Priority-based target coverage in directional sensor networks using a genetic algorithm

Sensor networks have been applied in a wide variety of situations. Recently directional sensor networks consisting of directional sensors have gained attention. As for the traditional target coverage problem, the limited sensing angle of directional sensors makes it even more challenging. Moreover, individual targets may also be associated with differentiated priorities. Considering the distance between the directional sensors and targets influences sensing quality, this paper proposes the priority-based target coverage problem and strives to choose a minimum subset of directional sensors that can monitor all targets, satisfying their prescribed priorities. Due to the NP-Complete complexity, the minimum subset of directional sensors is approximated by using a genetic algorithm. Simulation results reveal the effects of multiple factors on the size of the resulting subset.     

DCS电源供电系统的可靠性定量分析

根据DCS电源系统的现状,对目前几种不同的电源设计方案进行可靠性定量分析.通过建立不同DCS电源系统可靠性框图并估算相关的可靠性指标,比较了不同方案下的平均无故障工作时间 (MTBF),给出了系统可靠性的分析结果和改进措施,定量分析了改进后的方案.结果表明电源系统的MTBF有了明显的改善.     

基于模式驱动和模糊查询的模式发现方法

在蛋白质序列的比对研究中,拥有相似模式的蛋白质常常具有相似的功能.通过已知的蛋白质序列模式可以很方便地对新蛋白质序列的功能结构进行研究和确认.蛋白质序列的发现已成为一个很有意义的题目.对基于模式驱动Pratt算法进行改进以提高其效率,在原来基础上引入模糊查询方法,能够更为快捷地从互不相关的蛋白质序列集合中找出最具代表性的蛋白质模式.     

A Hybrid Heat Rate Forecasting Model Using Optimized LSSVM Based on Improved GSA

Heat rate value is considered as one of the most important thermal economic indicators, which determines the economic, efficient and safe operation of steam turbine unit. At the same time, an accurate heat rate forecasting is core task in the optimal operation of steam turbine unit. Recently, least squares support vector machine (LSSVM) is being proved an effective machine learning technique for solving nonlinear regression problem with a small sample set. However, it has also been proved that the prediction precision of LSSVM is highly dependent on its parameters, which are hardly choosing for the LSSVM. In the paper, an improved gravitational search algorithm (AC-GSA) is presented to further enhance optimal performance of GSA, and it is employed to serve as an approach for pre-selecting LSSVM parameters. Then, a novel soft computing method, based on LSSVM and AC-GSA, is therefore proposed to forecast heat rate of a 600 MW supercritical steam turbine unit. It combines the merits of the high accuracy of LSSVM and the fast convergence of GSA in order to build heat rate prediction model and obtain a well-generalized model. Results indicate that the developed AC-GSA–LSSVM model demonstrates better regression precision and generalization capability.     

Mean square detectability of LTI systems over finite-state digital block-fading channels

This paper studies the mean square quadratic (MSQ) detectability for multi-output networked systems over finite-state digital block-fading channels. The packet-loss rate of each digital fading channel depends on the channel power gain, as well as packet length and power level used for transmission. A finite-state random process is introduced to model time-varying fading channels, which characterizes various configurations of physical communication environment and/or different channel fading amplitudes. Necessary and sufficient conditions for MSQ detectability over finite-state Markov digital block-fading channels are given in the form of algebraic Riccati equations or linear matrix inequalities (LMIs). The estimation gain is given as a function of estimated/observed channel state. In addition, explicit conditions on network for MSQ detectability over finite-state independent identically distributed (i.i.d.) digital block-fading channels are presented in terms of the unstable poles of the multi-output plant. Finally, an application to Gilbert-Elliott channels (GECs) is provided to demonstrate the derived results.     

多现场总线接口智能仪表设计

在不同现场总线的产品共存的自动化系统中,如何使新兴智能仪表与原有现场设备或未来更新设备在通信方面相兼容,已经成为一个现实问题.为此,提出了智能仪表中多现场总线接口技术.从硬软件方面研究了智能仪表中MODBUS、PROFIBUS和CANBUS三种现场总线通信接口,重点分析了设计中的关键问题,并结合电工仪表产品实现了三种现...     

LabVIEW应用环境下数据库存储性能测试

针对Access、SQL Server 2000以及LabVIEW自带的TDMS数据库进行了相关存储性能的测试.对前两种数据库分别采用LabSQL和数据库连接工具包所提供的算法进行了比较分析.     

三维荧光二阶校正法直接快速测定血浆样中川芎嗪和阿魏酸含量

本文将三维荧光光谱与二阶校正方法相结合用于人体血浆样中的中药药理活性成分川芎嗪和阿魏酸含量的直接测定.尽管预测样存在血浆内源荧光物质的基体干扰,但由于该方法基于“数学分离”的思路和具有“二阶优势”,仍能对荧光光谱严重重叠的血浆样中的目标分析物进行直接同时定量测定,为川芎嗪和阿魏酸在体内的代谢监控及其药效研究提供了一种新思路.获得的预测样中川芎嗪和阿魏酸的平均回收率分别为(95.7±2.2)％和(100.8±2.5)％.该方法简单、快速,结果可靠.