基于PowerBuilder的WEB开发与应用

本文阐述了PowerBuiler的WEB应用原理．并结合实例论述了利用PowerBuiler开发WEB应用的过程。     

基于IEEE1641标准的自动测试系统体系结构

基于IEEE 1641标准的自动测试系统体系结构代表了自动测试系统软件的最新发展,建立符合IEEE1641标准的自动测试系统大大提高了软件的可移植性和仪器互换性;在分析ATLAS标准的基础上,提出了按照ATLAS的替代标准IEEE1641组建自动测试系统的必要性和优越性;介绍了IEEE1641标准的层次结构以及符合标准的ATS体系结构,尤其是基本信号组件BSC和测试信号框架TSF在基于信号面向UUT的自动测试系统的实现方法;通过实例说明了基于IEEE1641标准构建基于信号、面向UUT的自动测试系统的实现方案。     

低功耗数字控制超长波发射与接收系统

针对管道、矿山和水下等特殊环境中的信息通讯与信号传输等问题,根据超长波(ELF Electromagnetic Wave)具有传播损耗小且相位稳定等特点,给出了超长波发射与接收系统的设计原理与实现过程.发射系统采用单片机控制,输出的信号经发射天线产生23 Hz超长波,接收系统对采集到的信号进行带通滤波及放大处理.工程实验表明,所设计的系统在锂电池供电状态下,具有发射功耗低(连续工作时间大于72 h)、发射功率大(传播距离大于10 m)、且对接收的信号处理快速可靠(动态时滞小于5 s)等优点.     

Reliable and Energy-Efficient Routing for Static Wireless Ad Hoc Networks with Unreliable Links

Energy efficient routing and power control techniques in wireless ad hoc networks have drawn considerable research interests recently. In this paper, we address the problem of energy efficient reliable routing for wireless ad hoc networks in the presence of unreliable communication links or devices or lossy wireless link layers by integrating the power control techniques into the energy efficient routing. We consider both the case when the link layer implements a perfect reliability and the case when the reliability is implemented through the transport layer, e.g., TCP. We study the energy efficient unicast and multicast when the links are unreliable. Subsequently, we study how to perform power control (thus, controlling the reliability of each communication link) such that the unicast routings use the least power when the communication links are unreliable, while the power used by multicast is close to optimum. Extensive simulations have been conducted to study the power consumption, the end-to-end delay, and the network throughput of our proposed protocols compared with existing protocols.     

Soft sensing modelling based on optimal selection of secondary variables and its application

The composition of the distillation column is a very important quality value in refineries, unfortunately, few hardware sensors are available on-line to measure the distillation compositions. In this paper, a novel method using sensitivity matrix analysis and kernel ridge regression （KRR） to implement on-line soft sensing of distillation compositions is proposed. In this approach, the sensitivity matrix analysis is presented to select the most suitable secondary variables to be used as the soft sensor＇s input. The KRR is used to build the composition soft sensor. Application to a simulated distillation column demonstrates the effectiveness of the method.     

A data collection protocol for real-time sensor applications

The nature of many sensor applications as well as continuously changing sensor data often imposes real-time requirements on wireless sensor network protocols. Due to numerous design constraints, such as limited bandwidth, memory and energy of sensor platforms, and packet collisions that can potentially lead to an unbounded number of retransmissions, timeliness techniques designed for real-time systems and real-time databases cannot be applied directly to wireless sensor networks. Our objective is to design a protocol for sensor applications that require periodic collection of raw data reports from the entire network in a timely manner. We formulate the problem as a graph coloring problem. We then present TIGRA (Timely Sensor Data Collection using Distributed Graph Coloring) — a distributed heuristic for graph coloring that takes into account application semantics and special characteristics of sensor networks. TIGRA ensures that no interference occurs and spatial channel reuse is maximized by assigning a specific time slot for each node. Although the end-to-end delay incurred by sensor data collection largely depends on a specific topology, platform, and application, TIGRA provides a transmission schedule that guarantees a deterministic delay on sensor data collection.     

REDFLAG: A Run-timE, Distributed, Flexible, Lightweight, And Generic fault detection service for data-driven wireless sensor applications

Increased interest in wireless sensor networks by scientists and engineers is forcing wireless sensor networking research to focus on application requirements. Data is available as never before in many fields of study; practitioners are now burdened with the challenge of doing data-rich research rather than being data-starved. However, in situ sensors can be prone to errors, links between nodes are often unreliable, and nodes may become unresponsive in harsh environments, leaving to researchers the onerous task of deciphering often anomalous data. Presented here is the REDFLAG fault detection service for wireless sensor applications, a Run-timE, Distributed, Flexible, detector of faults, that is also Lightweight And Generic. REDFLAG addresses the two most worrisome issues in data-driven wireless sensor applications: abnormal data and missing data. REDFLAG exposes faults as they occur by using distributed algorithms in order to conserve energy. Simulation results show that REDFLAG is lightweight both in terms of footprint and required power resources while ensuring satisfactory detection and diagnosis accuracy. Being unrestrictive, REDFLAG is generically available to a myriad of applications and scenarios. As a matter of fact, REDFLAG has been applied into a subsurface contaminant transport model to improve the model performance in the presence of erroneous sensor data.     

Dynamic file grouping for load balancing in streaming media clustered server systems

A dynamic file grouping strategy is presented to address the load balancing problem in streaming media clustered server systems. This strategy increases the server cluster availability by balancing the workloads among the servers within a cluster. Additionally, it improves the access hit ratio of cached files in delivery servers to alleviate the limitation of I/O bandwidth of storage node. First, the load balancing problem is formulated as a two layers semi-Markov switching state-space control process. This analytic model captures the behaviors of streaming media clustered server systems accurately, and is with constructional flexibility and scalability. Then, a policy iteration based reinforcement learning algorithm is proposed to optimize the file grouping policy online. By utilizing the features of the event-driven policy, the proposed optimization algorithm is adaptive and with less computational cost. Simulation results demonstrate the effectiveness of the proposed approach. Recommended by Editor Hyun Seok Yang. This work was supported by the National Natural Science Foundation of China under grant Nos. 60774038, 60574065, National 863 HI-TECH Research & Development Plan of China under grant Nos. 2006AA01Z114, 2008AA01A317, Natural Science Foundation of Anhui Province under grant No. 070412063, Graduate Student Innovation Foundation of USTC under grant No. KD2006036, and Science Research Development Foundation of HFUT under grant No. GDBJ2008-045. Qi Jiang received the B.S. degree in Industrial Electrical Automation from Southeast University in 1989 and the Ph.D. degree in Control Science and Engineering from University of Science and Technology of China in 2008. He is currently a Post-doc in USTC. His research interests include optimization and control of stochastic dynamic systems, and performance analysis and optimization of network communication systems. Hong-Sheng Xi received the M.S. degree in Applied Mathematics from University of Science and Technology of China in 1977. He is currently a Professor in Department of Automation, USTC. His research interests include discrete event dynamic systems, performance analysis and optimization of network communication systems, robust control, and network security. Bao-Qun Yin received the B.S. degree in Mathematics from Sichuan University in 1985, the M.S. degree in Applied Mathematics and the Ph.D. degree in Pattern Recognition and Intelligent Systems from University of Science and Technology of China in 1993 and 1998, respectively. He is currently a Professor in Department of Automation, USTC. His research interests include discrete event dynamic systems, and Markov decision processes.     

抗量子计算公钥密码需求分析与技术路线

本文对国外量子计算机研究进展情况进行了分析,并针对量子计算机对于信息安全的挑战,讨论了国内下一代公钥密码技术的需求、发展思路和技术路线。     

地铁广告的文化性传承——浅析地铁广告中公益广告的投放

本文通过对地铁广告的含义、环境特征、受众结构等方面进行分析,阐述了公益广告在地铁广告中相对"沉默"的现状;通过对公益广告的社会功能和文化价值的分析,结合地铁广告的文化传承性,更好地协调公益广告-受众-环境和社会之间的关系,从而提出建议来促进公益广告的投放、发展规划;形成受众接受度高的广告形式,实现"艺术性"和"功能性"的统一。