. With the IDG, deleted intermediate datasets can be regenerated, and as such we develop a novel algorithm that can find a minimum cost storage strategy for the intermediate datasets in scientific cloud workflow systems. The strategy achieves the best trade-off of computation cost and storage cost by automatically storing the most appropriate intermediate datasets in the cloud storage. This strategy can be utilised on demand as a minimum cost benchmark for all other intermediate dataset storage strategies in the cloud. We utilise Amazon clouds’ cost model and apply the algorithm to general random as well as specific astrophysics pulsar searching scientific workflows for evaluation. The results show that benchmarking effectively demonstrates the cost effectiveness over other representative storage strategies.