分布式航行信号灯灯丝故障监测系统

针对船舶航行信号灯的使用环境及其要求,研制了一种分布式航行信号灯灯丝故障监测系统,采用从站和PC机两层结构监测,监测能力为8～256个点.主站与从站、主站与PC机均采用成熟的MAX485通信电路.故障时从站立即报警,并将故障航行信号灯状态数据发送到主站;主站分析处理后将故障航行信号灯的状态数据传送到PC机;PC机的人机...     

基于CAN总线电子系统在车辆底盘控制中的应用

对于军用特种车辆底盘控制系统使用的点对点控制方式所造成的车体底盘布线复杂、布局不合理、维修更换难等一系列技术问题进行了分析研究.设计了基于CAN总线的电子综合控制系统,各测控模块进行多点控制,同时各测控模块采用基板印制电路板加功能印制电路板的组合,可随时根据现场车体被控设备的要求进行添加或精简,各测控模块通过CAN总线...     

无线光电定位网络的设计

为满足非接触化、小型化、集成化、数字化、智能化等现代检测技术的发展要求,从成本、工作原理、灵敏度等方面综合考虑,现采用以光电定位模块为核心的光电定位技术,以无线传感器网络作为数据传输与管理的技术手段,构建了无线光电定位网络,并进行了实验分析.可实现多点实时监测、异地显示测量数据、数据网络化管理等特殊需求;涵盖了多学科领...     

基于氧电极的乙醇微生物传感器的在线检测系统

乙醇氧化菌消耗利用乙醇,并产生溶解氧的特性,结合 Clark 氧电极技术设计一种新的乙醇微生物传感器检测方法.该微生物为嗜有机甲基杆菌,是以乙醇作为唯一的碳源生长的菌株.采用利于微生物细胞生长的 PVA-海藻酸盐溶胶-凝胶包埋法,对筛选、分离得到的乙醇氧化细菌固定处理,通过 Clark 氧电极对催化乙醇产生的溶解氧进行...     

无线传感器网络监测数据的汇报机制研究

无线传感器网络监测数据的汇报机制是目前的研究热点.将目前无线传感器的应用分为非事件类、事件类以及混合类三大类,在设计了监测数据表现形式的基础上,着重对事件判别标准、消息的优先级、数据融合方法以及消息的汇报机制进行了分析和论述.汇报机制采用改进的队列作为缓存空间,以保证级别高的消息能够得到及时有效地的传输.实验结果表明:...     

Examining student satisfaction with wholly online learning

Learner satisfaction has been shown to be positively correlated with quality of learning outcomes. An understanding of the factors that influence student satisfaction with online learning in a particular context can be used as an input to the appropriate design of learning environments, and for the provision of targeted support to students, with an aim to positively influence the student online learning experience. Following the mandatory inclusion of at least one wholly online unit of study in all undergraduate programs at Deakin University, a large 'experiences of learning online' (ELO) survey was undertaken to gauge students' perceptions of studying in the wholly online mode. A multivariate linear regression of all the questionnaire items was performed against an overall satisfaction item. Five items were found to significantly contribute to a model that explained approximately 70% of reported student satisfaction. Factors that were found to positively influence student satisfaction with studying a wholly online unit primarily related to how confident they felt about their ability to communicate and learn online, having a clear understanding of what was required to succeed in the unit and how well they thought they were performing in the unit. Other results are also reported.     

变电站采用监控五防一体化系统的深入探讨

随着电网的不断发展,技术的不断进步,变电站的防误闭锁装置也在不断的改进和完善,防止电气误操作已经成为电力自动化技术的一个重要分支,成为保障电力安全生产的一项重要措施,监控系统操作必须有防误闭锁系统的保证才能发挥其应有的作用。监控五防一体系统采用集成于监控系统的五防子模块形式,实现操作票及防误闭锁功能,并支持包括专业五防硬件厂商电脑钥匙的通讯接口,配合五防锁具,实现电气设备的防误闭锁。它是微机防误闭锁技术与监控系统的有机结合,真正的实现了资源共享。     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Multi-Scale Adaptive Sampling with Mobile Agents for Mapping of Forest Fires

The use of robotics in distributed monitoring applications requires wireless sensors that are deployed efficiently. A very important aspect of sensor deployment includes positioning them for sampling at locations most likely to yield information about the spatio-temporal field of interest, for instance, the spread of a forest fire. In this paper, we use mobile robots (agents) that estimate the time-varying spread of wildfires using a distributed multi-scale adaptive sampling strategy. The proposed parametric sampling algorithm, “EKF-NN-GAS” is based on neural networks, the extended Kalman filter (EKF), and greedy heuristics. It combines measurements arriving at different times, taken at different scale lengths, such as from ground, airborne, and spaceborne observation platforms. One of the advantages of our algorithm is the ability to incorporate robot localization uncertainty in addition to sensor measurement and field parameter uncertainty into the same EKF model. We employ potential fields, generated naturally from the estimated fire field distribution, in order to generate fire-safe trajectories that could be used to rescue vehicles and personnel. The covariance of the EKF is used as a quantitative information measure for sampling locations most likely to yield optimal information about the sampled field distribution. Neural net training is used infrequently to generate initial low resolution estimates of the fire spread parameters. We present simulation and experimental results for reconstructing complex spatio-temporal forest fire fields “truth models”, approximated by radial basis function (RBF) parameterizations. When compared to a conventional raster scan approach, our algorithm shows a significant reduction in the time necessary to map the fire field.     

A MEMS affinity glucose sensor using a biocompatible glucose-responsive polymer

We present a MEMS affinity sensor that can potentially allow long-term continuous monitoring of glucose in subcutaneous tissue for diabetes management. The sensing principle is based on detection of viscosity changes due to affinity binding between glucose and poly(acrylamide-ran-3-acrylamidophenylboronic acid) (PAA-ran-PAAPBA), a biocompatible, glucose-specific polymer. The device uses a magnetically driven vibrating microcantilever as a sensing element, which is fabricated from Parylene and situated in a microchamber. A solution of PAA-ran-PAAPBA fills the microchamber, which is separated from the surroundings by a semi-permeable membrane. Glucose permeates through the membrane and binds reversibly to the phenylboronic acid moiety of the polymer. This results in a viscosity change of the sensing solution, which is obtained by measuring the damped cantilever vibration using an optical lever setup, allowing determination of the glucose concentration. Experimental results demonstrate that the device is capable of detecting glucose at physiologically relevant concentrations from 27 mg/dL to 324 mg/dL. The glucose response time constant of the sensor is approximately 3 min, which can be further improved with device design optimization. Excellent reversibility and stability are observed in sensor responses, as highly desired for long-term, stable continuous glucose monitoring.